EAST AND WEST ELEVATIONS OF REMOTE ANALYTICAL FACILITY (CPP627). INL ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

EAST AND WEST ELEVATIONS OF REMOTE ANALYTICAL FACILITY (CPP-627). INL DRAWING NUMBER 200-0627-00-098-105067. ALTERNATE ID NUMBER 4272-14-104. - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

EAST WEST NORTH ELEVATIONS OF MULTICURIE CELL ARCHITECTURAL DETAILS REMOTE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

EAST WEST NORTH ELEVATIONS OF MULTICURIE CELL ARCHITECTURAL DETAILS REMOTE ANALYTICAL FACILITY (CPP-627). INL DRAWING NUMBER 200-00627-00-706-050245. ALTERNATE ID NUMBER AED-D-245. - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Improved Calibration of Modeled Discharge and Storage Change in the Atchafalaya Floodplain Using SAR Interferometry

NASA Technical Reports Server (NTRS)

Jung, Hahn Chul; Jasinski, Michael; Kim, Jin-Woo; Shum, C. K.; Bates, Paul; Neal, Jeffrey; Lee, Hyongki; Alsdorf, Doug

2011-01-01

This study focuses on the feasibility of using SAR interferometry to support 2D hydrodynamic model calibration and provide water storage change in the floodplain. Two-dimensional (2D) flood inundation modeling has been widely studied using storage cell approaches with the availability of high resolution, remotely sensed floodplain topography. The development of coupled 1D/2D flood modeling has shown improved calculation of 2D floodplain inundation as well as channel water elevation. Most floodplain model results have been validated using remote sensing methods for inundation extent. However, few studies show the quantitative validation of spatial variations in floodplain water elevations in the 2D modeling since most of the gauges are located along main river channels and traditional single track satellite altimetry over the floodplain are limited. Synthetic Aperture Radar (SAR) interferometry recently has been proven to be useful for measuring centimeter-scale water elevation changes over the floodplain. In the current study, we apply the LISFLOOD hydrodynamic model to the central Atchafalaya River Basin, Louisiana, during a 62 day period from 1 April to 1 June 2008 using two different calibration schemes for Manning's n. First, the model is calibrated in terms of water elevations from a single in situ gauge that represents a more traditional approach. Due to the gauge location in the channel, the calibration shows more sensitivity to channel roughness relative to floodplain roughness. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. Since SAR interferometry receives strongly scatters in floodplain due to double bounce effect as compared to specular scattering of open water, the calibration shows more dependency to floodplain roughness. An iterative approach is used to determine the best-fit Manning's n for the two different calibration approaches. Results suggest similar floodplain roughness but slightly different channel roughness. However, application of SAR interferometry provides a unique view of the floodplain flow gradients, not possible with a single gauge calibration. These gradients, allow improved computation of water storage change over the 46-day simulation period. Overall, the results suggest that the use of 2D SAR water elevation changes in the Atchafalaya basin offers improved understanding and modeling of floodplain hydrodynamics.

Increasing the UAV data value by an OBIA methodology

NASA Astrophysics Data System (ADS)

García-Pedrero, Angel; Lillo-Saavedra, Mario; Rodriguez-Esparragon, Dionisio; Rodriguez-Gonzalez, Alejandro; Gonzalo-Martin, Consuelo

2017-10-01

Recently, there has been a noteworthy increment of using images registered by unmanned aerial vehicles (UAV) in different remote sensing applications. Sensors boarded on UAVs has lower operational costs and complexity than other remote sensing platforms, quicker turnaround times as well as higher spatial resolution. Concerning this last aspect, particular attention has to be paid on the limitations of classical algorithms based on pixels when they are applied to high resolution images. The objective of this study is to investigate the capability of an OBIA methodology developed for the automatic generation of a digital terrain model of an agricultural area from Digital Elevation Model (DEM) and multispectral images registered by a Parrot Sequoia multispectral sensor board on a eBee SQ agricultural drone. The proposed methodology uses a superpixel approach for obtaining context and elevation information used for merging superpixels and at the same time eliminating objects such as trees in order to generate a Digital Terrain Model (DTM) of the analyzed area. Obtained results show the potential of the approach, in terms of accuracy, when it is compared with a DTM generated by manually eliminating objects.

WEST ELEVATION OF REMOTE ANALYTICAL FACILITY (CPP627) AND HOT PILOT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

WEST ELEVATION OF REMOTE ANALYTICAL FACILITY (CPP-627) AND HOT PILOT PLANT (CPP-640) LOOKING NORTHEAST. INL PHOTO NUMBER HD-22-2-1. Mike Crane, Photographer, 11/1998 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

The Reference Elevation Model of Antarctica (REMA): A High Resolution, Time-Stamped Digital Elevation Model for the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Howat, I.; Noh, M. J.; Porter, C. C.; Smith, B. E.; Morin, P. J.

2017-12-01

We are creating the Reference Elevation Model of Antarctica (REMA), a continuous, high resolution (2-8 m), high precision (accuracy better than 1 m) reference surface for a wide range of glaciological and geodetic applications. REMA will be constructed from stereo-photogrammetric Digital Surface Models (DSM) extracted from pairs of submeter resolution DigitalGlobe satellite imagery and vertically registred to precise elevations from near-coincident airborne LiDAR, ground-based GPS surveys and Cryosat-2 radar altimetry. Both a seamless mosaic and individual, time-stamped DSM strips, collected primarily between 2012 and 2016, will be distributed to enable change measurement. These data will be used for mapping bed topography from ice thickness, measuring ice thickness changes, constraining ice flow and geodynamic models, mapping glacial geomorphology, terrain corrections and filtering of remote sensing observations, and many other science tasks. Is will also be critical for mapping ice traverse routes, landing sites and other field logistics planning. REMA will also provide a critical elevation benchmark for future satellite altimetry missions including ICESat-2. Here we report on REMA production progress, initial accuracy assessment and data availability.

Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.

2016-01-01

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Dynamic Inland Propagation of Thinning Due to Ice Loss at the Margins of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Wang, Wei Li; Li, Jun J.; Zwally, H. Jay

2012-01-01

Mass-balance analysis of the Greenland ice sheet based on surface elevation changes observed by the European Remote-sensing Satellite (ERS) (1992-2002) and Ice, Cloud and land Elevation Satellite (ICESat) (2003-07) indicates that the strongly increased mass loss at lower elevations (<2000 m) of the ice sheet, as observed during 2003-07, appears to induce interior ice thinning at higher elevations. In this paper, we perform a perturbation experiment with a three-dimensional anisotropic ice-flow model (AIF model) to investigate this upstream propagation. Observed thinning rates in the regions below 2000m elevation are used as perturbation inputs. The model runs with perturbation for 10 years show that the extensive mass loss at the ice-sheet margins does in fact cause interior thinning on short timescales (i.e. decadal). The modeled pattern of thinning over the ice sheet agrees with the observations, which implies that the strong mass loss since the early 2000s at low elevations has had a dynamic impact on the entire ice sheet. The modeling results also suggest that even if the large mass loss at the margins stopped, the interior ice sheet would continue thinning for 300 years and would take thousands of years for full dynamic recovery.

Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

NASA Astrophysics Data System (ADS)

Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

2017-12-01

To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

NORTH AND WEST ELEVATIONS OF REMOTE ANALYTICAL FACILITY (CPP627) LOOKING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

NORTH AND WEST ELEVATIONS OF REMOTE ANALYTICAL FACILITY (CPP-627) LOOKING SOUTHEAST. HEADEND PLANT (CPP-640) APPEARS IN THE BACKGROUND. INL PHOTO NUMBER HD-22-1-4. Mike Crane, Photographer, 11/1998 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Accessing and Visualizing scientific spatiotemporal data

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Bergou, Attila; Berriman, Bruce G.; Block, Gary L.; Collier, Jim; Curkendall, David W.; Good, John; Husman, Laura; Jacob, Joseph C.; Laity, Anastasia;

Remote Sensing of Cryosphere: Estimation of Mass Balance Change in Himalayan Glaciers

NASA Astrophysics Data System (ADS)

Ambinakudige, Shrinidhi; Joshi, Kabindra

2012-07-01

Glacial changes are an important indicator of climate change. Our understanding mass balance change in Himalayan glaciers is limited. This study estimates mass balance of some major glaciers in the Sagarmatha National Park (SNP) in Nepal using remote sensing applications. Remote sensing technique to measure mass balance of glaciers is an important methodological advance in the highly rugged Himalayan terrain. This study uses ASTER VNIR, 3N (nadir view) and 3B (backward view) bands to generate Digital Elevation Models (DEMs) for the SNP area for the years 2002, 2003, 2004 and 2005. Glacier boundaries were delineated using combination of boundaries available in the Global land ice measurement (GLIMS) database and various band ratios derived from ASTER images. Elevation differences, glacial area, and ice densities were used to estimate the change in mass balance. The results indicated that the rate of glacier mass balance change was not uniform across glaciers. While there was a decrease in mass balance of some glaciers, some showed increase. This paper discusses how each glacier in the SNP area varied in its annual mass balance measurement during the study period.

Examination of elevation dependency in observed and projected temperature change in the Upper Indus Basin and Western Himalaya

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Forsythe, N. D.; Blenkinsop, S.; Archer, D.; Hardy, A.; Janes, T.; Jones, R. G.; Holderness, T.

2013-12-01

We present results of two distinct, complementary analyses to assess evidence of elevation dependency in temperature change in the UIB (Karakoram, Eastern Hindu Kush) and wider WH. The first analysis component examines historical remotely-sensed land surface temperature (LST) from the second and third generation of the Advanced Very High Resolution Radiometer (AVHRR/2, AVHRR/3) instrument flown on NOAA satellite platforms since the mid-1980s through present day. The high spatial resolution (<4km) from AVHRR instrument enables precise consideration of the relationship between estimated LST and surface topography. The LST data product was developed as part of initiative to produce continuous time-series for key remotely sensed spatial products (LST, snow covered area, cloud cover, NDVI) extending as far back into the historical record as feasible. Context for the AVHRR LST data product is provided by results of bias assessment and validation procedures against both available local observations, both manned and automatic weather stations. Local observations provide meaningful validation and bias assessment of the vertical gradients found in the AVHRR LST as the elevation range from the lowest manned meteorological station (at 1460m asl) to the highest automatic weather station (4733m asl) covers much of the key range yielding runoff from seasonal snowmelt. Furthermore the common available record period of these stations (1995 to 2007) enables assessment not only of the AVHRR LST but also performance comparisons with the more recent MODIS LST data product. A range of spatial aggregations (from minor tributary catchments to primary basin headwaters) is performed to assess regional homogeneity and identify potential latitudinal or longitudinal gradients in elevation dependency. The second analysis component investigates elevation dependency, including its uncertainty, in projected temperature change trajectories in the downscaling of a seventeen member Global Climate Model (GCM) perturbed physics ensemble (PPE) of transient (130-year) simulations using a moderate resolution (25km) regional climate model (RCM). The GCM ensemble is the17-member QUMP (Quantifying Uncertainty in Model Projections) ensemble and the downscaling is done using HadRM3P, part of the PRECIS regional climate modelling system. Both the RCM and GCMs are models developed the UK Met Office Hadley Centre and are based on the HadCM3 GCM. Use of the multi-member PPE enables quantification of uncertainty in projected temperature change while the spatial resolution of RCM improves insight into the role of elevation in projected rates of change. Furthermore comparison with the results of the remote sensing analysis component - considered to provide an 'observed climatology' - permits evaluation of individual ensemble members with regards to biases in spatial gradients in temperature as well timing and magnitude of annual cycles.

A Citizen Science Campaign to Validate Snow Remote-Sensing Products

NASA Astrophysics Data System (ADS)

Wikstrom Jones, K.; Wolken, G. J.; Arendt, A. A.; Hill, D. F.; Crumley, R. L.; Setiawan, L.; Markle, B.

2017-12-01

The ability to quantify seasonal water retention and storage in mountain snow packs has implications for an array of important topics, including ecosystem function, water resources, hazard mitigation, validation of remote sensing products, climate modeling, and the economy. Runoff simulation models, which typically rely on gridded climate data and snow remote sensing products, would be greatly improved if uncertainties in estimates of snow depth distribution in high-elevation complex terrain could be reduced. This requires an increase in the spatial and temporal coverage of observational snow data in high-elevation data-poor regions. To this end, we launched Community Snow Observations (CSO). Participating citizen scientists use Mountain Hub, a multi-platform mobile and web-based crowdsourcing application that allows users to record, submit, and instantly share geo-located snow depth, snow water equivalence (SWE) measurements, measurement location photos, and snow grain information with project scientists and other citizen scientists. The snow observations are used to validate remote sensing products and modeled snow depth distribution. The project's prototype phase focused on Thompson Pass in south-central Alaska, an important infrastructure corridor that includes avalanche terrain and the Lowe River drainage and is essential to the City of Valdez and the fisheries of Prince William Sound. This year's efforts included website development, expansion of the Mountain Hub tool, and recruitment of citizen scientists through a combination of social media outreach, community presentations, and targeted recruitment of local avalanche professionals. We also conducted two intensive field data collection campaigns that coincided with an aerial photogrammetric survey. With more than 400 snow depth observations, we have generated a new snow remote-sensing product that better matches actual SWE quantities for Thompson Pass. In the next phase of the citizen science portion of this project we will focus on expanding our group of participants to a larger geographic area in Alaska, further develop our partnership with Mountain Hub, and build relationships in new communities as we conduct a photogrammetric survey in a different region next year.

OBLIQUE PHOTO OF NORTH AND WEST ELEVATIONS OF REMOTE ANALYTICAL ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

OBLIQUE PHOTO OF NORTH AND WEST ELEVATIONS OF REMOTE ANALYTICAL FACILITY (CPP-627) LOOKING SOUTHEAST. LABORATORY AND OFFICE BUILDING (CPP-602) APPEAR ON LEFT IN PHOTO. INL PHOTO NUMBER HD-22-2-2. Mike Crane, Photographer, 11/1998 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Analysis of potential debris flow source areas on Mount Shasta, California, by using airborne and satellite remote sensing data

USGS Publications Warehouse

Crowley, J.K.; Hubbard, B.E.; Mars, J.C.

2003-01-01

Remote sensing data from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the first spaceborne imaging spectrometer, Hyperion, show hydrothermally altered rocks mainly composed of natroalunite, kaolinite, cristobalite, and gypsum on both the Mount Shasta and Shastina cones. Field observations indicate that much of the visible altered rock consists of talus material derived from fractured rock zones within and adjacent to dacitic domes and nearby lava flows. Digital elevation data were utilized to distinguish steeply sloping altered bedrock from more gently sloping talus materials. Volume modeling based on the imagery and digital elevation data indicate that Mount Shasta drainage systems contain moderate volumes of altered rock, a result that is consistent with Mount Shasta's Holocene record of mostly small to moderate debris flows. Similar modeling for selected areas at Mount Rainier and Mount Adams, Washington, indicates larger altered rock volumes consistent with the occurrence of much larger Holocene debris flows at those volcanoes. The availability of digital elevation and spectral data from spaceborne sensors, such as Hyperion and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), greatly expands opportunities for studying potential debris flow source characteristics at stratovolcanoes around the world. ?? 2003 Elsevier Inc. All rights reserved.

Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey.

PubMed

Moss, William J; Hamapumbu, Harry; Kobayashi, Tamaki; Shields, Timothy; Kamanga, Aniset; Clennon, Julie; Mharakurwa, Sungano; Thuma, Philip E; Glass, Gregory

2011-06-10

The burden of malaria has decreased dramatically within the past several years in parts of sub-Saharan Africa. Further malaria control will require targeted control strategies based on evidence of risk. The objective of this study was to identify environmental risk factors for malaria transmission using remote sensing technologies to guide malaria control interventions in a region of declining burden of malaria. Satellite images were used to construct a sampling frame for the random selection of households enrolled in prospective longitudinal and cross-sectional surveys of malaria parasitaemia in Southern Province, Zambia. A digital elevation model (DEM) was derived from the Shuttle Radar Topography Mission version 3 DEM and used for landscape characterization, including landforms, elevation, aspect, slope, topographic wetness, topographic position index and hydrological models of stream networks. A total of 768 individuals from 128 randomly selected households were enrolled over 21 months, from the end of the rainy season in April 2007 through December 2008. Of the 768 individuals tested, 117 (15.2%) were positive by malaria rapid diagnostic test (RDT). Individuals residing within 3.75 km of a third order stream were at increased risk of malaria. Households at elevations above the baseline elevation for the region were at decreasing risk of having RDT-positive residents. Households where new infections occurred were overlaid on a risk map of RDT positive households and incident infections were more likely to be located in high-risk areas derived from prevalence data. Based on the spatial risk map, targeting households in the top 80th percentile of malaria risk would require malaria control interventions directed to only 24% of the households. Remote sensing technologies can be used to target malaria control interventions in a region of declining malaria transmission in southern Zambia, enabling a more efficient use of resources for malaria elimination.

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

USGS Publications Warehouse

Jones, J.W.; Desmond, G.B.; Henkle, C.; Glover, R.

2012-01-01

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (??15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data. ?? 2012 Taylor & Francis.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Hurricane Harvey Building Damage Assessment Using UAV Data

NASA Astrophysics Data System (ADS)

Yeom, J.; Jung, J.; Chang, A.; Choi, I.

2017-12-01

Hurricane Harvey which was extremely destructive major hurricane struck southern Texas, U.S.A on August 25, causing catastrophic flooding and storm damages. We visited Rockport suffered severe building destruction and conducted UAV (Unmanned Aerial Vehicle) surveying for building damage assessment. UAV provides very high resolution images compared with traditional remote sensing data. In addition, prompt and cost-effective damage assessment can be performed regardless of several limitations in other remote sensing platforms such as revisit interval of satellite platforms, complicated flight plan in aerial surveying, and cloud amounts. In this study, UAV flight and GPS surveying were conducted two weeks after hurricane damage to generate an orthomosaic image and a DEM (Digital Elevation Model). 3D region growing scheme has been proposed to quantitatively estimate building damages considering building debris' elevation change and spectral difference. The result showed that the proposed method can be used for high definition building damage assessment in a time- and cost-effective way.

Towards modeling hydrology and erosion exclusively with remote sensing data in the central Pamirs, Tajikistan

NASA Astrophysics Data System (ADS)

Pohl, E.; Gloaguen, R.; Andermann, C.

2012-12-01

Data scarcity, bad data quality, distribution and availability of measuring stations in remote mountain areas are a burden and hinder the application of models relying on meteorological input data. In this contribution, we present 1) a utilization of various remote sensing and modeled gridded data to run a distributed, conceptual hydrological model in the Tajik Pamirs, 2) derivation of qualitative and quantitative understanding of erosion in space and time, and 3) the linking of the hydrological discharge components to erosion dynamics and sediment transport. While some remote sensing products, such as digital elevation models, land cover classification, and increasingly precipitation products are widely used and accepted in hydrological modeling, holistic approaches are not the case yet. The key feature of the high elevation study area of the Gunt and Shakhdara catchments in the central Pamirs (average elevation of 4300 m a.s.l.) is the Westerlies-dominated precipitation input during winter and spring (two thirds of the annual precipitation of 320 mm/yr). During that time, temperatures are on average far below zero, and hence snowfall dominates the annual precipitation amount and temporarily offsets the river runoff generation. Thus, to model the snow accumulation and snowmelt, the amount of precipitation and its distribution pattern as well as the temperature, determining accumulation and snowmelt, are considered to be the most important parameters. For precipitation, we use two TRMM (Tropical Rainfall Measuring Mission) products and one APHRODITE (Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) product. As proxy for near ground air temperature we use two MODIS (Moderate Resolution Imaging Spectroradiometer) LST (Land Surface Temperature) products that were calibrated with in-situ air temperature data. Mathematical optimization of the model delivers NSE (Nash-Sutcliffe Efficiencies) between 0.66 and 0.82 with respect to the measured river discharge, depending on the chosen meteorological product combination. We use historical archive data on suspended sediment load and river discharge data to derive hysteresis curves to reveal the temporal dependency of the suspended sediment concentration. A transition from transport-limited to supply-limited behavior can be observed from small, high, mountainous catchments towards bigger, low-altitude catchments. The intra-annual dependency is extracted and applied to the modeled data to derive erosion maps. Results show the applicability of the approach to be a valuable and cost efficient tool in poorly accessible areas. We suggest the snow cover and the subsequent snowmelt to control the intra-annual erosion dynamics in the study area. Furthermore, we are able to presents the first quantitative estimations from numerical modeling and empirical observations for this region.

The use of cartographic modeling to assess the impacts of coastal flooding: a case study of Port Said Governorate, Egypt.

PubMed

Abou Samra, Rasha M

2017-09-01

Low-set coastal areas are expected to aggravate inundation on account of sea level rise (SLR). The present study is planned to appraise the impacts of coastal flooding in Port Said city, Egypt by using remote sensing, GIS, and cartographic modeling techniques. To accomplish this scope, Landsat 8-OLI image dated 2016 and SRTM 1Arc-Second Digital Elevation Model (DEM) data were used. Landsat image was classified into seven land use and land cover (LULC) classes by using remote sensing and GIS's software. Different inundation scenarios 1.0, 2.0, and 3.0-m coastal elevation were used to figure the influence of SLR on the study area. Estimation of potential losses under SLR was made by overlaying the expected scenarios on land use. The inundation areas under the expected SLR scenarios of 1.0, 2.0, and 3.0 m were estimated at 827.49, 1072.67, and 1179.41 km 2 , respectively. In conclusion, this study demonstrated that expected coastal flooding scenarios will lead up to serious impacts on LULC classes and coastal features in the study area.

A new, accurate, global hydrography data for remote sensing and modelling of river hydrodynamics

NASA Astrophysics Data System (ADS)

Yamazaki, D.

2017-12-01

A high-resolution hydrography data is an important baseline data for remote sensing and modelling of river hydrodynamics, given the spatial scale of river network is much smaller than that of land hydrology or atmosphere/ocean circulations. For about 10 years, HydroSHEDS, developed based on the SRTM3 DEM, has been the only available global-scale hydrography data. However, the data availability at the time of HydroSHEDS development limited the quality of the represented river networks. Here, we developed a new global hydrography data using latest geodata such as the multi-error-removed elevation data (MERIT DEM), Landsat-based global water body data (GSWO & G3WBM), cloud-sourced open geography database (OpenStreetMap). The new hydrography data covers the entire globe (including boreal regions above 60N), and it represents more detailed structure of the world river network and contains consistent supplementary data layers such as hydrologically adjusted elevations and river channel width. In the AGU meeting, the developing methodology, assessed quality, and potential applications of the new global hydrography data will be introduced.

Proxies for soil organic carbon derived from remote sensing

NASA Astrophysics Data System (ADS)

Rasel, S. M. M.; Groen, T. A.; Hussin, Y. A.; Diti, I. J.

2017-07-01

The possibility of carbon storage in soils is of interest because compared to vegetation it contains more carbon. Estimation of soil carbon through remote sensing based techniques can be a cost effective approach, but is limited by available methods. This study aims to develop a model based on remotely sensed variables (elevation, forest type and above ground biomass) to estimate soil carbon stocks. Field observations on soil organic carbon, species composition, and above ground biomass were recorded in the subtropical forest of Chitwan, Nepal. These variables were also estimated using LiDAR data and a WorldView 2 image. Above ground biomass was estimated from the LiDAR image using a novel approach where the image was segmented to identify individual trees, and for these trees estimates of DBH and Height were made. Based on AIC (Akaike Information Criterion) a regression model with above ground biomass derived from LiDAR data, and forest type derived from WorldView 2 imagery was selected to estimate soil organic carbon (SOC) stocks. The selected model had a coefficient of determination (R2) of 0.69. This shows the scope of estimating SOC with remote sensing derived variables in sub-tropical forests.

Snowmelt-runoff Model Utilizing Remotely-sensed Data

NASA Technical Reports Server (NTRS)

Rango, A.

1985-01-01

Remotely sensed snow cover information is the critical data input for the Snowmelt-Runoff Model (SRM), which was developed to simulatke discharge from mountain basins where snowmelt is an important component of runoff. Of simple structure, the model requires only input of temperature, precipitation, and snow covered area. SRM was run successfully on two widely separated basins. The simulations on the Kings River basin are significant because of the large basin area (4000 sq km) and the adequate performance in the most extreme drought year of record (1976). The performance of SRM on the Okutadami River basin was important because it was accomplished with minimum snow cover data available. Tables show: optimum and minimum conditions for model application; basin sizes and elevations where SRM was applied; and SRM strengths and weaknesses. Graphs show results of discharge simulation.

Applications of the SWOT Mission to Reservoirs in the Mekong River Basin

NASA Astrophysics Data System (ADS)

Bonnema, M.; Hossain, F.

2017-12-01

The forthcoming Surface Water and Ocean Topography (SWOT) mission has the potential to significantly improve our ability to observe artificial reservoirs globally from a remote sensing perspective. By providing simultaneous estimates of reservoir water surface extent and elevation with near global coverage, reservoir storage changes can be estimated. Knowing how reservoir storage changes over time is critical for understanding reservoir impacts on river systems. In data limited regions, remote sensing is often the only viable method of retrieving such information about reservoir operations. When SWOT launches in 2021, it will join an array of satellite sensors with long histories of reservoir observation and monitoring capabilities. There are many potential synergies in the complimentary use of future SWOT observations with observations from current satellite sensors. The work presented here explores the potential benefits of utilizing SWOT observations over 20 reservoirs in the Mekong River Basin. The SWOT hydrologic simulator, developed by NASA Jet Propulsion Laboratory, is used to generate realistic SWOT observations, which are then inserted into a previously established remote sensing modeling framework of the 20 Mekong Basin reservoirs. This framework currently combines data from Landsat missions, Jason radar altimeters, and the Shuttle Radar and Topography Mission (SRTM), to provide monthly estimates of reservoir storage change. The incorporation of SWOT derived reservoir surface area and elevation into the model is explored in an effort to improve both accuracy and temporal resolution of observed reservoir operations.

CLICK: The new USGS center for LIDAR information coordination and knowledge

USGS Publications Warehouse

Stoker, Jason M.; Greenlee, Susan K.; Gesch, Dean B.; Menig, Jordan C.

2006-01-01

Elevation data is rapidly becoming an important tool for the visualization and analysis of geographic information. The creation and display of three-dimensional models representing bare earth, vegetation, and structures have become major requirements for geographic research in the past few years. Light Detection and Ranging (lidar) has been increasingly accepted as an effective and accurate technology for acquiring high-resolution elevation data for bare earth, vegetation, and structures. Lidar is an active remote sensing system that records the distance, or range, of a laser fi red from an airborne or space borne platform such as an airplane, helicopter or satellite to objects or features on the Earth’s surface. By converting lidar data into bare ground topography and vegetation or structural morphologic information, extremely accurate, high-resolution elevation models can be derived to visualize and quantitatively represent scenes in three dimensions. In addition to high-resolution digital elevation models (Evans et al., 2001), other lidar-derived products include quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass (Lefsky et al., 2002), and models of urban areas such as building footprints and three-dimensional city models (Maas, 2001).

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

NASA Technical Reports Server (NTRS)

Kiang, Richard; Adimi, Farida; Kempler, Steven

2008-01-01

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Monitoring global snow cover

NASA Technical Reports Server (NTRS)

Armstrong, Richard; Hardman, Molly

1991-01-01

A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

Innovative use of soft data for the validation of a rainfall-runoff model forced by remote sensing data

NASA Astrophysics Data System (ADS)

van Emmerik, Tim; Eilander, Dirk; Piet, Marijn; Mulder, Gert

2013-04-01

The Chamcar Bei catchment in southern Cambodia is a typical ungauged basin. Neither meteorological data or discharge measurements are available. In this catchment, local farmers are highly dependent on the irrigation system. However, due to the unreliability of the water supply, it was required to make a hydrological model, with which further improvements of the irrigation system could be planned. First, we used knowledge generated in the IAHS decade on Predictions in Ungauged Basins (PUB) to estimate the annual water balance of the Chamcar Bei catchment. Next, using remotely sensed precipitation, vegetation, elevation and transpiration data, a monthly rainfall-runoff model has been developed. The rainfall-runoff model was linked to the irrigation system reservoir, which allowed to validate the model based on soft data such as historical knowledge of the reservoir water level and groundwater levels visible in wells. This study shows that combining existing remote sensing data and soft ground data can lead to useful modeling results. The approach presented in this study can be applied in other ungauged basins, which can be extremely helpful in managing water resources in developing countries.

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

USGS Publications Warehouse

Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

2013-01-01

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Research on Remote Sensing recognition features of Yuan Yang Terraces in Yunnan Province (China)

NASA Astrophysics Data System (ADS)

Xiang, Jie; Chen, Jianping; Lai, ZiLi; Yang, Wei

2016-04-01

Yuan Yang terraces is one of the most famous terraces in China, and it was successfully listed in the world heritage list at the 37th world heritage convention. On the one hand, Yuan Yang terraces retain more soil and water, to reduce both hydrological connectivity and erosion, and to support irrigation. On the other hand, It has the important tourism value, bring the huge revenue to local residents. In order to protect and make use of Yuan Yang terraces better, This study analyzed the spatial distribution and spectral characteristics of terraces:(1) Through visual interpretation, the study recognized the terraces based on the spatial adjusted remote sensing image (2010 Geoeye-1 with resolution of 1m/pix), and extracted topographic feature (elevation, slope, aspect, etc.) based on the digital elevation model with resolution of 20m/pix. The terraces cover a total area of about 11.58Km2, accounted for 24.4% of the whole study area. The terraces appear at range from 1400m to 1800m in elevation, 10°to 20°in slope, northwest to northeast in aspect; (2) Using the method of weight of evidence, this study assessed the importance of different topographic feature. The results show that the sort of importance: elevation>slope>aspect; (3) The study counted the Normalized Difference Vegetation Index (NDVI) changes of terraces throughout the year, based on the landsat-5 image with resolution of 30m/pix. The results show that the changes of terraces' NDVI are bigger than other stuff (e.g. forest, road, house, etc.). Those work made a good preparations for establishing the dynamic remote sensing monitoring system of Yuan Yang terraces.

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska

USGS Publications Warehouse

Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Minsley, Burke J.; Ji, Lei; Walvoord, Michelle Ann; Smith, Bruce D.; Abraham, Jared D.; Rose, Joshua R.

2013-01-01

Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6 m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes.

101. STARBOARD AIRPLANE ELEVATOR MACHINERY ROOM AFT LOOKING FORWARD ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

101. STARBOARD AIRPLANE ELEVATOR MACHINERY ROOM - AFT LOOKING FORWARD PORT TO STARBOARD SHOWING ELEVATOR ENGINE, LIFTING WIRES, HYDRAULIC PIPING WITH REMOTE OPERATOR. - U.S.S. HORNET, Puget Sound Naval Shipyard, Sinclair Inlet, Bremerton, Kitsap County, WA

Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000-2013)

NASA Astrophysics Data System (ADS)

Alexander, P. M.; Tedesco, M.; Fettweis, X.; van de Wal, R. S. W.; Smeets, C. J. P. P.; van den Broeke, M. R.

2014-12-01

Accurate measurements and simulations of Greenland Ice Sheet (GrIS) surface albedo are essential, given the role of surface albedo in modulating the amount of absorbed solar radiation and meltwater production. In this study, we assess the spatio-temporal variability of GrIS albedo during June, July, and August (JJA) for the period 2000-2013. We use two remote sensing products derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as outputs from the Modèle Atmosphérique Régionale (MAR) regional climate model (RCM) and data from in situ automatic weather stations. Our results point to an overall consistency in spatio-temporal variability between remote sensing and RCM albedo, but reveal a difference in mean albedo of up to ~0.08 between the two remote sensing products north of 70° N. At low elevations, albedo values simulated by the RCM are positively biased with respect to remote sensing products by up to ~0.1 and exhibit low variability compared with observations. We infer that these differences are the result of a positive bias in simulated bare ice albedo. MODIS albedo, RCM outputs, and in situ observations consistently indicate a decrease in albedo of -0.03 to -0.06 per decade over the period 2003-2013 for the GrIS ablation area. Nevertheless, satellite products show a decline in JJA albedo of -0.03 to -0.04 per decade for regions within the accumulation area that is not confirmed by either the model or in situ observations. These findings appear to contradict a previous study that found an agreement between in situ and MODIS trends for individual months. The results indicate a need for further evaluation of high elevation albedo trends, a reconciliation of MODIS mean albedo at high latitudes, and the importance of accurately simulating bare ice albedo in RCMs.

A Bayesian Hierarchical Modeling Scheme for Estimating Erosion Rates Under Current Climate Conditions

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2014-12-01

Computational modeling of surface erosion processes is inherently difficult because of the four-dimensional nature of the problem and the multiple temporal and spatial scales that govern individual mechanisms. Landscapes are modified via surface and fluvial erosion and exhumation, each of which takes place over a range of time scales. Traditional field measurements of erosion/exhumation rates are scale dependent, often valid for a single point-wise location or averaging over large aerial extents and periods with intense and mild erosion. We present a method of remotely estimating erosion rates using a Bayesian hierarchical model based upon the stream power erosion law (SPEL). A Bayesian approach allows for estimating erosion rates using the deterministic relationship given by the SPEL and data on channel slopes and precipitation at the basin and sub-basin scale. The spatial scale associated with this framework is the elevation class, where each class is characterized by distinct morphologic behavior observed through different modes in the distribution of basin outlet elevations. Interestingly, the distributions of first-order outlets are similar in shape and extent to the distribution of precipitation events (i.e. individual storms) over a 14-year period between 1998-2011. We demonstrate an application of the Bayesian hierarchical modeling framework for five basins and one intermontane basin located in the central Andes between 5S and 20S. Using remotely sensed data of current annual precipitation rates from the Tropical Rainfall Measuring Mission (TRMM) and topography from a high resolution (3 arc-seconds) digital elevation map (DEM), our erosion rate estimates are consistent with decadal-scale estimates based on landslide mapping and sediment flux observations and 1-2 orders of magnitude larger than most millennial and million year timescale estimates from thermochronology and cosmogenic nuclides.

An Alternative Approach of Coastal Sea-Level Observation from Remote Sensing Imageries

NASA Astrophysics Data System (ADS)

Peng, H. Y.; Tseng, K. H.; Chung-Yen, K.; Lin, T. H.; Liao, W. H.; Chen, C. F.

2017-12-01

Coastal sea level can be observed as waterline changes along a coastal digital elevation model (DEM). However, most global DEMs, such as the Shuttle Radar Topography Mission (SRTM) DEM with 30 m resolution, provide limited coverage over coastal area due to the impermeability of radar signal over water and the lack of low-tide coincidence. Therefore, we aim to extend to coverage of SRTM DEM for the determination of intertidal zone and to monitor sea-level changes along the entire coastline of Taiwan (>1200km). We firstly collect historical cloud-free images since the 1980s, including Landsat series, SPOT series and Sentinel-2, and then calculate the Modified Normalized Difference Water Index (MNDWI) to identify water pixels. After computing water appearance probability of each pixel, it is converted into actual elevation by introducing the DTU10 tide model for high tide and low tide boundaries. A coastal DEM of intertidal zone is reconstructed and the accuracy is at 50 cm level as compared with in situ DEM built by an unmanned aerial vehicle (UAV). Finally, we use this product to define the up-to-date intertidal zone and estimate sea-level changes by using remote sensing snapshots.

Multispectral Remote Sensing of the Earth and Environment Using KHawk Unmanned Aircraft Systems

NASA Astrophysics Data System (ADS)

Gowravaram, Saket

This thesis focuses on the development and testing of the KHawk multispectral remote sensing system for environmental and agricultural applications. KHawk Unmanned Aircraft System (UAS), a small and low-cost remote sensing platform, is used as the test bed for aerial video acquisition. An efficient image geotagging and photogrammetric procedure for aerial map generation is described, followed by a comprehensive error analysis on the generated maps. The developed procedure is also used for generation of multispectral aerial maps including red, near infrared (NIR) and colored infrared (CIR) maps. A robust Normalized Difference Vegetation index (NDVI) calibration procedure is proposed and validated by ground tests and KHawk flight test. Finally, the generated aerial maps and their corresponding Digital Elevation Models (DEMs) are used for typical application scenarios including prescribed fire monitoring, initial fire line estimation, and tree health monitoring.

Livelihoods Poised Between Cold and Dry: Modeling Land Surface Phenologies and Phenometric Lapse Rates in Central Asian Highland Pastures

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Tomaszewska, M. A.; Krehbiel, C. P.; Kelgenbaeva, K.

2016-12-01

To explore the vulnerability of high-elevation communities in the Kyrgyz Republic and in Uzbekistan to changing climatic, sociodemographic, and socioeconomic conditions, we assembled image time series to characterize the condition of pastures near villages at high elevation (>2000 masl) and in remote pastures at higher elevations. Here we describe the application of the convex quadratic (CxQ) model of land surface phenology to highland pasturelands for selected oblasts in the Kyrgyz Republic and in eastern Uzbekistan. We used 16 years (2000-2015) of Landsat normalized difference vegetation index (NDVI) data with MODIS land surface temperature data processed into accumulated growing degree-days. The peak height of the NDVI and the thermal time to peak are two key phenological metrics derived analytically from the fitted parameter coefficients of the CxQ model for each pixel time series. Both exhibited sensitivity to elevation, which we describe in terms of phenometric lapse rates (PLRs). Interannual variation in PLRs was expressed differently for the peak NDVI and the thermal time to peak. Peak NDVI increased with elevation up to a point but also exhibited more spatial variation in dry years than in wetter years. Thermal time to peak exhibited strong, highly significant negative linear relationships to elevation with steeper slopes in drier years. Both types of PLRs were modulated by aspect. These relationships and the associated CxQ models by elevation and aspect can provide expectations against which to detect changes in pasture status as a result of management or weather.

Remote sensing of snow and ice

NASA Technical Reports Server (NTRS)

Rango, A.

1979-01-01

This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

Entrainment and Optical Properties of an Elevated Canadian Forest Fire Plume Transported into the Planetary Boundary Layer near Washington, D.C.

NASA Technical Reports Server (NTRS)

Colarco, P. R.; Schoeberl, M. R.; Doddridge, B. G.; Marufu, L. T.; Torres, O.; Welton, E. J.

2003-01-01

Smoke and pollutants from Canadian forest fires were transported over the northeastern United States in July 2002. Lidar observations at the NASA Goddard Space Flight Center show the smoke from these fires arriving in an elevated plume that was subsequently mixed to the surface. Trajectory and three-dimensional model calculations confirm the origin of the smoke and show that it mixed to the surface after it was intercepted by the turbulent planetary boundary layer. Modeled smoke optical properties agreed well with aircraft and remote sensing observations provided coagulation of smoke particles was accounted for in the model. Our results have important implications for the long-range transport of pollutants and their subsequent entrainment to the surface, as well as the evolving optical properties of smoke from boreal forest fires.

Entrainment and Optical Properties of an Elevated Forest Fire Plume Transported into the Planetary Boundary Layer near Washington, D.C.

NASA Technical Reports Server (NTRS)

Colarco, P. R.; Schoeberl, M. R.; Marufu, L. T.; Torres, O.; Welton, E. J.; Doddridge, B. G.

2003-01-01

Smoke and pollutants from Canadian forest fires were transported over the northeastern United States in July 2002. Lidar observations at the NASA Goddard Space Flight Center show the smoke from these fires arriving in an elevated plume that was subsequently transported to the surface. Trajectory and three-dimensional model calculations confirm the origin of the smoke and show that it mixed to the surface after it was intercepted by the turbulent planetary boundary layer. Modeled smoke optical properties agreed well with aircraft and remote sensing observations provided coagulation of smoke particles was accounted for in the model. Our results have important implications for the long-range transport of pollutants and their subsequent entrainment to the surface, as well as the evolving optical properties of smoke from boreal forest fires.

Generation of the 30 M-Mesh Global Digital Surface Model by Alos Prism

NASA Astrophysics Data System (ADS)

Tadono, T.; Nagai, H.; Ishida, H.; Oda, F.; Naito, S.; Minakawa, K.; Iwamoto, H.

2016-06-01

Topographical information is fundamental to many geo-spatial related information and applications on Earth. Remote sensing satellites have the advantage in such fields because they are capable of global observation and repeatedly. Several satellite-based digital elevation datasets were provided to examine global terrains with medium resolutions e.g. the Shuttle Radar Topography Mission (SRTM), the global digital elevation model by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM). A new global digital surface model (DSM) dataset using the archived data of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS, nicknamed "Daichi") has been completed on March 2016 by Japan Aerospace Exploration Agency (JAXA) collaborating with NTT DATA Corp. and Remote Sensing Technology Center, Japan. This project is called "ALOS World 3D" (AW3D), and its dataset consists of the global DSM dataset with 0.15 arcsec. pixel spacing (approx. 5 m mesh) and ortho-rectified PRISM image with 2.5 m resolution. JAXA is also processing the global DSM with 1 arcsec. spacing (approx. 30 m mesh) based on the AW3D DSM dataset, and partially releasing it free of charge, which calls "ALOS World 3D 30 m mesh" (AW3D30). The global AW3D30 dataset will be released on May 2016. This paper describes the processing status, a preliminary validation result of the AW3D30 DSM dataset, and its public release status. As a summary of the preliminary validation of AW3D30 DSM, 4.40 m (RMSE) of the height accuracy of the dataset was confirmed using 5,121 independent check points distributed in the world.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Photochemical model evaluation of 2013 California wild fire air quality impacts using surface, aircraft, and satellite data.

PubMed

Baker, K R; Woody, M C; Valin, L; Szykman, J; Yates, E L; Iraci, L T; Choi, H D; Soja, A J; Koplitz, S N; Zhou, L; Campuzano-Jost, Pedro; Jimenez, Jose L; Hair, J W

2018-10-01

The Rim Fire was one of the largest wildfires in California history, burning over 250,000 acres during August and September 2013 affecting air quality locally and regionally in the western U.S. Routine surface monitors, remotely sensed data, and aircraft based measurements were used to assess how well the Community Multiscale Air Quality (CMAQ) photochemical grid model applied at 4 and 12 km resolution represented regional plume transport and chemical evolution during this extreme wildland fire episode. Impacts were generally similar at both grid resolutions although notable differences were seen in some secondary pollutants (e.g., formaldehyde and peroxyacyl nitrate) near the Rim fire. The modeling system does well at capturing near-fire to regional scale smoke plume transport compared to remotely sensed aerosol optical depth (AOD) and aircraft transect measurements. Plume rise for the Rim fire was well characterized as the modeled plume top was consistent with remotely sensed data and the altitude of aircraft measurements, which were typically made at the top edge of the plume. Aircraft-based lidar suggests O 3 downwind in the Rim fire plume was vertically stratified and tended to be higher at the plume top, while CMAQ estimated a more uniformly mixed column of O 3 . Predicted wildfire ozone (O 3 ) was overestimated both at the plume top and at nearby rural and urban surface monitors. Photolysis rates were well characterized by the model compared with aircraft measurements meaning aerosol attenuation was reasonably estimated and unlikely contributing to O 3 overestimates at the top of the plume. Organic carbon was underestimated close to the Rim fire compared to aircraft data, but was consistent with nearby surface measurements. Periods of elevated surface PM 2.5 at rural monitors near the Rim fire were not usually coincident with elevated O 3 . Published by Elsevier B.V.

Scoping of Flood Hazard Mapping Needs for Belknap County, New Hampshire

DTIC Science & Technology

2006-01-01

DEM Digital Elevation Model DFIRM Digital Flood Insurance Rate Map DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle DTM...Agriculture Imag- ery Program (NAIP) color Digital Orthophoto Quadrangles (DOQs)). Remote sensing, base map information, GIS data (for example, contour data...found on USGS topographic maps. More recently developed data were derived from digital orthophotos providing improved base map accuracy. NH GRANIT is

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

NASA Astrophysics Data System (ADS)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

Bayesian inference of ice thickness from remote-sensing data

NASA Astrophysics Data System (ADS)

Werder, Mauro A.; Huss, Matthias

2017-04-01

Knowledge about ice thickness and volume is indispensable for studying ice dynamics, future sea-level rise due to glacier melt or their contribution to regional hydrology. Accurate measurements of glacier thickness require on-site work, usually employing radar techniques. However, these field measurements are time consuming, expensive and sometime downright impossible. Conversely, measurements of the ice surface, namely elevation and flow velocity, are becoming available world-wide through remote sensing. The model of Farinotti et al. (2009) calculates ice thicknesses based on a mass conservation approach paired with shallow ice physics using estimates of the surface mass balance. The presented work applies a Bayesian inference approach to estimate the parameters of a modified version of this forward model by fitting it to both measurements of surface flow speed and of ice thickness. The inverse model outputs ice thickness as well the distribution of the error. We fit the model to ten test glaciers and ice caps and quantify the improvements of thickness estimates through the usage of surface ice flow measurements.

MicMac GIS application: free open source

NASA Astrophysics Data System (ADS)

Duarte, L.; Moutinho, O.; Teodoro, A.

2016-10-01

The use of Remotely Piloted Aerial System (RPAS) for remote sensing applications is becoming more frequent as the technologies on on-board cameras and the platform itself are becoming a serious contender to satellite and airplane imagery. MicMac is a photogrammetric tool for image matching that can be used in different contexts. It is an open source software and it can be used as a command line or with a graphic interface (for each command). The main objective of this work was the integration of MicMac with QGIS, which is also an open source software, in order to create a new open source tool applied to photogrammetry/remote sensing. Python language was used to develop the application. This tool would be very useful in the manipulation and 3D modelling of a set of images. The main objective was to create a toolbar in QGIS with the basic functionalities with intuitive graphic interfaces. The toolbar is composed by three buttons: produce the points cloud, create the Digital Elevation Model (DEM) and produce the orthophoto of the study area. The application was tested considering 35 photos, a subset of images acquired by a RPAS in the Aguda beach area, Porto, Portugal. They were used in order to create a 3D terrain model and from this model obtain an orthophoto and the corresponding DEM. The code is open and can be modified according to the user requirements. This integration would be very useful in photogrammetry and remote sensing community combined with GIS capabilities.

Remotely Sensed Based Lake/Reservoir Routing in Congo River Basin

NASA Astrophysics Data System (ADS)

Raoufi, R.; Beighley, E.; Lee, H.

2017-12-01

Lake and reservoir dynamics can influence local to regional water cycles but are often not well represented in hydrologic models. One challenge that limits their inclusion in models is the need for detailed storage-discharge behavior that can be further complicated in reservoirs where specific operation rules are employed. Here, the Hillslope River Routing (HRR) model is combined with a remotely sensed based Reservoir Routing (RR) method and applied to the Congo River Basin. Given that topographic data are often continuous over the entire terrestrial surface (i.e., does not differentiate between land and open water), the HRR-RR model integrates topographic derived river networks and catchment boundaries (e.g., HydroSHEDs) with water boundary extents (e.g., Global Lakes and Wetlands Database) to develop the computational framework. The catchments bordering lakes and reservoirs are partitioned into water and land portions, where representative flowpath characteristics are determined and vertical water balance and lateral routings is performed separately on each partition based on applicable process models (e.g., open water evaporation vs. evapotranspiration). To enable reservoir routing, remotely sensed water surface elevations and extents are combined to determine the storage change time series. Based on the available time series, representative storage change patterns are determined. Lake/reservoir routing is performed by combining inflows from the HRR-RR model and the representative storage change patterns to determine outflows. In this study, a suite of storage change patterns derived from remotely sensed measurements are determined representative patterns for wet, dry and average conditions. The HRR-RR model dynamically selects and uses the optimal storage change pattern for the routing process based on these hydrologic conditions. The HRR-RR model results are presented to highlight the importance of lake attenuation/routing in the Congo Basin.

TopoSCALE v.1.0: downscaling gridded climate data in complex terrain

NASA Astrophysics Data System (ADS)

Fiddes, J.; Gruber, S.

2014-02-01

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).

An Improved dem Construction Method for Mudflats Based on BJ-1 Small Satellite Images: a Case Study on Bohai Bay

NASA Astrophysics Data System (ADS)

Wu, D.; Du, Y.; Su, F.; Huang, W.; Zhang, L.

2018-04-01

The topographic measurement of muddy tidal flat is restricted by the difficulty of access to the complex, wide-range and dynamic tidal conditions. Then the waterline detection method (WDM) has the potential to investigate the morph-dynamics quantitatively by utilizing large archives of satellite images. The study explores the potential for using WDM with BJ-1 small satellite images to construct a digital elevation model (DEM) of a wide and grading mudflat. Three major conclusions of the study are as follows: (1) A new intelligent correlating model of waterline detection considering different tidal stages and local geographic conditions was explored. With this correlative algorithm waterline detection model, a series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of a year. The model proved to detect waterlines more efficiently and exactly. (2) The spatial structure of elevation superimposing on the points of waterlines was firstly constructed and a more accurate hydrodynamic ocean tide grid model was used. By the newly constructed abnormal hydrology evaluation model, a more reasonable and reliable set of waterline points was acquired to construct a smoother TIN and GRID DEM. (3) DEM maps of Bohai Bay, with a spatial resolution of about 30 m and height accuracy of about 0.35 m considering LiDAR and 0.19 m considering RTK surveying were constructed over an area of about 266 km2. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible and is an effective tool for monitoring the tidal flats.

Seasonal and Interannual Variations of Ice Sheet Surface Elevation at the Summit of Greenland: Observed and Modeled

NASA Technical Reports Server (NTRS)

Zwally, H. Jay; Jun, Li; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Observed seasonal and interannual variations in the surface elevation over the summit of the Greenland ice sheet are modeled using a new temperature-dependent formulation of firn-densification and observed accumulation variations. The observed elevation variations are derived from ERS (European Remote Sensing)-1 and ERS-2 radar altimeter data for the period between April 1992 and April 1999. A multivariate linear/sine function is fitted to an elevation time series constructed from elevation differences measured by radar altimetry at orbital crossovers. The amplitude of the seasonal elevation cycle is 0.25 m peak-to-peak, with a maximum in winter and a minimum in summer. Inter-annually, the elevation decreases to a minimum in 1995, followed by an increase to 1999, with an overall average increase of 4.2 cm a(exp -1) for 1992 to 1999. Our densification formulation uses an initial field-density profile, the AWS (automatic weather station) surface temperature record, and a temperature-dependent constitutive relation for the densification that is based on laboratory measurements of crystal growth rates. The rate constant and the activation energy commonly used in the Arrhenius-type constitutive relation for firn densification are also temperature dependent, giving a stronger temperature and seasonal amplitudes about 10 times greater than previous densification formulations. Summer temperatures are most important, because of the strong non-linear dependence on temperature. Much of firn densification and consequent surface lowering occurs within about three months of the summer season, followed by a surface build-up from snow accumulation until spring. Modeled interannual changes of the surface elevation, using the AWS measurements of surface temperature and accumulation and results of atmospheric modeling of precipitation variations, are in good agreement with the altimeter observations. In the model, the surface elevation decreases about 20 cm over the seven years due to more compaction driven by increasing summer temperatures. The minimum elevation in 1995 is driven mainly by a temporary accumulation decrease and secondarily by warmer temperatures. However, the overall elevation increase over the seven years is dominated by the accumulation increase in the later years.

Recent thinning of Bowdoin Glacier, a marine terminating outlet glacier in northwestern Greenland

NASA Astrophysics Data System (ADS)

Tsutaki, S.; Sugiyama, S.; Sakakibara, D.; Sawagaki, T.; Maruyama, M.

2014-12-01

Ice discharge from calving glaciers has increased in the Greenland ice sheet (GrIS), and this increase plays important roles in the volume change of GrIS and its contribution to sea level rise. Thinning of GrIS calving glaciers has been studied by the differentiation of digital elevation models (DEMs) derived by satellite remote-sensing (RS). Such studies rely on the accuracy of DEMs, but calibration of RS data with ground based data is difficult. This is because field data on GrIS calving glaciers are few. In this study, we combined field and RS data to measure surface elevation change of Bowdoin Glacier, a marine terminating outlet glacier in northwestern Greenland (77°41'18″N, 68°29'47″W). The fast flowing part of the glacier is approximately 3 km wide and 10 km long. Ice surface elevation within 6 km from the glacier terminus was surveyed in the field in July 2013 and 2014, by using the global positioning system. We also measured the surface elevation over the glacier on August 20, 2007 and September 4, 2010, by analyzing Advanced Land Observing Satellite (ALOS), Panchromatic remote-sensing Instrument for Stereo Mapping (PRISM) images. We calibrated the satellite derived elevation data with our field measurements, and generated DEM for each year with a 25 m grid mesh. The field data and DEMs were compared to calculate recent glacier elevation change. Mean surface elevation change along the field survey profiles were -16.3±0.2 m (-5.3±0.1 m yr-1) in 2007-2010 and -10.8±0.2 m (-3.8±0.1 m yr-1) in 2010-2013. These rates are much greater than those observed on non-calving ice caps in the region, and similar to those reported for other calving glaciers in northwestern Greenland. Loss of ice was greater near the glacier terminus, suggesting the importance of ice dynamics and/or interaction with the ocean.

TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States

NASA Astrophysics Data System (ADS)

Hashemi, H.; Nordin, K. M.; Lakshmi, V.; Knight, R. J.

2016-12-01

Precipitation can be quantified using a rain gauge network, or a remotely sensed precipitation product. Ultimately, the choice of dataset depends on the particular application, the catchment size, climate and the time period of study. In a region with a long record and a dense rain gauge network, the elevation-modified ground-based precipitation product, PRISM, has been found to work well. However, in poorly gauged regions the use of remotely sensed precipitation products is an absolute necessity. The Tropical Rainfall Measuring Mission (TRMM) has provided valuable precipitation datasets for hydrometeorological studies over the past two decades (1998-2015). One concern regarding the usage of TRMM data is the accuracy of the precipitation estimates, when compared to those obtained using PRISM. The reason for this concern is that TRMM and PRISM do not always agree and, typically, TRMM underestimates PRISM over the mountainous regions of the United States. In this study, we develop a correction function to improve the accuracy of the TRMM monthly product (TRMM-3B43) by estimating and removing the bias in the satellite data using the ground-based precipitation product, PRISM. We observe a strong relationship between the bias and land surface elevation; TRMM-3B43 tends to underestimate the PRISM product at altitudes greater than 1500 m above mean sea level (m.amsl) in the contiguous United States. A relationship is developed between TRMM-PRISM bias and elevation. The correction function is used to adjust the TRMM monthly precipitation using PRISM and elevation data. The model is calibrated using 25% of the available time period and the remaining 75% of the time period is used for validation. The corrected TRMM-3B43 product is verified for the high elevations over the contiguous United States and two local regions in the mountainous areas of the western United States. The results show a significant improvement in the accuracy of the TRMM product in the high elevations of the contiguous United States.

Near-field Oblique Remote Sensing of Stream Water-surface Elevation, Slope, and Surface Velocity

NASA Astrophysics Data System (ADS)

Minear, J. T.; Kinzel, P. J.; Nelson, J. M.; McDonald, R.; Wright, S. A.

2014-12-01

A major challenge for estimating discharges during flood events or in steep channels is the difficulty and hazard inherent in obtaining in-stream measurements. One possible solution is to use near-field remote sensing to obtain simultaneous water-surface elevations, slope, and surface velocities. In this test case, we utilized Terrestrial Laser Scanning (TLS) to remotely measure water-surface elevations and slope in combination with surface velocities estimated from particle image velocimetry (PIV) obtained by video-camera and/or infrared camera. We tested this method at several sites in New Mexico and Colorado using independent validation data consisting of in-channel measurements from survey-grade GPS and Acoustic Doppler Current Profiler (ADCP) instruments. Preliminary results indicate that for relatively turbid or steep streams, TLS collects tens of thousands of water-surface elevations and slopes in minutes, much faster than conventional means and at relatively high precision, at least as good as continuous survey-grade GPS measurements. Estimated surface velocities from this technique are within 15% of measured velocity magnitudes and within 10 degrees from the measured velocity direction (using extrapolation from the shallowest bin of the ADCP measurements). Accurately aligning the PIV results into Cartesian coordinates appears to be one of the main sources of error, primarily due to the sensitivity at these shallow oblique look angles and the low numbers of stationary objects for rectification. Combining remotely-sensed water-surface elevations, slope, and surface velocities produces simultaneous velocity measurements from a large number of locations in the channel and is more spatially extensive than traditional velocity measurements. These factors make this technique useful for improving estimates of flow measurements during flood flows and in steep channels while also decreasing the difficulty and hazard associated with making measurements in these conditions.

Automatic Large-Scalae 3d Building Shape Refinement Using Conditional Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Bittner, K.; d'Angelo, P.; Körner, M.; Reinartz, P.

2018-05-01

Three-dimensional building reconstruction from remote sensing imagery is one of the most difficult and important 3D modeling problems for complex urban environments. The main data sources provided the digital representation of the Earths surface and related natural, cultural, and man-made objects of the urban areas in remote sensing are the digital surface models (DSMs). The DSMs can be obtained either by light detection and ranging (LIDAR), SAR interferometry or from stereo images. Our approach relies on automatic global 3D building shape refinement from stereo DSMs using deep learning techniques. This refinement is necessary as the DSMs, which are extracted from image matching point clouds, suffer from occlusions, outliers, and noise. Though most previous works have shown promising results for building modeling, this topic remains an open research area. We present a new methodology which not only generates images with continuous values representing the elevation models but, at the same time, enhances the 3D object shapes, buildings in our case. Mainly, we train a conditional generative adversarial network (cGAN) to generate accurate LIDAR-like DSM height images from the noisy stereo DSM input. The obtained results demonstrate the strong potential of creating large areas remote sensing depth images where the buildings exhibit better-quality shapes and roof forms.

Comparison of different digital elevation models and satellite imagery for lineament analysis: Implications for identification and spatial arrangement of fault zones in crystalline basement rocks of the southern Black Forest (Germany)

NASA Astrophysics Data System (ADS)

Meixner, J.; Grimmer, J. C.; Becker, A.; Schill, E.; Kohl, T.

2018-03-01

GIS-based remote sensing techniques and lineament mapping provide additional information on the spatial arrangement of faults and fractures in large areas with variable outcrop conditions. Due to inherent censoring and truncation bias mapping of lineaments is still a challenging task. In this study we show how statistical evaluations help to improve the reliability of lineament mappings by comparing two digital elevation models (ASTER, LIDAR) and satellite imagery data sets in the seismically active southern Black Forest. A statistical assessment of the orientation, average length, and the total length of mapped lineaments reveals an impact of the different resolutions of the data sets that allow to define maximum (censoring bias) and minimum (truncation bias) observable lineament length for each data set. The increase of the spatial resolution of the digital elevation model from 30 m × 30 m to 5 m × 5 m results in a decrease of total lineament length by about 40% whereby the average lineament lengths decrease by about 60%. Lineament length distributions of both data sets follow a power law distribution as documented elsewhere for fault and fracture systems. Predominant NE-, N-, NNW-, and NW-directions of the lineaments are observed in all data sets and correlate with well-known, mappable large-scale structures in the southern Black Forest. Therefore, mapped lineaments can be correlated with faults and hence display geological significance. Lineament density in the granite-dominated areas is apparently higher than in the gneiss-dominated areas. Application of a slip- and dilation tendency analysis on the fault pattern reveals largest reactivation potentials for WNW-ESE and N-S striking faults as strike-slip faults whereas normal faulting may occur along NW-striking faults within the ambient stress field. Remote sensing techniques in combination with highly resolved digital elevation models and a slip- and dilation tendency analysis thus can be used to quickly get first order results of the spatial arrangement of critically stressed faults in crystalline basement rocks.

A Study of Flood Evacuation Center Using GIS and Remote Sensing Technique

NASA Astrophysics Data System (ADS)

Mustaffa, A. A.; Rosli, M. F.; Abustan, M. S.; Adib, R.; Rosli, M. I.; Masiri, K.; Saifullizan, B.

2016-07-01

This research demonstrated the use of Remote Sensing technique and GIS to determine the suitability of an evacuation center. This study was conducted in Batu Pahat areas that always hit by a series of flood. The data of Digital Elevation Model (DEM) was obtained by ASTER database that has been used to delineate extract contour line and elevation. Landsat 8 image was used for classification purposes such as land use map. Remote Sensing incorporate with GIS techniques was used to determined the suitability location of the evacuation center from contour map of flood affected areas in Batu Pahat. GIS will calculate the elevation of the area and information about the country of the area, the road access and percentage of the affected area. The flood affected area map may provide the suitability of the flood evacuation center during the several levels of flood. The suitability of evacuation centers can be determined based on several criteria and the existing data of the evacuation center will be analysed. From the analysis among 16 evacuation center listed, there are only 8 evacuation center suitable for the usage during emergency situation. The suitability analysis was based on the location and the road access of the evacuation center toward the flood affected area. There are 10 new locations with suitable criteria of evacuation center proposed on the study area to facilitate the process of rescue and evacuating flood victims to much safer and suitable locations. The results of this study will help in decision making processes and indirectly will help organization such as fire-fighter and the Department of Social Welfare in their work. Thus, this study can contribute more towards the society.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

Towards a general framework for predicting threat status of data-deficient species from phylogenetic, spatial and environmental information.

PubMed

Jetz, Walter; Freckleton, Robert P

2015-02-19

In taxon-wide assessments of threat status many species remain not included owing to lack of data. Here, we present a novel spatial-phylogenetic statistical framework that uses a small set of readily available or derivable characteristics, including phylogenetically imputed body mass and remotely sensed human encroachment, to provide initial baseline predictions of threat status for data-deficient species. Applied to assessed mammal species worldwide, the approach effectively identifies threatened species and predicts the geographical variation in threat. For the 483 data-deficient species, the models predict highly elevated threat, with 69% 'at-risk' species in this set, compared with 22% among assessed species. This results in 331 additional potentially threatened mammals, with elevated conservation importance in rodents, bats and shrews, and countries like Colombia, Sulawesi and the Philippines. These findings demonstrate the future potential for combining phylogenies and remotely sensed data with species distributions to identify species and regions of conservation concern. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Identification of erosional and inundation hazard zones in Ken-Betwa river linking area, India, using remote sensing and GIS.

PubMed

Avtar, Ram; Singh, Chander Kumar; Shashtri, Satayanarayan; Mukherjee, Saumitra

2011-11-01

Ken-Betwa river link is one of the pilot projects of the Inter Linking of Rivers program of Government of India in Bundelkhand Region. It will connect the Ken and Betwa rivers through a system of dams, reservoirs, and canals to provide storage for excess rainfall during the monsoon season and avoid floods. The main objective of this study is to identify erosional and inundation prone zones of Ken-Betwa river linking site in India using remote sensing and geographic information system tools. In this study, Landsat Thematic Mapper data of year 2005, digital elevation model from the Shuttle Radar Topographic Mission, and other ancillary data were analyzed to create various thematic maps viz. geomorphology, land use/land cover, NDVI, geology, soil, drainage density, elevation, slope, and rainfall. The integrated thematic maps were used for hazard zonation. This is based on categorizing the different hydrological and geomorphological processes influencing the inundation and erosion intensity. Result shows that the southern part of the study area which lies in Panna district of Madhya Pradesh, India, is more vulnerable than the other areas.

Analyzing remote sensing geobotanical trends in Quetico Provincial Park, Ontario, Canada, using digital elevation data

NASA Technical Reports Server (NTRS)

Warner, Timothy A.; Campagna, David J.; Levandowski, Don W.; Cetin, Haluk; Evans, Carla S.

1991-01-01

A 10 x 13-km area in Quetico Provincial Park, Canada has been studied using a digital elevation model to separate different drainage classes and to examine the influence of site factors and lithology on vegetation. Landsat Thematic Mapper data have been classified into six forest classes of varying deciduous-coniferous cover through nPDF, a procedure based on probability density functions. It is shown that forests growing on mafic lithologies are enriched in deciduous species, compared to those growing on granites. Of the forest classes found on mafics, the highest coniferous component was on north facing slopes, and the highest deciduous component on south facing slopes. Granites showed no substantial variation between site classes. The digital elevation derived site data is considered to be an important tool in geobotanical investigations.

Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007

NASA Astrophysics Data System (ADS)

Mason, D. C.; Scott, T. R.; Dance, S. L.

2010-04-01

Tidal Flats are important examples of extensive areas of natural environment that remain relatively unaffected by man. Monitoring of tidal flats is required for a variety of purposes. Remote sensing has become an established technique for the measurement of topography over tidal flats. A further requirement is to measure topographic changes in order to measure sediment budgets. To date there have been few attempts to make quantitative estimates of morphological change over tidal flat areas. This paper illustrates the use of remote sensing to measure quantitative and qualitative changes in the tidal flats of Morecambe Bay during the relatively long period 1991-2007. An understanding of the patterns of sediment transport within the Bay is of considerable interest for coastal management and defence purposes. Tidal asymmetry is considered to be the dominant cause of morphological change in the Bay, with the higher currents associated with the flood tide being the main agency moulding the channel system. Quantitative changes were measured by comparing a Digital Elevation Model (DEM) of the intertidal zone formed using the waterline technique applied to satellite Synthetic Aperture Radar (SAR) images from 1991-1994, to a second DEM constructed from airborne laser altimetry data acquired in 2005. Qualitative changes were studied using additional SAR images acquired since 2003. A significant movement of sediment from below Mean Sea Level (MSL) to above MSL was detected by comparing the two Digital Elevation Models, though the proportion of this change that could be ascribed to seasonal effects was not clear. Between 1991 and 2004 there was a migration of the Ulverston channel of the river Leven north-east by about 5 km, followed by the development of a straighter channel to the west, leaving the previous channel decoupled from the river. This is thought to be due to independent tidal and fluvial forcing mechanisms acting on the channel. The results demonstrate the effectiveness of remote sensing for measurement of long-term morphological change in tidal flat areas. An alternative use of waterlines as partial bathymetry for assimilation into a morphodynamic model of the coastal zone is also discussed.

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa

PubMed Central

2012-01-01

Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. PMID:22443452

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa.

PubMed

Dambach, Peter; Machault, Vanessa; Lacaux, Jean-Pierre; Vignolles, Cécile; Sié, Ali; Sauerborn, Rainer

2012-03-23

The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. © 2012 Dambach et al; licensee BioMed Central Ltd.

14 CFR 171.309 - General requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... satisfactorily under the following conditions: Wind Velocity: The ground equipment shall remain within monitor... equipment, associated monitor, remote control and indicator equipment. (2) Approach elevation equipment, associated monitor, remote control and indicator equipment. (3) A means for the encoding and transmission of...

14 CFR 171.309 - General requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... satisfactorily under the following conditions: Wind Velocity: The ground equipment shall remain within monitor... equipment, associated monitor, remote control and indicator equipment. (2) Approach elevation equipment, associated monitor, remote control and indicator equipment. (3) A means for the encoding and transmission of...

14 CFR 171.309 - General requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... satisfactorily under the following conditions: Wind Velocity: The ground equipment shall remain within monitor... equipment, associated monitor, remote control and indicator equipment. (2) Approach elevation equipment, associated monitor, remote control and indicator equipment. (3) A means for the encoding and transmission of...

High resolution remote sensing missions of a tethered satellite

NASA Technical Reports Server (NTRS)

Vetrella, S.; Moccia, A.

1986-01-01

The application of the Tethered Satellite (TS) as an operational remote sensing platform is studied. It represents a new platform capable of covering the altitudes between airplanes and free flying satellites, offering an adequate lifetime, high geometric and radiometric resolution and improved cartographic accuracy. Two operational remote sensing missions are proposed: one using two linear array systems for along track stereoscopic observation and one using a synthetic aperture radar combined with an interferometric technique. These missions are able to improve significantly the accuracy of future real time cartographic systems from space, also allowing, in the case of active microwave systems, the Earth's observation both in adverse weather and at any time, day or night. Furthermore, a simulation program is described in which, in order to examine carefully the potentiality of the TS as a new remote sensing platform, the orbital and attitude dynamics description of the TSS is integrated with the sensor viewing geometry, the Earth's ellipsoid, the atmospheric effects, the Sun illumination and the digital elevation model. A preliminary experiment has been proposed which consist of a metric camera to be deployed downwards during the second Shuttle demonstration flight.

