Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

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

Hamada, Yuki; Gilbert, Jack A.; Larsen, Peter E.

2014-04-01

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and belowground ecosystems. However, the integration of biophysical and soil remote sensing withmore » geospatial information about the e nvironment holds great promise for mapping SMC biogeography. Additional research needs invol ve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.« less

Toward Linking Aboveground Vegetation Properties and Soil Microbial Communities Using Remote Sensing

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

Hamada, Yuki; Gilbert, Jack A.; Larsen, Peter E.

2014-04-01

Despite their vital role in terrestrial ecosystem function, the distributions and dynamics of soil microbial communities (SMCs) are poorly understood. Vegetation and soil properties are the primary factors that influence SMCs. This paper discusses the potential effectiveness of remote sensing science and technologies for mapping SMC biogeography by characterizing surface biophysical properties (e.g., plant traits and community composition) strongly correlated with SMCs. Using remotely sensed biophysical properties to predict SMC distributions is extremely challenging because of the intricate interactions between biotic and abiotic factors and between above- and below-ground ecosystems. However, the integration of biophysical and soil remote sensing withmore » geospatial information about the environment holds great promise for mapping SMC biogeography. Additional research needs involve microbial taxonomic definition, soil environmental complexity, and scaling strategies. The collaborative effort of experts from diverse disciplines is essential to linking terrestrial surface biosphere observations with subsurface microbial community distributions using remote sensing.« less

Earth Survey Applications Division. [a bibliography

NASA Technical Reports Server (NTRS)

Carpenter, L. (Editor)

1981-01-01

Accomplishments of research and data analysis conducted to study physical parameters and processes inside the Earth and on the Earth's surface, to define techniques and systems for remotely sensing the processes and measuring the parameters of scientific and applications interest, and the transfer of promising operational applications techniques to the user community of Earth resources monitors, managers, and decision makers are described. Research areas covered include: geobotany, magnetic field modeling, crustal studies, crustal dynamics, sea surface topography, land resources, remote sensing of vegetation and soils, and hydrological sciences. Major accomplishments include: production of global maps of magnetic anomalies using Magsat data; computation of the global mean sea surface using GEOS-3 and Seasat altimetry data; delineation of the effects of topography on the interpretation of remotely-sensed data; application of snowmelt runoff models to water resources management; and mapping of snow depth over wheat growing areas using Nimbus microwave data.

Criteria for the optimal selection of remote sensing optical images to map event landslides

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Giordan, Daniele; Santangelo, Michele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

2018-01-01

Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.

Optical remote sensing of asteroid surfaces from spacecraft

NASA Technical Reports Server (NTRS)

Mccord, T. B.

1978-01-01

Reflectance spectroscopy and multispectral mapping are the techniques likely to be most useful for determining asteroid surfaces. Several other techniques should be considered for providing complementary information.

City of Flagstaff Project: Ground Water Resource Evaluation, Remote Sensing Component

USGS Publications Warehouse

Chavez, Pat S.; Velasco, Miguel G.; Bowell, Jo-Ann; Sides, Stuart C.; Gonzalez, Rosendo R.; Soltesz, Deborah L.

1996-01-01

Many regions, cities, and towns in the Western United States need new or expanded water resources because of both population growth and increased development. Any tools or data that can help in the evaluation of an area's potential water resources must be considered for this increasingly critical need. Remotely sensed satellite images and subsequent digital image processing have been under-utilized in ground water resource evaluation and exploration. Satellite images can be helpful in detecting and mapping an area's regional structural patterns, including major fracture and fault systems, two important geologic settings for an area's surface to ground water relations. Within the United States Geological Survey's (USGS) Flagstaff Field Center, expertise and capabilities in remote sensing and digital image processing have been developed over the past 25 years through various programs. For the City of Flagstaff project, this expertise and these capabilities were combined with traditional geologic field mapping to help evaluate ground water resources in the Flagstaff area. Various enhancement and manipulation procedures were applied to the digital satellite images; the results, in both digital and hardcopy format, were used for field mapping and analyzing the regional structure. Relative to surface sampling, remotely sensed satellite and airborne images have improved spatial coverage that can help study, map, and monitor the earth surface at local and/or regional scales. Advantages offered by remotely sensed satellite image data include: 1. a synoptic/regional view compared to both aerial photographs and ground sampling, 2. cost effectiveness, 3. high spatial resolution and coverage compared to ground sampling, and 4. relatively high temporal coverage on a long term basis. Remotely sensed images contain both spectral and spatial information. The spectral information provides various properties and characteristics about the surface cover at a given location or pixel (that is, vegetation and/or soil type). The spatial information gives the distribution, variation, and topographic relief of the cover types from pixel to pixel. Therefore, the main characteristics that determine a pixel's brightness/reflectance and, consequently, the digital number (DN) assigned to the pixel, are the physical properties of the surface and near surface, the cover type, and the topographic slope. In this application, the ability to detect and map lineaments, especially those related to fractures and faults, is critical. Therefore, the extraction of spatial information from the digital images was of prime interest in this project. The spatial information varies among the different spectral bands available; in particular, a near infrared spectral band is better than a visible band when extracting spatial information in highly vegetated areas. In this study, both visible and near infrared bands were analyzed and used to extract the desired spatial information from the images. The wide swath coverage of remotely sensed satellite digital images makes them ideal for regional analysis and mapping. Since locating and mapping highly fractured and faulted areas is a major requirement for ground water resource evaluation and exploration this aspect of satellite images was considered critical; it allowed us to stand back (actually up about 440 miles), look at, and map the regional structural setting of the area. The main focus of the remote sensing and digital image processing component of this project was to use both remotely sensed digital satellite images and a Digital Elevation Model (DEM) to extract spatial information related to the structural and topographic patterns in the area. The data types used were digital satellite images collected by the United States' Landsat Thematic Mapper (TM) and French Systeme Probatoire d'Observation de laTerre (SPOT) imaging systems, along with a DEM of the Flagstaff region. The USGS Mini Image Processing Sy

Crosscutting Airborne Remote Sensing Technologies for Oil and Gas and Earth Science Applications

NASA Technical Reports Server (NTRS)

Aubrey, A. D.; Frankenberg, C.; Green, R. O.; Eastwood, M. L.; Thompson, D. R.; Thorpe, A. K.

2015-01-01

Airborne imaging spectroscopy has evolved dramatically since the 1980s as a robust remote sensing technique used to generate 2-dimensional maps of surface properties over large spatial areas. Traditional applications for passive airborne imaging spectroscopy include interrogation of surface composition, such as mapping of vegetation diversity and surface geological composition. Two recent applications are particularly relevant to the needs of both the oil and gas as well as government sectors: quantification of surficial hydrocarbon thickness in aquatic environments and mapping atmospheric greenhouse gas components. These techniques provide valuable capabilities for petroleum seepage in addition to detection and quantification of fugitive emissions. New empirical data that provides insight into the source strength of anthropogenic methane will be reviewed, with particular emphasis on the evolving constraints enabled by new methane remote sensing techniques. Contemporary studies attribute high-strength point sources as significantly contributing to the national methane inventory and underscore the need for high performance remote sensing technologies that provide quantitative leak detection. Imaging sensors that map spatial distributions of methane anomalies provide effective techniques to detect, localize, and quantify fugitive leaks. Airborne remote sensing instruments provide the unique combination of high spatial resolution (<1 m) and large coverage required to directly attribute methane emissions to individual emission sources. This capability cannot currently be achieved using spaceborne sensors. In this study, results from recent NASA remote sensing field experiments focused on point-source leak detection, will be highlighted. This includes existing quantitative capabilities for oil and methane using state-of-the-art airborne remote sensing instruments. While these capabilities are of interest to NASA for assessment of environmental impact and global climate change, industry similarly seeks to detect and localize leaks of both oil and methane across operating fields. In some cases, higher sensitivities desired for upstream and downstream applications can only be provided by new airborne remote sensing instruments tailored specifically for a given application. There exists a unique opportunity for alignment of efforts between commercial and government sectors to advance the next generation of instruments to provide more sensitive leak detection capabilities, including those for quantitative source strength determination.

Sea-surface temperature and salinity mapping from remote microwave radiometric measurements of brightness temperature

NASA Technical Reports Server (NTRS)

Hans-Juergen, C. B.; Kendall, B. M.; Fedors, J. C.

1977-01-01

A technique to measure remotely sea surface temperature and salinity was demonstrated with a dual frequency microwave radiometer system. Accuracies in temperature of 1 C and in salinity of part thousand for salinity greater than 5 parts per thousand were attained after correcting for the influence of extraterrestrial background radiation, atmospheric radiation and attenuation, sea-surface roughness, and antenna beamwidth. The radiometers, operating at 1.43 and 2.65 GHz, comprise a third-generation system using null balancing and feedback noise injection. Flight measurements from an aircraft at an altitude of 1.4 km over the lower Chesapeake Bay and coastal areas of the Atlantic Ocean resulted in contour maps of sea-surface temperature and salinity with a spatial resolution of 0.5 km.

Comparing Geologic Data Sets Collected by Planetary Analog Traverses and by Standard Geologic Field Mapping: Desert Rats Data Analysis

NASA Technical Reports Server (NTRS)

Feng, Wanda; Evans, Cynthia; Gruener, John; Eppler, Dean

2014-01-01

Geologic mapping involves interpreting relationships between identifiable units and landforms to understand the formative history of a region. Traditional field techniques are used to accomplish this on Earth. Mapping proves more challenging for other planets, which are studied primarily by orbital remote sensing and, less frequently, by robotic and human surface exploration. Systematic comparative assessments of geologic maps created by traditional mapping versus photogeology together with data from planned traverses are limited. The objective of this project is to produce a geologic map from data collected on the Desert Research and Technology Studies (RATS) 2010 analog mission using Apollo-style traverses in conjunction with remote sensing data. This map is compared with a geologic map produced using standard field techniques.

To the National Map and beyond

USGS Publications Warehouse

Kelmelis, J.

2003-01-01

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

Mississippi Sound remote sensing study. [NASA Earth Resources Laboratory seasonal experiments

NASA Technical Reports Server (NTRS)

Atwell, B. H.; Thomann, G. C.

1973-01-01

A study of the Mississippi Sound was initiated in early 1971 by personnel of NASA Earth Resources Laboratory. Four separate seasonal experiments consisting of quasi-synoptic remote and surface measurements over the entire area were planned. Approximately 80 stations distributed throughout Mississippi Sound were occupied. Surface water temperature and secchi extinction depth were measured at each station and water samples were collected for water quality analyses. The surface distribution of three water parameters of interest from a remote sensing standpoint - temperature, salinity and chlorophyll content - are displayed in map form. Areal variations in these parameters are related to tides and winds. A brief discussion of the general problem of radiative measurements of water temperature is followed by a comparison of remotely measured temperatures (PRT-5) to surface vessel measurements.

Smart Cameras for Remote Science Survey

NASA Technical Reports Server (NTRS)

Thompson, David R.; Abbey, William; Allwood, Abigail; Bekker, Dmitriy; Bornstein, Benjamin; Cabrol, Nathalie A.; Castano, Rebecca; Estlin, Tara; Fuchs, Thomas; Wagstaff, Kiri L.

2012-01-01

Communication with remote exploration spacecraft is often intermittent and bandwidth is highly constrained. Future missions could use onboard science data understanding to prioritize downlink of critical features [1], draft summary maps of visited terrain [2], or identify targets of opportunity for followup measurements [3]. We describe a generic approach to classify geologic surfaces for autonomous science operations, suitable for parallelized implementations in FPGA hardware. We map these surfaces with texture channels - distinctive numerical signatures that differentiate properties such as roughness, pavement coatings, regolith characteristics, sedimentary fabrics and differential outcrop weathering. This work describes our basic image analysis approach and reports an initial performance evaluation using surface images from the Mars Exploration Rovers. Future work will incorporate these methods into camera hardware for real-time processing.

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

NASA Technical Reports Server (NTRS)

Fayne, Jessica Fayne; Bolten, John; Lakshmi, Venkat; Ahamed, Aakash

2016-01-01

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

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.

Remote sensing and human health: new sensors and new opportunities.

PubMed

Beck, L R; Lobitz, B M; Wood, B L

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Système Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Remote sensing and human health: new sensors and new opportunities

NASA Technical Reports Server (NTRS)

Beck, L. R.; Lobitz, B. M.; Wood, B. L.

2000-01-01

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

[The design and implementation of the web typical surface object spectral information system in arid areas based on .NET and SuperMap].

PubMed

Xia, Jun; Tashpolat, Tiyip; Zhang, Fei; Ji, Hong-jiang

2011-07-01

The characteristic of object spectrum is not only the base of the quantification analysis of remote sensing, but also the main content of the basic research of remote sensing. The typical surface object spectral database in arid areas oasis is of great significance for applied research on remote sensing in soil salinization. In the present paper, the authors took the Ugan-Kuqa River Delta Oasis as an example, unified .NET and the SuperMap platform with SQL Server database stored data, used the B/S pattern and the C# language to design and develop the typical surface object spectral information system, and established the typical surface object spectral database according to the characteristics of arid areas oasis. The system implemented the classified storage and the management of typical surface object spectral information and the related attribute data of the study areas; this system also implemented visualized two-way query between the maps and attribute data, the drawings of the surface object spectral response curves and the processing of the derivative spectral data and its drawings. In addition, the system initially possessed a simple spectral data mining and analysis capabilities, and this advantage provided an efficient, reliable and convenient data management and application platform for the Ugan-Kuqa River Delta Oasis's follow-up study in soil salinization. Finally, It's easy to maintain, convinient for secondary development and practically operating in good condition.

Prediction of forest canopy and surface fuels from lidar and satellite time series data in a bark beetle-affected forest

Treesearch

Benjamin C. Bright; Andrew T. Hudak; Arjan J. H. Meddens; Todd J. Hawbaker; Jennifer S. Briggs; Robert E. Kennedy

2017-01-01

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and...

Application of SAR Remote Sensing in Land Surface Processes Over Tropical region

NASA Technical Reports Server (NTRS)

Saatchi, Sasan S.

1996-01-01

This paper outlines the potential applications of polarimetric SAR systems over tropical regions such as mapping land use and deforestation, forest regeneration, wetland and inundation studies, and mapping land cover types for biodiversity and habitat conservation studies.

Deriving hourly evapotranspiration (ET) rates with SEBS: A lysimetric evaluation

USDA-ARS?s Scientific Manuscript database

Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance S...

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

Lunar Prospector: a Preliminary Surface Remote Sensing Resource Assessment for the Moon

NASA Technical Reports Server (NTRS)

Mardon, A. A.

1992-01-01

The potential existence of lunar volatiles is a scientific discovery that could distinctly change the direction of pathways of inner solar system human expansion. With a dedicated germanium gamma ray spectrometer launched in the early 1990's, surface water concentrations of 0.7 percent could be detected immediately upon full lunar polar orbit operations. The expense of lunar base construction and operation would be dramatically reduced over a scenario with no lunar volatile resources. Global surface mineral distribution could be mapped out and integrated into a GIS database for lunar base site selection. Extensive surface lunar mapping would also result in the utilization of archived Apollo images. A variety of remote sensing systems and their parameters have been proposed for use in the detection of these lunar ice masses. The detection or nondetection of subsurface and surface ice masses in lunar polar crater floors could dramatically direct the development pathways that the human race might follow in its radiation from the Earth to habitable locales in the inner terran solar system. Potential sources of lunar volatiles are described. The use of remote sensing to detect lunar volatiles is addressed.

Comparison of Model Prediction with Measurements of Galactic Background Noise at L-Band

NASA Technical Reports Server (NTRS)

LeVine, David M.; Abraham, Saji; Kerr, Yann H.; Wilson, Willam J.; Skou, Niels; Sobjaerg, S.

2004-01-01

The spectral window at L-band (1.413 GHz) is important for passive remote sensing of surface parameters such as soil moisture and sea surface salinity that are needed to understand the hydrological cycle and ocean circulation. Radiation from celestial (mostly galactic) sources is strong in this window and an accurate accounting for this background radiation is often needed for calibration. Modem radio astronomy measurements in this spectral window have been converted into a brightness temperature map of the celestial sky at L-band suitable for use in correcting passive measurements. This paper presents a comparison of the background radiation predicted by this map with measurements made with several modem L-band remote sensing radiometers. The agreement validates the map and the procedure for locating the source of down-welling radiation.

Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.; Broderick, P. W.; Garman, T. R.; Ludwig, R. W.; Beltran, G. N.; Heyman, P. J.; Hooker, L. K.

1983-01-01

Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.

Geochemical and spectral characterization of naturally altered rock surfaces

NASA Technical Reports Server (NTRS)

Chang, L. L. Y.; Sommer, S. E.; Buckingham, W. F.

1981-01-01

The possibility of using the visible-near infrared region for compositional analysis of remotely sensed rock surfaces is studied. This would allow mapping rock type both on the Earth's surface and on other planetary surfaces. Reflectance spectroscopy, economic geology, optical depth determination, and X-ray diffraction mineralogy are discussed.

Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China

NASA Astrophysics Data System (ADS)

Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.

2018-04-01

Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.

Remote sensing of geobotanical relations in Georgia

NASA Technical Reports Server (NTRS)

Arden, D. D., Jr.; Westra, R. N.

1977-01-01

The application of remote sensing to geological investigations, with special attention to geobotanical factors, was evaluated. The general areas of investigation included: (1) recognition of mineral deposits; (2) geological mapping; (3) delineation of geological structure, including areas of complex tectonics; and (4) limestone areas where ground withdrawal had intensified surface collapse.

Automated methodology for selecting hot and cold pixel for remote sensing based evapotranspiration mapping

USDA-ARS?s Scientific Manuscript database

Surface energy fluxes, especially the latent heat flux from evapotranspiration (ET), determine exchanges of energy and mass between the hydrosphere, atmosphere, and biosphere. There are numerous remote sensing-based energy balance approaches such as METRIC and SEBAL that use hot and cold pixels from...

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously unknown features. All of these applications are pertinent to the goals of site discovery and assessment in cultural resource management.

Using remotely-sensed multispectral imagery to build age models for alluvial fan surfaces

NASA Astrophysics Data System (ADS)

D'Arcy, Mitch; Mason, Philippa J.; Roda Boluda, Duna C.; Whittaker, Alexander C.; Lewis, James

2016-04-01

Accurate exposure age models are essential for much geomorphological field research, and generally depend on laboratory analyses such as radiocarbon, cosmogenic nuclide, or luminescence techniques. These approaches continue to revolutionise geomorphology, however they cannot be deployed remotely or in situ in the field. Therefore other methods are still needed for producing preliminary age models, performing relative dating of surfaces, or selecting sampling sites for the laboratory analyses above. With the widespread availability of detailed multispectral imagery, a promising approach is to use remotely-sensed data to discriminate surfaces with different ages. Here, we use new Landsat 8 Operational Land Imager (OLI) multispectral imagery to characterise the reflectance of 35 alluvial fan surfaces in the semi-arid Owens Valley, California. Alluvial fans are useful landforms to date, as they are widely used to study the effects of tectonics, climate and sediment transport processes on source-to-sink sedimentation. Our target fan surfaces have all been mapped in detail in the field, and have well-constrained exposure ages ranging from modern to ~ 125 ka measured using a high density of 10Be cosmogenic nuclide samples. Despite all having similar granitic compositions, the spectral properties of these surfaces vary systematically with their exposure ages. Older surfaces demonstrate a predictable shift in reflectance across the visible and short-wave infrared spectrum. Simple calculations, such as the brightness ratios of different wavelengths, generate sensitive power law relationships with exposure age that depend on post-depositional alteration processes affecting these surfaces. We investigate what these processes might be in this dryland location, and evaluate the potential for using remotely-sensed multispectral imagery for developing surface age models. The ability to remotely sense relative exposure ages has useful implications for preliminary mapping, selecting sampling sites for laboratory-based exposure age techniques, and correlating existing age constraints to un-sampled surfaces.

Geologic map of Mars

USGS Publications Warehouse

Tanaka, Kenneth L.; Skinner, James A.; Dohm, James M.; Irwin, Rossman P.; Kolb, Eric J.; Fortezzo, Corey M.; Platz, Thomas; Michael, Gregory G.; Hare, Trent M.

2014-01-01

This global geologic map of Mars, which records the distribution of geologic units and landforms on the planet's surface through time, is based on unprecedented variety, quality, and quantity of remotely sensed data acquired since the Viking Orbiters. These data have provided morphologic, topographic, spectral, thermophysical, radar sounding, and other observations for integration, analysis, and interpretation in support of geologic mapping. In particular, the precise topographic mapping now available has enabled consistent morphologic portrayal of the surface for global mapping (whereas previously used visual-range image bases were less effective, because they combined morphologic and albedo information and, locally, atmospheric haze). Also, thermal infrared image bases used for this map tended to be less affected by atmospheric haze and thus are reliable for analysis of surface morphology and texture at even higher resolution than the topographic products.

Global Environmental Data for Mapping Infectious Disease Distribution

PubMed Central

Hay, S.I.; Tatem, A.J.; Graham, A.J.; Goetz, S.J.; Rogers, D.J.

2011-01-01

This contribution documents the satellite data archives, data processing methods and temporal Fourier analysis (TFA) techniques used to create the remotely sensed datasets on the DVD distributed with this volume. The aim is to provide a detailed reference guide to the genesis of the data, rather than a standard review. These remotely sensed data cover the entire globe at either 1 × 1 or 8 × 8 km spatial resolution. We briefly evaluate the relationships between the 1 × 1 and 8 × 8 km global TFA products to explore their inter-compatibility. The 8 × 8 km TFA surfaces are used in the mapping procedures detailed in the subsequent disease mapping reviews, since the 1 × 1 km products have been validated less widely. Details are also provided on additional, current and planned sensors that should be able to provide continuity with these environmental variable surfaces, as well as other sources of global data that may be used for mapping infectious disease. PMID:16647967

Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology.

PubMed

Mogaji, Kehinde Anthony; Lim, Hwee San

2017-07-01

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.

Upgraded airborne scanner for commercial remote sensing

NASA Astrophysics Data System (ADS)

Chang, Sheng-Huei; Rubin, Tod D.

1994-06-01

Traditional commercial remote sensing has focused on the geologic market, with primary focus on mineral identification and mapping in the visible through short-wave infrared spectral regions (0.4 to 2.4 microns). Commercial remote sensing users now demand airborne scanning capabilities spanning the entire wavelength range from ultraviolet through thermal infrared (0.3 to 12 microns). This spectral range enables detection, identification, and mapping of objects and liquids on the earth's surface and gases in the air. Applications requiring this range of wavelengths include detection and mapping of oil spills, soil and water contamination, stressed vegetation, and renewable and non-renewable natural resources, and also change detection, natural hazard mitigation, emergency response, agricultural management, and urban planning. GER has designed and built a configurable scanner that acquires high resolution images in 63 selected wave bands in this broad wavelength range.

Mineralogical Mapping in the Cuprite Mining District, Nevada

NASA Technical Reports Server (NTRS)

Goetz, A. F. H.; Srivastava, V.

1985-01-01

The airborne imaging spectrometer (AIS) has provided for the first time, the possibility to map mineralogical constituents in the Earth's surface and thus has enormously increased the value of remote-sensing data as a tool in the solution of geologic problems. The question addressed with AIS at Cuprite was how well could the mineral components at the surface of a hydrothermal alteration zone be detected, identified and mapped? The question was answered positively and is discussed. A relatively rare mineral, buddingtonie, that could not have been detected by conventional means, was discovered and mapped by the use of AIS.

Fresh approaches to Earth surface modeling

NASA Astrophysics Data System (ADS)

Kopylova, N. S.; Starikov, I. P.

2018-05-01

The paper considers modelling of the surface when fixing objects in the geocentric coordinate systems in the course of GLONASS satellite system development. The authors revealed new approaches to presentation of geographical data to a user, transformation of map properties and the leading role of ERS (Earth remote sensing) as a source of mapping information; change of scientific paradigms aimed at improvement of high-accuracy cartographic objects representation in the plane.

MULTI-SCALE REMOTE SENSING MAPPING OF ANTHROPOGENIC IMPERVIOUS SURFACES: SPATIAL AND TEMPORAL SCALING ISSUES RELATED TO ECOLOGICAL AND HYDROLOGICAL LANDSCAPE ANALYSES

EPA Science Inventory

Anthropogenic impervious surfaces are leading contributors to non-point-source water pollution in urban watersheds. These human-created surfaces include such features as roads, parking lots, rooftops, sideways, and driveways. Aerial photography provides a historical vehicle for...

Understanding land surface evapotranspiration with satellite multispectral measurements

NASA Technical Reports Server (NTRS)

Menenti, M.

1993-01-01

Quantitative use of remote multispectral measurements to study and map land surface evapotranspiration has been a challenging issue for the past 20 years. Past work is reviewed against process physics. A simple two-layer combination-type model is used which is applicable to both vegetation and bare soil. The theoretic analysis is done to show which land surface properties are implicitly defined by such evaporation models and to assess whether they are measurable as a matter of principle. Conceptual implications of the spatial correlation of land surface properties, as observed by means of remote multispectral measurements, are illustrated with results of work done in arid zones. A normalization of spatial variability of land surface evaporation is proposed by defining a location-dependent potential evaporation and surface temperature range. Examples of the application of remote based estimates of evaporation to hydrological modeling studies in Egypt and Argentina are presented.

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

NASA Technical Reports Server (NTRS)

Vaughan, Greg R.; Calvin, Wendy M.

2005-01-01

To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

Remote sensing for oceanography, hydrology and agriculture; Proceedings of Symposia A5, A3 and A9 of the COSPAR 29th Plenary Meeting, Washington, Aug. 28-Sept. 5, 1992

NASA Technical Reports Server (NTRS)

Gower, J. F. R. (Editor); Salomonson, V. V. (Editor); Engman, E. T. (Editor); Ormsby, J. P. (Editor); Gupta, R. K. (Editor)

1993-01-01

New results from satellite studies of the ocean and radar mapping of the earth are presented. Atttention is given to data from the ERS-1 satellite. Synthetic aperture radar mapping of land surface features and sea ice, radar backscatter measurements, and orbit altitude measurements are discussed. The use of remote sensing in hydrology, soil moisture determination, precipitation measurement, agricultural meteorology, and crop growth estimation is reviewed.

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.

3D Reconstruction of geological structures based on remote sensing data: example from Anaran anticline, Lurestan province, Zagros folds and thrust belt, Iran.

NASA Astrophysics Data System (ADS)

Snidero, M.; Amilibia, A.; Gratacos, O.; Muñoz, J. A.

2009-04-01

This work presents a methodological workflow for the 3D reconstruction of geological surfaces at regional scale, based on remote sensing data and geological maps. This workflow has been tested on the reconstruction of the Anaran anticline, located in the Zagros Fold and Thrust belt mountain front. The used remote sensing data-set is a combination of Aster and Spot images as well as a high resolution digital elevation model. A consistent spatial positioning of the complete data-set in a 3D environment is necessary to obtain satisfactory results during the reconstruction. The Aster images have been processed by the Optimum Index Factor (OIF) technique, in order to facilitate the geological mapping. By pansharpening of the resulting Aster image with the SPOT panchromatic one we obtain the final high-resolution image used during the 3D mapping. Structural data (dip data) has been acquired through the analysis of the 3D mapped geological traces. Structural analysis of the resulting data-set allows us to divide the structure in different cylindrical domains. Related plunge lines orientation has been used to project data along the structure, covering areas with little or no information. Once a satisfactory dataset has been acquired, we reconstruct a selected horizon following the dip-domain concept. By manual editing, the obtained surfaces have been adjusted to the mapped geological limits as well as to the modeled faults. With the implementation of the Discrete Smooth Interpolation (DSI) algorithm, the final surfaces have been reconstructed along the anticline. Up to date the results demonstrate that the proposed methodology is a powerful tool for 3D reconstruction of geological surfaces when working with remote sensing data, in very inaccessible areas (eg. Iran, China, Africa). It is especially useful in semiarid regions where the structure strongly controls the topography. The reconstructed surfaces clearly show the geometry in the different sectors of the structure: presence of a back thrust affecting the back limb in the southern part of the anticline, the geometry of the grabens located along the anticline crest, the crosscutting relationship in the north-south faulted zone with the main thrust, the northern dome periclinal closure.

An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

USDA-ARS?s Scientific Manuscript database

There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

Geotechnical applications of remote sensing and remote data transmission; Proceedings of the Symposium, Cocoa Beach, FL, Jan. 31-Feb. 1, 1986

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

Johnson, A.I.; Pettersson, C.B.

1988-01-01

Papers and discussions concerning the geotechnical applications of remote sensing and remote data transmission, sources of remotely sensed data, and glossaries of remote sensing and remote data transmission terms, acronyms, and abbreviations are presented. Aspects of remote sensing use covered include the significance of lineaments and their effects on ground-water systems, waste-site use and geotechnical characterization, the estimation of reservoir submerging losses using CIR aerial photographs, and satellite-based investigation of the significance of surficial deposits for surface mining operations. Other topics presented include the location of potential ground subsidence and collapse features in soluble carbonate rock, optical Fourier analysis ofmore » surface features of interest in geotechnical engineering, geotechnical applications of U.S. Government remote sensing programs, updating the data base for a Geographic Information System, the joint NASA/Geosat Test Case Project, the selection of remote data telemetry methods for geotechnical applications, the standardization of remote sensing data collection and transmission, and a comparison of airborne Goodyear electronic mapping system/SAR with satelliteborne Seasat/SAR radar imagery.« less

An autonomous flying vehicle for Mars exploration

NASA Astrophysics Data System (ADS)

Bouras, Peter; Fox, Tim

1990-09-01

A remotely reprogrammable, autonomous flying craft for surveying and mapping the Martian surface environment is presented. This solar powered, modified flying wing design could cover about 2000 statute miles while maneuvering at Mach 0.3. The craft is configured to fly one km above the surface, measuring atmospheric properties, performing subsurface mapping, mapping the surface topography, and searching for the presence of water and perhaps life. A 35 kg scientific payload, plus communication and control electronics, are placed spanwise inside the flying wing, removing the requirement for a normal fuselage, and reducing structural needs. Thrust is provided by a two-bladed electrically driven propeller motorized by high-efficiency solar cells.

The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

NASA Astrophysics Data System (ADS)

Muhammad, R. R. D.; Saepuloh, A.

2016-09-01

Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.

The acquisition, storage, and dissemination of LANDSAT and other LACIE support data

NASA Technical Reports Server (NTRS)

Abbotts, L. F.; Nelson, R. M. (Principal Investigator)

1979-01-01

Activities performed at the LACIE physical data library are described. These include the researching, acquisition, indexing, maintenance, distribution, tracking, and control of LACIE operational data and documents. Much of the data available can be incorporated into an Earth resources data base. Elements of the data collection that can support future remote sensing programs include: (1) the LANDSAT full-frame image files; (2) the microfilm file of aerial and space photographic and multispectral maps and charts that encompasses a large portion of the Earth's surface; (3) the map/chart collection that includes various scale maps and charts for a good portion of the U.S. and the LACIE area in foreign countries; (4) computer-compatible tapes of good quality LANDSAT scenes; (5) basic remote sensing data, project data, reference material, and associated publications; (6) visual aids to support presentation on remote sensing projects; and (7) research acquisition and handling procedures for managing data.

Applications of remote sensing to watershed management

NASA Technical Reports Server (NTRS)

Rango, A.

1975-01-01

Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.

AVIRIS Land-Surface Mapping in Support of the Boreal Ecosystem-Atmosphere Study (BOREAS)

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Gamon, John; Keightley, Keir; Prentiss, Dylan; Reith, Ernest; Green, Robert

2001-01-01

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely-sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS follow-on program is concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has the potential of contributing to BOREAS through: (1) accurate retrieved apparent surface reflectance; (2) improved landcover classification; and (3) direct assessment of biochemical/biophysical information such as canopy liquid water and chlorophyll concentration through pigment fits. In this paper, we present initial products for major flux tower sites including: (1) surface reflectance of dominant cover types; (2) a land-cover classification developed using spectral mixture analysis (SMA) and Multiple Endmember Spectral Mixture Analysis (MESMA); and (3) liquid water maps. Our goal is to compare these land-cover maps to existing maps and to incorporate AVIRIS image products into models of photosynthetic flux.

Aircraft and satellite remote sensing of desert soils and landscapes

NASA Technical Reports Server (NTRS)

Petersen, G. W.; Connors, K. F.; Miller, D. A.; Day, R. L.; Gardner, T. W.

1987-01-01

Remote sensing data on desert soils and landscapes, obtained by the Landsat TM, Heat Capacity Mapping Mission (HCMM), Simulated SPOT, and Thermal IR Multispectral Scanner (TIMS) aboard an aircraft, are discussed together with the analytical techniques used in the studies. The TM data for southwestern Nevada were used to discriminate among the alluvial fan deposits with different degrees of desert pavement and varnish, and different vegetation cover. Thermal-IR data acquired from the HCMM satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures in central Utah. Simulated SPOT data for northwestern New Mexico identified geomorphic features, such as differences in eolian sand cover and fluvial incision, while the TIMS data depicted surface geologic features of the Saline Valley in California.

Introduction and Testing of a Monitoring and Colony-Mapping Method for Waterbird Populations That Uses High-Speed and Ultra-Detailed Aerial Remote Sensing

PubMed Central

Bakó, Gábor; Tolnai, Márton; Takács, Ádám

2014-01-01

Remote sensing is a method that collects data of the Earth's surface without causing disturbances. Thus, it is worthwhile to use remote sensing methods to survey endangered ecosystems, as the studied species will behave naturally while undisturbed. The latest passive optical remote sensing solutions permit surveys from long distances. State-of-the-art highly sensitive sensor systems allow high spatial resolution image acquisition at high altitudes and at high flying speeds, even in low-visibility conditions. As the aerial imagery captured by an airplane covers the entire study area, all the animals present in that area can be recorded. A population assessment is conducted by visual interpretations of an ortho image map. The basic objective of this study is to determine whether small- and medium-sized bird species are recognizable in the ortho images by using high spatial resolution aerial cameras. The spatial resolution needed for identifying the bird species in the ortho image map was studied. The survey was adjusted to determine the number of birds in a colony at a given time. PMID:25046012

GIS prospectivity mapping and 3D modeling validation for potential uranium deposit targets in Shangnan district, China

NASA Astrophysics Data System (ADS)

Xie, Jiayu; Wang, Gongwen; Sha, Yazhou; Liu, Jiajun; Wen, Botao; Nie, Ming; Zhang, Shuai

2017-04-01

Integrating multi-source geoscience information (such as geology, geophysics, geochemistry, and remote sensing) using GIS mapping is one of the key topics and frontiers in quantitative geosciences for mineral exploration. GIS prospective mapping and three-dimensional (3D) modeling can be used not only to extract exploration criteria and delineate metallogenetic targets but also to provide important information for the quantitative assessment of mineral resources. This paper uses the Shangnan district of Shaanxi province (China) as a case study area. GIS mapping and potential granite-hydrothermal uranium targeting were conducted in the study area combining weights of evidence (WofE) and concentration-area (C-A) fractal methods with multi-source geoscience information. 3D deposit-scale modeling using GOCAD software was performed to validate the shapes and features of the potential targets at the subsurface. The research results show that: (1) the known deposits have potential zones at depth, and the 3D geological models can delineate surface or subsurface ore-forming features, which can be used to analyze the uncertainty of the shape and feature of prospectivity mapping at the subsurface; (2) single geochemistry anomalies or remote sensing anomalies at the surface require combining the depth exploration criteria of geophysics to identify potential targets; and (3) the single or sparse exploration criteria zone with few mineralization spots at the surface has high uncertainty in terms of the exploration target.

Environmental application of remote sensing methods to coastal zone land use and marine resource management, Appendices A to E. [in southeastern Virginia

NASA Technical Reports Server (NTRS)

1972-01-01

Important data were compiled for use with the Richmond-Cape Henry Environmental Laboratory (RICHEL) remote sensing project in coastal zone land use and marine resources management, and include RICHEL climatological data and sources, a land use inventory, topographic and soil maps, and gaging records for RICHEL surface waters.

Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

NASA Astrophysics Data System (ADS)

Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

2016-12-01

Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

The Tetracorder user guide: version 4.4

USGS Publications Warehouse

Livo, Keith Eric; Clark, Roger N.

2014-01-01

Imaging spectroscopy mapping software assists in the identification and mapping of materials based on their chemical properties as expressed in spectral measurements of a planet including the solid or liquid surface or atmosphere. Such software can be used to analyze field, aircraft, or spacecraft data; remote sensing datasets; or laboratory spectra. Tetracorder is a set of software algorithms commanded through an expert system to identify materials based on their spectra (Clark and others, 2003). Tetracorder also can be used in traditional remote sensing analyses, because some of the algorithms are a version of a matched filter. Thus, depending on the instructions fed to the Tetracorder system, results can range from simple matched filter output, to spectral feature fitting, to full identification of surface materials (within the limits of the spectral signatures of materials over the spectral range and resolution of the imaging spectroscopy data). A basic understanding of spectroscopy by the user is required for developing an optimum mapping strategy and assessing the results.

CONFIRMING THE RESULTS: AN ACCURACY ASSESSMENT OF REMOTE PRODUCTS, AN EXAMPLE COMPARING MULTIPLE MID-ATLANTIC SUB-PIXEL IMPERVIOUS SURFACE MAPS

EPA Science Inventory

Anthropogenic impervious surfaces have an important relationship with non-point source pollution (NPS) in urban watersheds. The amount of impervious surface area in a watershed is a key indicator of landscape change. As a single variable, it serves to intcgrate a number of concur...

Estimating and validating surface energy fluxes at field scale over a heterogeneous land surfaces based on two-source energy balance model (TSEB)

USDA-ARS?s Scientific Manuscript database

Accurate estimation of surface energy fluxes at field scale over large areas has the potential to improve agricultural water management in arid and semiarid watersheds. Remote sensing may be the only viable approach for mapping fluxes over heterogeneous landscapes. The Two-Source Energy Balance mode...

Demonstration of centimeter-level precision, swath mapping, full-waveform laser altimetry from high altitude on the Global Hawk UAV for future application to cryospheric remote sensing

NASA Astrophysics Data System (ADS)

Blair, J. B.; Wake, S.; Rabine, D.; Hofton, M. A.; Mitchell, S.

2013-12-01

The Land Vegetation and Ice Sensor (LVIS) is a high-altitude, wide-swath laser altimeter that has, for over 15 years, demonstrated state-of-the-art performance in surface altimetry, including many aspects of remote sensing of the cryosphere such as precise topography of ice sheets and sea ice. NASA Goddard, in cooperation with NASA's Earth Science Technology Office (ESTO), has developed a new, more capable sensor that can operate autonomously from a high-altitude UAV aircraft to further enhance the LVIS capability and extend its reach and coverage. In June 2012, this latest sensor, known as LVIS-GH, was integrated onto NASA's Global Hawk aircraft and completed a successful high-altitude demonstration flight over Death Valley, Owens Valley, and the Sierra Nevada region of California. Data were collected over a wide variety of terrain types from 58,000' (> 17 km) altitude during the 6 hour long test flight. The full-waveform laser altimetry technique employed by LVIS and LVIS-GH provides precise surface topography measurements for solid earth and cryospheric applications and captures the vertical structure of forests in support of territorial ecology studies. LVIS-GH fully illuminates and maps a 4 km swath and provides cm-level range precision, as demonstrated in laboratory and horizontal range testing, as well as during this test flight. The cm range precision is notable as it applies to accurate measurements of sea ice freeboard and change detection of subtle surface deformation such as heaving in permafrost areas. In recent years, LVIS has primarily supported Operation IceBridge activities, including deployments to the Arctic and Antarctic on manned aircraft such as the NASA DC-8 and P-3. The LVIS-GH sensor provides an major upgrade of coverage capability and remote access; LVIS-GH operating on the long-duration Global Hawk aircraft can map up to 50,000 km^2 in a single flight and can provide access to remote regions such as the entirety of Antarctica. Future applications of LVIS-GH could include comprehensive mapping of cryosphere targets over large regions such as Alaska, Greenland, and Antarctica as well as an opportunity for seasonal mapping of sea and land ice. Data from the test flight will be presented along with accuracy assessment and specific examples of the cm-level range precision and wide swath mapping ability relevant to cryospheric remote sensing.

A global, 30-m resolution land-surface water body dataset for 2000

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Huang, C.; Song, D. X.; Song, X. P.; Channan, S.; Townshend, J. R.

2014-12-01

Inland surface water is essential to terrestrial ecosystems and human civilization. The distribution of surface water in space and its change over time are related to many agricultural, environmental and ecological issues, and are important factors that must be considered in human socioeconomic development. Accurate mapping of surface water is essential for both scientific research and policy-driven applications. Satellite-based remote sensing provides snapshots of Earth's surface and can be used as the main input for water mapping, especially in large areas. Global water areas have been mapped with coarse resolution remotely sensed data (e.g., the Moderate Resolution Imaging Spectroradiometer (MODIS)). However, most inland rivers and water bodies, as well as their changes, are too small to map at such coarse resolutions. Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) imagery has a 30m spatial resolution and provides decades of records (~40 years). Since 2008, the opening of the Landsat archive, coupled with relatively lower costs associated with computing and data storage, has made comprehensive study of the dynamic changes of surface water over large even global areas more feasible. Although Landsat images have been used for regional and even global water mapping, the method can hardly be automated due to the difficulties on distinguishing inland surface water with variant degrees of impurities and mixing of soil background with only Landsat data. The spectral similarities to other land cover types, e.g., shadow and glacier remnants, also cause misidentification. We have developed a probabilistic based automatic approach for mapping inland surface water bodies. Landsat surface reflectance in multiple bands, derived water indices, and data from other sources are integrated to maximize the ability of identifying water without human interference. The approach has been implemented with open-source libraries to facilitate processing large amounts of Landsat images on high-performance computing machines. It has been applied to the ~9,000 Landsat scenes of the Global Land Survey (GLS) 2000 data collection to produce a global, 30m resolution inland surface water body data set, which will be made available on the Global Land Cover Facility (GLCF) website (http://www.landcover.org).

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1987-01-01

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

A survey of natural aggregate properties and characteristics important in remote sensing and airborne geophysics

USGS Publications Warehouse

Knepper, D.H.; Langer, W.H.; Miller, S.

1995-01-01

Natural aggregate is vital to the construction industry. Although natural aggregate is a high volume/low value commodity that is abundant, new sources are becoming increasingly difficult to find and develop because of rigid industry specifications, political considerations, development and transportation costs, and environmental concerns. There are two primary sources of natural aggregate: (1) exposed or near-surface bedrock that can be crushed, and (2) deposits of sand and gravel. Remote sensing and airborne geophysics detect surface and near-surface phenomena, and may be useful for detecting and mapping potential aggregate sources; however, before a methodology for applying these techniques can be developed, it is necessary to understand the type, distribution, physical properties, and characteristics of natural aggregate deposits. The distribution of potential aggregate sources is closely tied to local geologic history. Conventional exploration for natural aggregate deposits has been largely a ground-based operation, although aerial photographs and topographic maps have been extensively used to target possible deposits. Today, the exploration process also considers factors such as the availability of the land, space and water supply for processing, political and environmental factors, and distance from the market; exploration and planning cannot be separated. There are many physical properties and characteristics by which to judge aggregate material for specific applications; most of these properties and characteristics pertain only to individual aggregate particles. The application of remote sensing and airborne geophysical measurements to detecting and mapping potential aggregate sources, however, is based on intrinsic bulk physical properties and extrinsic characteristics of the deposits that can be directly measured, mathematically derived from measurement, or interpreted with remote sensing and geophysical data. ?? 1995 Oxford UniversityPress.

DAFNE: A Matlab toolbox for Bayesian multi-source remote sensing and ancillary data fusion, with application to flood mapping

NASA Astrophysics Data System (ADS)

D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco P.; Pasquariello, Guido

2018-03-01

High-resolution, remotely sensed images of the Earth surface have been proven to be of help in producing detailed flood maps, thanks to their synoptic overview of the flooded area and frequent revisits. However, flood scenarios can be complex situations, requiring the integration of different data in order to provide accurate and robust flood information. Several processing approaches have been recently proposed to efficiently combine and integrate heterogeneous information sources. In this paper, we introduce DAFNE, a Matlab®-based, open source toolbox, conceived to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of following the evolution of an event through multi-temporal output flood maps. Each DAFNE module can be easily modified or upgraded to meet different user needs. The DAFNE suite is presented together with an example of its application.

Mapping Daily Evapotranspiration at Field to Global Scales using Geostationary and Polar Orbiting Satellite Imagery

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetati...

Imaging lithosphere structures using long period surface waves from ambient noise: a case study in western USA

NASA Astrophysics Data System (ADS)

Yang, Y.

2013-12-01

Since the emerging of ambient noise tomography in 2005, it has become a well-established method and been applied all over the world to imaging crustal and uppermost mantle structures because of its exclusive capability to extract short period surface waves. Most studies of ambient noise tomography performed so far use surface waves at periods shorter than 40/50 sec. There are a few studies of long period surface wave tomography from ambient noise (longer than 50 sec) in continental and global scales. To our knowledge, almost no tomography studies have been performed using long period surface waves (~50-200 sec) from ambient noise in regional scales with an aperture of several hundred kilometres. In this study, we demonstrate the capability of using long period surface waves from ambient noise in regional surface wave tomography by showing a case study of western USA using the USArray Transportable component (TA). We select about 150 TA stations located in a region including northern California, northern Nevada and Oregon as the 'base' stations and about 200 stations from Global Seismographic Network (GSN) and The International Federation of Digital Seismograph Networks (FDSN) as the 'remote' stations. We perform monthly cross-correlations of continuous ambient noise data recorded in 2006-2008 between the 'base' stations and the 'remote' stations and then use a stacking method based on instantaneous phase coherence to stack the monthly cross-correlations to obtain the final cross-correlations. The results show that high signal-to-noise ratio long period Raleigh waves are obtained between the 'base' stations and 'remote' stations located several thousand or even more than ten thousand kilometres away from the 'base' stations. By treating each of the 'remote' station as a 'virtual' teleseismic earthquake and measuring surface wave phases at the 'base' stations, we generate phase velocity maps at 50-200 sec periods in the regions covered by the 'base' stations using an array-based two-plane-wave tomography method. To evaluate the reliability of the resulting phase velocity maps, we compare them with published phase velocity maps using the same tomography method but based on teleseismic data. The comparison shows that long period surface wave phase velocity maps based 'virtual' events from ambient noise and those based on natural earthquakes are very similar with differences within the range of uncertainties. The similarity of phase velocity maps justifies the application of long period surface waves from ambient noise in regional lithosphere imaging. The successful extraction of long period surface waves between station pairs with distances as long as several thousand or ten thousand kilometres can link seismic arrays located in different continents, such as CEArray in China and USArray in USA. With the rapid developments of large scale seismic arrays in different continents, those inter-continental surface waves from ambient noise can be incorporated in both regional- and global-scale surface wave tomography to significantly increase the path coverage in both lateral and azimuthal senses, which is essential to improving imaging of high resolution heterogeneities and azimuthal anisotropy, especially at regions with gaps of azimuthal distributions of earthquakes.

Learning Methods of Remote Sensing In the 2013 Curriculum of Secondary School

NASA Astrophysics Data System (ADS)

Lili Somantri, Nandi

2016-11-01

The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Geologic Interpretation of Data Sets Collected by Planetary Analog Geology Traverses and by Standard Geologic Field Mapping. Part 1; A Comparison Study

NASA Technical Reports Server (NTRS)

Eppler, Dean B.; Bleacher, Jacob F.; Evans, Cynthia A.; Feng, Wanda; Gruener, John; Hurwitz, Debra M.; Skinner, J. A., Jr.; Whitson, Peggy; Janoiko, Barbara

2013-01-01

Geologic maps integrate the distributions, contacts, and compositions of rock and sediment bodies as a means to interpret local to regional formative histories. Applying terrestrial mapping techniques to other planets is challenging because data is collected primarily by orbiting instruments, with infrequent, spatiallylimited in situ human and robotic exploration. Although geologic maps developed using remote data sets and limited "Apollo-style" field access likely contain inaccuracies, the magnitude, type, and occurrence of these are only marginally understood. This project evaluates the interpretative and cartographic accuracy of both field- and remote-based mapping approaches by comparing two 1:24,000 scale geologic maps of the San Francisco Volcanic Field (SFVF), north-central Arizona. The first map is based on traditional field mapping techniques, while the second is based on remote data sets, augmented with limited field observations collected during NASA Desert Research & Technology Studies (RATS) 2010 exercises. The RATS mission used Apollo-style methods not only for pre-mission traverse planning but also to conduct geologic sampling as part of science operation tests. Cross-comparison demonstrates that the Apollo-style map identifies many of the same rock units and determines a similar broad history as the field-based map. However, field mapping techniques allow markedly improved discrimination of map units, particularly unconsolidated surficial deposits, and recognize a more complex eruptive history than was possible using Apollo-style data. Further, the distribution of unconsolidated surface units was more obvious in the remote sensing data to the field team after conducting the fieldwork. The study raises questions about the most effective approach to balancing mission costs with the rate of knowledge capture, suggesting that there is an inflection point in the "knowledge capture curve" beyond which additional resource investment yields progressively smaller gains in geologic knowledge.

Rapid-response tools and datasets for post-fire remediation: Linking remote sensing and process-based hydrological models

Treesearch

M. E. Miller; William Elliot; M. Billmire; Pete Robichaud; K. A. Endsley

2016-01-01

Post-wildfire flooding and erosion can threaten lives, property and natural resources. Increased peak flows and sediment delivery due to the loss of surface vegetation cover and fire-induced changes in soil properties are of great concern to public safety. Burn severity maps derived from remote sensing data reflect fire-induced changes in vegetative cover and soil...

Aquarius and Remote Sensing of Sea Surface Salinity from Space

NASA Technical Reports Server (NTRS)

LeVine, David M.; Lagerloef, G. S. E.; Torrusio, S.

2012-01-01

Aquarius is an L-band radiometer and scatterometer instrument combination designed to map the salinity field at the surface of the ocean from space. The instrument is designed to provide global salinity maps on a monthly basis with a spatial resolution of 150 km and an accuracy of 0.2 psu. The science objective is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean. This data will promote understanding of ocean circulation and its role in the global water cycle and climate.

Mapping Surface Soil Organic Carbon for Crop Fields with Remote Sensing

NASA Technical Reports Server (NTRS)

Chen, Feng; Kissel, David E.; West, Larry T.; Rickman, Doug; Luvall, J. C.; Adkins, Wayne

2004-01-01

The organic C concentration of surface soil can be used in agricultural fields to vary crop production inputs. Organic C is often highly spatially variable, so that maps of soil organic C can be used to vary crop production inputs using precision farming technology. The objective of this research was to demonstrate the feasibility of mapping soil organic C on three fields, using remotely sensed images of the fields with a bare surface. Enough soil samples covering the range in soil organic C must be taken from each field to develop a satisfactory relationship between soil organic C content and image reflectance values. The number of soil samples analyzed in the three fields varied from 22 to 26. The regression equations differed between fields, but gave highly significant relationships with R2 values of 0.93, 0.95, and 0.89 for the three fields. A comparison of predicted and measured values of soil organic C for an independent set of 2 soil samples taken on one of the fields gave highly satisfactory results, with a comparison equation of % organic C measured + 1.02% organic C predicted, with r2 = 0.87.

Synoptic thermal and oceanographic parameter distributions in the New York Bight Apex

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Bahn, G. S.; Thomas, J. P.

1981-01-01

Concurrent surface water measurements made from a moving oceanographic research vessel were used to calibrate and interpret remotely sensed data collected over a plume in the New York Bight Apex on 23 June 1977. Multiple regression techniques were used to develop equations to map synoptic distributions of chlorophyll a and total suspended matter in the remotely sensed scene. Thermal (which did not have surface calibration values) and water quality parameter distributions indicated a cold mass of water in the Bight Apex with an overflowing nutrient-rich warm water plume that originated in the Sandy Hook Bay and flowed south near the New Jersey shoreline. Data analysis indicates that remotely sensed data may be particularly useful for studying physical and biological processes in the top several metres of surface water at plume boundaries.

The Rise of GNSS Reflectometry for Earth Remote Sensing

NASA Technical Reports Server (NTRS)

Zuffada, Cinzia; Li, Zhijin; Nghiem, Son V.; Lowe, Steve; Shah, Rashmi; Clarizia, Maria Paola; Cardellach, Estel

2015-01-01

The Global Navigation Satellite System (GNSS) reflectometry, i.e. GNSS-R, is a novel remote-sensing technique first published in that uses GNSS signals reflected from the Earth's surface to infer its surface properties such as sea surface height (SSH), ocean winds, sea-ice coverage, vegetation, wetlands and soil moisture, to name a few. This communication discusses the scientific value of GNSS-R to (a) furthering our understanding of ocean mesoscale circulation toward scales finer than those that existing nadir altimeters can resolve, and (b) mapping vegetated wetlands, an emerging application that might open up new avenues to map and monitor the planet's wetlands for methane emission assessments. Such applications are expected to be demonstrated by the availability of data from GEROS-ISS, an ESA experiment currently in phase A, and CyGNSS [3], a NASA mission currently in development. In particular, the paper details the expected error characteristics and the role of filtering played in the assimilation of these data to reduce the altimetric error (when averaging many measurements).

Color Shaded-Relief and Surface-Classification Maps of the Fish Creek Area, Harrison Bay Quadrangle, Northern Alaska

USGS Publications Warehouse

Mars, John L.; Garrity, Christopher P.; Houseknecht, David W.; Amoroso, Lee; Meares, Donald C.

2007-01-01

Introduction The northeastern part of the National Petroleum Reserve in Alaska (NPRA) has become an area of active petroleum exploration during the past five years. Recent leasing and exploration drilling in the NPRA requires the U.S. Bureau of Land Management (BLM) to manage and monitor a variety of surface activities that include seismic surveying, exploration drilling, oil-field development drilling, construction of oil-production facilities, and construction of pipelines and access roads. BLM evaluates a variety of permit applications, environmental impact studies, and other documents that require rapid compilation and analysis of data pertaining to surface and subsurface geology, hydrology, and biology. In addition, BLM must monitor these activities and assess their impacts on the natural environment. Timely and accurate completion of these land-management tasks requires elevation, hydrologic, geologic, petroleum-activity, and cadastral data, all integrated in digital formats at a higher resolution than is currently available in nondigital (paper) formats. To support these land-management tasks, a series of maps was generated from remotely sensed data in an area of high petroleum-industry activity (fig. 1). The maps cover an area from approximately latitude 70?00' N. to 70?30' N. and from longitude 151?00' W. to 153?10' W. The area includes the Alpine oil field in the east, the Husky Inigok exploration well (site of a landing strip) in the west, many of the exploration wells drilled in NPRA since 2000, and the route of a proposed pipeline to carry oil from discovery wells in NPRA to the Alpine oil field. This map area is referred to as the 'Fish Creek area' after a creek that flows through the region. The map series includes (1) a color shaded-relief map based on 5-m-resolution data (sheet 1), (2) a surface-classification map based on 30-m-resolution data (sheet 2), and (3) a 5-m-resolution shaded relief-surface classification map that combines the shaded-relief and surface-classification data (sheet 3). Remote sensing datasets that were used to compile the maps include Landsat 7 Enhanced Thematic Mapper+ (ETM+), and interferometric synthetic aperture radar (IFSAR) data. In addition, a 1:250,000-scale geologic map of the Harrison Bay quadrangle, Alaska (Carter and Galloway, 1985, 2005) was used in conjunction with ETM+ and IFSAR data.

3D subsurface geological modeling using GIS, remote sensing, and boreholes data

NASA Astrophysics Data System (ADS)

Kavoura, Katerina; Konstantopoulou, Maria; Kyriou, Aggeliki; Nikolakopoulos, Konstantinos G.; Sabatakakis, Nikolaos; Depountis, Nikolaos

2016-08-01

The current paper presents the combined use of geological-geotechnical insitu data, remote sensing data and GIS techniques for the evaluation of a subsurface geological model. High accuracy Digital Surface Model (DSM), airphotos mosaic and satellite data, with a spatial resolution of 0.5m were used for an othophoto base map compilation of the study area. Geological - geotechnical data obtained from exploratory boreholes and the 1:5000 engineering geological maps were digitized and implemented in a GIS platform for a three - dimensional subsurface model evaluation. The study is located at the North part of Peloponnese along the new national road.

Expert system-based mineral mapping using AVIRIS

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Lefkoff, A. B.; Dietz, J. B.

1992-01-01

Integrated analysis of imaging spectrometer data and field spectral measurements were used in conjunction with conventional geologic field mapping to characterize bedrock and surficial geology at the northern end of Death Valley, California and Nevada. A knowledge-based expert system was used to automatically produce image maps from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data showing the principal surface mineralogy. The imaging spectrometer data show the spatial distribution of spectrally distinct minerals occurring both as primary rock-forming minerals and as alteration and weathering products. Field spectral measurements were used to verify the mineral maps and field mapping was used to extend the remote sensing results. Geographically referenced image-maps produced from these data form new base maps from which to develop improved understanding of the processes of deposition and erosion affecting the present land surface. The 'northern Grapevine Mountains' (NGM) study area was reported on in numerous papers. This area is an unnamed northwestward extension of the range. Most of the research here has concentrated on mapping of Jurassic-age plutons and associated hydrothermal alteration, however, the nature and scope of these studies is much broader, pertaining to the geologic history and development of the entire Death Valley region. AVIRIS data for the NGM site were obtained during May 1989. Additional AVIRIS data were acquired during September 1989 as part of the Geologic Remote Sensing Field Experiment (GRSFE). The area covered by these data overlaps slightly with the May 1989 data. Three and one-half AVIRIS scenes total were analyzed.

An intercomparison study of TSM, SEBS, and SEBAL using high-resolution imagery and lysimetric data

USDA-ARS?s Scientific Manuscript database

Over the past three decades, numerous remote sensing based ET mapping algorithms were developed. These algorithms provided a robust, economical, and efficient tool for ET estimations at field and regional scales. The Two Source Model (TSM), Surface Energy Balance System (SEBS), and Surface Energy Ba...

Osiris-REx Spacecraft Current Status and Forward Plans

NASA Technical Reports Server (NTRS)

Messenger, Scott; Lauretta, Dante S.; Connolly, Harold C., Jr.

2017-01-01

The NASA New Frontiers OSIRIS-REx spacecraft executed a flawless launch on September 8, 2016 to begin its 23-month journey to near-Earth asteroid (101955). The primary objective of the OSIRIS-REx mission is to collect and return to Earth a pristine sample of regolith from the asteroid surface. The sampling event will occur after a two-year period of remote sensing that will ensure a high probability of successful sampling of a region on the asteroid surface having high science value and within well-defined geological context. The OSIRIS-REx instrument payload includes three high-resolution cameras (OCAMS), a visible and near-infrared spectrometer (OVIRS), a thermal imaging spectrometer (OTES), an X-ray imaging spectrometer (REXIS), and a laser altimeter (OLA). As the spacecraft follows its nominal outbound-cruise trajectory, the propulsion, power, communications, and science instruments have undergone basic functional tests, with no major issues. Outbound cruise science investigations include a search for Earth Trojan asteroids as the spacecraft approaches the Sun-Earth L4 Lagrangian point in February 2017. Additional instrument checkouts and calibrations will be carried out during the Earth gravity assist maneuver in September 2017. During the Earth-moon flyby, visual and spectral images will be acquired to validate instrument command sequences planned for Bennu remote sensing. The asteroid Bennu remote sensing campaign will yield high resolution maps of the temperature and thermal inertia, distributions of major minerals and concentrations of organic matter across the asteroid surface. A high resolution 3d shape model including local surface slopes and a high-resolution gravity field will also be determined. Together, these data will be used to generate four separate maps that will be used to select the sampling site(s). The Safety map will identify hazardous and safe operational regions on the asteroid surface. The Deliverability map will quantify the accuracy with which the navigation team can deliver the spacecraft to and from specific sites on the asteroid surface. The Sampleability map quantifies the regolith properties, providing an estimation of how much material would be sampled at different points on the surface. The final Science Value map synthesizes the chemical, mineralogical, and geological, observations to identify the areas of the asteroid surface with the highest science value. Here, priority is given to organic, water-rich regions that have been minimally altered by surface processes. Asteroid surface samples will be acquired with a touch-and-go sample acquisition system (TAGSAM) that uses high purity pressurized N2 gas to mobilize regolith into a stainless steel canister. Although the mission requirement is to collect at least 60 g of material, tests of the TAGSAM routinely exceeded 300 g of simulant in micro-gravity tests. After acquiring the sample, the spacecraft will depart Bennu in 2021 to begin its return journey, with the sample return capsule landing at the Utah Test and Training Range on September 23, 2023. The OSIRIS-REx science team will carry out a series of detailed chemical, mineralogical, isotopic, and spectral studies that will be used to determine the origin and history of Bennu and to relate high spatial resolution sample studies to the global geological context from remote sensing. The outline of the sample analysis plan is described in a companion abstract.

Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

NASA Astrophysics Data System (ADS)

Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

2018-06-01

Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

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.

Using remote sensing and GIS techniques to estimate discharge and recharge. fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Keith, Turner A.

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Evaluation of aircraft microwave data for locating zones for well stimulation and enhanced gas recovery. [Arkansas Arkoma Basin

NASA Technical Reports Server (NTRS)

Macdonald, H.; Waite, W.; Elachi, C.; Babcock, R.; Konig, R.; Gattis, J.; Borengasser, M.; Tolman, D.

1980-01-01

Imaging radar was evaluated as an adjunct to conventional petroleum exploration techniques, especially linear mapping. Linear features were mapped from several remote sensor data sources including stereo photography, enhanced LANDSAT imagery, SLAR radar imagery, enhanced SAR radar imagery, and SAR radar/LANDSAT combinations. Linear feature maps were compared with surface joint data, subsurface and geophysical data, and gas production in the Arkansas part of the Arkoma basin. The best LANDSAT enhanced product for linear detection was found to be a winter scene, band 7, uniform distribution stretch. Of the individual SAR data products, the VH (cross polarized) SAR radar mosaic provides for detection of most linears; however, none of the SAR enhancements is significantly better than the others. Radar/LANDSAT merges may provide better linear detection than a single sensor mapping mode, but because of operator variability, the results are inconclusive. Radar/LANDSAT combinations appear promising as an optimum linear mapping technique, if the advantages and disadvantages of each remote sensor are considered.

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

NASA Technical Reports Server (NTRS)

Li, Shu-Sun; Romanovsky, V.; Lovick, Joe; Wang, Z.; Peterson, Rorik

2003-01-01

A method of mapping the active layer of Arctic permafrost using a combination of conventional synthetic aperture radar (SAR) backscatter and more sophisticated interferometric SAR (INSAR) techniques is proposed. The proposed research is based on the sensitivity of radar backscatter to the freeze and thaw status of the surface soil, and the sensitivity of INSAR techniques to centimeter- to sub-centimeter-level surface differential deformation. The former capability of SAR is investigated for deriving the timing and duration of the thaw period for surface soil of the active layer over permafrost. The latter is investigated for the feasibility of quantitative measurement of frost heaving and thaw settlement of the active layer during the freezing and thawing processes. The resulting knowledge contributes to remote sensing mapping of the active layer dynamics and Arctic land surface hydrology.

Summaries of the thematic conferences on remote sensing for exploration geology

NASA Technical Reports Server (NTRS)

1989-01-01

The Thematic Conference series was initiated to address the need for concentrated discussion of particular remote sensing applications. The program is primarily concerned with the application of remote sensing to mineral and hydrocarbon exploration, with special emphasis on data integration, methodologies, and practical solutions for geologists. Some fifty invited papers are scheduled for eleven plenary sessions, formulated to address such important topics as basement tectonics and their surface expressions, spectral geology, applications for hydrocarbon exploration, and radar applications and future systems. Other invited presentations will discuss geobotanical remote sensing, mineral exploration, engineering and environmental applications, advanced image processing, and integration and mapping.

Data needs and data bases for climate studies

NASA Technical Reports Server (NTRS)

Matthews, Elaine

1986-01-01

Two complementary global digital data bases of vegetation and land use, compiled at 1 deg resolution from published sources for use in climate studies, are discussed. The data bases were implemented, in several individually tailored formulations, in a series of climate related applications including: land-surface prescriptions in three-dimensional general circulation models, global biogeochemical cycles (CO2, methane), critical-area mapping for satellite monitoring of land-cover change, and large-scale remote sensing of surface reflectance. The climate applications are discussed with reference to data needs, and data availability from traditional and remote sensing sources.

Interactive Mapping on Virtual Terrain Models Using RIMS (Real-time, Interactive Mapping System)

NASA Astrophysics Data System (ADS)

Bernardin, T.; Cowgill, E.; Gold, R. D.; Hamann, B.; Kreylos, O.; Schmitt, A.

2006-12-01

Recent and ongoing space missions are yielding new multispectral data for the surfaces of Earth and other planets at unprecedented rates and spatial resolution. With their high spatial resolution and widespread coverage, these data have opened new frontiers in observational Earth and planetary science. But they have also precipitated an acute need for new analytical techniques. To address this problem, we have developed RIMS, a Real-time, Interactive Mapping System that allows scientists to visualize, interact with, and map directly on, three-dimensional (3D) displays of georeferenced texture data, such as multispectral satellite imagery, that is draped over a surface representation derived from digital elevation data. The system uses a quadtree-based multiresolution method to render in real time high-resolution (3 to 10 m/pixel) data over large (800 km by 800 km) spatial areas. It allows users to map inside this interactive environment by generating georeferenced and attributed vector-based elements that are draped over the topography. We explain the technique using 15 m ASTER stereo-data from Iraq, P.R. China, and other remote locations because our particular motivation is to develop a technique that permits the detailed (10 m to 1000 m) neotectonic mapping over large (100 km to 1000 km long) active fault systems that is needed to better understand active continental deformation on Earth. RIMS also includes a virtual geologic compass that allows users to fit a plane to geologic surfaces and thereby measure their orientations. It also includes tools that allow 3D surface reconstruction of deformed and partially eroded surfaces such as folded bedding planes. These georeferenced map and measurement data can be exported to, or imported from, a standard GIS (geographic information systems) file format. Our interactive, 3D visualization and analysis system is designed for those who study planetary surfaces, including neotectonic geologists, geomorphologists, marine geophysicists, and planetary scientists. The strength of our system is that it combines interactive rendering with interactive mapping and measurement of features observed in topographic and texture data. Comparison with commercially available software indicates that our system improves mapping accuracy and efficiency. More importantly, it enables Earth scientists to rapidly achieve a deeper level of understanding of remotely sensed data, as observations can be made that are not possible with existing systems.

Machine processing of remotely sensed data; Proceedings of the Fifth Annual Symposium, Purdue University, West Lafayette, Ind., June 27-29, 1979

NASA Technical Reports Server (NTRS)

Tendam, I. M. (Editor); Morrison, D. B.

1979-01-01

Papers are presented on techniques and applications for the machine processing of remotely sensed data. Specific topics include the Landsat-D mission and thematic mapper, data preprocessing to account for atmospheric and solar illumination effects, sampling in crop area estimation, the LACIE program, the assessment of revegetation on surface mine land using color infrared aerial photography, the identification of surface-disturbed features through a nonparametric analysis of Landsat MSS data, the extraction of soil data in vegetated areas, and the transfer of remote sensing computer technology to developing nations. Attention is also given to the classification of multispectral remote sensing data using context, the use of guided clustering techniques for Landsat data analysis in forest land cover mapping, crop classification using an interactive color display, and future trends in image processing software and hardware.

Mapping surface soil moisture with L-band radiometric measurements

NASA Technical Reports Server (NTRS)

Wang, James R.; Shiue, James C.; Schmugge, Thomas J.; Engman, Edwin T.

1989-01-01

A NASA C-130 airborne remote sensing aircraft was used to obtain four-beam pushbroom microwave radiometric measurements over two small Kansas tall-grass prairie region watersheds, during a dry-down period after heavy rainfall in May and June, 1987. While one of the watersheds had been burned 2 months before these measurements, the other had not been burned for over a year. Surface soil-moisture data were collected at the time of the aircraft measurements and correlated with the corresponding radiometric measurements, establishing a relationship for surface soil-moisture mapping. Radiometric sensitivity to soil moisture variation is higher in the burned than in the unburned watershed; surface soil moisture loss is also faster in the burned watershed.

Surface compositional variation on the comet 67P/Churyumov-Gerasimenko by OSIRIS data

NASA Astrophysics Data System (ADS)

Barucci, M. A.; Fornasier, S.; Feller, C.; Perna, D.; Hasselmann, H.; Deshapriya, J. D. P.; Fulchignoni, M.; Besse, S.; Sierks, H.; Forgia, F.; Lazzarin, M.; Pommerol, A.; Oklay, N.; Lara, L.; Scholten, F.; Preusker, F.; Leyrat, C.; Pajola, M.; Osiris-Rosetta Team

2015-10-01

Since the Rosetta mission arrived at the comet 67P/Churyumov-Gerasimenko (67/P C-G) on July 2014, the comet nucleus has been mapped by both OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System, [1]) NAC (Narrow Angle Camera) and WAC (Wide Angle Camera) acquiring a huge quantity of surface's images at different wavelength bands, under variable illumination conditions and spatial resolution, and producing the most detailed maps at the highest spatial resolution of a comet nucleus surface.67/P C-G's nucleus shows an irregular bi-lobed shape of complex morphology with terrains showing intricate features [2, 3] and a heterogeneity surface at different scales.

Characterization of water bodies for mosquito habitat using a multi-sensor approach

NASA Astrophysics Data System (ADS)

Midekisa, A.; Wimberly, M. C.; Senay, G. B.

2012-12-01

Malaria is a major health problem in Ethiopia. Anopheles arabiensis, which inhabits and breeds in a variety of aquatic habitats, is the major mosquito vector for malaria transmission in the region. In the Amhara region of Ethiopia, mosquito breeding sites are heterogeneously distributed. Therefore, accurate characterization of aquatic habitats and potential breeding sites can be used as a proxy to measure the spatial distribution of malaria risk. Satellite remote sensing provides the ability to map the spatial distribution and monitor the temporal dynamics of surface water. The objective of this study is to map the probability of surface water accumulation to identify potential vector breeding sites for Anopheles arabiensis using remote sensing data from sensors at multiple spatial and temporal resolutions. The normalized difference water index (NDWI), which is based on reflectance in the green and the near infrared (NIR) bands were used to estimate fractional cover of surface water. Temporal changes in surface water were mapped using NDWI indices derived from MODIS surface reflectance product (MOD09A1) for the period 2001-2012. Landsat TM and ETM+ imagery were used to train and calibrate model results from MODIS. Results highlighted interannual variation and seasonal changes in surface water that were observed from the MODIS time series. Static topographic indices that estimate the potential for water accumulation were generated from 30 meter Shuttle Radar Topography Mission (SRTM) elevation data. Integrated fractional surface water cover was developed by combining the static topographic indices and dynamic NDWI indices using Geographic Information System (GIS) overlay methods. Accuracy of the results was evaluated based on ground truth data that was collected on presence and absence of surface water immediately after the rainy season. The study provided a multi-sensor approach for mapping areas with a high potential for surface water accumulation that are potential breeding habitats for anopheline mosquitoes. The resulting products are useful for public health decision making towards effective prevention and control of the malaria burden in the Amhara region of Ethiopia.

Australian Multiexperimental Assessment of SIR-B (AMAS)

NASA Technical Reports Server (NTRS)

Richards, J. A.; Forster, B. C.; Milne, A. K.; Taylor, G. R.; Trinder, J. C.