Integration of Remote Sensing Data In Operational Flood Forecast In Southwest Germany

NASA Astrophysics Data System (ADS)

Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.

Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the project ESA's ENVISAT satellite, which will be launched in 2002, will serve as remote sensing data source. Until EN- VISAT data is available, algorithm retrieval, software development and product gener- ation is performed using existing sensors with ENVISAT-like specifications. Based on these data sets test cases and demonstration runs are conducted and will be presented to prove the advantages of the approach.

Models of the diffuse radar backscatter from Mars

NASA Technical Reports Server (NTRS)

England, A. W.; Austin, R. T.

1991-01-01

The topographies of several debris flow units near the Mount St. Helens Volcano were measured at lateral scales of millimeters to meters in September 1990. The objective was to measure the surface roughness of the debris flows at scales smaller than, on the order of, and larger that the radar wavelength of common remote sensing radars. A laser profiling system and surveying instruments were used to obtain elevation data for square areas that varied in size from 10 to 32 cm. The elevation data were converted to estimates of the power spectrum of surface roughness. The conversions were based upon standard periodogram techniques, and upon a modified spectral estimation technique that was developed.

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

Ozone in remote areas of the Southern Rocky Mountains

Treesearch

Robert C. Musselman; John L. Korfmacher

2014-01-01

Ozone (O3) data are sparse for remote, non-urban mountain areas of the western U.S. Ozone was monitored 2007e2011 at high elevation sites in national forests in Colorado and northeastern Utah using a portable battery-powered O3 monitor. The data suggest that many of these remote locations already have O3 concentrations that would contribute to exceedance of the current...

Derivation of Lake Areas and Elevations for the Mackenzie Basin Using Satellite Remote Sensing

NASA Technical Reports Server (NTRS)

Birkett, Charon; Kite, Geoff

1997-01-01

Modelling hydrological processes in large watersheds flowing to the Arctic ocean is one step towards larger-scale modelling of the global water and energy cycles. Models of the Mackenzie River Basin (Northern Canada) are currently available but omit explicit routing of river flows through the three main lakes - Athabasca, Great Slave Lake and Great Bear Lake (Kite et al, 1994). These lakes occupy an area of 65,000 sq km but little gauge information is available. The levels of the lakes are only measured at a few points on the circumferences and river flows are only measured downstream. The hydraulic relationships between level/discharge and level/area/volume are uncertain. It has been previously shown that satellite remote sensing can be utilised in providing measurements of both lake surface area using imaging techniques and lake level using radar altimetry (Birkett, 1994). Here, we explore the application of these techniques to derive the lake levels and areas for the Mackenzie Basin lakes.

Remote Zone Extracellular Volume and Left Ventricular Remodeling in Survivors of ST-Elevation Myocardial Infarction.

PubMed

Carberry, Jaclyn; Carrick, David; Haig, Caroline; Rauhalammi, Samuli M; Ahmed, Nadeem; Mordi, Ify; McEntegart, Margaret; Petrie, Mark C; Eteiba, Hany; Hood, Stuart; Watkins, Stuart; Lindsay, Mitchell; Davie, Andrew; Mahrous, Ahmed; Ford, Ian; Sattar, Naveed; Welsh, Paul; Radjenovic, Aleksandra; Oldroyd, Keith G; Berry, Colin

2016-08-01

The natural history and pathophysiological significance of tissue remodeling in the myocardial remote zone after acute ST-elevation myocardial infarction (STEMI) is incompletely understood. Extracellular volume (ECV) in myocardial regions of interest can now be measured with cardiac magnetic resonance imaging. Patients who sustained an acute STEMI were enrolled in a cohort study (BHF MR-MI [British Heart Foundation Magnetic Resonance Imaging in Acute ST-Segment Elevation Myocardial Infarction study]). Cardiac magnetic resonance was performed at 1.5 Tesla at 2 days and 6 months post STEMI. T1 modified Look-Locker inversion recovery mapping was performed before and 15 minutes after contrast (0.15 mmol/kg gadoterate meglumine) in 140 patients at 2 days post STEMI (mean age: 59 years, 76% male) and in 131 patients at 6 months post STEMI. Remote zone ECV was lower than infarct zone ECV (25.6±2.8% versus 51.4±8.9%; P<0.001). In multivariable regression, left ventricular ejection fraction was inversely associated with remote zone ECV (P<0.001), and diabetes mellitus was positively associated with remote zone ECV (P=0.010). No ST-segment resolution (P=0.034) and extent of ischemic area at risk (P<0.001) were multivariable associates of the change in remote zone ECV at 6 months (ΔECV). ΔECV was a multivariable associate of the change in left ventricular end-diastolic volume at 6 months (regression coefficient [95% confidence interval]: 1.43 (0.10-2.76); P=0.036). ΔECV is implicated in the pathophysiology of left ventricular remodeling post STEMI, but because the effect size is small, ΔECV has limited use as a clinical biomarker of remodeling. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02072850. © 2016 The Authors.

Remote Zone Extracellular Volume and Left Ventricular Remodeling in Survivors of ST-Elevation Myocardial Infarction

PubMed Central

Carberry, Jaclyn; Carrick, David; Haig, Caroline; Rauhalammi, Samuli M.; Ahmed, Nadeem; Mordi, Ify; McEntegart, Margaret; Petrie, Mark C.; Eteiba, Hany; Hood, Stuart; Watkins, Stuart; Lindsay, Mitchell; Davie, Andrew; Mahrous, Ahmed; Ford, Ian; Sattar, Naveed; Welsh, Paul; Radjenovic, Aleksandra; Oldroyd, Keith G.

2016-01-01

The natural history and pathophysiological significance of tissue remodeling in the myocardial remote zone after acute ST-elevation myocardial infarction (STEMI) is incompletely understood. Extracellular volume (ECV) in myocardial regions of interest can now be measured with cardiac magnetic resonance imaging. Patients who sustained an acute STEMI were enrolled in a cohort study (BHF MR-MI [British Heart Foundation Magnetic Resonance Imaging in Acute ST-Segment Elevation Myocardial Infarction study]). Cardiac magnetic resonance was performed at 1.5 Tesla at 2 days and 6 months post STEMI. T1 modified Look-Locker inversion recovery mapping was performed before and 15 minutes after contrast (0.15 mmol/kg gadoterate meglumine) in 140 patients at 2 days post STEMI (mean age: 59 years, 76% male) and in 131 patients at 6 months post STEMI. Remote zone ECV was lower than infarct zone ECV (25.6±2.8% versus 51.4±8.9%; P<0.001). In multivariable regression, left ventricular ejection fraction was inversely associated with remote zone ECV (P<0.001), and diabetes mellitus was positively associated with remote zone ECV (P=0.010). No ST-segment resolution (P=0.034) and extent of ischemic area at risk (P<0.001) were multivariable associates of the change in remote zone ECV at 6 months (ΔECV). ΔECV was a multivariable associate of the change in left ventricular end-diastolic volume at 6 months (regression coefficient [95% confidence interval]: 1.43 (0.10–2.76); P=0.036). ΔECV is implicated in the pathophysiology of left ventricular remodeling post STEMI, but because the effect size is small, ΔECV has limited use as a clinical biomarker of remodeling. Clinical Trial Registration— URL: https://www.clinicaltrials.gov. Unique identifier: NCT02072850. PMID:27354423

Using High Resolution Remote Sensing Images to Investigate Hydrologic Connectivity and Degradation Thresholds along a Precipitation Gradient in Semiarid Australia

NASA Astrophysics Data System (ADS)

Azadi, S.; Saco, P. M.; Moreno-de las Heras, M.; Willgoose, G. R.

2016-12-01

Arid and semiarid landscapes are particularly sensitive to climatic and anthropogenic disturbances. Previous work has identified that these landscapes are prone to undergo critical degradation thresholds above which rehabilitation is difficult to achieve. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity associated with the climatic or anthropogenic disturbances. In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects can eventually affect ecosystem functionality (e.g. Rainfall Use Efficiency). In this study, we explore the impact of degradation processes induced by vegetation disturbances (mostly due to grazing pressure) on ecosystem functionality and connectivity along a precipitation gradient (250 mm to 490 mm annual average rainfall) using a combination of remote sensing observations and Digital Elevation Model data. The sites were carefully selected in the Mulga landscapes bioregion (New South Wales, Queensland) and in sites of the Northern Territory in Australia, which display similar vegetation characteristics and good quality rainfall information. Vegetation patterns and the percent of fractional cover were obtained from high resolution remote sensing images (IKONOS, QuickBird and Pleiades). We computed rainfall use efficiency and precipitation marginal response using local precipitation data and MODIS vegetation indices. We estimated mean Flowlength as an indicator of structural hydrologic connectivity using vegetation binary maps and digital elevation models. We compared the trends for several sites along the precipitation gradient, and found that disturbances substantially increase hydrologic connectivity following a threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes show evidence of higher resilience.

The sky is the limit: reconstructing physical geography fieldwork from an aerial perspective

NASA Astrophysics Data System (ADS)

Williams, R.; Tooth, S.; Gibson, M.; Barrett, B.

2017-12-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products (e.g. aerial photographs, satellite images, digital elevation models) are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned aerial vehicles (UAVs) provide a relatively cheap opportunity to introduce the principles and practice of airborne remote sensing into fieldcourses, enabling students to learn about image acquisition, data processing and interpretation of derived products. Three case studies illustrate how a low cost DJI Phantom UAV can be used by students to acquire images that can be processed using off the shelf Structure-from-Motion photogrammetry software. Two case studies are drawn from an international fieldcourse that takes students to field sites that are the focus of current funded research whilst a third case study is from a course in topographic mapping. Results from a student questionnaire and analysis of assessed student reports showed that using UAVs in fieldwork enhanced student engagement with themes on their fieldcourse and equipped them with data processing skills. The derivation of bespoke orthophotos and Digital Elevation Models also provided students with opportunities to gain insight into the various data quality issues that are associated with aerial imagery acquisition and topographic reconstruction, although additional training is required to maximise this potential. Recognition of the successes and limitations of this teaching intervention provides scope for improving exercises that use UAVs and other technologies in future fieldcourses. UAVs are enabling both a reconstruction of how we measure the Earth's surface and a reconstruction of how students do fieldwork.

The Utilization of Remotely Sensed Data to Analyze the Estimated Volume of Pyroclastic Deposits and Morphological Changes Caused by the 2010-2015 Eruption of Sinabung Volcano, North Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Yulianto, Fajar; Suwarsono; Sofan, Parwati

2016-08-01

In this research, remotely sensed data has been used to estimate the volume of pyroclastic deposits and analyze morphological changes that have resulted from the eruption of Sinabung volcano. Topographic information was obtained from these data and used for rapid mapping to assist in the emergency response. Topographic information and change analyses (pre- and syn- eruption) were conducted using digital elevation models (DEMs) for the period 2010-2015. Advanced spaceborne thermal emission and reflection radiometer (ASTER) global digital elevation model (GDEM) data from 2009 were used to generate the initial DEMs for the condition prior to the eruption of 2010. Satellite pour l'observation de la terre 6 (SPOT 6) stereo images acquired on 21 June 2015 and were used to make a DEM for that time. The results show that the estimated total volume of lava and pyroclastic deposits, produced during the period 2010 to mid-2015 is approximately 2.8 × 108 m3. This estimated volume of pyroclastic deposits can be used to predict the magnitude of future secondary lahar hazards, which are also related to the capacity of rivers in the area. Morphological changes are illustrated using cross-sectional analysis of the deposits, which are currently deposited to the east, southeast and south of the volcano. Such analyses can also help in forecasting the direction of the future flow hazards. The remote sensing and analysis methods used at Sinabung can also be applied at other volcanoes and to assess the threats of other types of hazards such as landslides and land subsidence.

Water soluble organic aerosols in the Colorado Rocky Mountains, USA: composition, sources and optical properties

PubMed Central

Xie, Mingjie; Mladenov, Natalie; Williams, Mark W.; Neff, Jason C.; Wasswa, Joseph; Hannigan, Michael P.

2016-01-01

Atmospheric aerosols have been shown to be an important input of organic carbon and nutrients to alpine watersheds and influence biogeochemical processes in these remote settings. For many remote, high elevation watersheds, direct evidence of the sources of water soluble organic aerosols and their chemical and optical characteristics is lacking. Here, we show that the concentration of water soluble organic carbon (WSOC) in the total suspended particulate (TSP) load at a high elevation site in the Colorado Rocky Mountains was strongly correlated with UV absorbance at 254 nm (Abs254, r = 0.88 p < 0.01) and organic carbon (OC, r = 0.95 p < 0.01), accounting for >90% of OC on average. According to source apportionment analysis, biomass burning had the highest contribution (50.3%) to average WSOC concentration; SOA formation and motor vehicle emissions dominated the contribution to WSOC in the summer. The source apportionment and backward trajectory analysis results supported the notion that both wildfire and Colorado Front Range pollution sources contribute to the summertime OC peaks observed in wet deposition at high elevation sites in the Colorado Rocky Mountains. These findings have important implications for water quality in remote, high-elevation, mountain catchments considered to be our pristine reference sites. PMID:27991554

[Maximum entropy model versus remote sensing-based methods for extracting Oncomelania hupensis snail habitats].

PubMed

Cong-Cong, Xia; Cheng-Fang, Lu; Si, Li; Tie-Jun, Zhang; Sui-Heng, Lin; Yi, Hu; Ying, Liu; Zhi-Jie, Zhang

2016-12-02

To explore the technique of maximum entropy model for extracting Oncomelania hupensis snail habitats in Poyang Lake zone. The information of snail habitats and related environment factors collected in Poyang Lake zone were integrated to set up the maximum entropy based species model and generate snail habitats distribution map. Two Landsat 7 ETM+ remote sensing images of both wet and drought seasons in Poyang Lake zone were obtained, where the two indices of modified normalized difference water index (MNDWI) and normalized difference vegetation index (NDVI) were applied to extract snail habitats. The ROC curve, sensitivities and specificities were applied to assess their results. Furthermore, the importance of the variables for snail habitats was analyzed by using Jackknife approach. The evaluation results showed that the area under receiver operating characteristic curve (AUC) of testing data by the remote sensing-based method was only 0.56, and the sensitivity and specificity were 0.23 and 0.89 respectively. Nevertheless, those indices above-mentioned of maximum entropy model were 0.876, 0.89 and 0.74 respectively. The main concentration of snail habitats in Poyang Lake zone covered the northeast part of Yongxiu County, northwest of Yugan County, southwest of Poyang County and middle of Xinjian County, and the elevation was the most important environment variable affecting the distribution of snails, and the next was land surface temperature (LST). The maximum entropy model is more reliable and accurate than the remote sensing-based method for the sake of extracting snail habitats, which has certain guiding significance for the relevant departments to carry out measures to prevent and control high-risk snail habitats.

Simulations of snow distribution and hydrology in a mountain basin

USGS Publications Warehouse

Hartman, Melannie D.; Baron, Jill S.; Lammers, Richard B.; Cline, Donald W.; Band, Larry E.; Liston, Glen E.; Tague, Christina L.

1999-01-01

We applied a version of the Regional Hydro-Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind-driven sublimation to Loch Vale Watershed (LVWS), an alpine-subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind-driven sublimation was necessary to predict moisture losses.

Potential of high resolution satellite imagery, remote weather data and 1D hydraulic modeling to evaluate flood areas in Gonaives, Haiti

NASA Astrophysics Data System (ADS)

Bozza, Andrea; Durand, Arnaud; Allenbach, Bernard; Confortola, Gabriele; Bocchiola, Daniele

2013-04-01

We present a feasibility study to explore potential of high-resolution imagery, coupled with hydraulic flood modeling to predict flooding risks, applied to the case study of Gonaives basins (585 km²), Haiti. We propose a methodology working at different scales, providing accurate results and a faster intervention during extreme flood events. The 'Hispaniola' island, in the Caribbean tropical zone, is often affected by extreme floods events. Floods are caused by tropical springs and hurricanes, and may lead to several damages, including cholera epidemics, as recently occurred, in the wake of the earthquake upon January 12th 2010 (magnitude 7.0). Floods studies based upon hydrological and hydraulic modeling are hampered by almost complete lack of ground data. Thenceforth, and given the noticeable cost involved in the organization of field measurement campaigns, the need for exploitation of remote sensing images data. HEC-RAS 1D modeling is carried out under different scenarios of available Digital Elevation Models. The DEMs are generated using optical remote sensing satellite (WorldView-1) and SRTM, combined with information from an open source database (Open Street Map). We study two recent flood episodes, where flood maps from remote sensing were available. Flood extent and land use have been assessed by way of data from SPOT-5 satellite, after hurricane Jeanne in 2004 and hurricane Hanna in 2008. A semi-distributed, DEM based hydrological model is used to simulate flood flows during the hurricanes. Precipitation input is taken from daily rainfall data derived from TRMM satellite, plus proper downscaling. The hydraulic model is calibrated using floodplain friction as tuning parameters against the observed flooded area. We compare different scenarios of flood simulation, and the predictive power of model calibration. The method provide acceptable results in depicting flooded areas, especially considering the tremendous lack of ground data, and show the potential of remote sensing information in prediction of flood events in this area, for the purpose of risk assessment and land use planning, and possibly for flood forecast during extreme events.

Ecological Niche Modelling using satellite data for assessing distribution of threatened species Ceropegia bulbosa Roxb.

NASA Astrophysics Data System (ADS)

Kumar, S.; Kulloli, R. N.; Tewari, J. C.; Singh, J. P.; Singh, A.

2014-11-01

Ceropegia bulbosa Roxb. is a narrow endemic, tuberous twiner of Asclepiadaceae family. It is medicinally important: tubers are nutritive and edible, leaves are digestive and a cure for dysentery and diarrhea. Exploitation for its tubers and poor regeneration of this species has shrunk its distribution. In order to know its present status, we report here the results of its appraisal in Rajasthan, using remote sensing and ground truthing in the past five years (2009-14). A base map of C. bulbosa was prepared using Geographical Information System (GIS), open source software Quantum GIS, SAGA. The Landsat Enhanced Thematic Mapper (ETM) +Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Global Digital Elevation Model (GDEM) Satellite Data were used in this study. ASTER and GDEM Data was clipped with district boundary and provided color range to get elevation information. A digital elevation model of Rajasthan physiography was developed from ASTER GDEM of 30-m resolution. GIS layers of Area of occurrences for C. bulbosa plant and elevation were created. This map along with topographic sheets of 1:50000 were used for field traversing and ground truthing as per GPS location inferred from map. Its geographic distribution was assessed using MaxEnt distribution modelling algorithm that employed 12 presence locality data, 19 bioclimatic variables, and elevation data. Results of this modelling predicted occurrence of C. bulbosa in the districts of Sirohi, Jalore, Barmer, Pali, Ajmer, Jhalawar, Dungarpur, Banswara, Baran, Kota, Bundi and Chittorgarh. Ground validation in these districts revealed its presence only at four places in three districts confirming its rarity. Analysis of dominance at their sites of occurrence revealed their poor populations and sub dominant status (RIV = 20-32) and very low density (2-12 plants per tenth ha).

Remotely-sensed and in-situ observations of Greenland firn aquifers

NASA Astrophysics Data System (ADS)

Forster, R. R.; Miège, C.; Koenig, L.; Solomon, D. K.; Schmerr, N. C.; Miller, O. L.; Ligtenberg, S.; Montgomery, L. N.; Brucker, L.; Miller, J.; Legchenko, A.

2017-12-01

In 2011, prior to seasonal melt, our research team drilled into an unknown firn aquifer system in Southeast Greenland. Since 2013, we have conducted four field seasons, complemented with modeling and remote sensing to gain knowledge regarding firn aquifers and surrounding snow/firn/ice. We aim to provide a more complete picture of the system including formation conditions, controlling mechanisms, spatial and temporal changes, and connections with the larger ice sheet hydrologic system. This work summarizes remote sensing data since 1993 showing the spatial and temporal evolution of the aquifer extent. To complement the remote sensing and better characterize the firn aquifer in the field, we use a combination of three different geophysics methods. Ground penetrating radar provides us knowledge of the water table elevation and its variations, magnetic-resonance soundings give us the water volume held in the aquifer and the active seismic data allow us to locate the bottom of the aquifer. In addition, firn/ice-core stratigraphy suggests that the timing and evolution of the aquifer bottom is controlled by thermodynamics. Our compilation of remote sensing measurements point to a dynamic and expanding aquifer system. We found that firn aquifers have existed at least since 1993 (dataset start) in the high melt and high accumulation region of the South Eastern Greenland ice sheet. Firn aquifers are now growing toward the interior related to the warming air temperatures in the Arctic and more intense melt during summers. These remotely sensed observations and in-situ measurements are required to validate improved ice sheet mass balance models that incorporate firn aquifers. They are also needed to further investigate the potential of firn aquifer discharge to the glacier bed via crevasse hydrofracturing influencing ice dynamics.

Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+data.

Treesearch

D.L. Verbyla; E.S. Kasischke; E.E. Hoy

2008-01-01

The maximum solar elevation is typically less than 50 degrees in the Alaskan boreal region and solar elevation varies substantially during the growing season. Because of the relatively low solar elevation at boreal latitudes, the effect of topography on spectral reflectance can influence fire severity indices derived from remotely sensed data. We used Landsat Thematic...

Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5

USGS Publications Warehouse

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Lei; Lee, Wonjin; Lee, Chang-Wook

2012-01-01

An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.

Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover

NASA Astrophysics Data System (ADS)

Cornwell, E.; Molotch, N. P.; McPhee, J.

2016-01-01

Seasonal snow cover is the primary water source for human use and ecosystems along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution (500 m), daily distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow-covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically based energy balance model in order to obtain melt-season melt fluxes that are then aggregated to estimate the end-of-winter (or peak) snow water equivalent (SWE). Peak SWE estimates show an overall coefficient of determination R2 of 0.68 and RMSE of 274 mm compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. The spatial distribution of peak SWE shows that the 4000-5000 m a.s.l. elevation band is significant for snow accumulation, despite having a smaller surface area than the 3000-4000 m a.s.l. band. On average, maximum snow accumulation is observed in early September in the western Andes, and in early October on the eastern side of the continental divide. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.

Qualification testing of solar photovoltaic powered refrigerator freezers for medical use in remote geographic locations

NASA Astrophysics Data System (ADS)

Kaszeta, W. J.

1982-12-01

One of the primary obstacles to the application of vaccination in developing countries is the lack of refrigerated storage. Vaccines exposed to elevated temperatures suffer a permanent loss of potency. Photovoltaic (PV) powered refrigerator/freezer (R/F) units could surmount the problem of refrigeration in remote areas where no reliable commercial power supply is available. The performance measurements of two different models of PV powered R/F units for medical use are presented. Qualification testing consisted of four major procedures: no-load pull down, ice making, steady-state (maintenance), and holdover. Both R/F units met the major World Health Organization (WHO) requirements. However, the testing performed does not provide complete characterization of the two units; such information could be derived only from further extensive test procedures.

Qualification testing of solar photovoltaic powered refrigerator freezers for medical use in remote geographic locations

NASA Technical Reports Server (NTRS)

Kaszeta, W. J.

1982-01-01

One of the primary obstacles to the application of vaccination in developing countries is the lack of refrigerated storage. Vaccines exposed to elevated temperatures suffer a permanent loss of potency. Photovoltaic (PV) powered refrigerator/freezer (R/F) units could surmount the problem of refrigeration in remote areas where no reliable commercial power supply is available. The performance measurements of two different models of PV powered R/F units for medical use are presented. Qualification testing consisted of four major procedures: no-load pull down, ice making, steady-state (maintenance), and holdover. Both R/F units met the major World Health Organization (WHO) requirements. However, the testing performed does not provide complete characterization of the two units; such information could be derived only from further extensive test procedures.

Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data.

PubMed

Zhang, Jingyi; Li, Bin; Chen, Yumin; Chen, Meijie; Fang, Tao; Liu, Yongfeng

2018-06-11

This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF) method to estimate ground PM 2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR) models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM 2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM 2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM 2.5 analysis and prediction.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Investigating flood susceptible areas in inaccessible regions using remote sensing and geographic information systems.

PubMed

Lim, Joongbin; Lee, Kyoo-Seock

2017-03-01

Every summer, North Korea (NK) suffers from floods, resulting in decreased agricultural production and huge economic loss. Besides meteorological reasons, several factors can accelerate flood damage. Environmental studies about NK are difficult because NK is inaccessible due to the division of Korea. Remote sensing (RS) can be used to delineate flood inundated areas in inaccessible regions such as NK. The objective of this study was to investigate the spatial characteristics of flood susceptible areas (FSAs) using multi-temporal RS data and digital elevation model data. Such study will provide basic information to restore FSAs after reunification. Defining FSAs at the study site revealed that rice paddies with low elevation and low slope were the most susceptible areas to flood in NK. Numerous sediments from upper streams, especially streams through crop field areas on steeply sloped hills, might have been transported and deposited into stream channels, thus disturbing water flow. In conclusion, NK floods may have occurred not only due to meteorological factors but also due to inappropriate land use for flood management. In order to mitigate NK flood damage, reforestation is needed for terraced crop fields. In addition, drainage capacity for middle stream channel near rice paddies should be improved.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

ASTER VNIR 15 years growth to the standard imaging radiometer in remote sensing

NASA Astrophysics Data System (ADS)

Hiramatsu, Masaru; Inada, Hitomi; Kikuchi, Masakuni; Sakuma, Fumihiro

2015-10-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible and Near Infrared Radiometer (VNIR) is the remote sensing equipment which has 3 spectral bands and one along-track stereoscopic band radiometer. ASTER VNIR's planned long life design (more than 5 years) is successfully achieved. ASTER VNIR has been imaging the World-wide Earth surface multiband images and the Global Digital Elevation Model (GDEM). VNIR data create detailed world-wide maps and change-detection of the earth surface as utilization transitions and topographical changes. ASTER VNIR's geometric resolution is 15 meters; it is the highest spatial resolution instrument on NASA's Terra spacecraft. Then, ASTER VNIR was planned for the geometrical basis map makers in Terra instruments. After 15-years VNIR growth to the standard map-maker for space remote-sensing. This paper presents VNIR's feature items during 15-year operation as change-detection images , DEM and calibration result. VNIR observed the World-wide Earth images for biological, climatological, geological, and hydrological study, those successful work shows a way on space remote sensing instruments. Still more, VNIR 15 years observation data trend and onboard calibration trend data show several guide or support to follow-on instruments.

Combining remote sensing image with DEM to identify ancient Minqin Oasis, northwest of China

NASA Astrophysics Data System (ADS)

Xie, Yaowen

2008-10-01

The developing and desertification process of Minqin oasis is representative in the whole arid area of northwest China. Combining Remote Sensing image with Digital Elevation Model (DEM) can produce the three-dimensional image of the research area which can give prominence to the spatial background of historical geography phenomenon's distribution, providing the conditions for extracting and analyzing historical geographical information thoroughly. This research rebuilds the ancient artificial Oasis based on the three-dimensional images produced by the TM digital Remote Sensing image and DEM created using 1:100000 topographic maps. The result indicates that the whole area of the ancient artificial oasis in Minqin Basin over the whole historical period reaches 321km2, in the form of discontinuous sheet, separated on the two banks of ancient Shiyang River and its branches, namely, Xishawo area, west to modern Minqin Basin and Zhongshawo area, in the center of the oasis. Except for a little of the ancient oasis unceasingly used by later people, most of it became desert. The combination of digital Remote Sensing image and DEM can integrate the advantages of both in identifying ancient oasis and improve the interpreting accuracy greatly.

Constructing river stage-discharge rating curves using remotely sensed river cross-sectional inundation areas and river bathymetry

NASA Astrophysics Data System (ADS)

Pan, Feifei; Wang, Cheng; Xi, Xiaohuan

2016-09-01

Remote sensing from satellites and airborne platforms provides valuable data for monitoring and gauging river discharge. One effective approach first estimates river stage from satellite-measured inundation area based on the inundation area-river stage relationship (IARSR), and then the estimated river stage is used to compute river discharge based on the stage-discharge rating (SDR) curve. However, this approach is difficult to implement because of a lack of data for constructing the SDR curves. This study proposes a new method to construct the SDR curves using remotely sensed river cross-sectional inundation areas and river bathymetry. The proposed method was tested over a river reach between two USGS gauging stations, i.e., Kingston Mines (KM) and Copperas Creek (CC) along the Illinois River. First a polygon over each of two cross sections was defined. A complete IARSR curve was constructed inside each polygon using digital elevation model (DEM) and river bathymetric data. The constructed IARSR curves were then used to estimate 47 river water surface elevations at each cross section based on 47 river inundation areas estimated from Landsat TM images collected during 1994-2002. The estimated water surface elevations were substituted into an objective function formed by the Bernoulli equation of gradually varied open channel flow. A nonlinear global optimization scheme was applied to solve the Manning's coefficient through minimizing the objective function value. Finally the SDR curve was constructed at the KM site using the solved Manning's coefficient, channel cross sectional geometry and the Manning's equation, and employed to estimate river discharges. The root mean square error (RMSE) in the estimated river discharges against the USGS measured river discharges is 112.4 m3/s. To consider the variation of the Manning's coefficient in the vertical direction, this study also suggested a power-law function to describe the vertical decline of the Manning's coefficient with the water level from the channel bed lowest elevation to the bank-full level. The constructed SDR curve with the vertical variation of the Manning's coefficient reduced the RMSE in the estimated river discharges to 83.9 m3/s. These results indicate that the method developed and tested in this study is effective and robust, and has the potential for improving our ability of remote sensing of river discharge and providing data for water resources management, global water cycle study, and flood forecasting and prevention.

A Comparative Distributed Evaluation of the NWS-RDHM using Shape Matching and Traditional Measures with In Situ and Remotely Sensed Information

NASA Astrophysics Data System (ADS)

KIM, J.; Bastidas, L. A.

2011-12-01

We evaluate, calibrate and diagnose the performance of National Weather Service RDHM distributed model over the Durango River Basin in Colorado using simultaneously in situ and remotely sensed information from different discharge gaging stations (USGS), information about snow cover (SCV) and snow water equivalent (SWE) in situ from several SNOTEL sites and snow information distributed over the catchment from remotely sensed information (NOAA-NASA). In the process of evaluation we attempt to establish the optimal degree of parameter distribution over the catchment by calibration. A multi-criteria approach based on traditional measures (RMSE) and similarity based pattern comparisons using the Hausdorff and Earth Movers Distance approaches is used for the overall evaluation of the model performance. These pattern based approaches (shape matching) are found to be extremely relevant to account for the relatively large degree of inaccuracy in the remotely sensed SWE (judged inaccurate in terms of the value but reliable in terms of the distribution pattern) and the high reliability of the SCV (yes/no situation) while at the same time allow for an evaluation that quantifies the accuracy of the model over the entire catchment considering the different types of observations. The Hausdorff norm, due to its intrinsically multi-dimensional nature, allows for the incorporation of variables such as the terrain elevation as one of the variables for evaluation. The EMD, because of its extremely high computational overburden, requires the mapping of the set of evaluation variables into a two dimensional matrix for computation.

Assimilation of Remotely-Sensed Snow information to improve streamflow predictions in the Southwestern US

NASA Astrophysics Data System (ADS)

López-Burgos, V.; Rajagopal, S.; Martinez Baquero, G. F.; Gupta, H. V.

2009-12-01

Rapidly growing population in the southwestern US is leading to increasing demand and decreasing availability of water, requiring a detailed quantification of hydrological processes. The integration of detailed spatial information of water fluxes from remote sensing platforms, and hydrological models coupled with ground based data is an important step towards this goal. This project is exploring the use of Snow Water Equivalent (SWE) estimates to update the snow component of the Variable Infiltration Capacity model (VIC). SWE estimates are obtained by combining SNOTEL data with MODIS Snow Cover Area (SCA) information. Because, cloud cover corrupts the estimates of SCA, a rule-based method is used to clean up the remotely sensed images. The rules include a time interpolation method, and the probability of a pixel for been covered with snow based on the relationships between elevation, temperature, lapse rate, aspect and topographic shading. The approach is used to improve streamflow predictions on two rivers managed by the Salt River Project, a water and energy supplier in central Arizona. This solution will help improve the management of reservoirs in the Salt and Verde River in Phoenix, Arizona (tributaries of the lower Colorado River basin), by incorporating physically based distributed models and remote sensing observations into their Decision Support Tools and planning tools. This research seeks to increase the knowledge base used to manage reservoirs and groundwater resources in a region affected by a long-term drought. It will be applicable and relevant for other water utility companies facing the challenges of climate change and decreasing water resources.

Remote measurement of canopy reflectance shows the effects of elevated carbon dioxide and ozone on the structure and functioning of soybeans in a field setting.

NASA Astrophysics Data System (ADS)

Gray, S.; Dermody, O.; Delucia, E.

2006-12-01

By altering physiological processes and modifying canopy structure, elevated atmospheric CO2 and O3 directly and indirectly change the productivity of agroecosystems. Remote sensing of canopy reflectance can be used to monitor physiological and structural changes in an ecosystem over a growing season. To examine effects of changing tropospheric chemistry on water content, chlorophyll content, and changes in leaf area index (LAI), Free-Air Concentration Enrichment (FACE) technology was used to expose large plots of soybean (Glycine max) to elevated atmospheric CO2, elevated O3 (1.5 x ambient), and combined elevated CO2 and O3. The following indices were calculated from weekly measurements of reflectance: water index (WI), photochemical reflectance index (PRI), chlorophyll index, near-infrared/ red (NIR/red), and normalized difference vegetation index (NDVI). NIR/red and LAI were strongly correlated throughout the growth season; however NDVI and LAI were highly correlated only up to LAI of 3. Exposure to elevated CO2 accelerated early-season canopy development and delayed late-season senescence. Growth in elevated O3 had the opposite effect. Additionally, elevated CO2 compensated for negative effects of O3 when the canopy was exposed to both gases simultaneously. Reflectance indices revealed several physiological and structural responses of this agroecosystem to tropospheric change, and ultimately that elevated CO2 and O3 significantly affected this system's productivity and period for carbon gain.

Combining Imagery and Models to Understand River Dynamics

NASA Astrophysics Data System (ADS)

Blain, C. A.; Mied, R. P.; Linzell, R. S.

2014-12-01

Rivers pose one of the most challenging environments to characterize. Their geometric complexity and continually changing position and character are difficult to measure under optimal circumstances. Further compounding the problem is the often inaccessibility of these areas around the globe. Yet details of the river bank position and bed elevation are essential elements in the construction of accurate predictive river models. To meet this challenge, remote sensing imagery is first used to initialize the construction of advanced high resolution river circulation models. In turn, such models are applied to dynamically interpret remotely-sensed surface features. A method has been developed to automatically extract water and shoreline locations from arbitrarily sourced high resolution (~1m gsd) visual spectrum imagery without recourse to the spectral or color information. The approach relies on quantifying the difference in image texture between the relatively smooth water surface and the comparatively rough surface of surrounding land. Processing the segmented land/water interface results in ordered, continuous shoreline coordinates that bound river model construction. In the absence of observed bed elevations, one of several available analytic bathymetry cross-sectional relations are applied to complete the river model configuration. Successful application of this approach to the Snohomish River, WA and the Pearl River, MS are demonstrated. Once constructed, a hydrodynamic model of the river model can also be applied to unravel the dynamics responsible for observed surface features in the imagery. At a creek-river confluence in the Potomac River, MD, an ebb tide front observed in the imagery is analyzed using the model. The result is knowledge that an ebb shoal located just outside of the creek must be present and is essential for front formation. Furthermore, the front is found to be persistent throughout the tidal cycle, although it changes sign between ebb and flood phases. The presence of the creek only minimally modifies the underlying currents.

NORTH ELEVATION OF HOT PILOT PLANT (CPP640) LOOKING SOUTH AFTER ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

NORTH ELEVATION OF HOT PILOT PLANT (CPP-640) LOOKING SOUTH AFTER REMOTE ANALYTICAL FACILITY (CPP-627) WAS REMOVED. PHOTO NUMBER HD-54-33-2. Mike Crane, Photographer, 7/2006 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.

2017-12-01

Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning

On-Ground Processing of Yaogan-24 Remote Sensing Satellite Attitude Data and Verification Using Geometric Field Calibration

PubMed Central

Wang, Mi; Fan, Chengcheng; Yang, Bo; Jin, Shuying; Pan, Jun

2016-01-01

Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite’s on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%. PMID:27483287

Using satellite remote sensing to model and map the distribution of Bicknell's thrush (Catharus bicknelli) in the White Mountains of New Hampshire

NASA Astrophysics Data System (ADS)

Hale, Stephen Roy

Landsat-7 Enhanced Thematic Mapper satellite imagery was used to model Bicknell's Thrush (Catharus bicknelli) distribution in the White Mountains of New Hampshire. The proof-of-concept was established for using satellite imagery in species-habitat modeling, where for the first time imagery spectral features were used to estimate a species-habitat model variable. The model predicted rising probabilities of thrush presence with decreasing dominant vegetation height, increasing elevation, and decreasing distance to nearest Fir Sapling cover type. To solve the model at all locations required regressor estimates at every pixel, which were not available for the dominant vegetation height and elevation variables. Topographically normalized imagery features Normalized Difference Vegetation Index and Band 1 (blue) were used to estimate dominant vegetation height using multiple linear regression; and a Digital Elevation Model was used to estimate elevation. Distance to nearest Fir Sapling cover type was obtained for each pixel from a land cover map specifically constructed for this project. The Bicknell's Thrush habitat model was derived using logistic regression, which produced the probability of detecting a singing male based on the pattern of model covariates. Model validation using Bicknell's Thrush data not used in model calibration, revealed that the model accurately estimated thrush presence at probabilities ranging from 0 to <0.40 and from 0.50 to <0.60. Probabilities from 0.40 to <0.50 and greater than 0.60 significantly underestimated and overestimated presence, respectively. Applying the model to the study area illuminated an important implication for Bicknell's Thrush conservation. The model predicted increasing numbers of presences and increasing relative density with rising elevation, with which exists a concomitant decrease in land area. Greater land area of lower density habitats may account for more total individuals and reproductive output than higher density less abundant land area. Efforts to conserve areas of highest individual density under the assumption that density reflects habitat quality could target the smallest fraction of the total population.

The association between C-reactive protein levels and the risk for chronic kidney disease hospitalizations in adults of a remote Indigenous Australian community - A prospective cohort study.

PubMed

Arnold, Luke W; Hoy, Wendy E; Wang, Zhiqiang

2017-09-01

Indigenous Australians are significantly burdened by chronic kidney disease (CKD). Elevated levels of C-reactive protein (CRP) have been associated with diabetes and cardiovascular incidence in previous studies. Elevated CRP has been associated with albuminuria and reduced eGFR in cross-sectional studies. This study investigated the long-term predictive association between CRP measured at a baseline exam and the incidence of a CKD-related hospitalization. Health screening examinations were conducted in individuals of a remote indigenous Australian community between 1992 and 1998. The risk of subsequent CKD hospitalisations, documented through Northern Territory hospital records up to 2010, was estimated with Cox proportional hazard models in people aged over 18 years at the baseline screen and who had albumin-creatinine ratios (ACRs) less than 34g/mol. 546 participants were eligible for our study. Individuals in the highest CRP tertile at baseline had increased levels of traditional cardiovascular risk factors. They also had almost 4 times the risk of a CKD-related hospitalisation compared with participants in the lowest CRP tertile (HR=3.91, 95%CI 1.01-15.20, P=0.049) after adjustment for potential confounding factors. Participants with CRP concentrations greater than 3mg/L had almost 3 times the risk of CKD hospitalisations than those ≤3mg/L (HR=2.84, 95%CI 1.00-8.00, P=0.049). Furthermore, risk of CKD hospitalisations increased 34% per doubling of baseline CRP (HR=1.34, 95%CI 1.04-1.74, P=0.024). In individuals in this remote indigenous community without overt albuminuria at baseline the risk for incident CKD related hospitalisations was predicted by elevated C-reactive protein levels almost a decade earlier. Further research is needed to understand the roles that CRP and systemic inflammation play in CKD risk. © 2016 Asian Pacific Society of Nephrology.

Informing a hydrological model of the Ogooué with multi-mission remote sensing data

NASA Astrophysics Data System (ADS)

Kittel, Cecile M. M.; Nielsen, Karina; Tøttrup, Christian; Bauer-Gottwein, Peter

2018-02-01

Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall-runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953-1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterization of hydrological conditions in the Ogooué in light of the available observations.

Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987.

PubMed

Korsgaard, Niels J; Nuth, Christopher; Khan, Shfaqat A; Kjeldsen, Kristian K; Bjørk, Anders A; Schomacker, Anders; Kjær, Kurt H

2016-05-10

Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987

NASA Astrophysics Data System (ADS)

Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat A.; Kjeldsen, Kristian K.; Bjørk, Anders A.; Schomacker, Anders; Kjær, Kurt H.

2016-05-01

Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

Integrating geospatial and ground geophysical information as guidelines for groundwater potential zones in hard rock terrains of south India.

PubMed

Rashid, Mehnaz; Lone, Mahjoor Ahmad; Ahmed, Shakeel

2012-08-01

The increasing demand of water has brought tremendous pressure on groundwater resources in the regions were groundwater is prime source of water. The objective of this study was to explore groundwater potential zones in Maheshwaram watershed of Andhra Pradesh, India with semi-arid climatic condition and hard rock granitic terrain. GIS-based modelling was used to integrate remote sensing and geophysical data to delineate groundwater potential zones. In the present study, Indian Remote Sensing RESOURCESAT-1, Linear Imaging Self-Scanner (LISS-4) digital data, ASTER digital elevation model and vertical electrical sounding data along with other data sets were analysed to generate various thematic maps, viz., geomorphology, land use/land cover, geology, lineament density, soil, drainage density, slope, aquifer resistivity and aquifer thickness. Based on this integrated approach, the groundwater availability in the watershed was classified into four categories, viz. very good, good, moderate and poor. The results reveal that the modelling assessment method proposed in this study is an effective tool for deciphering groundwater potential zones for proper planning and management of groundwater resources in diverse hydrogeological terrains.

Using Terrain Analysis and Remote Sensing to Improve Snow Mass Balance and Runoff Prediction

NASA Astrophysics Data System (ADS)

Venteris, E. R.; Coleman, A. M.; Wigmosta, M. S.

2010-12-01

Approximately 70-80% of the water in the international Columbia River basin is sourced from snowmelt. The demand for this water has competing needs, as it is used for agricultural irrigation, municipal, hydro and nuclear power generation, and environmental in-stream flow requirements. Accurate forecasting of water supply is essential for planning current needs and prediction of future demands due to growth and climate change. A significant limitation on current forecasting is spatial and temporal uncertainty in snowpack characteristics, particularly snow water equivalent. Currently, point measurements of snow mass balance are provided by the NRCS SNOTEL network. Each site consists of a snow mass sensor and meteorology station that monitors snow water equivalent, snow depth, precipitation, and temperature. There are currently 152 sites in the mountains of Oregon and Washington. An important step in improving forecasts is determining how representative each SNOTEL site is of the total mass balance of the watershed through a full accounting of the spatiotemporal variability in snowpack processes. This variation is driven by the interaction between meteorological processes, land cover, and landform. Statistical and geostatistical spatial models relate the state of the snowpack (characterized through SNOTEL, snow course measurements, and multispectral remote sensing) to terrain attributes derived from digital elevation models (elevation, aspect, slope, compound topographic index, topographic shading, etc.) and land cover. Time steps representing the progression of the snow season for several meteorologically distinct water years are investigated to identify and quantify dominant physical processes. The spatially distributed snow balance data can be used directly as model inputs to improve short- and long-range hydrologic forecasts.

Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

NASA Astrophysics Data System (ADS)

Hadley, Brian Christopher

This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

Remote Estimation of River Discharge and Bathymetry: Sensitivity to Turbulent Dissipation and Bottom Friction

NASA Astrophysics Data System (ADS)

Simeonov, J.; Holland, K. T.

2016-12-01

We investigated the fidelity of a hierarchy of inverse models that estimate river bathymetry and discharge using measurements of surface currents and water surface elevation. Our most comprehensive depth inversion was based on the Shiono and Knight (1991) model that considers the depth-averaged along-channel momentum balance between the downstream pressure gradient due to gravity, the bottom drag and the lateral stresses induced by turbulence. The discharge was determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. The bottom friction coefficient was assumed to be known or determined by alternative means. We also considered simplifications of the comprehensive inversion model that exclude the lateral mixing term from the momentum balance and assessed the effect of neglecting this term on the depth and discharge estimates for idealized in-bank flow in symmetric trapezoidal channels with width/depth ratio of 40 and different side-wall slopes. For these simple gravity-friction models, we used two different bottom friction parameterizations - a constant Darcy-Weisbach local friction and a depth-dependent friction related to the local depth and a constant Manning (roughness) coefficient. Our results indicated that the Manning gravity-friction model provides accurate estimates of the depth and the discharge that are within 1% of the assumed values for channels with side-wall slopes between 1/2 and 1/17. On the other hand, the constant Darcy-Weisbach friction model underpredicted the true depth and discharge by 7% and 9%, respectively, for the channel with side-wall slope of 1/17. These idealized modeling results suggest that a depth-dependent parameterization of the bottom friction is important for accurate inversion of depth and discharge and that the lateral turbulent mixing is not important. We also tested the comprehensive and the simplified inversion models for the Kootenai River near Bonners Ferry (Idaho) using in situ and remote sensing measurements of surface currents and water surface elevation obtained during a 2010 field experiment.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Remote sensing for environmental protection of the eastern Mediterranean rugged mountainous areas, Lebanon

NASA Astrophysics Data System (ADS)

Khawlie, M.; Awad, M.; Shaban, A.; Bou Kheir, R.; Abdallah, C.

Lying along the eastern Mediterranean coast with elevated mountain chains higher than 2500 m straddling its terrain, Lebanon is a country of natural beauty and is thus attracting tourism. However, with a population density exceeding 800/km 2 and a rugged steep sloping land, problems abound in the country calling for holistic-approach studies. Only remote sensing, whose use is new in Lebanon can secure such needed studies within a scientific and pragmatic framework. The paper demonstrates for the concerned themes, the innovative use of remote sensing in such a difficult terrain, giving three examples of major environmental problems in the coastal mountains. Only few studies have so far focused on those mountains, notably application of remote sensing. The rugged mountainous terrain receives considerable rain, but the water is quickly lost running on the steep slopes, or infiltrating through fractures and the karstic conduits into the subsurface. Field investigations are difficult to achieve, therefore, remote sensing helps reveal various surface land features important in reflecting water feeding into the subsurface. Optical, radar and thermal infrared remotely sensed data cover a wide spectrum serving that purpose. A map of preferential groundwater accumulation potential is produced. It can serve for better water exploitation as well as protection. Because the terrain is karstic and rugged, the subsurface water flow is difficult to discern. Any pollution at a certain spot would certainly spread around. This constitutes the second example of environmental problems facing the mountainous areas in Lebanon. An integrated approach using remote sensing and geographic information systems (GIS) gives good results in finding out the likelihood of how pollution, or contaminants, can selectively move in the subsurface. A diagnostic analysis with a GIS-type software acts as a guide producing indicative maps for the above purpose. The third example given deals with the problem of losing soil, which is a very vital source in such mountainous land. With steep slopes, torrential rain and improper human interference, run-off is high and water-soil erosion is continuously deteriorating the land cover. Remote sensing can facilitate studying the factors enhancing the process, such as soil type, slope gradient, drainage, geology and land cover. Digital elevation models created from SAR imagery contribute significantly to assessing vulnerability of hydric-soil erosion over such a difficult terrain. GIS layers of the above factors are integrated with erosional criteria to produce a risk map of soil erosion. Results indicate that 36% of the Lebanese terrain is under threat of high-level erosion, and 52% of that is concentrated in the rugged mountainous regions.

Shuttle radar DEM hydrological correction for erosion modelling in small catchments

NASA Astrophysics Data System (ADS)

Jarihani, Ben; Sidle, Roy; Bartley, Rebecca

2016-04-01

Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modelling of environmental processes. Catchment and hillslope scale runoff and sediment processes (i.e., patterns of overland flow, infiltration, subsurface stormflow and erosion) are all topographically mediated. In remote and data-scarce regions, high resolution DEMs (LiDAR) are often not available, and moderate to course resolution digital elevation models (e.g., SRTM) have difficulty replicating detailed hydrological patterns, especially in relatively flat landscapes. Several surface reconditioning algorithms (e.g., Smoothing) and "Stream burning" techniques (e.g., Agree or ANUDEM), in conjunction with representation of the known stream networks, have been used to improve DEM performance in replicating known hydrology. Detailed stream network data are not available at regional and national scales, but can be derived at local scales from remotely-sensed data. This research explores the implication of high resolution stream network data derived from Google Earth images for DEM hydrological correction, instead of using course resolution stream networks derived from topographic maps. The accuracy of implemented method in producing hydrological-efficient DEMs were assessed by comparing the hydrological parameters derived from modified DEMs and limited high-resolution airborne LiDAR DEMs. The degree of modification is dominated by the method used and availability of the stream network data. Although stream burning techniques improve DEMs hydrologically, these techniques alter DEM characteristics that may affect catchment boundaries, stream position and length, as well as secondary terrain derivatives (e.g., slope, aspect). Modification of a DEM to better reflect known hydrology can be useful, however, knowledge of the magnitude and spatial pattern of the changes are required before using a DEM for subsequent analyses.

Hydroclimate of the Spring Mountains and Sheep Range, Clark County, Nevada

USGS Publications Warehouse

Moreo, Michael T.; Senay, Gabriel B.; Flint, Alan L.; Damar, Nancy A.; Laczniak, Randell J.; Hurja, James

2014-01-01

Precipitation, potential evapotranspiration, and actual evapotranspiration often are used to characterize the hydroclimate of a region. Quantification of these parameters in mountainous terrains is difficult because limited access often hampers the collection of representative ground data. To fulfill a need to characterize ecological zones in the Spring Mountains and Sheep Range of southern Nevada, spatially and temporally explicit estimates of these hydroclimatic parameters are determined from remote-sensing and model-based methodologies. Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation estimates for this area ranges from about 100 millimeters (mm) in the low elevations of the study area (700 meters [m]) to more than 700 mm in the high elevations of the Spring Mountains (> 2,800 m). The PRISM model underestimates precipitation by 7–15 percent based on a comparison with four high‑elevation precipitation gages having more than 20 years of record. Precipitation at 3,000-m elevation is 50 percent greater in the Spring Mountains than in the Sheep Range. The lesser amount of precipitation in the Sheep Range is attributed to partial moisture depletion by the Spring Mountains of eastward-moving, cool-season (October–April) storms. Cool-season storms account for 66–76 percent of annual precipitation. Potential evapotranspiration estimates by the Basin Characterization Model range from about 700 mm in the high elevations of the Spring Mountains to 1,600 mm in the low elevations of the study area. The model realistically simulates lower potential evapotranspiration on northeast-to-northwest facing slopes compared to adjacent southeast-to-southwest facing slopes. Actual evapotranspiration, estimated using a Moderate Resolution Imaging Spectroradiometer based water-balance model, ranges from about 100 to 600 mm. The magnitude and spatial variation of simulated, actual evapotranspiration was validated by comparison to PRISM precipitation. Estimated groundwater recharge, computed as the residual of precipitation depleted by actual evapotranspiration, is within the range of previous estimates. A climatic water deficit dataset and aridity-index-based climate zones are derived from precipitation and evapotranspiration datasets. Climate zones range from arid in the lower elevations of the study area to humid in small pockets on north- to northeast-facing slopes in the high elevations of the Spring Mountains. Correlative analyses between hydroclimatic variables and mean ecosystem elevations indicate that the climatic water deficit is the best predictor of ecosystem distribution (R2 = 0.92). Computed water balances indicate that substantially more recharge is generated in the Spring Mountains than in the Sheep Range. A geospatial database containing compiled and developed hydroclimatic data and other pertinent information accompanies this report.

Developing GIS-based eastern equine encephalitis vector-host models in Tuskegee, Alabama.

PubMed

Jacob, Benjamin G; Burkett-Cadena, Nathan D; Luvall, Jeffrey C; Parcak, Sarah H; McClure, Christopher J W; Estep, Laura K; Hill, Geoffrey E; Cupp, Eddie W; Novak, Robert J; Unnasch, Thomas R

2010-02-24

A site near Tuskegee, Alabama was examined for vector-host activities of eastern equine encephalomyelitis virus (EEEV). Land cover maps of the study site were created in ArcInfo 9.2 from QuickBird data encompassing visible and near-infrared (NIR) band information (0.45 to 0.72 microm) acquired July 15, 2008. Georeferenced mosquito and bird sampling sites, and their associated land cover attributes from the study site, were overlaid onto the satellite data. SAS 9.1.4 was used to explore univariate statistics and to generate regression models using the field and remote-sampled mosquito and bird data. Regression models indicated that Culex erracticus and Northern Cardinals were the most abundant mosquito and bird species, respectively. Spatial linear prediction models were then generated in Geostatistical Analyst Extension of ArcGIS 9.2. Additionally, a model of the study site was generated, based on a Digital Elevation Model (DEM), using ArcScene extension of ArcGIS 9.2. For total mosquito count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.041 km, nugget of 6.325 km, lag size of 7.076 km, and range of 31.43 km, using 12 lags. For total adult Cx. erracticus count, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.764 km, nugget of 6.114 km, lag size of 7.472 km, and range of 32.62 km, using 12 lags. For the total bird count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 4.998 km, nugget of 5.413 km, lag size of 7.549 km and range of 35.27 km, using 12 lags. For the Northern Cardinal count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 6.387 km, nugget of 5.935 km, lag size of 8.549 km and a range of 41.38 km, using 12 lags. Results of the DEM analyses indicated a statistically significant inverse linear relationship between total sampled mosquito data and elevation (R2 = -.4262; p < .0001), with a standard deviation (SD) of 10.46, and total sampled bird data and elevation (R2 = -.5111; p < .0001), with a SD of 22.97. DEM statistics also indicated a significant inverse linear relationship between total sampled Cx. erracticus data and elevation (R2 = -.4711; p < .0001), with a SD of 11.16, and the total sampled Northern Cardinal data and elevation (R2 = -.5831; p < .0001), SD of 11.42. These data demonstrate that GIS/remote sensing models and spatial statistics can capture space-varying functional relationships between field-sampled mosquito and bird parameters for determining risk for EEEV transmission.

Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

NASA Astrophysics Data System (ADS)

Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

2016-09-01

Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

Robust feature matching via support-line voting and affine-invariant ratios

NASA Astrophysics Data System (ADS)

Li, Jiayuan; Hu, Qingwu; Ai, Mingyao; Zhong, Ruofei

2017-10-01

Robust image matching is crucial for many applications of remote sensing and photogrammetry, such as image fusion, image registration, and change detection. In this paper, we propose a robust feature matching method based on support-line voting and affine-invariant ratios. We first use popular feature matching algorithms, such as SIFT, to obtain a set of initial matches. A support-line descriptor based on multiple adaptive binning gradient histograms is subsequently applied in the support-line voting stage to filter outliers. In addition, we use affine-invariant ratios computed by a two-line structure to refine the matching results and estimate the local affine transformation. The local affine model is more robust to distortions caused by elevation differences than the global affine transformation, especially for high-resolution remote sensing images and UAV images. Thus, the proposed method is suitable for both rigid and non-rigid image matching problems. Finally, we extract as many high-precision correspondences as possible based on the local affine extension and build a grid-wise affine model for remote sensing image registration. We compare the proposed method with six state-of-the-art algorithms on several data sets and show that our method significantly outperforms the other methods. The proposed method achieves 94.46% average precision on 15 challenging remote sensing image pairs, while the second-best method, RANSAC, only achieves 70.3%. In addition, the number of detected correct matches of the proposed method is approximately four times the number of initial SIFT matches.

The protective effects of pomegranate on liver and remote organs caused by experimental obstructive jaundice model.

PubMed

Yilmaz, E E; Arikanoğlu, Z; Turkoğlu, A; Kiliç, E; Yüksel, H; Gümüş, M

2016-01-01

We aimed to investigate the protective potential of pomegranate extract on the liver and remote organs in rats with obstructive jaundice. The rats were split into 4 groups. In Group 1 (G1) (sham group) rats, the common bile duct was mobilized without any ligation. Group 2 (G2) received a combination of the sham operation and synchronous treatment with pomegranate. Group 3 (G3) received common bile duct ligation (CBDL). Group 4 (G4) were subjected to CBDL and treatment with pomegranate. After 8 days, we measured total oxidative status (TOS) and antioxidant capacity in the rats' liver tissue and remote organs, and evaluated blood levels of malondialdehyde and total antioxidant capacity (TAC). G3 rats showed significantly raised malondialdehyde level as compared to G1 rats (p < 0.001). Following the pomegranate therapy, a decrease in malondialdehyde was observed (p = 0.015). TAC levels were significantly raised in the G3 rats compared to the G1 rats (p = 0.004). TAC levels dropped after pomegranate therapy (p = 0.011). CBDL caused elevated TOS levels in the liver and remote organs, with a statistically significant increase in the lung tissue (p = 0.002). TOS levels in the CBDL groups decreased after pomegranate treatment (p < 0.001). This study reveals the marked protective effect of pomegranate on the liver and remote organs in obstructive jaundice.

Remote Sensing Estimates of Glacier Mass Balance Changes in the Himalayas of Nepal

NASA Astrophysics Data System (ADS)

Ambinakudige, S.; Joshi, K.

2011-12-01

Mass balance changes of glaciers are important indicators of climate change. There are only 30 'reference' glaciers in the world that have continuous mass balance data with world glacier monitoring service since 1976. Especially, Himalayan glaciers are conspicuously absent from global mass balance records. This shows the urgent need for mass balance data for glaciers throughout the world. In this study, we estimated mass balance of some major glaciers in the Sagarmatha National Park (SNP) in Nepal using remote sensing applications. The SNP is one of the densest glaciated regions in the Himalayan range consisting approximately 296 glacial lakes. The region has experienced several glacial lake outburst floods (GLOFs) in recent years, causing extensive damage to local infrastructure and loss of human life. In general, mass balance is determined at seasonal or yearly intervals. Because of the rugged and difficult terrain of the Himalayan region, there are only a few field based measurements of mass balance available. Moreover, there are only few cases where the applications of remote sensing methods were used to calculate mass balance of the Himalayan glaciers due to the lack of accurate elevation data. Studies have shown that estimations of mass balance using remote sensing applications were within the range of field-based mass balance measurements from the same period. This study used ASTER VNIR, 3N (nadir view) and 3B (backward view) bands to generate Digital Elevation Models (DEMs) for the SNP area. 3N and 3B bands generate an along track stereo pair with a base-to-height (B/H) ratio of about 0.6. Accurate measurement of ground control points (GCPs), their numbers and distribution are important inputs in creating accurate DEMs. Because of the availability of topographic maps for this area, we were able to provide very accurate GCPs, in sufficient numbers and distribution. We created DEMs for the years 2002, 2003, 2004 and 2005 using ENVI DEM extraction tool. Bands 3N and 3B were used as left and right images respectively in the process of creating the DEM. Minimum elevation in these images was 1500m and maximum elevation was 8550m. Coordinates and elevation values from topographic maps in the non-glaciated region were used as GCPs while creating absolute DEMs. Considering the high terrain of the study area, we used large number of GCPs, tie points, higher windows search area, and high terrain parameters to improve DEM accuracy. Since these images were acquired in September, the accumulation area was clearly visible. The Global land ice measurement (GLIMS) database which is maintained at the National Snow and Ice Data Center (NSIDC) was used to delineate glacier boundaries. The differences between the elevations in consecutive years in the accumulation area were calculated using raster calculator. The total elevation differences were then multiplied by the area to estimate the change in volume. Density of ice used in mass balance calculation was 900kg per sq. meters. The result indicated that while there was a decrease in mass balance of some glaciers, some showed an increase in mass balance during the study period. The study helped to develop a data on mass balance change in some major glaciers in the Himalayas.

Global multi-resolution terrain elevation data 2010 (GMTED2010)

USGS Publications Warehouse

Danielson, Jeffrey J.; Gesch, Dean B.

2011-01-01

In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data. Since the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc-second DTEDRegistered level 0, the USGS and the National Geospatial-Intelligence Agency (NGA) have collaborated to produce an enhanced replacement for GTOPO30, the Global Land One-km Base Elevation (GLOBE) model and other comparable 30-arc-second-resolution global models, using the best available data. The new model is called the Global Multi-resolution Terrain Elevation Data 2010, or GMTED2010 for short. This suite of products at three different resolutions (approximately 1,000, 500, and 250 meters) is designed to support many applications directly by providing users with generic products (for example, maximum, minimum, and median elevations) that have been derived directly from the raw input data that would not be available to the general user or would be very costly and time-consuming to produce for individual applications. The source of all the elevation data is captured in metadata for reference purposes. It is also hoped that as better data become available in the future, the GMTED2010 model will be updated.

An assessment of two methods for identifying undocumented levees using remotely sensed data

USGS Publications Warehouse

Czuba, Christiana R.; Williams, Byron K.; Westman, Jack; LeClaire, Keith

2015-01-01

Many undocumented and commonly unmaintained levees exist in the landscape complicating flood forecasting, risk management, and emergency response. This report describes a pilot study completed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers to assess two methods to identify undocumented levees by using remotely sensed, high-resolution topographic data. For the first method, the U.S. Army Corps of Engineers examined hillshades computed from a digital elevation model that was derived from light detection and ranging (lidar) to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the U.S. Geological Survey applied a wavelet transform to a lidar-derived digital elevation model to identify potential levees. The hillshade method was applied to Delano, Minnesota, and the wavelet-transform method was applied to Delano and Springfield, Minnesota. Both methods were successful in identifying levees but also identified other features that required interpretation to differentiate from levees such as constructed barriers, high banks, and bluffs. Both methods are complementary to each other, and a potential conjunctive method for testing in the future includes (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.

USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response

NASA Astrophysics Data System (ADS)

Jones, B. K.

2014-12-01

The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

NASA's Earth Science Use of Commercially Availiable Remote Sensing Datasets: Cover Image

NASA Technical Reports Server (NTRS)

Underwood, Lauren W.; Goward, Samuel N.; Fearon, Matthew G.; Fletcher, Rose; Garvin, Jim; Hurtt, George

2008-01-01

The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

NASA Astrophysics Data System (ADS)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated peak SWE was 810 mm for WTH and 380 mm for WTH+SP, which led to underestimation of snow season length and melt rate by up to 30 days and 12 mm/day, respectively, in WTH scenario. These results indicate that point scale snow observations at higher elevation can be used to improve precipitation input to hydrologic modeling in mountainous basins.

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

Direct measurements of meltwater runoff on the Greenland ice sheet surface

NASA Astrophysics Data System (ADS)

Smith, Laurence C.; Yang, Kang; Pitcher, Lincoln H.; Overstreet, Brandon T.; Chu, Vena W.; Rennermalm, Åsa K.; Ryan, Jonathan C.; Cooper, Matthew G.; Gleason, Colin J.; Tedesco, Marco; Jeyaratnam, Jeyavinoth; van As, Dirk; van den Broeke, Michiel R.; van de Berg, Willem Jan; Noël, Brice; Langen, Peter L.; Cullather, Richard I.; Zhao, Bin; Willis, Michael J.; Hubbard, Alun; Box, Jason E.; Jenner, Brittany A.; Behar, Alberto E.

2017-12-01

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland's midelevation (1,207–1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.

Direct measurements of meltwater runoff on the Greenland ice sheet surface.

PubMed

Smith, Laurence C; Yang, Kang; Pitcher, Lincoln H; Overstreet, Brandon T; Chu, Vena W; Rennermalm, Åsa K; Ryan, Jonathan C; Cooper, Matthew G; Gleason, Colin J; Tedesco, Marco; Jeyaratnam, Jeyavinoth; van As, Dirk; van den Broeke, Michiel R; van de Berg, Willem Jan; Noël, Brice; Langen, Peter L; Cullather, Richard I; Zhao, Bin; Willis, Michael J; Hubbard, Alun; Box, Jason E; Jenner, Brittany A; Behar, Alberto E

2017-12-12

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km 2 moulin-terminating internally drained catchment (IDC) on Greenland's midelevation (1,207-1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems. Copyright © 2017 the Author(s). Published by PNAS.

Direct measurements of meltwater runoff on the Greenland ice sheet surface

PubMed Central

Smith, Laurence C.; Yang, Kang; Pitcher, Lincoln H; Overstreet, Brandon T.; Chu, Vena W.; Rennermalm, Åsa K.; Ryan, Jonathan C.; Cooper, Matthew G.; Gleason, Colin J.; Tedesco, Marco; Jeyaratnam, Jeyavinoth; van As, Dirk; van den Broeke, Michiel R.; van de Berg, Willem Jan; Noël, Brice; Langen, Peter L.; Cullather, Richard I.; Zhao, Bin; Hubbard, Alun; Box, Jason E.; Jenner, Brittany A.; Behar, Alberto E.

2017-01-01

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland’s midelevation (1,207–1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems. PMID:29208716

A multi-directional and multi-scale roughness filter to detect lineament segments on digital elevation models - analyzing spatial objects in R

NASA Astrophysics Data System (ADS)

Baumann, Sebastian; Robl, Jörg; Wendt, Lorenz; Willingshofer, Ernst; Hilberg, Sylke

2016-04-01

Automated lineament analysis on remotely sensed data requires two general process steps: The identification of neighboring pixels showing high contrast and the conversion of these domains into lines. The target output is the lineaments' position, extent and orientation. We developed a lineament extraction tool programmed in R using digital elevation models as input data to generate morphological lineaments defined as follows: A morphological lineament represents a zone of high relief roughness, whose length significantly exceeds the width. As relief roughness any deviation from a flat plane, defined by a roughness threshold, is considered. In our novel approach a multi-directional and multi-scale roughness filter uses moving windows of different neighborhood sizes to identify threshold limited rough domains on digital elevation models. Surface roughness is calculated as the vertical elevation difference between the center cell and the different orientated straight lines connecting two edge cells of a neighborhood, divided by the horizontal distance of the edge cells. Thus multiple roughness values depending on the neighborhood sizes and orientations of the edge connecting lines are generated for each cell and their maximum and minimum values are extracted. Thereby negative signs of the roughness parameter represent concave relief structures as valleys, positive signs convex relief structures as ridges. A threshold defines domains of high relief roughness. These domains are thinned to a representative point pattern by a 3x3 neighborhood filter, highlighting maximum and minimum roughness peaks, and representing the center points of lineament segments. The orientation and extent of the lineament segments are calculated within the roughness domains, generating a straight line segment in the direction of least roughness differences. We tested our algorithm on digital elevation models of multiple sources and scales and compared the results visually with shaded relief map of these digital elevation models. The lineament segments trace the relief structure to a great extent and the calculated roughness parameter represents the physical geometry of the digital elevation model. Modifying the threshold for the surface roughness value highlights different distinct relief structures. Also the neighborhood size at which lineament segments are detected correspond with the width of the surface structure and may be a useful additional parameter for further analysis. The discrimination of concave and convex relief structures perfectly matches with valleys and ridges of the surface.

Development of a drought forecasting model for the Asia-Pacific region using remote sensing and climate data: Focusing on Indonesia

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Kim, Gayoung; Im, Jungho

2017-04-01

Three regions of Indonesia with different rainfall characteristics were chosen to develop drought forecast models based on machine learning. The 6-month Standardized Precipitation Index (SPI6) was selected as the target variable. The models' forecast skill was compared to the skill of long-range climate forecast models in terms of drought accuracy and regression mean absolute error (MAE). Indonesian droughts are known to be related to El Nino Southern Oscillation (ENSO) variability despite of regional differences as well as monsoon, local sea surface temperature (SST), other large-scale atmosphere-ocean interactions such as Indian Ocean Dipole (IOD) and Southern Pacific Convergence Zone (SPCZ), and local factors including topography and elevation. Machine learning models are thus to enhance drought forecast skill by combining local and remote SST and remote sensing information reflecting initial drought conditions to the long-range climate forecast model results. A total of 126 machine learning models were developed for the three regions of West Java (JB), West Sumatra (SB), and Gorontalo (GO) and six long-range climate forecast models of MSC_CanCM3, MSC_CanCM4, NCEP, NASA, PNU, POAMA as well as one climatology model based on remote sensing precipitation data, and 1 to 6-month lead times. When compared the results between the machine learning models and the long-range climate forecast models, West Java and Gorontalo regions showed similar characteristics in terms of drought accuracy. Drought accuracy of the long-range climate forecast models were generally higher than the machine learning models with short lead times but the opposite appeared for longer lead times. For West Sumatra, however, the machine learning models and the long-range climate forecast models showed similar drought accuracy. The machine learning models showed smaller regression errors for all three regions especially with longer lead times. Among the three regions, the machine learning models developed for Gorontalo showed the highest drought accuracy and the lowest regression error. West Java showed higher drought accuracy compared to West Sumatra, while West Sumatra showed lower regression error compared to West Java. The lower error in West Sumatra may be because of the smaller sample size used for training and evaluation for the region. Regional differences of forecast skill are determined by the effect of ENSO and the following forecast skill of the long-range climate forecast models. While shown somewhat high in West Sumatra, relative importance of remote sensing variables was mostly low in most cases. High importance of the variables based on long-range climate forecast models indicates that the forecast skill of the machine learning models are mostly determined by the forecast skill of the climate models.

Rainwater harvesting and green area retention potential detection using commercial unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kamnik, Rok; Grajfoner, Blanka; Butyrin, Andrey; Nekrep Perc, Matjaz

2017-10-01

The objective of this work is to use simple photogrammetry to evaluate rainwater harvesting and green area retention potential in Maribor, Slovenia city centre. Several sources of remote sensing data have been described and a field test with semi-professional drone was performed by means of computer evaluation of rainwater harvesting and green area retention potential. Some of the most important design parameters for rainwater harvesting systems as roof area and slope and available green areas were identified and evaluated. The results have shown that even semi-professional low budget drones can be successfully used for mapping areas of interest. The results of six-minute flight over twelve hectares of Maribor city centre were comparable with professional results of plane remote sensing. Image segmentation from orthomosaic together with elevation model has been used to detect roofs and green areas.

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

Developments in remote sensing technology enable more detailed urban flood risk analysis.

NASA Astrophysics Data System (ADS)

Denniss, A.; Tewkesbury, A.

2009-04-01

Spaceborne remote sensors have been allowing us to build up a profile of planet earth for many years. With each new satellite launched we see the capabilities improve: new bands of data, higher resolution imagery, the ability to derive better elevation information. The combination of this geospatial data to create land cover and usage maps, all help inform catastrophe modelling systems. From Landsat 30m resolution to 2.44m QuickBird multispectral imagery; from 1m radar data collected by TerraSAR-X which enables rapid tracking of the rise and fall of a flood event, and will shortly have a twin satellite launched enabling elevation data creation; we are spoilt for choice in available data. However, just what is cost effective? It is always a question of choosing the appropriate level of input data detail for modelling, depending on the value of the risk. In the summer of 2007, the cost of the flooding in the UK was approximately £3bn and affected over 58,000 homes and businesses. When it comes to flood risk, we have traditionally considered rising river levels and surge tides, but with climate change and variations in our own construction behaviour, there are other factors to be taken into account. During those summer 2007 events, the Environment Agency suggested that around 70% of the properties damaged were the result of pluvial flooding, where high localised rainfall events overload localised drainage infrastructure, causing widespread flooding of properties and infrastructure. To create a risk model that is able to simulate such an event requires much more accurate source data than can be provided from satellite or radar. As these flood events cause considerable damage within relatively small, complex urban environments, therefore new high resolution remote sensing techniques have to be applied to better model these events. Detailed terrain data of England and Wales, plus cities in Scotland, have been produced by combining terrain measurements from the latest digital airborne sensors, both optical and lidar, to produce the input layer for surface water flood modelling. A national flood map product has been created. The new product utilises sophisticated modelling techniques, perfected over many years, which harness graphical processing power. This product will prove particularly valuable for risk assessment decision support within insurance/reinsurance, property/environmental, utilities, risk management and government agencies. However, it is not just the ground elevation that determines the behaviour of surface water. By combining height information (surface and terrain) with high resolution aerial photography and colour infrared imagery, a high definition land cover mapping dataset (LandBase) is being produced, which provides a precise measure of sealed versus non sealed surface. This will allows even more sophisticated modelling of flood scenarios. Thus, the value of airborne survey data can be demonstrated by flood risk analysis down to individual addresses in urban areas. However for some risks, an even more detailed survey may be justified. In order to achieve this, Infoterra is testing new 360˚ mobile lidar technology. Collecting lidar data from a moving vehicle allows each street to be mapped in very high detail, allowing precise information about the location, size and shape of features such as kerbstones, gullies, road camber and building threshold level to be captured quickly and accurately. These data can then be used to model the problem of overland flood risk at the scale of individual properties. Whilst at present it might be impractical to undertake such detailed modelling for all properties, these techniques can certainly be used to improve the flood risk analysis of key locations. This paper will demonstrate how these new high resolution remote sensing techniques can be combined to provide a new resolution of detail to aid urban flood modelling.

Increasing precision of turbidity-based suspended sediment concentration and load estimates.

PubMed

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

Dynamic stresses, Coulomb failure, and remote triggering

USGS Publications Warehouse

Hill, D.P.

2008-01-01

Dynamic stresses associated with crustal surface waves with 15-30-sec periods and peak amplitudes 5 km). The latter is consistent with the observation that extensional or transtensional tectonic regimes are more susceptible to remote triggering by Rayleigh-wave dynamic stresses than compressional or transpressional regimes. Locally elevated pore pressures may have a role in the observed prevalence of dynamic triggering in extensional regimes and geothermal/volcanic systems.

[Analysis of vegetation spatial and temporal variations in Qinghai Province based on remote sensing].

PubMed

Wang, Li-wen; Wei, Ya-xing; Niu, Zheng

2008-06-01

1 km MODIS NDVI time series data combining with decision tree classification, supervised classification and unsupervised classification was used to classify land cover type of Qinghai Province into 14 classes. In our classification system, sparse grassland and sparse shrub were emphasized, and their spatial distribution locations were labeled. From digital elevation model (DEM) of Qinghai Province, five elevation belts were achieved, and we utilized geographic information system (GIS) software to analyze vegetation cover variation on different elevation belts. Our research result shows that vegetation cover in Qinghai Province has been improved in recent five years. Vegetation cover area increases from 370047 km2 in 2001 to 374576 km2 in 2006, and vegetation cover rate increases by 0.63%. Among five grade elevation belts, vegetation cover ratio of high mountain belt is the highest (67.92%). The area of middle density grassland in high mountain belt is the largest, of which area is 94 003 km2. Increased area of dense grassland in high mountain belt is the greatest (1280 km2). During five years, the biggest variation is the conversion from sparse grassland to middle density grassland in high mountain belt, of which area is 15931 km2.

Adding Remote Sensing Data Products to the Nutrient Management Decision Support Toolbox

NASA Technical Reports Server (NTRS)

Lehrter, John; Schaeffer, Blake; Hagy, Jim; Spiering, Bruce; Blonski, Slawek; Underwood, Lauren; Ellis, Chris

2011-01-01

Some of the primary issues that manifest from nutrient enrichment and eutrophication (Figure 1) may be observed from satellites. For example, remotely sensed estimates of chlorophyll a (chla), total suspended solids (TSS), and light attenuation (Kd) or water clarity, which are often associated with elevated nutrient inputs, are data products collected daily and globally for coastal systems from satellites such as NASA s MODIS (Figure 2). The objective of this project is to inform water quality decision making activities using remotely sensed water quality data. In particular, we seek to inform the development of numeric nutrient criteria. In this poster we demonstrate an approach for developing nutrient criteria based on remotely sensed chla.

Impact of spatial inhomogeneities on stratospheric species vertical profiles from remote-sensing balloon-borne instruments

NASA Astrophysics Data System (ADS)

Berthet, Gwenael; Renard, Jean-Baptiste; Catoire, Valery; Huret, Nathalie; Lefevre, Franck; Hauchecorne, Alain; Chartier, Michel; Robert, Claude

Remote-sensing balloon observations have recurrently revealed high concentrations of polar stratospheric NO2 in particular in the lower stratosphere as can be seen in various published vertical profiles. A balloon campaign dedicated to the investigation of this problem through comparisons between remote-sensing (SALOMON) and in situ (SPIRALE) measurements of NO2 inside the polar vortex was conducted in January 2006. The published results show unexpected strong enhancements in the slant column densities of NO2 with respect to the elevation angle and displacement of the balloon. These fluctuations result from NO2 spatial inhomogeneities located above the balloon float altitude resulting from mid-latitude air intrusion as revealed by Potential Vorticity (PV) maps. The retrieval of the NO2 vertical profile is subsequently biased in the form of artificial excesses of NO2 concentrations. A direct implication is that the differences previously observed between measurements of NO2 and OClO and model results are probably mostly due to the improper inversion of NO2 in presence of either perturbed dynamical conditions or when mesospheric production events occur as recently highlighted from ENVISAT data. Through the occurrence of such events, we propose to re-examine formerly published high-latitude profiles from the remote-sensing instruments AMON and SALOMON using in parallel PV maps from the MIMOSA advection contour model and the REPROBUS CTM outputs. Mid-latitude profiles of NO2 will also be investigated since they are likely to be biased if presence of air from other latitudes was present at the time of the observations.

Generating High-Resolution Lake Bathymetry over Lake Mead using the ICESat-2 Airborne Simulator

NASA Astrophysics Data System (ADS)

Li, Y.; Gao, H.; Jasinski, M. F.; Zhang, S.; Stoll, J.

2017-12-01

Precise lake bathymetry (i.e., elevation/contour) mapping is essential for optimal decision making in water resources management. Although the advancement of remote sensing has made it possible to monitor global reservoirs from space, most of the existing studies focus on estimating the elevation, area, and storage of reservoirs—and not on estimating the bathymetry. This limitation is attributed to the low spatial resolution of satellite altimeters. With the significant enhancement of ICESat-2—the Ice, Cloud & Land Elevation Satellite #2, which is scheduled to launch in 2018—producing satellite-based bathymetry becomes feasible. Here we present a pilot study for deriving the bathymetry of Lake Mead by combining Landsat area estimations with airborne elevation data using the prototype of ICESat-2—the Multiple Altimeter Beam Experimental Lidar (MABEL). First, an ISODATA classifier was adopted to extract the lake area from Landsat images during the period from 1982 to 2017. Then the lake area classifications were paired with MABEL elevations to establish an Area-Elevation (AE) relationship, which in turn was applied to the classification contour map to obtain the bathymetry. Finally, the Lake Mead bathymetry image was embedded onto the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), to replace the existing constant values. Validation against sediment survey data indicates that the bathymetry derived from this study is reliable. This algorithm has the potential for generating global lake bathymetry when ICESat-2 data become available after next year's launch.

Examination of snowmelt over Western Himalayas using remote sensing data

NASA Astrophysics Data System (ADS)

Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.

2016-07-01

Snowmelt variability in the Western Himalayas has been examined using remotely sensed snow water equivalent (SWE) and snow-covered area (SCA) datasets. It is seen that climatological snowfall and snowmelt amount varies in the Himalayan region from west to east and from month to month. Maximum snowmelt occurs at the elevation zone between 4500 and 5000 m. As the spring and summer approach and snowmelt begins, a large amount of snow melts in May. Strength and weaknesses of temperature-based snowmelt models have been analyzed for this region by computing the snowmelt factor or the degree-day factor (DDF). It is seen that average DDF in the Himalayas is more in April and less in July. During spring and summer months, melting rate is higher in the areas that have height above 2500 m. The region that lies between 4500 and 5000 m elevation zones contributes toward more snowmelt with higher melting rate. Snowmelt models have been developed to estimate interannual variations of monthly snowmelt amount using the DDF, observed SWE, and surface air temperature from reanalysis datasets. In order to further improve the estimate snowmelt, regression between observed and modeled snowmelt has been carried out and revised DDF values have been computed. It is found that both the models do not capture the interannual variability of snowmelt in April. The skill of the model is moderate in May and June, but the skill is relatively better in July. In order to explain this skill, interannual variability (IAV) of surface air temperature has been examined. Compared to July, in April, the IAV of temperature is large indicating that a climatological value of DDF is not sufficient to explain the snowmelt rate in April. Snow area and snow amount depletion curves over Himalayas indicate that in a small area at high altitude, snow is still observed with large SWE whereas over most of the region, all the snow has melted.

Remote sensing and modelling analysis of the extreme dust storm hitting the Middle East and eastern Mediterranean in September 2015

NASA Astrophysics Data System (ADS)

Solomos, Stavros; Ansmann, Albert; Mamouri, Rodanthi-Elisavet; Binietoglou, Ioannis; Patlakas, Platon; Marinou, Eleni; Amiridis, Vassilis

2017-03-01

The extreme dust storm that affected the Middle East and the eastern Mediterranean in September 2015 resulted in record-breaking dust loads over Cyprus with aerosol optical depth exceeding 5.0 at 550 nm. We analyse this event using profiles from the European Aerosol Research Lidar Network (EARLINET) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), geostationary observations from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI), and high-resolution simulations from the Regional Atmospheric Modeling System (RAMS). The analysis of modelling and remote sensing data reveals the main mechanisms that resulted in the generation and persistence of the dust cloud over the Middle East and Cyprus. A combination of meteorological and surface processes is found, including (a) the development of a thermal low in the area of Syria that results in unstable atmospheric conditions and dust mobilization in this area, (b) the convective activity over northern Iraq that triggers the formation of westward-moving haboobs that merge with the previously elevated dust layer, and (c) the changes in land use due to war in the areas of northern Iraq and Syria that enhance dust erodibility.

Synergistic use of an oil drift model and remote sensing observations for oil spill monitoring.

PubMed

De Padova, Diana; Mossa, Michele; Adamo, Maria; De Carolis, Giacomo; Pasquariello, Guido

2017-02-01

In case of oil spills due to disasters, one of the environmental concerns is the oil trajectories and spatial distribution. To meet these new challenges, spill response plans need to be upgraded. An important component of such a plan would be models able to simulate the behaviour of oil in terms of trajectories and spatial distribution, if accidentally released, in deep water. All these models need to be calibrated with independent observations. The aim of the present paper is to demonstrate that significant support to oil slick monitoring can be obtained by the synergistic use of oil drift models and remote sensing observations. Based on transport properties and weathering processes, oil drift models can indeed predict the fate of spilled oil under the action of water current velocity and wind in terms of oil position, concentration and thickness distribution. The oil spill event that occurred on 31 May 2003 in the Baltic Sea offshore the Swedish and Danish coasts is considered a case study with the aim of producing three-dimensional models of sea circulation and oil contaminant transport. The High-Resolution Limited Area Model (HIRLAM) is used for atmospheric forcing. The results of the numerical modelling of current speed and water surface elevation data are validated by measurements carried out in Kalmarsund, Simrishamn and Kungsholmsfort stations over a period of 18 days and 17 h. The oil spill model uses the current field obtained from a circulation model. Near-infrared (NIR) satellite images were compared with numerical simulations. The simulation was able to predict both the oil spill trajectories of the observed slick and thickness distribution. Therefore, this work shows how oil drift modelling and remotely sensed data can provide the right synergy to reproduce the timing and transport of the oil and to get reliable estimates of thicknesses of spilled oil to prepare an emergency plan and to assess the magnitude of risk involved in case of oil spills due to disaster.

a Maximum Entropy Model of the Bearded Capuchin Monkey Habitat Incorporating Topography and Spectral Unmixing Analysis

NASA Astrophysics Data System (ADS)

Howard, A. M.; Bernardes, S.; Nibbelink, N.; Biondi, L.; Presotto, A.; Fragaszy, D. M.; Madden, M.

2012-07-01

Movement patterns of bearded capuchin monkeys (Cebus (Sapajus) libidinosus) in northeastern Brazil are likely impacted by environmental features such as elevation, vegetation density, or vegetation type. Habitat preferences of these monkeys provide insights regarding the impact of environmental features on species ecology and the degree to which they incorporate these features in movement decisions. In order to evaluate environmental features influencing movement patterns and predict areas suitable for movement, we employed a maximum entropy modelling approach, using observation points along capuchin monkey daily routes as species presence points. We combined these presence points with spatial data on important environmental features from remotely sensed data on land cover and topography. A spectral mixing analysis procedure was used to generate fraction images that represent green vegetation, shade and soil of the study area. A Landsat Thematic Mapper scene of the area of study was geometrically and atmospherically corrected and used as input in a Minimum Noise Fraction (MNF) procedure and a linear spectral unmixing approach was used to generate the fraction images. These fraction images and elevation were the environmental layer inputs for our logistic MaxEnt model of capuchin movement. Our models' predictive power (test AUC) was 0.775. Areas of high elevation (>450 m) showed low probabilities of presence, and percent green vegetation was the greatest overall contributor to model AUC. This work has implications for predicting daily movement patterns of capuchins in our field site, as suitability values from our model may relate to habitat preference and facility of movement.

Delineation of the riparian zone in data-scarce regions using fuzzy membership functions: An evaluation based on the case of the Naryn River in Kyrgyzstan

NASA Astrophysics Data System (ADS)

Betz, Florian; Lauermann, Magdalena; Cyffka, Bernd

2018-04-01

Riparian zones contain important ecosystems with a high biodiversity and relevant ecosystem services. From a process point of view, riparian zones are characterized by the interaction of hydrological, geomorphological and ecological processes. Consequently, their boundary is dynamic and blurred as it depends on not only the local valley morphology but also the hydrological regime. This makes a delineation of riparian zones from digital elevation data a challenging task as it should represent this blurred nature of riparian zone boundaries. While the application of high resolution topography from LIDAR and hydraulic models have become standard in many developed countries, studies and applications in remote areas still commonly rely on the freely available coarse resolution digital elevation models. In this article, we present the delineation of riparian zones from the SRTM-1 elevation model and fuzzy membership functions for the Naryn River in Kyrgyzstan having a length of approximately 700 km. We evaluate the extraction of the underlying channel network as well as the different indicator variables. The maximum user's accuracy for the delineation of riparian zones along the entire Naryn River is 82.14% reflecting the uncertainty arising from the heterogeneity of the riverscape as well as from the quality of the underlying elevation data. Despite the uncertainty, the fuzzy membership approach is considered as an appropriate method for riparian zone delineation as it reflects their dynamic, transitional character and can be used as indicator of connectivity within a riverscape.

Effect of winds and waves on salt intrusion in the Pearl River estuary

NASA Astrophysics Data System (ADS)

Gong, Wenping; Lin, Zhongyuan; Chen, Yunzhen; Chen, Zhaoyun; Zhang, Heng

2018-02-01

Salt intrusion in the Pearl River estuary (PRE) is a dynamic process that is influenced by a range of factors and to date, few studies have examined the effects of winds and waves on salt intrusion in the PRE. We investigate these effects using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system applied to the PRE. After careful validation, the model is used for a series of diagnostic simulations. It is revealed that the local wind considerably strengthens the salt intrusion by lowering the water level in the eastern part of the estuary and increasing the bottom landward flow. The remote wind increases the water mixing on the continental shelf, elevates the water level on the shelf and in the PRE and pumps saltier shelf water into the estuary by Ekman transport. Enhancement of the salt intrusion is comparable between the remote and local winds. Waves decrease the salt intrusion by increasing the water mixing. Sensitivity analysis shows that the axial down-estuary wind, is most efficient in driving increases in salt intrusion via wind straining effect.

Linking Arctic plant biodiversity measurements with landscape heterogeneity

NASA Astrophysics Data System (ADS)

Gerber, F.; Schaepman-Strub, G.; Furrer, R.

2016-12-01

Climate warming in the Arctic region triggers changes in the vegetation productivity and species composition of the tundra. To investigate these changes and their feedback to climate, we consider species richness and abundance data of the International Tundra EXperiment (ITEX). As this information is very sparse in time and space, we aim to upscale available records to climatically relevant scales with a remote sensing based characterization of the study sites. More precisely, we relate species richness and evenness derived from the ITEX data to summary statistics describing the landscape heterogeneity, which are derived from an elevation model (ASTER GDEM) and spectral satellite observations (LANDSAT 5 and 7). Preliminary results from the statistical analysis using generalized linear mixed models show that no remote sensing based landscape characterization does significantly explain species richness. Reasons could be a mismatch of the spatial scales, an inappropriate characterization of the test sites through the satellite measurements, incomparable plot measurements from the different test sites and/or too few plot measurements. We are looking forward to presenting our results and getting your inputs.

Multi-Scale Drought Analysis using Thermal Remote Sensing: A Case Study in Georgia’s Altamaha River Watershed

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Bhat, S.; Choi, M.; Mecikalski, J. R.; Anderson, M. C.

2009-12-01

The unprecedented recent droughts in the Southeast US caused reservoir levels to drop dangerously low, elevated wildfire hazard risks, reduced hydropower generation and caused severe economic hardships. Most drought indices are based on recent rainfall or changes in vegetation condition. However in heterogeneous landscapes, soils and vegetation (type and cover) combine to differentially stress regions even under similar weather conditions. This is particularly true for the heterogeneous landscapes and highly variable rainfall in the Southeastern United States. This research examines the spatiotemperal evolution of watershed scale drought using a remotely sensed stress index. Using thermal-infrared imagery, a fully automated inverse model of Atmosphere-Land Exchange (ALEXI), GIS datasets and analysis tools, modeled daily surface moisture stress is examined at a 10-km resolution grid covering central to southern Georgia. Regional results are presented for the 2000-2008 period. The ALEXI evaporative stress index (ESI) is compared to existing regional drought products and validated using local hydrologic measurements in Georgia’s Altamaha River watershed at scales from 10 to 10,000 km2.

New DEMs may stimulate significant advancements in remote sensing of soil moisture

NASA Astrophysics Data System (ADS)

Nolan, Matt; Fatland, Dennis R.

From Napoleon's defeat at Waterloo to increasing corn yields in Kansas to greenhouse gas flux in the Arctic, the importance of soil moisture is endemic to world affairs and merits the considerable attention it receives from the scientific community. This importance can hardly be overstated, though it often goes unstated.Soil moisture is one of the key variables in a variety of broad areas critical to the conduct of societies' economic and political affairs and their well-being; these include the health of agricultural crops, global climate dynamics, military trafficability planning, and hazards such as flooding and forest fires. Unfortunately the in situ measurement of the spatial distribution of soil moisture on a watershed-scale is practically impossible. And despite decades of international effort, a satellite remote sensing technique that can reliably measure soil moisture with a spatial resolution of meters has not yet been identified or implemented. Due to the lack of suitable measurement techniques and, until recently digital elevation models (DEMs), our ability to understand and predict soil moisture dynamics through modeling has largely remained crippled from birth [Grayson and Bloschl, 200l].

Advances in remote sensing of forest background reflectance with MODIS BRDF data across Europe

NASA Astrophysics Data System (ADS)

Pisek, Jan; Alikas, Krista; Lukeš, Petr; Lundin, Lars; Kobler, Johannes; Santos-Reis, Margarida; Chen, Jing

2017-04-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. However, systematic reflectance data covering different site types are almost missing. This presentation will focus on the validation of background reflectance retrievals using MODIS bidirectional reflectance distribution function (BRDF) data against in-situ understory reflectance measurements covering a diverse set of long-term ecological research (LTER) sites distributed along a wide latitudinal and elevational gradient across Europe: protected coniferous blueberry forest in Sweden, karst forest system in Austria, floodplain broadleaf forest and coniferous forest in the Czech Republic, and Mediterranean agro-sylvo-pastoral woodlands in Portugal. The multi-angle remote sensing data-based methodology was originally developed for the forest background signal retrieval in a boreal region. Here its performance will be tested across diverse forest conditions and moments during the growing season, which is a necessary step before conducting extensive mapping over forested areas. The results can be also used as an input for improved modeling of local carbon and energy fluxes.

Environmental factor analysis of cholera in China using remote sensing and geographical information systems.

PubMed

Xu, M; Cao, C X; Wang, D C; Kan, B; Xu, Y F; Ni, X L; Zhu, Z C

2016-04-01

Cholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.

Developing a protocol for long-term population monitoring and habitat projections for a climate-sensitive sentinel species to track ecosystem change and species range shifts

NASA Astrophysics Data System (ADS)

Beers, A.

2016-12-01

As a response to ongoing climate change, many species have started to shift their ranges poleward and toward higher elevations and mountain environments are predicted to experience especially rapid climatic changes. Because of this, there is likely a greater risk of habitat loss and local extinctions for species at high elevations compared to species at lower elevations. Among those potentially threatened habitat specialists is the American pika (Ochotona princeps), a climate sensitive indicator of climate change effects which may already be experiencing climate driven extirpations. Pikas are considered sentinels, indicators of greater ecosystem change. Changes in their distribution speaks to changes in availability of resources they require and shifts in the environment. Pika presence is closely tied to sub-surface ice features that act as a temperature buffer and water source. Those sub-surface ice features are critical in water cycling and long-term water storage and drive downstream hydrological and ecological processes. Understanding how this species responds to climate change therefore provides a model to inform landscape level conservation and management decisions. Pikas may be particularly vulnerable in parts of Colorado, including Rocky Mountain National Park (ROMO) and the Niwot Ridge LTER (NWT), where they may face population collapse as habitat suitability and connectivity both decline in response to various possible climate change scenarios, in large part because of cold stress and declining functional connectivity. Because of their potential role as an ecosystem indicator, their risk for decline, and how limitations to their survival likely vary across their range, management groups can use place based models of habitat suitability for pikas or other sentinel species in designing long term monitoring protocols to detect ecosystem responses to climate change. In this project we used remotely sensed data, occupancy surveys, and a random tessellation stratification to design a protocol for ROMO and NWT that best suits those environments. We also demonstrate the efficacy of habitat models based on remote sensing and their potential application toward tracking ecosystem change and species range shifts.

Historical deposition of mercury and selected trace elements to high-elevation National Parks in the Western U.S. inferred from lake-sediment cores

USGS Publications Warehouse

Mast, M. Alisa; Manthorne, David J.; Roth, David A.

2010-01-01

Atmospheric deposition of Hg and selected trace elements was reconstructed over the past 150 years using sediment cores collected from nine remote, high-elevation lakes in Rocky Mountain National Park in Colorado and Glacier National Park in Montana. Cores were age dated by 210Pb, and sedimentation rates were determined using the constant rate of supply model. Hg concentrations in most of the cores began to increase around 1900, reaching a peak sometime after 1980. Other trace elements, particularly Pb and Cd, showed similar post-industrial increases in lake sediments, confirming that anthropogenic contaminants are reaching remote areas of the Rocky Mountains via atmospheric transport and deposition. Preindustrial (pre-1875) Hg fluxes in the sediment ranged from 5.7 to 42 μg m−2 yr−1 and modern (post-1985) fluxes ranged from 17.7 to 141 μg m−2 yr−1. The average ratio of modern to preindustrial fluxes was 3.2, which is similar to remote lakes elsewhere in North America. Estimates of net atmospheric deposition based on the cores were 3.1 μg m−2 yr−1 for preindustrial and 11.7 μg m−2 yr−1for modern times. Current-day measurements of wet deposition range from 5.0 to 8.6 μg m−2 yr−1, which are lower than the modern sediment-based estimate of 11.7 μg m−2 yr−1, perhaps owing to inputs of dry-deposited Hg to the lakes.

Dynamic stresses, coulomb failure, and remote triggering: corrected

USGS Publications Warehouse

Hill, David P.

2012-01-01

Dynamic stresses associated with crustal surface waves with 15–30 s periods and peak amplitudes <1  MPa are capable of triggering seismicity at sites remote from the generating mainshock under appropriate conditions. Coulomb failure models based on a frictional strength threshold offer one explanation for instances of rapid‐onset triggered seismicity that develop during the surface‐wave peak dynamic stressing. Evaluation of the triggering potential of surface‐wave dynamic stresses acting on critically stressed faults using a Mohr’s circle representation together with the Coulomb failure criteria indicates that Love waves should have a higher triggering potential than Rayleigh waves for most fault orientations and wave incidence angles. That (1) the onset of triggered seismicity often appears to begin during the Rayleigh wave rather than the earlier arriving Love wave, and (2) Love‐wave amplitudes typically exceed those for Rayleigh waves suggests that the explanation for rapid‐onset dynamic triggering may not reside solely with a simple static‐threshold friction mode. The results also indicate that normal faults should be more susceptible to dynamic triggering by 20‐s Rayleigh‐wave stresses than thrust faults in the shallow seismogenic crust (<10  km) while the advantage tips in favor of reverse faults greater depths. This transition depth scales with wavelength and coincides roughly with the transition from retrograde‐to‐prograde particle motion. Locally elevated pore pressures may have a role in the observed prevalence of dynamic triggering in extensional regimes and geothermal/volcanic systems. The result is consistent with the apparent elevated susceptibility of extensional or transtensional tectonic regimes to remote triggering by Rayleigh‐wave dynamic stresses than compressional or transpressional regimes.

Space Station tethered elevator system

NASA Technical Reports Server (NTRS)

Haddock, Michael H.; Anderson, Loren A.; Hosterman, K.; Decresie, E.; Miranda, P.; Hamilton, R.

1989-01-01

The optimized conceptual engineering design of a space station tethered elevator is presented. The tethered elevator is an unmanned, mobile structure which operates on a ten-kilometer tether spanning the distance between Space Station Freedom and a platform. Its capabilities include providing access to residual gravity levels, remote servicing, and transportation to any point along a tether. The report discusses the potential uses, parameters, and evolution of the spacecraft design. Emphasis is placed on the elevator's structural configuration and three major subsystem designs. First, the design of elevator robotics used to aid in elevator operations and tethered experimentation is presented. Second, the design of drive mechanisms used to propel the vehicle is discussed. Third, the design of an onboard self-sufficient power generation and transmission system is addressed.

River discharge estimation from synthetic SWOT-type observations using variational data assimilation and the full Saint-Venant hydraulic model

NASA Astrophysics Data System (ADS)

Oubanas, Hind; Gejadze, Igor; Malaterre, Pierre-Olivier; Mercier, Franck

2018-04-01

The upcoming Surface Water and Ocean Topography satellite mission, to be launched in 2021, will measure river water surface elevation, slope and width, with an unprecedented level of accuracy for a remote sensing tool. This work investigates the river discharge estimation from synthetic SWOT observations, in the presence of strong uncertainties in the model inputs, i.e. the river bathymetry and bed roughness. The estimation problem is solved by a novel variant of the standard variational data assimilation, the '4D-Var' method, involving the full Saint-Venant 1.5D-network hydraulic model SIC2. The assimilation scheme simultaneously estimates the discharge, bed elevation and bed roughness coefficient and is designed to assimilate both satellite and in situ measurements. The method is tested on a 50 km-long reach of the Garonne River during a five-month period of the year 2010, characterized by multiple flooding events. First, the impact of the sampling frequency on discharge estimation is investigated. Secondly, discharge as well as the spatially distributed bed elevation and bed roughness coefficient are determined simultaneously. Results demonstrate feasibility and efficiency of the chosen combination of the estimation method and of the hydraulic model. Assimilation of the SWOT data results into an accurate estimation of the discharge at observation times, and a local improvement in the bed level and bed roughness coefficient. However, the latter estimates are not generally usable for different independent experiments.

Using remote sensing, ecological niche modeling, and Geographic Information Systems for Rift Valley fever risk assessment in the United States

NASA Astrophysics Data System (ADS)

Tedrow, Christine Atkins

The primary goal in this study was to explore remote sensing, ecological niche modeling, and Geographic Information Systems (GIS) as aids in predicting candidate Rift Valley fever (RVF) competent vector abundance and distribution in Virginia, and as means of estimating where risk of establishment in mosquitoes and risk of transmission to human populations would be greatest in Virginia. A second goal in this study was to determine whether the remotely-sensed Normalized Difference Vegetation Index (NDVI) can be used as a proxy variable of local conditions for the development of mosquitoes to predict mosquito species distribution and abundance in Virginia. As part of this study, a mosquito surveillance database was compiled to archive the historical patterns of mosquito species abundance in Virginia. In addition, linkages between mosquito density and local environmental and climatic patterns were spatially and temporally examined. The present study affirms the potential role of remote sensing imagery for species distribution prediction, and it demonstrates that ecological niche modeling is a valuable predictive tool to analyze the distributions of populations. The MaxEnt ecological niche modeling program was used to model predicted ranges for potential RVF competent vectors in Virginia. The MaxEnt model was shown to be robust, and the candidate RVF competent vector predicted distribution map is presented. The Normalized Difference Vegetation Index (NDVI) was found to be the most useful environmental-climatic variable to predict mosquito species distribution and abundance in Virginia. However, these results indicate that a more robust prediction is obtained by including other environmental-climatic factors correlated to mosquito densities (e.g., temperature, precipitation, elevation) with NDVI. The present study demonstrates that remote sensing and GIS can be used with ecological niche and risk modeling methods to estimate risk of virus establishment in mosquitoes and transmission to humans. Maps delineating the geographic areas in Virginia with highest risk for RVF establishment in mosquito populations and RVF disease transmission to human populations were generated in a GIS using human, domestic animal, and white-tailed deer population estimates and the MaxEnt potential RVF competent vector species distribution prediction. The candidate RVF competent vector predicted distribution and RVF risk maps presented in this study can help vector control agencies and public health officials focus Rift Valley fever surveillance efforts in geographic areas with large co-located populations of potential RVF competent vectors and human, domestic animal, and wildlife hosts. Keywords. Rift Valley fever, risk assessment, Ecological Niche Modeling, MaxEnt, Geographic Information System, remote sensing, Pearson's Product-Moment Correlation Coefficient, vectors, mosquito distribution, mosquito density, mosquito surveillance, United States, Virginia, domestic animals, white-tailed deer, ArcGIS

A robust interpolation method for constructing digital elevation models from remote sensing data

NASA Astrophysics Data System (ADS)

Chen, Chuanfa; Liu, Fengying; Li, Yanyan; Yan, Changqing; Liu, Guolin

2016-09-01

A digital elevation model (DEM) derived from remote sensing data often suffers from outliers due to various reasons such as the physical limitation of sensors and low contrast of terrain textures. In order to reduce the effect of outliers on DEM construction, a robust algorithm of multiquadric (MQ) methodology based on M-estimators (MQ-M) was proposed. MQ-M adopts an adaptive weight function with three-parts. The weight function is null for large errors, one for small errors and quadric for others. A mathematical surface was employed to comparatively analyze the robustness of MQ-M, and its performance was compared with those of the classical MQ and a recently developed robust MQ method based on least absolute deviation (MQ-L). Numerical tests show that MQ-M is comparative to the classical MQ and superior to MQ-L when sample points follow normal and Laplace distributions, and under the presence of outliers the former is more accurate than the latter. A real-world example of DEM construction using stereo images indicates that compared with the classical interpolation methods, such as natural neighbor (NN), ordinary kriging (OK), ANUDEM, MQ-L and MQ, MQ-M has a better ability of preserving subtle terrain features. MQ-M replaces thin plate spline for reference DEM construction to assess the contribution to our recently developed multiresolution hierarchical classification method (MHC). Classifying the 15 groups of benchmark datasets provided by the ISPRS Commission demonstrates that MQ-M-based MHC is more accurate than MQ-L-based and TPS-based MHCs. MQ-M has high potential for DEM construction.

Combining points and lines in rectifying satellite images

NASA Astrophysics Data System (ADS)

Elaksher, Ahmed F.

2017-09-01

The quick advance in remote sensing technologies established the potential to gather accurate and reliable information about the Earth surface using high resolution satellite images. Remote sensing satellite images of less than one-meter pixel size are currently used in large-scale mapping. Rigorous photogrammetric equations are usually used to describe the relationship between the image coordinates and ground coordinates. These equations require the knowledge of the exterior and interior orientation parameters of the image that might not be available. On the other hand, the parallel projection transformation could be used to represent the mathematical relationship between the image-space and objectspace coordinate systems and provides the required accuracy for large-scale mapping using fewer ground control features. This article investigates the differences between point-based and line-based parallel projection transformation models in rectifying satellite images with different resolutions. The point-based parallel projection transformation model and its extended form are presented and the corresponding line-based forms are developed. Results showed that the RMS computed using the point- or line-based transformation models are equivalent and satisfy the requirement for large-scale mapping. The differences between the transformation parameters computed using the point- and line-based transformation models are insignificant. The results showed high correlation between the differences in the ground elevation and the RMS.

Mapping geomorphic process domains to predict hillslope sediment size distribution using remotely-sensed data and field sampling, Inyo Creek, California

NASA Astrophysics Data System (ADS)

Leclere, S.; Sklar, L. S.; Genetti, J. R.

2014-12-01

The size distribution of sediments produced on hillslopes and supplied to channels depends on the geomorphic processes that weather, detach and transport rock fragments down slopes. Little in the way of theory or data is available to predict patterns in hillslope size distributions at the catchment scale from topographic and geologic maps. Here we use aerial imagery and a variety of remote sensing techniques to map and categorize geomorphic landscape units (GLUs) by inferred sediment production process regime, across the steep mountain catchment of Inyo Creek, eastern Sierra Nevada, California. We also use field measurements of particle size and local geomorphic attributes to test and refine GLU determinations. Across the 2 km of relief in this catchment, landcover varies from bare bedrock cliffs at higher elevations to vegetated, regolith-covered convex slopes at lower elevations. Hillslope gradient could provide a simple index of sediment production process, from rock spallation and landsliding at highest slopes, to tree-throw and other disturbance-driven soil production processes at lowest slopes. However, many other attributes are needed for a more robust predictive model, including elevation, curvature, aspect, drainage area, and color. We combine tools from ArcGIS, ERDAS Imagine and Envi with groundtruthing field work to find an optimal combination of attributes for defining sediment production GLUs. Key challenges include distinguishing: weathered from freshly eroded bedrock, boulders from intact bedrock, and landslide deposits from talus slopes. We take advantage of emerging technologies that provide new ways of conducting fieldwork and comparing field data to mapping solutions. In particular, cellphone GPS is approaching the accuracy of dedicated GPS systems and the ability to geo-reference photos simplifies field notes and increases accuracy of later map creation. However, the predictive power of the GLU mapping approach is limited by inherent uncertainty in remotely sensed data and aerial imagery. This work is a contribution toward the long-term goal of reliable and automated mapping of hillslope sediment size distributions for use in sediment budgets and hazard delineation, and for understanding the feedbacks between climate, erosion and topography that drive sediment production.

Digital elevation model of King Edward VII Peninsula, West Antarctica, from SAR interferometry and ICESat laser altimetry

USGS Publications Warehouse

Baek, S.; Kwoun, Oh-Ig; Braun, Andreas; Lu, Z.; Shum, C.K.

2005-01-01

We present a digital elevation model (DEM) of King Edward VII Peninsula, Sulzberger Bay, West Antarctica, developed using 12 European Remote Sensing (ERS) synthetic aperture radar (SAR) scenes and 24 Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles. We employ differential interferograms from the ERS tandem mission SAR scenes acquired in the austral fall of 1996, and four selected ICESat laser altimetry profiles acquired in the austral fall of 2004, as ground control points (GCPs) to construct an improved geocentric 60-m resolution DEM over the grounded ice region. We then extend the DEM to include two ice shelves using ICESat profiles via Kriging. Twenty additional ICESat profiles acquired in 2003-2004 are used to assess the accuracy of the DEM. After accounting for radar penetration depth and predicted surface changes, including effects due to ice mass balance, solid Earth tides, and glacial isostatic adjustment, in part to account for the eight-year data acquisition discrepancy, the resulting difference between the DEM and ICESat profiles is -0.57 ?? 5.88 m. After removing the discrepancy between the DEM and ICESat profiles for a final combined DEM using a bicubic spline, the overall difference is 0.05 ?? 1.35 m. ?? 2005 IEEE.

Geomorphic and climate influences on soil organic carbon concentration at large catchment scales

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Martinez, C.; Wells, T.; Dever, C.; Willgoose, G. R.; Bissett, A.

2013-12-01

Soils represent the largest terrestrial sink of carbon on Earth. Managing the soil organic carbon (SOC) pool is becoming increasingly important in light of growing concerns over global food security and the climatic effects of anthropogenic CO2 emissions. The development of accurate predictive SOC models are an important step for both land resource managers and policy makers alike. Presently, a number of SOC models are available which incorporate environmental data to produce SOC estimates. The accuracy of these models varies significantly over a range of landscapes due to the highly complex nature of SOC dynamics. Fundamental gaps exist in our understanding of SOC controls. To date, studies of SOC controls, and the subsequent models derived from their findings have focussed mainly on North American and European landscapes. Additionally, SOC studies often focus on the paddock to small catchment scale. Consequently, information about SOC in Australian landscapes and at the larger scale is limited. This study examines controls over SOC across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia. The aim was to develop a predictive model for use across a range of catchment sizes and climate. Here it was found that elevation (derived from DEMs) and vegetation (above ground biomass quantified by remote sensing were the primary controls of SOC. SOC was seen to increase with elevation and NDVI. This relationship is believed to be a reflection of rainfall patterns across the study area and plant growth potential. Further, a relationship was observed between SOC and the environmental tracer 137Cs which suggests that SOC and 137Cs move through catchment via similar sediment transport mechanisms. Therefore loss of SOC by erosion and gain by deposition may be necessary to be accounted for in any SOC budget. Model validation indicated that the use of simple linear relationships could predict SOC based on rainfall and vegetation (above ground biomass as quantified by remote sensing). The results suggest that simple landscape and climate models have the potential to predict the spatial distribution of SOC. The findings of this study emphasise the importance of tailoring SOC models to the appropriate scale.

A Historical Forcing Ice Sheet Model Validation Framework for Greenland

NASA Astrophysics Data System (ADS)

Price, S. F.; Hoffman, M. J.; Howat, I. M.; Bonin, J. A.; Chambers, D. P.; Kalashnikova, I.; Neumann, T.; Nowicki, S.; Perego, M.; Salinger, A.

2014-12-01

We propose an ice sheet model testing and validation framework for Greenland for the years 2000 to the present. Following Perego et al. (2014), we start with a realistic ice sheet initial condition that is in quasi-equilibrium with climate forcing from the late 1990's. This initial condition is integrated forward in time while simultaneously applying (1) surface mass balance forcing (van Angelen et al., 2013) and (2) outlet glacier flux anomalies, defined using a new dataset of Greenland outlet glacier flux for the past decade (Enderlin et al., 2014). Modeled rates of mass and elevation change are compared directly to remote sensing observations obtained from GRACE and ICESat. Here, we present a detailed description of the proposed validation framework including the ice sheet model and model forcing approach, the model-to-observation comparison process, and initial results comparing model output and observations for the time period 2000-2013.

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management

NASA Astrophysics Data System (ADS)

Reyes-Gonzalez, Arturo

Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently. Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to an atmometer for ETa estimation has not yet been attempted in eastern South Dakota. The results showed a good relationship between ETa estimated by the METRIC model and estimated with atmometer (r2 = 0.87 and RMSE = 0.65 mm day-1). However, ETa values from atmometer were consistently lower than ET a values from METRIC. The verification of remotely sensed estimates of surface variables is essential for any remote-sensing study. The relationships between LAI, Ts, and ETa estimated using the remote sensing-based METRIC model and in-situ measurements were established. The results showed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m -2, Ts had r2 = 0.87 and RMSE 1.24 °C and ETa presented r2= 0.89 and RMSE = 0.71 mm day -1. Estimation of ETa using energy balance method can be challenging and time consuming. Thus, there is a need to develop a simple and fast method to estimate ETa using minimum input parameters. Two methods were used, namely 1) an energy balance method (EB method) that used input parameters of the Landsat image, weather data, a digital elevation map, and a land cover map and 2) a Kc-NDVI method that use two input parameters: the Landsat image and weather data. A strong relationship was found between the two methods with r2 of 0.97 and RMSE of 0.37 mm day -1. Hence, the Kc-NDVI method performed well for ET a estimations, indicating that Kc-NDVI method can be a robust and reliable method to estimate ETa in a short period of time. Estimation of crop evapotranspiration (ETc) using satellite remote sensing-based vegetation index such as the Normalized Difference Vegetation Index (NDVI). The NDVI was calculated using near-infrared and red wavebands. The relationship between NDVI and tabulated Kc's was used to generate Kc maps. ETc maps were developed as an output of Kc maps multiplied by reference evapotranspiration (ETr). Daily ETc maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ETc maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water use at regional and field scales.

Exploring remote operation for ALMA Observatory

NASA Astrophysics Data System (ADS)

Shen, Tzu-Chiang; Soto, Ruben; Ovando, Nicolás.; Velez, Gaston; Fuica, Soledad; Schemrl, Anton; Robles, Andres; Ibsen, Jorge; Filippi, Giorgio; Pietriga, Emmanuel

2014-08-01

The Atacama Large Millimeter /submillimeter Array (ALMA) will be a unique research instrument composed of at least 66 reconfigurable high-precision antennas, located at the Chajnantor plain in the Chilean Andes at an elevation of 5000 m. The observatory has another office located in Santiago of Chile, 1600 km from the Chajnantor plain. In the Atacama desert, the wonderful observing conditions imply precarious living conditions and extremely high operation costs: i.e: flight tickets, hospitality, infrastructure, water, electricity, etc. It is clear that a purely remote operational model is impossible, but we believe that a mixture of remote and local operation scheme would be beneficial to the observatory, not only in reducing the cost but also in increasing the observatory overall efficiency. This paper describes the challenges and experience gained in such experimental proof of the concept. The experiment was performed over the existing 100 Mbps bandwidth, which connects both sites through a third party telecommunication infrastructure. During the experiment, all of the existent capacities of the observing software were validated successfully, although room for improvement was clearly detected. Network virtualization, MPLS configuration, L2TPv3 tunneling, NFS adjustment, operational workstations design are part of the experiment.

Tropical Rain Forest Structure, Tree Growth and Dynamics along a 2700-m Elevational Transect in Costa Rica

PubMed Central

Clark, David B.; Hurtado, Johanna; Saatchi, Sassan S.

2015-01-01

Rapid biological changes are expected to occur on tropical elevational gradients as species migrate upslope or go extinct in the face of global warming. We established a series of 9 1-ha plots in old-growth tropical rainforest in Costa Rica along a 2700 m relief elevational gradient to carry out long-term monitoring of tropical rain forest structure, dynamics and tree growth. Within each plot we mapped, identified, and annually measured diameter for all woody individuals with stem diameters >10 cm for periods of 3-10 years. Wood species diversity peaked at 400-600 m and decreased substantially at higher elevations. Basal area and stem number varied by less than two-fold, with the exception of the 2800 m cloud forest summit, where basal area and stem number were approximately double that of lower sites. Canopy gaps extending to the forest floor accounted for <3% of microsites at all elevations. Height of highest crowns and the coefficient of variation of crown height both decreased with increasing elevation. Rates of turnover of individuals and of stand basal area decreased with elevation, but rates of diameter growth and stand basal area showed no simple relation to elevation. We discuss issues encountered in the design and implementation of this network of plots, including biased sampling, missing key meteorological and biomass data, and strategies for improving species-level research. Taking full advantage of the major research potential of tropical forest elevational transects will require sustaining and extending ground based studies, incorporation of new remotely-sensed data and data-acquisition platforms, and new funding models to support decadal research on these rapidly-changing systems. PMID:25856163

Remotely-sensed near real-time monitoring of reservoir storage in India

NASA Astrophysics Data System (ADS)

Tiwari, A. D.; Mishra, V.

2017-12-01

Real-time reservoir storage information at a high temporal resolution is crucial to mitigate the influence of extreme events like floods and droughts. Despite large implications of near real-time reservoir monitoring in India for water resources and irrigation, remotely sensed monitoring systems have been lacking. Here we develop remotely sensed real-time monitoring systems for 91 large reservoirs in India for the period from 2000 to 2017. For the reservoir storage estimation, we combined Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day 250 m Enhanced Vegetation Index (EVI), and Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) ICESat/GLAS elevation data. Vegetation data with the highest temporal resolution available from the MODIS is at 16 days. To increase the temporal resolution to 8 days, we developed the 8-day composite of near infrared, red, and blue band surface reflectance. Surface reflectance 8-Day L3 Global 250m only have NIR band and Red band, therefore, surface reflectance of 8-Day L3 Global at 500m is used for the blue band, which was regridded to 250m spatial resolution. An area-elevation relationship was derived using area from an unsupervised classification of MODIS image followed by an image enhancement and elevation data from ICESat/GLAS. A trial and error method was used to obtain the area-elevation relationship for those reservoirs for which ICESat/GLAS data is not available. The reservoir storages results were compared with the gauge storage data from 2002 to 2009 (training period), which were then evaluated for the period of 2010 to 2016. Our storage estimates were highly correlated with observations (R2 = 0.6 to 0.96), and the normalized root mean square error (NRMSE) ranged between 10% and 50%. We also developed a relationship between precipitation and reservoir storage that can be used for prediction of storage during the dry season.

Ground-Truthing of Airborne LiDAR Using RTK-GPS Surveyed Data in Coastal Louisiana's Wetlands

NASA Astrophysics Data System (ADS)

Lauve, R. M.; Alizad, K.; Hagen, S. C.

2017-12-01

Airborne LiDAR (Light Detection and Ranging) data are used by engineers and scientists to create bare earth digital elevation models (DEM), which are essential to modeling complex coastal, ecological, and hydrological systems. However, acquiring accurate bare earth elevations in coastal wetlands is difficult due to the density of marsh grasses that prevent the sensors reflection off the true ground surface. Previous work by Medeiros et al. [2015] developed a technique to assess LiDAR error and adjust elevations according to marsh vegetation density and index. The aim of this study is the collection of ground truth points and the investigation on the range of potential errors found in existing LiDAR datasets within coastal Louisiana's wetlands. Survey grids were mapped out in an area dominated by Spartina alterniflora and a survey-grade Trimble Real Time Kinematic (RTK) GPS device was employed to measure bare earth ground elevations in the marsh system adjacent to Terrebonne Bay, LA. Elevations were obtained for 20 meter-spaced surveyed grid points and were used to generate a DEM. The comparison between LiDAR derived and surveyed data DEMs yield an average difference of 23 cm with a maximum difference of 68 cm. Considering the local tidal range of 45 cm, these differences can introduce substantial error when the DEM is used for ecological modeling [Alizad et al., 2016]. Results from this study will be further analyzed and implemented in order to adjust LiDAR-derived DEMs closer to their true elevation across Louisiana's coastal wetlands. ReferencesAlizad, K., S. C. Hagen, J. T. Morris, S. C. Medeiros, M. V. Bilskie, and J. F. Weishampel (2016), Coastal wetland response to sea-level rise in a fluvial estuarine system, Earth's Future, 4(11), 483-497, 10.1002/2016EF000385. Medeiros, S., S. Hagen, J. Weishampel, and J. Angelo (2015), Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density, Remote Sensing, 7(4), 3507-3525, 10.3390/rs70403507.

Long-term remote organ consequences following acute kidney injury.

PubMed

Shiao, Chih-Chung; Wu, Pei-Chen; Huang, Tao-Min; Lai, Tai-Shuan; Yang, Wei-Shun; Wu, Che-Hsiung; Lai, Chun-Fu; Wu, Vin-Cent; Chu, Tzong-Shinn; Wu, Kwan-Dun

2015-12-28

Acute kidney injury (AKI) has been a global health epidemic problem with soaring incidence, increased long-term risks for multiple comorbidities and mortality, as well as elevated medical costs. Despite the improvement of patient outcomes following the advancements in preventive and therapeutic strategies, the mortality rates among critically ill patients with AKI remain as high as 40-60 %. The distant organ injury, a direct consequence of deleterious systemic effects, following AKI is an important explanation for this phenomenon. To date, most evidence of remote organ injury in AKI is obtained from animal models. Whereas the observations in humans are from a limited number of participants in a relatively short follow-up period, or just focusing on the cytokine levels rather than clinical solid outcomes. The remote organ injury is caused with four underlying mechanisms: (1) "classical" pattern of acute uremic state; (2) inflammatory nature of the injured kidneys; (3) modulating effect of AKI of the underlying disease process; and (4) healthcare dilemma. While cytokines/chemokines, leukocyte extravasation, oxidative stress, and certain channel dysregulation are the pathways involving in the remote organ damage. In the current review, we summarized the data from experimental studies to clinical outcome studies in the field of organ crosstalk following AKI. Further, the long-term consequences of distant organ-system, including liver, heart, brain, lung, gut, bone, immune system, and malignancy following AKI with temporary dialysis were reviewed and discussed.

Classification of permafrost active layer depth from remotely sensed and topographic evidence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peddle, D.R.; Franklin, S.E.

1993-04-01

The remote detection of permafrost (perennially frozen ground) has important implications to environmental resource development, engineering studies, natural hazard prediction, and climate change research. In this study, the authors present results from two experiments into the classification of permafrost active layer depth within the zone of discontinuous permafrost in northern Canada. A new software system based on evidential reasoning was implemented to permit the integrated classification of multisource data consisting of landcover, terrain aspect, and equivalent latitude, each of which possessed different formats, data types, or statistical properties that could not be handled by conventional classification algorithms available to thismore » study. In the first experiment, four active layer depth classes were classified using ground based measurements of the three variables with an accuracy of 83% compared to in situ soil probe determination of permafrost active layer depth at over 500 field sites. This confirmed the environmental significance of the variables selected, and provided a baseline result to which a remote sensing classification could be compared. In the second experiment, evidence for each input variable was obtained from image processing of digital SPOT imagery and a photogrammetric digital elevation model, and used to classify active layer depth with an accuracy of 79%. These results suggest the classification of evidence from remotely sensed measures of spectral response and topography may provide suitable indicators of permafrost active layer depth.« less

Using terrestrial laser scanning for differential measurement of interannual rock glacier movement in the Argentine Dry Andes

NASA Astrophysics Data System (ADS)

Kane, Renato R.

Argentina has recently implemented laws to protect glaciers and buried ice in the Andes to improve the sustainability of scarce, long-term water resources. Therefore, all glaciers and buried ice terrains must be located and avoided in any commercial alterations of the landscape. Buried ice in this remote and often dangerous terrain typically is located via the use of remote-sensing techniques. This thesis applies one such technique, Light Detection and Ranging (LiDAR) in the form of Terrestrial Laser Scanning (TLS), to detect rock glacier movement that is indicative of flowing, buried ice not visible in near surface excavations. TLS surveys were completed at two locales, Los Azules and El Altar, in both AD 2013 and AD 2014 on landscapes where buried ice is suspected to have produced the current surface forms. Multiple TLS scans were co-registered with the use of benchmarks, both between scans and between years, which introduced quantifiable positional errors. Digital Elevation Models (DEMs) were derived from the point cloud data by standardizing the spacing of the points in the horizontal direction, creating 0.1 m by 0.1 m cells with elevation as the cell value. The DEMs for each year were subtracted from each other to yield a change in elevation. The surface roughness of the rock glaciers (vertical variability within each cell) was empirically determined and evaluated as a threshold for results. Both sites showed sub-decimeter interannual movements, and the direction of their movement is typical of forms with buried ice. The results of the study were validated using independent GPS data showing annual movement rates. Despite the downslope movement of these rock glaciers, the volume of ice contained within them remains unclear, and further study is required to assess the volume of water contained.

Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests

USGS Publications Warehouse

Elmore, A.J.; Guinn, S.M.; Minsley, B.J.; Richardson, A.D.

2012-01-01

The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field-based and remote-sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium-resolution remote sensing data, organized by day of year, to explore the influence of climate-related landscape factors on the timing of spring and autumn leaf-area trajectories in mid-Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape-scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.

Assessment of Acacia koa forest health across environmental gradients in Hawai'i using fine resolution remote sensing and GIS.

PubMed

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai'ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600-1,000 m asl in the island of Kaua'i, which correspond to gradients of temperature and rainfall ranging from 17-20 °C mean annual temperature and 750-1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai'i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species.

NORTH SECTION OF WEST ELEVATION OF MAIN PROCESSING BUILDING (CPP601) ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

NORTH SECTION OF WEST ELEVATION OF MAIN PROCESSING BUILDING (CPP-601) LOOKING EAST. HOT PILOT PLANT BUILDING (CPP-640) APPEARS IN RIGHT OF PHOTO. THE REMOTE ANALYTICAL FACILITY (CPP-627) WAS LOCATED ON CONCRETE PAD IN FOREGROUND. INL PHOTO NUMBER HD-54-33-3. Mike Crane, Photographer, 7/2006 - Idaho National Engineering Laboratory, Idaho Chemical Processing Plant, Fuel Reprocessing Complex, Scoville, Butte County, ID

Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China

PubMed Central

Wei, Lan; Qian, Quan; Wang, Zhi-Qiang; Glass, Gregory E.; Song, Shao-Xia; Zhang, Wen-Yi; Li, Xiu-Jun; Yang, Hong; Wang, Xian-Jun; Fang, Li-Qun; Cao, Wu-Chun

2011-01-01

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. PMID:21363991

Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity

NASA Astrophysics Data System (ADS)

Holmes, Keith Richard

Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.

Tracking greenhouse gas emissions from a U.S. megacity by remote sensing from a mountaintop site

NASA Astrophysics Data System (ADS)

Wong, Clare; Fu, Dejian; Pongetti, Thomas; Newman, Sally; Kort, Eric; Duren, Riley; Hsu, Ying-Kuang; Miller, Charles; Yung, Yuk; Sander, Stanley

2014-05-01

Cities, such as Los Angeles, are significant sources of anthropogenic greenhouse gases (GHGs). With the growth of populations in cities worldwide, GHG emissions will increase, and monitoring the temporal trends will provide crucial data for global climate models as well as assessments of the effectiveness of control policies. Currently, continuous GHG observations in the Los Angeles basin are limited to a few in situ measurements, which are shown to be sensitive to local emissions and do not represent the Los Angeles basin well. To quantify GHG emissions from the metropolitan area, which tend to have heterogeneous characteristics, it is important to perform measurements which provide both continuous temporal and spatial coverage of the domain. Here we present observations of the major greenhouse gases, CO2 and CH4, using a spectroscopic remote sensing technique from the California Laboratory for Atmospheric Remote Sensing (CLARS) at Mount Wilson, California (1.7 km elevation). A Fourier Transform Spectrometer (FTS) deployed at the CLARS site points downward at 28 selected land surfaces in the LA basin to measure the slant column abundances of CO2, CH4, N2¬O, CO and O2 using reflected sunlight in the near-infrared and short-wave infrared regions. This remote sensing technique provides continuous temporal and spatial measurements in the Los Angeles basin to achieve the goal of quantifying emissions of GHGs and CO. It also serves as a test-bed for future geostationary satellite missions to measure GHGs from space such as NASA JPL's Geostationary Carbon Process Investigation (GCPI). The path-averaged dry-air mixing ratio, XCO2 and XCH4, observed by the CLARS FTS, showed significant diurnal variability that arises from emissions in the Los Angeles basin and atmospheric transport processes. High-precision data have been collected since August 2011. We analyze the seasonal trends of the ratio XCH4:XCO2 and estimate the seasonal and annual CH4 emission in the Los Angeles basin observed by the CLARS FTS from August 2011 to present. This work demonstrates the ability to quantify and track GHG emissions in a megacity using ground-based remote sensing from an elevated platform and the potential for future geostationary satellite missions, such as GCPI, to monitor carbon fluxes in cities. Copyright 2014. California Institute of Technology. Government sponsorship acknowledged.

Remote sensing of trend and seasonal variability of greenhouse gas emissions from the Los Angeles basin using an FTS on Mount Wilson

NASA Astrophysics Data System (ADS)

Wong, C.; Fu, D.; Pongetti, T. J.; Newman, S.; Yung, Y. L.; Sander, S. P.

2013-12-01

Cities, such as Los Angeles, are significant sources of anthropogenic greenhouse gases (GHGs). With the growth of populations in cities worldwide, GHG emissions will increase, and monitoring the temporal trends will provide crucial data for global climate models as well as assessments of the effectiveness of control policies. Currently, continuous GHG observations in the Los Angeles basin are limited to a few in situ measurements, which are shown to be sensitive to local emissions and do not represent the Los Angeles basin well. To quantify GHG emissions from the metropolitan area, which tend to have heterogeneous characteristics, it is important to perform measurements which provide both continuous temporal and spatial coverage of the domain. Here we present observations of the major greenhouse gases, CO2 and CH4, using a spectroscopic remote sensing technique from the California Laboratory for Atmospheric Remote Sensing (CLARS) at Mount Wilson, California (1.7 km elevation). A Fourier Transform Spectrometer (FTS) deployed at the CLARS site points downward at 28 selected land surfaces in the Los Angeles basin to measure the slant column abundances of CO2, CH4, N2O, CO and O2 using reflected sunlight in the near-infrared and shortwave infrared regions. This remote sensing technique provides continuous temporal and spatial measurements in the Los Angeles basin to achieve the goal of quantifying emissions of GHGs and CO. It also serves as a test-bed for future geostationary satellite missions to measure GHGs from space such as JPL's Geostationary Carbon Process Investigation (GCPI). The path-averaged dry-air mixing ratio, XCO2 and XCH4, observed by the CLARS FTS, show significant diurnal variability that arises from emissions in the Los Angeles basin and atmospheric transport processes. High-precision data have been collected since August 2011. Here we analyze the annual and seasonal trend of the ratio XCH4:XCO2 in the Los Angeles basin observed by the CLARS FTS from August 2011 to present. This work demonstrates the ability to quantify and track GHG emissions in a megacity using ground-based remote sensing from an elevated platform and the potential for future geostationary satellite missions, such as GCPI, to monitor carbon fluxes in cities.

Dissecting the contribution of knee joint NGF to spinal nociceptive sensitization in a model of OA pain in the rat

PubMed Central

Sagar, D.R.; Nwosu, L.; Walsh, D.A.; Chapman, V.

2015-01-01

Summary Objective Although analgesic approaches targeting nerve growth factor (NGF) for the treatment of osteoarthritis (OA) pain remain of clinical interest, neurophysiological mechanisms by which NGF contribute to OA pain remain unclear. We investigated the impact of local elevation of knee joint NGF on knee joint, vs remote (hindpaw), evoked responses of spinal neurones in a rodent model of OA pain. Design In vivo spinal electrophysiology was carried out in anaesthetised rats with established pain behaviour and joint pathology following intra-articular injection of monosodium iodoacetate (MIA), vs injection of saline. Neuronal responses to knee joint extension and flexion, mechanical punctate stimulation of the peripheral receptive fields over the knee and at a remote site (ipsilateral hind paw) were studied before, and following, intra-articular injection of NGF (10 μg/50 μl) or saline. Results MIA-injected rats exhibited significant local (knee joint) and remote (lowered hindpaw withdrawal thresholds) changes in pain behaviour, and joint pathology. Intra-articular injection of NGF significantly (P < 0.05) increased knee extension-evoked firing of spinal neurones and the size of the peripheral receptive fields of spinal neurones (100% increase) over the knee joint in MIA rats, compared to controls. Intra-articular NGF injection did not significantly alter responses of spinal neurones following noxious stimulation of the ipsilateral hind paw in MIA-injected rats. Conclusion The facilitatory effects of intra-articular injection of NGF on spinal neurones receiving input from the knee joint provide a mechanistic basis for NGF mediated augmentation of OA knee pain, however additional mechanisms may contribute to the spread of pain to remote sites. PMID:25623624

Dissecting the contribution of knee joint NGF to spinal nociceptive sensitization in a model of OA pain in the rat.

PubMed

Sagar, D R; Nwosu, L; Walsh, D A; Chapman, V

2015-06-01

Although analgesic approaches targeting nerve growth factor (NGF) for the treatment of osteoarthritis (OA) pain remain of clinical interest, neurophysiological mechanisms by which NGF contribute to OA pain remain unclear. We investigated the impact of local elevation of knee joint NGF on knee joint, vs remote (hindpaw), evoked responses of spinal neurones in a rodent model of OA pain. In vivo spinal electrophysiology was carried out in anaesthetised rats with established pain behaviour and joint pathology following intra-articular injection of monosodium iodoacetate (MIA), vs injection of saline. Neuronal responses to knee joint extension and flexion, mechanical punctate stimulation of the peripheral receptive fields over the knee and at a remote site (ipsilateral hind paw) were studied before, and following, intra-articular injection of NGF (10 μg/50 μl) or saline. MIA-injected rats exhibited significant local (knee joint) and remote (lowered hindpaw withdrawal thresholds) changes in pain behaviour, and joint pathology. Intra-articular injection of NGF significantly (P < 0.05) increased knee extension-evoked firing of spinal neurones and the size of the peripheral receptive fields of spinal neurones (100% increase) over the knee joint in MIA rats, compared to controls. Intra-articular NGF injection did not significantly alter responses of spinal neurones following noxious stimulation of the ipsilateral hind paw in MIA-injected rats. The facilitatory effects of intra-articular injection of NGF on spinal neurones receiving input from the knee joint provide a mechanistic basis for NGF mediated augmentation of OA knee pain, however additional mechanisms may contribute to the spread of pain to remote sites. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling study of sea breezes in a complex coastal environment

NASA Astrophysics Data System (ADS)

Cai, X.-M.; Steyn, D. G.

This study investigates a mesoscale modelling of sea breezes blowing from a narrow strait into the lower Fraser valley (LFV), British Columbia, Canada, during the period of 17-20 July, 1985. Without a nudging scheme in the inner grid, the CSU-RAMS model produces satisfactory wind and temperature fields during the daytime. In comparison with observation, the agreement indices for surface wind and temperature during daytime reach about 0.6 and 0.95, respectively, while the agreement indices drop to 0.4 at night. In the vertical, profiles of modelled wind and temperature generally agree with tethersonde data collected on 17 and 19 July. The study demonstrates that in late afternoon, the model does not capture the advection of an elevated warm layer which originated from land surfaces outside of the inner grid. Mixed layer depth (MLD) is calculated from model output of turbulent kinetic energy field. Comparison of MLD results with observation shows that the method generates a reliable MLD during the daytime, and that accurate estimates of MLD near the coast require the correct simulation of wind conditions over the sea. The study has shown that for a complex coast environment like the LFV, a reliable modelling study depends not only on local surface fluxes but also on elevated layers transported from remote land surfaces. This dependence is especially important when local forcings are weak, for example, during late afternoon and at night.

Gravitational spreading of Danu, Freyja and Maxwell Montes, Venus

NASA Astrophysics Data System (ADS)

Smrekar, Suzanne E.; Solomon, Sean C.

1991-06-01

The potential energy of elevated terrain tends to drive the collapse of the topography. This process of gravitational spreading is likely to be more important on Venus than on Earth because the higher surface temperature weakens the crust. The highest topography on Venus is Ishtar Terra. The high plateau of Lakshmi Planum has an average elevation of 3 km above mean planetary radius, and is surrounded by mountain belts. Freyja, Danu, and Maxwell Montes rise, on average, an additional 3, 0.5, and 5 km above the plateau, respectively. Recent high resolution Magellan radar images of this area, east of approx. 330 deg E, reveal widespread evidence for gravity spreading. Some observational evidence is described for gravity spreading and the implications are discussed in terms of simple mechanical models. Several simple models predict that gravity spreading should be an important process on Venus. One difficulty in using remote observations to infer interior properties is that the observed features may not have formed in response to stresses which are still active. Several causes of surface topography are briefly examined.