1984-01-01

The utility of SIR-B data for analysis of surface properties and subsurface morphology in three arid regions of Australia is investigated. This study area is located in western New South Wales. It contains extensive aeolian and alluvially derived depositional plains and is the site of the University's Arid Zone Research Station; it is well-mapped and surveyed. Radar backscatter is mapped and evaluated against known terrain conditions. Relative components of surface and subsurface return are determined with a view to identifying structural properties of surface and subsurface morphology. The capability of microwave remote sensing in locating likely groundwater sources in the Bancannia Basin, near Fowler's Gap is assessed.

Spectral mapping of soil organic matter

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Baumgardner, M. F.; Johannsen, C. J.

1974-01-01

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

NASA Astrophysics Data System (ADS)

Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

2017-04-01

As a consequence of environmental changes surface waters are undergoing changes in time and space. A better knowledge of the spatial and temporal distribution of surface waters resources becomes essential to support sustainable policies and development activities. Especially because surface waters, are not only a vital sweet water resource, but can also pose hazards to human settlements and infrastructures through flooding. Floods are a highly frequent disaster in the world and can caused huge material losses. Detecting and mapping their spatial distribution is fundamental to ascertain damages and for relief efforts. Spaceborne Synthetic Aperture Radar (SAR) is an effective way to monitor surface waters bodies over large areas since it provides excellent temporal coverage and, all-weather day-and-night imaging capabilities. However, emergent vegetation, trees, wind or flow turbulence can increase radar back-scatter returns and pose problems for the delineation of inundated areas. In such areas, passive remote sensing data can be used to identify vegetated areas and support the interpretation of SAR data. The availability of new Earth Observation products, for example Sentinel-1 (active) and Sentinel-2 (passive) imageries, with both high spatial and temporal resolution, have the potential to facilitate flood detection and monitoring of surface waters changes which are very dynamic in space and time. In this context, the research consists of two parts. In the first part, the objective is to propose generic and reproducible methodologies for the analysis of Sentinel-1 time series data for floods detection and surface waters mapping. The processing chain comprises a series of pre-processing steps and the statistical modeling of the pixel value distribution to produce probabilistic maps for the presence of surface waters. Images pre-processing for all Sentinel-1 images comprise the reduction SAR effect like orbit errors, speckle noise, and geometric effects. A modified Split Based Approach (MSBA) is used in order to focus on surface water areas automatically and facilitate the estimation of class models for water and non-water areas. A Finite Mixture Model is employed as the underlying statistical model to produce probabilistic maps. Subsequently, bilateral filtering is applied to take into account spatial neighborhood relationships in the generation of final map. The elimination of shadows effect is performed in a post-processing step. The processing chain is tested on three case studies. The first case is a flood event in central Ireland, the second case is located in Yorkshire county / Great Britain, and the third test case covers a recent flood event in northern Italy. The tests showed that the modified SBA step and the Finite Mixture Models can be applied for the automatic surface water detection in a variety of test cases. An evaluation again Copernicus products derived from very-high resolution imagery was performed, and showed a high overall accuracy and F-measure of the obtained maps. This evaluation also showed that the use of probability maps and bilateral filtering improved the accuracy of classification results significantly. Based on this quantitative evaluation, it is concluded that the processing chain can be applied for flood mapping from Sentinel-1 data. To estimate robust statistical distributions the method requires sufficient surface waters areas in the observed zone and sufficient contrast between surface waters and other land use classes. Ongoing research addresses the fusion of Sentinel-1 and passive remote sensing data (e.g. Sentinel-2) in order to reduce the current shortcomings in the developed processing chain. In this work, fusion is performed at the feature level to better account for the difference image properties of SAR and optical sensors. Further, the processing chain is currently being optimized in terms of calculation time for a further integration as a flood mapping service on the A2S (Alsace Aval Sentinel) high-performance computing infrastructure of University of Strasbourg.

Advances in satellite remote sensing of environmental variables for epidemiological applications.

PubMed

Goetz, S J; Prince, S D; Small, J

2000-01-01

Earth-observing satellites have provided an unprecedented view of the land surface but have been exploited relatively little for the measurement of environmental variables of particular relevance to epidemiology. Recent advances in techniques to recover continuous fields of air temperature, humidity, and vapour pressure deficit from remotely sensed observations have significant potential for disease vector monitoring and related epidemiological applications. We report on the development of techniques to map environmental variables with relevance to the prediction of the relative abundance of disease vectors and intermediate hosts. Improvements to current methods of obtaining information on vegetation properties, canopy and surface temperature and soil moisture over large areas are also discussed. Algorithms used to measure these variables incorporate visible, near-infrared and thermal infrared radiation observations derived from time series of satellite-based sensors, focused here primarily but not exclusively on the Advanced Very High Resolution Radiometer (AVHRR) instruments. The variables compare favourably with surface measurements over a broad array of conditions at several study sites, and maps of retrieved variables captured patterns of spatial variability comparable to, and locally more accurate than, spatially interpolated meteorological observations. Application of multi-temporal maps of these variables are discussed in relation to current epidemiological research on the distribution and abundance of some common disease vectors.

Assessment of planetary geologic mapping techniques for Mars using terrestrial analogs: The SP Mountain area of the San Francisco Volcanic Field, Arizona

USGS Publications Warehouse

Tanaka, K.L.; Skinner, J.A.; Crumpler, L.S.; Dohm, J.M.

2009-01-01

We photogeologically mapped the SP Mountain region of the San Francisco Volcanic Field in northern Arizona, USA to evaluate and improve the fidelity of approaches used in geologic mapping of Mars. This test site, which was previously mapped in the field, is chiefly composed of Late Cenozoic cinder cones, lava flows, and alluvium perched on Permian limestone of the Kaibab Formation. Faulting and folding has deformed the older rocks and some of the volcanic materials, and fluvial erosion has carved drainage systems and deposited alluvium. These geologic materials and their formational and modificational histories are similar to those for regions of the Martian surface. We independently prepared four geologic maps using topographic and image data at resolutions that mimic those that are commonly used to map the geology of Mars (where consideration was included for the fact that Martian features such as lava flows are commonly much larger than their terrestrial counterparts). We primarily based our map units and stratigraphic relations on geomorphology, color contrasts, and cross-cutting relationships. Afterward, we compared our results with previously published field-based mapping results, including detailed analyses of the stratigraphy and of the spatial overlap and proximity of the field-based vs. remote-based (photogeologic) map units, contacts, and structures. Results of these analyses provide insights into how to optimize the photogeologic mapping of Mars (and, by extension, other remotely observed planetary surfaces). We recommend the following: (1) photogeologic mapping as an excellent approach to recovering the general geology of a region, along with examination of local, high-resolution datasets to gain insights into the complexity of the geology at outcrop scales; (2) delineating volcanic vents and lava-flow sequences conservatively and understanding that flow abutment and flow overlap are difficult to distinguish in remote data sets; (3) taking care to understand that surficial materials (such as alluvium and volcanic ash deposits) are likely to be under-mapped yet are important because they obscure underlying units and contacts; (4) where possible, mapping multiple contact and structure types based on their varying certainty and exposure that reflect the perceived accuracy of the linework; (5) reviewing the regional context and searching for evidence of geologic activity that may have affected the map area yet for which evidence within the map area may be absent; and (6) for multi-authored maps, collectively analyzing the mapping relations, approaches, and methods throughout the duration of the mapping project with the objective of achieving a solid, harmonious product.

Device for inspecting vessel surfaces

DOEpatents

Appel, D. Keith

1995-01-01

A portable, remotely-controlled inspection crawler for use along the walls of tanks, vessels, piping and the like. The crawler can be configured to use a vacuum chamber for supporting itself on the inspected surface by suction or a plurality of magnetic wheels for moving the crawler along the inspected surface. The crawler is adapted to be equipped with an ultrasonic probe for mapping the structural integrity or other characteristics of the surface being inspected. Navigation of the crawler is achieved by triangulation techniques between a signal transmitter on the crawler and a pair of microphones attached to a fixed, remote location, such as the crawler's deployment unit. The necessary communications are established between the crawler and computers external to the inspection environment for position control and storage and/or monitoring of data acquisition.

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.

Remote sensing and geographic information system for appraisal of salt-affected soils in India.

PubMed

Singh, Gurbachan; Bundela, D S; Sethi, Madhurama; Lal, Khajanchi; Kamra, S K

2010-01-01

Quantification of the nature, extent, and spatial distribution of salt-affected soils (SAS) for India and the world is essential for planning and implementing reclamation programs in a timely and cost-effective manner for sustained crop production. The national extent of SAS for India over the last four decades was assessed by conventional and remote sensing approaches using diverse methodologies and class definitions and ranged from 6.0 to 26.1 million hectares (Mha) and 1.2 to 10.1 Mha, respectively. In 1966, an area of 6 Mha under SAS was first reported using the former approach. Three national estimates, obtained using remote sensing, were reconciled using a geographic information system, resulting in an acceptable extent of 6.73 Mha. Moderately and severely salt-encrusted lands having large contiguous area have been correctly mapped, but slightly salt-encrusted land having smaller affected areas within croplands has not been accurately mapped. Recent satellite sensors (e.g., Resourcesat-1, Cartosat-2, IKONOS-II, and RISAT-2), along with improved image processing techniques integrated with terrain and other spatial data using a geographic information system, are enabling mapping at large scale. Significant variations in salt encrustation at the surface caused by soil moisture, waterlogging conditions, salt-tolerant crops, and dynamics of subsurface salts present constraints in appraisal, delineation, and mapping efforts. The article provides an overview of development, identification, characterization, and delineation of SAS, past and current national scenarios of SAS using conventional and remote sensing approaches, reconciliation of national estimates, issues of SAS mapping, and future scope.

Application of Remote Sensing in Geological Mapping, Case Study al Maghrabah Area - Hajjah Region, Yemen

NASA Astrophysics Data System (ADS)

Al-Nahmi, F.; Saddiqi, O.; Hilali, A.; Rhinane, H.; Baidder, L.; El arabi, H.; Khanbari, K.

2017-11-01

Remote sensing technology plays an important role today in the geological survey, mapping, analysis and interpretation, which provides a unique opportunity to investigate the geological characteristics of the remote areas of the earth's surface without the need to gain access to an area on the ground. The aim of this study is achievement a geological map of the study area. The data utilizes is Sentinel-2 imagery, the processes used in this study, the OIF Optimum Index Factor is a statistic value that can be used to select the optimum combination of three bands in a satellite image. It's based on the total variance within bands and correlation coefficient between bands, ICA Independent component analysis (3, 4, 6) is a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals, MNF Minimum Noise Fraction (1, 2, 3) is used to determine the inherent dimensionality of image data to segregate noise in the data and to reduce the computational requirements for subsequent processing, Optimum Index Factor is a good method for choosing the best band for lithological mapping. ICA, MNF, also a practical way to extract the structural geology maps. The results in this paper indicate that, the studied area can be divided into four main geological units: Basement rocks (Meta volcanic, Meta sediments), Sedimentary rocks, Intrusive rocks, volcanic rocks. The method used in this study offers great potential for lithological mapping, by using Sentinel-2 imagery, the results were compared with existing geologic maps and were superior and could be used to update the existing maps.

Application of Remote Sensors in Mapping Rice Area and Forecasting Its Production: A Review

PubMed Central

Mosleh, Mostafa K.; Hassan, Quazi K.; Chowdhury, Ehsan H.

2015-01-01

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ∼19% of the global dietary energy in recent times and its annual average consumption per capita was ∼65 kg during 2010–2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations. PMID:25569753

Application of remote sensors in mapping rice area and forecasting its production: a review.

PubMed

Mosleh, Mostafa K; Hassan, Quazi K; Chowdhury, Ehsan H

2015-01-05

Rice is one of the staple foods for more than three billion people worldwide. Rice paddies accounted for approximately 11.5% of the World's arable land area during 2012. Rice provided ~19% of the global dietary energy in recent times and its annual average consumption per capita was ~65 kg during 2010-2011. Therefore, rice area mapping and forecasting its production is important for food security, where demands often exceed production due to an ever increasing population. Timely and accurate estimation of rice areas and forecasting its production can provide invaluable information for governments, planners, and decision makers in formulating policies in regard to import/export in the event of shortfall and/or surplus. The aim of this paper was to review the applicability of the remote sensing-based imagery for rice area mapping and forecasting its production. Recent advances on the resolutions (i.e., spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the rice crop. For elaborative understanding of the application of remote sensing sensors, following issues were described: the rice area mapping and forecasting its production using optical and microwave imagery, synergy between remote sensing-based methods and other developments, and their implications as an operational one. The overview of the studies to date indicated that remote sensing-based methods using optical and microwave imagery found to be encouraging. However, there were having some limitations, such as: (i) optical remote sensing imagery had relatively low spatial resolution led to inaccurate estimation of rice areas; and (ii) radar imagery would suffer from speckles, which potentially would degrade the quality of the images; and also the brightness of the backscatters were sensitive to the interacting surface. In addition, most of the methods used in forecasting rice yield were empirical in nature, so thus it would require further calibration and validation prior to implement over other geographical locations.

Spectral stratigraphy

NASA Technical Reports Server (NTRS)

Lang, Harold R.

1991-01-01

A new approach to stratigraphic analysis is described which uses photogeologic and spectral interpretation of multispectral remote sensing data combined with topographic information to determine the attitude, thickness, and lithology of strata exposed at the surface. The new stratigraphic procedure is illustrated by examples in the literature. The published results demonstrate the potential of spectral stratigraphy for mapping strata, determining dip and strike, measuring and correlating stratigraphic sequences, defining lithofacies, mapping biofacies, and interpreting geological structures.

Investigation of remote sensing to detect near-surface groundwater on irrigated lands

NASA Technical Reports Server (NTRS)

Ryland, D. W.; Schmer, F. A.; Moore, D. G.

1975-01-01

The application of remote sensing techniques was studied for detecting areas with high water tables in irrigated agricultural lands. Aerial data were collected by the LANDSAT-1 satellite and aircraft over the Kansas/Bostwick Irrigation District in Republic and Jewell Counties, Kansas. LANDSAT-1 data for May 12 and August 10, 1973, and aircraft flights (midday and predawn) on August 10 and 11, 1973, and June 25 and 26, 1974, were obtained. Surface and water table contour maps and active observation well hydrographs were obtained from the Bureau of Reclamation for use in the analysis. Results of the study reveal that LANDSAT-1 data (May MSS band 6 and August MSS band 7) correlate significantly (0.01 level) with water table depth for 144 active observation wells located throughout the Kansas/Bostwick Irrigation District. However, a map of water table depths of less than 1.83 meters prepared from the LANDSAT-1 data did not compare favorably with a map of seeped lands of less than 1.22 m (4 feet) to the water table. Field evaluation of the map is necessary for a complete analysis. Analysis of three fields on a within or single-field basis for the 1973 LANDSAT-1 data also showed significant correlation results.

A generalized geologic map of Mars

NASA Technical Reports Server (NTRS)

Carr, M. H.; Masursky, H.; Saunders, R. S.

1973-01-01

A generalized geologic map of Mars has been constructed largely on the basis of differences in the topography of the surface. A number of topographic features on Mars whose form is highly diagnostic of their origin are shown. Of particular note are the shield volcanoes and lava plains. In some areas, the original features have been considerably modified by subsequent erosional and tectonic processes. These have not, however, resulted in homogenization of the planet's surface, but rather have emphasized its variegated character by leaving a characteristic imprint in specific areas. The topography of the planet, therefore, lends itself well to remote geologic interpretation.

Mapping Surface Water DOC in the Northern Gulf of Mexico Using CDOM Absorption Coefficients and Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Kelly, B.; Chelsky, A.; Bulygina, E.; Roberts, B. J.

2017-12-01

Remote sensing techniques have become valuable tools to researchers, providing the capability to measure and visualize important parameters without the need for time or resource intensive sampling trips. Relationships between dissolved organic carbon (DOC), colored dissolved organic matter (CDOM) and spectral data have been used to remotely sense DOC concentrations in riverine systems, however, this approach has not been applied to the northern Gulf of Mexico (GoM) and needs to be tested to determine how accurate these relationships are in riverine-dominated shelf systems. In April, July, and October 2017 we sampled surface water from 80+ sites over an area of 100,000 km2 along the Louisiana-Texas shelf in the northern GoM. DOC concentrations were measured on filtered water samples using a Shimadzu TOC-VCSH analyzer using standard techniques. Additionally, DOC concentrations were estimated from CDOM absorption coefficients of filtered water samples on a UV-Vis spectrophotometer using a modification of the methods of Fichot and Benner (2011). These values were regressed against Landsat visible band spectral data for those same locations to establish a relationship between the spectral data, CDOM absorption coefficients. This allowed us to spatially map CDOM absorption coefficients in the Gulf of Mexico using the Landsat spectral data in GIS. We then used a multiple linear regressions model to derive DOC concentrations from the CDOM absorption coefficients and applied those to our map. This study provides an evaluation of the viability of scaling up CDOM absorption coefficient and remote-sensing derived estimates of DOC concentrations to the scale of the LA-TX shelf ecosystem.

Applications of space technology to water resources management

NASA Technical Reports Server (NTRS)

Salomonson, V. V.

1977-01-01

Space technology transfer is discussed in terms of applying visible and infrared remote sensing measurement to water resources management. Mapping and monitoring of snowcovered areas, hydrologic land use, and surface water areas are discussed, using information acquired from LANDSAT and NOAA satellite systems.

Satellite mapping of crop water demand in California

USDA-ARS?s Scientific Manuscript database

Surface delivery of irrigation water in the San Joaquin Valley is becoming increasingly restricted due to urbanization and environmental regulation, and the strain is projected to worsen under most climate change scenarios. Remote sensing technology offers the potential to monitor crop evapotranspi...

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

NASA Technical Reports Server (NTRS)

Pavlak, Thomas A.; Broschart, Stephen B.; Lantoine, Gregory

2015-01-01

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, ping pong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities. The goal of this investigation is to understand the trade space associated with carrying out remote sensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically, this study seeks to understand the surface viewing geometries, ranges, etc. that are available from several commonly proposed mapping orbits architectures

Soil-vegetation-atmosphere energy fluxes: Land Surface Temperature evaluation by Terra/MODIS satellite images

NASA Astrophysics Data System (ADS)

Telesca, V.; Copertino, V. A.; Scavone, G.; Pastore, V.; Dal Sasso, S.

2009-04-01

Most of the hydrological models are by now founded on field and satellite data integration. In fact, the use of remote sensing techniques supplies the frequent lack of field-measured variables and parameters required to apply evaluation models of the hydrological cycle components at a regional scale. These components are very sensitive to the climatic and surface features and conditions. Remote sensing represent a complementary contribution to in situ investigation methodologies, furnishing repeated and real time observations. Naturally, the interest of these techniques is tied up to the existence of a solid correlation among the greatness to evaluate and the remote sensing information obtainable from the images. In this context, satellite remote sensing has become a basic tool since it allows the regular monitoring of extensive areas. Different surface variables and parameters can be extracted from the combination of the multi-spectral information contained in a satellite image. Land Surface Temperature (LST) is a fundamental parameter to estimate most of the components of the hydrological cycle and the soil-atmosphere energy balance, such as the net radiation, the sensible heat flux and the actual evapotranspiration. Besides, LST maps can be used in models for the fire monitoring and prevention. The aim of this work is to realize, exploiting the contribution of the remote sensing, some Land Surface Temperature maps, applying different "Split Windows" algorithms and to compare them with the "Day/Night" LST/MODIS, to select the best algorithm to apply in a Two-Source Energy Balance model (STSEB). Integrated into a rainfall/runoff model, it can contribute to cope with problems of land management for the protection from natural hazards. In particular, the energy balance procedure will be included into a model for the ‘in continuous' simulation and the forecast of floods. Another important application of our model is tied up to the forecast of scenarios connected to drought problems. In this context, they can contribute to the planning and the realization of mitigation interventions for the desertification risk.

Mapping Daily and Maximum Flood Extents at 90-m Resolution During Hurricanes Harvey and Irma Using Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Galantowicz, J. F.; Picton, J.; Root, B.

2017-12-01

Passive microwave remote sensing can provided a distinct perspective on flood events by virtue of wide sensor fields of view, frequent observations from multiple satellites, and sensitivity through clouds and vegetation. During Hurricanes Harvey and Irma, we used AMSR2 (Advanced Microwave Scanning Radiometer 2, JAXA) data to map flood extents starting from the first post-storm rain-free sensor passes. Our standard flood mapping algorithm (FloodScan) derives flooded fraction from 22-km microwave data (AMSR2 or NASA's GMI) in near real time and downscales it to 90-m resolution using a database built from topography, hydrology, and Global Surface Water Explorer data and normalized to microwave data footprint shapes. During Harvey and Irma we tested experimental versions of the algorithm designed to map the maximum post-storm flood extent rapidly and made a variety of map products available immediately for use in storm monitoring and response. The maps have several unique features including spanning the entire storm-affected area and providing multiple post-storm updates as flood water shifted and receded. From the daily maps we derived secondary products such as flood duration, maximum flood extent (Figure 1), and flood depth. In this presentation, we describe flood extent evolution, maximum extent, and local details as detected by the FloodScan algorithm in the wake of Harvey and Irma. We compare FloodScan results to other available flood mapping resources, note observed shortcomings, and describe improvements made in response. We also discuss how best-estimate maps could be updated in near real time by merging FloodScan products and data from other remote sensing systems and hydrological models.

Proceedings of the 2004 High Spatial Resolution Commercial Imagery Workshop

NASA Technical Reports Server (NTRS)

2006-01-01

Topics covered include: NASA Applied Sciences Program; USGS Land Remote Sensing: Overview; QuickBird System Status and Product Overview; ORBIMAGE Overview; IKONOS 2004 Calibration and Validation Status; OrbView-3 Spatial Characterization; On-Orbit Modulation Transfer Function (MTF) Measurement of QuickBird; Spatial Resolution Characterization for QuickBird Image Products 2003-2004 Season; Image Quality Evaluation of QuickBird Super Resolution and Revisit of IKONOS: Civil and Commercial Application Project (CCAP); On-Orbit System MTF Measurement; QuickBird Post Launch Geopositional Characterization Update; OrbView-3 Geometric Calibration and Geopositional Accuracy; Geopositional Statistical Methods; QuickBird and OrbView-3 Geopositional Accuracy Assessment; Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images; Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps; Stennis Space Center Verification and Validation Capabilities; Joint Agency Commercial Imagery Evaluation (JACIE) Team; Adjacency Effects in High Resolution Imagery; Effect of Pulse Width vs. GSD on MTF Estimation; Camera and Sensor Calibration at the USGS; QuickBird Geometric Verification; Comparison of MODTRAN to Heritage-based Results in Vicarious Calibration at University of Arizona; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Estimating Sub-Pixel Proportions of Sagebrush with a Regression Tree; How Do YOU Use the National Land Cover Dataset?; The National Map Hazards Data Distribution System; Recording a Troubled World; What Does This-Have to Do with This?; When Can a Picture Save a Thousand Homes?; InSAR Studies of Alaska Volcanoes; Earth Observing-1 (EO-1) Data Products; Improving Access to the USGS Aerial Film Collections: High Resolution Scanners; Improving Access to the USGS Aerial Film Collections: Phoenix Digitizing System Product Distribution; System and Product Characterization: Issues Approach; Innovative Approaches to Analysis of Lidar Data for the National Map; Changes in Imperviousness near Military Installations; Geopositional Accuracy Evaluations of QuickBird and OrbView-3: Civil and Commercial Applications Project (CCAP); Geometric Accuracy Assessment: OrbView ORTHO Products; QuickBird Radiometric Calibration Update; OrbView-3 Radiometric Calibration; QuickBird Radiometric Characterization; NASA Radiometric Characterization; Establishing and Verifying the Traceability of Remote-Sensing Measurements to International Standards; QuickBird Applications; Airport Mapping and Perpetual Monitoring Using IKONOS; OrbView-3 Relative Accuracy Results and Impacts on Exploitation and Accuracy Improvement; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Applying High-Resolution Satellite Imagery and Remotely Sensed Data to Local Government Applications: Sioux Falls, South Dakota; Automatic Co-Registration of QuickBird Data for Change Detection Applications; Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources; Automated, Near-Real Time Cloud and Cloud Shadow Detection in High Resolution VNIR Imagery; Science Applications of High Resolution Imagery at the USGS EROS Data Center; Draft Plan for Characterizing Commercial Data Products in Support of Earth Science Research; Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems; Determining Regional Arctic Tundra Carbon Exchange: A Bottom-Up Approach; Using IKONOS Imagery to Assess Impervious Surface Area, Riparian Buffers and Stream Health in the Mid-Atlantic Region; Commercial Remote Sensing Space Policy Civil Implementation Update; USGS Commercial Remote Sensing Data Contracts (CRSDC); and Commercial Remote Sensing Space Policy (CRSSP): Civil Near-Term Requirements Collection Update.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Report of the Workshop on Geologic Applications of Remote Sensing to the Study of Sedimentary Basins

NASA Technical Reports Server (NTRS)

Lang, H. R. (Editor)

1985-01-01

The Workshop on Geologic Applications of Remote Sensing to the Study of Sedimentary Basins, held January 10 to 11, 1985 in Lakewood, Colorado, involved 43 geologists from industry, government, and academia. Disciplines represented ranged from vertebrate paleontology to geophysical modeling of continents. Deliberations focused on geologic problems related to the formation, stratigraphy, structure, and evolution of foreland basins in general, and to the Wind River/Bighorn Basin area of Wyoming in particular. Geological problems in the Wind River/Bighorn basin area that should be studied using state-of-the-art remote sensing methods were identified. These include: (1) establishing the stratigraphic sequence and mapping, correlating, and analyzing lithofacies of basin-filling strata in order to refine the chronology of basin sedimentation, and (2) mapping volcanic units, fracture patterns in basement rocks, and Tertiary-Holocene landforms in searches for surface manifestations of concealed structures in order to refine models of basin tectonics. Conventional geologic, topographic, geophysical, and borehole data should be utilized in these studies. Remote sensing methods developed in the Wind River/Bighorn Basin area should be applied in other basins.

Optimalisation of remote sensing algorithm in mapping of chlorophyl-a concentration at Pasuruan coastal based on surface reflectance images of Aqua Modis

NASA Astrophysics Data System (ADS)

Wibisana, H.; Zainab, S.; Dara K., A.

2018-01-01

Chlorophyll-a is one of the parameters used to detect the presence of fish populations, as well as one of the parameters to state the quality of a water. Research on chlorophyll concentrations has been extensively investigated as well as with chlorophyll-a mapping using remote sensing satellites. Mapping of chlorophyll concentration is used to obtain an optimal picture of the condition of waters that is often used as a fishing area by the fishermen. The role of remote sensing is a technological breakthrough in broadly monitoring the condition of waters. And in the process to get a complete picture of the aquatic conditions it would be used an algorithm that can provide an image of the concentration of chlorophyll at certain points scattered in the research area of capture fisheries. Remote sensing algorithms have been widely used by researchers to detect the presence of chlorophyll content, where the channels corresponding to the mapping of chlorophyll -concentrations from Landsat 8 images are canals 4, 3 and 2. With multiple channels from Landsat-8 satellite imagery used for chlorophyll detection, optimum algorithmic search can be formulated to obtain maximum results of chlorophyll-a concentration in the research area. From the calculation of remote sensing algorithm hence can be known the suitable algorithm for condition at coast of Pasuruan, where green channel give good enough correlation equal to R2 = 0,853 with algorithm for Chlorophyll-a (mg / m3) = 0,093 (R (-0) Red - 3,7049, from this result it can be concluded that there is a good correlation of the green channel that can illustrate the concentration of chlorophyll scattered along the coast of Pasuruan

Remote Sensing in Geography in the New Millennium: Prospects, Challenges and Opportunities

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Walsh, Stephen J.; Jensen, John R.; Ridd, Merrill K.; Arnold, James E. (Technical Monitor)

2002-01-01

As noted in the first edition of Geography in America, the term remote sensing was coined in the early 1960's by geographers to describe the process of obtaining data by use of both photographic and nonphotographic instruments. Although this is still a working definition today, a more explicit and updated definition as it relates to geography can be phrased as: "remote sensing is the science, art, and technology of identifying, characterizing, measuring, and mapping of Earth surface, and near earth surface, phenomena from some position above using photographic or nonphotographic instruments." Both patterns and processes may be the object of investigation using remote sensing data. The science dimension of geographic remote sensing is rooted in the fact that: a) it is dealing with primary data, wherein the investigator must have an understanding of the environmental phenomena under scrutiny, and b) the investigator must understand something of the physics of the energy involved in the sensing instrument and the atmospheric pathway through which the energy passes from the energy source, to the Earth object to the sensor.

Device for inspecting vessel surfaces

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

Appel, D.K.

1995-12-12

A portable, remotely-controlled inspection crawler is described for use along the walls of tanks, vessels, piping and the like. The crawler can be configured to use a vacuum chamber for supporting itself on the inspected surface by suction or a plurality of magnetic wheels for moving the crawler along the inspected surface. The crawler is adapted to be equipped with an ultrasonic probe for mapping the structural integrity or other characteristics of the surface being inspected. Navigation of the crawler is achieved by triangulation techniques between a signal transmitter on the crawler and a pair of microphones attached to amore » fixed, remote location, such as the crawler`s deployment unit. The necessary communications are established between the crawler and computers external to the inspection environment for position control and storage and/or monitoring of data acquisition. 5 figs.« less

Feasibility study for locating archaeological village sites by satellite remote sensing techniques. [multispectral photography of Alaska

NASA Technical Reports Server (NTRS)

Cook, J. P. (Principal Investigator); Stringer, W. J.

1974-01-01

The author has identified the following significant results. The objective is to determine the feasibility of detecting large Alaskan archaeological sites by satellite remote sensing techniques and mapping such sites. The approach used is to develop digital multispectral signatures of dominant surface features including vegetation, exposed soils and rock, hydrological patterns and known archaeological sites. ERTS-1 scenes are then printed out digitally in a map-like array with a letter reflecting the most appropriate classification representing each pixel. Preliminary signatures were developed and tested. It was determined that there was a need to tighten up the archaeological site signature by developing accurate signatures for all naturally-occurring vegetation and surface conditions in the vicinity of the test area. These second generation signatures have been tested by means of computer printouts and classified tape displays on the University of Alaska CDU-200 and by comparison with aerial photography. It has been concluded that the archaeological signatures now in use are as good as can be developed. Plans are to print out signatures for the entire test area and locate on topographic maps the likely locations of archaeological sites within the test area.

Mapping CDOM Concentration in Waters Influenced by the Mississippi River Plume

NASA Technical Reports Server (NTRS)

Miller, Richard L.; DelCastillo, Carlos E.; Powell, Rodney T.; DSa, Eurico; Spiering, Bruce

2002-01-01

Colored dissolved organic matter (CDOM) is often an important component of the organic carbon pool in river-dominated coastal margins. CDOM directly influences remote sensing applications through its strong absorption in the UV and blue regions of the spectrum. This effect can complicate the use of chlorophyll a retrieval algorithms and phytoplankton production models that are based on remotely sensed ocean color. As freshwater input is the principle source of CDOM in coastal margins, CDOM distribution can often be described by conservative mixing with open ocean waters and may serve as an optical tracer of riverine water. Hence, there is considerable interest in the ability to accurately measure and map CDOM concentrations as well as understand the processes that govern the optical properties and distribution of CDOM in coastal environments. We are examining CDOM dynamics in the waters influenced by the Mississippi River plume. Our program incorporates discrete samples, flow-through measurements, and remote sensing. CDOM absorption spectra of discrete samples are measured at sea using a portable, multiple pathlength waveguide system. A SAFire multi-spectral fluorescence meter provides spectral characterization of CDOM (fluorescence and absorption) using a ship flow-through system for continuous surface mapping. In situ reflectance spectra are obtained by a hand held spectroradiometer. Remotely sensed images are obtained from the SeaWiFS and CRIS (Coastal Research Imaging Spectrometer) instruments. We describe here the instruments used, sampling protocols employed, and the relationships derived between in situ measurements and remotely sensed data for this optically complex environment.

Remote sensing applied to prospecting of thermomineral water in the county of Caldas Novas-Goias

NASA Technical Reports Server (NTRS)

Veneziani, P.; Eustaquiodosanjos, C.

1978-01-01

LANDSAT imagery of the region were studied allowing the placement of the area of study in the regional geological context. A geological mapping of the 1.60.000 scale was done. A methodology was developed which consisted in a regional temperature mapping using trend surface analysis. Through the correlation of all these data, four different areas were localized with a high potential as thermomineral sources.

Incorporating Land-Use Mapping Uncertainty in Remote Sensing Based Calibration of Land-Use Change Models

NASA Astrophysics Data System (ADS)

Cockx, K.; Van de Voorde, T.; Canters, F.; Poelmans, L.; Uljee, I.; Engelen, G.; de Jong, K.; Karssenberg, D.; van der Kwast, J.

2013-05-01

Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means of a particle filter data assimilation approach that incorporates uncertainty in land-use mapping and land-use model parameter assessment into the calibration process. This paper focuses on part of this work, more in particular the modelling of uncertainties associated with the impervious surface cover estimation and urban land-use classification adopted in the land-use mapping approach. Both stages are submitted to a Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The approach was applied on the central part of the Flanders region (Belgium), using a time-series of Landsat/SPOT-HRV data covering the years 1987, 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original classification, it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, incorporating uncertainty in the land-use change model calibration through particle filter data assimilation is proposed to address the uncertainty observed in the derived land-use maps and to reduce uncertainty in future land-use predictions.

Variations in the Characteristics of Craters of the Moon Lava Flows from Vent to Termination: Remotely Sensed Spectra and Field Observations

NASA Astrophysics Data System (ADS)

Hobson, V. R.; Shervais, J. W.

2004-12-01

Developing a method to characterize the physical, chemical and temporal aspects of terrestrial volcanics is a necessary step toward studying volcanics on other planetary bodies. Volcanoes and flows close to populated centers have been studied to varying degree, but remote volcanics remain largely unstudied. Remotely sensed data and derived information can be used to select field sites on Earth and on other planets. Scientists studying volcanics in dangerous areas would benefit from as much advance knowledge of the area as possible before beginning fieldwork. By using satellites and other remote sensing methods, information about the eruptive history can be derived and potentially, the hazard these remote volcanic areas may pose to current and future generations can be estimated. Using Landsat TM, ASTER and other remotely sensed data, the extent and characteristics of lava flows can be examined, but verification and refinement of these methods requires collection of data on the ground. Young lava flows at Craters of the Moon National Park were selected to test methods for remote mapping of recent volcanics. These late Pleistocene to Holocene basalt flows have been mapped to 1:100,000 scale (Kuntz et al, 1988) and have only minor vegetative cover. A range of remotely sensed spectral images were combined to optimize recovery of the mapped flows. Major flow units can be distinguished from each other using unsupervised classification of Landsat TM Bands 1-7, but differentiation of flows within these units presents greater difficulty. Principal component analyses revealed that during the daytime, thermal infrared variations outweigh variations in all other bands. Larger-scale features were observed like edge effects attributable to changes in surface roughness or texture that might occur at flow fronts or at boundaries between flows. Using a digitized version of the geologic map, TM and ASTER data for individual flows were isolated and examined for changes with distance from the source vent or fissure. Several flows were selected for further examination in the field, based on accessibility and scientific interest.

Water resources by orbital remote sensing: Examples of applications

NASA Technical Reports Server (NTRS)

Martini, P. R. (Principal Investigator)

1984-01-01

Selected applications of orbital remote sensing to water resources undertaken by INPE are described. General specifications of Earth application satellites and technical characteristics of LANDSAT 1, 2, 3, and 4 subsystems are described. Spatial, temporal and spectral image attributes of water as well as methods of image analysis for applications to water resources are discussed. Selected examples are referred to flood monitoring, analysis of water suspended sediments, spatial distribution of pollutants, inventory of surface water bodies and mapping of alluvial aquifers.