Remote sensing for industrial applications in the energy business: digital territorial data integration for planning of overhead power transmission lines (OHTLs)

NASA Astrophysics Data System (ADS)

Terrazzino, Alfonso; Volponi, Silvia; Borgogno Mondino, Enrico

2001-12-01

An investigation has been carried out, concerning remote sensing techniques, in order to assess their potential application to the energy system business: the most interesting results concern a new approach, based on digital data from remote sensing, to infrastructures with a large territorial distribution: in particular OverHead Transmission Lines, for the high voltage transmission and distribution of electricity on large distances. Remote sensing could in principle be applied to all the phases of the system lifetime, from planning to design, to construction, management, monitoring and maintenance. In this article, a remote sensing based approach is presented, targeted to the line planning: optimization of OHTLs path and layout, according to different parameters (technical, environmental and industrial). Planning new OHTLs is of particular interest in emerging markets, where typically the cartography is missing or available only on low accuracy scale (1:50.000 and lower), often not updated. Multi- spectral images can be used to generate thematic maps of the region of interest for the planning (soil coverage). Digital Elevation Models (DEMs), allow the planners to easily access the morphologic information of the surface. Other auxiliary information from local laws, environmental instances, international (IEC) standards can be integrated in order to perform an accurate optimized path choice and preliminary spotting of the OHTLs. This operation is carried out by an ABB proprietary optimization algorithm: the output is a preliminary path that bests fits the optimization parameters of the line in a life cycle approach.

Some technical notes on using UAV-based remote sensing for post disaster assessment

NASA Astrophysics Data System (ADS)

Rokhmana, Catur Aries; Andaru, Ruli

2017-07-01

Indonesia is located in an area prone to disasters, which are various kinds of natural disasters happen. In disaster management, the geoinformation data are needed to be able to evaluate the impact area. The UAV (Unmanned Aerial Vehicle)-Based remote sensing technology is a good choice to produce a high spatial resolution of less than 15 cm, while the current resolution of the satellite imagery is still greater than 50 cm. This paper shows some technical notes that should be considered when using UAV-Based remote sensing system in post disaster for rapid assessment. Some cases are Aceh Earthquake in years 2013 for seeing infrastructure damages, Banjarnegara landslide in year 2014 for seeing the impact; and Kelud volcano eruption in year 2014 for seeing the impact and volumetric material calculation. The UAV-Based remote sensing system should be able to produce the Orthophoto image that can provide capabilities for visual interpretation the individual damage objects, and the changes situation. Meanwhile the DEM (digital Elevation model) product can derive terrain topography, and volumetric calculation with accuracy 3-5 pixel or sub-meter also. The UAV platform should be able for working remotely and autonomously in dangerous area and limited infrastructures. In mountainous or volcano area, an unconventional flight plan should implemented. Unfortunately, not all impact can be seen from above such as wall crack, some parcel boundaries, and many objects that covered by others higher object. The previous existing geoinformation data are also needed to be able to evaluate the change detection automatically.

Developing a flood monitoring system from remotely sensed data for the Limpopo basin

USGS Publications Warehouse

Asante, K.O.; Macuacua, R.D.; Artan, G.A.; Lietzow, R.W.; Verdin, J.P.

2007-01-01

This paper describes the application of remotely sensed precipitation to the monitoring of floods in a region that regularly experiences extreme precipitation and flood events, often associated with cyclonic systems. Precipitation data, which are derived from spaceborne radar aboard the National Aeronautics and Space Administration's Tropical Rainfall Measuring Mission and from National Oceanic and Atmospheric Administration's infrared-based products, are used to monitor areas experiencing extreme precipitation events that are defined as exceedance of a daily mean areal average value of 50 mm over a catchment. The remotely sensed precipitation data are also ingested into a hydrologic model that is parameterized using spatially distributed elevation, soil, and land cover data sets that are available globally from remote sensing and in situ sources. The resulting stream-flow is classified as an extreme flood event when flow anomalies exceed 1.5 standard deviations above the short-term mean. In an application in the Limpopo basin, it is demonstrated that the use of satellite-derived precipitation allows for the identification of extreme precipitation and flood events, both in terms of relative intensity and spatial extent. The system is used by water authorities in Mozambique to proactively initiate independent flood hazard verification before generating flood warnings. The system also serves as a supplementary information source when in situ gauging systems are disrupted. This paper concludes that remotely sensed precipitation and derived products greatly enhance the ability of water managers in the Limpopo basin to monitor extreme flood events and provide at-risk communities with early warning information. ?? 2007 IEEE.

Mud deposit formation on the open coast of the larger Patos Lagoon-Cassino Beach system

NASA Astrophysics Data System (ADS)

Vinzon, S. B.; Winterwerp, J. C.; Nogueira, R.; de Boer, G. J.

2009-03-01

This paper proposes an explanation of the mud deposits on the inner Shelf of Cassino Beach, South Brazil, by using computational modeling. These mud deposits are mainly formed by sediments delivered from Patos Lagoon, a coastal lagoon connected to the Shelf, next to Cassino Beach. The deposits are characterized by (soft) mud layers of about 1 m thick and are found between the -5 and -20 isobaths. Two hydrodynamic models of the larger Patos Lagoon-Cassino Beach system were calibrated against water elevation measured for a 5 months period, and against currents and salinity measured for a week period. The circulation patterns and water exchange through the mouth were analyzed as a function of local and remote wind effects, and river discharges. The remote wind effect mainly governs the quantity of water exchange with the Lagoon through its effect on mean sea level as a result of Ekman dynamics, while river discharges are important for the salinity of the exchanged water masses. Local winds augment the export-import rates by set-up and set-down within the Lagoon, but their effects are much smaller than those of the remote wind. Currents patterns on the inner Shelf during water outflow revealed a recirculation zone south of the Lagoon, induced by the local geometry and bathymetry of the system. This recirculation zone coincides with observed locations of mud deposition. Water, hence suspended sediment export occurs when remote and local winds are from the N-E, which explains why fine sediment deposits are mainly found south of the Lagoon's breakwater. A sensitivity analysis with the numerical model quantified the contribution of the various mechanisms driving the transport and fate of the fine suspended sediments, i.e. the effects of remote and local wind, of the astronomical tide, of river discharge and fresh-salt water-induced density currents, and of earth rotation. It is concluded that gravitational circulation and earth rotation affects the further dispersion of the deposits largely, whereas the remote wind effect has the largest influence on the amount of sediment released from the Lagoon. It is noted that this paper analyzes the initial deposition patterns induced by current effects only. However, in reality, these deposits are further redistributed over the Shelf by wave effects—these are subject of a next study on the sediment dynamics of the larger Patos Lagoon-Cassino Beach system.

Ecohydrologic process modeling of mountain block groundwater recharge.

PubMed

Magruder, Ian A; Woessner, William W; Running, Steve W

2009-01-01

Regional mountain block recharge (MBR) is a key component of alluvial basin aquifer systems typical of the western United States. Yet neither water scientists nor resource managers have a commonly available and reasonably invoked quantitative method to constrain MBR rates. Recent advances in landscape-scale ecohydrologic process modeling offer the possibility that meteorological data and land surface physical and vegetative conditions can be used to generate estimates of MBR. A water balance was generated for a temperate 24,600-ha mountain watershed, elevation 1565 to 3207 m, using the ecosystem process model Biome-BGC (BioGeochemical Cycles) (Running and Hunt 1993). Input data included remotely sensed landscape information and climate data generated with the Mountain Climate Simulator (MT-CLIM) (Running et al. 1987). Estimated mean annual MBR flux into the crystalline bedrock terrain is 99,000 m(3) /d, or approximately 19% of annual precipitation for the 2003 water year. Controls on MBR predictions include evapotranspiration (radiation limited in wet years and moisture limited in dry years), soil properties, vegetative ecotones (significant at lower elevations), and snowmelt (dominant recharge process). The ecohydrologic model is also used to investigate how climatic and vegetative controls influence recharge dynamics within three elevation zones. The ecohydrologic model proves useful for investigating controls on recharge to mountain blocks as a function of climate and vegetation. Future efforts will need to investigate the uncertainty in the modeled water balance by incorporating an advanced understanding of mountain recharge processes, an ability to simulate those processes at varying scales, and independent approaches to calibrating MBR estimates. Copyright © 2009 The Author(s). Journal compilation © 2009 National Ground Water Association.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PubMed

Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

Optimal link budget to maximize data receiving from remote sensing satellite at different ground stations

NASA Astrophysics Data System (ADS)

Godse, Vinay V.; Rukmini, B.

2016-10-01

Earth observation satellite plays a significant role for global situation awareness. The earth observation satellite uses imaging payloads in RF and IR bands, which carry huge amount of data, needs to be transferred during visibility of satellite over the ground station. Location of ground station plays a very important role in communication with LEO satellites, as orbital speed of LEO satellite is much higher than earth rotation speed. It will be accessible for particular equatorial ground station for a very short duration. In this paper we want to maximize data receiving by optimizing link budget and receiving data at higher elevation links. Data receiving at multiple ground stations is preferred to counter less pass duration due to higher elevation links. Our approach is to calculate link budget for remote sensing satellite with a fixed power input and varying different minimum elevation angles to obtain maximum data. The minimum pass duration should be above 3 minutes for effective communication. We are proposing to start process of command handling as soon as satellite is visible to particular ground station with low elevation angle up to 5 degree and start receiving data at higher elevation angles to receive data with higher speed. Cartosat-2B LEO earth observation satellite is taken for the case study. Cartosat-2B will complete around 14 passes over equator in a day, out of which only 4-5 passes will be useful for near equator ground stations. Our aim is to receive data at higher elevation angles at higher speed and increase amount of data download, criteria being minimum pass duration of 3 minutes, which has been set for selecting minimum elevation angle.

Shoreline Erosion and Slope Failure Detection over Southwest Lakeshore Michigan using Temporal Radar and Digital Elevation Model

NASA Astrophysics Data System (ADS)

Sataer, G.; Sultan, M.; Yellich, J. A.; Becker, R.; Emil, M. K.; Palaseanu, M.

2017-12-01

Throughout the 20th century and into the 21st century, significant losses of residential, commercial and governmental property were reported along the shores of the Great Lakes region due to one or more of the following factors: high lake levels, wave actions, groundwater discharge. A collaborative effort (Western Michigan University, University of Toledo, Michigan Geological Survey [MGS], United States Geological Survey [USGS], National Oceanographic and Atmospheric Administration [NOAA]) is underway to examine the temporal topographic variations along the shoreline and the adjacent bluff extending from the City of South Haven in the south to the City of Saugatuck in the north within the Allegan County. Our objectives include two main tasks: (1) identification of the timing of, and the areas, witnessing slope failure and shoreline erosion, and (2) investigating the factors causing the observed failures and erosion. This is being accomplished over the study area by: (1) detecting and measuring slope subsidence rates (velocities along line of site) and failures using radar interferometric persistent scatter (PS) techniques applied to ESA's European Remote Sensing (ERS) satellites, ERS-1 and -2 (spatial resolution: 25 m) that were acquired in 1995 to 2007, (2) extracting temporal high resolution (20 cm) digital elevation models (DEM) for the study area from temporal imagery acquired by Unmanned Aerial Vehicles (UAVs), and applying change detection techniques to the extracted DEMs, (3) detecting change in elevation and slope profiles extracted from two LIDAR Coastal National Elevation Database (CoNED) DEMs (spatial resolution: 0.5m), acquired on 2008 and 2012, and (4) spatial and temporal correlation of the detected changes in elevation with relevant data sets (e.g., lake levels, precipitation, groundwater levels) in search of causal effects.

Remote radio control of insect flight.

PubMed

Sato, Hirotaka; Berry, Christopher W; Peeri, Yoav; Baghoomian, Emen; Casey, Brendan E; Lavella, Gabriel; Vandenbrooks, John M; Harrison, Jon F; Maharbiz, Michel M

2009-01-01

We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.

Forest canopy height estimation using double-frequency repeat pass interferometry

NASA Astrophysics Data System (ADS)

Karamvasis, Kleanthis; Karathanassi, Vassilia

2015-06-01

In recent years, many efforts have been made in order to assess forest stand parameters from remote sensing data, as a mean to estimate the above-ground carbon stock of forests in the context of the Kyoto protocol. Synthetic aperture radar interferometry (InSAR) techniques have gained traction in last decade as a viable technology for vegetation parameter estimation. Many works have shown that forest canopy height, which is a critical parameter for quantifying the terrestrial carbon cycle, can be estimated with InSAR. However, research is still needed to understand further the interaction of SAR signals with forest canopy and to develop an operational method for forestry applications. This work discusses the use of repeat pass interferometry with ALOS PALSAR (L band) HH polarized and COSMO Skymed (X band) HH polarized acquisitions over the Taxiarchis forest (Chalkidiki, Greece), in order to produce accurate digital elevation models (DEMs) and estimate canopy height with interferometric processing. The effect of wavelength-dependent penetration depth into the canopy is known to be strong, and could potentially lead to forest canopy height mapping using dual-wavelength SAR interferometry at X- and L-band. The method is based on scattering phase center separation at different wavelengths. It involves the generation of a terrain elevation model underneath the forest canopy from repeat-pass L-band InSAR data as well as the generation of a canopy surface elevation model from repeat pass X-band InSAR data. The terrain model is then used to remove the terrain component from the repeat pass interferometric X-band elevation model, so as to enable the forest canopy height estimation. The canopy height results were compared to a field survey with 6.9 m root mean square error (RMSE). The effects of vegetation characteristics, SAR incidence angle and view geometry, and terrain slope on the accuracy of the results have also been studied in this work.

Quantitative Morphometric Analysis of Terrestrial Glacial Valleys and the Application to Mars

NASA Astrophysics Data System (ADS)

Allred, Kory

Although the current climate on Mars is very cold and dry, it is generally accepted that the past environments on the planet were very different. Paleo-environments may have been warm and wet with oceans and rivers. And there is abundant evidence of water ice and glaciers on the surface as well. However, much of that comes from visual interpretation of imagery and other remote sensing data. For example, some of the characteristics that have been utilized to distinguish glacial forms are the presence of landscape features that appear similar to terrestrial glacial landforms, constraining surrounding topography, evidence of flow, orientation, elevation and valley shape. The main purpose of this dissertation is to develop a model that uses quantitative variables extracted from elevation data that can accurately categorize a valley basin as either glacial or non-glacial. The application of this model will limit the inherent subjectivity of image analysis by human interpretation. The model developed uses hypsometric attributes (elevation-area relationship), a newly defined variable similar to the equilibrium line altitude for an alpine glacier, and two neighborhood search functions intended to describe the valley cross-sectional curvature, all based on a digital elevation model (DEM) of a region. The classification model uses data-mining techniques trained on several terrestrial mountain ranges in varied geologic and geographic settings. It was applied to a select set of previously catalogued locations on Mars that resemble terrestrial glaciers. The results suggest that the landforms do have a glacial origin, thus supporting much of the previous research that has identified the glacial landforms. This implies that the paleo-environment of Mars was at least episodically cold and wet, probably during a period of increased planetary obliquity. Furthermore, the results of this research and the implications thereof add to the body of knowledge for the current and past Martian environments, which could inform future decisions for further scientific investigation and exploration of Mars, including landing sites selection and even human habitation.

A numerical study of tropospheric ozone in the springtime in East Asia

NASA Astrophysics Data System (ADS)

Zhang, Meigen; Xu, Yongfu; Itsushi, Uno; Hajime, Akimoto

2004-04-01

The Models-3 Community Multi-scale Air Quality modeling system (CMAQ) coupled with the Regional Atmospheric Modeling System (RAMS) is applied to East Asia to study the transport and photochemical transformation of tropospheric ozone in March 1998. The calculated mixing ratios of ozone and carbon monoxide are compared with ground level observations at three remote sites in Japan and it is found that the model reproduces the observed features very well. Examination of several high episodes of ozone and carbon monoxide indicates that these elevated levels are found in association with continental outflow, demonstrating the critical role of the rapid transport of carbon monoxide and other ozone precursors from the continental boundary layer. In comparison with available ozonesonde data, it is found that the model-calculated ozone concentrations are generally in good agreement with the measurements, and the stratospheric contribution to surface ozone mixing ratios is quite limited.

Tree growth and vegetation activity at the ecosystem-scale in the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Coulthard, Bethany L.; Touchan, Ramzi; Anchukaitis, Kevin J.; Meko, David M.; Sivrikaya, Fatih

2017-08-01

Linking annual tree growth with remotely-sensed terrestrial vegetation indices provides a basis for using tree rings as proxies for ecosystem primary productivity over large spatial and long temporal scales. In contrast with most previous tree ring/remote sensing studies that have focused on temperature-limited boreal and taiga environments, here we compare the normalized difference vegetation index (NDVI) with a network of Pinus brutia tree ring width chronologies collected along ecological gradients in semiarid Cyprus, where both radial tree growth and broader vegetation activity are controlled by drought. We find that the interaction between precipitation, elevation, and land-cover type generate a relationship between radial tree growth and NDVI. While tree ring chronologies at higher-elevation forested sites do not exhibit climate-driven linkages with NDVI, chronologies at lower-elevation dry sites are strongly correlated with NDVI during the winter precipitation season. At lower-elevation sites, land cover is dominated by grasslands and shrublands and tree ring widths operate as a proxy for ecosystem-scale vegetation activity. Tree rings can therefore be used to reconstruct productivity in water-limited grasslands and shrublands, where future drought stress is expected to alter the global carbon cycle, biodiversity, and ecosystem functioning in the 21st century.

Scaling approach of terrestrial carbon cycle over Alaska's black spruce forests: a synthesis of field observation, remote sensing, and ecosystem modeling

NASA Astrophysics Data System (ADS)

Ueyama, M.; Date, T.; Harazono, Y.; Ichii, K.

2007-12-01

Spatio-temporal scale up of the eddy covariance data is an important challenge especially in the northern high latitude ecosystems, since continuous ground observations are rarely conducted. In this study, we measured the carbon fluxes at a black spruce forest in interior Alaska, and then scale up the eddy covariance data to spatio- temporal variations in regional carbon budget by using satellite remote sensing data and a process based ecosystem model, Biome-BGC. At point scale, both satellite-based empirical model and Biome-BGC could reproduce seasonal and interannual variations in GPP/RE/NEE. The magnitude of GPP/RE is also consistent among the models. However, spatial patterns in GPP/RE are something different among the models; high productivity in low elevation area is estimated by the satellite-based model whereas insignificant relationship is simulated by Biome-BGC. Long- term satellite records, AVHRR and MODIS, show the gradual decline of NDVI in Alaska's black spruce forests between 1981 and 2006, resulting in a general trend of decreasing GPP/RE for Alaska's black spruce forests. These trends are consistent with the Biome-BGC simulation. The trend of carbon budget is also consistent among the models, where the carbon budget of black spruce forests did not significantly change in the period. The simulated results suggest that the carbon fluxes in black spruce forests could be more sensitive to water availability than air temperature.

Multisource Data Classification Using A Hybrid Semi-supervised Learning Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju; Bhaduri, Budhendra L; Shekhar, Shashi

2009-01-01

In many practical situations thematic classes can not be discriminated by spectral measurements alone. Often one needs additional features such as population density, road density, wetlands, elevation, soil types, etc. which are discrete attributes. On the other hand remote sensing image features are continuous attributes. Finding a suitable statistical model and estimation of parameters is a challenging task in multisource (e.g., discrete and continuous attributes) data classification. In this paper we present a semi-supervised learning method by assuming that the samples were generated by a mixture model, where each component could be either a continuous or discrete distribution. Overall classificationmore » accuracy of the proposed method is improved by 12% in our initial experiments.« less

Hookworm Infection and Environmental Factors in Mbeya Region, Tanzania: A Cross-Sectional, Population-Based Study

PubMed Central

Riess, Helene; Clowes, Petra; Kroidl, Inge; Kowuor, Dickens O.; Nsojo, Anthony; Mangu, Chacha; Schüle, Steffen A.; Mansmann, Ulrich; Geldmacher, Christof; Mhina, Seif; Maboko, Leonard; Hoelscher, Michael; Saathoff, Elmar

2013-01-01

Background Hookworm disease is one of the most common infections and cause of a high disease burden in the tropics and subtropics. Remotely sensed ecological data and model-based geostatistics have been used recently to identify areas in need for hookworm control. Methodology Cross-sectional interview data and stool samples from 6,375 participants from nine different sites in Mbeya region, south-western Tanzania, were collected as part of a cohort study. Hookworm infection was assessed by microscopy of duplicate Kato-Katz thick smears from one stool sample from each participant. A geographic information system was used to obtain remotely sensed environmental data such as land surface temperature (LST), vegetation cover, rainfall, and elevation, and combine them with hookworm infection data and with socio-demographic and behavioral data. Uni- and multivariable logistic regression was performed on sites separately and on the pooled dataset. Principal Findings Univariable analyses yielded significant associations for all ecological variables. Five ecological variables stayed significant in the final multivariable model: population density (odds ratio (OR) = 0.68; 95% confidence interval (CI) = 0.63–0.73), mean annual vegetation density (OR = 0.11; 95% CI = 0.06–0.18), mean annual LST during the day (OR = 0.81; 95% CI = 0.75–0.88), mean annual LST during the night (OR = 1.54; 95% CI = 1.44–1.64), and latrine coverage in household surroundings (OR = 1.02; 95% CI = 1.01–1.04). Interaction terms revealed substantial differences in associations of hookworm infection with population density, mean annual enhanced vegetation index, and latrine coverage between the two sites with the highest prevalence of infection. Conclusion/Significance This study supports previous findings that remotely sensed data such as vegetation indices, LST, and elevation are strongly associated with hookworm prevalence. However, the results indicate that the influence of environmental conditions can differ substantially within a relatively small geographic area. The use of large-scale associations as a predictive tool on smaller scales is therefore problematic and should be handled with care. PMID:24040430

Ecological Sensitivity Evaluation of Tourist Region Based on Remote Sensing Image - Taking Chaohu Lake Area as a Case Study

NASA Astrophysics Data System (ADS)

Lin, Y.; Li, W. J.; Yu, J.; Wu, C. Z.

2018-04-01

Remote sensing technology is of significant advantages for monitoring and analysing ecological environment. By using of automatic extraction algorithm, various environmental resources information of tourist region can be obtained from remote sensing imagery. Combining with GIS spatial analysis and landscape pattern analysis, relevant environmental information can be quantitatively analysed and interpreted. In this study, taking the Chaohu Lake Basin as an example, Landsat-8 multi-spectral satellite image of October 2015 was applied. Integrated the automatic ELM (Extreme Learning Machine) classification results with the data of digital elevation model and slope information, human disturbance degree, land use degree, primary productivity, landscape evenness , vegetation coverage, DEM, slope and normalized water body index were used as the evaluation factors to construct the eco-sensitivity evaluation index based on AHP and overlay analysis. According to the value of eco-sensitivity evaluation index, by using of GIS technique of equal interval reclassification, the Chaohu Lake area was divided into four grades: very sensitive area, sensitive area, sub-sensitive areas and insensitive areas. The results of the eco-sensitivity analysis shows: the area of the very sensitive area was 4577.4378 km2, accounting for about 37.12 %, the sensitive area was 5130.0522 km2, accounting for about 37.12 %; the area of sub-sensitive area was 3729.9312 km2, accounting for 26.99 %; the area of insensitive area was 382.4399 km2, accounting for about 2.77 %. At the same time, it has been found that there were spatial differences in ecological sensitivity of the Chaohu Lake basin. The most sensitive areas were mainly located in the areas with high elevation and large terrain gradient. Insensitive areas were mainly distributed in slope of the slow platform area; the sensitive areas and the sub-sensitive areas were mainly agricultural land and woodland. Through the eco-sensitivity analysis of the study area, the automatic recognition and analysis techniques for remote sensing imagery are integrated into the ecological analysis and ecological regional planning, which can provide a reliable scientific basis for rational planning and regional sustainable development of the Chaohu Lake tourist area.

Linking occupancy surveys with habitat characteristics to estimate abundance and distribution in an endangered cryptic bird

USGS Publications Warehouse

Crampton, Lisa H.; Brinck, Kevin W.; Pias, Kyle E.; Heindl, Barbara A. P.; Savre, Thomas; Diegmann, Julia S.; Paxton, Eben H.

2017-01-01

Accurate estimates of the distribution and abundance of endangered species are crucial to determine their status and plan recovery options, but such estimates are often difficult to obtain for species with low detection probabilities or that occur in inaccessible habitats. The Puaiohi (Myadestes palmeri) is a cryptic species endemic to Kauaʻi, Hawai‘i, and restricted to high elevation ravines that are largely inaccessible. To improve current population estimates, we developed an approach to model distribution and abundance of Puaiohi across their range by linking occupancy surveys to habitat characteristics, territory density, and landscape attributes. Occupancy per station ranged from 0.17 to 0.82, and was best predicted by the number and vertical extent of cliffs, cliff slope, stream width, and elevation. To link occupancy estimates with abundance, we used territory mapping data to estimate the average number of territories per survey station (0.44 and 0.66 territories per station in low and high occupancy streams, respectively), and the average number of individuals per territory (1.9). We then modeled Puaiohi occupancy as a function of two remote-sensed measures of habitat (stream sinuosity and elevation) to predict occupancy across its entire range. We combined predicted occupancy with estimates of birds per station to produce a global population estimate of 494 (95% CI 414–580) individuals. Our approach is a model for using multiple independent sources of information to accurately track population trends, and we discuss future directions for modeling abundance of this, and other, rare species.

Multiscale Framework for Assessing Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Wilderness Areas of the Western United States

NASA Astrophysics Data System (ADS)

Nanus, Leora; Clow, David; Saros, Jasmine; McMurray, Jill; Blett, Tamara; Sickman, James

2017-04-01

High-elevation aquatic ecosystems in Wilderness areas of the western United States are impacted by current and historic atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. A predictive framework was developed for sensitive high-elevation basins across the western United States at multiple spatial scales including the Rocky Mountain Region (Rockies), the Greater Yellowstone Area (GYA), and Yosemite (YOSE) and Sequoia & Kings Canyon (SEKI) National Parks. Spatial trends in critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with modeled N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed for better quantification of uncertainty and identification of areas most sensitive to high atmospheric N deposition (> 3 kg N ha-1 yr-1). For multiple spatial scales, the lowest critical loads estimates (<1.5 + 1 kg N ha-1 yr-1) occurred in high-elevation basins with steep slopes, sparse vegetation, and exposed bedrock and talus. Based on a nitrate threshold of 1 μmol L-1, estimated critical load exceedances (>1.5 + 1 kg N ha-1 yr-1) correspond with areas of high N deposition and vary spatially ranging from less than 20% to over 40% of the study area for the Rockies, GYA, YOSE, and SEKI. These predictive models and maps identify sensitive aquatic ecosystems that may be impacted by excess atmospheric N deposition and can be used to help protect against future anthropogenic disturbance. The approach presented here may be transferable to other remote and protected high-elevation ecosystems at multiple spatial scales that are sensitive to adverse effects of pollutant loading in the US and around the world.

Highlights: US Commercial Remote Sensing Industry Analysis

NASA Technical Reports Server (NTRS)

Rabin, Ron

2002-01-01

This viewgraph presentation profiles the US remote sensing industry based on responses to a survey by 1450 industry professionals. The presentation divides the industry into three sectors: academic, commercial, and government; the survey results from each are covered in a section of the presentation. The presentation also divides survey results on user needs into the following sectors: spatial resolution, geolocation accuracy; elevation accuracy, area coverage, imagery types, and timeliness. Data, information, and software characteristics are also covered in the presentation.

Modular radiochemistry synthesis system

DOEpatents

Satyamurthy, Nagichettiar; Barrio, Jorge R.; Amarasekera, Bernard; Van Dam, Michael R.; Olma, Sebastian; Williams, Dirk; Eddings, Mark; Shen, Clifton Kwang-Fu

2016-11-01

A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

Modular radiochemistry synthesis system

DOEpatents

Satyamurthy, Nagichettiar; Barrio, Jorge R.; Amarasekera, Bernard; Van Dam, R. Michael; Olma, Sebastian; Williams, Dirk; Eddings, Mark; Shen, Clifton Kwang-Fu

2015-12-15

A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

Modular radiochemistry synthesis system

DOEpatents

Satyamurthy, Nagichettiar; Barrio, Jorge R; Amarasekera, Bernard; Van Dam, R. Michael; Olma, Sebastian; Williams, Dirk; Eddings, Mark A; Shen, Clifton Kwang-Fu

2015-02-10

A modular chemical production system includes multiple modules for performing a chemical reaction, particularly of radiochemical compounds, from a remote location. One embodiment comprises a reaction vessel including a moveable heat source with the position thereof relative to the reaction vessel being controllable from a remote position. Alternatively the heat source may be fixed in location and the reaction vial is moveable into and out of the heat source. The reaction vessel has one or more sealing plugs, the positioning of which in relationship to the reaction vessel is controllable from a remote position. Also the one or more reaction vessel sealing plugs can include one or more conduits there through for delivery of reactants, gases at atmospheric or an elevated pressure, inert gases, drawing a vacuum and removal of reaction end products to and from the reaction vial, the reaction vial with sealing plug in position being operable at elevated pressures. The modular chemical production system is assembled from modules which can each include operating condition sensors and controllers configured for monitoring and controlling the individual modules and the assembled system from a remote position. Other modules include, but are not limited to a Reagent Storage and Delivery Module, a Cartridge Purification Module, a Microwave Reaction Module, an External QC/Analysis/Purification Interface Module, an Aliquotting Module, an F-18 Drying Module, a Concentration Module, a Radiation Counting Module, and a Capillary Reactor Module.

Seismic hazard assessment of Syria using seismicity, DEM, slope, active tectonic and GIS

NASA Astrophysics Data System (ADS)

Ahmad, Raed; Adris, Ahmad; Singh, Ramesh

2016-07-01

In the present work, we discuss the use of an integrated remote sensing and Geographical Information System (GIS) techniques for evaluation of seismic hazard areas in Syria. The present study is the first time effort to create seismic hazard map with the help of GIS. In the proposed approach, we have used Aster satellite data, digital elevation data (30 m resolution), earthquake data, and active tectonic maps. Many important factors for evaluation of seismic hazard were identified and corresponding thematic data layers (past earthquake epicenters, active faults, digital elevation model, and slope) were generated. A numerical rating scheme has been developed for spatial data analysis using GIS to identify ranking of parameters to be included in the evaluation of seismic hazard. The resulting earthquake potential map delineates the area into different relative susceptibility classes: high, moderate, low and very low. The potential earthquake map was validated by correlating the obtained different classes with the local probability that produced using conventional analysis of observed earthquakes. Using earthquake data of Syria and the peak ground acceleration (PGA) data is introduced to the model to develop final seismic hazard map based on Gutenberg-Richter (a and b values) parameters and using the concepts of local probability and recurrence time. The application of the proposed technique in Syrian region indicates that this method provides good estimate of seismic hazard map compared to those developed from traditional techniques (Deterministic (DSHA) and probabilistic seismic hazard (PSHA). For the first time we have used numerous parameters using remote sensing and GIS in preparation of seismic hazard map which is found to be very realistic.

Automated identification of potential snow avalanche release areas based on digital elevation models

NASA Astrophysics Data System (ADS)

Bühler, Y.; Kumar, S.; Veitinger, J.; Christen, M.; Stoffel, A.; Snehmani

2013-05-01

The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.

Modeling the Distribution of African Savanna Elephants in Kruger National Park: AN Application of Multi-Scale GLOBELAND30 Data

NASA Astrophysics Data System (ADS)

Xu, W.; Hays, B.; Fayrer-Hosken, R.; Presotto, A.

2016-06-01

The ability of remote sensing to represent ecologically relevant features at multiple spatial scales makes it a powerful tool for studying wildlife distributions. Species of varying sizes perceive and interact with their environment at differing scales; therefore, it is important to consider the role of spatial resolution of remotely sensed data in the creation of distribution models. The release of the Globeland30 land cover classification in 2014, with its 30 m resolution, presents the opportunity to do precisely that. We created a series of Maximum Entropy distribution models for African savanna elephants (Loxodonta africana) using Globeland30 data analyzed at varying resolutions. We compared these with similarly re-sampled models created from the European Space Agency's Global Land Cover Map (Globcover). These data, in combination with GIS layers of topography and distance to roads, human activity, and water, as well as elephant GPS collar data, were used with MaxEnt software to produce the final distribution models. The AUC (Area Under the Curve) scores indicated that the models created from 600 m data performed better than other spatial resolutions and that the Globeland30 models generally performed better than the Globcover models. Additionally, elevation and distance to rivers seemed to be the most important variables in our models. Our results demonstrate that Globeland30 is a valid alternative to the well-established Globcover for creating wildlife distribution models. It may even be superior for applications which require higher spatial resolution and less nuanced classifications.

Estimation of Forest Biomass Based on Muliti-Source Remote Sensing Data Set - a Case Study of Shangri-La County

NASA Astrophysics Data System (ADS)

Feng, Wanwan; Wang, Leiguang; Xie, Junfeng; Yue, Cairong; Zheng, Yalan; Yu, Longhua

2018-04-01

Forest biomass is an important indicator for the structure and function of forest ecosystems, and an accurate assessment of forest biomass is crucial for understanding ecosystem changes. Remote sensing has been widely used for inversion of biomass. However, in mature or over-mature forest areas, spectral saturation is prone to occur. Based on existing research, this paper synthesizes domestic high resolution satellites, ZY3-01 satellites, and GLAS14-level data from space-borne Lidar system, and other data set. Extracting texture and elevation features respectively, for the inversion of forest biomass. This experiment takes Shangri-La as the research area. Firstly, the biomass in the laser spot was calculated based on GLAS data and other auxiliary data, DEM, the second type inventory of forest resources data and the Shangri-La vector boundary data. Then, the regression model was established, that is, the relationship between the texture factors of ZY3-01 and biomass in the laser spot. Finally, by using this model and the forest distribution map in Shangri-La, the biomass of the whole area is obtained, which is 1.3972 × 108t.

Derivation of groundwater flow-paths based on semi-automatic extraction of lineaments from remote sensing data

NASA Astrophysics Data System (ADS)

Mallast, U.; Gloaguen, R.; Geyer, S.; Rödiger, T.; Siebert, C.

2011-08-01

In this paper we present a semi-automatic method to infer groundwater flow-paths based on the extraction of lineaments from digital elevation models. This method is especially adequate in remote and inaccessible areas where in-situ data are scarce. The combined method of linear filtering and object-based classification provides a lineament map with a high degree of accuracy. Subsequently, lineaments are differentiated into geological and morphological lineaments using auxiliary information and finally evaluated in terms of hydro-geological significance. Using the example of the western catchment of the Dead Sea (Israel/Palestine), the orientation and location of the differentiated lineaments are compared to characteristics of known structural features. We demonstrate that a strong correlation between lineaments and structural features exists. Using Euclidean distances between lineaments and wells provides an assessment criterion to evaluate the hydraulic significance of detected lineaments. Based on this analysis, we suggest that the statistical analysis of lineaments allows a delineation of flow-paths and thus significant information on groundwater movements. To validate the flow-paths we compare them to existing results of groundwater models that are based on well data.

Automated estimation of river bathymetry using change detection based on Landsat imagery and river morphological models

NASA Astrophysics Data System (ADS)

Donchyts, G.; Jagers, B.; Van De Giesen, N.; Baart, F.; van Dam, A.

2015-12-01

Free global data sets on river bathymetry at global scale are not yet available. While one of the mostly used free elevation datasets, SRTM, provides data on location and elevation of rivers, its quality usually is very limited. This happens mainly because water mask was derived from older satellite imagery, such as Landsat 5, and also because the radar instruments perform bad near water, especially with the presence of vegetation in riparian zone. Additional corrections are required before it can be used for applications such as higher resolution surface water flow simulations. On the other hand, medium resolution satellite imagery from Landsat mission can be used to estimate water mask changes during the last 40 years. Water mask from Landsat imagery can be derived on per-image basis, in some cases, resulting in up to one thousand water masks. For rivers where significant water mask changes can be observed, this information can be used to improve quality of existing digital elevation models in the range between minimum and maximum observed water levels. Furthermore, we can use this information to further estimate river bathymetry using morphological models. We will evaluate how Landsat imagery can be used to estimate river bathymetry and will point to cases of significant inconsistencies between SRTM and Landsat-based water masks. We will also explore other challenges on a way to automated estimation of river bathymetry using fusion of numerical morphological models and remote sensing data. Some of them include automatic generation of model mesh, estimation of river morphodynamic properties and issues related to spectral method used to analyse optical satellite imagery.

Temporal Data Fusion Approaches to Remote Sensing-Based Wetland Classification

NASA Astrophysics Data System (ADS)

Montgomery, Joshua S. M.

This thesis investigates the ecology of wetlands and associated classification in prairie and boreal environments of Alberta, Canada, using remote sensing technology to enhance classification of wetlands in the province. Objectives of the thesis are divided into two case studies, 1) examining how satellite borne Synthetic Aperture Radar (SAR), optical (RapidEye & SPOT) can be used to evaluate surface water trends in a prairie pothole environment (Shepard Slough); and 2) investigating a data fusion methodology combining SAR, optical and Lidar data to characterize wetland vegetation and surface water attributes in a boreal environment (Utikuma Regional Study Area (URSA)). Surface water extent and hydroperiod products were derived from SAR data, and validated using optical imagery with high accuracies (76-97% overall) for both case studies. High resolution Lidar Digital Elevation Models (DEM), Digital Surface Models (DSM), and Canopy Height Model (CHM) products provided the means for data fusion to extract riparian vegetation communities and surface water; producing model accuracies of (R2 0.90) for URSA, and RMSE of 0.2m to 0.7m at Shepard Slough when compared to field and optical validation data. Integration of Alberta and Canadian wetland classifications systems used to classify and determine economic value of wetlands into the methodology produced thematic maps relevant for policy and decision makers for potential wetland monitoring and policy development.

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

NASA Technical Reports Server (NTRS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-01-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

The characterization of a DIRSIG simulation environment to support the inter-calibration of spaceborne sensors

NASA Astrophysics Data System (ADS)

Ambeau, Brittany L.; Gerace, Aaron D.; Montanaro, Matthew; McCorkel, Joel

2016-09-01

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed.

The cryptoendolithic microbial environment in the Ross Desert of Antarctica: mathematical models of the thermal regime

NASA Technical Reports Server (NTRS)

Nienow, J. A.; McKay, C. P.; Friedmann, E. I.

1988-01-01

Microbial activity in the Antarctic cryptoendolithic habitat is regulated primarily by temperature. Previous field studies have provided some information on the thermal regime in this habitat, but this type of information is limited by the remoteness of the site and the harsh climatic conditions. Therefore, a mathematical model of the endolithic thermal regime was constructed to augment the field data. This model enabled the parameters affecting the horizontal and altitudinal distribution of the community to be examined. The model predicts that colonization should be possible on surfaces with zenith angle less than 15 degrees. At greater zenith angles, colonization should be restricted to surfaces with azimuth angles less than 135 degrees or greater than 225 degrees. The upper elevational limit of the community should be less than 2,500 m. The thermal regime probably does not influence the zonation of the community within a rock.

Trichuris trichiura infection and its relation to environmental factors in Mbeya region, Tanzania: A cross-sectional, population-based study.

PubMed

Manz, Kirsi M; Clowes, Petra; Kroidl, Inge; Kowuor, Dickens O; Geldmacher, Christof; Ntinginya, Nyanda E; Maboko, Leonard; Hoelscher, Michael; Saathoff, Elmar

2017-01-01

The intestinal nematode Trichuris trichiura is among the most common causes of human infectious disease worldwide. As for other soil-transmitted nematodes, its reproductive success and thus prevalence and intensity of infection in a given area strongly depend on environmental conditions. Characterization of the influence of environmental factors can therefore aid to identify infection hot spots for targeted mass treatment. We analyzed data from a cross-sectional survey including 6234 participants from nine distinct study sites in Mbeya region, Tanzania. A geographic information system was used to combine remotely sensed and individual data, which were analyzed using uni- and multivariable Poisson regression. Household clustering was accounted for and when necessary, fractional polynomials were used to capture non-linear relationships between T. trichiura infection prevalence and environmental variables. T. trichiura infection was restricted to the Kyela site, close to Lake Nyasa with only very few cases in the other eight sites. The prevalence of T. trichiura infection in Kyela was 26.6% (95% confidence interval (CI) 23.9 to 29.6%). Multivariable models revealed a positive association of infection with denser vegetation (prevalence ratio (PR) per 0.1 EVI units = 2.12, CI 1.28 to 3.50) and inverse associations with rainfall (PR per 100 mm = 0.54, CI 0.44 to 0.67) and elevation (PR per meter = 0.89, CI 0.86 to 0.93) while adjusting for age and previous worm treatment. Slope of the terrain was modelled non-linearly and also showed a positive association with T. trichiura infection (p-value p<0.001). Higher prevalences of T. trichiura infection were only found in Kyela, a study site characterized by denser vegetation, high rainfall, low elevation and flat terrain. But even within this site, we found significant influences of vegetation density, rainfall, elevation and slope on T. trichiura infection. The inverse association of rainfall with infection in Kyela is likely due to the fact, that rainfall in this site is beyond the optimum conditions for egg development. Our findings demonstrate that use of remotely sensed environmental data can aid to predict high-risk areas for targeted helminth control.

Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

PubMed

Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

2017-04-01

Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

Fire risk in California

NASA Astrophysics Data System (ADS)

Peterson, Seth Howard

Fire is an integral part of ecosystems in the western United States. Decades of fire suppression have led to (unnaturally) large accumulations of fuel in some forest communities, such as the lower elevation forests of the Sierra Nevada. Urban sprawl into fire prone chaparral vegetation in southern California has put human lives at risk and the decreased fire return intervals have put the vegetation community at risk of type conversion. This research examines the factors affecting fire risk in two of the dominant landscapes in the state of California, chaparral and inland coniferous forests. Live fuel moisture (LFM) is important for fire ignition, spread rate, and intensity in chaparral. LFM maps were generated for Los Angeles County by developing and then inverting robust cross-validated regression equations from time series field data and vegetation indices (VIs) and phenological metrics from MODIS data. Fire fuels, including understory fuels which are not visible to remote sensing instruments, were mapped in Yosemite National Park using the random forests decision tree algorithm and climatic, topographic, remotely sensed, and fire history variables. Combining the disparate data sources served to improve classification accuracies. The models were inverted to produce maps of fuel models and fuel amounts, and these showed that fire fuel amounts are highest in the low elevation forests that have been most affected by fire suppression impacting the natural fire regime. Wildland fires in chaparral commonly burn in late summer or fall when LFM is near its annual low, however, the Jesusita Fire burned in early May of 2009, when LFM was still relatively high. The HFire fire spread model was used to simulate the growth of the Jesusita Fire using LFM maps derived from imagery acquired at the time of the fire and imagery acquired in late August to determine how much different the fire would have been if it had occurred later in the year. Simulated fires were 1.5 times larger, and the fire reached the wildland urban interface three hours earlier, when using August LFM.

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, J.C.; Purkis, S.J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping. ?? 2009 Coastal Education and Research Foundation.

The emerging role of lidar remote sensing in coastal research and resource management

USGS Publications Warehouse

Brock, John C.; Purkis, Samuel J.

2009-01-01

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334

Approximating SIR-B response characteristics and estimating wave height and wavelength for ocean imagery

NASA Technical Reports Server (NTRS)

Tilley, David G.

1987-01-01

NASA Space Shuttle Challenger SIR-B ocean scenes are used to derive directional wave spectra for which speckle noise is modeled as a function of Rayleigh random phase coherence downrange and Poisson random amplitude errors inherent in the Doppler measurement of along-track position. A Fourier filter that preserves SIR-B image phase relations is used to correct the stationary and dynamic response characteristics of the remote sensor and scene correlator, as well as to subtract an estimate of the speckle noise component. A two-dimensional map of sea surface elevation is obtained after the filtered image is corrected for both random and deterministic motions.

Rotation and direction judgment from visual images head-slaved in two and three degrees-of-freedom.

PubMed

Adelstein, B D; Ellis, S R

2000-03-01

The contribution to spatial awareness of adding a roll degree-of-freedom (DOF) to telepresence camera platform yaw and pitch was examined in an experiment where subjects judged direction and rotation of stationary target markers in a remote scene. Subjects viewed the scene via head-slaved camera images in a head-mounted display. Elimination of the roll DOF affected rotation judgment, but only at extreme yaw and pitch combinations, and did not affect azimuth and elevation judgement. Systematic azimuth overshoot occurred regardless of roll condition. Observed rotation misjudgments are explained by kinematic models for eye-head direction of gaze.

Remote sensing as a tool to analyse lizards behaviour

NASA Astrophysics Data System (ADS)

Dos Santos, Remi; Teodoro, Ana C.; Carretero, Miguel; Sillero, Neftalí

2016-10-01

Although the spatial context is expected to be a major influence in the interactions among organisms and their environment, it is commonly ignored in ecological studies. This study is part of an investigation on home ranges and their influence in the escape behaviour of Iberian lizards. Fieldwork was conducted inside a 400 m2 mesocosm, using three acclimatized adult male individuals. In order to perform analyses at this local scale, tools with high spatial accuracy are needed. A total of 3016 GPS points were recorded and processed into a Digital Elevation Model (DEM), with a pixel resolution of 2 cm. Then, 1156 aerial photos were taken and processed to create an orthophoto. A refuge map, containing possible locations for retreats was generated with supervised image classification algorithms, obtaining four classes (refuges, vegetation, bare soil and organic soil). Furthermore, 50 data-loggers were randomly placed, recording evenly through the area temperature and humidity every 15'. After a month of recording, all environmental variables were interpolated using Kriging. The study area presented an irregular elevation. The humidity varied according to the topography and the temperature presented a West-East pattern. Both variables are of paramount importance for lizard activity and performance. In a predation risk scenario, a lizard located in a temperature close to its thermal optimum will be able to escape more efficiently. Integration of such ecologically relevant elements in a spatial context exemplifies how remote sensing tools can contribute to improve inference in behavioural ecology.

Ecohydrodynamics of cold-water coral reefs: a case study of the Mingulay Reef Complex (western Scotland).

PubMed

Moreno Navas, Juan; Miller, Peter I; Miller, Peter L; Henry, Lea-Anne; Hennige, Sebastian J; Roberts, J Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications.

Ecohydrodynamics of Cold-Water Coral Reefs: A Case Study of the Mingulay Reef Complex (Western Scotland)

PubMed Central

Navas, Juan Moreno; Miller, Peter L.; Henry, Lea-Anne; Hennige, Sebastian J.; Roberts, J. Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications. PMID:24873971

High Resolution Spectra of Carbon Monoxide, Propane and Ammonia for Atmospheric Remote Sensing

NASA Astrophysics Data System (ADS)

Beale, Christopher Andrew

Spectroscopy is a critical tool for analyzing atmospheric data. Identification of atmospheric parameters such as temperature, pressure and the existence and concentrations of constituent gases via remote sensing techniques are only possible with spectroscopic data. These form the basis of model atmospheres which may be compared to observations to determine such parameters. To this end, this dissertation explores the spectroscopy of three molecules: ammonia, propane and carbon monoxide. Infrared spectra have been recorded for ammonia in the region 2400-9000 cm-1. These spectra were recorded at elevated temperatures (from 293-973 K) using a Fourier Transform Spectrometer (FTS). Comparison between the spectra recorded at different temperatures yielded experimental lower state energies. These spectra resulted in the measurement of roughly 30000 lines and about 3000 quantum assignments. In addition spectra of propane were recorded at elevated temperatures (296-700 K) using an FTS. Atmospheres with high temperatures require molecular data at appropriate conditions. This dissertation describes collection of such data and the potential application to atmospheres in our solar system, such as auroral regions in Jupiter, to those of planets orbiting around other stars and cool sub-stellar objects known as brown dwarfs. The spectra of propane and ammonia provide the highest resolution and most complete experimental study of these gases in their respective spectral regions at elevated temperatures. Detection of ammonia in an exoplanet or detection of propane in the atmosphere of Jupiter will most likely rely on the work presented here. The best laboratory that we have to study atmospheres is our own planet. The same techniques that are applied to these alien atmospheres originated on Earth. As such it is appropriate to discuss remote sensing of our own atmosphere. This idea is explored through analysis of spectroscopic data recorded by an FTS on the Atmospheric Chemistry Experiment satellite of carbon monoxide. The effect of the atmosphere's chemistry and physics on this molecule is measured through its isotopologues, primarily 13CO (carbon-13 substituted carbon monoxide). Isotopic chemistry allows a key analysis of the atmosphere as it may be used as a tracer for chemical reactions and dynamical processes. The carbon monoxide fractionation results in Chapter IV present the first global measurements of isotopic fractionation of CO, showing significant fractionation in the upper atmosphere (60-80 km) as a result of the photolysis of carbon dioxide (CO2).

River recharge sources and the partitioning of catchment evapotranspiration fluxes as revealed by stable isotope signals in a typical high-elevation arid catchment

NASA Astrophysics Data System (ADS)

Guo, Xiaoyu; Tian, Lide; Wang, Lei; Yu, Wusheng; Qu, Dongmei

2017-06-01

Catchment-scale hydrological cycles are expected to suffer more extremes under a background of climate change. Quantifying hydrological changes in high and remote areas is practically challenging. However, stable isotopes in river water can be seen to vary, dependent upon the combined influence exerted by recharge sources and local climatic conditions; the study of river water stable isotopes can therefore provide a meaningful method for delineating catchment-scale hydrological studies. In this study, we present high-resolution time series of river δ18O and d-excess values; additionally, we identify the seasonal dynamics of river recharge sources and major components of the catchment-scale water balance, together with precipitation and groundwater isotopes, and concurrent meteorological data recorded in Magazangbu catchment on the northwestern Tibetan Plateau (TP). Using isotopic analysis, and within a proportional framework, we partitioned the isotopic fractionation (E1) or non-fractionation (E2) from soil evaporation fluxes (Esoil) apparent in different processes, using NDVI (Normal Differential Vegetation Index) data collected by MODIS satellites to calculate the vegetation fractional coverage (VFC), and Global Land Data Assimilation System (GLDAS) records to determine evapotranspiration data (ET). Finally, the contributions made by each ET component (Esoil and plant transpiration) to total catchment ET were computed for the high and remote northwestern TP. Our results show that: (1) river δ18O values were high in summer and low in winter, while d-excess values displayed a contrary seasonal cycle; (2) for the monsoon period, precipitation contributed 60.6% to Magazangbu catchment runoff. Deeper groundwater was the main water source for the winter low base flow, and shallow groundwater or high elevation snowmelt was the principal component of the spring thaw and autumn freezing periods; and (3) a substantial proportion of Esoil (96.4% annually; 92.2% during monsoon) was consumed without isotopic fractionation (E2); plant transpiration (T) constituted less than half of total ET (41% annually, 29% during monsoon) in Magazangbu catchment. This calculation of river recharge sources and partitioning of catchment ET components using isotopic signals and MODIS NDVI data or GLDAS ET data provide new methods for hydrological studies in high and remote areas. These results provide important catchment-scale water-balance information which is very useful to climate models conducted in a high-elevation arid environment.

Epigenetic Priming of Memory Updating during Reconsolidation to Attenuate Remote Fear Memories

PubMed Central

Gräff, Johannes; Joseph, Nadine F.; Horn, Meryl E.; Samiei, Alireza; Meng, Jia; Seo, Jinsoo; Rei, Damien; Bero, Adam W.; Phan, Trongha X.; Wagner, Florence; Holson, Edward; Xu, Jinbin; Sun, Jianjun; Neve, Rachael L.; Mach, Robert H.; Haggarty, Stephen J.; Tsai, Li-Huei

2014-01-01

Summary Traumatic events generate some of the most enduring forms of memories. Despite the elevated lifetime prevalence of anxiety disorders, effective strategies to attenuate long-term traumatic memories are scarce. The most efficacious treatments to diminish recent (i.e., day-old) traumata capitalize on memory updating mechanisms during reconsolidation that are initiated upon memory recall. Here, we show that, in mice, successful reconsolidation-updating paradigms for recent memories fail to attenuate remote (i.e., month-old) ones. We find that, whereas recent memory recall induces a limited period of hippocampal neuroplasticity mediated, in part, by S-nitrosylation of HDAC2 and histone acetylation, such plasticity is absent for remote memories. However, by using an HDAC2-targeting inhibitor (HDACi) during reconsolidation, even remote memories can be persistently attenuated. This intervention epigenetically primes the expression of neuroplasticity-related genes, which is accompanied by higher metabolic, synaptic, and structural plasticity. Thus, applying HDACis during memory reconsolidation might constitute a treatment option for remote traumata. PMID:24439381

Inference of effective river properties from remotely sensed observations of water surface

NASA Astrophysics Data System (ADS)

Garambois, Pierre-André; Monnier, Jérôme

2015-05-01

The future SWOT mission (Surface Water and Ocean Topography) will provide cartographic measurements of inland water surfaces (elevation, widths and slope) at an unprecedented spatial and temporal resolution. Given synthetic SWOT like data, forward flow models of hierarchical-complexity are revisited and few inverse formulations are derived and assessed for retrieving the river low flow bathymetry, roughness and discharge (A0, K, Q) . The concept of an effective low flow bathymetry A0 (the real one being never observed) and roughness K , hence an effective river dynamics description, is introduced. The few inverse models elaborated for inferring (A0, K, Q) are analyzed in two contexts: (1) only remotely sensed observations of the water surface (surface elevation, width and slope) are available; (2) one additional water depth measurement (or estimate) is available. The inverse models elaborated are independent of data acquisition dynamics; they are assessed on 91 synthetic test cases sampling a wide range of steady-state river flows (the Froude number varying between 0.05 and 0.5 for 1 km reaches) and in the case of a flood on the Garonne River (France) characterized by large spatio-temporal variabilities. It is demonstrated that the most complete shallow-water like model allowing to separate the roughness and bathymetry terms is the so-called low Froude model. In Case (1), the resulting RMSE on infered discharges are on the order of 15% for first guess errors larger than 50%. An important feature of the present inverse methods is the fairly good accuracy of the discharge Q obtained, while the identified roughness coefficient K includes the measurement errors and the misfit of physics between the real flow and the hypothesis on which the inverse models rely; the later neglecting the unobserved temporal variations of the flow and the inertia effects. A compensation phenomena between the indentifiedvalues of K and the unobserved bathymetry A0 is highlighted, while the present inverse models lead to an effective river dynamics model that is accurate in the range of the discharge variability observed. In Case (2), the effective bathymetry profile for 80 km of the Garonne River is retrieved with 1% relative error only. Next, accurate effective topography-friction pairs and also discharge can be inferred. Finally, defining river reaches from the observation grid tends to average the river properties in each reach, hence tends to smooth the hydraulic variability.

Data assimilation problems in glaciology

NASA Astrophysics Data System (ADS)

Shapero, Daniel

Rising sea levels due to mass loss from Greenland and Antarctica threaten to inundate coastal areas the world over. For the purposes of urban planning and hazard mitigation, policy makers would like to know how much sea-level rise can be anticipated in the next century. To make these predictions, glaciologists use mathematical models of ice sheet flow, together with remotely-sensed observations of the current state of the ice sheets. The quantities that are observable over large spatial scales are the ice surface elevation and speed, and the elevation of the underlying bedrock. There are other quantities, such as the viscosity within the ice and the friction coefficient for sliding over the bed, that are just as important in dictating how fast the glacier flows, but that are not observable at large scales using current methods. These quantities can be inferred from observations by using data assimilation methods, applied to a model of glacier flow. In this dissertation, I will describe my work on data assimilation problems in glaciology. My main contributions so far have been: computing the bed stress underneath the three biggest Greenland outlet glaciers; developing additional tools for glacier modeling and data assimilation in the form of the open-source library icepack ; and improving the statistical methodology through the user of total variation priors.

Internet-Based Software Tools for Analysis and Processing of LIDAR Point Cloud Data via the OpenTopography Portal

NASA Astrophysics Data System (ADS)

Nandigam, V.; Crosby, C. J.; Baru, C.; Arrowsmith, R.

2009-12-01

LIDAR is an excellent example of the new generation of powerful remote sensing data now available to Earth science researchers. Capable of producing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LIDAR data allows earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible, yet essential for their appropriate representation. Along with these high-resolution datasets comes an increase in the volume and complexity of data that the user must efficiently manage and process in order for it to be scientifically useful. Although there are expensive commercial LIDAR software applications available, processing and analysis of these datasets are typically computationally inefficient on the conventional hardware and software that is currently available to most of the Earth science community. We have designed and implemented an Internet-based system, the OpenTopography Portal, that provides integrated access to high-resolution LIDAR data as well as web-based tools for processing of these datasets. By using remote data storage and high performance compute resources, the OpenTopography Portal attempts to simplify data access and standard LIDAR processing tasks for the Earth Science community. The OpenTopography Portal allows users to access massive amounts of raw point cloud LIDAR data as well as a suite of DEM generation tools to enable users to generate custom digital elevation models to best fit their science applications. The Cyberinfrastructure software tools for processing the data are freely available via the portal and conveniently integrated with the data selection in a single user-friendly interface. The ability to run these tools on powerful Cyberinfrastructure resources instead of their own labs provides a huge advantage in terms of performance and compute power. The system also encourages users to explore data processing methods and the variations in algorithm parameters since all of the processing is done remotely and numerous jobs can be submitted in sequence. The web-based software also eliminates the need for users to deal with the hassles and costs associated with software installation and licensing while providing adequate disk space for storage and personal job archival capability. Although currently limited to data access and DEM generation tasks, the OpenTopography system is modular in design and can be modified to accommodate new processing tools as they become available. We are currently exploring implementation of higher-level DEM analysis tasks in OpenTopography, since such processing is often computationally intensive and thus lends itself to utilization of cyberinfrastructure. Products derived from OpenTopography processing are available in a variety of formats ranging from simple Google Earth visualizations of LIDAR-derived hillshades to various GIS-compatible grid formats. To serve community users less interested in data processing, OpenTopography also hosts 1 km^2 digital elevation model tiles as well as Google Earth image overlays for a synoptic view of the data.

Analysis of GOES imagery and digitized data for the SEV-UPS period, August 1979

NASA Technical Reports Server (NTRS)

Bowley, C. J.; Burke, H. H. K.; Barnes, J. C.

1981-01-01

In support of the Southeastern Virginia Urban Plume Study (SEV-UPS), GOES satellite imagery was analyzed for the month of August 1979. The analyzed GOES images provide an additional source of meteorological input useful in the evaluation of air quality data collected during the month long period of the SEV-UPS experiment. In addition to the imagery analysis, GOES digitized data were analyzed for the period of August 6 to 11, during which a regional haze pattern was detectable in the imagery. The results of the study indicate that the observed haze patterns correspond closely with areas shown in surface based measurements to have reduced visibilities and elevated pollution levels. Moreover, the results of the analysis of digitized data indicate that digital reflectance counts can be directly related to haze intensity both over land and ocean. The model results agree closely with the observed GOES digital reflectance counts, providing further indication that satellite remote sensing can be a useful tool for monitoring regional elevated pollution episodes.

Dengue transmission based on urban environmental gradients in different cities of Pakistan.

PubMed

Khalid, Bushra; Ghaffar, Abdul

2015-03-01

This study focuses on the dengue transmission in different regions of Pakistan. For this purpose, the data of dengue cases for 2009-2012 from four different cities (Rawalpindi, Islamabad, Lahore, and Karachi) of the country is collected, evaluated, and compiled. To identify the reasons and regions of higher risk of Dengue transmission, land use classification, analysis of climate covariates and drainage patterns was done. Analysis involves processing of SPOT 5 10 m, Landsat TM 30 m data sets, and SRTM 90 m digital elevation models by using remote sensing and GIS techniques. The results are based on the change in urbanization and population density, analysis of temperature, rainfall, and wind speed; calculation of drainage patterns including stream features, flow accumulation, and drainage density of the study areas. Results suggest that the low elevation areas with calm winds and minimum temperatures higher than the normal, rapid increase in unplanned urbanization, low flow accumulation, and higher drainage density areas favor the dengue transmission.

Geologic, geomorphic, and meteorological aspects of debris flows triggered by Hurricanes Frances and Ivan during September 2004 in the Southern Appalachian Mountains of Macon County, North Carolina (southeastern USA)

USGS Publications Warehouse

Wooten, R.M.; Gillon, K.A.; Witt, A.C.; Latham, R.S.; Douglas, T.J.; Bauer, J.B.; Fuemmeler, S.J.; Lee, L.G.

2008-01-01

In September 2004, rain from the remnants of Hurricanes Frances and Ivan triggered at least 155 landslides in the Blue Ridge Mountains of North Carolina. At least 33 debris flows occurred in Macon County, causing 5 deaths, destroying 16 homes, and damaging infrastructure. We mapped debris flows and debris deposits using a light-detecting and ranging digital elevation model, remote imagery and field studies integrated in a geographic information system. Evidence of past debris flows was found at all recent debris flow sites. Orographic rainfall enhancement along topographic escarpments influenced debris flow frequency at higher elevations. A possible trigger for the Wayah and fatal Peeks Creek debris flows was a spiral rain band within Ivan that moved across the area with short duration rainfall rates of 150-230 mm/h. Intersecting bedrock structures in polydeformed metamorphic rock influence the formation of catchments within structural-geomorphic domains where debris flows originate. ?? 2007 Springer-Verlag.

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

NASA Astrophysics Data System (ADS)

Soti, V.; Puech, C.; Lo Seen, D.; Bertran, A.; Vignolles, C.; Mondet, B.; Dessay, N.; Tran, A.

2010-08-01

In the Ferlo Region in Senegal, livestock depend on temporary ponds for water but are exposed to the Rift Valley Fever (RVF), a disease transmitted to herds by mosquitoes which develop in these ponds. Mosquito abundance is related to the emptying and filling phases of the ponds, and in order to study the epidemiology of RVF, pond modelling is required. In the context of a data scarce region, a simple hydrologic model which makes use of remote sensing data was developed to simulate pond water dynamics from daily rainfall. Two sets of ponds were considered: those located in the main stream of the Ferlo Valley whose hydrological dynamics are essentially due to runoff, and the ponds located outside, which are smaller and whose filling mechanisms are mainly due to direct rainfall. Separate calibrations and validations were made for each set of ponds. Calibration was performed from daily field data (rainfall, water level) collected during the 2001 and 2002 rainy seasons and from three different sources of remote sensing data: 1) very high spatial resolution optical satellite images to access pond location and surface area at given dates, 2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) data to estimate pond catchment area and 3) Tropical Rainfall Measuring Mission (TRMM) data for rainfall estimates. The model was applied to all ponds of the study area, the results were validated and a sensitivity analysis was performed. Water height simulations using gauge rainfall as input were compared to water level measurements from four ponds and Nash coefficients >0.7 were obtained. Comparison with simulations using TRMM rainfall data gave mixed results, with poor water height simulations for the year 2001 and good estimations for the year 2002. A pond map derived from a Quickbird satellite image was used to assess model accuracy for simulating pond water areas for all the ponds of the study area. The validation showed that modelled water areas were mostly underestimated but significantly correlated, particularly for the larger ponds. The results of the sensitivity analysis showed that parameters relative to pond shape and catchment area estimation have less effects on model simulation than parameters relative to soil properties (rainfall threshold causing runoff in dry soils and the coefficient expressing soil moisture decrease with time) or the water loss coefficient. Overall, our results demonstrate the possibility of using a simple hydrologic model with remote sensing data to track pond water heights and water areas in a homogeneous arid area.

I/O efficient algorithms and applications in geographic information systems

NASA Astrophysics Data System (ADS)

Danner, Andrew

Modern remote sensing methods such a laser altimetry (lidar) and Interferometric Synthetic Aperture Radar (IfSAR) produce georeferenced elevation data at unprecedented rates. Many Geographic Information System (GIS) algorithms designed for terrain modelling applications cannot process these massive data sets. The primary problem is that these data sets are too large to fit in the main internal memory of modern computers and must therefore reside on larger, but considerably slower disks. In these applications, the transfer of data between disk and main memory, or I/O, becomes the primary bottleneck. Working in a theoretical model that more accurately represents this two level memory hierarchy, we can develop algorithms that are I/O-efficient and reduce the amount of disk I/O needed to solve a problem. In this thesis we aim to modernize GIS algorithms and develop a number of I/O-efficient algorithms for processing geographic data derived from massive elevation data sets. For each application, we convert a geographic question to an algorithmic question, develop an I/O-efficient algorithm that is theoretically efficient, implement our approach and verify its performance using real-world data. The applications we consider include constructing a gridded digital elevation model (DEM) from an irregularly spaced point cloud, removing topological noise from a DEM, modeling surface water flow over a terrain, extracting river networks and watershed hierarchies from the terrain, and locating polygons containing query points in a planar subdivision. We initially developed solutions to each of these applications individually. However, we also show how to combine individual solutions to form a scalable geo-processing pipeline that seamlessly solves a sequence of sub-problems with little or no manual intervention. We present experimental results that demonstrate orders of magnitude improvement over previously known algorithms.

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

NASA Technical Reports Server (NTRS)

VandeVen, C.; Weiss, S. B.

2001-01-01

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

Evaluation of remote-sensing techniques to measure decadal-scale changes of Hofsjokull ice cap, Iceland

USGS Publications Warehouse

Hall, D.K.; Williams, R.S.; Barton, J.S.; Sigurdsson, O.; Smith, L.C.; Garvin, J.B.

2000-01-01

Dynamic surficial changes and changes in the position of the firn line and the areal extent of Hofsjökull ice cap, Iceland, were studied through analysis of a time series (1973–98) of synthetic-aperture radar (SAR) and Landsat data. A digital elevation model of Hofsjökull, which was constructed using SAR interferometry, was used to plot the SAR backscatter coefficient (σ°) vs elevation and air temperature along transects across the ice cap. Seasonal and daily σ° patterns are caused by freezing or thawing of the ice-cap surface, and abrupt changes in σ° are noted when the air temperature ranges from ∼−5° to 0°C. Late-summer 1997 σ° (SAR) and reflectance (Landsat) boundaries agree and appear to be coincident with the firn line and a SAR σ° boundary that can be seen in the January 1998 SAR image. In January 1994 through 1998, the elevation of this σ° boundary on the ice capwas quite stable, ranging from 1000 to 1300 m, while the equilibrium-line altitude, as measured on the ground, varied considerably. Thus the equilibrium line may be obscured by firn from previous years. Techniques are established to measure long-term changes in the elevation of the firn line and changes in the position of the ice margin.

Extraction of Airport Features from High Resolution Satellite Imagery for Design and Risk Assessment

NASA Technical Reports Server (NTRS)

Robinson, Chris; Qiu, You-Liang; Jensen, John R.; Schill, Steven R.; Floyd, Mike

2001-01-01

The LPA Group, consisting of 17 offices located throughout the eastern and central United States is an architectural, engineering and planning firm specializing in the development of Airports, Roads and Bridges. The primary focus of this ARC project is concerned with assisting their aviation specialists who work in the areas of Airport Planning, Airfield Design, Landside Design, Terminal Building Planning and design, and various other construction services. The LPA Group wanted to test the utility of high-resolution commercial satellite imagery for the purpose of extracting airport elevation features in the glide path areas surrounding the Columbia Metropolitan Airport. By incorporating remote sensing techniques into their airport planning process, LPA wanted to investigate whether or not it is possible to save time and money while achieving the equivalent accuracy as traditional planning methods. The Affiliate Research Center (ARC) at the University of South Carolina investigated the use of remotely sensed imagery for the extraction of feature elevations in the glide path zone. A stereo pair of IKONOS panchromatic satellite images, which has a spatial resolution of 1 x 1 m, was used to determine elevations of aviation obstructions such as buildings, trees, towers and fence-lines. A validation dataset was provided by the LPA Group to assess the accuracy of the measurements derived from the IKONOS imagery. The initial goal of this project was to test the utility of IKONOS imagery in feature extraction using ERDAS Stereo Analyst. This goal was never achieved due to problems with ERDAS software support of the IKONOS sensor model and the unavailability of imperative sensor model information from Space Imaging. The obstacles encountered in this project pertaining to ERDAS Stereo Analyst and IKONOS imagery will be reviewed in more detail later in this report. As a result of the technical difficulties with Stereo Analyst, ERDAS OrthoBASE was used to derive aviation obstruction measurements for this project. After collecting ancillary data such as GPS locations, South Carolina Geodetic Survey and Aero Dynamics ground survey points to set up the OrthoBASE Block File, measurements were taken of the various glide path obstructions and compared to the validation dataset. This process yielded the following conclusions: The IKONOS stereo model in conjunction with Imagine OrthoBASE can provide The LPA Group with a fast and cost efficient method for assessing aviation obstructions. Also, by creating our own stereo model we achieved any accuracy better currently available commercial products.

Trans-Pacific and Regional Atmospheric Transport of Polycyclic Aromatic Hydrocarbons and Pesticides in Biomass Burning Emissions to Western North America

PubMed Central

Genualdi, Susan A.; Killin, Robert K.; Woods, Jim; Wilson, Glenn; Schmedding, David; Massey Simonich, Staci L.

2014-01-01

The trans-Pacific and regional North American atmospheric transport of polycyclic aromatic hydrocarbons (PAHs) and pesticides in biomass burning emissions was measured in air masses from April to September 2003 at two remote sites in western North America. Mary’s Peak Observatory (MPO) is located in Oregon’s Coast Range and Cheeka Peak Observatory (CPO) is located on the tip of the Olympic Peninsula in Washington State. During this time period, both remote sites were influenced by PAH and pesticide emissions from forest fires in Siberia and regional fires in Oregon and Washington State. Concurrent samples were taken at both sites on June 2 and August 4, 2003. On these dates, CPO had elevated gas phase PAH, alpha-hexachlorocyclohexane and retene concentrations (p<0.05) and MPO had elevated retene, particulate phase PAH and levoglucosan concentrations due to trans-Pacific transport of emissions from fires in Siberia. In addition, during the April to September 2003 sampling period, CPO and MPO were influenced by emissions from regional fires that resulted in elevated levoglucosan, dacthal, endosulfan and gas phase PAH concentrations. Burned and unburned forest soil samples collected from the regional forest fire area showed that 34 to 100% of the pesticide mass was lost from soil due to burning. These data suggest that the transPacific and regional atmospheric transport of biomass burning emissions results in elevated PAH and pesticide concentrations in western North America. The elevated pesticide concentrations are likely due to re-emission of historically deposited pesticides from the soil and vegetation during the fire event. PMID:19320158

Remote sensing supported surveillance and characterization of tailings behavior at a gold mine site, Finland.

NASA Astrophysics Data System (ADS)

Rauhala, Anssi; Tuomela, Anne; Rossi, Pekka M.; Davids, Corine

2017-04-01

The management of vast amounts of tailings produced is one of the key issues in mining operations. The effective and economic disposal of the waste requires knowledge concerning both basic physical properties of the tailings as well as more complex aspects such as consolidation behavior. The behavior of tailings in itself is a very complex issue that can be affected by flocculation, sedimentation, consolidation, segregation, deposition, freeze-thaw, and desiccation phenomena. The utilization of remote sensing in an impoundment-scale monitoring of tailings could benefit the management of tailings, and improve our knowledge on tailings behavior. In order to gain better knowledge of tailings behavior in cold climate, we have utilized both modern remote sensing techniques and more traditional in situ and laboratory measurements in characterizing thickened gold tailings behavior at a Finnish gold mine site, where the production has been halted due to low gold prices. The remote sensing measurements consisted of elevation datasets collected from unmanned aerial vehicles during summers 2015 and 2016, and a further campaign is planned for the summer 2017. The ongoing traditional measurements include for example particle-size distribution, frost heave, frost depth, water retention, temperature profile, and rheological measurements. Initial results from the remote sensing indicated larger than expected settlements on parts of the tailings impoundment, and also highlighted some of the complexities related to data processing. The interpretation of the results and characterization of the behavior is in this case complicated by possible freeze-thaw effects and potential settlement of the impoundment bottom structure consisting of natural peat. Experiments with remote sensing and unmanned aerial vehicles indicate that they could offer potential benefits in frequent mine site monitoring, but there is a need towards more robust and streamlined data acquisition and processing. The gathered data and obtained results form the basis for further modelling efforts which aim at better management of tailings storage facilities.

Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography

NASA Astrophysics Data System (ADS)

Mackay, D. Scott; Band, Lawrence E.

1998-04-01

This paper presents a new method for extracting flow directions, contributing (upslope) areas, and nested catchments from digital elevation models in lake-dominated areas. Existing tools for acquiring descriptive variables of the topography, such as surface flow directions and contributing areas, were developed for moderate to steep topography. These tools are typically difficult to apply in gentle topography owing to limitations in explicitly handling lakes and other flat areas. This paper addresses the problem of accurately representing general topographic features by first identifying distinguishing features, such as lakes, in gentle topography areas and then using these features to guide the search for topographic flow directions and catchment marking. Lakes are explicitly represented in the topology of a watershed for use in water routing. Nonlake flat features help guide the search for topographic flow directions in areas of low signal to noise. This combined feature-based and grid-based search for topographic features yields improved contributing areas and watershed boundaries where there are lakes and other flat areas. Lakes are easily classified from remotely sensed imagery, which makes automated representation of lakes as subsystems within a watershed system tractable with widely available data sets.

Quantification of Glacier Depletion in the Central Tibetan Plateau by Using Integrated Satellite Remote Sensing and Gravimetry

NASA Astrophysics Data System (ADS)

Tseng, K.-H.; Liu, K. T.; Shum, C. K.; Jia, Y.; Shang, K.; Dai, C.

2016-06-01

Glaciers over the Tibetan Plateau have experienced accelerated depletion in the last few decades due primarily to the global warming. The freshwater drained into brackish lakes is also observed by optical remote sensing and altimetry satellites. However, the actual water storage change is difficult to be quantified since the altimetry or remote sensing only provide data in limited dimensions. The altimetry data give an elevation change of surface while the remote sensing images provide an extent variation in horizontal plane. Hence a data set used to describe the volume change is needed to measure the exact mass transition in a time span. In this study, we utilize GRACE gravimetry mission to quantify the total column mass change in the central Tibetan Plateau, especially focused on the lakes near Tanggula Mountains. By removing these factors, the freshwater storage change of glacier system at study area can be potentially isolated.

SU-E-T-675: Remote Dosimetry with a Novel PRESAGE Formulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mein, S; Juang, T; Malcolm, J

2015-06-15

Purpose: 3D-gel dosimetry provides high-resolution treatment validation; however, scanners aren’t widely available. In remote dosimetry, dosimeters are shipped out from a central base institution to a remote site for irradiation, then shipped back for scanning and analysis, affording a convenient service for treatment validation to institutions lacking the necessary equipment and resources. Previous works demonstrated the high-resolution performance and temporal stability of PRESAGE. Here the newest formulation is investigated for remote dosimetry use. Methods: A new formulation of PRESAGE was created with the aim of improved color stability post irradiation. Dose sensitivity was determined by irradiating cuvettes on a Varianmore » Linac (6MV) from 0–15Gy and measuring change in optical density at 633nm. Sensitivity readings were tracked over time in a temperature control study to determine long-term stability. A large volume study was performed to evaluate the accuracy for remote dosimetry. A 1kg dosimeter was pre-scanned, irradiated on-site with an 8Gy 4field box treatment, post-scanned and shipped to Princess Margaret Hospital for remote reading on an identical scanner. Results: Dose sensitivities ranged from 0.0194–0.0295 ΔOD/(Gy*cm)—similar to previous formulations. Post-irradiated cuvettes stored at 10°C retained 100% initial sensitivity over 5 days and 98.6% over 10 weeks while cuvettes stored at room temperature fell to 95.8% after 5 days and 37.4% after 10 weeks. The immediate and 5-day scans of the 4field box dosimeter data was reconstructed, registered to the corresponding eclipse dose-distribution, and compared with analytical tools in CERR. Immediate and 5-day scans looked visually similar. Line profiles revealed close agreement aside from a slight elevation in dose at the edge in the 5-day readout. Conclusion: The remote dosimetry formulation exhibits excellent temporal stability in small volumes. While immediate and 5-day readout scans of large volume dosimeters show promising agreement, further development is required to reduce an apparent time dependent edge elevation.« less

The pancreas responds to remote damage and systemic stress by secretion of the pancreatic secretory proteins PSP/regI and PAP/regIII.

PubMed

Reding, Theresia; Palmiere, Cristian; Pazhepurackel, Clinsyjos; Schiesser, Marc; Bimmler, Daniel; Schlegel, Andrea; Süss, Ursula; Steiner, Sabrina; Mancina, Leandro; Seleznik, Gitta; Graf, Rolf

2017-05-02

In patients with infection and sepsis serum levels of Pancreatic Stone protein/regenerating protein I (PSP) are highly elevated. The origin of PSP during these conditions is presumably the pancreas, however, an intestinal origin cannot be excluded. Similarly, pancreatitis-associated protein (PAP) was identified in the pancreas. These proteins were also localized in intestinal organs. Here we aim to elucidate the bio-distribution of PSP and PAP in animal models of sepsis and in healthy humans. PSP and PAP responded to remote lesions in rats although the pancreatic response was much more pronounced than the intestinal. Tissue distribution of PSP demonstrated a 100-fold higher content in the pancreas compared to any other organ while PAP was most abundant in the small intestine. Both proteins responded to CLP or sham operation in the pancreas. PSP also increased in the intestine during CLP. The distribution of PSP and PAP in human tissue mirrored the distribution in the murine models. Distribution of PSP and PAP was visualized by immunohistochemistry. Rats and mice underwent midline laparotomies followed by mobilization of tissue and incision of the pancreatic duct or duodenum. Standard cecum-ligation-puncture (CLP) procedures or sham laparotomies were performed. Human tissue extracts were analyzed for PSP and PAP. The pancreas reacts to remote lesions and septic insults in mice and rats with increased PSP synthesis, while PAP is selectively responsive to septic events. Furthermore, our results suggest that serum PSP in septic patients is predominantly derived through an acute phase response of the pancreas.

From Ground Truth to Space: Surface, Subsurface and Remote Observations Associated with Nuclear Test Detection

NASA Astrophysics Data System (ADS)

Sussman, A. J.; Anderson, D.; Burt, C.; Craven, J.; Kimblin, C.; McKenna, I.; Schultz-Fellenz, E. S.; Miller, E.; Yocky, D. A.; Haas, D.

2016-12-01

Underground nuclear explosions (UNEs) result in numerous signatures that manifest on a wide range of temporal and spatial scales. Currently, prompt signals, such as the detection of seismic waves provide only generalized locations and the timing and amplitude of non-prompt signals are difficult to predict. As such, research into improving the detection, location, and identification of suspect events has been conducted, resulting in advancement of nuclear test detection science. In this presentation, we demonstrate the scalar variably of surface and subsurface observables, briefly discuss current capabilities to locate, detect and characterize potential nuclear explosion locations, and explain how emergent technologies and amalgamation of disparate data sets will facilitate improved monitoring and verification. At the smaller scales, material and fracture characterization efforts on rock collected from legacy UNE sites and from underground experiments using chemical explosions can be incorporated into predictive modeling efforts. Spatial analyses of digital elevation models and orthoimagery of both modern conventional and legacy nuclear sites show subtle surface topographic changes and damage at nearby outcrops. Additionally, at sites where such technology cannot penetrate vegetative cover, it is possible to use the vegetation itself as both a companion signature reflecting geologic conditions and showing subsurface impacts to water, nutrients, and chemicals. Aerial systems based on RGB imagery, light detection and ranging, and hyperspectral imaging can allow for combined remote sensing modalities to perform pattern recognition and classification tasks. Finally, more remote systems such as satellite based synthetic aperture radar and satellite imagery are other techniques in development for UNE site detection, location and characterization.

Estimating Catchment-Scale Snowpack Variability in Complex Forested Terrain, Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Harpold, A. A.; Brooks, P. D.; Biederman, J. A.; Swetnam, T.

2011-12-01

Difficulty estimating snowpack variability across complex forested terrain currently hinders the prediction of water resources in the semi-arid Southwestern U.S. Catchment-scale estimates of snowpack variability are necessary for addressing ecological, hydrological, and water resources issues, but are often interpolated from a small number of point-scale observations. In this study, we used LiDAR-derived distributed datasets to investigate how elevation, aspect, topography, and vegetation interact to control catchment-scale snowpack variability. The study area is the Redondo massif in the Valles Caldera National Preserve, NM, a resurgent dome that varies from 2500 to 3430 m and drains from all aspects. Mean LiDAR-derived snow depths from four catchments (2.2 to 3.4 km^2) draining different aspects of the Redondo massif varied by 30%, despite similar mean elevations and mixed conifer forest cover. To better quantify this variability in snow depths we performed a multiple linear regression (MLR) at a 7.3 by 7.3 km study area (5 x 106 snow depth measurements) comprising the four catchments. The MLR showed that elevation explained 45% of the variability in snow depths across the study area, aspect explained 18% (dominated by N-S aspect), and vegetation 2% (canopy density and height). This linear relationship was not transferable to the catchment-scale however, where additional MLR analyses showed the influence of aspect and elevation differed between the catchments. The strong influence of North-South aspect in most catchments indicated that the solar radiation is an important control on snow depth variability. To explore the role of solar radiation, a model was used to generate winter solar forcing index (SFI) values based on the local and remote topography. The SFI was able to explain a large amount of snow depth variability in areas with similar elevation and aspect. Finally, the SFI was modified to include the effects of shading from vegetation (in and out of canopy), which further explained snow depth variability. The importance of SFI for explaining catchment-scale snow depth variability demonstrates that aspect is not a sufficient metric for direct radiation in complex terrain where slope and remote topographic shading are significant. Surprisingly, the net effects of interception and shading by vegetation on snow depths were minimal compared to elevation and aspect in these catchments. These results suggest that snowpack losses from interception may be balanced by increased shading to reduce the overall impacts from vegetation compared to topographic factors in this high radiation environment. Our analysis indicated that elevation and solar radiation are likely to control snow variability in larger catchments, with interception and shading from vegetation becoming more important at smaller scales.

Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes

NASA Astrophysics Data System (ADS)

Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.

2018-03-01

The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass (r2 = 0.72). We then used multiple measures of biomass each growing season over 20-25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series remote sensing data to assess ecological responses to climate stressors.

Topography-based analysis of Hurricane Katrina inundation of New Orleans: Chapter 3G in Science and the storms-the USGS response to the hurricanes of 2005

USGS Publications Warehouse

Gesch, Dean

2007-01-01

The ready availability of high-resolution, high-accuracy elevation data proved valuable for development of topographybased products to determine rough estimates of the inundation of New Orleans, La., from Hurricane Katrina. Because of its high level of spatial detail and vertical accuracy of elevation measurements, light detection and ranging (lidar) remote sensing is an excellent mapping technology for use in low-relief hurricane-prone coastal areas.

A methodology for mapping forest latent heat flux densities using remote sensing

NASA Technical Reports Server (NTRS)

Pierce, Lars L.; Congalton, Russell G.

1988-01-01

Surface temperatures and reflectances of an upper elevation Sierran mixed conifer forest were monitored using the Thematic Mapper Simulator sensor during the summer of 1985 in order to explore the possibility of using remote sensing to determine the distribution of solar energy on forested watersheds. The results show that the method is capable of quantifying the relative energy allocation relationships between the two cover types defined in the study. It is noted that the method also has the potential to map forest latent heat flux densities.

Predictors of Current and Longer-Term Patterns of Abundance of American Pikas (Ochotona princeps) across a Leading-Edge Protected Area.

PubMed

Moyer-Horner, Lucas; Beever, Erik A; Johnson, Douglas H; Biel, Mark; Belt, Jami

2016-01-01

American pikas (Ochotona princeps) have been heralded as indicators of montane-mammal response to contemporary climate change. Pikas no longer occupy the driest and lowest-elevation sites in numerous parts of their geographic range. Conversely, pikas have exhibited higher rates of occupancy and persistence in Rocky Mountain and Sierra Nevada montane 'mainlands'. Research and monitoring efforts on pikas across the western USA have collectively shown the nuance and complexity with which climate will often act on species in diverse topographic and climatic contexts. However, to date no studies have investigated habitat, distribution, and abundance of pikas across hundreds of sites within a remote wilderness area. Additionally, relatively little is known about whether climate acts most strongly on pikas through direct or indirect (e.g., vegetation-mediated) mechanisms. During 2007-2009, we collectively hiked >16,000 km throughout the 410,077-ha Glacier National Park, Montana, USA, in an effort to identify topographic, microrefugial, and vegetative characteristics predictive of pika abundance. We identified 411 apparently pika-suitable habitat patches with binoculars (in situ), and surveyed 314 of them for pika signs. Ranking of alternative logistic-regression models based on AICc scores revealed that short-term pika abundances were positively associated with intermediate elevations, greater cover of mosses, and taller forbs, and decreased each year, for a total decline of 68% during the three-year study; whereas longer-term abundances were associated only with static variables (longitude, elevation, gradient) and were lower on north-facing slopes. Earlier Julian date and time of day of the survey (i.e., midday vs. not) were associated with lower observed pika abundance. We recommend that wildlife monitoring account for this seasonal and diel variation when surveying pikas. Broad-scale information on status and abundance determinants of montane mammals, especially for remote protected areas, is crucial for land and wildlife-resource managers trying to anticipate mammalian responses to climate change.

Predictors of current and longer-term patterns of abundance of American pikas (Ochotona princeps) across a leading-edge protected area

USGS Publications Warehouse

Moyer-Horner, Lucas; Beever, Erik A.; Johnson, Douglas H.; Beil, Mark; Belt, Jami

2016-01-01

American pikas (Ochotona princeps) have been heralded as indicators of montane-mammal response to contemporary climate change. Pikas no longer occupy the driest and lowest-elevation sites in numerous parts of their geographic range. Conversely, pikas have exhibited higher rates of occupancy and persistence in Rocky Mountain and Sierra Nevada montane ‘mainlands’. Research and monitoring efforts on pikas across the western USA have collectively shown the nuance and complexity with which climate will often act on species in diverse topographic and climatic contexts. However, to date no studies have investigated habitat, distribution, and abundance of pikas across hundreds of sites within a remote wilderness area. Additionally, relatively little is known about whether climate acts most strongly on pikas through direct or indirect (e.g., vegetation-mediated) mechanisms. During 2007–2009, we collectively hiked >16,000 km throughout the 410,077-ha Glacier National Park, Montana, USA, in an effort to identify topographic, microrefugial, and vegetative characteristics predictive of pika abundance. We identified 411 apparently pika-suitable habitat patches with binoculars (in situ), and surveyed 314 of them for pika signs. Ranking of alternative logistic-regression models based on AICc scores revealed that short-term pika abundances were positively associated with intermediate elevations, greater cover of mosses, and taller forbs, and decreased each year, for a total decline of 68% during the three-year study; whereas longer-term abundances were associated only with static variables (longitude, elevation, gradient) and were lower on north-facing slopes. Earlier Julian date and time of day of the survey (i.e., midday vs. not) were associated with lower observed pika abundance. We recommend that wildlife monitoring account for this seasonal and diel variation when surveying pikas. Broad-scale information on status and abundance determinants of montane mammals, especially for remote protected areas, is crucial for land and wildlife-resource managers trying to anticipate mammalian responses to climate change.

Assessment of Acacia Koa Forest Health across Environmental Gradients in Hawai‘i Using Fine Resolution Remote Sensing and GIS

PubMed Central

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B.

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai‘ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600–1,000 m asl in the island of Kaua‘i, which correspond to gradients of temperature and rainfall ranging from 17–20 °C mean annual temperature and 750–1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai‘i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species. PMID:22163920

Remote Ischemic Perconditioning to Reduce Reperfusion Injury During Acute ST-Segment-Elevation Myocardial Infarction: A Systematic Review and Meta-Analysis.

PubMed

McLeod, Shelley L; Iansavichene, Alla; Cheskes, Sheldon

2017-05-17

Remote ischemic conditioning (RIC) is a noninvasive therapeutic strategy that uses brief cycles of blood pressure cuff inflation and deflation to protect the myocardium against ischemia-reperfusion injury. The objective of this systematic review was to determine the impact of RIC on myocardial salvage index, infarct size, and major adverse cardiovascular events when initiated before catheterization. Electronic searches of Medline, Embase, and Cochrane Central Register of Controlled Trials were conducted and reference lists were hand searched. Randomized controlled trials comparing percutaneous coronary intervention (PCI) with and without RIC for patients with ST-segment-elevation myocardial infarction were included. Two reviewers independently screened abstracts, assessed quality of the studies, and extracted data. Data were pooled using random-effects models and reported as mean differences and relative risk with 95% confidence intervals. Eleven articles (9 randomized controlled trials) were included with a total of 1220 patients (RIC+PCI=643, PCI=577). Studies with no events were excluded from meta-analysis. The myocardial salvage index was higher in the RIC+PCI group compared with the PCI group (mean difference: 0.08; 95% confidence interval, 0.02-0.14). Infarct size was reduced in the RIC+PCI group compared with the PCI group (mean difference: -2.46; 95% confidence interval, -4.66 to -0.26). Major adverse cardiovascular events were lower in the RIC+PCI group (9.5%) compared with the PCI group (17.0%; relative risk: 0.57; 95% confidence interval, 0.40-0.82). RIC appears to be a promising adjunctive treatment to PCI for the prevention of reperfusion injury in patients with ST-segment-elevation myocardial infarction; however, additional high-quality research is required before a change in practice can be considered. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Predictors of Current and Longer-Term Patterns of Abundance of American Pikas (Ochotona princeps) across a Leading-Edge Protected Area

PubMed Central

Moyer-Horner, Lucas; Beever, Erik A.; Johnson, Douglas H.; Biel, Mark; Belt, Jami

2016-01-01

American pikas (Ochotona princeps) have been heralded as indicators of montane-mammal response to contemporary climate change. Pikas no longer occupy the driest and lowest-elevation sites in numerous parts of their geographic range. Conversely, pikas have exhibited higher rates of occupancy and persistence in Rocky Mountain and Sierra Nevada montane ‘mainlands’. Research and monitoring efforts on pikas across the western USA have collectively shown the nuance and complexity with which climate will often act on species in diverse topographic and climatic contexts. However, to date no studies have investigated habitat, distribution, and abundance of pikas across hundreds of sites within a remote wilderness area. Additionally, relatively little is known about whether climate acts most strongly on pikas through direct or indirect (e.g., vegetation-mediated) mechanisms. During 2007–2009, we collectively hiked >16,000 km throughout the 410,077-ha Glacier National Park, Montana, USA, in an effort to identify topographic, microrefugial, and vegetative characteristics predictive of pika abundance. We identified 411 apparently pika-suitable habitat patches with binoculars (in situ), and surveyed 314 of them for pika signs. Ranking of alternative logistic-regression models based on AICc scores revealed that short-term pika abundances were positively associated with intermediate elevations, greater cover of mosses, and taller forbs, and decreased each year, for a total decline of 68% during the three-year study; whereas longer-term abundances were associated only with static variables (longitude, elevation, gradient) and were lower on north-facing slopes. Earlier Julian date and time of day of the survey (i.e., midday vs. not) were associated with lower observed pika abundance. We recommend that wildlife monitoring account for this seasonal and diel variation when surveying pikas. Broad-scale information on status and abundance determinants of montane mammals, especially for remote protected areas, is crucial for land and wildlife-resource managers trying to anticipate mammalian responses to climate change. PMID:27902732

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Remote measurement methods for 3-D modeling purposes using BAE Systems' Software

NASA Astrophysics Data System (ADS)

Walker, Stewart; Pietrzak, Arleta

2015-06-01

Efficient, accurate data collection from imagery is the key to an economical generation of useful geospatial products. Incremental developments of traditional geospatial data collection and the arrival of new image data sources cause new software packages to be created and existing ones to be adjusted to enable such data to be processed. In the past, BAE Systems' digital photogrammetric workstation, SOCET SET®, met fin de siècle expectations in data processing and feature extraction. Its successor, SOCET GXP®, addresses today's photogrammetric requirements and new data sources. SOCET GXP is an advanced workstation for mapping and photogrammetric tasks, with automated functionality for triangulation, Digital Elevation Model (DEM) extraction, orthorectification and mosaicking, feature extraction and creation of 3-D models with texturing. BAE Systems continues to add sensor models to accommodate new image sources, in response to customer demand. New capabilities added in the latest version of SOCET GXP facilitate modeling, visualization and analysis of 3-D features.

Risk of Herpes Zoster and Disseminated Varicella Zoster in Patients Taking Immunosuppressant Drugs at the Time of Zoster Vaccination.

PubMed

Cheetham, T Craig; Marcy, S Michael; Tseng, Hung-Fu; Sy, Lina S; Liu, In-Lu Amy; Bixler, Felicia; Baxter, Roger; Donahue, James G; Naleway, Allison L; Jacobsen, Steven J

2015-07-01

To determine the risks associated with zoster vaccine when administered to patients taking immunosuppressant medications. Patients enrolled in 1 of 7 managed care organizations affiliated with the Vaccine Safety Datalink between January 1, 2006, and December 31, 2009, were eligible. The exposure of interest was zoster vaccination in patients with current or remote immunosuppressant drug use. The primary outcomes were disseminated varicella zoster virus (VZV) and herpes zoster in the 42 days after vaccination. Automated data were collected on immunosuppressant drugs and baseline medical conditions. A logistic regression model using inverse probability treatment weights was used to estimate the odds of developing VZV or herpes zoster. A total of 14,554 individuals had an immunosuppressant medication dispensed around the time of vaccination, including 4826 with current use and 9728 with remote use. Most patients were taking low-dose corticosteroids. No cases of disseminated VZV were found in the current or remote users. The risk of herpes zoster was elevated in the 42 days after vaccination in current vs remote users (adjusted odds ratio, 2.99; 95% CI, 1.58-5.70). We found that patients taking immunosuppressant medications at the time of vaccination had a modest increased risk of herpes zoster in the 42 days after vaccination. The development of herpes zoster within 42 days after vaccination suggests that this is more likely due to reactivation of latent zoster virus than dissemination of the vaccine-derived varicella virus. These findings support the current zoster vaccination guidelines. Copyright © 2015 Mayo Foundation for Medical Education and Research. All rights reserved.

Ecological Model to Predict Potential Habitats of Oncomelania hupensis, the Intermediate Host of Schistosoma japonicum in the Mountainous Regions, China.

PubMed

Zhu, Hong-Ru; Liu, Lu; Zhou, Xiao-Nong; Yang, Guo-Jing

2015-01-01

Schistosomiasis japonica is a parasitic disease that remains endemic in seven provinces in the People's Republic of China (P.R. China). One of the most important measures in the process of schistosomiasis elimination in P.R. China is control of Oncomelania hupensis, the unique intermediate host snail of Schistosoma japonicum. Compared with plains/swamp and lake regions, the hilly/mountainous regions of schistosomiasis endemic areas are more complicated, which makes the snail survey difficult to conduct precisely and efficiently. There is a pressing call to identify the snail habitats of mountainous regions in an efficient and cost-effective manner. Twelve out of 56 administrative villages distributed with O. hupensis in Eryuan, Yunnan Province, were randomly selected to set up the ecological model. Thirty out of the rest of 78 villages (villages selected for building model were excluded from the villages for validation) in Eryuan and 30 out of 89 villages in Midu, Yunnan Province were selected via a chessboard method for model validation, respectively. Nine-year-average Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) as well as Digital Elevation Model (DEM) covering Eryuan and Midu were extracted from MODIS and ASTER satellite images, respectively. Slope, elevation and the distance from every village to its nearest stream were derived from DEM. Suitable survival environment conditions for snails were defined by comparing historical snail presence data and remote sensing derived images. According to the suitable conditions for snails, environment factors, i.e. NDVI, LST, elevation, slope and the distance from every village to its nearest stream, were integrated into an ecological niche model to predict O. hupensis potential habitats in Eryuan and Midu. The evaluation of the model was assessed by comparing the model prediction and field investigation. Then, the consistency rate of model validation was calculated in Eryuan and Midu Counties, respectively. The final ecological niche model for potential O. hupensis habitats prediction comprised the following environmental factors, namely: NDVI (≥ 0.446), LST (≥ 22.70°C), elevation (≤ 2,300 m), slope (≤ 11°) and the distance to nearest stream (≤ 1,000 m). The potential O. hupensis habitats in Eryuan distributed in the Lancang River basin and O. hupensis in Midu shows a trend of clustering in the north and spotty distribution in the south. The consistency rates of the ecological niche model in Eryuan and Midu were 76.67% and 83.33%, respectively. The ecological niche model integrated with NDVI, LST, elevation, slope and distance from every village to its nearest stream adequately predicted the snail habitats in the mountainous regions.

Effect of surface texture and structure on the development of stable fluvial armors

NASA Astrophysics Data System (ADS)

Bertin, Stephane; Friedrich, Heide

2018-04-01

Stable fluvial armors are found in river systems under conditions of partial sediment transport and limited sediment supply, a common occurrence in nature. Stable armoring is also readily recreated in experimental flumes. Initially, this bed stabilizing phenomenon was examined for different flow discharges and solely related to surface coarsening and bedload transport reduction. The models developed suggest a specific armor composition (i.e., texture) dependent on the parent bed material and formative discharge. Following developments in topographic remote sensing, recent research suggests that armor structure is an important control on bed stability and roughness. In this paper, replicated flume runs during which digital elevation models (DEMs) were collected from both exposed and flooded gravel beds are used to interpret armoring manifestations and to assess their replicability. A range of methodologies was used for the analysis, providing information on (i) surface grain size and orientation, (ii) bed-elevation distributions, (iii) the spatial coherence of the elevations at the grain-scale, (iv) surface slope and aspect, (v) grain imbrication and (vi) the spatial variability in DEM properties. The bed-surface topography was found to be more responsive than bed-material size to changes in flow strength. Our experimental results also provide convincing evidence that gravel-beds' response to water-work during parallel degradation is unique (i.e., replicable) given the formative parameters. Based on this finding, relationships between the armors' properties and formative parameters are proposed, and are supported by adding extensive data from previous research.

High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.

PubMed

Wang, Bin; Waters, Cathy; Orgill, Susan; Gray, Jonathan; Cowie, Annette; Clark, Anthony; Liu, De Li

2018-07-15

Efficient and effective modelling methods to assess soil organic carbon (SOC) stock are central in understanding the global carbon cycle and informing related land management decisions. However, mapping SOC stocks in semi-arid rangelands is challenging due to the lack of data and poor spatial coverage. The use of remote sensing data to provide an indirect measurement of SOC to inform digital soil mapping has the potential to provide more reliable and cost-effective estimates of SOC compared with field-based, direct measurement. Despite this potential, the role of remote sensing data in improving the knowledge of soil information in semi-arid rangelands has not been fully explored. This study firstly investigated the use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths (0-5cm and 0-30cm) in semi-arid rangelands of eastern Australia. Overall, model performance statistics showed that random forest (RF) and boosted regression trees (BRT) models performed better than support vector machine (SVM). The models obtained moderate results with R 2 of 0.32 for SOC stock at 0-5cm and 0.44 at 0-30cm, RMSE of 3.51MgCha -1 at 0-5cm and 9.16MgCha -1 at 0-30cm without considering SFC covariates. In contrast, by including SFC, the model accuracy for predicting SOC stock improved by 7.4-12.7% at 0-5cm, and by 2.8-5.9% at 0-30cm, highlighting the importance of including SFC to enhance the performance of the three modelling techniques. Furthermore, our models produced a more accurate and higher resolution digital SOC stock map compared with other available mapping products for the region. The data and high-resolution maps from this study can be used for future soil carbon assessment and monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Landscape determinants and remote sensing of anopheline mosquito larval habitats in the western Kenya highlands.

PubMed

Mushinzimana, Emmanuel; Munga, Stephen; Minakawa, Noboru; Li, Li; Feng, Chen-Chieng; Bian, Ling; Kitron, Uriel; Schmidt, Cindy; Beck, Louisa; Zhou, Guofa; Githeko, Andrew K; Yan, Guiyun

2006-02-16

In the past two decades the east African highlands have experienced several major malaria epidemics. Currently there is a renewed interest in exploring the possibility of anopheline larval control through environmental management or larvicide as an additional means of reducing malaria transmission in Africa. This study examined the landscape determinants of anopheline mosquito larval habitats and usefulness of remote sensing in identifying these habitats in western Kenya highlands. Panchromatic aerial photos, Ikonos and Landsat Thematic Mapper 7 satellite images were acquired for a study area in Kakamega, western Kenya. Supervised classification of land-use and land-cover and visual identification of aquatic habitats were conducted. Ground survey of all aquatic habitats was conducted in the dry and rainy seasons in 2003. All habitats positive for anopheline larvae were identified. The retrieved data from the remote sensors were compared to the ground results on aquatic habitats and land-use. The probability of finding aquatic habitats and habitats with Anopheles larvae were modelled based on the digital elevation model and land-use types. The misclassification rate of land-cover types was 10.8% based on Ikonos imagery, 22.6% for panchromatic aerial photos and 39.2% for Landsat TM 7 imagery. The Ikonos image identified 40.6% of aquatic habitats, aerial photos identified 10.6%, and Landsate TM 7 image identified 0%. Computer models based on topographic features and land-cover information obtained from the Ikonos image yielded a misclassification rate of 20.3-22.7% for aquatic habitats, and 18.1-25.1% for anopheline-positive larval habitats. One-metre spatial resolution Ikonos images combined with computer modelling based on topographic land-cover features are useful tools for identification of anopheline larval habitats, and they can be used to assist to malaria vector control in western Kenya highlands.

Recent Changes in Tree Species Abundance: Patterns, Trends, and Drivers Across Northeastern US Forests

NASA Astrophysics Data System (ADS)

Gudex-Cross, D.; Pontius, J.; Adams, A.

2017-12-01

Monitoring trends in the abundance and distribution of tree species is essential to understanding potential impacts of climate change on forested ecosystems. Related studies to date have largely focused on modeling distributional shifts according to future climate scenarios or used field inventory data to examine compositional changes across broader landscapes. Here, we leverage a novel remote sensing technique that utilizes field data, multitemporal Landsat imagery, and spectral unmixing to model regional changes in the abundance (percent basal area) of key northeastern US species over a 30-year period (1985-2015). We examine patterns in how species abundance has changed, as well as their relationship with climate, landscape, and soil characteristics using spatial regression models. Results show significant declines in overall abundance for sugar maple ( 8.6% 30-yr loss), eastern hemlock ( 7.8% 30-yr loss), balsam fir ( 5.0% 30-yr loss), and red spruce ( 3.8% total 30-yr loss). Species that saw significant increasing abundance include American beech ( 7.0% 30-yr gain) and red maple ( 2.5% 30-yr gain). However, these changes were not consistent across the landscape. For example, red spruce is increasing at upper elevations with concurrent losses in balsam fir and birch species. Similarly, sugar maple decreases are concentrated at lower elevations, likely due to increases in American beech. Various abiotic factors were significantly associated with changes in species composition including landscape position (e.g. longitude, elevation, and heat load index) and ecologically-relevant climate variables (e.g. growing season precipitation and annual temperature range). Interestingly, there was a stronger relationship in abundance changes across longitudes, rather than latitudes or elevations as predicted in modeled species migration scenarios.These results indicate that the dominant composition of northeastern forests is changing in ways that run counter to accepted successional patterns and land use history effects. We hypothesize that climate change and other anthropogenic stress agents (e.g. acid deposition legacy) are likely altering the competitive relationships among co-occurring species, with potential implications for forest management and ecosystem modeling efforts.

Anisotropic Scattering Shadow Compensation Method for Remote Sensing Image with Consideration of Terrain

NASA Astrophysics Data System (ADS)

Wang, Qiongjie; Yan, Li

2016-06-01

With the rapid development of sensor networks and earth observation technology, a large quantity of high resolution remote sensing data is available. However, the influence of shadow has become increasingly greater due to the higher resolution shows more complex and detailed land cover, especially under the shadow. Shadow areas usually have lower intensity and fuzzy boundary, which make the images hard to interpret automatically. In this paper, a simple and effective shadow (including soft shadow) detection and compensation method is proposed based on normal data, Digital Elevation Model (DEM) and sun position. First, we use high accuracy DEM and sun position to rebuild the geometric relationship between surface and sun at the time the image shoot and get the hard shadow boundary and sky view factor (SVF) of each pixel. Anisotropic scattering assumption is accepted to determine the soft shadow factor mainly affected by diffuse radiation. Finally, an easy radiation transmission model is used to compensate the shadow area. Compared with the spectral detection method, our detection method has strict theoretical basis, reliable compensation result and minor affected by the image quality. The compensation strategy can effectively improve the radiation intensity of shadow area, reduce the information loss brought by shadow and improve the robustness and efficiency of the classification algorithms.

Can Satellite Remote Sensing be Applied in Geological Mapping in Tropics?

NASA Astrophysics Data System (ADS)

Magiera, Janusz

2018-03-01

Remote sensing (RS) techniques are based on spectral data registered by RS scanners as energy reflected from the Earth's surface or emitted by it. In "geological" RS the reflectance (or emittence) should come from rock or sediment. The problem in tropical and subtropical areas is a dense vegetation. Spectral response from the rocks and sediments is gathered only from the gaps among the trees and shrubs. Images of high resolution are appreciated here, therefore. New generation of satellites and scanners (Digital Globe WV2, WV3 and WV4) yield imagery of spatial resolution of 2 m and up to 16 spectral bands (WV3). Images acquired by Landsat (TM, ETM+, OLI) and Sentinel 2 have good spectral resolution too (6-12 bands in visible and infrared) and, despite lower spatial resolution (10-60 m of pixel size) are useful in extracting lithological information too. Lithological RS map may reveal good precision (down to a single rock or outcrop of a meter size). Supplemented with the analysis of Digital Elevation Model and high resolution ortophotomaps (Google Maps, Bing etc.) allows for quick and cheap mapping of unsurveyed areas.

Application research for 4D technology in flood forecasting and evaluation

NASA Astrophysics Data System (ADS)

Li, Ziwei; Liu, Yutong; Cao, Hongjie

1998-08-01

In order to monitor the region which disaster flood happened frequently in China, satisfy the great need of province governments for high accuracy monitoring and evaluated data for disaster and improve the efficiency for repelling disaster, under the Ninth Five-year National Key Technologies Programme, the method was researched for flood forecasting and evaluation using satellite and aerial remoted sensed image and land monitor data. The effective and practicable flood forecasting and evaluation system was established and DongTing Lake was selected as the test site. Modern Digital photogrammetry, remote sensing and GIS technology was used in this system, the disastrous flood could be forecasted and loss can be evaluated base on '4D' (DEM -- Digital Elevation Model, DOQ -- Digital OrthophotoQuads, DRG -- Digital Raster Graph, DTI -- Digital Thematic Information) disaster background database. The technology of gathering and establishing method for '4D' disaster environment background database, application technology for flood forecasting and evaluation based on '4D' background data and experimental results for DongTing Lake test site were introduced in detail in this paper.

Comparison of Landsat-8, ASTER and Sentinel 1 satellite remote sensing data in automatic lineaments extraction: A case study of Sidi Flah-Bouskour inlier, Moroccan Anti Atlas

NASA Astrophysics Data System (ADS)

Adiri, Zakaria; El Harti, Abderrazak; Jellouli, Amine; Lhissou, Rachid; Maacha, Lhou; Azmi, Mohamed; Zouhair, Mohamed; Bachaoui, El Mostafa

2017-12-01

Certainly, lineament mapping occupies an important place in several studies, including geology, hydrogeology and topography etc. With the help of remote sensing techniques, lineaments can be better identified due to strong advances in used data and methods. This allowed exceeding the usual classical procedures and achieving more precise results. The aim of this work is the comparison of ASTER, Landsat-8 and Sentinel 1 data sensors in automatic lineament extraction. In addition to image data, the followed approach includes the use of the pre-existing geological map, the Digital Elevation Model (DEM) as well as the ground truth. Through a fully automatic approach consisting of a combination of edge detection algorithm and line-linking algorithm, we have found the optimal parameters for automatic lineament extraction in the study area. Thereafter, the comparison and the validation of the obtained results showed that the Sentinel 1 data are more efficient in restitution of lineaments. This indicates the performance of the radar data compared to those optical in this kind of study.

Control System and Tests for the 13.2-m RAEGE Antenna at Yebes

NASA Astrophysics Data System (ADS)

de Vicente, P.; Bolaño, R.; Barbas, L.

2014-12-01

The RAEGE network is being deployed. The antenna at the Yebes Observatory is the first one in the network, and its construction finished in October 2013. During the construction phase, the remote control system for the antenna and the receivers was developed, and during the commisioning time the software was tested by MT-Mechatronics. As a result, both the control system from MT-Mechatronics and the remote control system by the IGN-CDT were debugged. We have tested the basic functionality of the antenna operated as a single dish telescope. First light at S, X, and Ka band was achieved on February 10^{th}. Afterwards a pointing model for the whole sky was determined, together with an optimum focus position as a function of elevation. Commisioning is not finished yet, and the antenna will be totally delivered to the IGN-CDT in the next weeks. VLBI equipment will be installed within three months, and VLBI observations are foreseen by the end of 2014. In this paper, we provide an overview of the control system and of the main results achieved.

Overview of the NASA tropospheric environmental quality remote sensing program

NASA Technical Reports Server (NTRS)

Allario, F.; Ayers, W. G.; Hoell, J. M.

1979-01-01

This paper will summarize the current NASA Tropospheric Environmental Quality Remote Sensing Program for studying the global and regional troposphere from space, airborne and ground-based platforms. As part of the program to develop remote sensors for utilization from space, NASA has developed a series of passive and active remote sensors which have undergone field test measurements from airborne and ground platforms. Recent measurements with active lidar and passive gas filter correlation and infrared heterodyne techniques will be summarized for measurements of atmospheric aerosols, CO, SO2, O3, and NH3. These measurements provide the data base required to assess the sensitivity of remote sensors for applications to urban and regional field measurement programs. Studies of Earth Observation Satellite Systems are currently being performed by the scientific community to assess the capability of satellite imagery to detect regions of elevated pollution in the troposphere. The status of NASA sponsored research efforts in interpreting satellite imagery for determining aerosol loadings over land and inland bodies of water will be presented, and comments on the potential of these measurements to supplement in situ and airborne remote sensors in detecting regional haze will be made.

Evolution of Subaerial Coastal Fluvial Delta Island Topography into Multiple Stable States Under Influence of Vegetation and Stochastic Hydrology

NASA Astrophysics Data System (ADS)

Moffett, K. B.; Smith, B. C.; O'Connor, M.; Mohrig, D. C.

2014-12-01

Coastal fluvial delta morphodynamics are prominently controlled by external fluvial sediment and water supplies; however, internal sediment-water-vegetation feedbacks are now being proposed as potentially equally significant in organizing and maintaining the progradation and aggradation of such systems. The time scales of fluvial and climate influences on these feedbacks, and of their responses, are also open questions. Historical remote sensing study of the Wax Lake Delta model system (Louisiana, USA) revealed trends in the evolution of the subaerial island surfaces from a non-systematic arrangement of elevations to a discrete set of levees and intra-island platforms with distinct vegetation types, designated as high marsh, low marsh, and mudflat habitat. We propose that this elevation zonation is consistent with multiple stable state theory, e.g. as applied to tidal salt marsh systems but not previously to deltas. According to zonally-distributed sediment core analyses, differentiation of island elevations was not due to organic matter accumulation as in salt marshes, but rather by differential mineral sediment accumulation with some organic contributions. Mineral sediment accumulation rates suggested that elevation growth was accelerating or holding steady over time, at least to date in this young delta, in contrast to theory suggesting rates should slow as elevation increases above mean water level. Hydrological analysis of island flooding suggested a prominent role of stochastic local storm events in raising island water levels and supplying mineral sediment to the subaerial island surfaces at short time scales; over longer time scales, the relative influences of local storms and inland/regional floods on the coupled sediment-water-vegetation system of the subaerial delta island surfaces remain the subject of ongoing study. These results help provide an empirical foundation for the next generation of coupled sediment-water-vegetation modeling and theory.

UAS-Borne Photogrammetry for Surface Topographic Characterization: A Ground-Truth Baseline for Future Change Detection and Refinement of Scaled Remotely-Sensed Datasets

NASA Astrophysics Data System (ADS)

Coppersmith, R.; Schultz-Fellenz, E. S.; Sussman, A. J.; Vigil, S.; Dzur, R.; Norskog, K.; Kelley, R.; Miller, L.

2015-12-01

While long-term objectives of monitoring and verification regimes include remote characterization and discrimination of surficial geologic and topographic features at sites of interest, ground truth data is required to advance development of remote sensing techniques. Increasingly, it is desirable for these ground-based or ground-proximal characterization methodologies to be as nimble, efficient, non-invasive, and non-destructive as their higher-altitude airborne counterparts while ideally providing superior resolution. For this study, the area of interest is an alluvial site at the Nevada National Security Site intended for use in the Source Physics Experiment's (Snelson et al., 2013) second phase. Ground-truth surface topographic characterization was performed using a DJI Inspire 1 unmanned aerial system (UAS), at very low altitude (< 5-30m AGL). 2D photographs captured by the standard UAS camera payload were imported into Agisoft Photoscan to create three-dimensional point clouds. Within the area of interest, careful installation of surveyed ground control fiducial markers supplied necessary targets for field collection, and information for model georectification. The resulting model includes a Digital Elevation Model derived from 2D imagery. It is anticipated that this flexible and versatile characterization process will provide point cloud data resolution equivalent to a purely ground-based LiDAR scanning deployment (e.g., 1-2cm horizontal and vertical resolution; e.g., Sussman et al., 2012; Schultz-Fellenz et al., 2013). In addition to drastically increasing time efficiency in the field, the UAS method also allows for more complete coverage of the study area when compared to ground-based LiDAR. Comparison and integration of these data with conventionally-acquired airborne LiDAR data from a higher-altitude (~ 450m) platform will aid significantly in the refinement of technologies and detection capabilities of remote optical systems to identify and detect surface geologic and topographic signatures of interest. This work includes a preliminary comparison of surface signatures detected from varying standoff distances to assess current sensor performance and benefits.

Remote Sensing of Martian Terrain Hazards via Visually Salient Feature Detection

NASA Astrophysics Data System (ADS)

Al-Milli, S.; Shaukat, A.; Spiteri, C.; Gao, Y.

2014-04-01

The main objective of the FASTER remote sensing system is the detection of rocks on planetary surfaces by employing models that can efficiently characterise rocks in terms of semantic descriptions. The proposed technique abates some of the algorithmic limitations of existing methods with no training requirements, lower computational complexity and greater robustness towards visual tracking applications over long-distance planetary terrains. Visual saliency models inspired from biological systems help to identify important regions (such as rocks) in the visual scene. Surface rocks are therefore completely described in terms of their local or global conspicuity pop-out characteristics. These local and global pop-out cues are (but not limited to); colour, depth, orientation, curvature, size, luminance intensity, shape, topology etc. The currently applied methods follow a purely bottom-up strategy of visual attention for selection of conspicuous regions in the visual scene without any topdown control. Furthermore the choice of models used (tested and evaluated) are relatively fast among the state-of-the-art and have very low computational load. Quantitative evaluation of these state-ofthe- art models was carried out using benchmark datasets including the Surrey Space Centre Lab Testbed, Pangu generated images, RAL Space SEEKER and CNES Mars Yard datasets. The analysis indicates that models based on visually salient information in the frequency domain (SRA, SDSR, PQFT) are the best performing ones for detecting rocks in an extra-terrestrial setting. In particular the SRA model seems to be the most optimum of the lot especially that it requires the least computational time while keeping errors competitively low. The salient objects extracted using these models can then be merged with the Digital Elevation Models (DEMs) generated from the same navigation cameras in order to be fused to the navigation map thus giving a clear indication of the rock locations.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

A new bed elevation model for the Weddell Sea sector of the West Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Jeofry, Hafeez; Ross, Neil; Corr, Hugh F. J.; Li, Jilu; Morlighem, Mathieu; Gogineni, Prasad; Siegert, Martin J.

2018-04-01

We present a new digital elevation model (DEM) of the bed, with a 1 km gridding, of the Weddell Sea (WS) sector of the West Antarctic Ice Sheet (WAIS). The DEM has a total area of ˜ 125 000 km2 covering the Institute, Möller and Foundation ice streams, as well as the Bungenstock ice rise. In comparison with the Bedmap2 product, our DEM includes new aerogeophysical datasets acquired by the Center for Remote Sensing of Ice Sheets (CReSIS) through the NASA Operation IceBridge (OIB) program in 2012, 2014 and 2016. We also improve bed elevation information from the single largest existing dataset in the region, collected by the British Antarctic Survey (BAS) Polarimetric radar Airborne Science Instrument (PASIN) in 2010-2011, from the relatively crude measurements determined in the field for quality control purposes used in Bedmap2. While the gross form of the new DEM is similar to Bedmap2, there are some notable differences. For example, the position and size of a deep subglacial trough (˜ 2 km below sea level) between the ice-sheet interior and the grounding line of the Foundation Ice Stream have been redefined. From the revised DEM, we are able to better derive the expected routing of basal water and, by comparison with that calculated using Bedmap2, we are able to assess regions where hydraulic flow is sensitive to change. Given the potential vulnerability of this sector to ocean-induced melting at the grounding line, especially in light of the improved definition of the Foundation Ice Stream trough, our revised DEM will be of value to ice-sheet modelling in efforts to quantify future glaciological changes in the region and, from this, the potential impact on global sea level. The new 1 km bed elevation product of the WS sector can be found at https://doi.org/10.5281/zenodo.1035488.

Large-scale hydrological model river storage and discharge correction using a satellite altimetry-based discharge product

NASA Astrophysics Data System (ADS)

Emery, Charlotte Marie; Paris, Adrien; Biancamaria, Sylvain; Boone, Aaron; Calmant, Stéphane; Garambois, Pierre-André; Santos da Silva, Joecila

2018-04-01

Land surface models (LSMs) are widely used to study the continental part of the water cycle. However, even though their accuracy is increasing, inherent model uncertainties can not be avoided. In the meantime, remotely sensed observations of the continental water cycle variables such as soil moisture, lakes and river elevations are more frequent and accurate. Therefore, those two different types of information can be combined, using data assimilation techniques to reduce a model's uncertainties in its state variables or/and in its input parameters. The objective of this study is to present a data assimilation platform that assimilates into the large-scale ISBA-CTRIP LSM a punctual river discharge product, derived from ENVISAT nadir altimeter water elevation measurements and rating curves, over the whole Amazon basin. To deal with the scale difference between the model and the observation, the study also presents an initial development for a localization treatment that allows one to limit the impact of observations to areas close to the observation and in the same hydrological network. This assimilation platform is based on the ensemble Kalman filter and can correct either the CTRIP river water storage or the discharge. Root mean square error (RMSE) compared to gauge discharges is globally reduced until 21 % and at Óbidos, near the outlet, RMSE is reduced by up to 52 % compared to ENVISAT-based discharge. Finally, it is shown that localization improves results along the main tributaries.

NASA Remote Sensing Research as Applied to Archaeology

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Thomas, Michael R.

2002-01-01

The use of remotely sensed images is not new to archaeology. Ever since balloons and airplanes first flew cameras over archaeological sites, researchers have taken advantage of the elevated observation platforms to understand sites better. When viewed from above, crop marks, soil anomalies and buried features revealed new information that was not readily visible from ground level. Since 1974 and initially under the leadership of Dr. Tom Sever, NASA's Stennis Space Center, located on the Mississippi Gulf Coast, pioneered and expanded the application of remote sensing to archaeological topics, including cultural resource management. Building on remote sensing activities initiated by the National Park Service, archaeologists increasingly used this technology to study the past in greater depth. By the early 1980s, there were sufficient accomplishments in the application of remote sensing to anthropology and archaeology that a chapter on the subject was included in fundamental remote sensing references. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, or nearing deployment, offer significantly finer spatial and spectral resolutions than were previously available. Paired with new techniques of image analysis, this technology may make the direct detection of archaeological sites a realistic goal.

Modelling coastal processes by means of innovative integration of remote sensing and modelling analysis

NASA Astrophysics Data System (ADS)

Taramelli, A.; Zanuttigh, B.; Zucca, F.; Dejana, M.; Valentini, E.

2011-12-01

Coastal marine and inland landforms are dynamic systems undergoing adjustments in form at different time and space scales in response to varying conditions external to the system. Coastal emerged and shallow submerged nearshore areas, affected by short-term perturbations, return to their pre-disturbance morphology and generally reach a dynamic equilibrium. Worldwide in the last century we have experienced in increased coastal inundation, erosion and ecosystem losses. However, erosion can result from a number of other factors, such as altered wind and current patterns, high-energy waves, and reduced fluvial sediment inputs. Direct impacts of human activities, including reclamation of coastal wetlands, deforestation, damming, channelization, diversions of coastal waterways, construction of seawalls and other structures, alter circulation patterns. Also indirect human impacts such as land-uses changes through time (eg. from agricultural to industrial use) have affected coastal ecosystems. The objective of this research is to propose innovative remote sensing applications to monitor specific coastal processes in order to use them within a physical modelling to quantify and model their time evolution. The research was applied in two dynamic and densely populated deltas and coastal areas (the Po and the Plymouth delta) by combining multi-sensor spaceborne remote sensing (SAR and OPTICAL) to physical modelling. The main results are: a) deformation and spatiotemporal variations maps in coastal morphology with a special focus to point out the temporal subsidence evolution, b) inter and intra-annual change detection maps that are both used a to feed a coastal physical modelling (MIKE 21). The basic strategy was to highlight the different components of the coastal system environment through: 1) deformation and spatio-temporal variations maps of coastal morphology, by the use of time-stack from 1992 up today of ESA SAR data (ERS-1/2 and ENVISAT-ASAR sensors) were used to produce deformation maps and to point out the temporal evolution and 2) multitemporal hyperspectral endmembers fractions map of coastal morphology, 3) numerical model well-established through remote sensed based procedures and results in order to produce spatio-temporal scenario in coastal areas. The objective was to locate and characterize important coastal indicators for different regions using multitemporal data from the multi-hyperspectral sensors, as well as topographic elevation, SAR and derived products (eg. coherence) data. The identification of different indicators was based on land spectral properties, topography/landforms (low topography), disturbed areas (agricultural, construction), and vegetation distribution. Moreover, the indicators were assessed at seasonal and interannual time scales over two temporal decades horizons starting from 1990 and 2000.

An improved method to represent DEM uncertainty in glacial lake outburst flood propagation using stochastic simulations

NASA Astrophysics Data System (ADS)

Watson, Cameron S.; Carrivick, Jonathan; Quincey, Duncan

2015-10-01

Modelling glacial lake outburst floods (GLOFs) or 'jökulhlaups', necessarily involves the propagation of large and often stochastic uncertainties throughout the source to impact process chain. Since flood routing is primarily a function of underlying topography, communication of digital elevation model (DEM) uncertainty should accompany such modelling efforts. Here, a new stochastic first-pass assessment technique was evaluated against an existing GIS-based model and an existing 1D hydrodynamic model, using three DEMs with different spatial resolution. The analysis revealed the effect of DEM uncertainty and model choice on several flood parameters and on the prediction of socio-economic impacts. Our new model, which we call MC-LCP (Monte Carlo Least Cost Path) and which is distributed in the supplementary information, demonstrated enhanced 'stability' when compared to the two existing methods, and this 'stability' was independent of DEM choice. The MC-LCP model outputs an uncertainty continuum within its extent, from which relative socio-economic risk can be evaluated. In a comparison of all DEM and model combinations, the Shuttle Radar Topography Mission (SRTM) DEM exhibited fewer artefacts compared to those with the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), and were comparable to those with a finer resolution Advanced Land Observing Satellite Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) derived DEM. Overall, we contend that the variability we find between flood routing model results suggests that consideration of DEM uncertainty and pre-processing methods is important when assessing flow routing and when evaluating potential socio-economic implications of a GLOF event. Incorporation of a stochastic variable provides an illustration of uncertainty that is important when modelling and communicating assessments of an inherently complex process.

A Study on Integrated Community Based Flood Mitigation with Remote Sensing Technique in Kota Bharu, Kelantan

NASA Astrophysics Data System (ADS)

'Ainullotfi, A. A.; Ibrahim, A. L.; Masron, T.

2014-02-01

This study is conducted to establish a community based flood management system that is integrated with remote sensing technique. To understand local knowledge, the demographic of the local society is obtained by using the survey approach. The local authorities are approached first to obtain information regarding the society in the study areas such as the population, the gender and the tabulation of settlement. The information about age, religion, ethnic, occupation, years of experience facing flood in the area, are recorded to understand more on how the local knowledge emerges. Then geographic data is obtained such as rainfall data, land use, land elevation, river discharge data. This information is used to establish a hydrological model of flood in the study area. Analysis were made from the survey approach to understand the pattern of society and how they react to floods while the analysis of geographic data is used to analyse the water extent and damage done by the flood. The final result of this research is to produce a flood mitigation method with a community based framework in the state of Kelantan. With the flood mitigation that involves the community's understanding towards flood also the techniques to forecast heavy rainfall and flood occurrence using remote sensing, it is hope that it could reduce the casualties and damage that might cause to the society and infrastructures in the study area.

(abstract) Mount Rainier: New Remote Sensing Observations of a Decade Volcano

NASA Technical Reports Server (NTRS)

Realmuto, V. J.; Zebker, H. A.; Frank, D.

1994-01-01

Mount Rainier was selected as a Decade Volcano by the International Association of Volcanology and Chemistry of the Earth's Interior. The purpose of this selection is to focus scientific and public attention on Mount Rainier during the current decade, the United Nations-designated International Decade of Natural Hazard Reduction. The Mount Rainier science plan calls for remote sensing surveys to monitor the volcano. To date, we have conducted airborne surveys with visible and near-infrared, thermal infrared, and interferometric radar instruments. Our preliminary analysis of some night-time time-series thermal infrared survey data sets of the summit suggests that, aside from seasonal variations in snow cover, there have been no qualitative changes in the size or pattern of the summit hot spots. Day-time airborne surveys were done to record the current surface appearance of the volcano and map hydrothermal alteration in the summit region. An interferometric radar survey yielded a high-resolution digital elevation model (DEM) which serves as a base for the registration of the other remote sensing data sets. More importantly, the DEM documents the current topography of glaciers and valleys. Planned biannual radar survey of mount rainier will produce a data set from which seasonal changes in glacier and valley topography can be characterized. Such characterization is essential if we are to recognize geothermally induced changes in snow and ice cover.

Comparison of Bacteria and Color Removal in Two Surface Waters using Nanofiltration

EPA Science Inventory

Small communities typically have small budgets, but big issues to deal with in providing safe drinking water and protecting public health. Communities in remote locations are frequently faced with elevated levels of naturally-occurring organic matter (NOM) that combine with chlo...

Comparison of Bacteria and Color Removal in Two Surface Waters using Nanofiltration

EPA Science Inventory

Small communities typically have small budgets, but big issues to deal with in providing safe drinking water and protecting public health. Communities in remote locations are frequently faced with elevated levels of naturally-occurring organic matter (NOM) that combine with chlor...

IMPACTS OF HISTORIC AND CURRENT-USE CHEMICALS IN WESTERN NATIONAL PARKS

EPA Science Inventory

The Western Airborne Contaminants Assessment Project (WACAP) is an interagency effort to determine if airborne contaminants such as semi-volatile organic compounds (sacs) and metals

(e.g. mercury) are impacting National Parks in the western United States. Remote, high elev...

In situ correlative measurements for the ultraviolet differential absorption lidar and the high spectral resolution lidar air quality remote sensors: 1980 PEPE/NEROS program

NASA Technical Reports Server (NTRS)

Gregory, G. L.; Beck, S. M.; Mathis, J. J., Jr.

1981-01-01

In situ correlative measurements were obtained with a NASA aircraft in support of two NASA airborne remote sensors participating in the Environmental Protection Agency's 1980persistent elevated pollution episode (PEPE) and Northeast regional oxidant study (NEROS) field program in order to provide data for evaluating the capability of two remote sensors for measuring mixing layer height, and ozone and aerosol concentrations in the troposphere during the 1980 PEPE/NEROS program. The in situ aircraft was instrumented to measure temperature, dewpoint temperature, ozone concentrations, and light scattering coefficient. In situ measurements for ten correlative missions are given and discussed. Each data set is presented in graphical and tabular format aircraft flight plans are included.

Susceptibility Evaluation and Mapping of CHINA'S Landslide Disaster Based on Multi-Temporal Ground and Remote Sensing Satellite Data

NASA Astrophysics Data System (ADS)

Liu, C.; Li, W.; Lu, P.; Sang, K.; Hong, Y.; Li, R.

2012-07-01

Under the circumstances of global climate change, nowadays landslide occurs in China more frequently than ever before. The landslide hazard and risk assessment remains an international focus on disaster prevention and mitigation. It is also an important approach for compiling and quantitatively characterizing landslide damages. By integrating empirical models for landslide disasters, and through multi-temporal ground data and remote sensing data, this paper will perform a landslide susceptibility assessment throughout China. A landslide susceptibility (LS) map will then be produced, which can be used for disaster evaluation, and provide basis for analyzing China's major landslide-affected regions. Firstly, based on previous research of landslide susceptibility assessment, this paper collects and analyzes the historical landslide event data (location, quantity and distribution) of past sixty years in China as a reference for late-stage studies. Secondly, this paper will make use of regional GIS data of the whole country provided by the National Geomatics Centre and China Meteorological Administration, including regional precipitation data, and satellite remote sensing data such as from TRMM and MODIS. By referring to historical landslide data of past sixty years, it is possible to develop models for assessing LS, including producing empirical models for prediction, and discovering both static and dynamic key factors, such as topography and landforms (elevation, curvature and slope), geologic conditions (lithology of the strata), soil type, vegetation cover, hydrological conditions (flow distribution). In addition, by analyzing historical data and combining empirical models, it is possible to synthesize a regional statistical model and perform a LS assessment. Finally, based on the 1km×1km grid, the LS map is then produced by ANN learning and multiplying the weighted factor layers. The validation is performed with reference to the frequency and distribution of historical data. This research reveals the spatiotemporal distribution of landslide disasters in China. The study develops a complete algorithm of data collecting, processing, modelling and synthesizing, which fulfils the assessment of landslide susceptibility, and provides theoretical basis for prediction and forecast of landslide disasters throughout China.

Spatially distributed storm runoff modeling using remote sensing and geographic information systems

NASA Astrophysics Data System (ADS)

Melesse, Assefa Mekonnen

Advances in scientific knowledge and new techniques of remote sensing permit a better understanding of the physical land features governing hydrologic processes, and make possible efficient, large-scale hydrologic modeling. The need for land-cover and hydrologic response change detection at a larger scale and at times of the year when hydrologic studies are critical makes satellite imagery the most cost effective, efficient and reliable source of data. The use of a Geographic Information System (GIS) to store, manipulate and visualize these data, and ultimately to estimate runoff from watersheds, has gained increasing attention in recent years. In this work, remotely-sensed data and GIS tools were used to estimate the changes in land-cover, and to estimate runoff response, for three watersheds (Etonia, Econlockhatchee, and S-65A sub-basins) in Florida. Land-use information from Digital Orthophoto Quarter Quadrangles (DOQQ), Landsat Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) were analyzed for the years 1973, 1984, 1990, 1995, and 2000. Spatial distribution of land-cover was assessed over time. The corresponding infiltration excess runoff response of the study areas due to these changes was estimated using the United States Department of Agriculture, Natural Resources Conservation Service Curve Number (USDA-NRCS-CN) method. A Digital Elevation Model (DEM)-GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. The method was tested on a representative watershed (Simms Creek) in the Etonia sub-basin. Simulated and observed runoff volume and hydrographs were compared for 17 storm events. Isolated storms, with volumes of not less than 12.75 mm (0.5 inch) were selected. This is the minimum amount of rainfall volume recommended for the NRCS-CN method. Results show that the model predicts the runoff response of the study area with an average efficiency of 57%. Comparison of the runoff prediction to Snyder's synthetic Unit hydrograph method and TOPMODEL shows the spatially distributed infiltration excess travel time model performs better than both the Snyder's method and TOPMODEL. The model is applicable to ungaged watersheds and useful for predicting runoff hydrographs resulting from changes in the land-cover.

Validation of "AW3D" Global Dsm Generated from Alos Prism

NASA Astrophysics Data System (ADS)

Takaku, Junichi; Tadono, Takeo; Tsutsui, Ken; Ichikawa, Mayumi

2016-06-01

Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM), one of onboard sensors carried by Advanced Land Observing Satellite (ALOS), was designed to generate worldwide topographic data with its optical stereoscopic observation. It has an exclusive ability to perform a triplet stereo observation which views forward, nadir, and backward along the satellite track in 2.5 m ground resolution, and collected its derived images all over the world during the mission life of the satellite from 2006 through 2011. A new project, which generates global elevation datasets with the image archives, was started in 2014. The data is processed in unprecedented 5 m grid spacing utilizing the original triplet stereo images in 2.5 m resolution. As the number of processed data is growing steadily so that the global land areas are almost covered, a trend of global data qualities became apparent. This paper reports on up-to-date results of the validations for the accuracy of data products as well as the status of data coverage in global areas. The accuracies and error characteristics of datasets are analyzed by the comparison with existing global datasets such as Ice, Cloud, and land Elevation Satellite (ICESat) data, as well as ground control points (GCPs) and the reference Digital Elevation Model (DEM) derived from the airborne Light Detection and Ranging (LiDAR).

Urban Density Indices Using Mean Shift-Based Upsampled Elevetion Data

NASA Astrophysics Data System (ADS)

Charou, E.; Gyftakis, S.; Bratsolis, E.; Tsenoglou, T.; Papadopoulou, Th. D.; Vassilas, N.

2015-04-01

Urban density is an important factor for several fields, e.g. urban design, planning and land management. Modern remote sensors deliver ample information for the estimation of specific urban land classification classes (2D indicators), and the height of urban land classification objects (3D indicators) within an Area of Interest (AOI). In this research, two of these indicators, Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) are numerically and automatically derived from high-resolution airborne RGB orthophotos and LiDAR data. In the pre-processing step the low resolution elevation data are fused with the high resolution optical data through a mean-shift based discontinuity preserving smoothing algorithm. The outcome is an improved normalized digital surface model (nDSM) is an upsampled elevation data with considerable improvement regarding region filling and "straightness" of elevation discontinuities. In a following step, a Multilayer Feedforward Neural Network (MFNN) is used to classify all pixels of the AOI to building or non-building categories. For the total surface of the block and the buildings we consider the number of their pixels and the surface of the unit pixel. Comparisons of the automatically derived BCR and FAR indicators with manually derived ones shows the applicability and effectiveness of the methodology proposed.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

River Discharge and Bathymetry Estimation from Hydraulic Inversion of Surface Currents and Water Surface Elevation Observations

NASA Astrophysics Data System (ADS)

Simeonov, J.; Holland, K. T.

2015-12-01

We developed an inversion model for river bathymetry and discharge estimation based on measurements of surface currents, water surface elevation and shoreline coordinates. The model uses a simplification of the 2D depth-averaged steady shallow water equations based on a streamline following system of coordinates and assumes spatially uniform bed friction coefficient and eddy viscosity. The spatial resolution of the predicted bathymetry is related to the resolution of the surface currents measurements. The discharge is determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. The inversion model was tested using in situ and remote sensing measurements of the Kootenai River east of Bonners Ferry, ID. The measurements were obtained in August 2010 when the discharge was about 223 m3/s and the maximum river depth was about 6.5 m. Surface currents covering a 10 km reach with 8 m spatial resolution were estimated from airborne infrared video and were converted to depth-averaged currents using acoustic Doppler current profiler (ADCP) measurements along eight cross-stream transects. The streamwise profile of the water surface elevation was measured using real-time kinematic GPS from a drifting platform. The value of the friction coefficient was obtained from forward calibration simulations that minimized the difference between the predicted and measured velocity and water level along the river thalweg. The predicted along/cross-channel water depth variation was compared to the depth measured with a multibeam echo sounder. The rms error between the measured and predicted depth along the thalweg was found to be about 60cm and the estimated discharge was 5% smaller than the discharge measured by the ADCP.

Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

NASA Astrophysics Data System (ADS)

Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

2013-05-01

Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and transferring locally unknown hydrological process parameters from cold regions mountain environments in Canada. Some soil moisture parameters were calibrated from streamflow observations. Model performance was estimated through comparison with observed streamflow records. Simulations using observed precipitation had negligible representativeness of streamflow (Nash-Sutcliffe coefficient, NS ≈ 0.2), while those using any of the two reanalyses as forcing data had reasonable model performance (NS ≈ 0.7). In spite of the better spatial resolution of the CFSR, the ability to simulate streamflow were not significantly different using either CFSR or ERA-Interim. The modeled water balance shows that snowfall is about 30% of the total precipitation input, but snowmelt superficial runoff comprises about 10% of total runoff. About 75% of all precipitation is infiltrated, and approximately 15% of the losses are attributed to evapotranspiration from soil and lake evaporation.

Developing a hydrological model in the absence of field data

NASA Astrophysics Data System (ADS)

Sproles, E. A.; Orrego Nelson, C.; Kerr, T.; Lopez Aspe, D.

2014-12-01

We present two runoff models that use remotely-sensed snow cover products from the Moderate Resolution Imaging Spectrometer (MODIS) as the first order hydrologic input. These simplistic models are the first step in developing an operational model for the Elqui River watershed located in northern Central Chile (30°S). In this semi-arid region, snow and glacier melt are the dominant hydrologic inputs where annual precipitation is limited to three or four winter events. Unfortunately winter access to the Andean Cordillera where snow accumulates is limited. While a monitoring network to measure snow where it accumulates in the upper elevations is under development, management decisions regarding water resources cannot wait. The two models we present differ in structure. The first applies a Monte Carlo approach to determine relationships between lagged changes in monthly snow cover frequency and monthly discharge. The second is a modified degree-day melt model, utilizing the MODIS snow cover product to determine where and when snow melt occurs. These models are not watershed specific and are applicable in other regions where snow dominates hydrologic inputs, but measurements are minimal.

Void-Filled SRTM Digital Elevation Model of Afghanistan

USGS Publications Warehouse

Chirico, Peter G.; Barrios, Boris

2005-01-01

EXPLANATION The purpose of this data set is to provide a single consistent elevation model to be used for national scale mapping, GIS, remote sensing applications, and natural resource assessments for Afghanistan's reconstruction. For 11 days in February of 2000, the National Aeronautics and Space Administration (NASA), the National Geospatial-Intelligence Agency ian Space Agency (ASI) flew X-band and C-band radar interferometry onboard the Space Shuttle Endeavor. The mission covered the Earth between 60?N and 57?S and will provide interferometric digital elevation models (DEMs) of approximately 80% of the Earth's land mass when processing is complete. The radar-pointing angle was approximately 55? at scene center. Ascending and descending orbital passes generated multiple interferometric data scenes for nearly all areas. Up to eight passes of data were merged to form the final processed Shuttle Radar Topography Mission (SRTM) DEMs. The effect of merging scenes averages elevation values recorded in coincident scenes and reduces, but does not completely eliminate, the amount of area with layover and terrain shadow effects. The most significant form of data processing for the Afghanistan DEM was gap-filling areas where the SRTM data contained a data void. These void areas are as a result of radar shadow, layover, standing water, and other effects of terrain as well as technical radar interferometry phase unwrapping issues. To fill these gaps, topographic contours were digitized from 1:200,000 - scale Soviet General Staff Topographic Maps which date from the middle to late 1980's. Digital contours were gridded to form elevation models for void areas and subsequently were merged with the SRTM data through GIS and image processing techniques. The data contained in this publication includes SRTM DEM quadrangles projected and clipped in geographic coordinates for the entire country. An index of all available SRTM DEM quadrangles is displayed here: Index_Geo_DD.pdf. Also included are quadrangles projected into their appropriate Universal Transverse Mercator (UTM) projection. The country of Afghanistan spans three UTM Zones: Zone 41, Zone 42, and Zone 43. Maps are stored in their respective UTM Zone projection. Indexes of all available SRTM DEM quadrangles in their respective UTM zone are displayed here: Index_UTM_Z41.pdf, Index_UTM_Z42.pdf, Index_UTM_Z43.pdf.

The Upper Mississippi River floodscape: spatial patterns of flood inundation and associated plant community distributions

USGS Publications Warehouse

DeJager, Nathan R.; Rohweder, Jason J.; Yin, Yao; Hoy, Erin E.

2016-01-01

Questions How is the distribution of different plant communities associated with patterns of flood inundation across a large floodplain landscape? Location Thirty-eight thousand nine hundred and seventy hectare of floodplain, spanning 320 km of the Upper Mississippi River (UMR). Methods High-resolution elevation data (Lidar) and 30 yr of daily river stage data were integrated to produce a ‘floodscape’ map of growing season flood inundation duration. The distributions of 16 different remotely sensed plant communities were quantified along the gradient of flood duration. Results Models fitted to the cumulative frequency of occurrence of different vegetation types as a function of flood duration showed that most types exist along a continuum of flood-related occurrence. The diversity of community types was greatest at high elevations (0–10 d of flooding), where both upland and lowland community types were found, as well as at very low elevations (70–180 d of flooding), where a variety of lowland herbaceous communities were found. Intermediate elevations (20–60 d of flooding) tended to be dominated by floodplain forest and had the lowest diversity of community types. Conclusions Although variation in flood inundation is often considered to be the main driver of spatial patterns in floodplain plant communities, few studies have quantified flood–vegetation relationships at broad scales. Our results can be used to identify targets for restoration of historical hydrological regimes or better anticipate hydro-ecological effects of climate change at broad scales.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Multielevation calibration of frequency-domain electromagnetic data

USGS Publications Warehouse

Minsley, Burke J.; Kass, M. Andy; Hodges, Greg; Smith, Bruce D.

2014-01-01

Systematic calibration errors must be taken into account because they can substantially impact the accuracy of inverted subsurface resistivity models derived from frequency-domain electromagnetic data, resulting in potentially misleading interpretations. We have developed an approach that uses data acquired at multiple elevations over the same location to assess calibration errors. A significant advantage is that this method does not require prior knowledge of subsurface properties from borehole or ground geophysical data (though these can be readily incorporated if available), and is, therefore, well suited to remote areas. The multielevation data were used to solve for calibration parameters and a single subsurface resistivity model that are self consistent over all elevations. The deterministic and Bayesian formulations of the multielevation approach illustrate parameter sensitivity and uncertainty using synthetic- and field-data examples. Multiplicative calibration errors (gain and phase) were found to be better resolved at high frequencies and when data were acquired over a relatively conductive area, whereas additive errors (bias) were reasonably resolved over conductive and resistive areas at all frequencies. The Bayesian approach outperformed the deterministic approach when estimating calibration parameters using multielevation data at a single location; however, joint analysis of multielevation data at multiple locations using the deterministic algorithm yielded the most accurate estimates of calibration parameters. Inversion results using calibration-corrected data revealed marked improvement in misfit, lending added confidence to the interpretation of these models.

Topographic Structure from Motion

NASA Astrophysics Data System (ADS)

Fonstad, M. A.; Dietrich, J. T.; Courville, B. C.; Jensen, J.; Carbonneau, P.

2011-12-01

The production of high-resolution topographic datasets is of increasing concern and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) generally requires a significant investment in personnel time, hardware and/or software. However, image-based methods such as digital photogrammetry have steadily been decreasing in costs. Initially developed for the purpose of rapid, inexpensive and easy three dimensional surveys of buildings or small objects, the "structure from motion" photogrammetric approach (SfM) is a purely image based method which could deliver a step-change if transferred to river remote sensing, and requires very little training and is extremely inexpensive. Using the online SfM program Microsoft Photosynth, we have created high-resolution digital elevation models (DEM) of rivers from ordinary photographs produced from a multi-step workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three-dimensional space. One of the products of the SfM process is a three-dimensional point cloud of features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected via GPS in the field. The georeferenced point cloud can then be used to create a variety of digital elevation model products. Among several study sites, we examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand-held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low-altitude platforms can produce point clouds with point densities considerably better than airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Advanced structure from motion software (such as Bundler and OpenSynther) are currently under development and should increase the density of topographic points rivaling those of terrestrial laser scanning when using images shot from low altitude platforms such as helikites, poles, remote-controlled aircraft and rotocraft, and low-flying manned aircraft. Clearly, the development of this set of inexpensive and low-required-expertise tools has the potential to fundamentally shift the production of digital fluvial topography from a capital-intensive enterprise of a low number of researchers to a low-cost exercise of many river researchers.

Multi-scale Visualization of Remote Sensing and Topographic Data of the Amazon Rain Forest for Environmental Monitoring of the Petroleum Industry.

NASA Astrophysics Data System (ADS)

Fonseca, L.; Miranda, F. P.; Beisl, C. H.; Souza-Fonseca, J.

2002-12-01

PETROBRAS (the Brazilian national oil company) built a pipeline to transport crude oil from the Urucu River region to a terminal in the vicinities of Coari, a city located in the right margin of the Solimoes River. The oil is then shipped by tankers to another terminal in Manaus, capital city of the Amazonas state. At the city of Coari, changes in water level between dry and wet seasons reach up to 14 meters. This strong seasonal character of the Amazonian climate gives rise to four distinct scenarios in the annual hydrological cycle: low water, high water, receding water, and rising water. These scenarios constitute the main reference for the definition of oil spill response planning in the region, since flooded forests and flooded vegetation are the most sensitive fluvial environments to oil spills. This study focuses on improving information about oil spill environmental sensitivity in Western Amazon by using 3D visualization techniques to help the analysis and interpretation of remote sensing and digital topographic data, as follows: (a) 1995 low flood and 1996 high flood JERS-1 SAR mosaics, band LHH, 100m pixel; (b) 2000 low flood and 2001 high flood RADARSAT-1 W1 images, band CHH, 30m pixel; (c) 2002 high flood airborne SAR images from the SIVAM project (System for Surveillance of the Amazon), band LHH, 3m pixel and band XHH, 6m pixel; (d) GTOPO30 digital elevation model, 30' resolution; (e) Digital elevation model derived from topographic information acquired during seismic surveys, 25m resolution; (f) panoramic views obtained from low altitude helicopter flights. The methodology applied includes image processing, cartographic conversion and generation of value-added product using 3D visualization. A semivariogram textural classification was applied to the SAR images in order to identify areas of flooded forest and flooded vegetation. The digital elevation models were color shaded to highlight subtle topographic features. Both datasets were then converted to the same cartographic projection and inserted into the Fledermaus 3D visualization environment. 3D visualization proved to be an important aid in understanding the spatial distribution pattern of the environmentally sensitive vegetation cover. The dynamics of the hydrological cycle was depicted in a basin-wide scale, revealing new geomorphic information relevant to assess the environmental risk of oil spills. Results demonstrate that pipelines constitute an environmentally saver option for oil transportation in the region when compared to fluvial tanker routes.

Radiative Impact of Observed and Simulated Aerosol Layers Over the East Coast of North America

NASA Astrophysics Data System (ADS)

Berg, L. K.; Fast, J. D.; Burton, S. P.; Chand, D.; Comstock, J. M.; Ferrare, R. A.; Hair, J. W.; Hostetler, C. A.; Hubbe, J. M.; Kassianov, E.; Rogers, R. R.; Sedlacek, A. J., III; Shilling, J. E.; Tomlinson, J. M.; Wilson, J. M.; Zelenyuk, A.

2014-12-01

The vertical distribution of particles in the atmospheric column can have a large impact on the radiative forcing and cloud microphysics. A recent climatology constructed using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) suggests elevated layers of aerosol are quite common near the North American east coast during both winter and summer. The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study utilizing both in situ and remotely sensed measurements designed to provide a comprehensive data set that can be used to investigate science questions related to aerosol radiative forcing and the vertical distribution of aerosol. The study sampled the atmosphere at a number of altitudes within two atmospheric columns; one located near the coast of North America (over Cape Cod, MA) and a second over the Atlantic Ocean several hundred kilometers from the coast. TCAP included the yearlong deployment of the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) located at the base of the Cape Cod column, as well as summer and winter aircraft intensive observation periods (IOPs) using the ARM Aerial Facility. One important finding from the TCAP summer IOP is the relatively common occurrence (during four of the six nearly cloud-free flights) of elevated aerosol layers in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA Langley Research Center High-Spectral Resolution Lidar (HSRL-2). These elevated layers contributed up to 60% of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. Both the in situ and remote sensing observations have been compared to simulations from the regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The model simulated the observed layers well in some cases, but in other instances there were differences in the altitude, mass loading, and aerosol water associated with regional scale transport and the representation of the aerosol lifecycle.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

Vegetation cover and relationships of habitat-type with elevation on the Mississippi-Alabama Barrier Islands in the initial six years after Hurricane Katrina

NASA Astrophysics Data System (ADS)

Funderburk, W.; Carter, G. A.; Anderson, C. P.; Jeter, G. W., Jr.; Otvos, E. G.; Lucas, K. L.; Hopper, N. L.

2015-12-01

Quantifying change in vegetation and geomorphic features which occur during and after storm impact is necessary toward understanding barrier island habitat resiliency under continued climate warming and sea level rise. In August, 2005, the Mississippi-Alabama barrier islands, including, from west-to-east, Cat, West Ship, East Ship, Horn, Petit Bois and Dauphin islands, were completely inundated by the tidal surge of Hurricane Katrina. Overwash, scouring, burial under sand, and mechanical damage combined with saltwater flooding and post-storm drought resulted in immediate and long-term vegetation loss. Remotely-sensed data acquired before (2004-2005) and after (2005-2011) Katrina were compared via image classification to determine immediate storm impacts and assess natural re-growth of land area and vegetation. By 2008, merely three years after the storm, total land area of Cat, West Ship, East Ship, Horn, Petit Bois and West Dauphin had recovered to 92, 90, 33, 99, 93 and 91 percent, and total vegetated land area to 85, 101, 85, 94, 83 and 102 percent of pre-Katrina values, respectively. Habitat-type maps developed from field survey, SPOT-5 and radar data were compared with LIDAR-derived elevation models to assess 2010 habitat-type distribution with respect to ground elevation. Although median MSL elevations associated with habitat classes ranged only from 0.5 m to 1.4 m, habitat-type changed distinctively with decimeter-scale changes in elevation. Low marsh, high marsh, estuarine shrubland, slash pine woodland, beach dune, bare sand and beach dune herbland were associated with median elevations of 0.5, 0.9, 1.0, 1.1, 1.2, 1.3 and 1.4 m ± 0.1 m, respectively. The anticipated increases in sea level and tropical storm energy under a continually warming climate will likely inhibit the reformation of higher-elevation habitat-types, such as shrublands and woodlands, in the 21st century.

Strategies for using remotely sensed data in hydrologic models

NASA Technical Reports Server (NTRS)

Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

1981-01-01

Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

'Achievement, pride and inspiration': outcomes for volunteer role models in a community outreach program in remote Aboriginal communities.

PubMed

Cinelli, Renata L; Peralta, Louisa R

2015-01-01

There is growing support for the prosocial value of role modelling in programs for adolescents and the potentially positive impact role models can have on health and health behaviours in remote communities. Despite known benefits for remote outreach program recipients, there is limited literature on the outcomes of participation for role models. Twenty-four role models participated in a remote outreach program across four remote Aboriginal communities in the Northern Territory, Australia (100% recruitment). Role models participated in semi-structured one-on-one interviews. Transcripts were coded and underwent thematic analysis by both authors. Cultural training, Indigenous heritage and prior experience contributed to general feelings of preparedness, yet some role models experienced a level of culture shock, being confronted by how disparate the communities were to their home communities. Benefits of participation included exposure to and experience with remote Aboriginal peoples and community, increased cultural knowledge, personal learning, forming and building relationships, and skill development. Effective role model programs designed for remote Indigenous youth can have positive outcomes for both role models and the program recipients. Cultural safety training is an important factor for preparing role models and for building their cultural competency for implementing health and education programs in remote Indigenous communities in Australia. This will maximise the opportunities for participants to achieve outcomes and minimise their culture shock.

[Estimation of net primary productivity in arid region based on coupling model.

PubMed

Yang, Hui Jin; Li, Xiao Yu; Liu, Li Juan; Ma, Jin Long; Wang, Jin

2016-06-01

Net primary productivity (NPP), as the base for the research of matter recycling and energy flow in terrestrial ecosystem, is sensitive to the changes of environment and climate in arid region, and also is an important indicator of eco-environmental characteristics. Based on remote sensing (RS) and geographic information system (GIS), using meteorological data, eddy cova-riance data, Landsat 8 and MODIS data, this study coupled SEBAL model and light utility efficiency model to estimate the NPP of vegetation in Manas River Watershed, and the spatial pattern of NPP and the relationships between NPP and terrain factors (elevation and slope) were analyzed. Results showed that the estimated result of NPP in Manas River Watershed by coupling model was reasonable and could actually reflect the NPP of vegetation. The total annual NPP of vegetation and the mean annual NPP in Manas River Watershed in 2013 were 7066.72 Tg C·a -1 and 278.06 g C·m -2 ·a -1 respectively. With the variation of geomorphic type and land cover, the NPP changed remarkably from south to north in a trend of increase-decrease-increase-decrease pattern. The temporal variations of NPP were also obvious, with the NPP in July and August accounting for 52.2% of total annual NPP. With the increase of the elevation and slope, the mean annual NPP decreased as a whole with fluctuations induced by different land covers and environmental factors.

Predicting the spatial extent of liquefaction from geospatial and earthquake specific parameters

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.; Wald, David J.; Knudsen, Keith L.; Deodatis, George; Ellingwood, Bruce R.; Frangopol, Dan M.

2014-01-01

The spatially extensive damage from the 2010-2011 Christchurch, New Zealand earthquake events are a reminder of the need for liquefaction hazard maps for anticipating damage from future earthquakes. Liquefaction hazard mapping as traditionally relied on detailed geologic mapping and expensive site studies. These traditional techniques are difficult to apply globally for rapid response or loss estimation. We have developed a logistic regression model to predict the probability of liquefaction occurrence in coastal sedimentary areas as a function of simple and globally available geospatial features (e.g., derived from digital elevation models) and standard earthquake-specific intensity data (e.g., peak ground acceleration). Some of the geospatial explanatory variables that we consider are taken from the hydrology community, which has a long tradition of using remotely sensed data as proxies for subsurface parameters. As a result of using high resolution, remotely-sensed, and spatially continuous data as a proxy for important subsurface parameters such as soil density and soil saturation, and by using a probabilistic modeling framework, our liquefaction model inherently includes the natural spatial variability of liquefaction occurrence and provides an estimate of spatial extent of liquefaction for a given earthquake. To provide a quantitative check on how the predicted probabilities relate to spatial extent of liquefaction, we report the frequency of observed liquefaction features within a range of predicted probabilities. The percentage of liquefaction is the areal extent of observed liquefaction within a given probability contour. The regional model and the results show that there is a strong relationship between the predicted probability and the observed percentage of liquefaction. Visual inspection of the probability contours for each event also indicates that the pattern of liquefaction is well represented by the model.

Geoenvironmental and structural studies for developing new water resources in arid and semi-arid regions using remote sensing and GIS

NASA Astrophysics Data System (ADS)

Amer, Reda Mohammed

2011-12-01

Water crises are rising with increasing world population and decreasing of freshwater resources. This problem is magnified in the arid and semi-arid regions because surface water resources are very limited and highly unreliable and therefore groundwater is the primary source of water supply in these regions. This study presents an integrated approach for the identification of groundwater occurrences using remote sensing, geological, and geophysical data, and establishing sustainable paths to groundwater management. The Central Eastern Desert (CED) of Egypt was selected as a test site for this study because its climate is arid and there is an urgent need to identify potential areas for groundwater accumulations. Field investigations indicated that the CED has three types of aquifers; shallow alluvial (SA), and fracture zone (FZ) aquifers in the valley depressions, and deep aquifers in the sedimentary succession that range in age from Late Cretaceous to Recent in the marginal extensional sub-basins (ESB) along the Red Sea coast. I developed three models: (1) a Geographic Information System (GIS) model for groundwater potential in the SA and FZ shallow aquifers; (2) a kinematic model for the development of the ESB; and (3) a groundwater budget model for the ESB aquifers. The GIS model is based on the analysis of remote sensing data of the Phased Array L-band Synthetic Aperture Radar, the Landsat Enhanced Thematic Mapper Plus, and the Advanced Spaceborne Thermal Emission and Reflection Radiometer digital elevation model. The model was evaluated and proven successful against the existing shallow water wells, and by geophysical surveys using Ground Penetrating Radar and Geoelectric methods. The kinematic model indicated that the ESB were formed in the orthogonal rifting phase in the late Oligocene that is followed by oblique rifting phase during the early Miocene which resulted to the en-echelon pattern of the inland ESB and nucleation of the rift depression into segments separated by oblique-slip accommodation zones. The groundwater budget model shows that the ESB aquifers have considerable amounts of paleowater that can be purified and used for drinking. The renewable groundwater of SA and FZ aquifers can be used for herding, irrigation, and ore dressing in the mining zones.

Productivity in the barents sea--response to recent climate variability.

PubMed

Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.

Determining Greenland Ice Sheet Accumulation Rates from Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Jezek, Kenneth C.

2002-01-01

An important component of NASA's Program for Arctic Regional Climate Assessment (PARCA) is a mass balance investigation of the Greenland Ice Sheet. The mass balance is calculated by taking the difference between the areally Integrated snow accumulation and the net ice discharge of the ice sheet. Uncertainties in this calculation Include the snow accumulation rate, which has traditionally been determined by interpolating data from ice core samples taken from isolated spots across the ice sheet. The sparse data associated with ice cores juxtaposed against the high spatial and temporal resolution provided by remote sensing , has motivated scientists to investigate relationships between accumulation rate and microwave observations as an option for obtaining spatially contiguous estimates. The objective of this PARCA continuation proposal was to complete an estimate of surface accumulation rate on the Greenland Ice Sheet derived from C-band radar backscatter data compiled in the ERS-1 SAR mosaic of data acquired during, September-November, 1992. An empirical equation, based on elevation and latitude, is used to determine the mean annual temperature. We examine the influence of accumulation rate, and mean annual temperature on C-band radar backscatter using a forward model, which incorporates snow metamorphosis and radar backscatter components. Our model is run over a range of accumulation and temperature conditions. Based on the model results, we generate a look-up table, which uniquely maps the measured radar backscatter, and mean annual temperature to accumulation rate. Our results compare favorably with in situ accumulation rate measurements falling within our study area.

Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes

USGS Publications Warehouse

Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.

2018-01-01

The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass (r2 = 0.72). We then used multiple measures of biomass each growing season over 20–25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series remote sensing data to assess ecological responses to climate stressors.

Productivity in the Barents Sea - Response to Recent Climate Variability

PubMed Central

Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513

Remote infrared signage evaluation for transit stations and intersections.

PubMed

Crandall, W; Brabyn, J; Bentzen, B L; Myers, L

1999-10-01

Opportunities for education and employment depend upon effective and independent travel. For mainstream society, this is accomplished to a large extent by printed signs. People who are print disabled, visually impaired, or totally blind are at a disadvantage because they do not have access to signage. Remote infrared signage, such as the Talking Signs (TS) system, provides a solution to this need by labeling the environment for distant viewing. The system uses a transmitting "sign" and a hand-held receiver to tell people about their surroundings. In a seamless infrared signage environment, a visually impaired traveler could: walk safely across an intersection to an ATM or fare machine, from fare machine to bus stop, from bus stop to bus; from bus to building, from building to elevator, from elevator to office, from office to restroom, and so forth. This paper focuses on two problems that are among the most challenging and dangerous faced by blind travelers: negotiating complex transit stations and controlled intersections. We report on human factors studies of TS in these critical tasks, examining such issues as how much training is needed to use the system, its impact on performance and safety, benefits for different population subgroups and user opinions of its value. Results indicate that blind people can quickly and easily learn to use remote infrared signage effectively, and that its use improves travel safety, efficiency, and independence.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan Curtis; Margaret Torn

Data generated from an observational platform (Tram) consisting of 68 meters of elevated track 1 to 1.5 meters above the surface and an automated cart carrying a suite of radiation and remote sensing instruments (see below table). The Tram is in the footprint of NGEE Arctic/AmeriFlux tower at the Barrow Environmental Observatory, Barrow, Alaska.

Photogrammetry and Remote Sensing: New German Standards (din) Setting Quality Requirements of Products Generated by Digital Cameras, Pan-Sharpening and Classification

NASA Astrophysics Data System (ADS)

Reulke, R.; Baltrusch, S.; Brunn, A.; Komp, K.; Kresse, W.; von Schönermark, M.; Spreckels, V.

2012-08-01

10 years after the first introduction of a digital airborne mapping camera in the ISPRS conference 2000 in Amsterdam, several digital cameras are now available. They are well established in the market and have replaced the analogue camera. A general improvement in image quality accompanied the digital camera development. The signal-to-noise ratio and the dynamic range are significantly better than with the analogue cameras. In addition, digital cameras can be spectrally and radiometrically calibrated. The use of these cameras required a rethinking in many places though. New data products were introduced. In the recent years, some activities took place that should lead to a better understanding of the cameras and the data produced by these cameras. Several projects, like the projects of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) or EuroSDR (European Spatial Data Research), were conducted to test and compare the performance of the different cameras. In this paper the current DIN (Deutsches Institut fuer Normung - German Institute for Standardization) standards will be presented. These include the standard for digital cameras, the standard for ortho rectification, the standard for classification, and the standard for pan-sharpening. In addition, standards for the derivation of elevation models, the use of Radar / SAR, and image quality are in preparation. The OGC has indicated its interest in participating that development. The OGC has already published specifications in the field of photogrammetry and remote sensing. One goal of joint future work could be to merge these formerly independent developments and the joint development of a suite of implementation specifications for photogrammetry and remote sensing.

Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

NASA Astrophysics Data System (ADS)

Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

2016-12-01

Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

USGS Publications Warehouse

Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.

2007-01-01

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

PubMed Central

ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470

An earth remote sensing satellite- 1 Synthetic Aperture Radar Mosaic of the Tanana River Basin in Alaska

USGS Publications Warehouse

Wivell, Charles E.; Olmsted, Coert; Steinwand, Daniel R.; Taylor, Christopher

1993-01-01

Because the pixel location in a line of Synthetic Aperture Radar (SAR) image data is directly related to the distance the pixel is from the radar, terrain elevations cause large displacement errors in the geo-referenced location of the pixel. This is especially true for radar systems with small angles between the nadir and look vectors. Thus, to geo-register a SAR image accurately, the terrain of the area must be taken into account. (Curlander et al., 1987; Kwok et al., 1987, Schreier et al., 1990; Wivell et al., 1992). As part of the 1992 National Aeronautics and Space Administration's Earth Observing System Version 0 activities, a prototype SAR geocod-. ing and terrain correction system was developed at the US. Geological Survey's (USGS) E~os Data Center (EDC) in Sioux Falls, South Dakota. Using this system with 3-arc-second digital elevation models (DEMs) mosaicked at the ED^ Alaska Field Office, 21 ERS-I s.4~ scenes acquired at the Alaska SAR Facility were automatically geocoded, terrain corrected, and mosaicked. The geo-registered scenes were mosaicked using a simple concatenation.

Implementation and Evaluation of a Recurring Interdisciplinary Community Health Fair in a Remote U.S.-Mexico Border Community.

PubMed

Lee, July; McKennett, Marianne; Rodriguez, Xavier; Smith, Sunny

2018-03-06

The purpose of this project was to design, implement, and assess a recurring interdisciplinary community health fair in an underserved border town. University of California San Diego (UCSD) medical and pharmacy students, under faculty supervision, worked alongside community partners in Calexico, California to implement a health fair two miles from the U.S.-Mexico border. Demographic and screening data were described from 293 participants from 2014 to 2016. Over 90% (269/293) listed Mexico as their country of birth, 82.9% (243/293) were monolingual Spanish speakers, 75.4% (221/293) had an annual household income of ≤ $20,000, and 58.7% (172/293) described their health as fair or poor. Screening revealed 91.1% (265/291) were overweight or obese, 37.8% (109/288) had hypertension, 9.3% (27/289) had elevated blood sugar, and 11.4% (33/289) had elevated total cholesterol levels. This model could be replicated in other training settings to increase exposure to border health issues and connect patients to local health services.

Topographic mapping on large-scale tidal flats with an iterative approach on the waterline method

NASA Astrophysics Data System (ADS)

Kang, Yanyan; Ding, Xianrong; Xu, Fan; Zhang, Changkuan; Ge, Xiaoping

2017-05-01

Tidal flats, which are both a natural ecosystem and a type of landscape, are of significant importance to ecosystem function and land resource potential. Morphologic monitoring of tidal flats has become increasingly important with respect to achieving sustainable development targets. Remote sensing is an established technique for the measurement of topography over tidal flats; of the available methods, the waterline method is particularly effective for constructing a digital elevation model (DEM) of intertidal areas. However, application of the waterline method is more limited in large-scale, shifting tidal flats areas, where the tides are not synchronized and the waterline is not a quasi-contour line. For this study, a topographical map of the intertidal regions within the Radial Sand Ridges (RSR) along the Jiangsu Coast, China, was generated using an iterative approach on the waterline method. A series of 21 multi-temporal satellite images (18 HJ-1A/B CCD and three Landsat TM/OLI) of the RSR area collected at different water levels within a five month period (31 December 2013-28 May 2014) was used to extract waterlines based on feature extraction techniques and artificial further modification. These 'remotely-sensed waterlines' were combined with the corresponding water levels from the 'model waterlines' simulated by a hydrodynamic model with an initial generalized DEM of exposed tidal flats. Based on the 21 heighted 'remotely-sensed waterlines', a DEM was constructed using the ANUDEM interpolation method. Using this new DEM as the input data, it was re-entered into the hydrodynamic model, and a new round of water level assignment of waterlines was performed. A third and final output DEM was generated covering an area of approximately 1900 km2 of tidal flats in the RSR. The water level simulation accuracy of the hydrodynamic model was within 0.15 m based on five real-time tide stations, and the height accuracy (root mean square error) of the final DEM was 0.182 m based on six transects of measured data. This study aimed at construction of an accurate DEM for a large-scale, high-variable zone within a short timespan based on an iterative way of the waterline method.

Preliminary Findings of Inflight Icing Field Test to Support Icing Remote Sensing Technology Assessment

NASA Technical Reports Server (NTRS)

King, Michael; Reehorst, Andrew; Serke, Dave

2015-01-01

NASA and the National Center for Atmospheric Research have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize a vertical pointing cloud radar, a multifrequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport.

High resolution mapping of riffle-pool dynamics based on ADCP and close-range remote sensing data

NASA Astrophysics Data System (ADS)

Salmela, Jouni; Kasvi, Elina; Alho, Petteri

2017-04-01

Present development of mobile laser scanning (MLS) and close-range photogrammetry with unmanned aerial vehicle (UAV) enable us to create seamless digital elevation models (DEMs) of the riverine environment. Remote-controlled flow measurement platforms have also improved spatio-temporal resolution of the flow field data. In this study, acoustic Doppler current profiler (ADCP) attached to remote-controlled mini-boat, UAV-based bathymetry and MLS techniques were utilized to create the high-resolution DEMs of the river channel. These high-resolution measurements can be used in many fluvial applications such as computational fluid dynamics, channel change detection, habitat mapping or hydro-electric power plant planning. In this study we aim: 1) to analyze morphological changes of river channel especially riffle and pool formations based on fine-scale DEMs and ADCP measurements, 2) to analyze flow fields and their effect on morphological changes. The interest was mainly focused on reach-scale riffle-pool dynamics within two-year period of 2013 and 2014. The study was performed in sub-arctic meandering Pulmankijoki River located in Northern Finland. The river itself has shallow and clear water and sandy bed sediment. Discharge remains typically below 10 m3s-1 most of the year but during snow melt period in spring the discharge may exceed 70 m3s-1. We compared DEMs and ADCP measurements to understand both magnitude and spatio-temporal change of the river bed. Models were accurate enough to study bed form changes and locations and persistence of riffles and pools. We analyzed their locations with relation to flow during the peak and low discharge. Our demonstrated method has improved significantly spatio-temporal resolution of riverine DEMs compared to other cross-sectional and photogrammetry based models. Together with flow field measurements we gained better understanding of riverbed-water interaction

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tissue contaminants and associated transcriptional response in trout liver from high elevation lakes of Washington

USGS Publications Warehouse

Moran, P.W.; Aluru, N.; Black, R.W.; Vijayan, M.M.

2007-01-01

The consistent cold temperatures and large amount of precipitation in the Olympic and Cascade ranges of Washington State are thought to enhance atmospheric deposition of contaminants. However, little is known about contaminant levels in organisms residing in these remote high elevation lakes. We measured total mercury and 28 organochlorine compounds in trout collected from 14 remote lakes in the Olympic, Mt. Rainer, and North Cascades National Parks. Mercury was detected in trout from all lakes sampled (15 to 262 ??g/kg ww), while two organochlorines, total polychlorinated biphenyls (tPCB) and dichlorodiphenyldichloroethylene (DDE), were also detected in these fish tissues (<25 ??g/kg ww). In sediments, organochlorine levels were below detection, while median total and methyl mercury were 30.4 and 0.34 ??g/ kg dry weight (ww), respectively. Using fish from two lakes, representing different contaminant loading levels (Wilcox lake: high; Skymo lake: low), we examined transcriptional response in the liver using a custom-made low-density targeted rainbow trout cDNA microarray. We detected significant differences in liver transcriptional response, including significant changes in metabolic, endocrine, and immune-related genes, in fish collected from Wilcox Lake compared to Skymo Lake. Overall, our results suggest that local urban areas contribute to the observed contaminant patterns in these high elevation lakes, while the transcriptional changes point to a biological response associated with exposure to these contaminants in fish. Specifically, the gene expression pattern leads us to hypothesize a role for mercury in disrupting the metabolic and reproductive pathways in fish from high elevation lakes in western Washington. ?? 2007 American Chemical Society.

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

NASA Technical Reports Server (NTRS)

2002-01-01

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Investigation of the cross-ship comparison monitoring method of failure detection in the HIMAT RPRV. [digital control techniques using airborne microprocessors

NASA Technical Reports Server (NTRS)

Wolf, J. A.

1978-01-01

The Highly maneuverable aircraft technology (HIMAT) remotely piloted research vehicle (RPRV) uses cross-ship comparison monitoring of the actuator RAM positions to detect a failure in the aileron, canard, and elevator control surface servosystems. Some possible sources of nuisance trips for this failure detection technique are analyzed. A FORTRAN model of the simplex servosystems and the failure detection technique were utilized to provide a convenient means of changing parameters and introducing system noise. The sensitivity of the technique to differences between servosystems and operating conditions was determined. The cross-ship comparison monitoring method presently appears to be marginal in its capability to detect an actual failure and to withstand nuisance trips.

An integrated remote sensing approach for identifying ecological range sites. [parker mountain

NASA Technical Reports Server (NTRS)

Jaynes, R. A.

1983-01-01

A model approach for identifying ecological range sites was applied to high elevation sagebrush-dominated rangelands on Parker Mountain, in south-central Utah. The approach utilizes map information derived from both high altitude color infrared photography and LANDSAT digital data, integrated with soils, geological, and precipitation maps. Identification of the ecological range site for a given area requires an evaluation of all relevant environmental factors which combine to give that site the potential to produce characteristic types and amounts of vegetation. A table is presented which allows the user to determine ecological range site based upon an integrated use of the maps which were prepared. The advantages of identifying ecological range sites through an integrated photo interpretation/LANDSAT analysis are discussed.

Changes in the Carbon Cycle of Amazon Ecosystems During the 2010 Drought

NASA Technical Reports Server (NTRS)

Potter, Christophera; Klooster, Steven; Hiatt, Cyrus; Genovese, Vanessa; Castilla-Rubino, Juan Carlos

2011-01-01

Satellite remote sensing was combined with the NASA-CASA carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production (NPP) in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO2 uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon River basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO2 to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to forests outside the main river floodplains.

Using remotely sensed data and stochastic models to simulate realistic flood hazard footprints across the continental US

NASA Astrophysics Data System (ADS)

Bates, P. D.; Quinn, N.; Sampson, C. C.; Smith, A.; Wing, O.; Neal, J. C.

2017-12-01

Remotely sensed data has transformed the field of large scale hydraulic modelling. New digital elevation, hydrography and river width data has allowed such models to be created for the first time, and remotely sensed observations of water height, slope and water extent has allowed them to be calibrated and tested. As a result, we are now able to conduct flood risk analyses at national, continental or even global scales. However, continental scale analyses have significant additional complexity compared to typical flood risk modelling approaches. Traditional flood risk assessment uses frequency curves to define the magnitude of extreme flows at gauging stations. The flow values for given design events, such as the 1 in 100 year return period flow, are then used to drive hydraulic models in order to produce maps of flood hazard. Such an approach works well for single gauge locations and local models because over relatively short river reaches (say 10-60km) one can assume that the return period of an event does not vary. At regional to national scales and across multiple river catchments this assumption breaks down, and for a given flood event the return period will be different at different gauging stations, a pattern known as the event `footprint'. Despite this, many national scale risk analyses still use `constant in space' return period hazard layers (e.g. the FEMA Special Flood Hazard Areas) in their calculations. Such an approach can estimate potential exposure, but will over-estimate risk and cannot determine likely flood losses over a whole region or country. We address this problem by using a stochastic model to simulate many realistic extreme event footprints based on observed gauged flows and the statistics of gauge to gauge correlations. We take the entire USGS gauge data catalogue for sites with > 45 years of record and use a conditional approach for multivariate extreme values to generate sets of flood events with realistic return period variation in space. We undertake a number of quality checks of the stochastic model and compare real and simulated footprints to show that the method is able to re-create realistic patterns even at continental scales where there is large variation in flood generating mechanisms. We then show how these patterns can be used to drive a large scale 2D hydraulic to predict regional scale flooding.

Mapping Post-Fire Vegetation Recovery at Different Lithologies of Taygetos mt (greece) with Multi-Temporal Remote Sensing Data

NASA Astrophysics Data System (ADS)

Vassilakis, Emmanuel; Mallinis, George; Christopoulou, Anastasia; Farangitakis, Georgios-Pavlos; Papanikolaou, Ioannis; Arianoutsou, Margarita

2017-04-01

Mt Taygetos (2407m), located at southern Peloponnese (Greece) suffered a large fire during the summer of 2007. The fire burned approximately 45% of the area covered by the endemic Greek fir (Abies cephalonica) and Black Pine (Pinus nigra) forest ecosystems. The aim of the current study is to examine the potential differences on post-fire vegetation recovery imposed by the lithology as well as the geomorphology of the given area over sites of the same climatic and landscape conditions (elevation, aspect, slope etc.). The main lithologies consist of carbonate, permeable, not easily erodible formations (limestones and marbles) and clastic, impermeable (schists, slate and flysch) erodible ones. A time-series of high spatial resolution satellite images were interpreted, analyzed and compared in order to detect changes in vegetation coverage which could prioritize areas of interest for fieldwork campaigns. The remote sensing datasets were acquired before (Ikonos-2), a few months after (Quickbird-2) and some years after (Worldview-3) the 2007 fire. High resolution Digital Elevation Model was used for the ortho-rectification and co-registration of the remote sensing data, but also for the extraction of the mountainous landscape characteristics. The multi-temporal image dataset was analyzed through GEographic-Object Based Image Analysis (GEOBIA). Objects corresponding to different vegetation types through time were identified through spectral and textural features. The classification results were combined with basic layers such as lithological outcrops, pre-fire vegetation, landscape morphology etc., supplementing a spatial geodatabase used for classifying burnt areas with varying post-fire plant community recovery. We validated the results of the classification during fieldwork and found that at a local scale, where the landscape features are quite similar, the bedrock type proves to be an important factor for vegetation recovery, as it clearly defines the soil generation along with its properties. Plant species recovery seems to be controlled by the local lithology as it was found weaker in plots overlying limestones and marbles, comparing to that observed over schists, even for the same species. In conclusion, post-fire vegetation recovery seems to be a complex process controlled not only from species biology, but also from the geological features.

Modeling the role of groundwater and vegetation in the hydrological response of tropical glaciated watersheds to climate change

NASA Astrophysics Data System (ADS)

Ng, G. H. C.; Wickert, A. D.; McLaughlin, R.; La Frenierre, J.; Liess, S.; Saberi, L.

2016-12-01

Climate change projections show greater rates at higher elevations, making tropical glaciated regions some of the most vulnerable hydrological systems and the earliest windows into changing conditions in mountainous watersheds. Many of the subsistence agrarian communities below Volcán Chimborazo, Ecuador, experience water stress, heightening the urgency to understand the hydrological impacts of climate change. Previous hydrochemical and physical observations suggest that a significant fraction of glacial melt may first recharge underlying groundwater before discharging to streams at lower elevations. This has important implications for tracking hydrological response to climate change, due to differences in the spatiotemporal behavior of surface water vs. groundwater. However, differentiating meltwater-sourced and precipitation-sourced groundwater throughout the watershed poses a challenge in elucidating the influence of accelerated but finite glacial melt on streamflow. In addition to glacial melt, recently noted upslope vegetation migration on Chimborazo will likely complicate future predictions of water availability by influencing the relative amounts of groundwater sources and changing discharge through altered evapotranspiration along riparian zones. To investigate the roles of groundwater pathways and vegetation on glacial melt contributions to streamflow, we implement the coupled groundwater/rainfall-runoff model GSFLOW. We infer hydrogeological model inputs from geological maps of Chimborazo and vegetation properties from a combination of remotely sensed imagery and in-situ surveys. Dynamically downscaled meteorological state variables, checked against field data, force the model. Such a model enables the quantification of the current meltwater contribution to streamflow at critical water extraction points and allows us to probe potential meltwater and water resource changes under future climate change scenarios.

High Resolution Habitat Suitability Modelling For Restricted-Range Hawaiian Alpine Arthropod Species

NASA Astrophysics Data System (ADS)

Stephenson, N. M.

2016-12-01

Mapping potentially suitable habitat is critical for effective species conservation and management but can be challenging in areas exhibiting complex heterogeneity. An approach that combines non-intrusive spatial data collection techniques and field data can lead to a better understanding of landscapes and species distributions. Nysius wekiuicola, commonly known as the wēkiu bug, is the most studied arthropod species endemic to the Maunakea summit in Hawai`i, yet details about its geographic distribution and habitat use remain poorly understood. To predict the geographic distribution of N. wekiuicola, MaxEnt habitat suitability models were generated from a diverse set of input variables, including fifteen years of species occurrence data, high resolution digital elevation models, surface mineralogy maps derived from hyperspectral remote sensing, and climate data. Model results indicate that elevation (78.2 percent), and the presence of nanocrystalline hematite surface minerals (13.7 percent) had the highest influence, with lesser contributions from aspect, slope, and other surface mineral classes. Climatic variables were not included in the final analysis due to auto-correlation and coarse spatial resolution. Biotic factors relating to predation and competition also likely dictate wēkiu bug capture patterns and influence our results. The wēkiu bug range and habitat suitability models generated as a result of this study will be directly incorporated into management and restoration goals for the summit region and can also be adapted for other arthropod species present, leading to a more holistic understanding of metacommunity dynamics. Key words: Microhabitat, Structure from Motion, Lidar, MaxEnt, Habitat Suitability

Assessment of lake sensitivity to acidic deposition in national parks of the Rocky Mountains.

PubMed

Nanus, L; Williams, M W; Campbell, D H; Tonnessen, K A; Blett, T; Clow, D W

2009-06-01

The sensitivity of high-elevation lakes to acidic deposition was evaluated in five national parks of the Rocky Mountains based on statistical relations between lake acid-neutralizing capacity concentrations and basin characteristics. Acid-neutralizing capacity (ANC) of 151 lakes sampled during synoptic surveys and basin-characteristic information derived from geographic information system (GIS) data sets were used to calibrate the statistical models. The explanatory basin variables that were considered included topographic parameters, bedrock type, and vegetation type. A logistic regression model was developed, and modeling results were cross-validated through lake sampling during fall 2004 at 58 lakes. The model was applied to lake basins greater than 1 ha in area in Glacier National Park (n = 244 lakes), Grand Teton National Park (n = 106 lakes), Great Sand Dunes National Park and Preserve (n = 11 lakes), Rocky Mountain National Park (n = 114 lakes), and Yellowstone National Park (n = 294 lakes). Lakes that had a high probability of having an ANC concentration <100 microeq/L, and therefore sensitive to acidic deposition, are located in basins with elevations >3000 m, with <30% of the catchment having northeast aspect and with >80% of the catchment bedrock having low buffering capacity. The modeling results indicate that the most sensitive lakes are located in Rocky Mountain National Park and Grand Teton National Park. This technique for evaluating the lake sensitivity to acidic deposition is useful for designing long-term monitoring plans and is potentially transferable to other remote mountain areas of the United States and the world.

Estimation of hydromorphological attributes of a small forested catchment by applying the Structure from Motion (SfM) approach

NASA Astrophysics Data System (ADS)

Méndez-Barroso, Luis A.; Zárate-Valdez, Jose L.; Robles-Morúa, Agustín

2018-07-01

Structure from Motion (SfM) represents a good low-cost alternative to generate high resolution topography where LiDAR (Light Detection and Ranging) data is scarce or unaffordable. In this work, we demonstrate the advantages of high resolution elevation models (DEM) obtained using the SfM technique to delineate catchment boundaries and the stream network. The SfM-based DEM was compared with LiDAR data, distributed by the Mexican Government, and a previous high resolution topographic map generated by a RTK-GPS system. Aerial images were collected on a forested ecohydrological monitoring site in northwest Mexico using a commercial grade digital camera attached to a tethered helium balloon. Here we applied the SfM method with the removal of the vegetation, similarly to the more advance LiDAR methods. This was achieved by adjusting the point cloud classification parameters (maximum angle, maximum distance and cell size), which to our knowledge, has not has not been reported in the available SfM literature. The SfM terrain model showed minimal differences in ground elevation in the center of the image domain (0-0.5 m) while errors increased on the edges of the domain. The SfM model generated the largest catchment area, main and total channel length (1.07 ha, 106.1 and 223 m, respectively) while LiDAR model obtained the smallest area and main channel length (0.77 ha and 92.9 m, respectively). On the other hand, the SfM model had a better and accurate representation of the river network among all models evaluated due to its closest proximity to the observed GPS-tracked main channel. We concluded that the integration of low cost unmanned aerial vehicles and the SfM method is a good alternative to estimate hydro-morphological attributes in small catchments. Furthermore, we found that high resolution SfM-based terrain models had a fairly good representation of small catchments which is useful in regions with limited data availability. The main findings of this research provide scientific value within the field of hydrological remote sensing in particular in the acquisition of high resolution topography in remote areas without access to more expensive LiDAR or survey techniques. High resolution DEMs allow for a better characterization of catchment area size and stream network delineation which influence hydrological processes (i.e. soil moisture redistribution, runoff, ET).

Amazon floodplain channels regulate channel-floodplain water exchange

NASA Astrophysics Data System (ADS)

Bates, P. D.; Baugh, C.; Trigg, M.

2017-12-01

We examine the role of floodplain channels in regulating the exchange of water between the Amazon main stem and its extensive floodplains using a combination of field survey, remote sensing and numerical modelling for a 30,000 km2 area around the confluence of the Solimões and Purus rivers. From Landsat imagery we identified 1762 individual floodplain channel reaches with total length of nearly 9300 line km that range in width from 900m to 20m. Using a boat survey we measured width and depth along 509 line km of floodplain channels in 45 separate reaches and used these data to develop geomorphic relationships between width and depth. This enabled reconstruction of the depth of all other channels in the Landsat survey to an RMSE of 2.5m. We then constructed a 2D hydraulic model of this site which included all 9300km of floodplain channels as sub-grid scale features using a recently developed version of the LISFLOOD-FP code. The DEM for the model was derived from a version of the SRTM Digital Elevation Model that was processed to remove vegetation artefacts. The model was run at 270m resolution over the entire 30,000 km2 domain for the period from 2002-2009. Simulations were run with and without floodplain channels to examine the impact of these features on floodplain flow dynamics and storage. Simulated floodplain channel hydraulics were validated against a combination of in-situ and remotely sensed data. Our results show that approximately 100 km3 of water is exchanged between the channel and the floodplain during a typical annual cycle, and 8.5±2.1% of mainstem flows is routed through the floodplain. The overall effect of floodplains channels was to increase the duration of connections between the Amazon River and the floodplain. Inclusion of floodplain channels in the model increased inundation volume by 7.3% - 11.3% at high water, and decreased it at low water by 4.0% - 16.6%, with the range in these estimates due to potential errors in floodplain channel geometry. Inundation extent in the model did not increase at high water, but low water flood extents declined by 8.8% - 29.7% due to increased connectivity between the floodplain and the mainstem. The wide range of flow decrease estimates demonstrates that the results are sensitive to errors in the estimation of floodplain channel geometries, particularly bed elevations.

How morphometric characteristics affect flow accumulation values

NASA Astrophysics Data System (ADS)

Farek, Vladimir

2014-05-01

Remote sensing methods (like aerial based LIDAR recording, land-use recording etc.) become continually more available and accurate. On the other hand in-situ surveying is still expensive. Above all in small, anthropogenically uninfluenced catchments, with poor, or non-existing surveying network could be remote sensing methods extremely useful. Overland flow accumulation (FA) values belong to important indicators of higher flash floods or soil erosion exposure. This value gives the number of cells of the Digital Elevation Model (DEM) grid, which are drained to each point of the catchment. This contribution deals with relations between basic geomorphological and morphometric characteristics (like hypsometric integral, Melton index of subcatchment etc.) and FA values. These relations are studied in the rocky sandstone landscapes of National park Ceské Svycarsko with the particular occurrence of broken relief. All calculations are based on high-resolution LIDAR DEM named Genesis created by TU Dresden. The main computational platform is GIS GRASS . The goal of the conference paper is to submit a quick method or indicators to estimate small particular subcatchments threatened by higher flash floods or soil erosion risks, without the necessity of using sophisticated rainfall-runoff models. There is a possibility to split catchments easily to small subcatchments (or use existing disjunction), compute basic characteristics and (with knowledge of links between this characteristics and FA values) identify, which particular subcatchment is potentially threatened by flash floods or soil erosion.

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

Mapping suitability areas for concentrated solar power plants using remote sensing data

DOE PAGES

Omitaomu, Olufemi A.; Singh, Nagendra; Bhaduri, Budhendra L.

2015-05-14

The political push to increase power generation from renewable sources such as solar energy requires knowing the best places to site new solar power plants with respect to the applicable regulatory, operational, engineering, environmental, and socioeconomic criteria. Therefore, in this paper, we present applications of remote sensing data for mapping suitability areas for concentrated solar power plants. Our approach uses digital elevation model derived from NASA s Shuttle Radar Topographic Mission (SRTM) at a resolution of 3 arc second (approx. 90m resolution) for estimating global solar radiation for the study area. Then, we develop a computational model built on amore » Geographic Information System (GIS) platform that divides the study area into a grid of cells and estimates site suitability value for each cell by computing a list of metrics based on applicable siting requirements using GIS data. The computed metrics include population density, solar energy potential, federal lands, and hazardous facilities. Overall, some 30 GIS data are used to compute eight metrics. The site suitability value for each cell is computed as an algebraic sum of all metrics for the cell with the assumption that all metrics have equal weight. Finally, we color each cell according to its suitability value. Furthermore, we present results for concentrated solar power that drives a stream turbine and parabolic mirror connected to a Stirling Engine.« less

Remote geologic structural analysis of Yucca Flat

NASA Astrophysics Data System (ADS)

Foley, M. G.; Heasler, P. G.; Hoover, K. A.; Rynes, N. J.; Thiessen, R. L.; Alfaro, J. L.

1991-12-01

The Remote Geologic Analysis (RGA) system was developed by Pacific Northwest Laboratory (PNL) to identify crustal structures that may affect seismic wave propagation from nuclear tests. Using automated methods, the RGA system identifies all valleys in a digital elevation model (DEM), fits three-dimensional vectors to valley bottoms, and catalogs all potential fracture or fault planes defined by coplanar pairs of valley vectors. The system generates a cluster hierarchy of planar features having greater-than-random density that may represent areas of anomalous topography manifesting structural control of erosional drainage development. Because RGA uses computer methods to identify zones of hypothesized control of topography, ground truth using a well-characterized test site was critical in our evaluation of RGA's characterization of inaccessible test sites for seismic verification studies. Therefore, we applied RGA to a study area centered on Yucca Flat at the Nevada Test Site (NTS) and compared our results with both mapped geology and geologic structures and with seismic yield-magnitude models. This is the final report of PNL's RGA development project for peer review within the U.S. Department of Energy Office of Arms Control (OAC) seismic-verification community. In this report, we discuss the Yucca Flat study area, the analytical basis of the RGA system and its application to Yucca Flat, the results of the analysis, and the relation of the analytical results to known topography, geology, and geologic structures.

Remote sensing-based characterization, 2-m, Plant Functional Type Distributions, Barrow Environmental Observatory, 2010

DOE Data Explorer

Langford, Zachary; Kumar, Jitendra; Hoffman, Forrest

2014-01-01

Arctic ecosystems have been observed to be warming faster than the global average and are predicted to experience accelerated changes in climate due to global warming. Arctic vegetation is particularly sensitive to warming conditions and likely to exhibit shifts in species composition, phenology and productivity under changing climate. Mapping and monitoring of changes in vegetation is essential to understand the effect of climate change on the ecosystem functions. Vegetation exhibits unique spectral characteristics which can be harnessed to discriminate plant types and develop quantitative vegetation indices. We have combined high resolution multi-spectral remote sensing from the WorldView 2 satellite with LIDAR-derived digital elevation models to characterize the tundra landscape on the North Slope of Alaska. Classification of landscape using spectral and topographic characteristics yields spatial regions with expectedly similar vegetation characteristics. A field campaign was conducted during peak growing season to collect vegetation harvests from a number of 1m x 1m plots in the study region, which were then analyzed for distribution of vegetation types in the plots. Statistical relationships were developed between spectral and topographic characteristics and vegetation type distributions at the vegetation plots. These derived relationships were employed to statistically upscale the vegetation distributions for the landscape based on spectral characteristics. Vegetation distributions developed are being used to provide Plant Functional Type (PFT) maps for use in the Community Land Model (CLM).

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Conifer density within lake catchments predicts fish mercury concentrations in remote subalpine lakes

USGS Publications Warehouse

Eagles-Smith, Collin A.; Herring, Garth; Johnson, Branden L.; Graw, Rick

2016-01-01

Remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited mercury through freshwater food webs, as well as for evaluating the relative importance of mercury loading versus landscape influences on mercury bioaccumulation. The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish.

Climatic controls on the isotopic composition and availability of soil nitrogen in mountainous tropical forests

NASA Astrophysics Data System (ADS)

Weintraub, S. R.; Cole, R. J.; Schmitt, C. G.; All, J.

2014-12-01

Tropical forests in mountainous regions are often assumed to be nitrogen (N) limited, yet N dynamics across rugged terrain can be complex due to gradients in climate and topography. Elucidating patterns of N availability and loss across such gradients is necessary to predict and manage tropical forest response to environmental changes such as increasing N deposition and rising temperatures. However, such data is currently lacking, particularly in remote locations that are of high conservation value. To address this gap, a research expedition organized by the American Climber Science Program recently made a coast-to-coast journey across a remote region of Costa Rica, travelling over the Cordillera Talamanca and through La Amistad International Park. Numerous biological, chemical and hydrologic measurements were made en-route across montane to premontane wet tropical forests, spanning nearly 2,000 m in elevation and 200 km. Surface soil samples collected at regular intervals along this transect illuminate environmental drivers of N dynamics across the region. The dataset reveals strong links between soil natural abundance N isotopic composition (δ15N) and elevation and temperature parameters, and weaker links to precipitation and topography. This is in general agreement with global scale observations, but divergence from some previously published works is apparent and will be discussed. δ15N mass balance models suggest that N isotope patterns reflect differences in forms of N loss and the relative importance of fractionating and non-fractionating pathways. When combined with data on several other edaphic properties, especially C:N stoichiometry, the results points toward notable variation in soil N availability and N constraints across the transect. This study illustrates large, but predictable, variation in key N cycle traits across the premontane to montane wet tropical forest transition. These findings have management-relevant implications for tropical regions.

Conifer density within lake catchments predicts fish mercury concentrations in remote subalpine lakes.

PubMed

Eagles-Smith, Collin A; Herring, Garth; Johnson, Branden; Graw, Rick

2016-05-01

Remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited mercury through freshwater food webs, as well as for evaluating the relative importance of mercury loading versus landscape influences on mercury bioaccumulation. The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish. Published by Elsevier Ltd.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1992-01-01

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the image-processing based evaluation of the acquired images to characterize spatial and temporal details of landslide behaviour. We will also sketch first schemes of joint interpretation or 'data fusion' of UAV-based remote sensing with the results from geophysical mapping of underground distribution of soil moisture and fracture processes (Walter & Joswig, EGU 2009).

NASA participation in the 1980 Persistent Elevated Pollution Episode/Northeast Regional Oxidant Study (PEPE/NROS) Project: Operational aspects

NASA Technical Reports Server (NTRS)

Maddrea, G. L., Jr.; Bendura, R. J.

1981-01-01

A field experiment designed to further understand the formation and transport of visibility reducing aerosols and to characterize regional scale air masses and urban plumes is described. Measurements were made primarily in the Ohio River Valley region. The NASA participation included obtaining measurements for the determination of mixing layer height and ozone profiles by using airborne remote sensor systems such as the ultraviolet differential absorption lidar, the high spectral resolution lidar, and the laser absorption spectrometer. Other NASA systems included the microwave atmospheric remote sensor, tethered balloons, an in situ measurements aircraft, and several photometer/transmissiometer systems.

Ocean current surface measurement using dynamic elevations obtained by the GEOS-3 radar altimeter

NASA Technical Reports Server (NTRS)

Leitao, C. D.; Huang, N. E.; Parra, C. G.

1977-01-01

Remote Sensing of the ocean surface from the GEOS-3 satellite using radar altimeter data has confirmed that the altimeter can detect the dynamic ocean topographic elevations relative to an equipotential surface, thus resulting in a reliable direct measurement of the ocean surface. Maps of the ocean dynamic topography calculated over a one month period and with 20 cm contour interval are prepared for the last half of 1975. The Gulf Stream is observed by the rapid slope change shown by the crowding of contours. Cold eddies associated with the current are seen as roughly circular depressions.

Remote sensing analysis of vegetation at the San Carlos Apache Reservation, Arizona and surrounding area

USGS Publications Warehouse

Norman, Laura M.; Middleton, Barry R.; Wilson, Natalie R.

2018-01-01

Mapping of vegetation types is of great importance to the San Carlos Apache Tribe and their management of forestry and fire fuels. Various remote sensing techniques were applied to classify multitemporal Landsat 8 satellite data, vegetation index, and digital elevation model data. A multitiered unsupervised classification generated over 900 classes that were then recoded to one of the 16 generalized vegetation/land cover classes using the Southwest Regional Gap Analysis Project (SWReGAP) map as a guide. A supervised classification was also run using field data collected in the SWReGAP project and our field campaign. Field data were gathered and accuracy assessments were generated to compare outputs. Our hypothesis was that a resulting map would update and potentially improve upon the vegetation/land cover class distributions of the older SWReGAP map over the 24,000  km2 study area. The estimated overall accuracies ranged between 43% and 75%, depending on which method and field dataset were used. The findings demonstrate the complexity of vegetation mapping, the importance of recent, high-quality-field data, and the potential for misleading results when insufficient field data are collected.

Remote imagery for unmanned ground vehicles: the future of path planning for ground robotics

NASA Astrophysics Data System (ADS)

Frederick, Philip A.; Theisen, Bernard L.; Ward, Derek

2006-10-01

Remote Imagery for Unmanned Ground Vehicles (RIUGV) uses a combination of high-resolution multi-spectral satellite imagery and advanced commercial off-the-self (COTS) object-oriented image processing software to provide automated terrain feature extraction and classification. This information, along with elevation data, infrared imagery, a vehicle mobility model and various meta-data (local weather reports, Zobler Soil map, etc...), is fed into automated path planning software to provide a stand-alone ability to generate rapidly updateable dynamic mobility maps for Manned or Unmanned Ground Vehicles (MGVs or UGVs). These polygon based mobility maps can reside on an individual platform or a tactical network. When new information is available, change files are generated and ingested into existing mobility maps based on user selected criteria. Bandwidth concerns are mitigated by the use of shape files for the representation of the data (e.g. each object in the scene is represented by a shape file and thus can be transmitted individually). User input (desired level of stealth, required time of arrival, etc...) determines the priority in which objects are tagged for updates. This paper will also discuss the planned July 2006 field experiment.

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Mapping the Risk of Rift Valley fever re-emergence in Southern Africa using remote sensing data

USDA-ARS?s Scientific Manuscript database

Rift Valley fever is a viral disease of animals and humans that occurs throughout sub-Saharan Africa, Egypt and the Arabian Peninsula. Outbreaks of the disease are episodic and closely linked to climate variability, especially widespread elevated rainfall that facilitates Rift Valley fever virus tra...

FIELD ACTIVITIES AND PRELIMINARY RESULTS FROM THE INVESTIGATION OF WESTERN AIRBORNE CONTAMINANTS IN TWO HIGH ELEVATION WATERSHEDS OF ROCKY MOUNTAIN NATIONAL PARK

EPA Science Inventory

The National Park Service initiated the Western Airborne Contaminants Assessment Project (WACAP) in 2002 to determine if airborne contaminants from long-range transport and/or regional sources are having an impact on remote western ecosystems, including AK. Rocky Mountain Nation...

Current and historical deposition of PBDEs, pesticides, PCBs, and PAHs to Rocky Mountain National Park

EPA Science Inventory

An analytical method was developed for the trace analysis of 98 semi-volatile organic compounds (SOCs) in remote, high elevation lake sediment. Sediment cores from Lone Pine Lake (West of the Continental Divide) and Mills Lake (East of the Continental Divide) in Rocky Mountain Na...

Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and CARTOSAT-1 Dems

NASA Astrophysics Data System (ADS)

Bagheri, H.; Schmitt, M.; Zhu, X. X.

2017-05-01

Recently, with InSAR data provided by the German TanDEM-X mission, a new global, high-resolution Digital Elevation Model (DEM) has been produced by the German Aerospace Center (DLR) with unprecedented height accuracy. However, due to SAR-inherent sensor specifics, its quality decreases over urban areas, making additional improvement necessary. On the other hand, DEMs derived from optical remote sensing imagery, such as Cartosat-1 data, have an apparently greater resolution in urban areas, making their fusion with TanDEM-X elevation data a promising perspective. The objective of this paper is two-fold: First, the height accuracies of TanDEM-X and Cartosat-1 elevation data over different land types are empirically evaluated in order to analyze the potential of TanDEM-XCartosat- 1 DEM data fusion. After the quality assessment, urban DEM fusion using weighted averaging is investigated. In this experiment, both weight maps derived from the height error maps delivered with the DEM data, as well as more sophisticated weight maps predicted by a procedure based on artificial neural networks (ANNs) are compared. The ANN framework employs several features that can describe the height residual performance to predict the weights used in the subsequent fusion step. The results demonstrate that especially the ANN-based framework is able to improve the quality of the final DEM through data fusion.

Inferring Discharge at River Mouths from Water Surface Height Measurements

NASA Astrophysics Data System (ADS)

Branch, R.; Horner-Devine, A.; Chickadel, C. C.

2016-02-01

Numerical model results suggest that a relationship exists between river discharge and surface height anomalies near the mouth of rivers, which presents an opportunity to use satellite elevation data to measure discharge remotely. Here we investigate whether such a relationship can be observed in the field using airborne lidar data at the mouth of the Columbia River. Airborne Lidar data were used because current NASA altimeter data does not have high enough spatial resolution to image surface elevation along a river. NASA's Surface Water and Ocean Topography, SWOT, sensor is planned to have a spatial resolution of less than 100 m and maximum height precision of 1 cm. The magnitude and temporal duration of the elevation signal found in the lidar data will be used to determine if SWOT will have the resolution and precision capabilities to measure discharge from space. Lidar data were acquired during a range of tidal conditions and discharge rates from May through September of 2013. Our results suggest that there is a measurable surface height anomaly at the river mouth during part of the tidal cycle. A 0.7 m surface depression was found during ebb tide and a uniform surface tilt was found at slack tide. The variation of the anomaly over the tidal period presents a challenge for decoupling the tidal component from that due to the discharge.

An ice sheet model validation framework for the Greenland ice sheet.

PubMed

Price, Stephen F; Hoffman, Matthew J; Bonin, Jennifer A; Howat, Ian M; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P; Evans, Katherine J; Kennedy, Joseph H; Lenaerts, Jan; Lipscomb, William H; Perego, Mauro; Salinger, Andrew G; Tuminaro, Raymond S; van den Broeke, Michiel R; Nowicki, Sophie M J

2017-01-01

We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

Creating a water depth map from Earth Observation-derived flood extent and topography data

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Chini, Marco; Hostache, Renaud; Pelich, Ramona; Schlaffer, Stefan

2017-04-01

Enhanced methods for monitoring temporal and spatial variations of water depth in rivers and floodplains are very important in operational water management. Currently, variations of water elevation can be estimated indirectly at the land-water interface using sequences of satellite EO imagery in combination with topographic data. In recent years high-resolution digital elevation models (DEM) and satellite EO data have become more readily available at global scale. This study introduces an approach for efficiently converting remote sensing-derived flood extent maps into water depth maps using a floodplain's topography information. For this we make the assumption of uniform flow, that is the depth of flow with respect to the drainage network is considered to be the same at every section of the floodplain. In other words, the depth of water above the nearest drainage is expected to be constant for a given river reach. To determine this value we first need the Height Above Nearest Drainage (HAND) raster obtained by using the area of interest's DEM as source topography and a shapefile of the river network. The HAND model normalizes the topography with respect to the drainage network. Next, the HAND raster is thresholded in order to generate a binary mask that optimally fits, over the entire region of study, the flood extent map obtained from SAR or any other remote sensing product, including aerial photographs. The optimal threshold value corresponds to the height of the water line above the nearest drainage, termed HANDWATER, and is considered constant for a given subreach. Once the HANDWATER has been optimized, a water depth map can be generated by subtracting the value of the HAND raster at the each location from this parameter value. These developments enable large scale and near real-time applications and only require readily available EO data, a DEM and the river network as input data. The approach is based on a hierarchical split-based approach that subdivides a drainage network into segments of variable length with evidence of uniform flow. The method has been tested with remote sensing data and DEM data that differ in terms of spatial resolution and accuracy. A comprehensive evaluation of the obtained water depth maps with hydrodynamic modelling results and in situ measured water level recordings was carried out on a reach of the river Severn located in the United Kingdom. First results show that the obtained root mean squared difference is 10 cm when using high resolution high precision data sets (i.e. aerial photographs of flood extent and a LiDAR-derived DEM) and amount to 50 cm when using as inputs moderate resolution SAR imagery from ENVISAT and a SRTM-derived DEM.

Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Lopez-Tamayo, Alejandro; Merediz-Alonso, Gonzalo; Olesen, Daniel; Jakobsen, Jakob; Wang, Sheng; Garcia, Monica; Bauer-Gottwein, Peter

2018-04-01

Observations of water surface elevation (WSE) and bathymetry of the lagoons and cenotes of the Yucatán Peninsula (YP) in southeast Mexico are of hydrogeological interest. Observations of WSE (orthometric water height above mean sea level, amsl) are required to inform hydrological models, to estimate hydraulic gradients and groundwater flow directions. Measurements of bathymetry and water depth (elevation of the water surface above the bed of the water body) improve current knowledge on how lagoons and cenotes connect through the complicated submerged cave systems and the diffuse flow in the rock matrix. A novel approach is described that uses unmanned aerial vehicles (UAVs) to monitor WSE and bathymetry of the inland water bodies on the YP. UAV-borne WSE observations were retrieved using a radar and a global navigation satellite system on-board a multi-copter platform. Water depth was measured using a tethered floating sonar controlled by the UAV. This sonar provides depth measurements also in deep and turbid water. Bathymetry (wet-bed elevation amsl) can be computed by subtracting water depth from WSE. Accuracy of the WSE measurements is better than 5-7 cm and accuracy of the water depth measurements is estimated to be 3.8% of the actual water depth. The technology provided accurate measurements of WSE and bathymetry in both wetlands (lagoons) and cenotes. UAV-borne technology is shown to be a more flexible and lower cost alternative to manned aircrafts. UAVs allow monitoring of remote areas located in the jungle of the YP, which are difficult to access by human operators.