Lunar Science Conference, 6th, Houston, Tex., March 17-21, 1975, Proceedings. Volume 3 - Physical studies

NASA Technical Reports Server (NTRS)

Merrill, R. B.

1975-01-01

Recent investigations of the moon are reported. Topics discussed include the Apollo 17 site, selenography, craters, remote sensing, selenophysics, lunar surface fields and particles, magnetic properties of lunar samples, physical property measurements, surface-correlated properties, micrometeoroids, solar-system regoliths, and cosmic rays. Lunar orbital data maps are presented, and the evolution of lunar features is examined.

Innovative Technique for High-Accuracy Remote Monitoring of Surface Water

NASA Astrophysics Data System (ADS)

Gisler, A.; Barton-Grimley, R. A.; Thayer, J. P.; Crowley, G.

2016-12-01

Lidar (light detection and ranging) provides absolute depth and topographic mapping capability compared to other remote sensing methods, which is useful for mapping rapidly changing environments such as riverine systems and agricultural waterways. Effectiveness of current lidar bathymetric systems is limited by the difficulty in unambiguously identifying backscattered lidar signals from the water surface versus the bottom, limiting their depth resolution to 0.3-0.5 m. Additionally these are large, bulky systems that are constrained to expensive aircraft-mounted platforms and use waveform-processing techniques requiring substantial computation time. These restrictions are prohibitive for many potential users. A novel lidar device has been developed that allows for non-contact measurements of water depth down to 1 cm with an accuracy and precision of < 1 cm by exploiting the polarization properties of the light-surface interaction. This system can transition seamlessly from ranging over land to shallow to deep water allowing for shoreline charting, measuring water volume, mapping bottom topology, and identifying submerged objects. The scalability of the technique opens up the ability for handheld or UAS-mounted lidar bathymetric systems, which provides for potential applications currently unavailable to the community. The high laser pulse repetition rate allows for very fine horizontal resolution while the photon-counting technique permits real-time depth measurement and object detection. The enhanced measurement capability, portability, scalability, and relatively low-cost creates the opportunity to perform frequent high-accuracy monitoring and measuring of aquatic environments which is crucial for monitoring water resources on fast timescales. Results from recent campaigns measuring water depth in flowing creeks and murky ponds will be presented which demonstrate that the method is not limited by rough water surfaces and can map underwater topology through moderately turbid water.

Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin

USGS Publications Warehouse

Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Rose, Joshua R.; Rigge, Matthew; Walvoord, Michelle Ann

2014-01-01

The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

What would we miss if we characterized the Moon and Mars with just planetary meteorites, remote mapping, and robotic landers?. [Abstract only

NASA Technical Reports Server (NTRS)

Lindstrom, M. M.

1994-01-01

Exploration of the Moon and planets began with telescopic studies of their surfaces, continued with orbiting spacecraft and robotic landers, and will culminate with manned exploration and sample return. For the Moon and Mars we also have accidental samples provided by impacts on their surfaces, the lunar and martian meteorites. How much would we know about the lunar surface if we only had lunar meteorites, orbital spacecraft, and robotic exploration, and not the Apollo and Luna returned samples? What does this imply for Mars? With martian meteorites and data from Mariner, Viking, and the future Pathfinder missions, how much could we learn about Mars? The basis of most of our detailed knowledge about the Moon is the Apollo samples. They provide ground truth for the remote mapping, timescales for lunar processes, and samples from the lunar interior. The Moon is the foundation of planetary science and the basis for our interpretation of the other planets. Mars is similar to the Moon in that impact and volcanism are the dominant processes, but Mars' surface has also been affected by wind and water, and hence has much more complex surface geology. Future geochemical or mineralogical mapping of Mars' surface should be able to tell us whether the dominant rock types of the ancient southern highlands are basaltic, anorthositic, granitic, or something else, but will not be able to tell us the detailed mineralogy, geochemistry, or age. Without many more martian meteorites or returned samples we will not know the diversity of martian rocks, and therefore will be limited in our ability to model martian geological evolution.

Prediction of forest canopy and surface fuels from Lidar and satellite time series data in a bark beetle-affected forest

USGS Publications Warehouse

Bright, Benjamin C.; Hudak, Andrew T.; Meddens, Arjan J.H.; Hawbaker, Todd J.; Briggs, Jenny S.; Kennedy, Robert E.

2017-01-01

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and surface fuels from light detection and ranging (lidar) and Landsat time series explanatory variables via random forest (RF) modeling across a coniferous montane forest in Colorado, USA, which was affected by mountain pine beetles (Dendroctonus ponderosae Hopkins) approximately six years prior. We examined relationships between mapped fuels and the severity of tree mortality with correlation tests. RF models explained 59%, 48%, 35%, and 70% of the variation in available canopy fuel, canopy bulk density, canopy base height, and canopy height, respectively (percent root-mean-square error (%RMSE) = 12–54%). Surface fuels were predicted less accurately, with models explaining 24%, 28%, 32%, and 30% of the variation in litter and duff, 1 to 100-h, 1000-h, and total surface fuels, respectively (%RMSE = 37–98%). Fuel metrics were negatively correlated with the severity of tree mortality, except canopy base height, which increased with greater tree mortality. Our results showed how bark beetle-caused tree mortality significantly reduced canopy fuels in our study area. We demonstrated that lidar and Landsat time series data contain substantial information about canopy and surface fuels and can be used for large-scale efforts to monitor and map fuel loads for fire behavior modeling at a landscape scale.

Development of a Silicon Drift Detector Array: An X-Ray Fluorescence Spectrometer for Remote Surface Mapping

NASA Technical Reports Server (NTRS)

Gaskin, Jessica A.; Carini, Gabriella A.; Wei, Chen; Elsner, Ronald F.; Kramer, Georgiana; De Geronimo, Gianluigi; Keister, Jeffrey W.; Zheng, Li; Ramsey, Brian D.; Rehak, Pavel;

Mapping playa evaporite minerals and associated sediments in Death Valley, California, with multispectral thermal infrared images

USGS Publications Warehouse

Crowley, J.K.; Hook, S.J.

1996-01-01

Efflorescent salt crusts and associated sediments in Death Valley, California, were studied with remote-sensing data acquired by the NASA thermal infrared multispectral scanner (TIMS). Nine spectral classes that represent a variety of surface materials were distinguished, including several classes that reflect important aspects of the playa groundwater chemistry and hydrology. Evaporite crusts containing abundant thenardite (sodium sulfate) were mapped along the northern and eastern margins of the Cottonball Basin, areas where the inflow waters are rich in sodium. Gypsum (calcium sulfate) crusts were more common in the Badwater Basin, particularly near springs associated with calcic groundwaters along the western basin margin. Evaporite-rich crusts generally marked areas where groundwater is periodically near the surface and thus able to replenish the crusts though capillary evaporation. Detrital silicate minerals were prevalent in other parts of the salt pan where shallow groundwater does not affect the surface composition. The surface features in Death Valley change in response to climatic variations on several different timescales. For example, salt crusts on low-lying mudflats form and redissolve during seasonal-to-interannual cycles of wetting and desiccation. In contrast, recent flooding and erosion of rough-salt surfaces in Death Valley probably reflect increased regional precipitation spanning several decades. Remote-sensing observations of playas can provide a means for monitoring changes in evaporite facies and for better understanding the associated climatic processes. At present, such studies are limited by the availability of suitable airborne scanner data. However, with the launch of the Earth Observing System (EOS) AM-1 Platform in 1998, multispectral visible/near-infrared and thermal infrared remote-sensing data will become globally available. Copyright 1996 by the American Geophysical Union.

Remote magnetic navigation to map and ablate left coronary cusp ventricular tachycardia.

PubMed

Burkhardt, J David; Saliba, Walid I; Schweikert, Robert A; Cummings, Jennifer; Natale, Andrea

2006-10-01

Premature ventricular contractions (PVCs) and ventricular tachycardia may arise from the coronary cusps. Navigation, mapping, and ablation in the coronary cusps can be challenging. Remote magnetic navigation may offer an alternative to conventional manually operated catheters. We report a case of left coronary cusp ventricular tachycardia ablation using remote magnetic navigation. Right ventricular outflow tract and coronary cusp mapping, and ablation of the left coronary cusp using a remote magnetic navigation and three-dimensional (3-D) mapping system was performed in a 28-year-old male with frequent, symptomatic PVCs and ventricular tachycardia. Successful ablation of left coronary cusp ventricular tachycardia was performed using remote magnetic navigation. Remote magnetic navigation may be used to map and ablate PVCs and ventricular tachycardia originating from the coronary cusps.

Mapping the Upper Subsurface of MARS Using Radar Polarimetry

NASA Technical Reports Server (NTRS)

Carter, L. M.; Rincon, R.; Berkoski, L.

2012-01-01

Future human exploration of Mars will require detailed knowledge of the surface and upper several meters of the subsurface in potential landing sites. Likewise, many of the Planetary Science Decadal Survey science goals, such as understanding the history of Mars climate change, determining how the surface was altered through processes like volcanism and fluvial activity, and locating regions that may have been hospitable to life in the past, would be significantly advanced through mapping of the upper meters of the surface. Synthetic aperture radar (SAR) is the only remote sensing technique capable of penetrating through meters of material and imaging buried surfaces at high (meters to tens-of-meters) spatial resolution. SAR is capable of mapping the boundaries of buried units and radar polarimetry can provide quantitative information about the roughness of surface and subsurface units, depth of burial of stratigraphic units, and density of materials. Orbital SAR systems can obtain broad coverage at a spatial scale relevant to human and robotic surface operations. A polarimetric SAR system would greatly increase the safety and utility of future landed systems including sample caching.

Mars hemispherical albedo map: absolute value and interannual variability inferred from OMEGA data.

NASA Astrophysics Data System (ADS)

Vincendon, M.; Audouard, J.; Langevin, Y.; Poulet, F.; Bellucci, G.; Bibring, J.-P.; Gondet, B.

2012-04-01

The surface reflectance integrated over all directions and solar wavelengths ("hemispherical albedo") controls the radiative budget at the surface of Mars, and hence its climate. Reference albedo maps are usually derived from nadir observation of surface reflectance through clear atmospheric conditions. However, the atmosphere of Mars is permanently loaded with a significant amount of aerosols (typical visible optical depths of 0.5 under clear atmospheric conditions), which impacts the evaluation of "aerosol free" surface reflectances from remote sensing data. Moreover, the Martian surface is usually assumed to be Lambertian, both for simplicity and due to the lack of robust constraints about its bidirectional properties. We used OMEGA visible and near-IR measurements, with an appropriate UV extrapolation, to calculate as a function of space and time the hemispherical surface albedo of Mars. The contribution of aerosols is removed using a radiative transfer model and recent aerosols properties. Uncertainties associated with this procedure are calculated. The aerosols correction increases the bright/dark surfaces contrast. Typical, mean bidirectional reflectance properties of the martian surface are estimated using MER surface measurements and CRISM remote "EPF" observations. From these constraints, we have derived a typical relationship that makes it possible to convert single nadir measurements of the reflectance into hemispherical albedo. Accounting for the BRDF of the martian surface typically modify by ± 15% the derived albedo, depending on solar zenith angles. We will present our methods and preliminary results regarding seasonal and interannual variations of the surface albedo of Mars during years 2004-2011.

Mapping spatial variation in rock properties in relationship to scale-dependent structure using spectral curvature

NASA Astrophysics Data System (ADS)

Stewart, S. A.; Wynn, T. J.

2000-08-01

Maps of the three-dimensional geometry of geologic surfaces show that structural curvature commonly varies with scale of observation: This fact can be viewed as superposition of structures at different wavelengths. Rock properties such as fracture density and orientation reflect the contribution of superimposed structures. For this reason, characterization of geologic surfaces is fundamentally different from purely geometrical characterization, for which local description of surface properties is sufficient. We show that measured curvature decays according to a power law with increasing size of measurement window, so short-wavelength curvatures do not obscure long-wavelength curvatures in the same data set. This property can be taken advantage of in a simple technique for automatically mapping multiwavelength curvatures. At each point on a surface, curvature is measured at a range of wavelengths. This curvature spectrum can be analyzed in map view or collapsed into a single value at each point in space. The results indicate that complex geologic surfaces can be characterized without any prior knowledge of structural wavelengths and orientation. The method should prove useful in applications requiring knowledge of spatial variation in rock properties from remotely sensed data, such as exploration for hydrocarbon reservoirs or nuclear waste repositories.

Remote Sensing of Salinity and Overview of Results from Aquarius

NASA Technical Reports Server (NTRS)

Le Vine, D. M.; Dinnat, E. P.; Meissner, T.; Wentz, F.; Yueh, S. H.; Lagerloef, G. S. E.

2015-01-01

Aquarius is a combined active/passive microwave (L-band) instrument designed to map the salinity of global oceans from space. The specific goal of Aquarius is to monitor the seasonal and interannual variation of the large scale features of the sea surface salinity (SSS) field of the open ocean (i.e. away from land). The instrumentation has been designed to provide monthly maps with a spatial resolution of 150 km and an accuracy of 0.2 psu

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations: 1. North polar region

NASA Technical Reports Server (NTRS)

Paige, David A.; Bachman, Jennifer E.; Keegan, Kenneth D.

1994-01-01

We present the first maps of the apparent thermal inertia and albedo of the north polar region of Mars. The observations used to create these maps were acquired by the infrared thermal mapper (IRTM) instruments on the two Viking orbiters over a 50-day period in 1978 during the Martian early northern summer season. The maps cover the region from 60 deg N to the north pole at a spatial resolution of 1/2 deg of latitude. The analysis and interpretation of these maps is aided by the results of a one-dimensional radiative convective model, which is used to calculate diurnal variations in surface and atmospheric temperatures, and brightness temperatures at the top of the atmospphere for a wide range of assumptions concerning aerosol optical properties and aerosol optical depths. The results of these calculations show that the effects of the Martian atmosphere on remote determinations of surface thermal inertia are more significant than have been indicated in previous studies. The maps of apparent thermal inertia and albedo show a great deal of spatial structure that is well correlated with surface features.

Observing Planets and Small Bodies in Sputtered High Energy Atom (SHEA) Fluxes

NASA Technical Reports Server (NTRS)

Milillo, A.; Orsini, S.; Hsieh, K. C.; Baragiola, R.; Fama, M.; Johnson, R.; Mura, A.; Plainaki, Ch.; Sarantos, M.; Cassidy, T. A.;

Quantifying sub-pixel urban impervious surface through fusion of optical and inSAR imagery

USGS Publications Warehouse

Yang, L.; Jiang, L.; Lin, H.; Liao, M.

2009-01-01

In this study, we explored the potential to improve urban impervious surface modeling and mapping with the synergistic use of optical and Interferometric Synthetic Aperture Radar (InSAR) imagery. We used a Classification and Regression Tree (CART)-based approach to test the feasibility and accuracy of quantifying Impervious Surface Percentage (ISP) using four spectral bands of SPOT 5 high-resolution geometric (HRG) imagery and three parameters derived from the European Remote Sensing (ERS)-2 Single Look Complex (SLC) SAR image pair. Validated by an independent ISP reference dataset derived from the 33 cm-resolution digital aerial photographs, results show that the addition of InSAR data reduced the ISP modeling error rate from 15.5% to 12.9% and increased the correlation coefficient from 0.71 to 0.77. Spatially, the improvement is especially noted in areas of vacant land and bare ground, which were incorrectly mapped as urban impervious surfaces when using the optical remote sensing data. In addition, the accuracy of ISP prediction using InSAR images alone is only marginally less than that obtained by using SPOT imagery. The finding indicates the potential of using InSAR data for frequent monitoring of urban settings located in cloud-prone areas.

An application of remotely derived climatological fields for risk assessment of vector-borne diseases : a spatial study of filariasis prevalence in the Nile Delta, Egypt.

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

Crombie, M. K.; Gillies, R. R.; Arvidson, R. E.

1999-12-01

This paper applies a relatively straightforward remote sensing method that is commonly used to derive climatological variables. Measurements of surface reflectance and surface radiant temperature derived from Landsat Thematic Mapper data were used to create maps of fractional vegetation and surface soil moisture availability for the southern Nile delta in Egypt. These climatological variables were subsequently used to investigate the spatial distribution of the vector borne disease Bancroftian filariasis in the Nile delta where it is focally endemic and a growing problem. Averaged surface soil moisture values, computed for a 5-km border area around affected villages, were compared to filariasismore » prevalence rates. Prevalence rates were found to be negligible below a critical soil moisture value of 0.2, presumably because of a lack of appropriate breeding sites for the Culex Pipiens mosquito species. With appropriate modifications to account for local conditions and vector species, this approach should be useful as a means to map, predict, and control insect vector-borne diseases that critically depend on wet areas for propagation. This type of analysis may help governments and health agencies that are involved in filariasis control to better focus limited resources to identifiable high-risk areas.« less

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yang, Jian; He, Yuhong

2017-02-01

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.

Combined use of visible, reflected infrared, and thermal infrared images for mapping Hawaiian lava flows

NASA Technical Reports Server (NTRS)

Abrams, Michael; Abbott, Elsa; Kahle, Anne

1991-01-01

The weathering of Hawaiian basalts is accompanied by chemical and physical changes of the surfaces. These changes have been mapped using remote sensing data from the visible and reflected infrared and thermal infrared wavelength regions. They are related to the physical breakdown of surface chill coats, the development and erosion of silica coatings, the oxidation of mafic minerals, and the development of vegetation cover. These effects show systematic behavior with age and can be mapped using the image data and related to relative ages of pahoehoe and aa flows. The thermal data are sensitive to silica rind development and fine structure of the scene; the reflectance data show the degree of oxidation and differentiate vegetation from aa and cinders. Together, data from the two wavelength regions show more than either separately. The combined data potentially provide a powerful tool for mapping basalt flows in arid to semiarid volcanic environments.

Determining suitability of Large Aperture Scintillometer for validating remote sensing based evapotranspiration maps

NASA Astrophysics Data System (ADS)

Paul, G.; Gowda, P. H.; Howell, T. A.; Basu, S.; Colaizzi, P. D.; Marek, T.

2013-12-01

Scintillation method is a relatively new technique for measuring the sensible heat and water fluxes over land surfaces. Path integrating capabilities of scintillometer over heterogeneous landscapes make it a potential tool for comparing the energy fluxes derived from remote sensing based energy balance algorithms. For this reason, scintillometer-derived evapotranspiration (ET) fluxes are being used to evaluate remote sensing based energy balance algorithms for their ability to estimate ET fluxes. However, LAS' (Large Aperture Scintillometer) ability to derive ET fluxes is not thoroughly tested. The objective of this study was to evaluate LAS- and Surface Energy Balance System (SEBS)-derived fluxes against lysimetric data to determine LAS' suitability for validating remote sensing based evapotranspiration (ET) maps. The study was conducted during the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment - 2008 (BEAREX-08) at the USDA-ARS Conservation and Production Research Laboratory (CPRL), Bushland, Texas. SEBS was coded in a GIS environment to retrieve ET fluxes from the high resolution imageries acquired using airborne multispectral sensors. The CPRL has four large weighing lysimeters (3 m long x 3 m wide x 2.4 m deep), each located in the middle of approximately 5 ha fields, arranged in a block pattern. The two lysimeter fields located on the east (NE and SE) were managed under irrigated conditions, and the other two lysimeters on the west (NW and SW) were under dryland management. Each lysimeter field was equipped with an automated weather station that provided measurements for net radiation (Rn), Ts, soil heat flux (Go), Ta, relative humidity, and wind speed. During BEAREX08, the NE and SE fields were planted to cotton on May 21, and the NW and SW dryland lysimeters fields were planted to cotton on June 5. One LAS each was deployed across two large dryland lysimeter fields (NW and SW) and two large irrigated lysimeter fields (NE and SE). The structural parameter of refractive index of air was measured at 1-min interval and averaged at 15-min, and synchronized with weather station. The source area (footprint) of the surface energy fluxes were computed using a footprint model. ET fluxes were derived using LAS-estimated H as a residual from the energy balance equation. Comparison of SEBS- and LAS-derived ET fluxes were made against lysimetric data and performance of each method was discussed to determine the suitability of LAS for evaluating accuracy of remote sensing based ET maps.

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.

Spectroscopic remote sensing for material identification, vegetation characterization, and mapping

USGS Publications Warehouse

Kokaly, Raymond F.; Lewis, Paul E.; Shen, Sylvia S.

2012-01-01

Identifying materials by measuring and analyzing their reflectance spectra has been an important procedure in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow materials to be mapped across the landscape. With many existing airborne sensors and new satellite-borne sensors planned for the future, robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral feature analyses of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described. MICA is a module of the PRISM (Processing Routines in IDL for Spectroscopic Measurements) software, available to the public from the U.S. Geological Survey (USGS) at http://pubs.usgs.gov/of/2011/1155/. The core concepts of MICA include continuum removal and linear regression to compare key diagnostic absorption features in reference laboratory/field spectra and the spectra being analyzed. The reference spectra, diagnostic features, and threshold constraints are defined within a user-developed MICA command file (MCF). Building on several decades of experience in mineral mapping, a broadly-applicable MCF was developed to detect a set of minerals frequently occurring on the Earth's surface and applied to map minerals in the country-wide coverage of the 2007 Afghanistan HyMap data set. MICA has also been applied to detect sub-pixel oil contamination in marshes impacted by the Deepwater Horizon incident by discriminating the C-H absorption features in oil residues from background vegetation. These two recent examples demonstrate the utility of a spectroscopic approach to remote sensing for identifying and mapping the distributions of materials in imaging spectrometer data.

Remote magnetic navigation for mapping and ablating right ventricular outflow tract tachycardia.

PubMed

Thornton, Andrew S; Jordaens, Luc J

2006-06-01

Navigation, mapping, and ablation in the right ventricular outflow tract (RVOT) can be difficult. Catheter navigation using external magnetic fields may allow more accurate mapping and ablation. The purpose of this study was to assess the feasibility of RVOT tachycardia ablation using remote magnetic navigation. Mapping and ablation were performed in eight patients with outflow tract ventricular arrhythmias. Tachycardia mapping was undertaken with a 64-polar basket catheter, followed by remote activation and pace-mapping using a magnetically enabled catheter. The area of interest was localized on the basket catheter in seven patients in whom an RVOT arrhythmia was identified. Remote navigation of the magnetic catheter to this area was followed by pace-mapping. Ablation was performed at the site of perfect pace-mapping, with earliest activation if possible. Acute success was achieved in all patients (median four applications). Median procedural time was 144 minutes, with 13.4 minutes of patient fluoroscopy time and 3.8 minutes of physician fluoroscopy time. No complications occurred. One recurrence occurred during follow-up (mean 366 days). RVOT tachycardias can be mapped and ablated using remote magnetic navigation, initially guided by a basket catheter. Precise activation and pace-mapping are possible. Remote magnetic navigation permitted low fluoroscopy exposure for the physician. Long-term results are promising.

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.

Mapping the Distribution of Potential Land Drought in Batam Island Using the Integration of Remote Sensing and Geographic Information Systems (GIS)

NASA Astrophysics Data System (ADS)

Lubis, M. Z.; Taki, H. M.; Anurogo, W.; Pamungkas, D. S.; Wicaksono, P.; Aprilliyanti, T.

2017-12-01

Potential land drought mapping on Batam is needed to determine the distribution of areas that are very potential to the physical drought of the land. It is because the drought is always threatening on the long dry season. This research integrates remote sensing science with Geographic Information System (GIS). This research aims to map the distribution of land drought potential in Batam Island. The parameters used in this research are land use, Land Surface Temperature (LST), Potential dryness of land on the Batam island. The resulting map indicates the existence of five potential drought classes on the island of Batam. The area of very low drought potential is 2629.45 ha, mostly located in the Sungai Beduk sub-district. High drought potential with an area of 7081.39 ha is located in Sekupang sub-district. The distribution of very high land drought potential is in Batam city and Nongsa sub-district with area of 15600.12 ha. The coefficient of determination (R 2) is 0.6279. This indicates a strong positive relationship between field LST and modelled LST.

Exploring the Martian Highlands using a Rover-Deployed Ground Penetrating Radar

NASA Technical Reports Server (NTRS)

Grant, J. A.; Schutz, A. E.; Campbell, B. A.

2001-01-01

The Martian highlands record a long and often complex history of geologic activity that has shaped the planet over time. Results of geologic mapping and new data from the Mars Global Surveyor spacecraft reveal layered surfaces created by multiple processes that are often mantled by eolian deposits. Knowledge of the near-surface stratigraphy as it relates to evolution of surface morphology will provide critical context for interpreting rover/lander remote sensing data and for defining the geologic setting of a highland lander. Rover-deployed ground penetrating radar (GPR) can directly measure the range and character of in situ radar properties, thereby helping to constrain near-surface geology and structure. As is the case for most remote sensing instruments, a GPR may not detect water unambiguously on Mars. Nevertheless, any local, near-surface occurrence of liquid water will lead to large, easily detected dielectric contrasts. Moreover, definition of stratigraphy and setting will help in evaluating the history of aqueous activity and where any water might occur and be accessible. GPR data can also be used to infer the degree of any post-depositional pedogenic alteration or weathering, thereby enabling assessment of pristine versus secondary morphology. Most importantly perhaps, GPR can provide critical context for other rover and orbital instruments/data sets. Hence, rover-deployment of a GPR deployment should enable 3-D mapping of local stratigraphy and could guide subsurface sampling.

A GeoNode-Based Multiscale Platform For Management, Visualization And Integration Of DInSAR Data With Different Geospatial Information Sources

NASA Astrophysics Data System (ADS)

Buonanno, Sabatino; Fusco, Adele; Zeni, Giovanni; Manunta, Michele; Lanari, Riccardo

2017-04-01

This work describes the implementation of an efficient system for managing, viewing, analyzing and updating remotely sensed data, with special reference to Differential Interferometric Synthetic Aperture Radar (DInSAR) data. The DInSAR products measure Earth surface deformation both in space and time, producing deformation maps and time series[1,2]. The use of these data in research or operational contexts requires tools that have to handle temporal and spatial variability with high efficiency. For this aim we present an implementation based on Spatial Data Infrastructure (SDI) for data integration, management and interchange, by using standard protocols[3]. SDI tools provide access to static datasets that operate only with spatial variability . In this paper we use the open source project GeoNode as framework to extend SDI infrastructure functionalities to ingest very efficiently DInSAR deformation maps and deformation time series. GeoNode allows to realize comprehensive and distributed infrastructure, following the standards of the Open Geospatial Consortium, Inc. - OGC, for remote sensing data management, analysis and integration [4,5]. In the current paper we explain the methodology used for manage the data complexity and data integration using the opens source project GeoNode. The solution presented in this work for the ingestion of DinSAR products is a very promising starting point for future developments of the OGC compliant implementation of a semi-automatic remote sensing data processing chain . [1] Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E. (2002). A new Algorithm for Surface Deformation Monitoring based on Small Baseline Differential SAR Interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40, 11, pp. 2375-2383. [2] Lanari R., F. Casu, M. Manzo, G. Zeni,, P. Berardino, M. Manunta and A. Pepe (2007), An overview of the Small Baseline Subset Algorithm: a DInSAR Technique for Surface Deformation Analysis, P. Appl. Geophys., 164, doi: 10.1007/s00024-007-0192-9. [3] Nebert, D.D. (ed). 2000. Developing Spatial data Infrastructures: The SDI Cookbook. [4] Geonode (www.geonode.org) [5] Kolodziej, k. (ed). 2004. OGC OpenGIS Web Map Server Cookbook. Open Geospatial Consortium, 1.0.2 edition.

Application of remote sensor data to geologic analysis of the Bonanza test site, Colorado

NASA Technical Reports Server (NTRS)

Lee, K. (Compiler)

1972-01-01

A variety of remote sensor data has aided geologic mapping in central Colorado. This report summarizes the application of sensor data to both regional and local geologic mapping and presents some conclusions on the practical use of remote sensing for solving geologic mapping problems. It is emphasized that this study was not conducted primarily to test or evaluate remote sensing systems or data, but, rather, to apply sensor data as an accessory tool for geologic mapping. The remote sensor data used were acquired by the NASA Earth Observations Aircraft Program. Conclusions reached on the utility of the various sensor data and interpretation techniques for geologic mapping were by-products of attempts to use them.

Land Use and Land Cover (LULC) Change Detection in Islamabad and its Comparison with Capital Development Authority (CDA) 2006 Master Plan

NASA Astrophysics Data System (ADS)

Hasaan, Zahra

2016-07-01

Remote sensing is very useful for the production of land use and land cover statistics which can be beneficial to determine the distribution of land uses. Using remote sensing techniques to develop land use classification mapping is a convenient and detailed way to improve the selection of areas designed to agricultural, urban and/or industrial areas of a region. In Islamabad city and surrounding the land use has been changing, every day new developments (urban, industrial, commercial and agricultural) are emerging leading to decrease in vegetation cover. The purpose of this work was to develop the land use of Islamabad and its surrounding area that is an important natural resource. For this work the eCognition Developer 64 computer software was used to develop a land use classification using SPOT 5 image of year 2012. For image processing object-based classification technique was used and important land use features i.e. Vegetation cover, barren land, impervious surface, built up area and water bodies were extracted on the basis of object variation and compared the results with the CDA Master Plan. The great increase was found in built-up area and impervious surface area. On the other hand vegetation cover and barren area followed a declining trend. Accuracy assessment of classification yielded 92% accuracies of the final land cover land use maps. In addition these improved land cover/land use maps which are produced by remote sensing technique of class definition, meet the growing need of legend standardization.

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance

NASA Technical Reports Server (NTRS)

Eck, Thomas F.; Dye, Dennis G.

1991-01-01

A new satellite remote sensing method for estimating the amount of photosynthetically active radiation (PAR, 400-700 nm) incident at the earth's surface is described and tested. Potential incident PAR for clear sky conditions is computed from an existing spectral model. A major advantage of the UV approach over existing visible band approaches to estimating insolation is the improved ability to discriminate clouds from high-albedo background surfaces. UV spectral reflectance data from the Total Ozone Mapping Spectrometer (TOMS) were used to test the approach for three climatically distinct, midlatitude locations. Estimates of monthly total incident PAR from the satellite technique differed from values computed from ground-based pyranometer measurements by less than 6 percent. This UV remote sensing method can be applied to estimate PAR insolation over ocean and land surfaces which are free of ice and snow.

Method for identifying anomalous terrestrial heat flows

DOEpatents

Del Grande, Nancy Kerr

1977-01-25

A method for locating and mapping the magnitude and extent of terrestrial heat-flow anomalies from 5 to 50 times average with a tenfold improved sensitivity over orthodox applications of aerial temperature-sensing surveys as used for geothermal reconnaissance. The method remotely senses surface temperature anomalies such as occur from geothermal resources or oxidizing ore bodies by: measuring the spectral, spatial, statistical, thermal, and temporal features characterizing infrared radiation emitted by natural terrestrial surfaces; deriving from these measurements the true surface temperature with uncertainties as small as 0.05 to 0.5 K; removing effects related to natural temperature variations of topographic, hydrologic, or meteoric origin, the surface composition, detector noise, and atmospheric conditions; factoring out the ambient normal-surface temperature for non-thermally enhanced areas surveyed under otherwise identical environmental conditions; distinguishing significant residual temperature enhancements characteristic of anomalous heat flows and mapping the extent and magnitude of anomalous heat flows where they occur.

Laser remote sensing of an algal bloom in a freshwater reservoir

NASA Astrophysics Data System (ADS)

Grishin, M. Ya; Lednev, V. N.; Pershin, S. M.; Bunkin, A. F.; Kobylyanskiy, V. V.; Ermakov, S. A.; Kapustin, I. A.; Molkov, A. A.

2016-12-01

Laser remote sensing of an algal bloom in a freshwater reservoir on the Volga River in central Russia was carried out. The compact Raman lidar was installed on a small ship to probe the properties of the surface water layer in different typical regions of Gorky Water Reservoir. Elastic and Raman scattering as well as chlorophyll fluorescence were quantified, mapped and compared with data acquired by a commercial salinity, temperature and depth probe (STD probe) equipped with a blue-green algae sensor. Good correlation between lidar and STD measurements was established.

Feasibility of Using Remotely Sensed Data to Aid in Long-Term Monitoring of Biodiversity

NASA Technical Reports Server (NTRS)

Carroll, Mark L.; Brown, Molly E.; Elders, Akiko; Johnson, Kiersten

2014-01-01

Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.

Interactive Computer-Enhanced Remote Viewing System (ICERVS): Final report, November 1994--September 1996

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

NONE

1997-05-01

The Interactive Computer-Enhanced Remote Viewing System (ICERVS) is a software tool for complex three-dimensional (3-D) visualization and modeling. Its primary purpose is to facilitate the use of robotic and telerobotic systems in remote and/or hazardous environments, where spatial information is provided by 3-D mapping sensors. ICERVS provides a robust, interactive system for viewing sensor data in 3-D and combines this with interactive geometric modeling capabilities that allow an operator to construct CAD models to match the remote environment. Part I of this report traces the development of ICERVS through three evolutionary phases: (1) development of first-generation software to render orthogonalmore » view displays and wireframe models; (2) expansion of this software to include interactive viewpoint control, surface-shaded graphics, material (scalar and nonscalar) property data, cut/slice planes, color and visibility mapping, and generalized object models; (3) demonstration of ICERVS as a tool for the remediation of underground storage tanks (USTs) and the dismantlement of contaminated processing facilities. Part II of this report details the software design of ICERVS, with particular emphasis on its object-oriented architecture and user interface.« less

Multitemporal ALSM change detection, sediment delivery, and process mapping at an active earthflow

USGS Publications Warehouse

DeLong, Stephen B.; Prentice, Carol S.; Hilley, George E.; Ebert, Yael

2012-01-01

Remote mapping and measurement of surface processes at high spatial resolution is among the frontiers in Earth surface process research. Remote measurements that allow meter-scale mapping of landforms and quantification of landscape change can revolutionize the study of landscape evolution on human timescales. At Mill Gulch in northern California, USA, an active earthflow was surveyed in 2003 and 2007 by airborne laser swath mapping (ALSM), enabling meter-scale quantification of landscape change. We calculate four-year volumetric flux from the earthflow and compare it to long-term catchment average erosion rates from cosmogenic radionuclide inventories from adjacent watersheds. We also present detailed maps of changing features on the earthflow, from which we can derive velocity estimates and infer dominant process. These measurements rely on proper digital elevation model (DEM) generation and a simple surface-matching technique to align the multitemporal data in a manner that eliminates systematic error in either dataset. The mean surface elevation of the earthflow and an opposite slope that was directly influenced by the earthflow decreased 14 ± 1 mm/yr from 2003 to 2007. By making the conservative assumption that these features were the dominant contributor of sediment flux from the entire Mill Gulch drainage basin during this time interval, we calculate a minimum catchment-averaged erosion rate of 0·30 ± 0·02 mm/yr. Analysis of beryllium-10 (10Be) concentrations in fluvial sand from nearby Russian Gulch and the South Fork Gualala River provide catchment averaged erosion rates of 0·21 ± 0·04 and 0·23 ± 0·03 mm/yr respectively. From translated landscape features, we can infer surface velocities ranging from 0·5 m/yr in the wide upper ‘source’ portion of the flow to 5 m/yr in the narrow middle ‘transport’ portion of the flow. This study re-affirms the importance of mass wasting processes in the sediment budgets of uplifting weak lithologies.

Multicriteria analysis for sources of renewable energy using data from remote sensing

NASA Astrophysics Data System (ADS)

Matejicek, L.

2015-04-01

Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.

[Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

PubMed

Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

2006-08-01

In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Turner, A.K.; ,

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Toward irrigation retrieval by combining multi-sensor remote sensing data into a land surface model over a semi-arid region

NASA Astrophysics Data System (ADS)

Malbéteau, Y.; Lopez, O.; Houborg, R.; McCabe, M.