In vitro and in vivo evaluation of sanguinarine liposomes prepared by a remote loading method with three different ammonium salts.

PubMed

Ke, X; Bei, J H; Zhang, Y; Li, J

2011-04-01

Sanguinarine liposomes were prepared by a remote loading method using three different ammonium salts. A series of studies, including in vitro release, in vitro and in vivo anti-tumor effects and pharmacokinetics in rats, were conducted. The three liposomes showed pH-sensitive release characteristics in vitro, but there were obvious variations in their release profiles. Among the three liposomes, the liposomes made using ammonium citrate and phosphate possessed better anti-tumor activity in vitro and in vivo, compared with the liposome using ammonium sulfate. Pharmacokinetics test results in rats indicated that sanguinarine liposomes have notably elevated AUC (P<0.05) and markedly lower CL (P<0.05) compared with the solution, but there were no obvious differences between the three liposomes. The present study may be useful for better understanding and better choice of a suitable ammonium salt for the remote loading method.

A Randomized Controlled Trial Examination of a Remote Parenting Intervention: Engagement and Effects on Parenting Behavior and Child Abuse Potential.

PubMed

Baggett, Kathleen; Davis, Betsy; Feil, Edward; Sheeber, Lisa; Landry, Susan; Leve, Craig; Johnson, Ursula

2017-11-01

Technology advances increasingly allow for access to remotely delivered interventions designed to promote early parenting practices that protect against child maltreatment. Among low-income families, at somewhat elevated risk for child maltreatment, there is some evidence that parents do engage in and benefit from remote-coaching interventions. However, little is known about the effectiveness of such programs to engage and benefit families at high risk for child maltreatment due to multiple stressors associated with poverty. To address this limitation, we examined engagement and outcomes among mothers at heightened risk for child abuse, who were enrolled in a randomized controlled, intent-to-treat trial of an Internet adaptation of an evidence-based infant parenting intervention. We found that engagement patterns were similar between higher and lower risk groups. Moreover, an intervention dose by condition effect was found for increased positive parent behavior and reduced child abuse potential.

American Society of Photogrammetry and American Congress on Surveying and Mapping, Fall Technical Meeting, ASP Technical Papers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1981-01-01

Various topics in the field of photogrammetry are addressed. Among the subjects discussed are: remote sensing of Gulf Stream dynamics using VHRR satellite imagery an interactive rectification system for remote sensing imagery use of a single photo and digital terrain matrix for point positioning crop type analysis using Landsat digital data use of a fisheye lens in solar energy assessment remote sensing inventory of Rocky Mountain elk habitat Washington state's large scale ortho program educational image processing. Also discussed are: operational advantages of on-line photogrammetric triangulation analysis of fracturation field photogrammetry as a tool for measuring glacier movement double modelmore » orthophotos used for forest inventory mapping map revisioning module for the Kern PG2 stereoplotter assessing accuracy of digital land-use and terrain data accuracy of earthwork calculations from digital elevation data.« less

Spatial Relationships Between Snow Contaminant Content, Grain Size, and Surface Temperature in Multi-spectral Remote Sensing Data of Mt. Rainier, WA

NASA Astrophysics Data System (ADS)

Kay, J. E.; Hansen, G.; Gillespie, A.; Pettit, E.

2002-12-01

Relating cryosphere change to climate change requires estimation of radiative fluxes on snow-covered surfaces. The distribution of, and relationship between, snow-pack properties that affect radiative balance can be estimated with high-resolution remote-sensing data. MODIS/ASTER airborne simulator (MASTER) data were collected at Mt. Rainier to reveal spatial patterns of, and correlations between, snow contaminant content, grain size, and temperature. The visible and near-infrared (VNIR: 11 bands, 0.4-1.0 μm) and the short-wave infrared (SWIR: 14 bands, 1.6-2.4 μm) data are processed to bi-directional reflectance (BDR) and albedo, by removing atmospheric effects and by normalizing to Solar irradiance and incidence angle. VNIR BDR and albedo are used as a proxy for snow contaminant content. Physical and optical grain size are estimated by comparing SWIR BDR and albedo to modeled and measured spectra, and ground-truth measurements. The thermal infrared data (TIR: 10 bands, 8-13 μm) are processed to temperature by removing emissivity and atmospheric effects. In combination, the VNIR, SWIR, and TIR data reveal a distinct pattern of contaminants, grain size, and temperature related to a recent snowfall and the end-of-the-summer melting season. At lower elevations, the surface accumulation of dirty lag deposits resulted in snow with very low visible albedo (20-30 %), large physical and optical grain radii (500-1500 μm, 200 μm), and temperatures near the melting point. At higher elevations, the recent snowfall left snow with low contaminant content, and a higher visible albedo (60-90 %). However, a region near the summit with smaller physical and optical grain radii (400 μm, 100 μm), and temperatures below the melting point, is distinguished from a middle elevation region with grain sizes and temperatures similar to the lower region. Contaminants reduce VNIR albedo and significantly enhance absorption of incoming solar radiation. The spatial correlation between temperature and grain size supports the idea that rapid, destructive metamorphism occurs when snow temperatures are at the melting point.

Shuttle Topography Data Inform Solar Power Analysis

NASA Technical Reports Server (NTRS)

2013-01-01

The next time you flip on a light switch, there s a chance that you could be benefitting from data originally acquired during the Space Shuttle Program. An effort spearheaded by Jet Propulsion Laboratory (JPL) and the National Geospatial-Intelligence Agency (NGA) in 2000 put together the first near-global elevation map of the Earth ever assembled, which has found use in everything from 3D terrain maps to models that inform solar power production. For the project, called the Shuttle Radar Topography Mission (SRTM), engineers at JPL designed a 60-meter mast that was fitted onto Shuttle Endeavour. Once deployed in space, an antenna attached to the end of the mast worked in combination with another antenna on the shuttle to simultaneously collect data from two perspectives. Just as having two eyes makes depth perception possible, the SRTM data sets could be combined to form an accurate picture of the Earth s surface elevations, the first hight-detail, near-global elevation map ever assembled. What made SRTM unique was not just its surface mapping capabilities but the completeness of the data it acquired. Over the course of 11 days, the shuttle orbited the Earth nearly 180 times, covering everything between the 60deg north and 54deg south latitudes, or roughly 80 percent of the world s total landmass. Of that targeted land area, 95 percent was mapped at least twice, and 24 percent was mapped at least four times. Following several years of processing, NASA released the data to the public in partnership with NGA. Robert Crippen, a member of the SRTM science team, says that the data have proven useful in a variety of fields. "Satellites have produced vast amounts of remote sensing data, which over the years have been mostly two-dimensional. But the Earth s surface is three-dimensional. Detailed topographic data give us the means to visualize and analyze remote sensing data in their natural three-dimensional structure, facilitating a greater understanding of the features and processes taking place on Earth."

Hyperspectral detection of a subsurface CO2 leak in the presence of water stressed vegetation.

PubMed

Bellante, Gabriel J; Powell, Scott L; Lawrence, Rick L; Repasky, Kevin S; Dougher, Tracy

2014-01-01

Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS) sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa) to one of four possible treatment groups: 1) a CO2 injection group; 2) a water stress group; 3) an interaction group that was subjected to both water stress and CO2 injection; or 4) a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87) for the classification tree analysis and 83% (Kappa of 0.77) for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool.

Hyperspectral Detection of a Subsurface CO2 Leak in the Presence of Water Stressed Vegetation

PubMed Central

Bellante, Gabriel J.; Powell, Scott L.; Lawrence, Rick L.; Repasky, Kevin S.; Dougher, Tracy

2014-01-01

Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS) sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa) to one of four possible treatment groups: 1) a CO2 injection group; 2) a water stress group; 3) an interaction group that was subjected to both water stress and CO2 injection; or 4) a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87) for the classification tree analysis and 83% (Kappa of 0.77) for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool. PMID:25330232

Using Remote Sensing to Determine Timing of High Altitude Grass Hay Growth Stages

NASA Astrophysics Data System (ADS)

Mefford, B.

2015-12-01

Remote sensing has become the standard for collecting data to determine potential irrigation consumptive use in Wyoming for the Green River Basin. The Green River Basin within Wyoming is around 10.8 million acres, located in south western Wyoming and is a sub-basin of the Colorado River Basin. Grass hay is the main crop grown in the basin. The majority of the hay is grown at elevations 7,000 feet above mean sea level. Daily potential irrigation consumptive use is calculated for the basin during the growing season (May 1st to September 30th). To determine potential irrigation consumptive use crop coefficients, reference evapotranspiration (ET) and effective precipitation are required. Currently crop coefficients are the hardest to determine as most research on crop coefficients are based at lower elevations. Values for crop coefficients for grass hay still apply to high altitude grass hay, but the hay grows at a much slower rate than low elevation grass hay. To be able to more accurately determine the timing of the growth stages of hay in this basin, time-lapse cameras were installed at two different irrigated hay fields in the basin for the 2015 growing season and took pictures automatically once a day at 1 P.M.. Both of the fields also contained a permanent research grade weather station. Imagery obtained from these cameras was used as indicators of timing of the major growth stages of the hay and the length of days between the stages. A crop coefficient value was applied every day in the growing season based on the results from the imagery. Daily potential ET was calculated using the crop coefficients and the data from the on-site weather stations. The final result was potential irrigation induced crop consumptive use for each site. Using remote sensing provided necessary information that normally would be applied arbitrarily in determining irrigation induced consumptive use in the Green River Basin.

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

USGS Publications Warehouse

Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

2013-01-01

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

Using Remote Sensing to Visualize and Extract Building Inventories of Urban Areas for Disaster Planning and Response

NASA Astrophysics Data System (ADS)

Lang, A. F.; Salvaggio, C.

2016-12-01

Climate change, skyrocketing global population, and increasing urbanization have set the stage for more so-called "mega-disasters." We possess the knowledge to mitigate and predict the scope of these events, and recent advancements in remote sensing can inform these efforts. Satellite and aerial imagery can be obtained anywhere of interest; unmanned aerial systems can be deployed quickly; and improved sensor resolutions and image processing techniques allow close examination of the built environment. Combined, these technologies offer an unprecedented ability for the disaster community to visualize, assess, and communicate risk. Disaster mitigation and response efforts rely on an accurate representation of the built environment, including knowledge of building types, structural characteristics, and juxtapositions to known hazards. The use of remote sensing to extract these inventory data has come far in the last five years. Researchers in the Digital Imaging and Remote Sensing (DIRS) group at the Rochester Institute of Technology are meeting the needs of the disaster community through the development of novel image processing methods capable of extracting detailed information of individual buildings. DIRS researchers have pioneered the ability to generate three-dimensional building models from point cloud imagery (e.g., LiDAR). This method can process an urban area and recreate it in a navigable virtual reality environment such as Google Earth within hours. Detailed geometry is obtained for individual structures (e.g., footprint, elevation). In a recent step forward, these geometric data can now be combined with imagery from other sources, such as high resolution or multispectral imagery. The latter ascribes a spectral signature to individual pixels, suggesting construction material. Ultimately, these individual building data are amassed over an entire region, facilitating aggregation and risk modeling analyses. The downtown region of Rochester, New York is presented as a case study. High resolution optical, LiDAR, and multi-spectral imagery was captured of this region. Using the techniques described, these imagery sources are combined and processed to produce a holistic representation of the built environment, inclusive of individual building characteristics.

Zonation of High Disaster Potential Communities for Remote Mountainous Areas in Southern Taiwan

NASA Astrophysics Data System (ADS)

Chen, Yie-Ruey; Tsai, Kuang-Jung; Chang, Chwen-Ming; Chen, Jing-Wen; Chiang, Jie-Lun; Lu, Yi-Ching; Tsai, Hui-Wen

2017-04-01

About three-quarters of Taiwan are covered by hillside areas. Most of the hillside regions in Taiwan are sedimentary and metamorphic rocks which are fragile and highly weathered. In recent years, human development coupled with the global impact of extreme weather, typhoons and heavy rains have caused the landslide disasters and leaded to human causalities and properties loss. The landslides also endanger the major public works and almost make the overall industrial economic development and transport path overshadowed by disasters. Therefore, this research assesses the exploration of landslide potential analysis and zonation of high disaster potential communities for remote mountainous areas in southern Taiwan. In this study, the time series of disaster records and land change of remote mountainous areas in southern Taiwan are collected using techniques of interpretation from satellite images corresponding to multi-year and multi-rainfall events. To quantify the slope hazards, we adopt statistical analysis model to analyze massive data of slope disasters and explore the variance, difference and trend of influence factors of hillside disaster; establish the disaster potential analysis model under the climate change and construct the threshold of disaster. Through analysis results of disaster potential assessment, the settlement distribution with high-risk hazard potential of study area is drawn with geographic information system. Results of image classification show that the values of coefficient of agreement for different time periods are at high level. Compared with the historical disaster records of research areas, the accuracy of predicted landslide potential is in reasonable confidence level. The spatial distribution of landslide depends on the interaction of rainfall patterns, slope and elevation of the research area. The results also show that the number and scale of secondary landslide sites are much larger than those of new landslide sites after rainfall. The greater the slope land disturbance, the more likely the scale of secondary landslide uprises. The results of the map for the zonation of high-disaster potential communities can be a useful reference for the government to plan strategies on adaptation to climate change for remote mountainous communities in southern Taiwan.

Remote sensing-based characterization of land management and biophysical factors in grassland

NASA Astrophysics Data System (ADS)

Ramspott, Matthew E.

Land use and management are important factors influencing ecosystem functions, including the cycling of carbon (C) in plant/soil systems. Information about land use and management, needed to prioritize conservation efforts in managed grasslands of the Central Great Plains, can be obtained using remote sensing techniques, but this process is complex in grasslands because of the subtle class differences, large within-class variability, and complex seasonal changes in canopy spectral characteristics. In this study, time-series of remotely sensed data were used to derive vegetation index (VI) and image texture measures. The utility of these measures for classification of five managed grassland types was assessed using ANOVA and stepwise discriminant analysis methods. Image texture was found to improve the accuracy of classification by ˜13% over the use of VI alone. The optimal timing of data acquisition for classification with VI was found to be in April/May and in October; optimal timing for acquisition of texture was in June. Remotely sensed VI have been commonly used to model photosynthetic capacity and net primary production in ecosystems. Since VI theoretically assume canopy conditions of uniform geometry and greenness, seasonally variable management-induced changes in the grassland canopy can potentially influence the VI response and therefore the strength and stability of the model. This study examined the seasonal and inter-annual stability of the relationship between VI and photosynthetic capacity under both idealized and realized conditions. With regression analysis, the relationship between VI and field-measured estimates of photosynthetic capacity was established and evaluated. This work identified two types of management activity strongly influencing the stability of this relationship: (1) Conservation management, in which the vegetation is neither hayed nor grazed, results in accumulation of senescent canopy material and leads to lower than expected VI response; (2) Heavy grazing management leads to elevated levels of forb (non-grass species) cover in the canopy coupled with low photosynthetic capacity and high levels of bare ground, resulting in higher than expected VI response. When sites exhibiting these characteristics were removed, the relationship between VI and photosynthetic capacity was found to be stable seasonally and between years.

Unsupervised Change Detection for Geological and Ecological Monitoring via Remote Sensing: Application on a Volcanic Area

NASA Astrophysics Data System (ADS)

Falco, N.; Pedersen, G. B. M.; Vilmunandardóttir, O. K.; Belart, J. M. M. C.; Sigurmundsson, F. S.; Benediktsson, J. A.

2016-12-01

The project "Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS)" aims at providing fast and reliable mapping and monitoring techniques on a big spatial scale with a high temporal resolution of the Icelandic landscape. Such mapping and monitoring will be crucial to both mitigate and understand the scale of processes and their often complex interlinked feedback mechanisms.In the EMMIRS project, the Hekla volcano area is one of the main sites under study, where the volcanic eruptions, extreme weather and human activities had an extensive impact on the landscape degradation. The development of innovative remote sensing approaches to compute earth observation variables as automatically as possible is one of the main tasks of the EMMIRS project. Furthermore, a temporal remote sensing archive is created and composed by images acquired by different sensors (Landsat, RapidEye, ASTER and SPOT5). Moreover, historical aerial stereo photos allowed decadal reconstruction of the landscape by reconstruction of digital elevation models. Here, we propose a novel architecture for automatic unsupervised change detection analysis able to ingest multi-source data in order to detect landscape changes in the Hekla area. The change detection analysis is based on multi-scale analysis, which allows the identification of changes at different level of abstraction, from pixel-level to region-level. For this purpose, operators defined in mathematical morphology framework are implemented to model the contextual information, represented by the neighbour system of a pixel, allowing the identification of changes related to both geometrical and spectral domains. Automatic radiometric normalization strategy is also implemented as pre-processing step, aiming at minimizing the effect of different acquisition conditions. The proposed architecture is tested on multi-temporal data sets acquired over different time periods coinciding with the last three eruptions (1980-1981, 1991, 2000) occurred on Hekla volcano. The results reveal emplacement of new lava flows and the initial vegetation succession, providing insightful information on the evolving of vegetation in such environment. Shadow and snow patch changes are resolved in post-processing by exploiting the available spectral information.

Remote ischaemic preconditioning and prevention of cerebral injury.

PubMed

Rehni, Ashish K; Shri, Richa; Singh, Manjeet

2007-03-01

Bilateral carotid artery occlusion of 10 min followed by reperfusion for 24 hr was employed in present study to produce ischaemia and reperfusion induced cerebral injury in mice. Cerebral infarct size was measured using triphenyltetrazolium chloride staining. Short-term memory was evaluated using elevated plus maze. Inclined beam walking test was employed to assess motor incoordination. Bilateral carotid artery occlusion followed by reperfusion produced cerebral infarction and impaired short-term memory, motor co-ordination and lateral push response. A preceding episode of mesenteric artery occlusion for 15 min and reperfusion of 15 min (remote mesenteric ischaemic preconditioning) prevented markedly ischaemia-reperfusion-induced cerebral injury measured in terms of infarct size, loss of short-term memory, motor coordination and lateral push response. Glibenclamide (5 mg/kg, iv) a KATP channel blocker and caffeine (7 mg/kg, iv) an adenosine receptor blocker attenuated the neuroprotective effect of remote mesenteric ischaemic preconditioning. It may be concluded that neuroprotective effect of remote mesenteric ischaemic preconditioning may be due to activation of adenosine receptors and consequent activation of KATP channels in mice.

SERIAL ULTRASOUND EVALUATION OF INTRAMYOCARDIAL STRAIN AFTER REPERFUSED MYOCARDIAL INFARCTION REVEALS THAT REMOTE ZONE DYSSYNCHRONY DEVELOPS IN CONCERT WITH LEFT VENTRICULAR REMODELING

PubMed Central

Li, Yinbo; Garson, Christopher D.; Xu, Yaqin; Helm, Patrick A.; Hossack, John A.; French, Brent A.

2011-01-01

This study noninvasively evaluated the development of left ventricular (LV) dyssynchrony following reperfused myocardial infarction (MI) in mice using an ultrasonic speckle-tracking method. Eight C57BL/6J mice were assessed by high-resolution echocardiography at baseline and at eight time-points following MI. Images were acquired at 1mm elevational intervals encompassing the entire LV to determine chamber volumes and radial strain. Receiver-operating characteristic (ROC) analysis of regional radial strain was used to segment the three-dimensional (3-D) LV into infarct, adjacent and remote zones. This in vivo segmentation was correlated to histologic infarct size (R = 0.89, p < 0.01) in a short-axis, slice-by-slice comparison. The onset of dyssynchrony during LV remodeling was assessed by standard deviation of time to peak radial strain in the infarct, adjacent and remote zones. It was discovered that the form of LV dyssynchrony that develops in the remote zone late after MI does so in concert with the progression of LV remodeling (R = 0.70, p < 0.05). PMID:21640480

Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington

USGS Publications Warehouse

Tabor, Rowland W.; Booth, Derek B.

2017-11-06

This map is an interpretation of a modern lidar digital elevation model combined with the geology depicted on the Geologic Map of the Des Moines 7.5' Quadrangle, King County, Washington (Booth and Waldron, 2004). Booth and Waldron described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Des Moines 7.5' quadrangle. The base map that they used was originally compiled in 1943 and revised using 1990 aerial photographs; it has 25-ft contours, nominal horizontal resolution of about 40 ft (12 m), and nominal mean vertical accuracy of about 10 ft (3 m). Similar to many geologic maps, much of the geology in the Booth and Waldron (2004) map was interpreted from landforms portrayed on the topographic map. In 2001, the Puget Sound Lidar Consortium obtained a lidar-derived digital elevation model (DEM) for much of the Puget Sound area, including the entire Des Moines 7.5' quadrangle. This new DEM has a horizontal resolution of about 6 ft (2 m) and a mean vertical accuracy of about 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM compared to topography constructed from air-photo stereo models have much improved the interpretation of geology, even in this heavily developed area, especially the distribution and relative age of some surficial deposits. For a brief description of the light detection and ranging (lidar) remote sensing method and this data acquisition program, see Haugerud and others (2003). 

A study of remote sensing as applied to regional and small watersheds. Volume 1: Summary report

NASA Technical Reports Server (NTRS)

Ambaruch, R.

1974-01-01

The accuracy of remotely sensed measurements to provide inputs to hydrologic models of watersheds is studied. A series of sensitivity analyses on continuous simulation models of three watersheds determined: (1)Optimal values and permissible tolerances of inputs to achieve accurate simulation of streamflow from the watersheds; (2) Which model inputs can be quantified from remote sensing, directly, indirectly or by inference; and (3) How accurate remotely sensed measurements (from spacecraft or aircraft) must be to provide a basis for quantifying model inputs within permissible tolerances.

Hurricane coastal flood analysis using multispectral spectral images

NASA Astrophysics Data System (ADS)

Ogashawara, I.; Ferreira, C.; Curtarelli, M. P.

2013-12-01

Flooding is one of the main hazards caused by extreme events such as hurricanes and tropical storms. Therefore, flood maps are a crucial tool to support policy makers, environmental managers and other government agencies for emergency management, disaster recovery and risk reduction planning. However traditional flood mapping methods rely heavily on the interpolation of hydrodynamic models results, and most recently, the extensive collection of field data. These methods are time-consuming, labor intensive, and costly. Efficient and fast response alternative methods should be developed in order to improve flood mapping, and remote sensing has been proved as a valuable tool for this application. Our goal in this paper is to introduce a novel technique based on spectral analysis in order to aggregate knowledge and information to map coastal flood areas. For this purpose we used the Normalized Diference Water Index (NDWI) which was derived from two the medium resolution LANDSAT/TM 5 surface reflectance product from the LANDSAT climate data record (CDR). This product is generated from specialized software called Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). We used the surface reflectance products acquired before and after the passage of Hurricane Ike for East Texas in September of 2008. We used as end member a classification of estimated flooded area based on the United States Geological Survey (USGS) mobile storm surge network that was deployed for Hurricane Ike. We used a dataset which consisted of 59 water levels recording stations. The estimated flooded area was delineated interpolating the maximum surge in each location using a spline with barriers method with high tension and a 30 meter Digital Elevation Model (DEM) from the National Elevation Dataset (NED). Our results showed that, in the flooded area, the NDWI values decreased after the hurricane landfall on average from 0.38 to 0.18 and the median value decreased from 0.36 to 0.2. However for the non-flooded area the NDWI increased after the hurricane landfall. The average value varied from 0.15 to 0.43 and the median value from 0.13 to 0.43. These results demonstrate that these differences can be explored for the mapping of flood areas. As NDWI was developed to quantify the amount of water in the leaf of the plants, the increase of the value is expected within the amount of water that the leaf will absorb. However in flooded areas the amount of water is so high that it is possible that the reflectance follows the water spectral behavior absorbing more than reflecting in the Near Infrared region. Thus, remote sensing techniques showed to be powerful tools since they could characterize flooded areas. However further studies are needed, applying and validating these techniques for other regions and different storms. Optical remote sensing is promising for many applications, since it will be an open door to studies of spatial and temporal analysis of the flood impacts mainly in areas with remote access and with a lack of in situ data.

Evaluation and time series analysis of mountain snow from MODIS and VIIRS fractional snow cover products

NASA Astrophysics Data System (ADS)

Bormann, K.; Rittger, K.; Painter, T. H.

2016-12-01

The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow cover products and those working in remote sensing of the mountain snowpack.

Study on Net Primary Productivity over Complicated Mountainous Area based on Multi-Source Remote Sensing Data

NASA Astrophysics Data System (ADS)

Guan, X.; Shen, H.; Li, X.; Gan, W.

2017-12-01

Mountainous area hosts approximately a quarter of the global land surface, with complex climate and ecosystem conditions. More knowledge about mountainous ecosystem could highly advance our understanding of the global carbon cycle and climate change. Net Primary Productivity (NPP), the biomass increment of plants, is a widely used ecological indicator that can be obtained by remote sensing methods. However, limited by the defective characteristic of sensors, which cannot be long-term with enough spatial details synchronously, the mountainous NPP was far from being understood. In this study, a multi-sensor fusion framework was applied to synthesize a 1-km NPP series from 1982 to 2014 in mountainous southwest China, where elevation ranged from 76m to 6740m. The validation with field-measurements proved this framework greatly improved the accuracy of NPP (r=0.79, p<0.01). The detailed spatial and temporal analysis indicated that NPP variation trends changed from decreasing to increasing with the ascending elevation, as a result of a warmer and drier climate over the region. The correlation of NPP and temperature varied from negative to positive almost at the same elevation break-point of NPP trends, but the opposite for precipitation. This phenomenon was determined by the altitudinal and seasonally uneven allocation of climatic factors, as well as the downward run-off. What is more, it was indicated that the NPP variation showed three distinct stages at the year break-point of 1992 and 2002 over the region. The NPP in low-elevation area varied almost triple more drastic than the high-elevation area for all the three stages, due to the much greater change rate of precipitation. In summary, this study innovatively conducted a long-term and accurate NPP study on the not understood mountainous ecosystem with multi-source data, the framework and conclusions will be beneficial for the further cognition of global climate change.

Marsh collapse thresholds for coastal Louisiana estimated using elevation and vegetation index data

USGS Publications Warehouse

Couvillion, Brady R.; Beck, Holly

2013-01-01

Forecasting marsh collapse in coastal Louisiana as a result of changes in sea-level rise, subsidence, and accretion deficits necessitates an understanding of thresholds beyond which inundation stress impedes marsh survival. The variability in thresholds at which different marsh types cease to occur (i.e., marsh collapse) is not well understood. We utilized remotely sensed imagery, field data, and elevation data to help gain insight into the relationships between vegetation health and inundation. A Normalized Difference Vegetation Index (NDVI) dataset was calculated using remotely sensed data at peak biomass (August) and used as a proxy for vegetation health and productivity. Statistics were calculated for NDVI values by marsh type for intermediate, brackish, and saline marsh in coastal Louisiana. Marsh-type specific NDVI values of 1.5 and 2 standard deviations below the mean were used as upper and lower limits to identify conditions indicative of collapse. As marshes seldom occur beyond these values, they are believed to represent a range within which marsh collapse is likely to occur. Inundation depth was selected as the primary candidate for evaluation of marsh collapse thresholds. Elevation relative to mean water level (MWL) was calculated by subtracting MWL from an elevation dataset compiled from multiple data types including light detection and ranging (lidar) and bathymetry. A polynomial cubic regression was used to examine a random subset of pixels to determine the relationship between elevation (relative to MWL) and NDVI. The marsh collapse uncertainty range values were found by locating the intercept of the regression line with the 1.5 and 2 standard deviations below the mean NDVI value for each marsh type. Results indicate marsh collapse uncertainty ranges of 30.7–35.8 cm below MWL for intermediate marsh, 20–25.6 cm below MWL for brackish marsh, and 16.9–23.5 cm below MWL for saline marsh. These values are thought to represent the ranges of inundation depths within which marsh collapse is probable.

Recent Changes in Glacial Area and Volume on Tuanjiefeng Peak Region of Qilian Mountains, China

PubMed Central

Xu, Junli; Liu, Shiyin; Zhang, Shiqiang; Guo, Wanqin; Wang, Jian

2013-01-01

Glaciers' runoff in the Qilian Mountains serves as a critical water resource in the northern sections of the Gansu province, the northeastern sections of the Qinghai province, and the northeastern fringe of the Tibetan Plateau. Changes in the glacial area and volume around the highest peak of the Qilian Mountains, i.e., Tuanjiefeng Peak, were estimated using multi-temporal remote-sensing images and digital elevation models, and all possible sources of uncertainty were considered in detail. The total glacier area decreased by 16.1±6.34 km2 (9.9±3.9%) during 1966 to 2010. The average annual glacier shrinkage was −0.15% a−1 from 1966 to 1995, −0.61% a−1 from 1995 to 2000, −0.20% a−1 from 2000 to 2006, and −0.45% a−1 from 2006 to 2010. A comparison of glacier surface elevations using digital elevation models derived from topographic maps in 1966 and from the Shuttle Radar Topography Mission in 1999 suggests that 65% of the grid cells has decreased, thereby indicating that the glacier thickness has declined. The average change in glacier thickness was −7.3±1.5 m (−0.21±0.04 m·a−1) from 1966 to 1999. Glaciers with northeastern aspects thinned by 8.3±1.4 m from 1966 to 1999, i.e., almost twice as much as those with southwestern aspects (4.3±1.3 m). The ice volume decreased by 11.72±2.38×108 m3 from 1966 to 1999, which was about 17.4% more than the value calculated from the statistical relationship between glacier area and volume. The relationship between glacier area change and elevation zone indicates that glacier change is not only dominated by climate change but also affected by glacier dynamics, which are related to local topography. The varied response of a single glacier to climate change indicates that the glacier area change scheme used in some models must be improved. PMID:24015174

A Methylmercury Prediction Too For Surface Waters Across The Contiguous United States (Invited)

NASA Astrophysics Data System (ADS)

Krabbenhoft, D. P.; Booth, N.; Lutz, M.; Fienen, M. N.; Saltman, T.

2009-12-01

About 20 years ago, researchers at a few locations across the globe discovered high levels of mercury in fish from remote settings lacking any obvious mercury source. We now know that for most locations atmospheric deposition is the dominant mercury source, and that mercury methylation is the key process that translates low mercury loading rates into relatively high levels in top predators of aquatic food webs. Presently, almost all US states have advisories for elevated levels of mercury in sport fish, and as a result there is considerable public awareness and concern for this nearly ubiquitous contaminant issue. In some states, “statewide” advisories have been issued because elevated fish mercury levels are so common, or the state has no effective way to monitor thousands of lakes, reservoirs, wetlands, and streams. As such, resource managers and public health officials have limited options for informing the public on of where elevated mercury concentrations in sport fish are more likely to occur than others. This project provides, for the first time, a national map of predicted (modeled) methylmercury concentrations in surface waters, which is the most toxic and bioaccumulative form of mercury in the environment. The map is the result of over two decades of research that resulted in the formulation of conceptual models of the mercury methylation process, which is strongly governed by environmental conditions - specifically hydrologic landscapes and water quality. The resulting predictive map shows clear regional trends in the distribution of methylmercury concentrations in surface waters. East of the Mississippi, the Gulf and southeastern Atlantic coast, the northeast, the lower Mississippi valley, and Great Lakes area are predicted to have generally higher environmental methylmercury levels. Higher-elevation, well-drained areas of Appalachia are predicted to have relatively lower methylmercury abundance. Other than the prairie pothole region, in the western US incessant regional patterns are less clear. However, the full range of predicted methylmercury levels are predicted to occur in western US watersheds. Lastly, although this map is being presented at the continental US scale, the principles used to generate the modeled results can easily applied to data sets that represent a range of geographic scales.

2D Flood Modelling Using Advanced Terrain Analysis Techniques And A Fully Continuous DEM-Based Rainfall-Runoff Algorithm

NASA Astrophysics Data System (ADS)

Nardi, F.; Grimaldi, S.; Petroselli, A.

2012-12-01

Remotely sensed Digital Elevation Models (DEMs), largely available at high resolution, and advanced terrain analysis techniques built in Geographic Information Systems (GIS), provide unique opportunities for DEM-based hydrologic and hydraulic modelling in data-scarce river basins paving the way for flood mapping at the global scale. This research is based on the implementation of a fully continuous hydrologic-hydraulic modelling optimized for ungauged basins with limited river flow measurements. The proposed procedure is characterized by a rainfall generator that feeds a continuous rainfall-runoff model producing flow time series that are routed along the channel using a bidimensional hydraulic model for the detailed representation of the inundation process. The main advantage of the proposed approach is the characterization of the entire physical process during hydrologic extreme events of channel runoff generation, propagation, and overland flow within the floodplain domain. This physically-based model neglects the need for synthetic design hyetograph and hydrograph estimation that constitute the main source of subjective analysis and uncertainty of standard methods for flood mapping. Selected case studies show results and performances of the proposed procedure as respect to standard event-based approaches.

Electromechanical feedback with reduced cellular connectivity alters electrical activity in an infarct injured left ventricle: a finite element model study

PubMed Central

Guccione, Julius M.; Ratcliffe, Mark B.; Sundnes, Joakim S.

2012-01-01

Myocardial infarction (MI) significantly alters the structure and function of the heart. As abnormal strain may drive heart failure and the generation of arrhythmias, we used computational methods to simulate a left ventricle with an MI over the course of a heartbeat to investigate strains and their potential implications to electrophysiology. We created a fully coupled finite element model of myocardial electromechanics consisting of a cellular physiological model, a bidomain electrical diffusion solver, and a nonlinear mechanics solver. A geometric mesh built from magnetic resonance imaging (MRI) measurements of an ovine left ventricle suffering from a surgically induced anteroapical infarct was used in the model, cycled through the cardiac loop of inflation, isovolumic contraction, ejection, and isovolumic relaxation. Stretch-activated currents were added as a mechanism of mechanoelectric feedback. Elevated fiber and cross fiber strains were observed in the area immediately adjacent to the aneurysm throughout the cardiac cycle, with a more dramatic increase in cross fiber strain than fiber strain. Stretch-activated channels decreased action potential (AP) dispersion in the remote myocardium while increasing it in the border zone. Decreases in electrical connectivity dramatically increased the changes in AP dispersion. The role of cross fiber strain in MI-injured hearts should be investigated more closely, since results indicate that these are more highly elevated than fiber strain in the border of the infarct. Decreases in connectivity may play an important role in the development of altered electrophysiology in the high-stretch regions of the heart. PMID:22058157

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

NASA Astrophysics Data System (ADS)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at the Field Research Facility at Duck, NC in September 2010 focused on assimilation of tower-based electo-optical, infrared, and radar measurements in predictions of longshore currents. Here we provide an overview of our contribution to the RIVET I experiment at New River Inlet, NC in May 2012. During the course of the 3-week measurement period, continuous tower-based remote sensing measurements were made using electro-optical, infrared, and radar techniques covering the nearshore zone and the inlet mouth. A total of 50 hours of airborne measurements were made using high-resolution infrared imagers and a customized along track interferometric synthetic aperture radar (ATI SAR). The airborne IR imagery provides kilometer-scale mapping of frontal features that evolve as the inlet flow interacts with the oceanic wave and current fields. The ATI SAR provides maps of the two-dimensional surface currents. Near-surface measurements of turbulent velocities and surface waves using SWIFT drifters, designed to measures near-surface properties relevant to remote sensing, complimented the extensive in situ measurements by RIVET investigators.

Open area 2 × 2 MIMO channel model for 2 GHz low-elevation links with diversity and capacity applications

NASA Astrophysics Data System (ADS)

Zelený, J.; Pérez-Fontán, F.; Pechac, P.; Mariño-Espiñeira, P.

2017-05-01

In civil surveillance applications, unmanned aerial vehicles (UAV) are being increasingly used in floods, fires, and law enforcement scenarios. In order to transfer large amounts of information from UAV-mounted cameras, relays, or sensors, large bandwidths are needed in comparison to those required for remotely commanding the UAV. This demands the use of higher-frequency bands, in all probability in the vicinity of 2 or 5 GHz. Novel hardware developments need propagation channel models for the ample range of operational scenarios envisaged, including multiple-input, multiple-output (MIMO) deployments. These configurations may enable a more robust transmission by increasing either the carrier-to-noise ratio statistics or the achievable capacity. In this paper, a 2 × 2 MIMO propagation channel model for an open-field environment capable of synthesizing a narrowband time series at 2 GHz is described. Maximal ratio combining diversity and capacity improvements are also evaluated through synthetic series and compared with measurement results. A simple flat, open scenario was evaluated based on which other, more complex environments can be modeled.

Urban change analysis and future growth of Istanbul.

PubMed

Akın, Anıl; Sunar, Filiz; Berberoğlu, Süha

2015-08-01

This study is aimed at analyzing urban change within Istanbul and assessing the city's future growth potential using appropriate approach modeling for the year 2040. Urban growth is a major driving force of land-use change, and spatial and temporal components of urbanization can be identified through accurate spatial modeling. In this context, widely used urban modeling approaches, such as the Markov chain and logistic regression based on cellular automata (CA), were used to simulate urban growth within Istanbul. The distance from each pixel to the urban and road classes, elevation, and slope, together with municipality and land use maps (as an excluded layer), were identified as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986, and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps, and a kappa index of agreement was derived. The results indicate that urban expansion will influence mainly forest areas during the time period of 2013-2040. The urban expansion was predicted as 429 and 327 km(2) with the Markov chain and logistic regression models, respectively.

Comparing live and remote models in eating conformity research.

PubMed

Feeney, Justin R; Polivy, Janet; Pliner, Patricia; Sullivan, Margot D

2011-01-01

Research demonstrates that people conform to how much other people eat. This conformity occurs in the presence of other people (live model) and when people view information about how much food prior participants ate (remote models). The assumption in the literature has been that remote models produce a similar effect to live models, but this has never been tested. To investigate this issue, we randomly paired participants with a live or remote model and compared their eating to those who ate alone. We found that participants exposed to both types of model differed significantly from those in the control group, but there was no significant difference between the two modeling procedures. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Topography and Landforms of Ecuador

USGS Publications Warehouse

Chirico, Peter G.; Warner, Michael B.

2005-01-01

EXPLANATION The digital elevation model of Ecuador represented in this data set was produced from over 40 individual tiles of elevation data from the Shuttle Radar Topography Mission (SRTM). Each tile was downloaded, converted from its native Height file format (.hgt), and imported into a geographic information system (GIS) for additional processing. Processing of the data included data gap filling, mosaicking, and re-projection of the tiles to form one single seamless digital elevation model. For 11 days in February of 2000, NASA, the National Geospatial-Intelligence Agency (NGA), the German Aerospace Center (DLR), and the Italian Space Agency (ASI) flew X-band and C-band radar interferometry onboard the Space Shuttle Endeavor. The mission covered the Earth between 60?N and 57?S and will provide interferometric digital elevation models (DEMs) of approximately 80% of the Earth's land mass when processing is complete. The radar-pointing angle was approximately 55? at scene center. Ascending and descending orbital passes generated multiple interferometric data scenes for nearly all areas. Up to eight passes of data were merged to form the final processed SRTM DEMs. The effect of merging scenes averages elevation values recorded in coincident scenes and reduces, but does not completely eliminate, the amount of area with layover and terrain shadow effects. The most significant form of data processing for the Ecuador DEM was gap-filling areas where the SRTM data contained a data void. These void areas are a result of radar shadow, layover, standing water, and other effects of terrain, as well as technical radar interferometry phase unwrapping issues. To fill these gaps, topographic contours were digitized from 1:50,000 - scale topographic maps which date from the mid-late 1980's (Souris, 2001). Digital contours were gridded to form elevation models for void areas and subsequently were merged with the SRTM data through GIS and remote sensing image-processing techniques. The data contained in this publication includes a gap filled, countrywide SRTM DEM of Ecuador projected in Universal Transverse Mercator (UTM) Zone 17 North projection, Provisional South American, 1956, Ecuador datum and a non gap filled SRTM DEM of the Galapagos Islands projected in UTM Zone 15 North projection. Both the Ecuador and Galapagos Islands DEMs are available as an ESRI Grid, stored as ArcInfo Export files (.e00), and in Erdas Imagine (IMG) file formats with a 90 meter pixel resolution. Also included in this publication are high and low resolution Adobe Acrobat (PDF) files of topography and landforms maps in Ecuador. The high resolution map should be used for printing and display, while the lower resolution map can be used for quick viewing and reference purposes.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

Combining hydrological modeling and remote sensing observations to enable data-driven decision making for Devils Lake flood mitigation in a changing climate

NASA Astrophysics Data System (ADS)

Zhang, X.; Lim, Y. H.; Teng, W. L.; Kirilenko, A.

2010-12-01

The water level of Devils Lake in North Dakota has been rising since 1993, reaching record highs in each of the past three years. Nearly $1 billion have already been spent in mitigating the flooding impacts. If the current wet cycle continues, Devils Lake, a terminal lake currently at 1452 ft, will likely overflow at 1458 ft and cause extensive downstream flooding, with devastating environmental and economic impacts at local, regional, and international levels. We have implemented a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model. The entire watershed with an area of about 10,000 km2 was delineated into six sub-basins using 30 m DEM, with each sub-basin having several hundred thousand hydrological cells. We generated a fine-resolution weather data set, based on a combination of ground observations and remote sensing data, to drive the hydrological simulations. Compared with a very limited number of data series available from five meteorological stations located within the watershed (none belonging to the US Historical Climate Network), NASA data offer a uniform coverage and dense distribution. The satellite and ground observations of precipitation and temperature agreed well with each other. However, if only weather station data were used, the observed runoff was underestimated by at least 30%, regardless of the value of the snow melt-rate coefficient used. The inclusion of NASA data, on the other hand, greatly improved the accuracy of runoff estimates, to within 2% of observations. Better runoff estimates will enable better predictions of water levels. The watershed hydrological model is coupled with a reservoir model, HEC-ResSim. The calibration against the observed lake elevation and monthly evaporation estimates from 2001 to 2004 showed a lake seepage varying between 500 - 1300 cfs. The coupled models can reproduce water level of the lake at sub-feet accuracy, and will be driven by the downscaled CMIP-3 projections of future climate, to provide decision support for mitigation measures in response to the potential flooding.

Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS)

NASA Astrophysics Data System (ADS)

Liu, H.; Jin, Y.; Devine, S.; Dahlgren, R. A.; Covello, S.; Larsen, R.; O'Geen, A. T.

2017-12-01

California rangelands cover 23 million hectares and support a $3.4 billion annual cattle industry. Rangeland forage production varies appreciably from year-to-year and across short distances on the landscape. Spatially explicit and near real-time information on forage production at a high resolution is critical for effective rangeland management, especially during an era of climatic extremes. We here integrated a multispectral MicaSense RedEdge camera with a 3DR solo quad-copter and acquired time-series images during the 2017 growing season over a topographically complex 10-hectare rangeland in San Luis Obispo County, CA. Soil moisture and temperature sensors were installed at 16 landscape positions, and vegetation clippings were collected at 36 plots to quantify forage dry biomass. We built four centimeter-level models for forage production mapping using time series of sUAS images and ground measurements of forage biomass and soil temperature and moisture. The biophysical model based on Monteith's eco-physiological plant growth theory estimated forage production reasonably well with a coefficient of determination (R2) of 0.86 and a root-mean-square error (RMSE) of 424 kg/ha when the soil parameters were included, and a R2 of 0.79 and a RMSE of 510 kg/ha when only remote sensing and topographical variables were included. We built two empirical models of forage production using a stepwise variable selection technique, one with soil variables. Results showed that cumulative absorbed photosynthetically active radiation (APAR) and elevation were the most important variables in both models, explaining more than 40% of the spatio-temporal variance in forage production. Soil moisture accounted for an additional 29% of the variance. Illumination condition was selected as a proxy for soil moisture in the model without soil variables, and accounted for 18% of the variance. We applied the remote sensing-based models to map daily forage production at 30-cm resolution for the whole study area during the 2017 growing season. The forage maps captured similar seasonal and spatial patterns of forage production as ground measured dry biomass. This study demonstrated a near real-time monitoring tool for ranchers to estimate forage production with sUAS technology and improved watershed-scale rangeland management.

Reduced complexity modeling of Arctic delta dynamics

NASA Astrophysics Data System (ADS)

Piliouras, A.; Lauzon, R.; Rowland, J. C.

2017-12-01

How water and sediment are routed through deltas has important implications for our understanding of nutrient and sediment fluxes to the coastal ocean. These fluxes may be especially important in Arctic environments, because the Arctic ocean receives a disproportionately large amount of river discharge and high latitude regions are expected to be particularly vulnerable to climate change. The Arctic has some of the world's largest but least studied deltas. This lack of data is due to remote and hazardous conditions, sparse human populations, and limited remote sensing resources. In the absence of data, complex models may be of limited scientific utility in understanding Arctic delta dynamics. To overcome this challenge, we adapt the reduced complexity delta-building model DeltaRCM for Arctic environments to explore the influence of sea ice and permafrost on delta morphology and dynamics. We represent permafrost by increasing the threshold for sediment erosion, as permafrost has been found to increase cohesion and reduce channel migration rates. The presence of permafrost in the model results in the creation of more elongate channels, fewer active channels, and a rougher shoreline. We consider several effects of sea ice, including introducing friction which increases flow resistance, constriction of flow by landfast ice, and changes in effective water surface elevation. Flow constriction and increased friction from ice results in a rougher shoreline, more frequent channel switching, decreased channel migration rates, and enhanced deposition offshore of channel mouths. The reduced complexity nature of the model is ideal for generating a basic understanding of which processes unique to Arctic environments may have important effects on delta evolution, and it allows us to explore a variety of rules for incorporating those processes into the model to inform future Arctic delta modelling efforts. Finally, we plan to use the modeling results to determine how the presence of permafrost and sea ice may influence delta morphology and the resulting large-scale patterns of water and sediment fluxes at the coast.

Surface elevation change over the Patagonia Ice Fields using CryoSat-2 swath altimetry

NASA Astrophysics Data System (ADS)

Foresta, Luca; Gourmelen, Noel; José Escorihuela, MarÍa; Garcia Mondejar, Albert; Wuite, Jan; Shepherd, Andrew; Roca, Mònica; Nagler, Thomas; Brockley, David; Baker, Steven; Nienow, Pete

2017-04-01

Satellite altimetry has been traditionally used in the past few decades to infer elevation of land ice, quantify changes in ice topography and infer mass balance estimates over large and remote areas such as the Greenland and Antarctic ice sheets. Radar Altimetry (RA) is particularly well suited to this task due to its all-weather year-round capability of observing the ice surface. However, monitoring of ice caps (area < 104 km^2) as well as mountain glaciers has proven more challenging. The large footprint of a conventional radar altimeter and relatively coarse ground track coverage are less suited to monitoring comparatively small regions with complex topography, so that mass balance estimates from RA rely on extrapolation methods to regionalize elevation change. Since 2010, the European Space Agency's CryoSat-2 (CS-2) satellite has collected ice elevation measurements over ice caps with its novel radar altimeter. CS-2 provides higher density of observations w.r.t. previous satellite altimeters, reduces the along-track footprint using Synthetic Aperture Radar (SAR) processing and locates the across-track origin of a surface reflector in the presence of a slope with SAR Interferometry (SARIn). Here, we exploit CS-2 as a swath altimeter [Hawley et al., 2009; Gray et al., 2013; Christie et al., 2016; Ignéczi et al., 2016, Foresta et al., 2016] over the Southern and Northern Patagonian Ice Fields (SPI and NPI, respectively). The SPI and NPI are the two largest ice masses in the southern hemisphere outside of Antarctica and are thinning very rapidly in recent decades [e.g Rignot et al., 2003; Willis et al, 2012]. However, studies of surface, volume and mass change in the literature, covering the entire SPI and NPI, are limited in number due to their remoteness, extremely complex topography and wide range of slopes. In this work, we present rates of surface elevation change for five glaciological years between 2011-2016 using swath-processed CS-2 SARIn heights and discuss the spatial and temporal coverage of elevation and its rate of change over the two regions.

Quantitative assessment of Urmia Lake water using spaceborne multisensor data and 3D modeling.

PubMed

Jeihouni, Mehrdad; Toomanian, Ara; Alavipanah, Seyed Kazem; Hamzeh, Saeid

2017-10-18

Preserving aquatic ecosystems and water resources management is crucial in arid and semi-arid regions for anthropogenic reasons and climate change. In recent decades, the water level of the largest lake in Iran, Urmia Lake, has decreased sharply, which has become a major environmental concern in Iran and the region. The efforts to revive the lake concerns the amount of water required for restoration. This study monitored and assessed Urmia Lake status over a period of 30 years (1984 to 2014) using remotely sensed data. A novel method is proposed that generates a lakebed digital elevation model (LBDEM) for Urmia Lake based on time series images from Landsat satellites, water level field measurements, remote sensing techniques, GIS, and 3D modeling. The volume of water required to restore the Lake water level to that of previous years and the ecological water level was calculated based on LBDEM. The results indicate a marked change in the area and volume of the lake from its maximum water level in 1998 to its minimum level in 2014. During this period, 86% of the lake became a salt desert and the volume of the lake water in 2013 was just 0.83% of the 1998 volume. The volume of water required to restore Urmia Lake from benchmark status (in 2014) to ecological water level (1274.10 m) is 12.546 Bm 3 , excluding evaporation. The results and the proposed method can be used by national and international environmental organizations to monitor and assess the status of Urmia Lake and support them in decision-making.

The use of multi temporal LiDAR to assess basin-scale erosion and deposition following the catastrophic January 2011 Lockyer flood, SE Queensland, Australia

NASA Astrophysics Data System (ADS)

Croke, Jacky; Todd, Peter; Thompson, Chris; Watson, Fiona; Denham, Robert; Khanal, Giri

2013-02-01

Advances in remote sensing and digital terrain processing now allow for a sophisticated analysis of spatial and temporal changes in erosion and deposition. Digital elevation models (DEMs) can now be constructed and differenced to produce DEMs of Difference (DoD), which are used to assess net landscape change for morphological budgeting. To date this has been most effectively achieved in gravel-bed rivers over relatively small spatial scales. If the full potential of the technology is to be realised, additional studies are required at larger scales and across a wider range of geomorphic features. This study presents an assessment of the basin-scale spatial patterns of erosion, deposition, and net morphological change that resulted from a catastrophic flood event in the Lockyer Creek catchment of SE Queensland (SEQ) in January 2011. Multitemporal Light Detection and Ranging (LiDAR) DEMs were used to construct a DoD that was then combined with a one-dimensional flow hydraulic model HEC-RAS to delineate five major geomorphic landforms, including inner-channel area, within-channel benches, macrochannel banks, and floodplain. The LiDAR uncertainties were quantified and applied together with a probabilistic representation of uncertainty thresholded at a conservative 95% confidence interval. The elevation change distribution (ECD) for the 100-km2 study area indicates a magnitude of elevation change spanning almost 10 m but the mean elevation change of 0.04 m confirms that a large part of the landscape was characterised by relatively low magnitude changes over a large spatial area. Mean elevation changes varied by geomorphic feature and only two, the within-channel benches and macrochannel banks, were net erosional with an estimated combined loss of 1,815,149 m3 of sediment. The floodplain was the zone of major net deposition but mean elevation changes approached the defined critical limit of uncertainty. Areal and volumetric ECDs for this extreme event provide a representative expression of the balance between erosion and deposition, and importantly sediment redistribution, which is extremely difficult to quantify using more traditional channel planform or cross-sectional surveys. The ability of LiDAR to make a rapid and accurate assessment of key geomorphic processes over large spatial scales contributes to our understanding of key processes and, as demonstrated here, to the assessment of major geomorphological hazards such as extreme flood events.

Future Plans in US Flight Missions: Using Laser Remote Sensing for Climate Science Observations

NASA Technical Reports Server (NTRS)

Callahan, Lisa W.

2010-01-01

Laser Remote Sensing provides critical climate science observations necessary to better measure, understand, model and predict the Earth's water, carbon and energy cycles. Laser Remote Sensing applications for studying the Earth and other planets include three dimensional mapping of surface topography, canopy height and density, atmospheric measurement of aerosols and trace gases, plume and cloud profiles, and winds measurements. Beyond the science, data from these missions will produce new data products and applications for a multitude of end users including policy makers and urban planners on local, national and global levels. NASA Missions in formulation including Ice, Cloud, and land Elevation Satellite (ICESat 2) and the Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI), and future missions such as the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS), will incorporate the next generation of LIght Detection And Ranging (lidar) instruments to measure changes in the surface elevation of the ice, quantify ecosystem carbon storage due to biomass and its change, and provide critical data on CO 2 in the atmosphere. Goddard's plans for these instruments and potential uses for the resulting data are described below. For the ICESat 2 mission, GSFC is developing a micro-pulse multi-beam lidar. This instrument will provide improved ice elevation estimates over high slope and very rough areas and result in improved lead detection for sea ice estimates. Data about the sea ice and predictions related to sea levels will continue to help inform urban planners as the changes in the polar ice accelerate. DESDynI is planned to be launched in 2017 and includes both lidar and radar instruments. GSFC is responsible for the lidar portion of the DESDynI mission and is developing a scanning laser altimeter that will measure the Earth's topography, the structure of tree canopies, biomass, and surface roughness. The DESDynI lidar will also measure and predict the response of ice masses to climate change and impact on sea level. Data from the lidar will ultimately be fused with radar data products with heretofore unseen results and applications. The 3-D structure of forests is critical to understanding the impact of land use and associated landscape changes on the habitat of life forms and consequently on their biodiversity. Lidar instruments are also under development to measure trace gases in the atmospheric such as CO2 and methane. GSFC is developing an active measurement approach to determine the CO2 column density and surface pressure for the proposed ASCENDS mission. The objective of this approach is to produce data on the amounts of anthropogenic and organic CO2 in the atmosphere with sufficient accuracy to meet the needs of target users including state, federal and international users as well as policy-related legislative, regulatory, and voluntary carbon-related management groups local to international interests. In summary, NASA will continue to rely on laser remote sensing for critical climate science observations and is committed to the development of the next generation of lidar instruments for a range of applications.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Acute health impacts of airborne particles estimated from satellite remote sensing.

PubMed

Wang, Zhaoxi; Liu, Yang; Hu, Mu; Pan, Xiaochuan; Shi, Jing; Chen, Feng; He, Kebin; Koutrakis, Petros; Christiani, David C

2013-01-01

Satellite-based remote sensing provides a unique opportunity to monitor air quality from space at global, continental, national and regional scales. Most current research focused on developing empirical models using ground measurements of the ambient particulate. However, the application of satellite-based exposure assessment in environmental health is still limited, especially for acute effects, because the development of satellite PM(2.5) model depends on the availability of ground measurements. We tested the hypothesis that MODIS AOD (aerosol optical depth) exposure estimates, obtained from NASA satellites, are directly associated with daily health outcomes. Three independent healthcare databases were used: unscheduled outpatient visits, hospital admissions, and mortality collected in Beijing metropolitan area, China during 2006. We use generalized linear models to compare the short-term effects of air pollution assessed by ground monitoring (PM(10)) with adjustment of absolute humidity (AH) and AH-calibrated AOD. Across all databases we found that both AH-calibrated AOD and PM(10) (adjusted by AH) were consistently associated with elevated daily events on the current day and/or lag days for cardiovascular diseases, ischemic heart diseases, and COPD. The relative risks estimated by AH-calibrated AOD and PM(10) (adjusted by AH) were similar. Additionally, compared to ground PM(10), we found that AH-calibrated AOD had narrower confidence intervals for all models and was more robust in estimating the current day and lag day effects. Our preliminary findings suggested that, with proper adjustment of meteorological factors, satellite AOD can be used directly to estimate the acute health impacts of ambient particles without prior calibrating to the sparse ground monitoring networks. Copyright © 2012 Elsevier Ltd. All rights reserved.

Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

NASA Astrophysics Data System (ADS)

Tsai, F.; Lai, J. S.; Chiang, S. H.

2015-12-01

Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results demonstrate that the accuracies of landslide susceptibility analysis in all sequential predictions have been improved significantly after eliminating landslide depositions.

Can we protect high-elevation wilderness vegetation from air pollution impacts?

Treesearch

Anna W. Schoettle

1998-01-01

Our wilderness and alpine ecosystem areas are a unique resource. While these areas are in remote locations they are not isolated from long-range atmospheric transport. The increase in regional air pollution sources may expose them to anthropogenic pollutants. The Clean Air Act of 1990, as amended, charges the Federal Land Manager (FLM) with the affirmative...

Cascading water underneath Wilkes Land, East Antarctic ice sheet, observed using altimetry and digital elevation models

NASA Astrophysics Data System (ADS)

Flament, T.; Berthier, E.; Rémy, F.

2014-04-01

We describe a major subglacial lake drainage close to the ice divide in Wilkes Land, East Antarctica, and the subsequent cascading of water underneath the ice sheet toward the coast. To analyse the event, we combined altimetry data from several sources and subglacial topography. We estimated the total volume of water that drained from Lake CookE2 by differencing digital elevation models (DEM) derived from ASTER and SPOT5 stereo imagery acquired in January 2006 and February 2012. At 5.2 ± 1.5 km3, this is the largest single subglacial drainage event reported so far in Antarctica. Elevation differences between ICESat laser altimetry spanning 2003-2009 and the SPOT5 DEM indicate that the discharge started in November 2006 and lasted approximately 2 years. A 13 m uplift of the surface, corresponding to a refilling of about 0.6 ± 0.3 km3, was observed between the end of the discharge in October 2008 and February 2012. Using the 35-day temporal resolution of Envisat radar altimetry, we monitored the subsequent filling and drainage of connected subglacial lakes located downstream of CookE2. The total volume of water traveling within the theoretical 500-km-long flow paths computed with the BEDMAP2 data set is similar to the volume that drained from Lake CookE2, and our observations suggest that most of the water released from Lake CookE2 did not reach the coast but remained trapped underneath the ice sheet. Our study illustrates how combining multiple remote sensing techniques allows monitoring of the timing and magnitude of subglacial water flow beneath the East Antarctic ice sheet.

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

NASA Technical Reports Server (NTRS)

Seinfeld, J. H. (Principal Investigator)

1982-01-01

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed.

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

NASA Technical Reports Server (NTRS)

Seinfeld, J. H. (Principal Investigator)

1982-01-01

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.

Fiber-Optic Sensor-Based Remote Acoustic Emission Measurement in a 1000 °C Environment.

PubMed

Yu, Fengming; Okabe, Yoji

2017-12-14

Recently, the authors have proposed a remote acoustic emission (AE) measurement configuration using a sensitive fiber-optic Bragg grating (FBG) sensor. In the configuration, the FBG sensor was remotely bonded on a plate, and an optical fiber was used as the waveguide to propagate AE waves from the adhesive point to the sensor. The previous work (Yu et al., Smart Materials and Structures 25 (10), 105,033 (2016)) has clarified the sensing principle behind the special remote measurement system that enables accurate remote sensing of AE signals. Since the silica-glass optical fibers have a high heat-resistance exceeding 1000 °C, this work presents a preliminary high-temperature AE detection method by using the optical fiber-based ultrasonic waveguide to propagate the AE from a high-temperature environment to a room-temperature environment, in which the FBG sensor could function as the receiver of the guided wave. As a result, the novel measurement configuration successfully achieved highly sensitive and stable AE detection in an alumina plate at elevated temperatures in the 100 °C to 1000 °C range. Due to its good performance, this detection method will be potentially useful for the non-destructive testing that can be performed in high-temperature environments to evaluate the microscopic damage in heat-resistant materials.

Estimating Discharge, Depth and Bottom Friction in Sand Bed Rivers Using Surface Currents and Water Surface Elevation Observations

NASA Astrophysics Data System (ADS)

Simeonov, J.; Czapiga, M. J.; Holland, K. T.

2017-12-01

We developed an inversion model for river bathymetry estimation using measurements of surface currents, water surface elevation slope and shoreline position. The inversion scheme is based on explicit velocity-depth and velocity-slope relationships derived from the along-channel momentum balance and mass conservation. The velocity-depth relationship requires the discharge value to quantitatively relate the depth to the measured velocity field. The ratio of the discharge and the bottom friction enter as a coefficient in the velocity-slope relationship and is determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. Completing the inversion requires an estimate of the bulk friction, which in the case of sand bed rivers is a strong function of the size of dune bedforms. We explored the accuracy of existing and new empirical closures that relate the bulk roughness to parameters such as the median grain size diameter, ratio of shear velocity to sediment fall velocity or the Froude number. For given roughness parameterization, the inversion solution is determined iteratively since the hydraulic roughness depends on the unknown depth. We first test the new hydraulic roughness parameterization using estimates of the Manning roughness in sand bed rivers based on field measurements. The coupled inversion and roughness model is then tested using in situ and remote sensing measurements of the Kootenai River east of Bonners Ferry, ID.

Integration of aerial remote sensing imaging data in a 3D-GIS environment

NASA Astrophysics Data System (ADS)

Moeller, Matthias S.

2003-03-01

For some years sensor systems have been available providing digital images of a new quality. Especially aerial stereo scanners acquire digital multispectral images with an extremely high ground resolution of about 0.10 - 0.15m and provide in addition a Digital Surface Models (DSM). These imaging products both can be used for a detailed monitoring at scales up to 1:500. The processed georeferenced multispectral orthoimages can be readily integrated into GIS making them useful for a number of applications. The DSM, derived from forward and backward facing sensors of an aerial imaging system provides a ground resolution of 0.5 m and can be used for 3D visualization purposes. In some cases it is essential, to store the ground elevation as a Digital Terrain Model (DTM) and also the height of 3-dimensional objects in a separated database. Existing automated algorithms do not work precise for the extraction of DTM from aerial scanner DSM. This paper presents a new approach which combines the visible image data and the DSM data for the generation of DTM with a reliable geometric accuracy. Already existing cadastral data can be used as a knowledge base for the extraction of building heights in cities. These elevation data is the essential source for a GIS based urban information system with a 3D visualization component.

Geospatial tools for assessing land degradation in Budgam district, Kashmir Himalaya, India

NASA Astrophysics Data System (ADS)

Rashid, Mehnaz; Lone, Mahjoor Ahmad; Romshoo, Shakil Ahmad

2011-06-01

Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS `Spatial Analyst Module'. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.

AirSWOT observations versus hydrodynamic model outputs of water surface elevation and slope in a multichannel river

NASA Astrophysics Data System (ADS)

Altenau, Elizabeth H.; Pavelsky, Tamlin M.; Moller, Delwyn; Lion, Christine; Pitcher, Lincoln H.; Allen, George H.; Bates, Paul D.; Calmant, Stéphane; Durand, Michael; Neal, Jeffrey C.; Smith, Laurence C.

2017-04-01

Anabranching rivers make up a large proportion of the world's major rivers, but quantifying their flow dynamics is challenging due to their complex morphologies. Traditional in situ measurements of water levels collected at gauge stations cannot capture out of bank flows and are limited to defined cross sections, which presents an incomplete picture of water fluctuations in multichannel systems. Similarly, current remotely sensed measurements of water surface elevations (WSEs) and slopes are constrained by resolutions and accuracies that limit the visibility of surface waters at global scales. Here, we present new measurements of river WSE and slope along the Tanana River, AK, acquired from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission. Additionally, we compare the AirSWOT observations to hydrodynamic model outputs of WSE and slope simulated across the same study area. Results indicate AirSWOT errors are significantly lower than model outputs. When compared to field measurements, RMSE for AirSWOT measurements of WSEs is 9.0 cm when averaged over 1 km squared areas and 1.0 cm/km for slopes along 10 km reaches. Also, AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics, while model outputs of spatial variations in slope are very poor. Combining AirSWOT and future SWOT measurements with hydrodynamic models can result in major improvements in model simulations at local to global scales. Scientists can use AirSWOT measurements to constrain model parameters over long reach distances, improve understanding of the physical processes controlling the spatial distribution of model parameters, and validate models' abilities to reproduce spatial variations in slope. Additionally, AirSWOT and SWOT measurements can be assimilated into lower-complexity models to try and approach the accuracies achieved by higher-complexity models.

Model for equitable care and outcomes for remote full care hemodialysis units.

PubMed

Bernstein, Keevin; Zacharias, James; Blanchard, James F; Yu, B Nancy; Shaw, Souradet Y

2010-04-01

Remotely located patients not living close to a nephrologist present major challenges for providing care. Various models of remotely delivered care have been developed, with a gap in knowledge regarding the outcomes of these heterogeneous models. This report describes a satellite care model for remote full-care hemodialysis units managed homogenously in the province of Manitoba, Canada, without onsite nephrologists. Survival in remotely located full-care units is compared with a large, urban full-care center with onsite nephrologists. Data from a Canadian provincial dialysis registry were extracted on 2663 patients between 1990 and 2005. All-cause mortality after initiation of chronic hemodialysis was assessed with Cox proportional hazards regression. Both short-term (1 year) and long-term (2 to 5 years) survival were analyzed. Survival for patients receiving remotely delivered care was shown to be better than for those receiving care in the urban care center with this particular Canadian model of care. Furthermore, there was no difference when assessing short- and long-term survival. This was independent of distance from the urban center. Chronic hemodialysis patients receiving remotely delivered care in a specialized facility attain comparable, if not better survival outcomes than their urban counterparts with direct onsite nephrology care. This model can potentially be adapted to other underserviced areas, including increasingly larger urban centers.

EPA's National Dioxin Air Monitoring Network (NDAMN): Design, implementation, and final results

NASA Astrophysics Data System (ADS)

Lorber, Matthew; Ferrario, Joseph; Byrne, Christian

2013-10-01

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m-3 with dl-PCBs contributing 0.8 fg TEQ m-3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra - through hexa PCDD/PCDF congeners, with elevations in four congeners - a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these categories were: urban = 15.9 fg TEQ m-3, rural = 13.9 fg TEQ m-3, and remote = 1.2 fg TEQ m-3. Rural sites showed elevations during the fall or winter months when compared to the spring or summer months, and the same might be said for urban sites, but the remote sites appear to show little variation over time. The four highest individual moment measurements were 847, 292, 241, and 132 fg TEQ m-3. For the 847 and 292 fg TEQ m-3 samples, the concentrations of all congeners were elevated over their site averages, but for the 241 and 132 fg TEQ m-3 measurements, only the PCDD congeners were elevated while PCDF and dl-PCB concentrations were similar to the site averages.

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

NASA Technical Reports Server (NTRS)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

NASA Technical Reports Server (NTRS)

Miller, L. D.; Tom, C.; Nualchawee, K.

1977-01-01

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

LiDAR and IFSAR-Based Flood Inundation Model Estimates for Flood-Prone Areas of Afghanistan

NASA Astrophysics Data System (ADS)

Johnson, W. C.; Goldade, M. M.; Kastens, J.; Dobbs, K. E.; Macpherson, G. L.

2014-12-01

Extreme flood events are not unusual in semi-arid to hyper-arid regions of the world, and Afghanistan is no exception. Recent flashfloods and flashflood-induced landslides took nearly 100 lives and destroyed or damaged nearly 2000 homes in 12 villages within Guzargah-e-Nur district of Baghlan province in northeastern Afghanistan. With available satellite imagery, flood-water inundation estimation can be accomplished remotely, thereby providing a means to reduce the impact of such flood events by improving shared situational awareness during major flood events. Satellite orbital considerations, weather, cost, data licensing restrictions, and other issues can often complicate the acquisition of appropriately timed imagery. Given the need for tools to supplement imagery where not available, complement imagery when it is available, and bridge the gap between imagery based flood mapping and traditional hydrodynamic modeling approaches, we have developed a topographic floodplain model (FLDPLN), which has been used to identify and map river valley floodplains with elevation data ranging from 90-m SRTM to 1-m LiDAR. Floodplain "depth to flood" (DTF) databases generated by FLDPLN are completely seamless and modular. FLDPLN has been applied in Afghanistan to flood-prone areas along the northern and southern flanks of the Hindu Kush mountain range to generate a continuum of 1-m increment flood-event models up to 10 m in depth. Elevation data used in this application of FLDPLN included high-resolution, drone-acquired LiDAR (~1 m) and IFSAR (5 m; INTERMAP). Validation of the model has been accomplished using the best available satellite-derived flood inundation maps, such as those issued by Unitar's Operational Satellite Applications Programme (UNOSAT). Results provide a quantitative approach to evaluating the potential risk to urban/village infrastructure as well as to irrigation systems, agricultural fields and archaeological sites.

Snowpack Estimates Improve Water Resources Climate-Change Adaptation Strategies

NASA Astrophysics Data System (ADS)

Lestak, L.; Molotch, N. P.; Guan, B.; Granger, S. L.; Nemeth, S.; Rizzardo, D.; Gehrke, F.; Franz, K. J.; Karsten, L. R.; Margulis, S. A.; Case, K.; Anderson, M.; Painter, T. H.; Dozier, J.

2010-12-01

Observed climate trends over the past 50 years indicate a reduction in snowpack water storage across the Western U.S. As the primary water source for the region, the loss in snowpack water storage presents significant challenges for managing water deliveries to meet agricultural, municipal, and hydropower demands. Improved snowpack information via remote sensing shows promise for improving seasonal water supply forecasts and for informing decadal scale infrastructure planning. An ongoing project in the California Sierra Nevada and examples from the Rocky Mountains indicate the tractability of estimating snowpack water storage on daily time steps using a distributed snowpack reconstruction model. Fractional snow covered area (FSCA) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data were used with modeled snowmelt from the snowpack model to estimate snow water equivalent (SWE) in the Sierra Nevada (64,515 km2). Spatially distributed daily SWE estimates were calculated for 10 years, 2000-2009, with detailed analysis for two anamolous years, 2006, a wet year and 2009, an over-forecasted year. Sierra-wide mean SWE was 0.8 cm for 01 April 2006 versus 0.4 cm for 01 April 2009, comparing favorably with known outflow. Modeled SWE was compared to in-situ (observed) SWE for 01 April 2006 for the Feather (northern Sierra, lower-elevation) and Merced (central Sierra, higher-elevation) basins, with mean modeled SWE 80% of observed SWE. Integration of spatial SWE estimates into forecasting operations will allow for better visualization and analysis of high-altitude late-season snow missed by in-situ snow sensors and inter-annual anomalies associated with extreme precipitation events/atmospheric rivers. Collaborations with state and local entities establish protocols on how to meet current and future information needs and improve climate-change adaptation strategies.

Field and airborne spectral characterization of suspected damage in red spruce (picea rubens) from Vermont

NASA Technical Reports Server (NTRS)

Rock, B. N.; Vogelmann, J. E.; Williams, D. L.

1985-01-01

The utilization of remote sensing to monitor forest damage due to acid deposition is investigated. Spectral and water measurements and aircraft radiance data of red spruce and balsam fir, collected in Camels Hump Mountain and Ripton, Vermont between August 13-20, 1984, are analyzed to evaluate the damage levels of the trees. Variations in reflectance features and canopy moisture content are studied. It is observed that damage correlates with elevation (greater damage at higher elevations); xylem water column tension is greater at higher damage sites; and a 'blue shift' is indicated in the spectral data at high damage sites.

A comparison of observed and analytically derived remote sensing penetration depths for turbid water

NASA Technical Reports Server (NTRS)

Morris, W. D.; Usry, J. W.; Witte, W. G.; Whitlock, C. H.; Guraus, E. A.

1981-01-01

The depth to which sunlight will penetrate in turbid waters was investigated. The tests were conducted in water with a single scattering albedo range, and over a range of solar elevation angles. Two different techniques were used to determine the depth of light penetration. It showed little change in the depth of sunlight penetration with changing solar elevation angle. A comparison of the penetration depths indicates that the best agreement between the two methods was achieved when the quasisingle scattering relationship was not corrected for solar angle. It is concluded that sunlight penetration is dependent on inherent water properties only.

The space station tethered elevator system

NASA Technical Reports Server (NTRS)

Anderson, Loren A.

1989-01-01

The optimized conceptual engineering design of a space station tethered elevator is presented. The elevator is an unmanned mobile structure which operates on a ten kilometer tether spanning the distance between the Space Station and a tethered platform. Elevator capabilities include providing access to residual gravity levels, remote servicing, and transportation to any point along a tether. The potential uses, parameters, and evolution of the spacecraft design are discussed. Engineering development of the tethered elevator is the result of work conducted in the following areas: structural configurations; robotics, drive mechanisms; and power generation and transmission systems. The structural configuration of the elevator is presented. The structure supports, houses, and protects all systems on board the elevator. The implementation of robotics on board the elevator is discussed. Elevator robotics allow for the deployment, retrieval, and manipulation of tethered objects. Robotic manipulators also aid in hooking the elevator on a tether. Critical to the operation of the tethered elevator is the design of its drive mechanisms, which are discussed. Two drivers, located internal to the elevator, propel the vehicle along a tether. These modular components consist of endless toothed belts, shunt-wound motors, regenerative power braking, and computer controlled linear actuators. The designs of self-sufficient power generation and transmission systems are reviewed. Thorough research indicates all components of the elevator will operate under power provided by fuel cells. The fuel cell systems will power the vehicle at seven kilowatts continuously and twelve kilowatts maximally. A set of secondary fuel cells provides redundancy in the unlikely event of a primary system failure. Power storage exists in the form of Nickel-Hydrogen batteries capable of powering the elevator under maximum loads.

Evolution of rock glaciers in Tien Shan, Central Asia, 1971 - 2016 using high-resolution stereo satellite imagery

NASA Astrophysics Data System (ADS)

Bolch, T.; Strel, A.

2017-12-01

The reactions of glaciers to climate change are relatively well known and numerous remote sensing and modelling studies exist. Also debris-covered glaciers are meanwhile relatively well investigated. However, rock glaciers react differently but respective studies are less frequent despite the fact that they also occur in many mountain ranges and can be of significance in relation to hydrology, geomorphology and hazards. Rock glaciers are abundant in Tien Shan and rock glaciers with areas larger 1 km² are common. However, investigating rock glaciers by remote sensing is difficult because their topographical changes are of lower magnitude and less evident than the changes of glaciers. Hence, high resolution imagery and digital terrain models (DTMs) are needed to study these periglacial landforms. We used 1971 Corona KH-4B (resolution 2m), 2012 GeoEye (0.5m) and 2016 Pléiades (0.5m) stereo images to map and investigate the velocity and surface elevation changes of the rock glaciers in the central part of Ile Alatau (Northern Tien Shan) in Kazakhstan. DTMs with a resolution of 5 m were generated and subsequently co-registered. Surface displacements were calculated by feature tracking. Overall we identified almost 50 active rock glaciers covering an area of about 18km², which is more than 40% of the glacier cover of the year 2016 in the investigated valleys. Moraine-type rock glaciers are more common than talus-type rock glaciers. The average surface velocity of the rock glaciers was 0.44 ± 0.30 m a-1 with rates of up to 2m a-1. On average the rock glaciers showed only a slight insignificant surface lowering of 0.04 m a-1 for the period 1971-2012 and of 0.06 m a-1 for 2012-2016. Most of the investigated rock glaciers showed similar distinct patters of change: A surface elevation gain at their fronts indicating an advance, a significant lowering in the upper probably glacier affected parts of the rock glaciers and areas of elevation gain and lowering in between caused by flow patterns and loss of subsurface ice. Analogues results were found for rock glaciers at Ak-Shirak range in Central Tien Shan using similar data. Hence, changes of rock glaciers differ significantly from debris-free and debris-covered glaciers. Work is underway to investigate the rock glaciers more in detail including in-situ measurements using geophysics.

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

PubMed

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Towards an improved Land Surface Phenology mapping using a new MODIS product: A case study of Bavarian Forest National Park

NASA Astrophysics Data System (ADS)

Misra, Gourav; Buras, Allan; Asam, Sarah; Menzel, Annette

2017-04-01

Past work in remote sensing of land surface phenology have mapped vegetation cycles at multiple scales. Much has been discussed and debated about the uncertainties associated with the selection of data, data processing and the eventual conclusions drawn. Several studies do however provide evidence of strong links between different land surface phenology (LSP) metrics with specific ground phenology (GP) (Fisher and Mustard, 2007; Misra et al., 2016). Most importantly the use of high temporal and spatial resolution remote sensing data and ground truth information is critical for such studies. In this study, we use a higher temporal resolution 4 day MODIS NDVI product developed by EURAC (Asam et al., in prep) for the Bavarian Forest National Park during 2002-2015 period and extract various phenological metrics covering different phenophases of vegetation (start of season / sos and end of season / eos). We found the LSP-sos to be more strongly linked to the elevation of the area than LSP-eos which has been cited to be harder to detect (Stöckli et al., 2008). The LSP metrics were also correlated to GP information at 4 different stations covering elevations ranging from approx. 500 to 1500 metres. Results show that among the five dominant species in the area i.e. European ash, Norway spruce, European beech, Norway maple and orchard grass, only particular GP observations for some species show stronger correlations with LSP than others. Spatial variations in the LSP-GP correlations were also observed, with certain areas of the National Park showing positive correlations and others negative. An analysis of temporal trends of LSP also indicates the possibility to detect those areas in the National Park that were affected by extreme events. Further investigations are planned to explain the heterogeneity in the derived LSP metrics using high resolution ground truth data and multivariate statistical analyses. Acknowledgement: This research received funding from the Bavarian State Ministry of the Environment and Consumer Protection. References: 1. Fisher, J.I.; Mustard, J.F. Cross-scalar satellite phenology from ground, Landsat, and MODIS data. Remote Sens. Environ. 2007, 109, 261-273. 2. Misra, G.; Buras, A.; Menzel, A. Effects of Different Methods on the Comparison be-tween Land Surface and Ground Phenology—A Methodological Case Study from South-Western Germany. Remote Sens. 2016, 8, 753. 3. Asam, S.; Callegari, M.; Fiore, G.; Matiu, M.; De Gregorio, L.; Jacob, A.; Staab, J.; Men-zel, A.; Notarnicola, C. Analysis of spatiotemporal variations of climate, snow cover and plant phenology over the Alps. 2017 (in preparation). 4. Stöckli, R.; Rutishauser, T.; Dragoni, D.; O'Keefe, J.; Thornton, P. E.; Jolly, M.; Lu, L.; Denning, A. S. Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research: Biogeosciences. 2008, 113.

Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity - The Gaza case study

NASA Astrophysics Data System (ADS)

Gampe, David; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating seven test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. One of those seven sites is the Gaza Strip, located in the Eastern Mediterranean and part of the Palestinian Autonomous Area, covers an area of 365km² with a length of 35km and 6 to 12km in width. Elevation ranges from sea level up to 104m in the East of the test site. Mean annual precipitation varies from 235mm in the South to 420mm in the North of the area. The inter annual variability of rainfall and the rapid population growth in an highly agricultural used area represent the major challenges in this area. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) is setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. WaSiM was driven with meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. For the parameterization of the vegetation the Leaf Area Index (LAI) is a crucial component. However, the LAI is difficult to access at field scale, hence a simple remote sensing approach, using the Normalized Difference Vegetation Index (NDVI) and MODIS LAI information, was applied for the parameterization in WaSiM. As no permanent streams, hence no discharge measurements, exist in the Gaza Strip, the actual evapotranspiration (ETact) outputs of the model were used for model validation. Landsat TM images were applied to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season.

Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

NASA Astrophysics Data System (ADS)

Wang, R.; Chen, J. M.; Luo, X.

2016-12-01

Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

NASA Astrophysics Data System (ADS)

Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

2017-11-01

Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

Remote sensing-based predictors improve distribution models of rare, early successional and boradleaf tree species in Utah

Treesearch

N. E. Zimmermann; T. C. Edwards; G. G. Moisen; T. S. Frescino; J. A. Blackard

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species...

Offshore Wind Resource Characterization | Wind | NREL

Science.gov Websites

identify critical data needed. Remote Sensing and Modeling Photo of the SeaZephIR Prototype at sea. 2009 techniques such as remote sensing and modeling to provide data on design conditions. Research includes comparing the data provided by remote sensing devices and models to data collected by traditional methods

Remote sensing analysis of vegetation recovery following short-interval fires in Southern California shrublands.

PubMed

Meng, Ran; Dennison, Philip E; D'Antonio, Carla M; Moritz, Max A

2014-01-01

Increased fire frequency has been shown to promote alien plant invasions in the western United States, resulting in persistent vegetation type change. Short interval fires are widely considered to be detrimental to reestablishment of shrub species in southern California chaparral, facilitating the invasion of exotic annuals and producing "type conversion". However, supporting evidence for type conversion has largely been at local, site scales and over short post-fire time scales. Type conversion has not been shown to be persistent or widespread in chaparral, and past range improvement studies present evidence that chaparral type conversion may be difficult and a relatively rare phenomenon across the landscape. With the aid of remote sensing data covering coastal southern California and a historical wildfire dataset, the effects of short interval fires (<8 years) on chaparral recovery were evaluated by comparing areas that burned twice to adjacent areas burned only once. Twelve pairs of once- and twice-burned areas were compared using normalized burn ratio (NBR) distributions. Correlations between measures of recovery and explanatory factors (fire history, climate and elevation) were analyzed by linear regression. Reduced vegetation cover was found in some lower elevation areas that were burned twice in short interval fires, where non-sprouting species are more common. However, extensive type conversion of chaparral to grassland was not evident in this study. Most variables, with the exception of elevation, were moderately or poorly correlated with differences in vegetation recovery.

Characterizing the landscape dynamics of an invasive plant and risk of invasion using remote sensing.

PubMed

Bradley, Bethany A; Mustard, John F

2006-06-01

Improved understanding of the spatial dynamics of invasive plant species may lead to more effective land management and reduced future invasion. Here, we identified the spatial extents of nonnative cheatgrass (Bromus tectorum) in the north central Great Basin using remotely sensed data from Landsat MSS, TM, and ETM+. We compared cheatgrass extents in 1973 and 2001 to six spatially explicit landscape variables: elevation, aspect, hydrographic channels, cultivation, roads, and power lines. In 2001, Cheatgrass was 10% more likely to be found in elevation ranges from 1400 to 1700 m (although the data suggest a preferential invasion into lower elevations by 2001), 6% more likely on west and northwest facing slopes, and 3% more likely within hydrographic channels. Over this time period, cheatgrass expansion was also closely linked to proximity to land use. In 2001, cheatgrass was 20% more likely to be found within 3 km of cultivation, 13% more likely to be found within 700 m of a road, and 15% more likely to be found within 1 km of a power line. Finally, in 2001 cheatgrass was 26% more likely to be present within 150 m of areas occupied by cheatgrass in 1973. Using these relationships, we created a risk map of future cheatgrass invasion that may aid land management. These results highlight the importance of including land use variables and the extents of current plant invasion in predictions of future risk.

Remote Sensing Analysis of Vegetation Recovery following Short-Interval Fires in Southern California Shrublands

PubMed Central

Meng, Ran; Dennison, Philip E.; D’Antonio, Carla M.; Moritz, Max A.

2014-01-01

Increased fire frequency has been shown to promote alien plant invasions in the western United States, resulting in persistent vegetation type change. Short interval fires are widely considered to be detrimental to reestablishment of shrub species in southern California chaparral, facilitating the invasion of exotic annuals and producing “type conversion”. However, supporting evidence for type conversion has largely been at local, site scales and over short post-fire time scales. Type conversion has not been shown to be persistent or widespread in chaparral, and past range improvement studies present evidence that chaparral type conversion may be difficult and a relatively rare phenomenon across the landscape. With the aid of remote sensing data covering coastal southern California and a historical wildfire dataset, the effects of short interval fires (<8 years) on chaparral recovery were evaluated by comparing areas that burned twice to adjacent areas burned only once. Twelve pairs of once- and twice-burned areas were compared using normalized burn ratio (NBR) distributions. Correlations between measures of recovery and explanatory factors (fire history, climate and elevation) were analyzed by linear regression. Reduced vegetation cover was found in some lower elevation areas that were burned twice in short interval fires, where non-sprouting species are more common. However, extensive type conversion of chaparral to grassland was not evident in this study. Most variables, with the exception of elevation, were moderately or poorly correlated with differences in vegetation recovery. PMID:25337785

Feasibility of remote sensing for detecting thermal pollution. Part 1: Feasibility study. Part 2: Implementation plan. [coastal ecology

NASA Technical Reports Server (NTRS)

Veziroglu, T. N.; Lee, S. S.

1973-01-01

A feasibility study for the development of a three-dimensional generalized, predictive, analytical model involving remote sensing, in-situ measurements, and an active system to remotely measure turbidity is presented. An implementation plan for the development of the three-dimensional model and for the application of remote sensing of temperature and turbidity measurements is outlined.

Data Assimilation of AirSWOT and Synthetically Derived SWOT Observations of Water Surface Elevation in a Multichannel River

NASA Astrophysics Data System (ADS)

Altenau, E. H.; Pavelsky, T.; Andreadis, K.; Bates, P. D.; Neal, J. C.

2017-12-01

Multichannel rivers continue to be challenging features to quantify, especially at regional and global scales, which is problematic because accurate representations of such environments are needed to properly monitor the earth's water cycle as it adjusts to climate change. It has been demonstrated that higher-complexity, 2D models outperform lower-complexity, 1D models in simulating multichannel river hydraulics at regional scales due to the inclusion of the channel network's connectivity. However, new remote sensing measurements from the future Surface Water and Ocean Topography (SWOT) mission and it's airborne analog AirSWOT offer new observations that can be used to try and improve the lower-complexity, 1D models to achieve accuracies closer to the higher-complexity, 2D codes. Here, we use an Ensemble Kalman Filter (EnKF) to assimilate AirSWOT water surface elevation (WSE) measurements from a 2015 field campaign into a 1D hydrodynamic model along a 90 km reach of Tanana River, AK. This work is the first to test data assimilation methods using real SWOT-like data from AirSWOT. Additionally, synthetic SWOT observations of WSE are generated across the same study site using a fine-resolution 2D model and assimilated into the coarser-resolution 1D model. Lastly, we compare the abilities of AirSWOT and the synthetic-SWOT observations to improve spatial and temporal model outputs in WSEs. Results indicate 1D model outputs of spatially distributed WSEs improve as observational coverage increases, and improvements in temporal fluctuations in WSEs depend on the number of observations. Furthermore, results reveal that assimilation of AirSWOT observations produce greater error reductions in 1D model outputs compared to synthetic SWOT observations due to lower measurement errors. Both AirSWOT and the synthetic SWOT observations significantly lower spatial and temporal errors in 1D model outputs of WSEs.

ASTER Global DEM contribution to GEOSS demonstrates open data sharing

NASA Astrophysics Data System (ADS)

Sohre, T.; Duda, K. A.; Meyer, D. J.; Behnke, J.; Nasa Esdis Lp Daac

2010-12-01

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing instrument on the Terra spacecraft has been acquiring images of Earth since launch in 1999. Throughout this time data products have been openly available to the general public through sites in the U.S. and Japan. As the ASTER mission matured, a spatially broad and temporally deep data archive was gradually established. With this extensive accumulation of Earth observations, it became possible to create a new global digital elevation product, the ASTER Global Digital Elevation Model (GDEM), using multi-temporal data, resulting in over 22,000 static 10 X 10 tiles. The ASTER GDEM was contributed by Japan’s Ministry of Economy Trade and Industry (METI) and the U.S. National Aeronautics and Space Administration (NASA) to the Global Earth Observation System of Systems (GEOSS) for distribution at no cost to users. As such, both METI and NASA desired to understand the uses of the ASTER GDEM, expressed as one of the GEOSS applications themes: disasters, health, energy, climate, water, weather, ecosystems, agriculture or biodiversity. This required both the registration of users, and restrictions on redistribution, to capture the intended use in terms of the GEOSS themes. The ASTER GDEM was made available to users worldwide via electronic download from the Earth Remote Sensing Data Analysis Center (ERSDAC) of Japan and from NASA’s Land Processes Distributed Active Archive Center (LP DAAC). During the first three months after product release, over 4 million GDEM tiles were distributed from the LP DAAC and ERSDAC. The ASTER GDEM release generated nearly 20,000 new user registrations in the NASA EOS ClearingHOuse (ECHO)/WIST and the ERSDAC systems. By the end of 2009, over 6.5 Million GDEM tiles were distributed by the LP DAAC and ERSDAC. Users have requested tiles over specific areas of interest as well as the entire dataset for global research. Intense global interest in the GDEM across all the GEOSS Societal Benefit areas was shown. The release of the global tiled research-grade DEM resulted in a significant increase in demand for ASTER elevation models, and increased awareness of related products. No cost access to these data has also promoted new applications of remotely sensed data, increasing their use across the full range of the GEOSS societal benefit areas. In addition, the simplified data access and greatly expanded pool of users resulted in a number of suggestions from researchers in many disciplines for possible enhancements to future versions of the ASTER GDEM. The broad distribution of the product can be directly attributed to the adoption of fundamental GEOSS data sharing principles, which are directed toward expanded access by minimizing time delay and cost, thus facilitating data use for education, research, and a range of other applications. The ASTER GDEM demonstrated the need and user demand for an improved global DEM product as well as the added benefit of not only “full and open” distribution, but “free and open” distribution.

Mapping three-dimensional geological features from remotely-sensed images and digital elevation models

NASA Astrophysics Data System (ADS)

Morris, Kevin Peter

Accurate mapping of geological structures is important in numerous applications, ranging from mineral exploration through to hydrogeological modelling. Remotely sensed data can provide synoptic views of study areas enabling mapping of geological units within the area. Structural information may be derived from such data using standard manual photo-geologic interpretation techniques, although these are often inaccurate and incomplete. The aim of this thesis is, therefore, to compile a suite of automated and interactive computer-based analysis routines, designed to help a the user map geological structure. These are examined and integrated in the context of an expert system. The data used in this study include Digital Elevation Model (DEM) and Airborne Thematic Mapper images, both with a spatial resolution of 5m, for a 5 x 5 km area surrounding Llyn Cow lyd, Snowdonia, North Wales. The geology of this area comprises folded and faulted Ordo vician sediments intruded throughout by dolerite sills, providing a stringent test for the automated and semi-automated procedures. The DEM is used to highlight geomorphological features which may represent surface expressions of the sub-surface geology. The DEM is created from digitized contours, for which kriging is found to provide the best interpolation routine, based on a number of quantitative measures. Lambertian shading and the creation of slope and change of slope datasets are shown to provide the most successful enhancement of DEMs, in terms of highlighting a range of key geomorphological features. The digital image data are used to identify rock outcrops as well as lithologically controlled features in the land cover. To this end, a series of standard spectral enhancements of the images is examined. In this respect, the least correlated 3 band composite and a principal component composite are shown to give the best visual discrimination of geological and vegetation cover types. Automatic edge detection (followed by line thinning and extraction) and manual interpretation techniques are used to identify a set of 'geological primitives' (linear or arc features representing lithological boundaries) within these data. Inclusion of the DEM data provides the three-dimensional co-ordinates of these primitives enabling a least-squares fit to be employed to calculate dip and strike values, based, initially, on the assumption of a simple, linearly dipping structural model. A very large number of scene 'primitives' is identified using these procedures, only some of which have geological significance. Knowledge-based rules are therefore used to identify the relevant. For example, rules are developed to identify lake edges, forest boundaries, forest tracks, rock-vegetation boundaries, and areas of geomorphological interest. Confidence in the geological significance of some of the geological primitives is increased where they are found independently in both the DEM and remotely sensed data. The dip and strike values derived in this way are compared to information taken from the published geological map for this area, as well as measurements taken in the field. Many results are shown to correspond closely to those taken from the map and in the field, with an error of < 1°. These data and rules are incorporated into an expert system which, initially, produces a simple model of the geological structure. The system also provides a graphical user interface for manual control and interpretation, where necessary. Although the system currently only allows a relatively simple structural model (linearly dipping with faulting), in the future it will be possible to extend the system to model more complex features, such as anticlines, synclines, thrusts, nappes, and igneous intrusions.

Development of a remote digital augmentation system and application to a remotely piloted research vehicle

NASA Technical Reports Server (NTRS)

Edwards, J. W.; Deets, D. A.

1975-01-01

A cost-effective approach to flight testing advanced control concepts with remotely piloted vehicles is described. The approach utilizes a ground based digital computer coupled to the remotely piloted vehicle's motion sensors and control surface actuators through telemetry links to provide high bandwidth feedback control. The system was applied to the control of an unmanned 3/8-scale model of the F-15 airplane. The model was remotely augmented; that is, the F-15 mechanical and control augmentation flight control systems were simulated by the ground-based computer, rather than being in the vehicle itself. The results of flight tests of the model at high angles of attack are discussed.

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

PubMed Central

Yang, Bao; He, Minhui; Shishov, Vladimir; Tychkov, Ivan; Vaganov, Eugene; Rossi, Sergio; Ljungqvist, Fredrik Charpentier; Bräuning, Achim; Grießinger, Jussi

2017-01-01

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world’s largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960–2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960–2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982–2014. No significant changes in SOS or EOS were observed during 1960–1981. April–June and August–September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April–June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale. PMID:28630302

Earth Observation and Geospatial techniques for Soil Salinity and Land Capability Assessment over Sundarban Bay of Bengal Coast, India

NASA Astrophysics Data System (ADS)

Das, Sumanta; Choudhury, Malini Roy; Das, Subhasish; Nagarajan, M.

2016-12-01

To guarantee food security and job creation of small scale farmers to commercial farmers, unproductive farms in the South 24 PGS, West Bengal need land reform program to be restructured and evaluated for agricultural productivity. This study established a potential role of remote sensing and GIS for identification and mapping of salinity zone and spatial planning of agricultural land over the Basanti and Gosaba Islands(808.314sq. km) of South 24 PGS. District of West Bengal. The primary data i.e. soil pH, Electrical Conductivity (EC) and Sodium Absorption ratio (SAR) were obtained from soil samples of various GCP (Ground Control Points) locations collected at 50 mts. intervals by handheld GPS from 0-100 cm depths. The secondary information is acquired from the remotely sensed satellite data (LANDSAT ETM+) in different time scale and digital elevation model. The collected field samples were tested in the laboratory and were validated with Remote Sensing based digital indices analysisover the temporal satellite data to assess the potential changes due to over salinization. Soil physical properties such as texture, structure, depth and drainage condition is stored as attributes in a geographical soil database and linked with the soil map units. The thematic maps are integrated with climatic and terrain conditions of the area to produce land capability maps for paddy. Finally, The weighted overlay analysis was performed to assign theweights according to the importance of parameters taken into account for salineareaidentification and mapping to segregate higher, moderate, lower salinity zonesover the study area.

Using LiDAR data to measure the 3D green biomass of Beijing urban forest in China.

PubMed

He, Cheng; Convertino, Matteo; Feng, Zhongke; Zhang, Siyu

2013-01-01

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m(3), of which coniferous was 28.7871 million m(3) and broad-leaf was 370.3424 million m(3). The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities.

Using LiDAR Data to Measure the 3D Green Biomass of Beijing Urban Forest in China

PubMed Central

He, Cheng; Convertino, Matteo; Feng, Zhongke; Zhang, Siyu

2013-01-01

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m3, of which coniferous was 28.7871 million m3 and broad-leaf was 370.3424 million m3. The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities. PMID:24146792

Regional landslide susceptibility assessment using multi-stage remote sensing data along the coastal range highway in northeastern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ching-Fang; Huang, Wei-Kai; Chang, Yu-Lin; Chi, Shu-Yeong; Liao, Wu-Chang

2018-01-01

Typhoons Megi (2010) and Saola (2012) brought torrential rainfall which triggered regional landslides and flooding hazards along Provincial Highway No. 9 in northeastern Taiwan. To reduce property loss and saving lives, this study combines multi-hazard susceptibility assessment with environmental geology map a rock mass rating system (RMR), remote sensing analysis, and micro-topography interpretation to develop an integrated landslide hazard assessment approach and reflect the intrinsic state of slopeland from the past toward the future. First, the degree of hazard as indicated by historical landslides was used to determine many landslide regions in the past. Secondly, geo-mechanical classification of rock outcroppings was performed by in-situ investigation along the vulnerable road sections. Finally, a high-resolution digital elevation model was extracted from airborne LiDAR and multi-temporal remote sensing images which was analyzed to discover possible catastrophic landslide hotspot shortly. The results of the analysis showed that 37% of the road sections in the study area were highly susceptible to landslide hazards. The spatial distribution of the road sections revealed that those characterized by high susceptibility were located near the boundaries of fault zones and in areas of lithologic dissimilarity. Headward erosion of gullies and concave-shaped topographic features had an adverse effect and was the dominant factor triggering landslides. Regional landslide reactivation on this coastal highway are almost related to the past landslide region based on hazard statistics. The final results of field validation demonstrated that an accuracy of 91% could be achieved for forecasting geohazard followed by intense rainfall events and typhoons.

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

NASA Astrophysics Data System (ADS)

Yang, Bao; He, Minhui; Shishov, Vladimir; Tychkov, Ivan; Vaganov, Eugene; Rossi, Sergio; Charpentier Ljungqvist, Fredrik; Bräuning, Achim; Grießinger, Jussi

2017-07-01

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world’s largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960-2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960-2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982-2014. No significant changes in SOS or EOS were observed during 1960-1981. April-June and August-September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April-June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale.

Testing a model-driven Geographical Information System for risk assessment during an effusive volcanic crisis

NASA Astrophysics Data System (ADS)

Harris, Andrew; Latutrie, Benjamin; Andredakis, Ioannis; De Groeve, Tom; Langlois, Eric; van Wyk de Vries, Benjamin; Del Negro, Ciro; Favalli, Massimiliano; Fujita, Eisuke; Kelfoun, Karim; Rongo, Rocco

2016-04-01

RED-SEED stands for Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters, and combines stakeholders from the remote sensing, modeling and response communities with experience in tracking volcanic effusive events. It is an informal working group that has evolved around the philosophy of combining global scientific resources, in the realm of physical volcanology, remote sensing and modeling, to better define and limit uncertainty. The group first met during a three day-long workshop held in Clermont Ferrand (France) between 28 and 30 May 2013. The main recommendation of the workshop in terms of modeling was that there is a pressing need for "real-time input of reliable Time-Averaged Discharge Rate (TADR) data with regular up-dates of Digital Elevation Models (DEMs) if modeling is to be effective; the DEMs can be provided by the radar/photogrammetry community." We thus set up a test to explore (i) which model source terms are needed, (ii) how they can be provided and updated, and (iii) how can models be run and applied in an ensemble approach. The test used two hypothetical effusive events in the Chaîne des Puys (Auvergne, France), for which a prototype Geographical Information System (GIS) was set up to allow loss assessment during an effusive crisis. This system drew on all immediately available data for population, land use, communications, utility and building-type. After defining lava flow model source terms (vent location, effusion rate, lava chemistry, temperature, crystallinity and vesicularity), five operational lava flow emplacement models were run (DOWNFLOW, FLOWGO, LAVASIM, MAGFLOW and VOLCFLOW) to produce a projection for likelihood of impact for all pixels within the area covered by the GIS, based on agreement between models. The test thus aimed not to assess the model output, but instead to examine overlapping output. Next, inundation maps and damage reports for impacted zones were produced. The exercise identified several shortcomings of the modeling systems, but indicates that generation of a global response system for effusive crises that uses rapid-response model projections for lava inundation driven by real-time satellite hot spot detection - and open access data sets - is within the current capabilities of the community.

Stream Temperature Estimation From Thermal Infrared Images

NASA Astrophysics Data System (ADS)

Handcock, R. N.; Kay, J. E.; Gillespie, A.; Naveh, N.; Cherkauer, K. A.; Burges, S. J.; Booth, D. B.

2001-12-01

Stream temperature is an important water quality indicator in the Pacific Northwest where endangered fish populations are sensitive to elevated water temperature. Cold water refugia are essential for the survival of threatened salmon when events such as the removal of riparian vegetation result in elevated stream temperatures. Regional assessment of stream temperatures is limited by sparse sampling of temperatures in both space and time. If critical watersheds are to be properly managed it is necessary to have spatially extensive temperature measurements of known accuracy. Remotely sensed thermal infrared (TIR) imagery can be used to derive spatially distributed estimates of the skin temperature (top 100 nm) of streams. TIR imagery has long been used to estimate skin temperatures of the ocean, where split-window techniques have been used to compensate for atmospheric affects. Streams are a more complex environment because 1) most are unresolved in typical TIR images, and 2) the near-bank environment of stream corridors may consist of tall trees or hot rocks and soils that irradiate the stream surface. As well as compensating for atmospheric effects, key problems to solve in estimating stream temperatures include both subpixel unmixing and multiple scattering. Additionally, fine resolution characteristics of the stream surface such as evaporative cooling due to wind, and water surface roughness, will effect measurements of radiant skin temperatures with TIR devices. We apply these corrections across the Green River and Yakima River watersheds in Washington State to assess the accuracy of remotely sensed stream surface temperature estimates made using fine resolution TIR imagery from a ground-based sensor (FLIR), medium resolution data from the airborne MASTER sensor, and coarse-resolution data from the Terra-ASTER satellite. We use linear spectral mixture analysis to isolate the fraction of land-leaving radiance originating from unresolved streams. To compensate the data for atmospheric effects we combine radiosonde profiles with a physically based radiative transfer model (MODTRAN) and an in-scene relative correction adapted from the ISAC algorithm. Laboratory values for water emissivities are used as a baseline estimate of stream emissivities. Emitted radiance reflected by trees in the stream near-bank environment is estimated from the height and canopy temperature, using a radiosity model.

Application of High Resolution Topography and Remote Sensing: Imagery to the Kinematics of Fold-and-Thrust Belts

NASA Technical Reports Server (NTRS)

Rubin, Charles

1997-01-01

This report summarizes one year of funding for NASA contract NAGW-3691, Application of High Resolution Topography and Remote Sensing: Imagery to the Kinematics of Fold-and-Thrust Belts. I never received year three from NASA. The funds were to support on going tectonic and topographic studies along the front of the central Transverse Ranges and expand the topographic studies to the north. Below are results from the first two years of actual funds that I received from NASA (see attached Federal Cash Transaction Reports). The main focus of this contract was to define and understand the major tectonic processes affecting the formation and evolution of the topography in convergent tectonic settings. The results will be used to test ongoing space-based geodetic measurements and will be compared with present-day seismicity in the central Transverse Ranges and adjacent basins. Two major factors that controls topography in active regions are (1) tectonic uplift due to fault-normal compression and (2) subsequent erosion. The central Transverse and Temblor Ranges are excellent regions for these focused topographic studies. The tectonic processes leading to the mountain building are relatively straightforward and thus are easy to model. Available evidence suggests that the topography in this region is relatively young, - 3.5 Ma or less. In addition,, erosional processes may be relatively easier to model compared to larger and more ancient mountain belts. For example, in larger mountain belts, topographic relief may cause significant orographic effects and high elevation may result in part of the topography located above snowline. Both factors complicate interpretation of erosional processes that may be controlled by elevation. Mountain ranges that are significantly older may have experienced a much wider variety of erosional or climatic conditions over their lifetime. While erosion rates have certainly not been consistent in the Transverse or Temblor ranges over its 3.5 Ma lifetime, we are sure that the region was spared the Pleistocene glaciation that affected parts of the Sierra Nevada Range.

Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea.

PubMed

Venter, Michelle; Dwyer, John; Dieleman, Wouter; Ramachandra, Anurag; Gillieson, David; Laurance, Susan; Cernusak, Lucas A; Beehler, Bruce; Jensen, Rigel; Bird, Michael I

2017-11-01

Our ability to model global carbon fluxes depends on understanding how terrestrial carbon stocks respond to varying environmental conditions. Tropical forests contain the bulk of the biosphere's carbon. However, there is a lack of consensus as to how gradients in environmental conditions affect tropical forest carbon. Papua New Guinea (PNG) lies within one of the largest areas of contiguous tropical forest and is characterized by environmental gradients driven by altitude; yet, the region has been grossly understudied. Here, we present the first field assessment of aboveground biomass (AGB) across three main forest types of PNG using 193 plots stratified across 3,100-m elevation gradient. Unexpectedly, AGB had no direct relationship to rainfall, temperature, soil, or topography. Instead, natural disturbances explained most variation in AGB. While large trees (diameter at breast height > 50 cm) drove altitudinal patterns of AGB, resulting in a major peak in AGB (2,200-3,100 m) and some of the most carbon-rich forests at these altitudes anywhere. Large trees were correlated to a set of climatic variables following a hump-shaped curve. The set of "optimal" climatic conditions found in montane cloud forests is similar to that of maritime temperate areas that harbor the largest trees in the world: high ratio of precipitation to evapotranspiration (2.8), moderate mean annual temperature (13.7°C), and low intra-annual temperature range (7.5°C). At extreme altitudes (2,800-3,100 m), where tree diversity elsewhere is usually low and large trees are generally rare or absent, specimens from 18 families had girths >70 cm diameter and maximum heights 20-41 m. These findings indicate that simple AGB-climate-edaphic models may not be suitable for estimating carbon storage in forests where optimal climate niches exist. Our study, conducted in a very remote area, suggests that tropical montane forests may contain greater AGB than previously thought and the importance of securing their future under a changing climate is therefore enhanced. © 2017 John Wiley & Sons Ltd.

Mapping Geohazards in the Churia Region of Nepal: An Application of Remote Sensing and Geographic Information Systems

NASA Astrophysics Data System (ADS)

Bannister, Terri

The Churia region of Nepal is experiencing serious environmental degradation due to landslides, monsoon flooding, land use changes, and gravel excavation. The objectives of this study were to quantify the temporal change of landslides as related to changes in land use/deforestation/urbanization, to quantify the temporal change and extent of river inundation in the Terai, to quantify the extent to which stone quarrying exacerbates the degradation process, and to generate a landslide hazard risk map. Gravel extraction and precipitation data, along with field work and geospatial methods, were used to map degradation by focusing on the centrally located districts of Bara, Rautahat, and Makwanpur. Landsat land use classifications were conducted on imagery from 1976, 1988, 1999, and 2015. A modified Normalized Difference Mid-Infrared (NDMIDIR) algorithm was created by incorporating slope, elevation, and land use types to identify landslide scars. A GIS model using weighted landslide variables derived from remote sensing and GIS methods to predict landslide susceptibility was created. These variables include hydrology, settlement, lithology, geology, precipitation, infrastructure, elevation, slope, aspect, land use, and previous landslides. Gravel excavation in 2007/2008 was nearly 700% higher than in 2001/2002. The Normalized Difference Vegetation Index (NDVI) results showed that the study area is losing 1.03% forest cover annually; in 1977, there was 70% forest cover, but only 32% forest cover remained in 2016. The accuracy assessment of the 2015 Landsat 8 land use classification was 79%. NDMIDIR results showed that from 1988 to 2016, the total area representing landslide scars increased from 7.26km2 to 8.73 km2. The weighted variable GIS model output map indicated that 70% of the Siwalik zone and southern Lesser Himalayan zone in the three study districts have significant risk of landslides. Landslides and flooding from heavy monsoon rain, deforestation to develop agriculture and urbanization, and gravel extraction have caused rapid and ongoing environmental degradation in the Churia region of Nepal. Results provide information for disaster management and assist policy planners in landslide prone areas decrease loss of lives and property.

Reconstruction of the sea surface elevation from the analysis of the data collected by a wave radar system

NASA Astrophysics Data System (ADS)

Ludeno, Giovanni; Soldovieri, Francesco; Serafino, Francesco; Lugni, Claudio; Fucile, Fabio; Bulian, Gabriele

2016-04-01

X-band radar system is able to provide information about direction and intensity of the sea surface currents and dominant waves in a range of few kilometers from the observation point (up to 3 nautical miles). This capability, together with their flexibility and low cost, makes these devices useful tools for the sea monitoring either coastal or off-shore area. The data collected from wave radar system can be analyzed by using the inversion strategy presented in [1,2] to obtain the estimation of the following sea parameters: peak wave direction; peak period; peak wavelength; significant wave height; sea surface current and bathymetry. The estimation of the significant wave height represents a limitation of the wave radar system because of the radar backscatter is not directly related to the sea surface elevation. In fact, in the last period, substantial research has been carried out to estimate significant wave height from radar images either with or without calibration using in-situ measurements. In this work, we will present two alternative approaches for the reconstruction of the sea surface elevation from wave radar images. In particular, the first approach is based on the basis of an approximated version of the modulation transfer function (MTF) tuned from a series of numerical simulation, following the line of[3]. The second approach is based on the inversion of radar images using a direct regularised least square technique. Assuming a linearised model for the tilt modulation, the sea elevation has been reconstructed as a least square fitting of the radar imaging data[4]. References [1]F. Serafino, C. Lugni, and F. Soldovieri, "A novel strategy for the surface current determination from marine X-band radar data," IEEE Geosci.Remote Sens. Lett., vol. 7, no. 2, pp. 231-235, Apr. 2010. [2]Ludeno, G., Brandini, C., Lugni, C., Arturi, D., Natale, A., Soldovieri, F., Serafino, F. (2014). Remocean System for the Detection of the Reflected Waves from the Costa Concordia Ship Wreck. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(7). [3]Nieto Borge, J., Rodriguez, G.R., Hessner, K., González, P.I., (2004). Inversion of Marine Radar Images for Surface Wave Analysis. J. Atmos. Oceanic Technol. 21, 1291-1300. [4] Fucile, F., Ludeno, G., Serafino, F.,Bulian, G., Soldovieri, F., Lugni, C. "Some challenges in recovering wave features from a wave radar system". Paper submitted to the International Ocean and Polar Engineering Conference, ISOPE, Rhodes 2016

Assessing species habitat using Google Street View: a case study of cliff-nesting vultures.

PubMed

Olea, Pedro P; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species' habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species' potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km²). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture's habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62-95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures' nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs.

Assessing Species Habitat Using Google Street View: A Case Study of Cliff-Nesting Vultures

PubMed Central

Olea, Pedro P.; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species’ habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species’ potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km2). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture’s habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62–95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures’ nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs. PMID:23355880

Real time forest fire warning and forest fire risk zoning: a Vietnamese case study

NASA Astrophysics Data System (ADS)

Chu, T.; Pham, D.; Phung, T.; Ha, A.; Paschke, M.

2016-12-01

Forest fire occurs seriously in Vietnam and has been considered as one of the major causes of forest lost and degradation. Several studies of forest fire risk warning were conducted using Modified Nesterov Index (MNI) but remaining shortcomings and inaccurate predictions that needs to be urgently improved. In our study, several important topographic and social factors such as aspect, slope, elevation, distance to residential areas and road system were considered as "permanent" factors while meteorological data were updated hourly using near-real-time (NRT) remotely sensed data (i.e. MODIS Terra/Aqua and TRMM) for the prediction and warning of fire. Due to the limited number of weather stations in Vietnam, data from all active stations (i.e. 178) were used with the satellite data to calibrate and upscale meteorological variables. These data with finer resolution were then used to generate MNI. The only significant "permanent" factors were selected as input variables based on the correlation coefficients that computed from multi-variable regression among true fire-burning (collected from 1/2007) and its spatial characteristics. These coefficients also used to suggest appropriate weight for computing forest fire risk (FR) model. Forest fire risk model was calculated from the MNI and the selected factors using fuzzy regression models (FRMs) and GIS based multi-criteria analysis. By this approach, the FR was slightly modified from MNI by the integrated use of various factors in our fire warning and prediction model. Multifactor-based maps of forest fire risk zone were generated from classifying FR into three potential danger levels. Fire risk maps were displayed using webgis technology that is easy for managing data and extracting reports. Reported fire-burnings thereafter have been used as true values for validating the forest fire risk. Fire probability has strong relationship with potential danger levels (varied from 5.3% to 53.8%) indicating that the higher potential risk, the more chance of fire happen. By adding spatial factors to continuous daily updated remote sensing based meteo-data, results are valuable for both mapping forest fire risk zones in short and long-term and real time fire warning in Vietnam. Key words: Near-real-time, forest fire warning, fuzzy regression model, remote sensing.

Remote sensing applications to hydrologic modeling

NASA Technical Reports Server (NTRS)

Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

1977-01-01

An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

Leveraging field and remotely sensed data to reduce uncertainty in national inventories of coastal wetland carbon fluxes: Year 2 findings from the NASA "Blue" Carbon Monitoring System

NASA Astrophysics Data System (ADS)

Windham-Myers, L.; Holmquist, J. R.; Woo, I.; Bergamaschi, B. A.; Byrd, K. B.; Crooks, S.; Drexler, J. Z.; Feagin, R. A.; Ferner, M. C.; Gonneea, M. E.; Kroeger, K. D.; Megonigal, P.; Morris, J. T.; Schile, L. M.; Simard, M.; Sutton-Grier, A.; Takekawa, J.; Troxler, T.; Weller, D.; Callaway, J.; Herold, N.

2016-12-01

In Year 2, the NASA Blue Carbon Monitoring Systems group leveraged USDA, USFWS and NOAA datasets, extensive field datasets, and targeted remote-sensing products to address basic questions regarding the size of carbon (C) stocks, and the directions and magnitudes of C fluxes in the US coastal zone since 1996. We review the uncertainty associated with 5 major terms in our Land Use-Land Cover Change (LULCC)-based accounting, both nationally and within sentinel sites (Cape Cod, Chesapeake Bay, Everglades, Louisiana, San Francisco Bay, Puget Sound). 1) To make distinctions between tidal and non-tidal wetlands we have relied on a combination of wetland and LiDAR-derived elevation maps. Existing products appear sufficient for saline wetlands, however many freshwater wetlands (1M ha) may be tidal despite current hydrologic mapcodes. 2) We are currently estimating methane emissions using salinity regime as a proxy. Methane emissions are variable across intermediate salinities, though not captured by the current binary classification of wetlands as either fresh or saline. 3) We are currently using a combination of USDA's SSURGO and independent core data to map soil C stocks. Soil C density varies little and is consistent across depth, salinity regime, and dominant plant cover type. 4) To model soil C fluxes, with C accumulating as sea level rises and C released with erosion or oxidation, we have applied IPCC default emission factors for the 2% of tidal wetland acreage lost to water (the dominant conversion), but have modeled C gain in wetlands-remaining-wetlands (98% of CONUS tidal wetlands) based on correlations between sea-level rise and sediment accretion, with the equation - Δ soil organic C stock = Δ elevation x soil C density. 5) To quantify biomass change through time, we developed a robust (R2 > 0.6) hybrid mapping approach including object-based image analysis, multispectral data, and RADAR. Overall, soil and biomass C stocks appear readily estimated and improved from Tier 1 default values. To further reduce uncertainty in the US GHG inventory for coastal wetlands, we propose efforts to confirm the extent of tidal inundation, develop default values for methane emissions associated with intermediate salinities, and model soil C accretion, the dominant "blue carbon" sink, across continental and local gradients.

Threats, status & management options for bristlecone pines and limber pines in Southern Rockies

Treesearch

A. W. Schoettle; K. S. Burns; F. Freeman; R. A. Sniezko

2006-01-01

High-elevation white pines define the most remote alpine-forest ecotones in western North America yet they are not beyond the reach of a lethal non-native pathogen. The pathogen (Cronartium ribicola), a native to Asia, causes the disease white pine blister rust (WPBR) and was introduced into western Canada in 1910. Whitebark (Pinus albicaulis) and...

Occurrence of an exotic earthworm (Amynthas agrestis) in undisturbed soils of the southern Appalachian Mountains, USA

Treesearch

Mac. A. Callaham; Paul F. Hendrix; Ross J. Phillips

2003-01-01

This study documents the occurrence of an aggressive invasive earthworm species in undisturbed forest soils of the southern Appalachian Mountains of northern Georgia, USA. Earthworms were sorted from samples collected in pitfall traps that had been set in mature, mesic oak-hickory forests in remote, high elevation, locations across northern Georgia. Specimens were...

Improving Understanding of Glacier Melt Contribution to High Asian River Discharge through Collaboration and Capacity Building with High Asian CHARIS Partner Institutions

NASA Astrophysics Data System (ADS)

Armstrong, Richard; Brodzik, Mary Jo; Armstrong, Betsy; Barrett, Andrew; Fetterer, Florence; Hill, Alice; Jodha Khalsa, Siri; Racoviteanu, Adina; Raup, Bruce; Rittger, Karl; Williams, Mark; Wilson, Alana; Ye, Qinghua

2017-04-01

The Contribution to High Asia Runoff from Ice & Snow (CHARIS) project uses remote sensing data combined with modeling from 2000 to the present to improve proportional estimates of melt from glaciers and seasonal snow surfaces. Based at the National Snow and Ice Data Center (NSIDC), University of Colorado, Boulder, USA, the CHARIS project objectives are twofold: 1) capacity-building efforts with CHARIS partners from eight High Asian countries to better forecast future availability and vulnerability of water resources in the region, and 2) improving our ability to systematically assess the role of glaciers and seasonal snow in the freshwater resources of High Asia. Capacity-building efforts include working with CHARIS partners from Bhutan, Nepal, India, Pakistan, Afghanistan, Kazakhstan, Kyrgyzstan and Tajikistan. Our capacity-building activities include training, data sharing, supporting fieldwork, graduate student education and infrastructure development. Because of the scarcity of in situ data in this High Asian region, we are using the wealth of available remote sensing data to characterize digital elevation, daily maps of fractional snow-cover, annual maps of glacier and permanent snow cover area and downscaled reanalysis temperature data in snow melt models to estimate the relative proportions of river runoff from glacierized and seasonally snow-covered surfaces. Current collaboration with Qinghua Ye, visiting scientist at NSIDC from the Institute of Tibetan Plateau Research, CAS, focuses on remote sensing methods to detect changes in the mountain cryosphere. Collaboration with our Asian partners supports the systematic analysis of the annual cycle of seasonal snow and glacier ice melt across the High Mountain Asia region. With our Asian partners, we have derived reciprocal benefits, learning from their specialized local knowledge and obtaining access to their in situ data. We expect that the improved understanding of runoff from snow and glacier surfaces will inform the development of adaptation and mitigation measures. The CHARIS Project is funded by USAID.

Using Remotely Piloted Aircraft System to Study the Evolution of the Boundary Layer Related to Fog Events

NASA Astrophysics Data System (ADS)

Roberts, G. C.; Cayez, G.; Ronflé-Nadaud, C.; Albrand, M.; Dralet, J. P.; Momboisse, G.; Nicoll, K.; Seity, Y.; Bronz, M.; Hattenberger, G.; Gorraz, M.; Bustico, A.

2014-12-01

Over the past decade, the scientific community has embraced the use of RPAS (remotely piloted aircraft system) as a tool to improve observations of the Earth's surface and atmospheric phenomena. The use of small RPAS (Remotely Piloted Aircraft System) in atmospheric research has increased because of their relative low-cost, compact size and ease of operation. Small RPAS are especially adapted for observing the atmospheric boundary layer processes at high vertical and temporal resolution. To this end, CNRM, ENAC, and ENM have developed the VOLTIGE (Vecteurs d'Observation de La Troposphere pour l'Investigation et la Gestion de l'Environnement) program to study the life cycle of fog with multiple, small RPAS. The instrumented RPAS flights have successfully observed the evolution of the boundary layer and dissipation of fog events. In addition, vertical profiles from the RPAS have been compared with Météo France forecast models, and the results suggest that forecast models may be improved using high resolution and frequent in-situ measurements. Within the VOLTIGE project, a flying-wing RPAS with four control surfaces was developed to separate elevator and aileron controls in order to reduce the pitch angle envelope and improve turbulence and albedo measurements. The result leads to a small RPAS with the capability of flying up to two hours with 150 grams of payload, while keeping the hand-launch capability as a constraint for regular atmospheric research missions. High frequency data logging has been integrated into the main autopilot in order to synchronize navigation and payload measurements, as well as allowing an efficient sensor-based navigation. The VOLTIGE program also encourages direct participation of students on the advancement of novel observing systems for atmospheric sciences, and provides a step towards deploying small RPAS in an operational network. VOLTIGE is funded by the Agence Nationale de Recherche (ANR-Blanc 2012) and supported by Aerospace Valley.

Improved image classification with neural networks by fusing multispectral signatures with topological data

NASA Technical Reports Server (NTRS)

Harston, Craig; Schumacher, Chris

1992-01-01

Automated schemes are needed to classify multispectral remotely sensed data. Human intelligence is often required to correctly interpret images from satellites and aircraft. Humans suceed because they use various types of cues about a scene to accurately define the contents of the image. Consequently, it follows that computer techniques that integrate and use different types of information would perform better than single source approaches. This research illustrated that multispectral signatures and topographical information could be used in concert. Significantly, this dual source tactic classified a remotely sensed image better than the multispectral classification alone. These classifications were accomplished by fusing spectral signatures with topographical information using neural network technology. A neural network was trained to classify Landsat mulitspectral signatures. A file of georeferenced ground truth classifications were used as the training criterion. The network was trained to classify urban, agriculture, range, and forest with an accuracy of 65.7 percent. Another neural network was programmed and trained to fuse these multispectral signature results with a file of georeferenced altitude data. This topological file contained 10 levels of elevations. When this nonspectral elevation information was fused with the spectral signatures, the classifications were improved to 73.7 and 75.7 percent.

Evaluation of a scale-model experiment to investigate long-range acoustic propagation

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Mcaninch, Gerry L.; Carlberg, Ingrid A.

1987-01-01

Tests were conducted to evaluate the feasibility of using a scale-model experiment situated in an anechoic facility to investigate long-range sound propagation over ground terrain. For a nominal scale factor of 100:1, attenuations along a linear array of six microphones colinear with a continuous-wave type of sound source were measured over a wavelength range from 10 to 160 for a nominal test frequency of 10 kHz. Most tests were made for a hard model surface (plywood), but limited tests were also made for a soft model surface (plywood with felt). For grazing-incidence propagation over the hard surface, measured and predicted attenuation trends were consistent for microphone locations out to between 40 and 80 wavelengths. Beyond 80 wavelengths, significant variability was observed that was caused by disturbances in the propagation medium. Also, there was evidence of extraneous propagation-path contributions to data irregularities at more remote microphones. Sensitivity studies for the hard-surface and microphone indicated a 2.5 dB change in the relative excess attenuation for a systematic error in source and microphone elevations on the order of 1 mm. For the soft-surface model, no comparable sensitivity was found.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding

NASA Astrophysics Data System (ADS)

Rizki, Permata Nur Miftahur; Lee, Heezin; Lee, Minsu; Oh, Sangyoon

2017-01-01

With the rapid advance of remote sensing technology, the amount of three-dimensional point-cloud data has increased extraordinarily, requiring faster processing in the construction of digital elevation models. There have been several attempts to accelerate the computation using parallel methods; however, little attention has been given to investigating different approaches for selecting the most suited parallel programming model for a given computing environment. We present our findings and insights identified by implementing three popular high-performance parallel approaches (message passing interface, MapReduce, and GPGPU) on time demanding but accurate kriging interpolation. The performances of the approaches are compared by varying the size of the grid and input data. In our empirical experiment, we demonstrate the significant acceleration by all three approaches compared to a C-implemented sequential-processing method. In addition, we also discuss the pros and cons of each method in terms of usability, complexity infrastructure, and platform limitation to give readers a better understanding of utilizing those parallel approaches for gridding purposes.

Massive collapse of volcano edifices triggered by hydrothermal pressurization

USGS Publications Warehouse

Reid, M.E.

2004-01-01

Catastrophic collapse of steep volcano flanks threatens lives at stratovolcanoes around the world. Although destabilizing shallow intrusion of magma into the edifice accompanies some collapses (e.g., Mount St. Helens), others have occurred without eruption of juvenile magmatic materials (e.g., Bandai). These latter collapses can be difficult to anticipate. Historic collapses without magmatic eruption are associated with shallow hydrothermal groundwater systems at the time of collapse. Through the use of numerical models of heat and groundwater flow, I evaluate the efficacy of hydrothermally driven collapse. Heating from remote magma intrusion at depth can generate temporarily elevated pore-fluid pressures that propagate upward into an edifice. Effective-stress deformation modeling shows that these pressures are capable of destabilizing the core of an edifice, resulting in massive, deep-seated collapse. Far-field pressurization only occurs with specific rock hydraulic properties; however, data from numerous hydrothermal systems illustrate that this process can transpire in realistic settings. ?? 2004 Geological Society of America.

Balance Mass Flux and Velocity Across the Equilibrium Line in Ice Drainage Systems of Greenland

NASA Technical Reports Server (NTRS)

Zwally, H. Jay; Giovinetto, Mario B.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Estimates of balance mass flux and the depth-averaged ice velocity through the cross-section aligned with the equilibrium line are produced for each of six drainage systems in Greenland. (The equilibrium line, which lies at approximately 1200 m elevation on the ice sheet, is the boundary between the area of net snow accumulation at higher elevations and the areas of net melting at lower elevations around the ice sheet.) Ice drainage divides and six major drainage systems are delineated using surface topography from ERS (European Remote Sensing) radar altimeter data. The net accumulation rate in the accumulation zone bounded by the equilibrium line is 399 Gt/yr and net ablation rate in the remaining area is 231 Gt/yr. (1 GigaTon of ice is 1090 kM(exp 3). The mean balance mass flux and depth-averaged ice velocity at the cross-section aligned with the modeled equilibrium line are 0.1011 Gt kM(exp -2)/yr and 0.111 km/yr, respectively, with little variation in these values from system to system. The ratio of the ice mass above the equilibrium line to the rate of mass output implies an effective exchange time of approximately 6000 years for total mass exchange. The range of exchange times, from a low of 3 ka in the SE drainage system to 14 ka in the NE, suggests a rank as to which regions of the ice sheet may respond more rapidly to climate fluctuations.

Using Remote Sensing Technology, Web Casts, and Participation in a Valuable Research Project to Jazz Teachers and Excite Students About Science

NASA Astrophysics Data System (ADS)

Benko, T. M.; Czajkowski, K. P.; Struble, J.; Zhao, L.

2002-12-01

Scientific education of primary and secondary school children has become a topic of concern in Ohio and throughout the United States. So with that in mind, how do you get students excited about learning science? One route is to inform and jazz teachers about current technology! The University of Toledo has hosted three one-week, NASA and OhioView sponsored professional development institutes entitled, Observing Earth from Space, for teachers from grades K-12 during July 2000, 2001, and 2002. Sixty-seven teachers from the Upper Midwest and Kansas with Earth Science, Social Studies, and Physics backgrounds attended. Each participant acquired new ideas, plenty of educational materials, and posters of satellite imagery. The teachers received basic training in remote sensing, global positioning systems, digital elevation models, and weather observing techniques and learned about useful remote sensing applications. This instruction was conducted through: 1) presentations given by research scientists, 2) integration of the learned content into authentic, hands-on lesson plans, and 3) participation in a learning adventure, where their students collected real-time earth science data at their respective schools while university research scientists gathered corresponding satellite imagery. The students observations were submitted via a simple Web interface: www.remotesensing.utoledo.edu. One of the very exciting platforms used to communicate with the teachers and students throughout the school year were live Web Casts sponsored by NASA Glenn Research Center. The students data have successfully assisted in the validation of cloud/snow remote sensing algorithms, and next year the students observations will include various surface temperature readings. The participation in a cutting-edge technology workshop and in an important global climate change research project, applicable in the classroom, has added another worthwhile dimension to the learning process and career awareness for both the teachers and their students.

Clinical significance of automatic warning function of cardiac remote monitoring systems in preventing acute cardiac episodes

PubMed Central

Chen, Shou-Qiang; Xing, Shan-Shan; Gao, Hai-Qing

2014-01-01

Objective: In addition to ambulatory Holter electrocardiographic recording and transtelephonic electrocardiographic monitoring (TTM), a cardiac remote monitoring system can provide an automatic warning function through the general packet radio service (GPRS) network, enabling earlier diagnosis, treatment and improved outcome of cardiac diseases. The purpose of this study was to estimate its clinical significance in preventing acute cardiac episodes. Methods: Using 2 leads (V1 and V5 leads) and the automatic warning mode, 7160 patients were tested with a cardiac remote monitoring system from October 2004 to September 2007. If malignant arrhythmias or obvious ST-T changes appeared in the electrocardiogram records was automatically transferred to the monitoring center, the patient and his family members were informed, and the corresponding precautionary or therapeutic measures were implemented immediately. Results: In our study, 274 cases of malignant arrhythmia, including sinus standstill and ventricular tachycardia, and 43 cases of obvious ST-segment elevation were detected and treated. Because of early detection, there was no death or deformity. Conclusions: A cardiac remote monitoring system providing an automatic warning function can play an important role in preventing acute cardiac episodes. PMID:25674124

Estimating lava volume by precision combination of multiple baseline spaceborne and airborne interferometric synthetic aperture radar: The 1997 eruption of Okmok Volcano, Alaska

USGS Publications Warehouse

Lu, Z.; Fielding, E.; Patrick, M.R.; Trautwein, C.M.

2003-01-01

Interferometric synthetic aperture radar (InSAR) techniques are used to calculate the volume of extrusion at Okmok volcano, Alaska by constructing precise digital elevation models (DEMs) that represent volcano topography before and after the 1997 eruption. The posteruption DEM is generated using airborne topographic synthetic aperture radar (TOPSAR) data where a three-dimensional affine transformation is used to account for the misalignments between different DEM patches. The preeruption DEM is produced using repeat-pass European Remote Sensing satellite data; multiple interferograms are combined to reduce errors due to atmospheric variations, and deformation rates are estimated independently and removed from the interferograms used for DEM generation. The extrusive flow volume associated with the 1997 eruption of Okmok volcano is 0.154 ?? 0.025 km3. The thickest portion is approximately 50 m, although field measurements of the flow margin's height do not exceed 20 m. The in situ measurements at lava edges are not representative of the total thickness, and precise DEM data are absolutely essential to calculate eruption volume based on lava thickness estimations. This study is an example that demonstrates how InSAR will play a significant role in studying volcanoes in remote areas.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

Development of new mapping standards for geological surveys in Greenland

NASA Astrophysics Data System (ADS)

Mätzler, Eva; langley, Kirsty; Hollis, Julie; Heide-Jørgensen, Helene

2017-04-01

The current official topographic and geological maps of Greenland are in scale of 1:250:000 and 1:500.000 respectively, allowing only very limited amount of detail. The maps are outdated, and periglacial landscapes have changed significantly since the acquisition date. Hence, new affordable mapping products of high quality are in demand that can be available within a restricted time frame. In order to fulfill those demands a new mapping standard based on satellite imagery was developed, where classifications are mainly carried out with algorithms suitable for automatization. A Digital Elevation Model (ArcticDEM) was applied allowing examination of topographic and geological structures and 3D visualizing. Information on topographic features and lithology was extracted based on analysis of spectral characteristics from different multispectral data sources (Landsat 8, ASTER, WorldView-3) partly combined with the DEM. A first product is completed, and validation was carried out by field surveys. Field and remotely sensed data were integrated into a GIS database, and derived data will be freely available providing a valuable tool for planning and carrying out mineral exploration and other field activities. This study offers a method for generating up-to-date, low-cost and high quality mapping products suitable for Arctic regions, where accessibility is restricted due to remoteness and lack of infrastructure.

The effect of flight altitude to data quality of fixed-wing UAV imagery: case study in Murcia, Spain

NASA Astrophysics Data System (ADS)

Anders, Niels; Keesstra, Saskia; Cammeraat, Erik

2014-05-01

Unmanned Aerial System (UAS) are becoming popular tools in the geosciences due to improving technology and processing techniques. They can potentially fill the gap between spaceborne or manned aircraft remote sensing and terrestrial remote sensing, both in terms of spatial and temporal resolution. In this study we tested a fixed-wing Unmanned Aerial System (UAS) for the application of digital landscape analysis. The focus was to analyze the effect of flight altitude and the effect to accuracy and detail of the produced digital elevation models, derived terrain properties and orthophotos. The aircraft was equipped with a Panasonic GX1 16MP pocket camera with 20 mm lens to capture normal JPEG RGB images. Images were processed using Agisoft Photoscan Pro which includes the structure-from-motion and multiview stereopsis algorithms. The test area consisted of small abandoned agricultural fields in semi-arid Murcia in southeastern Spain. The area was severely damaged after a destructive rainfall event, including damaged check dams, rills, deep gully incisions and piping. Results suggest that careful decisions on flight altitude are essential to find a balance between the area coverage, ground sampling distance, UAS ground speed, camera processing speed and the accurate registration of specific soil erosion features of interest.

A Warning System for Rainfall-Induced Debris Flows: A Integrated Remote Sensing and Data Mining Approach

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Sultan, M.; Nurmemet, I.; Al Harbi, H.; Youssef, A.; Elbayoumi, T.; Zabramwi, Y.; Alzahrani, S.; Bahamil, A.

2014-12-01

We developed methodologies that heavily rely on observations extracted from a wide-range of remote sensing data sets (TRMM, Landsat ETM, ENVISAT, ERS, SPOT, Orbview, GeoEye) to develop a warning system for rainfall-induced debris flows in the Jazan province in the Red Sea Hills. The developed warning system integrates static controlling factors and dynamic triggering factors. The algorithm couples a susceptibility map with a rainfall I-D curve, both are developed using readily available remote sensing datasets. The static susceptibility map was constructed as follows: (1) an inventory was compiled for debris flows identified from high spatial resolution datasets and field verified; (2) 10 topographical and land cover predisposing factors (i.e. slope angle, slope aspect, normalized difference vegetation index, topographical position index, stream power index, flow accumulation, distance to drainage line, soil weathering index, elevation and topographic wetness index) were generated; (3) an artificial neural network model (ANN) was constructed, optimized and validated; (4) a debris-flow susceptibility map was generated using the ANN model and refined (using differential backscatter coefficient radar images). The rainfall threshold curve was derived as follows: (1) a spatial database was generated to host temporal co-registered and radiometrically and atmospherically corrected Landsat images; (2) temporal change detection images were generated for pairs of successively acquired Landsat images and criteria were established to identify "the change" related to debris flows, (3) the duration and intensity of the precipitation event that caused each of the identified debris flow events was assumed to be that of the most intense event within the investigated period; and (4) the I-D curve was extracted using data (intensity and duration of precipitation) for the inventoried events. Our findings include: (1) the spatial controlling factors with the highest predictive power of debris-flow locations are: topographic position index, slope, NDVI and distance to drainage line; (2) the ANN model showed an excellent prediction performance (area under receiver operating characteristic [ROC] curve: 0.961); 3) the preliminary I-D curve is I=39.797×D-0.7355 (I: Intensity and D: duration).

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Concurrent remote sensing of Arctic sea ice from submarine and aircraft

NASA Technical Reports Server (NTRS)

Wadhams, P.; Davis, N. R.; Comiso, J. C.; Kutz, R.; Crawford, J.; Jackson, G.; Krabill, W.; Sear, C. B.; Swift, R.; Tucker, W. B., III

1991-01-01

In May 1987 a concurrent remote sensing study of Arctic sea ice from above and below was carried out. A submarine equipped with sidescan and upward looking sonar collaborated with two remote sensing aircraft equipped with passive microwave, synthetic aperture radar (SAR), a laser profilometer and an infrared radiometer. By careful registration of the three tracks it has been possible to find relationships between ice type, ice morphology and thickness, SAR backscatter and microwave brightness temperatures. The key to the process has been the sidescan sonar's ability to identify ice type through differences in characteristic topography. Over a heavily ridged area of mainly multiyear ice there is a strong positive correlation between SAR backscatter and ice draft or elevation. It was also found that passive and active microwave complement each other in that SAR has a high contrast between open water and multiyear ice, while passive microwave has a high contrast between open water and first-year ice.