2017-12-01

Agriculture places considerable pressure on water resources, with the relationship between water availability and food production being critical for sustaining population growth. Monitoring water resources is particularly important in arid and semi-arid regions, where irrigation can represent up to 80% of the consumptive uses of water. In this context, it is necessary to optimize on-farm irrigation management by adjusting irrigation to crop water requirements throughout the growing season. However, in situ point measurements are not routinely available over extended areas and may not be representative at the field scale. Remote sensing approaches present as a cost-effective technique for mapping and monitoring broad areas. By taking advantage of multi-sensor remote sensing methodologies, such as those provided by MODIS, Landsat, Sentinel and Cubesats, we propose a new method to estimate irrigation input at pivot-scale. Here we explore the development of crop-water use estimates via these remote sensing data and integrate them into a land surface modeling framework, using a farm in Saudi Arabia as a demonstration of what can be achieved at larger scales.

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

NASA Astrophysics Data System (ADS)

Li, Nana; Jia, Li; Lu, Jing; Menenti, Massimo; Zhou, Jie

2017-01-01

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from -7 to -0.5 K in LST amplitude and from -300 to 300 J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.

Multidata remote sensing approach to regional geologic mapping in Venezuela

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

Baker, R.N.

1996-08-01

Remote Sensing played an important role in evaluating the exploration potential of selected lease blocks in Venezuela. Data sets used ranged from regional Landsat and airborne radar (SLAR) surveys to high-quality cloud-free air photos for local but largely inaccessible terrains. The resulting data base provided a framework for the conventional analyses of surface and subsurface information available to the project team. (1) Regional surface geology and major structural elements were interpreted from Landsat MSS imagery supplemented by TM and a regional 1:250,000 airborne radar (SLAR) survey. Evidence of dextral offset, en echelon folds and major thoroughgoing faults suggest a regionalmore » transpressional system modified by local extension and readjustment between small-scale crustal blocks. Surface expression of the major structural elements diminishes to the east, but can often be extended beneath the coastal plain by drainage anomalies and subtle geomorphic trends. (2) Environmental conditions were mapped using the high resolution airborne radar images which were used to relate vegetation types to surface texture and elevation; wetlands, outcrop and cultural features to image brightness. Additional work using multispectral TM or SPOT imagery is planned to more accurately define environmental conditions and provide a baseline for monitoring future trends. (3) Offshore oil seeps were detected using ERS-1 satellite radar (SAR) and known seeps in the Gulf of Paria as analogs. While partially successful, natural surfactants, wind shadow and a surprising variety of other phenomena created {open_quotes}false alarms{close_quotes} which required other supporting data and field sampling to verify the results. Key elements of the remote sensing analyses will be incorporated into a comprehensive geographic information (GIS) which will eventually include all of Venezuela.« less

The U.S. Geological Survey Land Remote Sensing Program

USGS Publications Warehouse

,

2003-01-01

In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.

Hyperspectral remote sensing exploration of carbonatite - an example from Epembe, Kunene region, Namibia

NASA Astrophysics Data System (ADS)

Zimmermann, Robert; Brandmeier, Melanie; Andreani, Louis; Gloaguen, Richard

2015-04-01

Remote sensing data can provide valuable information about ore deposits and their alteration zones at surface level. High spectral and spatial resolution of the data is essential for detailed mapping of mineral abundances and related structures. Carbonatites are well known for hosting economic enrichments in REE, Ta, Nb and P (Jones et al. 2013). These make them a preferential target for exploration for those critical elements. In this study we show how combining geomorphic, textural and spectral data improves classification result. We selected a site with a well-known occurrence in northern Namibia: the Epembe dyke. For analysis LANDSAT 8, SRTM and airborne hyperspectral (HyMap) data were chosen. The overlapping data allows a multi-scale and multi-resolution approach. Results from data analysis were validated during fieldwork in 2014. Data was corrected for atmospherical and geometrical effects. Image classification, mineral mapping and tectonic geomorphology allow a refinement of the geological map by lithological mapping in a second step. Detailed mineral abundance maps were computed using spectral unmixing techniques. These techniques are well suited to map abundances of carbonate minerals, but not to discriminate the carbonatite itself from surrounding rocks with similar spectral signatures. Thus, geometric indices were calculated using tectonic geomorphology and textures. For this purpose the TecDEM-toolbox (SHAHZAD & GLOAGUEN 2011) was applied to the SRTM-data for geomorphic analysis. Textural indices (e.g. uniformity, entropy, angular second moment) were derived from HyMap and SRTM by a grey-level co-occurrence matrix (CLAUSI 2002). The carbonatite in the study area is ridge-forming and shows a narrow linear feature in the textural bands. Spectral and geometric information were combined using kohonen Self-Organizing Maps (SOM) for unsupervised clustering. The resulting class spectra were visually compared and interpreted. Classes with similar signatures were merged according to geological context. The major conclusions are: 1. Carbonate minerals can be mapped using spectral unmixing techniques. 2. Carbonatites are associated with specific geometric pattern 3. The combination of spectral and geometric information improves classification result and reduces misclassification. References Clausi, D. A. (2002): An analysis of co-occurrence texture statistics as a function of grey-level quantization. - Canadian Journal of Remote Sensing, 28 (1), 45-62 Jones, A. P., Genge, M. and Carmody, L (2013): Carbonate Melts and Carbonatites. - Reviews in Mineralogy & Geochemistry, 75, 289-322 Shahzad, F. & Gloaguen, R. (2011): TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 2: Surface dynamics and basin analysis. - Computers and Geosciences, 37 (2), 261-271

An integrated approach for high spatial resolution mapping of water and carbon fluxes using multi-sensor data

USDA-ARS?s Scientific Manuscript database

In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a cor...

Soil moisture remote sensing: State of the science

USDA-ARS?s Scientific Manuscript database

Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac...

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.

Investigation of remote sensing techniques as inputs to operational resource management. [Butte County, Black Hills, South Dakota, Blackhawk Quadrangle, and Belle Fouche Basin

NASA Technical Reports Server (NTRS)

Schmer, F. A. (Principal Investigator); Isakson, R. E.; Eidenshink, J. C.

1977-01-01

The author has identified the following significant results. Visual interpretation of 1:125,000 color LANDSAT prints produced timely level 1 maps of accuracies in excess of 80% for agricultural land identification. Accurate classification of agricultural land via digital analysis of LANDSAT CCT's required precise timing of the date of data collection with mid to late June optimum for western South Dakota. The LANDSAT repetitive nine day cycle over the state allowed the surface areas of stockdams and small reservoir systems to be monitored to provide a timely approximation of surface water conditions on the range. Combined use of DIRS, K-class, and LANDSAT CCT's demonstrated the ability to produce aspen maps of greater detail and timeliness than was available using US Forest Service maps. Visual temporal analyses of LANDSAT imagery improved highway map drainage information and were used to prepare a seven county drainage network. An optimum map of flood-prone areas was developed, utilizing high altitude aerial photography and USGS maps.

Method based on artificial excitation of characteristic radiation by an electron beam for remote X-ray spectral elemental analysis of surface rocks on atmosphereless celestial bodies

NASA Astrophysics Data System (ADS)

Kolesnikov, E. K.

2016-11-01

This article, like our previous one [1], is devoted to advanced space technology concepts. It evaluates the potential for developing active systems to conduct a remote elemental analysis of surface rocks on an atmosphereless celestial body. The analysis is based on the spectrometry of characteristic X-rays (CXR) artificially excited in the surface soil layer. It has been proposed to use an electron beam injected from aboard a spacecraft orbiting the celestial body (or moving in a flyby trajectory) to excite the CXR elements contained in surface rocks. The focus is on specifying technical requirements to the parameters of payloads for a global mapping of the composition of lunar rocks from aboard of a low-orbiting lunar satellite. This article uses the results obtained in [2], our first study that shows the potential to develop an active system for a remote elemental analysis of lunar surface rocks using the above method. Although there has been interest in our research on the part of leading national academic institutions and space technology developers in the Soviet Union, the studies were discontinued because of the termination of the Soviet lunar program and the completion of the American Apollo program.

Remote sensing of land degradation: experiences from Latin America and the Caribbean.

PubMed

Metternicht, G; Zinck, J A; Blanco, P D; del Valle, H F

2010-01-01

Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

Synergistic use of optical and InSAR data for urban impervious surface mapping: A case study in Hong Kong

USGS Publications Warehouse

Jiang, L.; Liao, M.; Lin, H.; Yang, L.

2009-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning and watershed resource management, require accurate and up‐to‐date geospatial data of urban impervious surfaces. In this study, the potential of the synergistic use of optical and InSAR data in urban impervious surface mapping at the sub‐pixel level was investigated. A case study in Hong Kong was conducted for this purpose by applying a classification and regression tree (CART) algorithm to SPOT 5 multispectral imagery and ERS‐2 SAR data. Validated by reference data derived from high‐resolution colour‐infrared (CIR) aerial photographs, our results show that the addition of InSAR feature information can improve the estimation of impervious surface percentage (ISP) in comparison with using SPOT imagery alone. The improvement is especially notable in separating urban impervious surface from the vacant land/bare ground, which has been a difficult task in ISP modelling with optical remote sensing data. In addition, the results demonstrate the potential to map urban impervious surface by using InSAR data alone. This allows frequent monitoring of world's cities located in cloud‐prone and rainy areas.

Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2

USGS Publications Warehouse

Kokaly, Raymond F.; King, Trude V.V.; Hoefen, Todd M.

2013-01-01

This report presents a new version of surface mineral maps derived from HyMap imaging spectrometer data collected over Afghanistan in the fall of 2007. This report also describes the processing steps applied to the imaging spectrometer data. The 218 individual flight lines composing the Afghanistan dataset, covering more than 438,000 square kilometers, were georeferenced to a mosaic of orthorectified Landsat images. The HyMap data were converted from radiance to reflectance using a radiative transfer program in combination with ground-calibration sites and a network of cross-cutting calibration flight lines. The U.S. Geological Survey Material Identification and Characterization Algorithm (MICA) was used to generate two thematic maps of surface minerals: a map of iron-bearing minerals and other materials, which have their primary absorption features at the shorter wavelengths of the reflected solar wavelength range, and a map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials, which have their primary absorption features at the longer wavelengths of the reflected solar wavelength range. In contrast to the original version, version 2 of these maps is provided at full resolution of 23-meter pixel size. The thematic maps, MICA summary images, and the material fit and depth images are distributed in digital files linked to this report, in a format readable by remote sensing software and Geographic Information Systems (GIS). The digital files can be downloaded from http://pubs.usgs.gov/ds/787/downloads/.

Discovering the Ancient Maya from Space

NASA Technical Reports Server (NTRS)

Sever, T. L.

2008-01-01

The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Discovering the Ancient Maya From Space

NASA Technical Reports Server (NTRS)

Sever, T. L.

2007-01-01

The Peten region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use o f limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Assisting Groundwater Exploration for Refugee/IDP Camps by Remote Sensing and GIS

NASA Astrophysics Data System (ADS)

Wendt, Lorenz; Robl, Jörg; Hilberg, Sylke; Braun, Andreas; Rogenhofer, Edith; Dirnberger, Daniel; Strasser, Thomas; Füreder, Petra; Lang, Stefan

2015-04-01

Refugee camps and camps of internally displaced people (IDP) often form spontaneously or have to be established rapidly in remote, rural areas, where little is known about the hydrogeological situation. This requires a rapid assessment of the availability of groundwater to enable humanitarian organisations like Médecins Sans Frontières (MSF) to supply the camp population with sufficient potable water. Within the project EO4HumEn, hydrogeological reconnaissance maps are produced for MSF by integrating remote sensing data like SRTM, Landsat, ASTER, optical very-high resolution (VHR) imagery, and SAR data. Depending on the specific situation of the camps, these maps contain topography, permanent and temporary water bodies, hard rock outcrops and their geological variability, locations of existing boreholes and wells (if available), potential contamination sources, roads and obstacles (e.g. swampland). In areas characterized by unconsolidated sediments, specific landforms like alluvial fans, meanders, levees, deltas or beach ridges are identified. Here, the reconnaissance map can be sufficient to plan drill sites for groundwater abstraction. In hard rock areas, the lithology is determined, if the vegetation cover allows it. Fractures, faults and karst features are mapped to resolve the structural setting. Anomalous vegetation patterns are interpreted in terms of near-surface groundwater. The maps provide an overview of the camp surroundings, and allow the field hydrogeologists to focus their investigations on the most promising locations. The maps are complemented by a literature review on geological maps, articles and reports available for the area of interest. Assisting groundwater exploration by remote sensing data analysis is not a new development, but it has not been widely adopted by the humanitarian community as interfaces between humanitarian organisations and GI-scientists were missing. EO4HumEn fills this gap by a strong interdisciplinary cooperation between MSF, GI-scientists and geologists. This allows exploiting the potential of remote sensing and in particular of the freely available datasets (SRTM, Landsat, Sentinel 1+2) for the water supply of refugee/IDP camps, and to receive feedback on the validity of the delivered map products. EO4HumEn is funded by the Austrian Research Promotion Agency (EO-based services to support humanitarian operations: monitoring population and natural resources in refugee/IDP camps; FFG, ASAP 9, Nr 840081). Besides hydrogeological assessments, further products and services developed in EO4HumEn comprise the estimation and monitoring of camp population numbers by semi-automatically extracting dwellings from VHR imagery using object-based image analysis (OBIA), and the monitoring of changes of the environment in the vicinity of camps.

Integrating Statistical and Expert Knowledge to Develop Phenoregions for the Continental United States

NASA Astrophysics Data System (ADS)

Hoffman, F. M.; Kumar, J.; Hargrove, W. W.

2013-12-01

Vegetated ecosystems typically exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and storm disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution to develop phenological signatures of emergent ecological regimes called phenoregions. By applying a unsupervised, quantitative data mining technique to NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. Utilizing spatial overlays with multiple expert-derived maps, this "label-stealing"' technique exploits the knowledge contained in a collection of maps to identify biome characteristics of our statistically derived phenoregions. Generalized land cover maps were produced by combining phenoregions according to their degree of spatial coincidence with expert-developed land cover or biome regions. Goodness-of-fit maps, which show the strength the spatial correspondence, were also generated.

Mesoscale Turbulence in the Ocean and Synergy of Variables: Merging of Smos and Aquarius SSS Maps Using New, Non-Parametric Methods

NASA Astrophysics Data System (ADS)

Turiel, A.; Umbert, M.; Hoareau, N.; Ballabrera-Poy, J.; Font, J.

2012-12-01

Remote sensing platforms onboard satellites provide synoptic maps of ocean surface and thus an accurate picture of many processes taking place in the ocean at mesoscale and sub-mesoscale levels mainly can be gained. Since the first ocean observation satellites these images has been exploited to assess ocean processes; however, extracting further dynamic information from remote sensing maps generally implies a higher degree of processing complexity, involving the use of numerical models and assimilation schemes. A critical variable for the understanding the climate system is Sea Surface Salinity (SSS). The arrival of SMOS and Aquarius missions has given us access to SSS in a regular basis. However, those images still suffer of many acquisition and processing issues, what precludes gaining a complete picture of ocean surface dynamics. In order to favor the oceanographic exploitation of SMOS and Aquarius maps new filtering schemes need to be devised. During the last years a new branch of image processing techniques applied to ocean observation has arisen with force, namely multiscale/multifractal analysis. Different scalars submitted to the action of the ocean flow develop an identical inner structure (multifractal structure) that can be revealed by means of the appropriate analysis tools (singularity analysis). These tools allow for instance to characterize surface currents from snapshots of different scalars (Turiel et al, Ocean Sciences, 2009). In this work we go further away, with the introduction of a new method to blend different types of scalar in a single map of improved quality. The method does not imply the introduction of any parameter, nor relies in any numerical model, but in the assumption that the action of the oceanic flow leads to the same multifractal structure in any ocean variable. The method allows, for instance, to use the multifractal structure coming from SST images to improve the quality of SSS maps (as illustrated in the figure). It can also be applied to merge SMOS and Aquarius maps to increase the quality and spatial coverage.; Top row: 10-day MW SST (left), SMOS SSS (middle), and SSS resulting from fusing SST singularities (right). Bottom row: Associated singularity exponents. Brighter colors are associated to most singular (i.e., negative) exponents.

Towards a High-Resolution Global Inundation Delineation Dataset

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.

2011-12-01

Although their importance for biodiversity, flow regulation and ecosystem service provision is widely recognized, wetlands and temporarily inundated landscapes remain poorly mapped globally because of their inherent elusive nature. Inventorying of wetland resources has been identified in international agreements as an essential component of appropriate conservation efforts and management initiatives of these threatened ecosystems. However, despite recent advances in remote sensing surface water monitoring, current inventories of surface water variations remain incomplete at the regional-to-global scale due to methodological limitations restricting truly global application. Remote sensing wetland applications such as SAR L-band are particularly constrained by image availability and heterogeneity of acquisition dates, while coarse resolution passive microwave and multi-sensor methods cannot discriminate distinct surface water bodies. As a result, the most popular global wetland dataset remains to this day the Global Lake & Wetland Database (Lehner and Doll, 2004) a spatially inconsistent database assembled from various existing data sources. The approach taken in this project circumvents the limitations of current global wetland monitoring methods by combining globally available topographic and hydrographic data to downscale coarse resolution global inundation data (Prigent et al., 2007) and thus create a superior inundation delineation map product. The developed procedure downscales inundation data from the coarse resolution (~27km) of current passive microwave sensors to the finer spatial resolution (~500m) of the topographic and hydrographic layers of HydroSHEDS' data suite (Lehner et al., 2006), while retaining the high temporal resolution of the multi-sensor inundation dataset. From the downscaling process emerges new information on the specific location of inundation, but also on its frequency and duration. The downscaling algorithm employs a decision tree classifier trained on regional remote sensing wetland maps, to derive inundation probability followed by a seeded region growing segmentation process to redistribute the inundated area at the finer resolution. Assessment of the algorithm's performance is accomplished by evaluating the level of agreement between its outputted downscaled inundation maps and existing regional remote sensing inundation delineation. Upon completion, this project's will offer a dynamic globally seamless inundation map at an unprecedented spatial and temporal scale, which will provide the baseline inventory long requested by the research community, and will open the door to a wide array of possible conservation and hydrological modeling applications which were until now data-restricted. Literature Lehner, B., K. Verdin, and A. Jarvis. 2008. New global hydrography derived from spaceborne elevation data. Eos 89, no. 10. Lehner, B, and P Doll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296, no. 1-4: 1-22. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews. 2007. Global inundation dynamics inferred from multiple satellite observations, 1993-2000. Journal of Geophysical Research 112, no. D12: 1-13.

Novel robotic catheter manipulation system integrated with remote magnetic navigation for fully remote ablation of atrial tachyarrhythmias: a two-centre evaluation.

PubMed

Nölker, Georg; Gutleben, Klaus-Jürgen; Muntean, Bogdan; Vogt, Jürgen; Horstkotte, Dieter; Dabiri Abkenari, Lara; Akca, Ferdi; Szili-Torok, Tamas

2012-12-01

Studies have shown that remote magnetic navigation is safe and effective for ablation of atrial arrhythmias, although optimal outcomes often require frequent manual manipulation of a circular mapping catheter. The Vdrive robotic system ('Vdrive') was designed for remote navigation of circular mapping catheters to enable a fully remote procedure. This study details the first human clinical experience with remote circular catheter manipulation in the left atrium. This was a prospective, multi-centre, non-randomized consecutive case series that included patients presenting for catheter ablation of left atrial arrhythmias. Remote systems were used exclusively to manipulate both the circular mapping catheter and the ablation catheter. Patients were followed through hospital discharge. Ninety-four patients were included in the study, including 23 with paroxysmal atrial fibrillation (AF), 48 with persistent AF, and 15 suffering from atrial tachycardias. The population was predominately male (77%) with a mean age of 60.5 ± 11.7 years. The Vdrive was used for remote navigation between veins, creation of chamber maps, and gap identification with segmental isolation. The intended acute clinical endpoints were achieved in 100% of patients. Mean case time was 225.9 ± 70.5 min. Three patients (3.2%) crossed over to manual circular mapping catheter navigation. There were no adverse events related to the use of the remote manipulation system. The results of this study demonstrate that remote manipulation of a circular mapping catheter in the ablation of atrial arrhythmias is feasible and safe. Prospective randomized studies are needed to prove efficiency improvements over manual techniques.

Geology of the Shakespeare quadrangle (H03), Mercury

NASA Astrophysics Data System (ADS)

Guzzetta, L.; Galluzzi, V.; Ferranti, L.; Palumbo, P.

2017-09-01

A 1:3M geological map of the H03 Shakespeare quadrangle of Mercury has been compiled through photointerpretation of the remotely sensed images of the NASA MESSENGER mission. This quadrangle is characterized by the occurrence of three main types of plains materials and four basin materials, pertaining to the Caloris basin, the largest impact crater on Mercury's surface. The geologic boundaries have been redefined compared to the previous 1:5M map of the quadrangle and the craters have been classified privileging their stratigraphic order rather than morphological appearance. The abundant tectonic landforms have been interpreted and mapped as thrusts or wrinkle ridges.

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.

Mineralogical Composition and Potential Dust Source of Playas in the Western U.S. and Australia as Remotely Identified Through Imaging Spectroscopy.

NASA Astrophysics Data System (ADS)

Raming, L. W.; Farrand, W. H.; Bowen, B.

2015-12-01

Playas are significant dust sources and as a result are potentially hazardous to human health. The composition of the dust is a function of the mineralogical content of the playa and associated brines. Playas are found in arid climates globally, however they are challenging to map geologically as they are often hard to access, have subtle variations in mineralogy, and are topographically featureless. This study uses remote sensing in the form of imaging spectroscopy to map the mineralogical composition of five playas from different geologic settings: Railroad Valley Playa, Nevada, USA; Bonneville Salt Flats, Utah, USA; White Sands National Monument, New Mexico, USA; Lake Brown, Western Australia, Australia; and Lake Tyrrell, Victoria, Australia.Multiple spectrometers were used for this study; these include the multispectral sensor ASTER, and the hyperspectral sensors AVIRIS, HICO, and HyMap. All scenes were processed in ENVI and corrected to at surface reflectance using FLAASH, QUAC or Empirical Line methods. Minerals were identified through a standard end-member extraction approach and mapped using multi-range spectral feature fitting and other methods. Additionally, remote data are combined with in-situ field-based spectra and sample-based laboratory spectra.Initial results suggest various and differing mineralogy between playas. The most abundant mineralogy includes clay minerals such as illite and montmorillonite and evaporites such as gypsum. Additionally there has been identification of Fe absorption bands in the visible / near infrared at White Sands National Monument, and Lake Brown and Lake Tyrell, suggesting the presence of iron bearing minerals. Further research will provide a more comprehensive list of minerals identified by absorption features as related to specific sensors. Collectively, these analyses will be used characterize overall patterns in playa surface mineralogy and to evaluate the parameters that influence playa dust source composition.

Monitoring Drought at Continental Scales Using Thermal Remote Sensing of Evapotranspiration (Invited)

NASA Astrophysics Data System (ADS)

Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.

2009-12-01

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for assessing standard meteorologically-based drought indicators, and may be more robust in regions with limited monitoring networks. In this study, monthly maps of ESI anomalies for 2000-2008 are compared to standard drought indices and to drought classifications in the U.S. Drought Monitor. The ESI shows better skill in ranking drought severity than do precipitation-based indices composited over comparable time intervals. The thermal remote sensing inputs to ALEXI detect drought conditions even under the dense forest cover along the East Coast of the United States, where microwave soil moisture retrievals typically lose sensitivity. On the other hand, microwave observations are not constrained by cloud cover and provide better temporal continuity, but typically at significantly lower spatial resolution. A merged TIR-microwave moisture anomaly product may have potential for optimizing both spatial and temporal coverage in continental-scale drought monitoring.

C-band RISAT-1 imagery for geospatial mapping of cryospheric surface features in the Antarctic environment

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Panditrao, Satej N.; Luis, Alvarinho J.

2016-05-01

Cryospheric surface feature classification is one of the widely used applications in the field of polar remote sensing. Precise surface feature maps derived from remotely sensed imageries are the major requirement for many geoscientific applications in polar regions. The present study explores the capabilities of C-band dual polarimetric (HH & HV) SAR imagery from Indian Radar Imaging Satellite (RISAT-1) for land cryospheric surface feature mapping. The study areas selected for the present task were Larsemann Hills and Schirmacher Oasis, East Antarctica. RISAT-1 Fine Resolution STRIPMAP (FRS-1) mode data with 3-m spatial resolution was used in the present research attempt. In order to provide additional context to the amount of information in dual polarized RISAT-1 SAR data, a band HH+HV was introduced to make use of the original two polarizations. In addition to the data calibration, transformed divergence (TD) procedure was performed for class separability analysis to evaluate the quality of the statistics before image classification. For most of the class pairs the TD values were comparable, which indicated that the classes have good separability. Fuzzy and Artificial Neural Network classifiers were implemented and accuracy was checked. Nonparametric classifier Support Vector Machine (SVM) was also used to classify RISAT-1 data with an optimized polarization combination into three land-cover classes consisting of sea ice/snow/ice, rocks/landmass, and lakes/waterbodies. This study demonstrates that C-band FRS1 image mode data from the RISAT-1 mission can be exploited to identify, map and monitor land cover features in the polar regions, even during dark winter period. For better landcover classification and analysis, hybrid polarimetric data (cFRS-1 mode) from RISAT-1, which incorporates phase information, unlike the dual-pol linear (HH, HV) can be used for obtaining better polarization signatures.

Using Remotely Sensed Data to Map Urban Vulnerability to Heat

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2010-01-01

This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.

Integration of remote sensing and geographic information systems for Great Lakes water quality monitoring

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

Lathrop, R.G. Jr.

1988-01-01

The utility of three operational satellite remote sensing systems, namely, the Landsat Thematic Mapper (TM), the SPOT High Resolution Visible (HRV) sensors and the NOAA Advanced Very High Resolution Radiometer (AVHRR), were evaluated as a means of estimating water quality and surface temperature. Empirical calibration through linear regression techniques was used to relate near-simultaneously acquired satellite radiance/reflectance data and water quality observations obtained in Green Bay and the nearshore waters of Lake Michigan. Four dates of TM and one date each of SPOT and AVHRR imagery/surface reference data were acquired and analyzed. Highly significant relationships were identified between the TMmore » and SPOT data and secchi disk depth, nephelometric turbidity, chlorophyll a, total suspended solids (TSS), absorbance, and surface temperature (TM only). The AVHRR data were not analyzed independently but were used for comparison with the TM data. Calibrated water quality image maps were input to a PC-based raster GIS package, EPPL7. Pattern interpretation and spatial analysis techniques were used to document the circulation dynamics and model mixing processes in Green Bay. A GIS facilitates the retrieval, query and spatial analysis of mapped information and provides the framework for an integrated operational monitoring system for the Great Lakes.« less

High-resolution, real-time mapping of surface soil moisture at the field scale using ground penetrating radar

NASA Astrophysics Data System (ADS)

Lambot, S.; Minet, J.; Slob, E.; Vereecken, H.; Vanclooster, M.

2008-12-01

Measuring soil surface water content is essential in hydrology and agriculture as this variable controls important key processes of the hydrological cycle such as infiltration, runoff, evaporation, and energy exchanges between the earth and the atmosphere. We present a ground-penetrating radar (GPR) method for automated, high-resolution, real-time mapping of soil surface dielectric permittivity and correlated water content at the field scale. Field scale characterization and monitoring is not only necessary for field scale management applications, but also for unravelling upscaling issues in hydrology and bridging the scale gap between local measurements and remote sensing. In particular, such methods are necessary to validate and improve remote sensing data products. The radar system consists of a vector network analyzer combined with an off-ground, ultra-wideband monostatic horn antenna, thereby setting up a continuous-wave steeped-frequency GPR. Radar signal analysis is based on three-dimensional electromagnetic inverse modelling. The forward model accounts for all antenna effects, antenna-soil interactions, and wave propagation in three-dimensional multilayered media. A fast procedure was developed to evaluate the involved Green's function, resulting from a singular, complex integral. Radar data inversion is focused on the surface reflection in the time domain. The method presents considerable advantages compared to the current surface characterization methods using GPR, namely, the ground wave and common reflection methods. Theoretical analyses were performed, dealing with the effects of electric conductivity on the surface reflection when non-negligible, and on near-surface layering, which may lead to unrealistic values for the surface dielectric permittivity if not properly accounted for. Inversion strategies are proposed. In particular the combination of GPR with electromagnetic induction data appears to be promising to deal with highly conductive soils. Finally, we present laboratory and field results where the GPR measurements are compared to ground-truth gravimetric and time domain reflectometry data. An example of high resolution surface soil moisture map is presented and discussed. The proposed method appears to be an appropriate solution in any applications where soil surface water content must be known at the field scale.

Dust transport over the eastern Mediterranean derived from Total Ozone Mapping Spectrometer, Aerosol Robotic Network, and surface measurements

NASA Astrophysics Data System (ADS)

Kalivitis, N.; Gerasopoulos, E.; Vrekoussis, M.; Kouvarakis, G.; Kubilay, N.; Hatzianastassiou, N.; Vardavas, I.; Mihalopoulos, N.

2007-02-01

Multiyear surface PM10 measurements performed on Crete Island, Greece, have been used in conjunction with satellite (Total Ozone Mapping Spectrometer (TOMS)) and ground-based remote sensing measurements (Aerosol Robotic Network (AERONET)) to enhance our understanding of the evolution of mineral dust events over the eastern Mediterranean. An analysis of southerly air masses at altitudes of 1000 and 3000 m over a 5 year period (2000-2005), showed that dust can potentially arrive over Crete, either simultaneously in the lower free troposphere and inside the boundary layer (vertical extended transport (VET)) or initially into the free troposphere with the heavier particles gradually being scavenged inside the boundary layer (free troposphere transport (FTT)). Both pathways present significant seasonal variations but on an annual basis contribute almost equally to the dust transport in the area. During VET the aerosol index (AI) derived from TOMS was significantly correlated with surface PM10, and in general AI was found to be adequate for the characterization of dust loadings over the eastern Mediterranean on a climatological basis. A significant covariance between PM10 and AOT was observed during VET as well, indicating that AOT levels from AERONET may be estimated by PM10 levels at the surface. Surface measurements are thus crucial for the validation of remote sensing measurements and hence are a powerful tool for the investigation of the impact of aerosols on climate.

Tracking lava flow emplacement on the east rift zone of Kilauea, Hawai’i with synthetic aperture radar (SAR) coherence

USGS Publications Warehouse

Dietterich, Hannah R.; Poland, Michael P.; Schmidt, David; Cashman, Katharine V.; Sherrod, David R.; Espinosa, Arkin Tapia

2012-01-01

Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu‘u ‘Ō‘ō-Kupaianaha eruption at Kīlauea, Hawai‘i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post-emplacement flow subsidence.

Tracking lava flow emplacement on the east rift zone of Kīlauea, Hawai‘i, with synthetic aperture radar coherence

NASA Astrophysics Data System (ADS)

Dietterich, Hannah R.; Poland, Michael P.; Schmidt, David A.; Cashman, Katharine V.; Sherrod, David R.; Espinosa, Arkin Tapia

2012-05-01

Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu`u `Ō`ō-Kupaianaha eruption at Kīlauea, Hawai`i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post-emplacement flow subsidence.

Remote sensing the sea surface CO2 of the Baltic Sea using the SOMLO methodology

NASA Astrophysics Data System (ADS)

Parard, G.; Charantonis, A. A.; Rutgerson, A.

2015-06-01

Studies of coastal seas in Europe have noted the high variability of the CO2 system. This high variability, generated by the complex mechanisms driving the CO2 fluxes, complicates the accurate estimation of these mechanisms. This is particularly pronounced in the Baltic Sea, where the mechanisms driving the fluxes have not been characterized in as much detail as in the open oceans. In addition, the joint availability of in situ measurements of CO2 and of sea-surface satellite data is limited in the area. In this paper, we used the SOMLO (self-organizing multiple linear output; Sasse et al., 2013) methodology, which combines two existing methods (i.e. self-organizing maps and multiple linear regression) to estimate the ocean surface partial pressure of CO2 (pCO2) in the Baltic Sea from the remotely sensed sea surface temperature, chlorophyll, coloured dissolved organic matter, net primary production, and mixed-layer depth. The outputs of this research have a horizontal resolution of 4 km and cover the 1998-2011 period. These outputs give a monthly map of the Baltic Sea at a very fine spatial resolution. The reconstructed pCO2 values over the validation data set have a correlation of 0.93 with the in situ measurements and a root mean square error of 36 μatm. Removing any of the satellite parameters degraded this reconstructed CO2 flux, so we chose to supply any missing data using statistical imputation. The pCO2 maps produced using this method also provide a confidence level of the reconstruction at each grid point. The results obtained are encouraging given the sparsity of available data, and we expect to be able to produce even more accurate reconstructions in coming years, given the predicted acquisition of new data.

Into the third dimension: Benefits of incorporating LiDAR data in wildlife habitat models

Treesearch

Melissa J. Merrick; John L. Koprowski; Craig Wilcox

2013-01-01

LiDAR (Light detection and ranging) is a tool with potential for characterizing wildlife habitat by providing detailed, three-dimensional landscape information not available from other remote sensing applications. The ability to accurately map structural components such as canopy height, canopy cover, woody debris, tree density, and ground surface has potential to...

An airborne laser fluorosensor for the detection of oil on water

NASA Technical Reports Server (NTRS)

Kim, H. H.; Hickman, G. D.

1973-01-01

The successful operation of an airborne laser fluorosensor system is reported that makes it possible to detect and map surface oil, either of natural-seepage or spill origin, on large bodies of water. Preliminary results indicate that the sensitivity of the instrument exceeds that of conventional passive remote sensors currently available for oil spill detection.

Remote Sensing of Surficial Process Responses to Extreme Meteorological Events

NASA Technical Reports Server (NTRS)

Brakenridge, G. Robert

1997-01-01

Changes in the frequency and magnitude of extreme meteorological events are associated with changing environmental means. Such events are important in human affairs, and can also be investigated by orbital remote sensing. During the course of this project, we applied ERS-1, ERS-2, Radarsat, and an airborne sensor (AIRSAR-TOPSAR) to measure flood extents, flood water surface profiles, and flood depths. We established a World Wide Web site (the Dartmouth Flood Observatory) for publishing remote sensing-based maps of contemporary floods worldwide; this is also an online "active archive" that presently constitutes the only global compilation of extreme flood events. We prepared an article for EOS concerning SAR imaging of the Mississippi Valley flood; an article for the International Journal of Remote Sensing on measurement of a river flood wave using ERS-2, began work on an article (since completed and published) on the Flood Observatory for a Geoscience Information Society Proceedings volume, and presented lectures at several Geol. Soc. of America Natl. Meetings, an Assoc. of Amer. Geographers Natl. Meeting, and a Binghamton Geomorphology Symposium (all on SAR remote sensing of the Mississippi Valley flood). We expanded in-house modeling capabilities by installing the latest version of the Army Corps of Engineers RMA two-dimensional hydraulics software and BYU Engineering Graphics Lab's Surface Water Modeling System (finite elements based pre- and post-processors for RMA work) and also added watershed modeling software. We are presently comparing the results of the 2-d flow models with SAR image data. The grant also supported several important upgrades of pc-based remote sensing infrastructure at Dartmouth. During work on this grant, we collaborated with several workers at the U.S. Army Corps of Engineers, Remote Sensing/GIS laboratory (for flood inundation mapping and modeling; particularly of the Illinois River using the AIRSAR/TOPSAR/ERS-2 combined data), with Dr. Karen Prestegaard at the University of Maryland (geomorphological responses to the extreme 1993 flood along the Raccoon drainage in central Iowa), and with Mr Tim Scrom of the Albany National Weather Service River Forecast Center (initial planning for the use of Radarsat and ERS-2 for flood warning). The work thus initiated with this proposal is continuing.

Improving alpine-region spectral unmixing with optimal-fit snow endmembers

NASA Technical Reports Server (NTRS)

Painter, Thomas H.; Roberts, Dar A.; Green, Robert O.; Dozier, Jeff

1995-01-01

Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data.

Semi-automated surface mapping via unsupervised classification

NASA Astrophysics Data System (ADS)

D'Amore, M.; Le Scaon, R.; Helbert, J.; Maturilli, A.

2017-09-01

Due to the increasing volume of the returned data from space mission, the human search for correlation and identification of interesting features becomes more and more unfeasible. Statistical extraction of features via machine learning methods will increase the scientific output of remote sensing missions and aid the discovery of yet unknown feature hidden in dataset. Those methods exploit algorithm trained on features from multiple instrument, returning classification maps that explore intra-dataset correlation, allowing for the discovery of unknown features. We present two applications, one for Mercury and one for Vesta.

Surface inspection using FTIR spectroscopy

NASA Technical Reports Server (NTRS)

Powell, G. L.; Smyrl, N. R.; Williams, D. M.; Meyers, H. M., III; Barber, T. E.; Marrero-Rivera, M.

1995-01-01

The use of reflectance Fourier transform infrared (FTIR) spectroscopy as a tool for surface inspection is described. Laboratory instruments and portable instruments can support remote sensing probes that can map chemical contaminants on surfaces with detection limits under the best of conditions in the sub-nanometer range, i.e.. near absolute cleanliness, excellent performance in the sub-micrometer range, and useful performance for films tens of microns thick. Examples of discovering and quantifying contamination such as mineral oils and greases, vegetable oils, and silicone oils on aluminum foil, galvanized sheet steel, smooth aluminum tubing, and sandblasted 7075 aluminum alloy and D6AC steel. The ability to map in time and space the distribution of oil stains on metals is demonstrated. Techniques associated with quantitatively applying oils to metals, subsequently verifying the application, and non-linear relationships between reflectance and the quantity oil are described.

Sensitivity of thermal inertia calculations to variations in environmental factors. [in mapping of Earth's surface by remote sensing

NASA Technical Reports Server (NTRS)

Kahle, A. B.; Alley, R. E.; Schieldge, J. P.

1984-01-01

The sensitivity of thermal inertia (TI) calculations to errors in the measurement or parameterization of a number of environmental factors is considered here. The factors include effects of radiative transfer in the atmosphere, surface albedo and emissivity, variations in surface turbulent heat flux density, cloud cover, vegetative cover, and topography. The error analysis is based upon data from the Heat Capacity Mapping Mission (HCMM) satellite for July 1978 at three separate test sites in the deserts of the western United States. Results show that typical errors in atmospheric radiative transfer, cloud cover, and vegetative cover can individually cause root-mean-square (RMS) errors of about 10 percent (with atmospheric effects sometimes as large as 30-40 percent) in HCMM-derived thermal inertia images of 20,000-200,000 pixels.

Remote-sensing applications as utilized in Florida's coastal zone management program

NASA Technical Reports Server (NTRS)

Worley, D. R.

1975-01-01

Land use maps were developed from photomaps obtained by remote sensing in order to develop a comprehensive state plan for the protection, development, and zoning of coastal regions. Only photographic remote sensors have been used in support of the coastal council's planning/management methodology. Standard photointerpretation and cartographic application procedures for map compilation were used in preparing base maps.

Remote sensing of potential lunar resources. I - Near-side compositional properties

NASA Technical Reports Server (NTRS)

Johnson, Jeffrey R.; Larson, Stephen M.; Singer, Robert B.

1991-01-01

Using telescopic CCD multispectral images of the lunar near side and the results of 330-870 nm spectroscopy of selected regions, the compositional differences relevant to the locations of potential lunar resources (such as ilmenite, FeTiO3, and solar-wind-implanted He-3 and H) are estimated. The 400/560 nm CCD ratio images were converted to weight percent TiO2, and the values were used to construct a new TiO2 abundance map which can be used to estimate the areas potentially rich in ilmenite. A 950/560 nm CCD ratio mosaic of the full moon provides estimates of relative surface maturity. Since high He-3 concentrations correlate with mature ilmenite-rich soils, a combination of relative surface maturity maps and the TiO2 abundance maps can be used to estimate distributions of He-3 (and possibly H) on local scales.

COSMO-SkyMed and GIS applications

NASA Astrophysics Data System (ADS)

Milillo, Pietro; Sole, Aurelia; Serio, Carmine

2013-04-01

Geographic Information Systems (GIS) and Remote Sensing have become key technology tools for the collection, storage and analysis of spatially referenced data. Industries that utilise these spatial technologies include agriculture, forestry, mining, market research as well as the environmental analysis . Synthetic Aperture Radar (SAR) is a coherent active sensor operating in the microwave band which exploits relative motion between antenna and target in order to obtain a finer spatial resolution in the flight direction exploiting the Doppler effect. SAR have wide applications in Remote Sensing such as cartography, surface deformation detection, forest cover mapping, urban planning, disasters monitoring , surveillance etc… The utilization of satellite remote sensing and GIS technology for this applications has proven to be a powerful and effective tool for environmental monitoring. Remote sensing techniques are often less costly and time-consuming for large geographic areas compared to conventional methods, moreover GIS technology provides a flexible environment for, analyzing and displaying digital data from various sources necessary for classification, change detection and database development. The aim of this work si to illustrate the potential of COSMO-SkyMed data and SAR applications in a GIS environment, in particular a demostration of the operational use of COSMO-SkyMed SAR data and GIS in real cases will be provided for what concern DEM validation, river basin estimation, flood mapping and landslide monitoring.

Mapping the surface characteristics of the Mojave with remote sensing for terrestrial habitat modeling

NASA Astrophysics Data System (ADS)

Nowicki, S. A.; Skuse, R. J.

2012-12-01

High-resolution ecological and climate modeling requires quantification of surface characteristics such as rock abundance, soil induration and surface roughness at fine-scale, since these features can affect the micro and macro habitat of a given area and ultimately determine the assemblage of plant and animal species that may occur there. Our objective is to develop quantitative data layers of thermophysical properties of the entire Mojave Desert Ecoregion for applications to habitat modeling being conducted by the USGS Western Ecological Research Center. These research efforts are focused on developing habitat models and a better physical understanding of the Mojave Desert, which have implications the development of solar and wind energy resources, military installation expansion and residential development planned for the Mojave. Thus there is a need to improve our understanding of the mechanical composition and thermal characteristics of natural and modified surfaces in the southwestern US at as high-resolution as possible. Since the Mojave is a sparsely-vegetated, arid landscape with little precipitation, remote sensing-based thermophysical analyses using Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) day and nighttime imagery are ideal for determining the physical properties of the surface. New mosaicking techniques for thermal imagery acquired at different dates, seasons and temperatures have allowed for the highest-resolution mosaics yet generated at 100m/pixel for thermal infrared wavelengths. Among our contributions is the development of seamless day and night ASTER mosaics of land surface temperatures that are calibrated to Moderate Resolution Imaging Spectroradiometer (MODIS) coincident observations to produce both a seamless mosaic and quantitative temperatures across the region that varies spectrally and thermophysically over a large number of orbit tracks. Products derived from this dataset include surface rock abundance, apparent thermal inertia, and diurnal/seasonal thermal regime. Additionally, the combination of moderate and high-resolution thermal observations are used to map the spatial and temporal variation of significant rain storms that intermittently increase the surface moisture. The resulting thermally-derived layers are in the process of being combined with composition, vegetation and surface reflectance datasets to map the Mojave at the highest VNIR resolution (20m/pixel) and compared to currently-available lower-resolution datasets.

Methodology of the interpretation of remote sensing data and applications in geology

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Veneziani, P.; Dosanjos, C. E.

1981-01-01

Methods used for interpreting orbital (LANDSAT) data for regional geological mapping in Brazil are examined. Particular attention is given to the levels of analysis used for studying geomorphology, structural geology, lithology, stratigraphy, surface geology, and dynamic processes. Examples of regional mapping described include: (1) rock intrusions in SE Sao Paulo, the southern parts of Minas Gerais, and the states of Rio de Janeiro, and Espiritu Santo; (2) a preliminary survey of Pre-Cambrian geology in the State of Piaui; and (3) the Gondwana Project - surveying Jaguaribe plants. Mineral exploration in Rio Grande do Sul, and the geology of the Alcalino complex of Itatiaia are discussed as well as the use of automatic classifications of rock intrusions and of ilmenite deposits in the Floresta Region. Aerial photography, side looking radar, and thermal infrared scanning are other types of remote sensors also used in prospecting for geothermal anomalies in the city of Caldas Novas-Goias.

Remote sensing of strippable coal reserves and mine inventory in part of the Warrior Coal Field in Alabama

NASA Technical Reports Server (NTRS)

Joiner, T. J.; Copeland, C. W., Jr.; Russell, D. D.; Evans, F. E., Jr.; Sapp, C. D.; Boone, P. A.

1978-01-01

Methods by which estimates of the remaining reserves of strippable coal in Alabama could be made were developed. Information acquired from NASA's Earth Resources Office was used to analyze and map existing surface mines in a four-quadrangle area in west central Alabama. Using this information and traditional methods for mapping coal reserves, an estimate of remaining strippable reserves was derived. Techniques for the computer analysis of remotely sensed data and other types of available coal data were developed to produce an estimate of strippable coal reserves for a second four-quadrangle area. Both areas lie in the Warrior coal field, the most prolific and active of Alabama's coal fields. They were chosen because of the amount and type of coal mining in the area, their location relative to urban areas, and the amount and availability of base data necessary for this type of study.

Applications of low-cost radio-controlled airplanes to environmental restoration at Oak Ridge National Laboratory

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

Nyquist, J.E.

1996-10-01

The US DOE is endeavoring to clean up contamination created by the disposal of chemical and nuclear waste on the Oak Ridge Reservation (ORR), Tennessee, with an emphasis on minimizing off-site migration of contaminated surface and ground water. The task is complicated by inadequate disposal records and by the complexity of the local geology. Remote sensing data, including aerial photography and geophysics, have played an important role in the ORR site characterization. Are there advantages to collecting remote sensing data using Unmanned Aerial Vehicles (UAV`s)? In this paper, I will discuss the applications of UAV`s being explored at Oak Ridgemore » National Laboratory (ORNL) under the sponsorship of the Department of Energy`s Office of Science and technology. These applications are : aerial photography, magnetic mapping, and Very Low Frequency (VLF) electromagnetic mapping.« less

Integrating Statistical and Expert Knowledge to Develop Phenoregions for the Continental United States

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Biondi, F.; Bradford, J. B.; Foster, J. R.; Betancourt, J. L.; Foster, J. R.; Biondi, F.; Bradford, J. B.; Henebry, G. M.; Post, E.; Koenig, W.; Hoffman, F. M.; de Beurs, K.; Hoffman, F. M.; Kumar, J.; Hargrove, W. W.; Norman, S. P.; Brooks, B. G.

2016-12-01

Vegetated ecosystems exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and weather disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) every eight days at 250 m resolution for the period 2000-2015 to develop phenological signatures of emergent ecological regimes called phenoregions. We employed a "Big Data" classification approach on a supercomputer, specifically applying an unsupervised data mining technique, to this large collection of NDVI measurements to develop annual maps of phenoregions. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency of occurrence. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. We will present the phenoregions methodology and resulting maps for the CONUS, describe the "label-stealing" technique for ascribing biome characteristics to phenoregions, and introduce a new polar plotting scheme for processing NDVI data by localized seasonality.

Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

NASA Astrophysics Data System (ADS)

Chen, H.; Kelly, R. E. J.

2017-12-01

Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

Sedimentary Environments Mapping in the Yellow Sea Using TanDEM-X and Optic Satellites

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Lee, Y. K.; Kim, S. W.

2017-12-01

Due to land reclamation and dredging, 57% of China's coastal wetlands have disappeared since the 1950s, and the total area of tidal flats in South Korea decreased from approximately 2,800km2 in 1990 to 2392km2 in 2005(Qiu, 2011 and MLTM, 2010). Intertidal DEM and sedimentary facies are useful for understanding intertidal functions and monitoring their response to natural and anthropogenic actions. Highly accurate intertidal DEMs with 5-m resolution were generated based on the TanDEM-X interferometric SAR (InSAR) technique because TanDEM-X allows the acquisition of the coherent InSAR pairs with no time lag or approximately 10-second temporal baseline between master and slave SAR image. We successfully generated intertidal zone DEMs with 5-7-m spatial resolutions and interferometric height accuracies better than 0.15 m for three representative tidal flats on the west coast of the Korean Peninsula and one site of chinese coastal region in the Yellow Sea. Surface sediment classification based on remotely sensed data must circumspectly consider an effective critical grain size, water content, local topography, and intertidal structures. The earlier studies have some limitation that the classification map is not considered to analysis various environmental conditions. Therefore, the purpose of this study was minutely to mapping the surface sedimentary facies by analyzing the tidal channel, topography with multi-sensor remotely sensed data and in-situ data.

Testing Extensions of Our Quantitative Daily of San Joaquin Wintertime Aerosols Using MAIAC and Meteorology Without Transport/Transformation Assumptions

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Sorek Hamer, Meytar; Esswein, Robert F.

2017-01-01

The Western US and many regions globally present daunting difficulties in understanding and mapping PM2.5 episodes. We evaluate extensions of a method independent of source-description and transport/transformation. These regions suffer frequent few-day episodes due to shallow mixing; low satellite AOT and bright surfaces complicate the description. Nevertheless, we expect residual errors in our maps of less than 8 ug/m^3 in episodes reaching 60-100 ug/m^3; maps which detail pollution from Interstate 5. Our current success is due to use of physically meaningful functions of MODIS-MAIAC-derived AOD, afternoon mixed-layer height, and relative humidity for a basin in which the latter are correlated. A mixed-effects model then describes a daily AOT-to-PM2.5 relationship. (Note: in other published mixed-effects models, AOT contributes minimally. We seek to extend on these to develop useful estimation methods for similar situations. We evaluate existing but more spotty information on size distribution (AERONET, MISR, MAIA, CALIPSO, other remote sensing). We also describe the usefulness of an equivalent mixing depth for water vapor vs meteorological boundary layer height. Each has virtues and limitations. Finally, we begin to evaluate methods for removing the complications due to detached but polluted layers (which don't mix to the surface) using geographical, meteorological, and remotely sensed data.

Surface Emissivity Maps for Use in Satellite Retrievals of Longwave Radiation

NASA Technical Reports Server (NTRS)

Wilber, Anne C.; Kratz, David P.; Gupta, Shashi K.

1999-01-01

Accurate accounting of surface emissivity is essential for the retrievals of surface temperature from remote sensing measurements, and for the computations of longwave (LW) radiation budget of the Earth?s surface. Past studies of the above topics assumed that emissivity for all surface types, and across the entire LW spectrum is equal to unity. There is strong evidence, however, that emissivity of many surface materials is significantly lower than unity, and varies considerably across the LW spectrum. We have developed global maps of surface emissivity for the broadband LW region, the thermal infrared window region (8-12 micron), and 12 narrow LW spectral bands. The 17 surface types defined by the International Geosphere Biosphere Programme (IGBP) were adopted as such, and an additional (18th) surface type was introduced to represent tundra-like surfaces. Laboratory measurements of spectral reflectances of 10 different surface materials were converted to corresponding emissivities. The 10 surface materials were then associated with 18 surface types. Emissivities for the 18 surface types were first computed for each of the 12 narrow spectral bands. Emissivities for the broadband and the window region were then constituted from the spectral band values by weighting them with Planck function energy distribution.

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

Treesearch

Ronald E. McRoberts; Warren B. Cohen; Erik Naesset; Stephen V. Stehman; Erkki O. Tomppo

2010-01-01

Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic...

Evaluating the potential for remote bathymetric mapping of a turbid, sand-bed river: 1. field spectroscopy and radiative transfer modeling

USGS Publications Warehouse

Legleiter, Carl J.; Kinzel, Paul J.; Overstreet, Brandon T.

2011-01-01

Remote sensing offers an efficient means of mapping bathymetry in river systems, but this approach has been applied primarily to clear-flowing, gravel bed streams. This study used field spectroscopy and radiative transfer modeling to assess the feasibility of spectrally based depth retrieval in a sand-bed river with a higher suspended sediment concentration (SSC) and greater water turbidity. Attenuation of light within the water column was characterized by measuring the amount of downwelling radiant energy at different depths and calculating a diffuse attenuation coefficient, Kd. Attenuation was strongest in blue and near-infrared bands due to scattering by suspended sediment and absorption by water, respectively. Even for red wavelengths with the lowest values of Kd, only a small fraction of the incident light propagated to the bed, restricting the range of depths amenable to remote sensing. Spectra recorded above the water surface were used to establish a strong, linear relationship (R2 = 0.949) between flow depth and a simple band ratio; even under moderately turbid conditions, depth remained the primary control on reflectance. Constraints on depth retrieval were examined via numerical modeling of radiative transfer within the atmosphere and water column. SSC and sensor radiometric resolution limited both the maximum detectable depth and the precision of image-derived depth estimates. Thus, although field spectra indicated that the bathymetry of turbid channels could be remotely mapped, model results implied that depth retrieval in sediment-laden rivers would be limited to shallow depths (on the order of 0.5 m) and subject to a significant degree of uncertainty.

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

Treesearch

Steven H. Ackers; Raymond J. Davis; Keith A. Olsen; Katie M. Dugger

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last fewdecades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often...

Remote sensing for environmental site screening and watershed evaluation in Utah Mine lands - East Tintic mountains, Oquirrh mountains, and Tushar mountains

USGS Publications Warehouse

Rockwell, Barnaby W.; McDougal, Robert R.; Gent, Carol A.

2005-01-01

Imaging spectroscopy-a powerful remote-sensing tool for mapping subtle variations in the composition of minerals, vegetation, and man-made materials on the Earth's surface-was applied in support of environmental assessments and watershed evaluations in several mining districts in the State of Utah. Three areas were studied through the use of Landsat 7 ETM+ and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data: (1) the Tintic mining district in the East Tintic Mountains southwest of Provo, (2) the Camp Floyd mining district (including the Mercur mine) and the Stockton (or Rush Valley) mining district in the Oquirrh Mountains south of the Great Salt Lake, and (3) the Tushar Mountains and Antelope Range near Marysvale. The Landsat 7 ETM+ data were used for initial site screening and the planning of AVIRIS surveys. The AVIRIS data were analyzed to create spectrally defined maps of surface minerals with special emphasis on locating and characterizing rocks and soils with acid-producing potential (APP) and acid-neutralizing potential (ANP). These maps were used by the United States Environmental Protection Agency (USEPA) for three primary purposes: (1) to identify unmined and anthropogenic sources of acid generation in the form of iron sulfide and (or) ferric iron sulfate-bearing minerals such as jarosite and copiapite; (2) to seek evidence for downstream or downwind movement of minerals associated with acid generation, mine waste, and (or) tailings from mines, mill sites, and zones of unmined hydrothermally altered rocks; and (3) to identify carbonate and other acid-buffering minerals that neutralize acidic, potentially metal bearing, solutions and thus mitigate potential environmental effects of acid generation. Calibrated AVIRIS surface-reflectance data were spectrally analyzed to identify and map selected surface materials. Two maps were produced from each flightline of AVIRIS data: a map of iron-bearing minerals and water having absorption features in the spectral region from 0.35 ?m to 1.35 ?m and a map of minerals (including clays, sulfates, micas, and carbonates) having absorptions in the spectral region from 1.45 ?m to 2.51 ?m. Several methods were used to verify the AVIRIS mapping results, including field checking of selected locations with a portable spectrometer, visual inspection of the AVIRIS reflectance spectra, and X-ray diffraction (XRD) analysis of field samples. The maps of iron-bearing minerals derived from analysis of the visible (VIS) and near-infrared (NIR) regions of the electromagnetic spectrum were shown to be more consistently reliable in indicating the presence of jarosite than were the maps generated from analysis of the short-wave infrared (SWIR) region. When present in abundance, phyllosilicate minerals tend to dominate the SWIR and mask the spectral features of jarosite in that wavelength region. The crystal field absorptions of jarosite in the VIS and NIR spectral regions will commonly be present regardless of whether the Fe-OH absorption feature near 2.27 ?m can be detected. For this reason, the VIS and NIR were preferable to the SWIR for the remote spectroscopic identification of jarosite (and other iron-bearing minerals). Large exposures of unmined hydrothermally altered rocks occur throughout the three study areas. These rocks commonly contain sulfide or sulfate minerals that produce sulfuric acid upon subaerial oxidation. The acid may be introduced into local surface and ground water and thus lower the baseline (that is, the premining) pH for a watershed. The three study areas also have widespread exposures of rocks with acid-neutralizing potential. Lithologies containing carbonates and (or) other acid-buffering minerals-such as sedimentary limestones and dolomites and propylitically altered igneous rocks-were mapped with the AVIRIS data throughout the Oquirrh and East Tintic Mountains and locally in the Antelope Range and Tushar Mountains. Because elevated levels o

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."

Testing random forest classification for identifying lava flows and mapping age groups on a single Landsat 8 image

NASA Astrophysics Data System (ADS)

Li, Long; Solana, Carmen; Canters, Frank; Kervyn, Matthieu

2017-10-01

Mapping lava flows using satellite images is an important application of remote sensing in volcanology. Several volcanoes have been mapped through remote sensing using a wide range of data, from optical to thermal infrared and radar images, using techniques such as manual mapping, supervised/unsupervised classification, and elevation subtraction. So far, spectral-based mapping applications mainly focus on the use of traditional pixel-based classifiers, without much investigation into the added value of object-based approaches and into advantages of using machine learning algorithms. In this study, Nyamuragira, characterized by a series of > 20 overlapping lava flows erupted over the last century, was used as a case study. The random forest classifier was tested to map lava flows based on pixels and objects. Image classification was conducted for the 20 individual flows and for 8 groups of flows of similar age using a Landsat 8 image and a DEM of the volcano, both at 30-meter spatial resolution. Results show that object-based classification produces maps with continuous and homogeneous lava surfaces, in agreement with the physical characteristics of lava flows, while lava flows mapped through the pixel-based classification are heterogeneous and fragmented including much "salt and pepper noise". In terms of accuracy, both pixel-based and object-based classification performs well but the former results in higher accuracies than the latter except for mapping lava flow age groups without using topographic features. It is concluded that despite spectral similarity, lava flows of contrasting age can be well discriminated and mapped by means of image classification. The classification approach demonstrated in this study only requires easily accessible image data and can be applied to other volcanoes as well if there is sufficient information to calibrate the mapping.

A low-power, radiation-resistant, Silicon-Drift-Detector array for extraterrestrial element mapping

NASA Astrophysics Data System (ADS)

Ramsey, B. D.; Gaskin, J. A.; Elsner, R. F.; Chen, W.; Carini, G. A.; De Geronimo, G.; Keister, J.; Li, S.; Li, Z.; Siddons, D. P.; Smith, G.

2012-02-01

We are developing a modular Silicon Drift Detector (SDD) X-Ray Spectrometer (XRS) for measuring the abundances of light surface elements (C to Fe) fluoresced by ambient radiation on remote airless bodies. The value of fluorescence spectrometry for surface element mapping is demonstrated by its inclusion on three recent lunar missions and by exciting new data that have recently been announced from the Messenger Mission to Mercury. The SDD-XRS instrument that we have been developing offers excellent energy resolution and an order of magnitude lower power requirement than conventional CCDs, making much higher sensitivities possible with modest spacecraft resources. In addition, it is significantly more radiation resistant than x-ray CCDs and therefore will not be subject to the degradation that befell recent lunar instruments. In fact, the intrinsic radiation resistance of the SDD makes it applicable even to the harsh environment of the Jovian system where it can be used to map the light surface elements of Europa. In this paper, we first discuss our element-mapping science-measurement goals. We then derive the necessary instrument requirements to meet these goals and discuss our current instrument development status with respect to these requirements.

A Low-Power, Radiation-Resistant, Silicon-Drift-Detector Array for Extraterrestrial Element Mapping

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

Ramsey B. D.; De Geronimo G.; Gaskin, J.A.

2012-02-08

We are developing a modular Silicon Drift Detector (SDD) X-Ray Spectrometer (XRS) for measuring the abundances of light surface elements (C to Fe) fluoresced by ambient radiation on remote airless bodies. The value of fluorescence spectrometry for surface element mapping is demonstrated by its inclusion on three recent lunar missions and by exciting new data that have recently been announced from the Messenger Mission to Mercury. The SDD-XRS instrument that we have been developing offers excellent energy resolution and an order of magnitude lower power requirement than conventional CCDs, making much higher sensitivities possible with modest spacecraft resources. In addition,more » it is significantly more radiation resistant than x-ray CCDs and therefore will not be subject to the degradation that befell recent lunar instruments. In fact, the intrinsic radiation resistance of the SDD makes it applicable even to the harsh environment of the Jovian system where it can be used to map the light surface elements of Europa. In this paper, we first discuss our element-mapping science-measurement goals. We then derive the necessary instrument requirements to meet these goals and discuss our current instrument development status with respect to these requirements.« less

Remote Sensing for Hydrology: Surface Water Dynamics from Three Decades of Landsat Data

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Broich, M.; Kingsford, R.; Lucas, R.; Keith, D.

2014-12-01

Surface water is a vital resource affected by changes in climate and anthropogenic factors. Knowledge of surface water dynamics provides critical information for flood and drought management. Here we focused on the on the entire Murray-Darling Basin (MDB) of Australia, a large semi-arid region with scarce water resources, high hydroclimatic variability and competing water demands, impacted by climate change, altered flow regimes and land use changes. The MDB is also an area where substantial investment in environmental water allocation of large volumes of environmental flow was made. We used Landsat TM and ETM+ time series to synoptically map the dynamic of surface water extent with an internally consistent algorithm (Tulbure and Broich, 2013) over decades (1986-2011). We used a subset of Landsat path/rows for image training in both wet and dry years. Results show high interannual variability in number and size of flooded areas, with flooded areas during the Millennium Drought (until 2009) being substantially smaller than during the excessive 2010-2011 La Nina flooding. Flooding frequency in 2006, a very dry year was lower than in 2010, the La Nina year when extensive floods occurred. More developed areas of the basin showed different inter-annual patterns from natural areas of the basin. At Barmah-Millewa, the largest river red gum forest in the world, we also mapped flooded forest and tracked changes in NDVI. Higher NDVI values were found in areas more frequently flooded. Knowledge of the spatial and temporal dynamics of flooding and the response of riparian vegetation communities to flooding is important for management of floodplain wetlands and vegetation communities and for investigating effectiveness of environmental flows and flow regimes in the MDB. Existing maps of inundated areas are linked with river flow to quantify the relationship between river flow and inundated area in the MDB. Historic flood inundation extent mapped via remote sensing can be used to quantify spatially explicit changes in surface water dynamics and vegetation communities as outcomes of management scenarios in response to water management decisions. This methodology is globally applicable and relevant to areas prone to flooding with competing water demands and can be used for mapping water availability in data scarce regions.

A GIS and statistical approach to identify variables that control water quality in hydrothermally altered and mineralized watersheds, Silverton, Colorado, USA

USGS Publications Warehouse

Yager, Douglas B.; Johnson, Raymond H.; Rockwell, Barnaby W.; Caine, Jonathan S.; Smith, Kathleen S.

2013-01-01

Hydrothermally altered bedrock in the Silverton mining area, southwest Colorado, USA, contains sulfide minerals that weather to produce acidic and metal-rich leachate that is toxic to aquatic life. This study utilized a geographic information system (GIS) and statistical approach to identify watershed-scale geologic variables in the Silverton area that influence water quality. GIS analysis of mineral maps produced using remote sensing datasets including Landsat Thematic Mapper, advanced spaceborne thermal emission and reflection radiometer, and a hybrid airborne visible infrared imaging spectrometer and field-based product enabled areas of alteration to be quantified. Correlations between water quality signatures determined at watershed outlets, and alteration types intersecting both total watershed areas and GIS-buffered areas along streams were tested using linear regression analysis. Despite remote sensing datasets having varying watershed area coverage due to vegetation cover and differing mineral mapping capabilities, each dataset was useful for delineating acid-generating bedrock. Areas of quartz–sericite–pyrite mapped by AVIRIS have the highest correlations with acidic surface water and elevated iron and aluminum concentrations. Alkalinity was only correlated with area of acid neutralizing, propylitically altered bedrock containing calcite and chlorite mapped by AVIRIS. Total watershed area of acid-generating bedrock is more significantly correlated with acidic and metal-rich surface water when compared with acid-generating bedrock intersected by GIS-buffered areas along streams. This methodology could be useful in assessing the possible effects that alteration type area has in either generating or neutralizing acidity in unmined watersheds and in areas where new mining is planned.

Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

2015-04-01

Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices

NASA Astrophysics Data System (ADS)

Yang, Xiucheng; Chen, Li

2017-04-01

Urban surface water is characterized by complex surface continents and small size of water bodies, and the mapping of urban surface water is currently a challenging task. The moderate-resolution remote sensing satellites provide effective ways of monitoring surface water. This study conducts an exploratory evaluation on the performance of the newly available Sentinel-2A multispectral instrument (MSI) imagery for detecting urban surface water. An automatic framework that integrates pixel-level threshold adjustment and object-oriented segmentation is proposed. Based on the automated workflow, different combinations of visible, near infrared, and short-wave infrared bands in Sentinel-2 image via different water indices are first compared. Results show that object-level modified normalized difference water index (MNDWI with band 11) and automated water extraction index are feasible in urban surface water mapping for Sentinel-2 MSI imagery. Moreover, comparative results are obtained utilizing optimal MNDWI from Sentinel-2 and Landsat 8 images, respectively. Consequently, Sentinel-2 MSI achieves the kappa coefficient of 0.92, compared with that of 0.83 from Landsat 8 operational land imager.

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests

Treesearch

Bernard R. Parresol; Joe H. Scott; Anne Andreu; Susan Prichard; Laurie Kurth

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or...

Tracking lava flow emplacement on the east rift zone of Kilauea, Hawai'i with InSAR coherence

NASA Astrophysics Data System (ADS)

Dietterich, H. R.; Schmidt, D. A.; Poland, M. P.; Cashman, K. V.

2010-12-01

Remote sensing of lava flows from the Pu`u `O`o-Kupaianaha eruption on the east rift zone of Kilauea serves to document the ongoing eruption, while yielding insights into how lava flow fields develop. InSAR is widely used to measure deformation by detecting minute changes in ground surfaces that stay correlated during repeat observations. The eruption and emplacement of fresh lava on the surface, however, disrupts the coherence of the radar echoes, allowing the area of these flows to be mapped with InSAR coherence images. We use InSAR correlation to visualize surface flow activity from 2003-2010 in order to quantify eruption rates and explore lava flow behavior from emplacement onward. This method for mapping flows does not require daylight, cloudless skies, or access to the active flow fields that is necessary for traditional visual surveys. We produce coherence maps for hundreds of 35 to 105-day periods from twelve tracks of ENVISAT SAR data using the GAMMA software package. By combining these coherence maps we create a unique dataset with which to develop this technique and amass lava flow observations. Where correlation images overlap in time, they are summed and normalized to derive a time series of surface coherence with a spatial resolution of 20 meters and a temporal resolution of as little as a few days. We identify existing stable flows by their high radar coherence, and determine a coherence threshold that is applied to each correlation image. This threshold is calibrated so as to reduce the effects of varying baseline, time duration, and atmospheric effects between images, as well as decorrelation due to vegetation. The final images illustrate lava flow activity that corresponds well with surface flow outlines and tube locations recorded by the USGS mapping effort. The InSAR-derived results serve to enhance these traditional maps by documenting pixel-scale changes over time. When compared with forward looking infrared (FLIR) thermal imagery, pixel decorrelation can be related to specific styles of activity, including surface breakouts or deformation, where field examination is difficult. We analyze these detailed snapshots of the flows to derive estimates of flow parameters, including effusion rates, lava flow areas and volumes, and surface lava flow activity over time, which provides a means of examining controls on flow paths, advance rates, and morphologies. We find that once emplaced, flows remain decorrelated for months before becoming correlated again in a piecewise fashion, suggesting that correlation rate may be dependent on thickness and cooling rate. As the eruption continues, this ever-expanding dataset has great potential for remotely capturing quantitative data from an active flow field and improving our knowledge of lava flows and their hazards.

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)

USGS Publications Warehouse

Slonecker, Terry; Jones, Daniel K.; Pellerin, Brian A.

2016-01-01

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM).

PubMed

Slonecker, E Terrence; Jones, Daniel K; Pellerin, Brian A

2016-06-30

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles. Published by Elsevier Ltd.

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

NASA Astrophysics Data System (ADS)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Optimal land use/cover classification using remote sensing imagery for hydrological modelling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2007-10-01

Land use/cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/cover. This paper presents different approaches to attain an optimal land use/cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/cover map was not sufficient for the delineation of HRUs, since the agricultural land use/cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Therefore we adopted a visual classification approach using optical data alone and also fused with ENVISAT ASAR data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modelling.

Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Kokaly, R.F.; Rockwell, B.W.; Haire, S.L.; King, T.V.V.

2007-01-01

Forest fires leave behind a changed ecosystem with a patchwork of surface cover that includes ash, charred organic matter, soils and soil minerals, and dead, damaged, and living vegetation. The distributions of these materials affect post-fire processes of erosion, nutrient cycling, and vegetation regrowth. We analyzed high spatial resolution (2.4??m pixel size) Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over the Cerro Grande fire, to map post-fire surface cover into 10 classes, including ash, soil minerals, scorched conifer trees, and green vegetation. The Cerro Grande fire occurred near Los Alamos, New Mexico, in May 2000. The AVIRIS data were collected September 3, 2000. The surface cover map revealed complex patterns of ash, iron oxide minerals, and clay minerals in areas of complete combustion. Scorched conifer trees, which retained dry needles heated by the fire but not fully combusted by the flames, were found to cover much of the post-fire landscape. These scorched trees were found in narrow zones at the edges of completely burned areas. A surface cover map was also made using Landsat Enhanced Thematic Mapper plus (ETM+) data, collected September 5, 2000, and a maximum likelihood, supervised classification. When compared to AVIRIS, the Landsat classification grossly overestimated cover by dry conifer and ash classes and severely underestimated soil and green vegetation cover. In a comparison of AVIRIS surface cover to the Burned Area Emergency Rehabilitation (BAER) map of burn severity, the BAER high burn severity areas did not capture the variable patterns of post-fire surface cover by ash, soil, and scorched conifer trees seen in the AVIRIS map. The BAER map, derived from air photos, also did not capture the distribution of scorched trees that were observed in the AVIRIS map. Similarly, the moderate severity class of Landsat-derived burn severity maps generated from the differenced Normalized Burn Ratio (dNBR) calculation had low agreement with the AVIRIS classes of scorched conifer trees. Burn severity and surface cover images were found to contain complementary information, with the dNBR map presenting an image of degree of change caused by fire and the AVIRIS-derived map showing specific surface cover resulting from fire.

Mapping Palm Swamp Wetland Ecosystems in the Peruvian Amazon: a Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Podest, E.; McDonald, K. C.; Schroeder, R.; Pinto, N.; Zimmerman, R.; Horna, V.

2012-12-01

Wetland ecosystems are prevalent in the Amazon basin, especially in northern Peru. Of specific interest are palm swamp wetlands because they are characterized by constant surface inundation and moderate seasonal water level variation. This combination of constantly saturated soils and warm temperatures year-round can lead to considerable methane release to the atmosphere. Because of the widespread occurrence and expected sensitivity of these ecosystems to climate change, it is critical to develop methods to quantify their spatial extent and inundation state in order to assess their carbon dynamics. Spatio-temporal information on palm swamps is difficult to gather because of their remoteness and difficult accessibility. Spaceborne microwave remote sensing is an effective tool for characterizing these ecosystems since it is sensitive to surface water and vegetation structure and allows monitoring large inaccessible areas on a temporal basis regardless of atmospheric conditions or solar illumination. We developed a remote sensing methodology using multi-sensor remote sensing data from the Advanced Land Observing Satellite (ALOS) Phased Array L-Band Synthetic Aperture Radar (PALSAR), Shuttle Radar Topography Mission (SRTM) DEM, and Landsat to derive maps at 100 meter resolution of palm swamp extent and inundation based on ground data collections; and combined active and passive microwave data from AMSR-E and QuikSCAT to derive inundation extent at 25 kilometer resolution on a weekly basis. We then compared information content and accuracy of the coarse resolution products relative to the high-resolution datasets. The synergistic combination of high and low resolution datasets allowed for characterization of palm swamps and assessment of their flooding status. This work has been undertaken partly within the framework of the JAXA ALOS Kyoto & Carbon Initiative. PALSAR data have been provided by JAXA. Portions of this work were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Mars Observer: Mission toward a basic understanding of Mars

NASA Technical Reports Server (NTRS)

Albee, Arden L.

1992-01-01

The Mars Observer Mission will provide a spacecraft platform about Mars from which the entire Martian surface and atmosphere will be observed and mapped by remote sensing instruments for at least 1 Martian year. The scientific objectives for the Mission emphasize qualitative and quantitative determination of the elemental and mineralogical composition of the surface; measurement of the global surface topography, gravity field, and magnetic field; and the development of a synoptic data base of climatological conditions. The Mission will provide basic global understanding of Mars as it exists today and will provide a framework for understanding its past.

Remote sensing with spaceborne synthetic aperture imaging radars: A review

NASA Technical Reports Server (NTRS)

Cimino, J. B.; Elachi, C.

1983-01-01

A review is given of remote sensing with Spaceborne Synthetic Aperture Radars (SAR's). In 1978, a spaceborne SA was flown on the SEASAT satellite. It acquired high resulution images over many regions in North America and the North Pacific. The acquired data clearly demonstrate the capability of spaceborne SARs to: image and track polar ice floes; image ocean surface patterns including swells, internal waves, current boundaries, weather boundaries and vessels; and image land features which are used to acquire information about the surface geology and land cover. In 1981, another SAR was flown on the second shuttle flight. This Shuttle Imaging Radar (SIR-A) acquired land and ocean images over many areas around the world. The emphasis of the SIR-A experiment was mainly toward geologic mapping. Some of the key results of the SIR-A experiment are given.

Potential mapping with charged-particle beams

NASA Technical Reports Server (NTRS)

Robinson, J. W.; Tillery, D. G.

1979-01-01

Experimental methods of mapping the equipotential surfaces near some structure of interest rely on the detection of charged particles which have traversed the regions of interest and are detected remotely. One method is the measurement of ion energies for ions created at a point of interest and expelled from the region by the fields. The ion energy at the detector in eV corresponds to the potential where the ion was created. An ionizing beam forms the ions from background neutrals. The other method is to inject charged particles into the region of interest and to locate their exit points. A set of several trajectories becomes a data base for a systematic mapping technique. An iterative solution of a boundary value problem establishes concepts and limitations pertaining to the mapping problem.

Empirical relationships among atmospheric variables from rawinsonde and field data as surrogates for AVIRIS measurements: Estimation of regional land surface evapotranspiration

NASA Technical Reports Server (NTRS)

Conel, James E.; Hoover, Gordon; Nolin, Anne; Alley, Ron; Margolis, Jack

1992-01-01

Empirical relationships between variables are ways of securing estimates of quantities difficult to measure by remote sensing methods. The use of empirical functions was explored between: (1) atmospheric column moisture abundance W (gm H2O/cm(sup 2) and surface absolute water vapor density rho(q-bar) (gm H2O/cm(sup 3), with rho density of moist air (gm/cm(sup 3), q-bar specific humidity (gm H2O/gm moist air), and (2) column abundance and surface moisture flux E (gm H2O/(cm(sup 2)sec)) to infer regional evapotranspiration from Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) water vapor mapping data. AVIRIS provides, via analysis of atmospheric water absorption features, estimates of column moisture abundance at very high mapping rate (at approximately 100 km(sup 2)/40 sec) over large areas at 20 m ground resolution.

Instantaneous and daily values of the surface energy balance over agricultural fields using remote sensing and a reference field in an arid environment

USGS Publications Warehouse

Kustas, William P.; Moran, M.S.; Jackson, R. D.; Gay, L.W.; Duell, L.F.W.; Kunkel, K.E.; Matthias, A.D.

1990-01-01

Remotely sensed surface temperature and reflectance in the visible and near infrared wavebands along with ancilliary meteorological data provide the capability of computing three of the four surface energy balance components (i.e., net radiation, soil heat flux, and sensible heat flux) at different spatial and temporal scales. As a result, under nonadvective conditions, this enables the estimation of the remaining term (i.e., the latent heat flux). One of the practical applications with this approach is to produce evapotranspiration (ET) maps for agricultural regions which consist of an array of fields containing different crops at varying stages of growth and soil moisture conditions. Such a situation exists in the semiarid southwest at the University of Arizona Maricopa Agricultural Center, south of Phoenix. For one day (14 June 1987), surface temperature and reflectance measurements from an aircraft 150 m above ground level (agl) were acquired over fields from zero to nearly full cover at four times between 1000 MST and 1130 MST. The diurnal pattern of the surface energy balance was measured over four fields, which included alfalfa at 60% cover, furrowed cotton at 20% and 30% cover, and partially plowed what stubble. Instantaneous and daily values of ET were estimated for a representative area around each flux site with an energy balance model that relies on a reference ET. This reference value was determined with remotely sensed data and several meteorological inputs. The reference ET was adjusted to account for the different surface conditions in the other fields using only remotely sensed variables. A comparison with the flux measurements suggests the model has difficulties with partial canopy conditions, especially related to the estimation of the sensible heat flux. The resulting errors for instantaneous ET were on the order of 100 W m-2 and for daily values of order 2 mm day-1. These findings suggest future research should involve development of methods to account for the variability of meteorological parameters brought about by changes in surface conditions and improvements in the modeling of sensible heat transfer across the surface-atmosphere interface for partial canopy conditions using remote sensing information. ?? 1990.

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.

Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling

USGS Publications Warehouse

Keane, Robert E.; Burgan, Robert E.; Van Wagtendonk, Jan W.

2001-01-01

Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

Subsurface geological modeling using GIS and remote sensing data: a case study from Platanos landslide, Western Greece

NASA Astrophysics Data System (ADS)

Kavoura, K.; Kordouli, M.; Nikolakopoulos, K.; Elias, P.; Sykioti, O.; Tsagaris, V.; Drakatos, G.; Rondoyanni, Th.; Tsiambaos, G.; Sabatakakis, N.; Anastasopoulos, V.

2014-08-01

Landslide phenomena constitute a major geological hazard in Greece and especially in the western part of the country as a result of anthropogenic activities, growing urbanization and uncontrolled land - use. More frequent triggering events and increased susceptibility of the ground surface to instabilities as consequence of climate change impacts (continued deforestation mainly due to the devastating forest wildfires and extreme meteorological events) have also increased the landslide risk. The studied landslide occurrence named "Platanos" has been selected within the framework of "Landslide Vulnerability Model - LAVMO" project that aims at creating a persistently updated electronic platform assessing risks related with landslides. It is a coastal area situated between Korinthos and Patras at the northwestern part of the elongated graben of the Corinth Gulf. The paper presents the combined use of geological-geotechnical insitu data, remote sensing data and GIS techniques for the evaluation of a subsurface geological model. High accuracy Digital Surface Model (DSM), airphotos mosaic and satellite data, with a spatial resolution of 0.5m were used for an othophoto base map compilation of the study area. Geological - geotechnical data obtained from exploratory boreholes were digitized and implemented in a GIS platform with engineering geological maps for a three - dimensional subsurface model evaluation. This model is provided for being combined with inclinometer measurements for sliding surface location through the instability zone.

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites

PubMed Central

Karl, Jason W.

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral ‘fingerprint’ of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches. PMID:28414731

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.

PubMed

Maynard, Jonathan J; Karl, Jason W

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral 'fingerprint' of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches.

Is There Ecological Information in Optical Polarization Data?

NASA Technical Reports Server (NTRS)

Vanderbilt, Vern; Daughtry, Craig; Dahlgren, Robert

2015-01-01

Optical linear polarization? In remote sensing it's due to specular reflection. The first surface that incident light encounters - a smooth water surface or the waxy first surface of a leaf's cuticle, if it's even somewhat smooth (i.e. shiny) - will specularly reflect and linearly polarize the incident light. We provide three examples of the types of ecological information contained in remotely sensed optical linear polarization measurements. Remove the surface reflection to better see the interior. The linearly polarized light reflected by leaf surfaces contains no information about cellular pigments, metabolites, or water contained in the leaf interiors of a plant canopy, because it never enters the leaf interior to interact with them. Thus, for purposes of remotely sensing the leaf interiors of a plant canopy, the linearly polarized light should be subtracted from the total reflected light, because including it would add noise to the measurement. In particular 'minus specular' vegetation indices should allow improved monitoring of a plant canopy's physiological processes. Estimate plant development stage and yield. Wheat and sorghum grain heads, following emergence, rapidly extend upward and very quickly tower over nearby leaves, partially blocking our view of the sunlight reflected by those leaf surfaces. The resulting decrease in the amount of surface reflected and polarized sunlight, if monitored over time, potentially allows per-field estimates of the dates of the heading and flowering development stages to be interleaved with weather data in models, which is key to better estimating per-field grain yield. Similar polarization changes may occur in other grasses, such as oats, barley, corn and rice, each a crop so widely grown that it potentially affects climate at the regional scale. Wetlands Mapping. The sunlight specularly reflected by surface waters is blindingly bright, spectrally flat and polarized - all of which telegraphs that the ground area is inundated. Inundated soils exchange methane with the atmosphere; non-inundated soils, carbon dioxide. Aquatic plants growing through the water surface pipe the soil-produced methane via the stomata to the atmosphere, enhancing exchanges rates by factors of 10-20 compared to ebullition (bubbling) or diffusion through the water column to the atmosphere. Thus, mapping wetland areas into three community types - inundated areas with emergent vegetation, open water and uplands - provides potentially key information to water, carbon and energy budgets at landscape to global scales.

Completing the Picture: Importance of Considering Participatory Mapping for REDD+ Measurement, Reporting and Verification (MRV)

PubMed Central

Rafanoharana, Serge; Boissière, Manuel; Wijaya, Arief; Wardhana, Wahyu

2016-01-01

Remote sensing has been widely used for mapping land cover and is considered key to monitoring changes in forest areas in the REDD+ Measurement, Reporting and Verification (MRV) system. But Remote Sensing as a desk study cannot capture the whole picture; it also requires ground checking. Therefore, complementing remote sensing analysis using participatory mapping can help provide information for an initial forest cover assessment, gain better understanding of how local land use might affect changes, and provide a way to engage local communities in REDD+. Our study looked at the potential of participatory mapping in providing complementary information for remotely sensed maps. The research sites were located in different ecological and socio-economic contexts in the provinces of Papua, West Kalimantan and Central Java, Indonesia. Twenty-one maps of land cover and land use were drawn with local community participation during focus group discussions in seven villages. These maps, covering a total of 270,000ha, were used to add information to maps developed using remote sensing, adding 39 land covers to the eight from our initial desk assessment. They also provided additional information on drivers of land use and land cover change, resource areas, territory claims and land status, which we were able to correlate to understand changes in forest cover. Incorporating participatory mapping in the REDD+ MRV protocol would help with initial remotely sensed land classifications, stratify an area for ground checks and measurement plots, and add other valuable social data not visible at the RS scale. Ultimately, it would provide a forum for local communities to discuss REDD+ activities and develop a better understanding of REDD+. PMID:27977685

The nature and origin of mineral coatings on volcanic rocks of the Black Mountain, Stonewall Mountain and Kane Springs Wash volcanic centers in southern Nevada

NASA Technical Reports Server (NTRS)

Taranik, J. V.; Noble, D. D.; Hsu, L. C.; Hutsinpiller, A.

1986-01-01

Four LANDSAT thematic mapping scenes in southern Nevada were requested at two different acquisition times in order to assess the effect of vegetation on the signature of the volcanic units. The remote sensing data acquisition and analysis portion are nearly completed. The LANDSAT thematic mapping data is of good quality, and image analysis techniques are so far successful in delineating areas with distinct spectral characteristics. Spectrally distinct areas were correlated with variations in surface coating and lithologies of the volcanic rocks.

Heat Capacity Mapping Mission investigation no. 25 (Tellus project)

NASA Technical Reports Server (NTRS)

Deparatesi, S. G. (Principal Investigator); Reiniger, P. (Editor)

1982-01-01

The TELLUS pilot project, utilizing 0.5 to 1.1 micron and 10.5 to 12.5 micron day and/or night imagery from the Heat Capacity Mapping Mission, is described. The application of remotely sensed data to synoptic evaluation of evapotranspiration and moisture in agricultural soils was considered. The influence of topography, soils, land use, and meteorology on surface temperature distribution was evaluated. Anthropogenic heat release was investigated. Test areas extended from semi-arid land in southern Italy to polders in the Netherlands, and from vine-growing hills in the Rhineland to grasslands in Buckinghamshire.

Mars Thermal Inertia

NASA Technical Reports Server (NTRS)

2001-01-01

This image shows the global thermal inertia of the Martian surface as measured by the Thermal Emission Spectrometer (TES) instrument on the Mars Global Surveyor. The data were acquired during the first 5000 orbits of the MGS mapping mission. The pattern of inertia variations observed by TES agrees well with the thermal inertia maps made by the Viking Infrared Thermal Mapper experiment, but the TES data shown here are at significantly higher spatial resolution (15 km versus 60 km).

The TES instrument was built by Santa Barbara Remote Sensing and is operated by Philip R. Christensen, of Arizona State University, Tempe, AZ.

The Small Bodies Thermal Mapper: An Instrument for Future Missions to Study the Compositional and Thermal Properties of Phobos

NASA Astrophysics Data System (ADS)

Donaldson Hanna, Kerri; Bowles, Neil; Calcutt, Simon; Greenhagen, Benjamin; Glotch, Timothy; Edwards, Christopher

2015-04-01

The surface of Phobos holds many keys for understanding its formation and evolution as well as the history and dynamics of the Mars-Phobos system. Phobos has been the target for numerous flyby and sample return missions in the past (e.g. Rosetta [Pajola et al., 2012] and Phobos Grunt [Kuzmin et al., 2003]). Previous telescopic and spacecraft observations have revealed a surface that is compositionally heterogeneous [e.g. Pang et al., 1978; Pollack et al., 1978, Lunine et al., 1982; Murchie and Erard, 1996; Roush and Hogan, 2001; Rivkin et al., 2002; Giuranna et al., 2011; Fraeman et al., 2014] and with large variations in surface topography [e.g. Shi et al., 2011; 2012; Willner et al., 2014]. For any future sample return mission, remote sensing observations, in particular thermal infrared observations, will be key in characterising possible landing/sampling sites and placing returned samples into their geological context. The European Space Agency has identified Phootprint, a European sample return mission to Phobos, as a candidate mission of the Mars Robotic Exploration Preparation Programme 2 (MREP-2). Using this mission concept as a baseline, we have studied the options for a simple multichannel radiometer to provide thermal mapping and compositional remote sensing data. By mapping Phobos' diurnal thermal response, a thermal imaging instrument will provide key information on the nature of the surface and near sub-surface (the thermal inertia) and composition. These measurements will support visible imaging observations to determine landing sites that are compatible with the spacecraft's sampling mechanisms. Remotely sensed thermal maps of the surface will also prevent otherwise unpredictable thermal loads on the spacecraft due to variations in local topography and albedo. The instrument design resulting from this study, the Small Bodies Thermal Mapper (SBTM), is a compact multichannel radiometer and thermal imager. The SBTM is based on the Compact Modular Sounder (CMS) instrument currently flying on the UK's TechDemoSat-1 spacecraft in low Earth orbit. This gives a significant level of flight heritage with optimisations for the expected Phobos environment. The SBTM instrument uses a two-dimensional uncooled thermal detector array to provide imaging of Phobos. In addition, ten narrow-band infrared filters located around diagnostic mineral spectral features provide additional compositional discrimination. For the SBTM, the optimisations studied include options for the detector and filters required to cover the wide range of diurnal temperatures expected at Phobos (e.g. 130 to > 300 K) [e.g. Kuzmin et al., 2003]. Options studied include the use of a broadband micro bolometer array (e.g. http://www.ulis-ir.com/uploads/Products/PICO640E-041-BroadBand.pdf) or a thermopile detector [Foote et al., 1998] array. Optimisation of filter band passes for remote measurement of composition is also considered, based on mineral spectra measured under simulated Phobos environment [e.g. Glotch et al., 2014].

Cooperative studies between the United States of America and the People's Republic of China on applications of remote sensing to surveying and mapping

USGS Publications Warehouse

Lauer, Donald T.; Chu, Liangcai

1992-01-01

A Protocol established between the National Bureau of Surveying and Mapping, People's Republic of China (PRC) and the U.S. Geological Survey, United States of America (US), resulted in the exchange of scientific personnel, technical training, and exploration of the processing of remotely sensed data. These activities were directed toward the application of remotely sensed data to surveying and mapping. Data were processed and various products were generated for the Black Hills area in the US and the Ningxiang area of the PRC. The results of these investigations defined applicable processes in the creation of satellite image maps, land use maps, and the use of ancillary data for further map enhancements.

Software for a GPS-Reflection Remote-Sensing System

NASA Technical Reports Server (NTRS)

Lowe, Stephen

2003-01-01

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

Mapping irrigated areas of Ghana using fusion of 30 m and 250 m resolution remote-sensing data

USGS Publications Warehouse

Gumma, M.K.; Thenkabail, P.S.; Hideto, F.; Nelson, A.; Dheeravath, V.; Busia, D.; Rala, A.

2011-01-01

Maps of irrigated areas are essential for Ghana's agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+) data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to map irrigated agricultural areas as well as other land use/land cover (LULC) classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI) pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks) and dug-outs (in river bottoms) that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha) was 20-57% higher than irrigated areas reported by Ghana's Irrigation Development Authority (GIDA). This was because of the uncertainties involved in factors such as: (a) absence of shallow irrigated area statistics in GIDA statistics, (b) non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c) errors of omissions and commissions in the remote sensing approach, and (d) comparison involving widely varying data types, methods, and approaches used in determining irrigated area statistics using GIDA and remote sensing. Extensive field campaigns to help in better classification and validation of irrigated areas using high (30 m ) to very high (<5 m) resolution remote sensing data that are fused with multi temporal data like MODIS are the way forward. This is especially true in accounting for small yet contiguous patches of irrigated areas from dug-wells and dug-outs. ?? 2011 by the authors.

Assessments of urban growth in the Tampa Bay watershed using remote sensing data

USGS Publications Warehouse

Xian, G.; Crane, M.

2005-01-01

Urban development has expanded rapidly in the Tampa Bay area of west-central Florida over the past century. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. This research utilizes an innovative approach for mapping urban extent and its changes through determining impervious surfaces from Landsat satellite remote sensing data. By 2002, areas with subpixel impervious surface greater than 10% accounted for approximately 1800 km2, or 27 percent of the total watershed area. The impervious surface area increases approximately three-fold from 1991 to 2002. The resulting imperviousness data are used with a defined suite of geospatial data sets to simulate historical urban development and predict future urban and suburban extent, density, and growth patterns using SLEUTH model. Also examined is the increasingly important influence that urbanization and its associated imperviousness extent have on the individual drainage basins of the Tampa Bay watershed.

Alteration mineral mapping and metallogenic prediction using CASI/SASI airborne hyperspectral data in Mingshujing area of Gansu Province, NW China

NASA Astrophysics Data System (ADS)

Sun, Yu; Zhao, Yingjun; Qin, Kai; Tian, Feng

2016-04-01

Hyperspectral remote sensing is a frontier of remote sensing. Due to its advantage of integrated image with spectrum, it can realize objects identification, superior to objects classification of multispectral remote sensing. Taken the Mingshujing area in Gansu Province of China as an example, this study extracted the alteration minerals and thus to do metallogenic prediction using CASI/SASI airborne hyperspectral data. The Mingshujing area, located in Liuyuan region of Gansu Province, is dominated by middle Variscan granites and Indosinian granites, with well developed EW- and NE-trending faults. In July 2012, our project team obtained the CASI/SASI hyperspectral data of Liuyuan region by aerial flight. The CASI hyperspectral data have 32 bands and the SASI hyperspectral data have 88 bands, with spectral resolution of 15nm for both. The hyperspectral raw data were first preprocessed, including radiometric correction and geometric correction. We then conducted atmospheric correction using empirical line method based on synchronously measured ground spectra to obtain hyperspectral reflectance data. Spectral dimension of hyperspectral data was reduced by the minimum noise fraction transformation method, and then purity pixels were selected. After these steps, image endmember spectra were obtained. We used the endmember spectrum election method based on expert knowledge to analyze the image endmember spectra. Then, the mixture tuned matched filter (MTMF) mapping method was used to extract mineral information, including limonite, Al-rich sericite, Al-poor sericite and chlorite. Finally, the distribution of minerals in the Mingshujing area was mapped. According to the distribution of limonite and Al-rich sericite mapped by CASI/SASI hyperspectral data, we delineated five gold prospecting areas, and further conducted field verification in these areas. It is shown that there are significant gold mineralized anomalies in surface in the Baixianishan and Xitan prospecting areas. The application of CASI/SASI airborne hyperspectral remote sensing data in the metallogenic prediction of the Mingshujing area has achieved ideal results, indicative of their wide application potential in geological research.

Hyperspatial Thermal Imaging of Surface Hydrothermal Features at Pilgrim Hot Springs, Alaska using a small Unmanned Aerial System (sUAS)

NASA Astrophysics Data System (ADS)

Haselwimmer, C. E.; Wilson, R.; Upton, C.; Prakash, A.; Holdmann, G.; Walker, G.

2013-12-01

Thermal remote sensing provides a valuable tool for mapping and monitoring surface hydrothermal features associated with geothermal activity. The increasing availability of low-cost, small Unmanned Aerial Systems (sUAS) with integrated thermal imaging sensors offers a means to undertake very high spatial resolution (hyperspatial), quantitative thermal remote sensing of surface geothermal features in support of exploration and long-term monitoring efforts. Results from the deployment of a quadcopter sUAS equipped with a thermal camera over Pilgrim Hot Springs, Alaska for detailed mapping and heat flux estimation for hot springs, seeps, and thermal pools are presented. Hyperspatial thermal infrared imagery (4 cm pixels) was acquired over Pilgrim Hot Springs in July 2013 using a FLIR TAU 640 camera operating from an Aeryon Scout sUAS flying at an altitude of 40m. The registered and mosaicked thermal imagery is calibrated to surface temperature values using in-situ measurements of uniform blackbody tarps and the temperatures of geothermal and other surface pools acquired with a series of water temperature loggers. Interpretation of the pre-processed thermal imagery enables the delineation of hot springs, the extents of thermal pools, and the flow and mixing of individual geothermal outflow plumes with an unprecedented level of detail. Using the surface temperatures of thermal waters derived from the FLIR data and measured in-situ meteorological parameters the hot spring heat flux and outflow rate is calculated using a heat budget model for a subset of the thermal drainage. The heat flux/outflow rate estimates derived from the FLIR data are compared against in-situ measurements of the hot spring outflow rate recorded at the time of the thermal survey.

Preliminary determination of geothermal working area based on Thermal Infrared and Synthetic Aperture Radar (SAR) remote sensing

NASA Astrophysics Data System (ADS)

Agoes Nugroho, Indra; Kurniawahidayati, Beta; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Remote sensing is one of the methods for geothermal exploration. This method can be used to map the geological structures, manifestations, and predict the geothermal potential area. The results from remote sensing were used as guidance for the next step exploration. Analysis of target in remote sensing is an efficient method to delineate geothermal surface manifestation without direct contact to the object. The study took a place in District Merangin, Jambi Province, Indonesia. The area was selected due to existing of Merangin volcanic complex composed by Mounts Sumbing and Hulunilo with surface geothermal manifestations presented by hot springs and hot pools. The location of surface manifestations could be related with local and regional structures of Great Sumatra Fault. The methods used in this study were included identification of volcanic products, lineament extraction, and lineament density quantification. The objective of this study is to delineate the potential zones for sitting the geothermal working site based on Thermal Infrared and Synthetic Aperture Radar (SAR) sensors. The lineament-related to geological structures, was aimed for high lineament density, is using ALOS - PALSAR (Advanced Land Observing Satellite - The Phased Array type L-band Synthetic Aperture Radar) level 1.1. The Normalized Difference Vegetation Index (NDVI) analysis was used to predict the vegetation condition using Landsat 8 OLI-TIRS (The Operational Land Imager - Thermal Infrared Sensor). The brightness temperature was extracted from TIR band to estimate the surface temperature. Geothermal working area identified based on index overlay method from extracted parameter of remote sensing data was located at the western part of study area (Graho Nyabu area). This location was identified because of the existence of high surface temperature about 30°C, high lineament density about 4 - 4.5 km/km2 and low NDVI values less than 0.3.

Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties

NASA Technical Reports Server (NTRS)

Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.

1997-01-01

This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface soil moisture. Validation of results using field measured values and soil texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.

Paleogeodesy of the Southern Santa Cruz Mountains Frontal Thrusts, Silicon Valley, CA

NASA Astrophysics Data System (ADS)

Aron, F.; Johnstone, S. A.; Mavrommatis, A. P.; Sare, R.; Hilley, G. E.

2015-12-01

We present a method to infer long-term fault slip rate distributions using topography by coupling a three-dimensional elastic boundary element model with a geomorphic incision rule. In particular, we used a 10-m-resolution digital elevation model (DEM) to calculate channel steepness (ksn) throughout the actively deforming southern Santa Cruz Mountains in Central California. We then used these values with a power-law incision rule and the Poly3D code to estimate slip rates over seismogenic, kilometer-scale thrust faults accommodating differential uplift of the relief throughout geologic time. Implicit in such an analysis is the assumption that the topographic surface remains unchanged over time as rock is uplifted by slip on the underlying structures. The fault geometries within the area are defined based on surface mapping, as well as active and passive geophysical imaging. Fault elements are assumed to be traction-free in shear (i.e., frictionless), while opening along them is prohibited. The free parameters in the inversion include the components of the remote strain-rate tensor (ɛij) and the bedrock resistance to channel incision (K), which is allowed to vary according to the mapped distribution of geologic units exposed at the surface. The nonlinear components of the geomorphic model required the use of a Markov chain Monte Carlo method, which simulated the posterior density of the components of the remote strain-rate tensor and values of K for the different mapped geologic units. Interestingly, posterior probability distributions of ɛij and K fall well within the broad range of reported values, suggesting that the joint use of elastic boundary element and geomorphic models may have utility in estimating long-term fault slip-rate distributions. Given an adequate DEM, geologic mapping, and fault models, the proposed paleogeodetic method could be applied to other crustal faults with geological and morphological expressions of long-term uplift.

The application of automatic recognition techniques in the Apollo 9 SO-65 experiment

NASA Technical Reports Server (NTRS)

Macdonald, R. B.

1970-01-01

A synoptic feature analysis is reported on Apollo 9 remote earth surface photographs that uses the methods of statistical pattern recognition to classify density points and clusterings in digital conversion of optical data. A computer derived geological map of a geological test site indicates that geological features of the range are separable, but that specific rock types are not identifiable.

Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in southern California

Treesearch

Sarah A. Lewis; Leigh B. Lentile; Andrew T. Hudak; Peter R. Robichaud; Penelope Morgan; Michael J. Bobbitt

2007-01-01

Wildfire effects on the ground surface are indicative of the potential for post-fire watershed erosion response. Areas with remaining organic ground cover will likely experience less erosion than areas of complete ground cover combustion or exposed mineral soil. The Simi and Old fires burned ~67,000 ha in southern California in 2003. Burn severity indices calculated...

Technical note: A simple approach for efficient collection of field reference data for calibrating remote sensing mapping of northern wetlands

NASA Astrophysics Data System (ADS)

Gålfalk, Magnus; Karlson, Martin; Crill, Patrick; Bousquet, Philippe; Bastviken, David

2018-03-01

The calibration and validation of remote sensing land cover products are highly dependent on accurate field reference data, which are costly and practically challenging to collect. We describe an optical method for collection of field reference data that is a fast, cost-efficient, and robust alternative to field surveys and UAV imaging. A lightweight, waterproof, remote-controlled RGB camera (GoPro HERO4 Silver, GoPro Inc.) was used to take wide-angle images from 3.1 to 4.5 m in altitude using an extendable monopod, as well as representative near-ground (< 1 m) images to identify spectral and structural features that correspond to various land covers in present lighting conditions. A semi-automatic classification was made based on six surface types (graminoids, water, shrubs, dry moss, wet moss, and rock). The method enables collection of detailed field reference data, which is critical in many remote sensing applications, such as satellite-based wetland mapping. The method uses common non-expensive equipment, does not require special skills or training, and is facilitated by a step-by-step manual that is included in the Supplement. Over time a global ground cover database can be built that can be used as reference data for studies of non-forested wetlands from satellites such as Sentinel 1 and 2 (10 m pixel size).

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

USGS Publications Warehouse

McShane, Ryan R.; Driscoll, Katelyn P.; Sando, Roy

2017-09-27

Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ETa estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ETa and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ETa that are currently applied successfully in the United States. The METRIC model can produce maps of ETa at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ETa against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ETa. The SSEBop model has been used to produce maps of ETa over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ETa estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ETa estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth EngineTM has been used to implement METRIC with automated calibration for regional-scale estimates of ETa using Landsat data. The U.S. Geological Survey also is using Google Earth EngineTM to implement SSEBop for estimating ETa in the United States at a continental scale using Landsat data.

Lithological mapping of Kanjamalai hill using hyperspectral remote sensing tools in Salem district, Tamil Nadu, India

NASA Astrophysics Data System (ADS)

Arulbalaji, Palanisamy; Balasubramanian, Gurugnanam

2017-07-01

This study uses advanced spaceborne thermal emission and reflection radiometer (ASTER) hyperspectral remote sensing techniques to discriminate rock types composing Kanjamalai hill located in the Salem district of Tamil Nadu, India. Kanjamalai hill is of particular interest because it contains economically viable iron ore deposits. ASTER hyperspectral data were subjected to principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF) to improve identification of lithologies remotely and to compare these digital data results with published geologic maps. Hyperspectral remote sensing analysis indicates that PCA (R∶G∶B=2∶1∶3), MNF (R∶G∶B=3∶2∶1), and ICA (R∶G∶B=1∶3∶2) provide the best band combination for effective discrimination of lithological rock types composing Kanjamalai hill. The remote sensing-derived lithological map compares favorably with a published geological map from Geological Survey of India and has been verified with ground truth field investigations. Therefore, ASTER data-based lithological mapping provides fast, cost-effective, and accurate geologic data useful for lithological discrimination and identification of ore deposits.

Vegetation Water Content Mapping for Agricultural Regions in SMAPVEX16

NASA Astrophysics Data System (ADS)

White, W. A.; Cosh, M. H.; McKee, L.; Berg, A. A.; McNairn, H.; Hornbuckle, B. K.; Colliander, A.; Jackson, T. J.

2017-12-01

Vegetation water content impacts the ability of L-band radiometers to measure surface soil moisture. Therefore it is necessary to quantify the amount of water held in surface vegetation for an accurate soil moisture remote sensing retrieval. A methodology is presented for generating agricultural vegetation water content maps using Landsat 8 scenes for agricultural fields of Iowa and Manitoba for the Soil Moisture Active Passive Validation Experiments in 2016 (SMAPVEX16). Manitoba has a variety of row crops across the region, and the study period encompasses the time frame from emergence to reproduction, as well as a forested region. The Iowa study site is dominated by corn and soybeans, presenting an easier challenge. Ground collection of vegetation biomass and water content were also collected to provide a ground truth data source. Errors for the resulting vegetation water content maps ranged depending upon crop type, but generally were less than 15% of the total plant water content per crop type. Interpolation is done between Landsat overpasses to produce daily vegetation water content maps for the summer of 2016 at a 30 meter resolution.

Fusion of radar and optical data for mapping and monitoring of water bodies

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyn

2017-10-01

Remote sensing techniques owe their great popularity to the possibility to obtain of rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. The main areas of interest for remote sensing research had always been concerned with environmental studies, especially water bodies monitoring. Many methods that are using visible and near- an infrared band of the electromagnetic spectrum had been already developed to detect surface water reservoirs. Moreover, the usage of an image obtained in visible and infrared spectrum allows quality monitoring of water bodies. Nevertheless, retrieval of water boundaries and mapping surface water reservoirs with optical sensors is still quite demanding. Therefore, the microwave data could be the perfect complement to data obtained with passive optical sensors to detect and monitor aquatic environment especially surface water bodies. This research presents the methodology to detect water bodies with open- source satellite imagery acquired with both optical and microwave sensors. The SAR Sentinel- 1 and multispectral Sentinel- 2 imagery were used to detect and monitor chosen reservoirs in Poland. In the research Level, 1 Sentinel- 2 data and Level 1 SAR images were used. SAR data were mainly used for mapping water bodies. Next, the results of water boundaries extraction with Sentinel-1 data were compared to results obtained after application of modified spectral indices for Sentinel- 2 data. The multispectral optical data can be used in the future for the evaluation of the quality of the reservoirs. Preliminary results obtained in the research had shown, that the fusion of data obtained with optical and microwave sensors allow for the complex detection of water bodies and could be used in the future quality monitoring of water reservoirs.

Evaluating the potential for remote bathymetric mapping of a turbid, sand-bed river: 1. Field spectroscopy and radiative transfer modeling

USGS Publications Warehouse

Legleiter, C.J.; Kinzel, P.J.; Overstreet, B.T.

2011-01-01

Remote sensing offers an efficient means of mapping bathymetry in river systems, but this approach has been applied primarily to clear-flowing, gravel bed streams. This study used field spectroscopy and radiative transfer modeling to assess the feasibility of spectrally based depth retrieval in a sand-bed river with a higher suspended sediment concentration (SSC) and greater water turbidity. Attenuation of light within the water column was characterized by measuring the amount of downwelling radiant energy at different depths and calculating a diffuse attenuation coefficient, Kd. Attenuation was strongest in blue and near-infrared bands due to scattering by suspended sediment and absorption by water, respectively. Even for red wavelengths with the lowest values of Kd, only a small fraction of the incident light propagated to the bed, restricting the range of depths amenable to remote sensing. Spectra recorded above the water surface were used to establish a strong, linear relationship (R2 = 0.949) between flow depth and a simple band ratio; even under moderately turbid conditions, depth remained the primary control on reflectance. Constraints on depth retrieval were examined via numerical modeling of radiative transfer within the atmosphere and water column. SSC and sensor radiometric resolution limited both the maximum detectable depth and the precision of image-derived depth estimates. Thus, although field spectra indicated that the bathymetry of turbid channels could be remotely mapped, model results implied that depth retrieval in sediment-laden rivers would be limited to shallow depths (on the order of 0.5 m) and subject to a significant degree of uncertainty. ?? 2011 by the American Geophysical Union.

Flood Vulnerability Analysis of the part of Karad Region, Satara District, Maharashtra using Remote Sensing and Geographic Information System technique

NASA Astrophysics Data System (ADS)

Warghat, Sumedh R.; Das, Sandipan; Doad, Atul; Mali, Sagar; Moon, Vishal S.

2012-07-01

Karad City is situated on the bank of confluence of river Krishna & Koyana, which is severely flood prone area. The floodwaters enter the city through the roads and disrupt the infrastructure in the whole city. Furthermore, due to negligence of the authorities and unplanned growth of the city, the people living in the city have harnessed the natural flow of water by constructing unnecessary embankments in the river Koyna. Due to this reason now river koyna is flowing in the form of a narrow channel, which very easily over-flows during very minor flooding.Flood Vulnerabilty Analysis has been done for the karad region of satara district, maharashtra using remote sensing and geographic information system technique. The aim of this study is to identify flood vulnerability zone by using GIS and RS technique and an attempt has been to demonstrat the application of remote sensing and GIS in order to map flood vulnerabilty area by utilizing ArcMap, and Erdas software. Flood vulnerabilty analysis of part the Karad Regian of Satara District, Maharashtra has been carried out with the objectives - Identify the Flood Prone area in the Koyana and Krishna river basin, Calculate surface runoff and Delineate flood sensitive areas. Delineate classified hazard Map, Evaluate the Flood affected area, Prepare the Flood Vulnerability Map by utilizing Remote Sensing and GIS technique. (C.J. Kumanan;S.M. Ramasamy)The study is based on GIS and spatial technique is used for analysis and understanding of flood problem in Karad Tahsil. The flood affected areas of the different magnitude has been identified and mapped using Arc GIS software. The analysis is useful for local planning authority for identification of risk areas and taking proper decision in right moment. In the analysis causative factors for flooding in watershed are taken into account as annual rainfall, size of watershed, basin slope, drainage density of natural channels and land use. (Dinand Alkema; Farah Aziz.)This study of flood vulnerable area determination in a part of Karad Tahsil is employed to illustrate the different approaches.

Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2009-10-01

Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/land cover. This paper presents different approaches to attain an optimal land use/land cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/land cover map was not sufficient for the delineation of HRUs, since the agricultural land use/land cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Subsequently the digital classification on fused data (ASAR and ASTER) were attempted to map land use/land cover classes with emphasis to delineate the paddy and maize crops but the supervised classification over fused datasets did not provide the desired accuracy and proper delineation of paddy and maize crops. Eventually, we adopted a visual classification approach on fused data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modeling.

Thematic and positional accuracy assessment of digital remotely sensed data

Treesearch

Russell G. Congalton

2007-01-01

Accuracy assessment or validation has become a standard component of any land cover or vegetation map derived from remotely sensed data. Knowing the accuracy of the map is vital to any decisionmaking performed using that map. The process of assessing the map accuracy is time consuming and expensive. It is very important that the procedure be well thought out and...

Mapping of submerged vegetation using remote sensing technology

NASA Technical Reports Server (NTRS)

Savastano, K. J.; Faller, K. H.; Mcfadin, L. W.; Holley, H.

1981-01-01

Techniques for mapping submerged sea grasses using aircraft supported remote sensors are described. The 21 channel solid state array spectroradiometer was successfully used as a remote sensor in the experiment in that the system operated without problem and obtained data. The environmental conditions of clear water, bright sandy bottom and monospecific vegetation (Thalassia) were ideal.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

Global radiation maps and their modulation by clouds. - An assessment of limitations and deficiencies in global modelling

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Stubenrauch, Claudia; Raschke, Erhard

2010-05-01

Satellite sensed solar and infrared broadband radiation maps at the top of the atmosphere (ToA) usually serve as reference and constrains to global modelling. Complimentary radiation maps at the surface are less certain, as they require accurate knowledge about atmospheric and environmental properties. Despite differences among multi-decadal data-projects of ISCCP, the SRB and the CERES, their diversity is small in comparison to efforts in global modelling. Based on simulations for the IPCC fourth assessment, clear biases on a regional and seasonal basis are identified and illustrate deficiencies in the representation of clouds. These deficiencies are explored in the context of available cloud data from passive and active remote sensing from space.

Mapping wetlands and surface water in the Prairie Pothole Region of North America: Chapter 16

USGS Publications Warehouse

Rover, Jennifer R.; Mushet, David M.

2015-01-01

The Prairie Pothole Region (PPR) is one of the most highly productive wetland regions in the world. Prairie Pothole wetlands serve as a primary feeding and breeding habitat for more than one-half of North America’s waterfowl population, as well as a variety of songbirds, waterbirds, shorebirds, and other wildlife. During the last century, extensive land conversions from grassland with wetlands to cultivated cropland and grazed pastureland segmented and reduced wetland habitat. Inventorying and characterizing remaining wetland habitat is critical for the management of wetland ecosystem services. Remote sensing technologies are often utilized for mapping and monitoring wetlands. This chapter presents background specific to the PPR and discusses approaches employed in mapping its wetlands before presenting a case study.

@KarlTheFog has been mapped!

USGS Publications Warehouse

Torregrosa, Alicia

2016-01-01

Within the world of mapping, clouds are a pesky interference to be removed from satellite remote sensed imagery.  However, to many of us, that is a waste of pixels. Cloud maps are becoming increasingly valuable in the quest to understand land cover change and surface processes. In coastal California, the dynamic summertime interactions between air masses, the ocean, and topography result in blankets of fog and low clouds flowing into low lying areas of the San Francisco Bay Area. The low clouds and fog advected from the Pacific bring moisture and shade to coastal ecosystems. This acts to reduce temperatures and evapotranspiration stress during the otherwise arid Mediterranean climate season, in turn impacting vegetation distribution, irrigation needs, and urban energy consumption.

Mapping snow depth in alpine terrain with remotely piloted aerial systems and structure-from-motion photogrammetry - first results from a pilot study

NASA Astrophysics Data System (ADS)

Adams, Marc; Fromm, Reinhard; Bühler, Yves; Bösch, Ruedi; Ginzler, Christian

2016-04-01

Detailed information on the spatio-temporal distribution of seasonal snow in the alpine terrain plays a major role for the hydrological cycle, natural hazard management, flora and fauna, as well as tourism. Current methods are mostly only valid on a regional scale or require a trade-off between the data's availability, cost and resolution. During a one-year pilot study, we investigated the potential of remotely piloted aerial systems (RPAS) and structure-from-motion photogrammetry for snow depth mapping. We employed multi-copter and fixed-wing RPAS, equipped with different low-cost, off-the shelf sensors, at four test sites in Austria and Switzerland. Over 30 flights were performed during the winter 2014/15, where different camera settings, filters and lenses, as well as data collection routines were tested. Orthophotos and digital surface models (DSM) where calculated from the imagery using structure-from-motion photogrammetry software. Snow height was derived by subtracting snow-free from snow-covered DSMs. The RPAS-results were validated against data collected using a variety of well-established remote sensing (i.e. terrestrial laser scanning, large frame aerial sensors) and in-situ measurement techniques. The results show, that RPAS i) are able to map snow depth within accuracies of 0.07-0.15 m root mean square error (RMSE), when compared to traditional in-situ data; ii) can be operated at lower cost, easier repeatability, less operational constraints and higher GSD than large frame aerial sensors on-board manned aircraft, while achieving significantly higher accuracies; iii) are able to acquire meaningful data even under harsh environmental conditions above 2000 m a.s.l. (turbulence, low temperature and high irradiance, low air density). While providing a first prove-of-concept, the study also showed future challenges and limitations of RPAS-based snow depth mapping, including a high dependency on correct co-registration of snow-free and snow-covered height measurements, as well as a significant impact of the underlying vegetation and illumination of the snow surface on the fidelity of the results.

Expading fluvial remote sensing to the riverscape: Mapping depth and grain size on the Merced River, California

NASA Astrophysics Data System (ADS)

Richardson, Ryan T.

This study builds upon recent research in the field of fluvial remote sensing by applying techniques for mapping physical attributes of rivers. Depth, velocity, and grain size are primary controls on the types of habitat present in fluvial ecosystems. This thesis focuses on expanding fluvial remote sensing to larger spatial extents and sub-meter resolutions, which will increase our ability to capture the spatial heterogeneity of habitat at a resolution relevant to individual salmonids and an extent relevant to species. This thesis consists of two chapters, one focusing on expanding the spatial extent over which depth can be mapped using Optimal Band Ratio Analysis (OBRA) and the other developing general relations for mapping grain size from three-dimensional topographic point clouds. The two chapters are independent but connected by the overarching goal of providing scientists and managers more useful tools for quantifying the amount and quality of salmonid habitat via remote sensing. The OBRA chapter highlights the true power of remote sensing to map depths from hyperspectral images as a central component of watershed scale analysis, while also acknowledging the great challenges involved with increasing spatial extent. The grain size mapping chapter establishes the first general relations for mapping grain size from roughness using point clouds. These relations will significantly reduce the time needed in the field by eliminating the need for independent measurements of grain size for calibrating the roughness-grain size relationship and thus making grain size mapping with SFM more cost effective for river restoration and monitoring. More data from future studies are needed to refine these relations and establish their validity and generality. In conclusion, this study adds to the rapidly growing field of fluvial remote sensing and could facilitate river research and restoration.

Wind Streaks on Earth; Exploration and Interpretation

NASA Astrophysics Data System (ADS)

Cohen-Zada, Aviv Lee; Blumberg, Dan G.; Maman, Shimrit

2015-04-01

Wind streaks, one of the most common aeolian features on planetary surfaces, are observable on the surface of the planets Earth, Mars and Venus. Due to their reflectance properties, wind streaks are distinguishable from their surroundings, and they have thus been widely studied by remote sensing since the early 1970s, particularly on Mars. In imagery, these streaks are interpreted as the presence - or lack thereof - of small loose particles on the surface deposited or eroded by wind. The existence of wind streaks serves as evidence for past or present active aeolian processes. Therefore, wind streaks are thought to represent integrative climate processes. As opposed to the comprehensive and global studies of wind streaks on Mars and Venus, wind streaks on Earth are understudied and poorly investigated, both geomorphologically and by remote sensing. The aim of this study is, thus, to fill the knowledge gap about the wind streaks on Earth by: generating a global map of Earth wind streaks from modern high-resolution remotely sensed imagery; incorporating the streaks in a geographic information system (GIS); and overlaying the GIS layers with boundary layer wind data from general circulation models (GCMs) and data from the ECMWF Reanalysis Interim project. The study defines wind streaks (and thereby distinguishes them from other aeolian features) based not only on their appearance in imagery but more importantly on their surface appearance. This effort is complemented by a focused field investigation to study wind streaks on the ground and from a variety of remotely sensed images (both optical and radar). In this way, we provide a better definition of the physical and geomorphic characteristics of wind streaks and acquire a deeper knowledge of terrestrial wind streaks as a means to better understand global and planetary climate and climate change. In a preliminary study, we detected and mapped over 2,900 wind streaks in the desert regions of Earth distributed in approximately 500 sites. Most terrestrial wind streaks are formed on a relatively young geological surface and are concentrated along the equator (± 30°). They are categorized by the combination of their planform and reflectance; with linear-bright and dark are the most common. A site-specific examination of remote-sensing effects on wind streaks identification has been conducted. The results thus far, indicate that in images with varying spatial and spectral specifications some wind streaks are actually composed of other aeolian bedforms, especially dunes. Specific regions of the Earth were then compared qualitatively to surface wind data extracted from a general circulation model. Understanding the mechanism and spatial and temporal distribution of wind streak formation is important not only for understanding surface modifications in the geomorphological context but also for shedding light on past and present climatic processes and atmospheric circulation on Earth. This study yields an explanation for wind streaks as a geomorphological feature. Moreover, it is in this planet-wide geomorphological research ability to lay down the foundations for comparative planetary research.

Mapping variations in weight percent silica measured from multispectral thermal infrared imagery - Examples from the Hiller Mountains, Nevada, USA and Tres Virgenes-La Reforma, Baja California Sur, Mexico

USGS Publications Warehouse

Hook, S.J.; Dmochowski, J.E.; Howard, K.A.; Rowan, L.C.; Karlstrom, K.E.; Stock, J.M.

2005-01-01

Remotely sensed multispectral thermal infrared (8-13 ??m) images are increasingly being used to map variations in surface silicate mineralogy. These studies utilize the shift to longer wavelengths in the main spectral feature in minerals in this wavelength region (reststrahlen band) as the mineralogy changes from felsic to mafic. An approach is described for determining the amount of this shift and then using the shift with a reference curve, derived from laboratory data, to remotely determine the weight percent SiO2 of the surface. The approach has broad applicability to many study areas and can also be fine-tuned to give greater accuracy in a particular study area if field samples are available. The approach was assessed using airborne multispectral thermal infrared images from the Hiller Mountains, Nevada, USA and the Tres Virgenes-La Reforma, Baja California Sur, Mexico. Results indicate the general approach slightly overestimates the weight percent SiO2 of low silica rocks (e.g. basalt) and underestimates the weight percent SiO2 of high silica rocks (e.g. granite). Fine tuning the general approach with measurements from field samples provided good results for both areas with errors in the recovered weight percent SiO2 of a few percent. The map units identified by these techniques and traditional mapping at the Hiller Mountains demonstrate the continuity of the crystalline rocks from the Hiller Mountains southward to the White Hills supporting the idea that these ranges represent an essentially continuous footwall block below a regional detachment. Results from the Baja California data verify the most recent volcanism to be basaltic-andesite. ?? 2005 Elsevier Inc. All rights reserved.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey (Editor); Lobitz, Brad; Spanner, Michael; Strub, Richard; Lobitz, Brad

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

Polar Applications of Spaceborne Scatterometers.

PubMed

Long, David G

2017-05-01

Wind scatterometers were originally developed for observation of near-surface winds over the ocean. They retrieve wind indirectly by measuring the normalized radar cross section ( σ o ) of the surface, and estimating the wind via a geophysical model function relating σ o to the vector wind. The σ o measurements have proven to be remarkably capable in studies of the polar regions where they can map snow cover; detect the freeze/thaw state of forest, tundra, and ice; map and classify sea ice; and track icebergs. Further, a long time series of scatterometer σ o observations is available to support climate studies. In addition to fundamental scientific research, scatterometer data are operationally used for sea-ice mapping to support navigation. Scatterometers are, thus, invaluable tools for monitoring the polar regions. In this paper, a brief review of some of the polar applications of spaceborne wind scatterometer data is provided. The paper considers both C-band and Ku-band scatterometers, and the relative merits of fan-beam and pencil-beam scatterometers in polar remote sensing are discussed.

Polar Applications of Spaceborne Scatterometers

PubMed Central

Long, David G.

2017-01-01

Wind scatterometers were originally developed for observation of near-surface winds over the ocean. They retrieve wind indirectly by measuring the normalized radar cross section (σo) of the surface, and estimating the wind via a geophysical model function relating σo to the vector wind. The σo measurements have proven to be remarkably capable in studies of the polar regions where they can map snow cover; detect the freeze/thaw state of forest, tundra, and ice; map and classify sea ice; and track icebergs. Further, a long time series of scatterometer σo observations is available to support climate studies. In addition to fundamental scientific research, scatterometer data are operationally used for sea-ice mapping to support navigation. Scatterometers are, thus, invaluable tools for monitoring the polar regions. In this paper, a brief review of some of the polar applications of spaceborne wind scatterometer data is provided. The paper considers both C-band and Ku-band scatterometers, and the relative merits of fan-beam and pencil-beam scatterometers in polar remote sensing are discussed. PMID:28919936

Remote sensing: a tool for park planning and management

USGS Publications Warehouse

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

Remote sensing may be defined as the science of imaging or measuring objects from a distance. More commonly, however, the term is used in reference to the acquisition and use of photographs, photo-like images, and other data acquired from aircraft and satellites. Thus, remote sensing includes the use of such diverse materials as photographs taken by hand from a light aircraft, conventional aerial photographs obtained with a precision mapping camera, satellite images acquired with sophisticated scanning devices, radar images, and magnetic and gravimetric data that may not even be in image form. Remotely sensed images may be color or black and white, can vary in scale from those that cover only a few hectares of the earth's surface to those that cover tens of thousands of square kilometers, and they may be interpreted visually or with the assistance of computer systems. This article attempts to describe several of the commonly available types of remotely sensed data, to discuss approaches to data analysis, and to demonstrate (with image examples) typical applications that might interest managers of parks and natural areas.

Sensible Success

NASA Technical Reports Server (NTRS)

2001-01-01

Commercial remote sensing uses satellite imagery to provide valuable information about the planet's features. By capturing light reflected from the Earth's surface with cameras or sensor systems, usually mounted on an orbiting satellite, data is obtained for business enterprises with an interest in land feature distribution. Remote sensing is practical when applied to large-area coverage, such as agricultural monitoring, regional mapping, environmental assessment, and infrastructure planning. For example, cellular service providers use satellite imagery to select the most ideal location for a communication tower. Crowsey Incorporated has the ability to use remote sensing capabilities to conduct spatial geographic visualizations and other remote-sensing services. Presently, the company has found a demand for these services in the area of litigation support. By using spatial information and analyses, Crowsey helps litigators understand and visualize complex issues and then to communicate a clear argument, with complete indisputable evidence. Crowsey Incorporated is a proud partner in NASA's Mississippi Space Commerce Initiative, with research offices at the John C. Stennis Space Center.

Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

NASA Astrophysics Data System (ADS)

Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

2016-06-01

The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

Exploring Pacific Seamounts through Telepresence Mapping on the NOAA Ship Okeanos Explorer

NASA Astrophysics Data System (ADS)

Lobecker, E.; Malik, M.; Sowers, D.; Kennedy, B. R.

2016-12-01

Telepresence utilizes modern computer networks and a high bandwidth satellite connection to enable remote users to participate virtually in ocean research and exploration cruises. NOAA's Office of Ocean Exploration and Research (OER) has been leveraging telepresence capabilities since the early 2000s. Through telepresence, remote users have provided support for operations planning and execution, troubleshooting hardware and software, and data interpretation during exploratory ocean mapping and remotely operated vehicle missions conducted by OER. The potential for this technology's application to immersive data acquisition and processing during mapping missions, however, has not yet been fully realized. We report the results of the application of telepresence to an 18-day 24 hour / day seafloor mapping expedition with the NOAA Ship Okeanos Explorer. The mapping team was split between shipboard and shore-based mission team members based at the Exploration Command Center at the University of New Hampshire. This cruise represented the third dedicated mapping cruise in a multi-year NOAA Campaign to Address the Pacific monument Science, Technology, and Ocean Needs (CAPSTONE). Cruise objectives included mapping several previously unmapped seamounts in the Wake Atoll Unit of the recently expanded Pacific Remote Islands Marine National Monument, and mapping of prominent seamount, ridge, and fracture zone features during transits. We discuss (1) expanded shore-based data processing of multiple sonar data streams leading to enhanced, rapid, initial site characterization, (2) remote access control of shipboard sonar data acquisition and processing computers, and (3) potential for broadening multidisciplinary applications of ocean mapping cruises including outreach, education, and communications efforts focused on expanding societal cognition and benefits of ocean exploration.

Extraction of quantitative surface characteristics from AIRSAR data for Death Valley, California

NASA Technical Reports Server (NTRS)

Kierein-Young, K. S.; Kruse, F. A.

1992-01-01

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in Sep. 1989. AIRSAR is a four-look, quad-polarization, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The AIRSAR data were calibrated using in-scene trihedral corner reflectors to remove cross-talk; and to calibrate the phase, amplitude, and co-channel gain imbalance. The calibration allows for the extraction of accurate values of rms surface roughness, dielectric constants, sigma(sub 0) backscatter, and polarization information. The radar data sets allow quantitative characterization of small scale surface structure of geologic units, providing information about the physical and chemical processes that control the surface morphology. Combining the quantitative information extracted from the radar data with other remotely sensed data sets allows discrimination, identification and mapping of geologic units that may be difficult to discern using conventional techniques.

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.

Remote sensing as a mineral prospecting technique

NASA Technical Reports Server (NTRS)

Meneses, P. R. (Principal Investigator)

1984-01-01

Remote sensing and its application as an alternative technique to mineral resource exploration are reviewed. Emphasis is given here to the analysis of the three basic attributes of remote sensing, i.e., spatial attributes related to regional structural mapping, spectral attributes related to rock discrimination and seasonal attributes related to geobotanic anomalies mapping, all of which are employed in mineral exploration. Special emphasis is given to new developments of the Thematic Mapper of the LANDSAT-5, principally with reference to the application of the bands 1.6 and 2.2 microns to map hydrothermally altered rocks and the band of red and blue shift to geobotanical anomalies mapping.

Improved Remote Sensing Retrieval of Land Surface Temperature in the Thermal Infrared (TIR) Using Visible/Short Wave Infrared (VSWIR) Imaging Spectrometer Estimated Water Vapor

NASA Astrophysics Data System (ADS)

Grigsby, S.; Hulley, G. C.; Roberts, D. A.; Scheele, C. J.; Ustin, S.; Alsina, M. M.

2014-12-01

Land surface temperature (LST) is an important parameter in many ecological studies, where processes such as evapotranspiration have impacts at temperature gradients less than 1 K. Current errors in standard MODIS and ASTER LST products are greater than 1 K, and for ASTER can be greater than 2 K in humid conditions due to incomplete atmospheric correction of atmospheric water vapor. Estimates of water vapor, either derived from visible-to-shortwave-infrared (VSWIR) remote sensing data or taken from weather simulation data such as NCEP, can be combined with coincident Thermal-Infrared (TIR) remote sensing data to yield improved accuracy in LST measurements. This study compares LST retrieval accuracies derived using the standard JPL MASTER Temperature Emissivity Separation (TES) algorithm, and the Water Vapor Scaling (WVS) atmospheric correction method proposed for the Hyperspectral Infrared Imager, or HyspIRI, mission with ground observations. The 2011 ER-2 Delano/Lost Hills flights acquired TIR data from the MODIS/ASTER Simulator (MASTER) and VSWIR data from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) instruments flown concurrently. The TES and WVS retrieval methods are run with and without high spatial resolution AVIRIS-derived water vapor maps to assess the improvement using VSWIR water vapor estimates. We find improvement using VSWIR derived water vapor maps in both cases, with the WVS method being most accurate overall. For closed canopy agricultural vegetation we observed canopy temperature retrieval RMSEs of 0.49 K and 0.70 K using the WVS method on MASTER data with and without AVIRIS derived water vapor, respectively.

Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado

USGS Publications Warehouse

Rockwell, Barnaby W.

2012-01-01

The efficacy of airborne spectroscopic, or "hyperspectral," remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated mineral group mapping products described in this study are ideal for application to mineral resource and mineral-environmental assessments at regional and national scales.

Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications

USDA-ARS?s Scientific Manuscript database

Remote sensing based evapotranspiration (ET) mapping has become an important tool for water resources management at a regional scale. Accurate hourly climatic data and reference ET are crucial input for successfully implementing remote sensing based ET models such as Mapping ET with internal calibra...

Compensating for environmental variability in the thermal inertia approach to remote sensing of soil moisture

NASA Technical Reports Server (NTRS)

Idso, S. B.; Jackson, R. D.; Reginato, R. J.

1976-01-01

A procedure is developed for removing data scatter in the thermal-inertia approach to remote sensing of soil moisture which arises from environmental variability in time and space. It entails the utilization of nearby National Weather Service air temperature measurements to normalize measured diurnal surface temperature variations to what they would have been for a day of standard diurnal air temperature variation, arbitrarily assigned to be 18 C. Tests of the procedure's basic premise on a bare loam soil and a crop of alfalfa indicate it to be conceptually sound. It is possible that the technique could also be useful in other thermal-inertia applications, such as lithographic mapping.

Sedimentary Facies Mapping Based on Tidal Channel Network and Topographic Features

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Lee, Y. K.; Kim, K.; Kim, B.

2015-12-01

Tidal flats on the west coast of Korea suffer intensive changes in their surface sedimentary facies as a result of the influence of natural and artificial changes. Spatial relationships between surface sedimentary facies distribution and benthic environments were estimated for the open-type Ganghwa tidal flat and semi closed-type Hwangdo tidal flat, Korea. In this study, we standardized the surface sedimentary facies and tidal channel index of the channel density, distance, thickness and order. To extract tidal channel information, we used remotely sensed data, such as those from the Korea Multi-Purpose Satellite (KOMPSAT)-2, KOMPSAT-3, and aerial photographs. Surface sedimentary facies maps were generated based on field data using an interpolation method.The tidal channels in each sediment facies had relatively constant meandering patterns, but the density and complexity were distinguishable. The second fractal dimension was 1.7-1.8 in the mud flat, about 1.4 in the mixed flat, and about 1.3 in the sand flat. The channel density was 0.03-0.06 m/m2 in the mud flat and less than 0.02 m/m2 in the mixed and sand flat areas of the two test areas. Low values of the tidal channel index, which indicated a simple pattern of tidal channel distribution, were identified at areas having low elevation and coarse-grained sediments. By contrast, high values of the tidal channel index, which indicated a dendritic pattern of tidal channel distribution, were identified at areas having high elevation and fine-grained sediments. Surface sediment classification based on remotely sensed data must circumspectly consider an effective critical grain size, water content, local topography, and intertidal structures.

Remote sensing-based detection and quantification of roadway debris following natural disasters

NASA Astrophysics Data System (ADS)

Axel, Colin; van Aardt, Jan A. N.; Aros-Vera, Felipe; Holguín-Veras, José

2016-05-01

Rapid knowledge of road network conditions is vital to formulate an efficient emergency response plan following any major disaster. Fallen buildings, immobile vehicles, and other forms of debris often render roads impassable to responders. The status of roadways is generally determined through time and resource heavy methods, such as field surveys and manual interpretation of remotely sensed imagery. Airborne lidar systems provide an alternative, cost-effective option for performing network assessments. The 3D data can be collected quickly over a wide area and provide valuable insight about the geometry and structure of the scene. This paper presents a method for automatically detecting and characterizing debris in roadways using airborne lidar data. Points falling within the road extent are extracted from the point cloud and clustered into individual objects using region growing. Objects are classified as debris or non-debris using surface properties and contextual cues. Debris piles are reconstructed as surfaces using alpha shapes, from which an estimate of debris volume can be computed. Results using real lidar data collected after a natural disaster are presented. Initial results indicate that accurate debris maps can be automatically generated using the proposed method. These debris maps would be an invaluable asset to disaster management and emergency response teams attempting to reach survivors despite a crippled transportation network.

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

Utility of remote sensing-based surface energy balance models to track water stress in rain-fed switchgrass under dry and wet conditions

NASA Astrophysics Data System (ADS)

Bhattarai, Nishan; Wagle, Pradeep; Gowda, Prasanna H.; Kakani, Vijaya G.

2017-11-01

The ability of remote sensing-based surface energy balance (SEB) models to track water stress in rain-fed switchgrass (Panicum virgatum L.) has not been explored yet. In this paper, the theoretical framework of crop water stress index (CWSI; 0 = extremely wet or no water stress condition and 1 = extremely dry or no transpiration) was utilized to estimate CWSI in rain-fed switchgrass using Landsat-derived evapotranspiration (ET) from five remote sensing based single-source SEB models, namely Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET with Internalized Calibration (METRIC), Surface Energy Balance System (SEBS), Simplified Surface Energy Balance Index (S-SEBI), and Operational Simplified Surface Energy Balance (SSEBop). CWSI estimates from the five SEB models and a simple regression model that used normalized difference vegetation index (NDVI), near-surface temperature difference, and measured soil moisture (SM) as covariates were compared with those derived from eddy covariance measured ET (CWSIEC) for the 32 Landsat image acquisition dates during the 2011 (dry) and 2013 (wet) growing seasons. Results indicate that most SEB models can predict CWSI reasonably well. For example, the root mean square error (RMSE) ranged from 0.14 (SEBAL) to 0.29 (SSEBop) and the coefficient of determination (R2) ranged from 0.25 (SSEBop) to 0.72 (SEBAL), justifying the added complexity in CWSI modeling as compared to results from the simple regression model (R2 = 0.55, RMSE = 0.16). All SEB models underestimated CWSI in the dry year but the estimates from SEBAL and S-SEBI were within 7% of the mean CWSIEC and explained over 60% of variations in CWSIEC. In the wet year, S-SEBI mostly overestimated CWSI (around 28%), while estimates from METRIC, SEBAL, SEBS, and SSEBop were within 8% of the mean CWSIEC. Overall, SEBAL was the most robust model under all conditions followed by METRIC, whose performance was slightly worse and better than SEBAL in dry and wet years, respectively. Underestimation of CWSI under extremely dry soil conditions and the substantial role of SM in the regression model suggest that integration of SM in SEB models could improve their performances under dry conditions. These insights will provide useful guidance on the broader applicability of SEB models for mapping water stresses in switchgrass under varying geographical and meteorological conditions.

Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response

NASA Astrophysics Data System (ADS)

Kruse, F. A.; Kim, A. M.; Runyon, S. C.; Carlisle, Sarah C.; Clasen, C. C.; Esterline, C. H.; Jalobeanu, A.; Metcalf, J. P.; Basgall, P. L.; Trask, D. M.; Olsen, R. C.

2014-06-01

The Naval Postgraduate School (NPS) Remote Sensing Center (RSC) and research partners have completed a remote sensing pilot project in support of California post-earthquake-event emergency response. The project goals were to dovetail emergency management requirements with remote sensing capabilities to develop prototype map products for improved earthquake response. NPS coordinated with emergency management services and first responders to compile information about essential elements of information (EEI) requirements. A wide variety of remote sensing datasets including multispectral imagery (MSI), hyperspectral imagery (HSI), and LiDAR were assembled by NPS for the purpose of building imagery baseline data; and to demonstrate the use of remote sensing to derive ground surface information for use in planning, conducting, and monitoring post-earthquake emergency response. Worldview-2 data were converted to reflectance, orthorectified, and mosaicked for most of Monterey County; CA. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired at two spatial resolutions were atmospherically corrected and analyzed in conjunction with the MSI data. LiDAR data at point densities from 1.4 pts/m2 to over 40 points/ m2 were analyzed to determine digital surface models. The multimodal data were then used to develop change detection approaches and products and other supporting information. Analysis results from these data along with other geographic information were used to identify and generate multi-tiered products tied to the level of post-event communications infrastructure (internet access + cell, cell only, no internet/cell). Technology transfer of these capabilities to local and state emergency response organizations gives emergency responders new tools in support of post-disaster operational scenarios.

The EarthServer Geology Service: web coverage services for geosciences

NASA Astrophysics Data System (ADS)

Laxton, John; Sen, Marcus; Passmore, James

2014-05-01

The EarthServer FP7 project is implementing web coverage services using the OGC WCS and WCPS standards for a range of earth science domains: cryospheric; atmospheric; oceanographic; planetary; and geological. BGS is providing the geological service (http://earthserver.bgs.ac.uk/). Geoscience has used remote sensed data from satellites and planes for some considerable time, but other areas of geosciences are less familiar with the use of coverage data. This is rapidly changing with the development of new sensor networks and the move from geological maps to geological spatial models. The BGS geology service is designed initially to address two coverage data use cases and three levels of data access restriction. Databases of remote sensed data are typically very large and commonly held offline, making it time-consuming for users to assess and then download data. The service is designed to allow the spatial selection, editing and display of Landsat and aerial photographic imagery, including band selection and contrast stretching. This enables users to rapidly view data, assess is usefulness for their purposes, and then enhance and download it if it is suitable. At present the service contains six band Landsat 7 (Blue, Green, Red, NIR 1, NIR 2, MIR) and three band false colour aerial photography (NIR, green, blue), totalling around 1Tb. Increasingly 3D spatial models are being produced in place of traditional geological maps. Models make explicit spatial information implicit on maps and thus are seen as a better way of delivering geosciences information to non-geoscientists. However web delivery of models, including the provision of suitable visualisation clients, has proved more challenging than delivering maps. The EarthServer geology service is delivering 35 surfaces as coverages, comprising the modelled superficial deposits of the Glasgow area. These can be viewed using a 3D web client developed in the EarthServer project by Fraunhofer. As well as remote sensed imagery and 3D models, the geology service is also delivering DTM coverages which can be viewed in the 3D client in conjunction with both imagery and models. The service is accessible through a web GUI which allows the imagery to be viewed against a range of background maps and DTMs, and in the 3D client; spatial selection to be carried out graphically; the results of image enhancement to be displayed; and selected data to be downloaded. The GUI also provides access to the Glasgow model in the 3D client, as well as tutorial material. In the final year of the project it is intended to increase the volume of data to 20Tb and enhance the WCPS processing, including depth and thickness querying of 3D models. We have also investigated the use of GeoSciML, developed to describe and interchange the information on geological maps, to describe model surface coverages. EarthServer is developing a combined WCPS and xQuery query language, and we will investigate applying this to the GeoSciML described surfaces to answer questions such as 'find all units with a predominant sand lithology within 25m of the surface'.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1982-01-01

Research projects described include: (1) identifying coniferous forest types in Michigan using LANDSAT imagery; (2) investigating synoptic temperature patterns in Michigan as determined via GOES and HCMM thermal imagery; (3) land surface change detection using satellite data and a geographic data base; (4) determining soil map unit composition by electronic scanning densitometry; and (5) delimiting areas of virus infection in vineyards and blueberry fields in southwestern and western Michigan. Contractual activities involve important farmlands inventory, changes in aquatic vegetation in Saginaw Bay, digitized soil association map of Michigan, and aerial photography for hybrid-poplar research. On-going projects are also being conducted in Jamaica, Honduras, the Dominican Republic and Kenya.

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

NASA Technical Reports Server (NTRS)

Zhang, Ting-Jun; Li, Shu-Sun

2003-01-01

The objective of this project is to map the spatial variation of the active layer over the arctic permafrost in terms of two parameters: (i) timing and duration of thaw period and (ii) differential frost heave and thaw settlement of the active layer. To achieve this goal, remote sensing, numerical modeling, and related field measurements are required. Tasks for the University of Colorado team are to: (i) determine the timing of snow disappearance in spring through changes in surface albedo (ii) simulate the freezing and thawing processes of the active layer and (iii) simulate the impact of snow cover on permafrost presence.

Mineral Physicochemistry based Geoscience Products for Mapping the Earth's Surface and Subsurface

NASA Astrophysics Data System (ADS)

Laukamp, C.; Cudahy, T.; Caccetta, M.; Haest, M.; Rodger, A.; Western Australian Centre of Excellence3D Mineral Mapping

2011-12-01

Mineral maps derived from remotes sensing data can be used to address geological questions about mineral systems important for exploration and mining. This paper focuses on the application of geoscience-tuned multi- and hyperspectral sensors (e.g. ASTER, HyMap) and the methods to routinely create meaningful higher level geoscience products from these data sets. The vision is a 3D mineral map of the earth's surface and subsurface. Understanding the physicochemistry of rock forming minerals and the related diagnostic absorption features in the visible, near, mid and far infrared is a key for mineral mapping. For this, reflectance spectra obtained with lab based visible and infrared spectroscopic (VIRS) instruments (e.g. Bruker Hemisphere Vertex 70) are compared to various remote and proximal sensing techniques. Calibration of the various sensor types is a major challenge with any such comparisons. The spectral resolution of the respective instruments and the band positions are two of the main factors governing the ability to identify mineral groups or mineral species and compositions of those. The routine processing method employed by the Western Australian Centre of Excellence for 3D Mineral Mapping (http://c3dmm.csiro.au) is a multiple feature extraction method (MFEM). This method targets mineral specific absorption features rather than relying on spectral libraries or the need to find pure endmembers. The principle behind MFEM allows us to easily compare hyperspectral surface and subsurface data, laying the foundation for a seamless and accurate 3-dimensional mineral map. The advantage of VIRS techniques for geoscientific applications is the ability to deliver quantitative mineral information over multiple scales. For example, C3DMM is working towards a suite of ASTER-derived maps covering the Australian continent, scheduled for publication in 2012. A suite of higher level geoscience products of Western Australia (e.g. AlOH group abundance and composition) are now available. The multispectral satellite data can be integrated with hyperspectral airborne and drill core data (e.g. HyLogging), which is demonstrated by various case studies ranging from Channel Iron Deposits in the Hamersley Basin (WA) to various Australian orogenic Au deposits. Comparison with airborne and field hyperspectral or lab-based VIRS, as well as independent analyses such as XRD and geochemistry, enables us to deliver cross-calibrated geoscience products derived from the whole suite of geoscience tuned multi- and hyperspectral technologies. Kaolin crystallinity and hematite-goethite ratio for characterization of regolith, and Tschermak substitution in white micas for mapping of chemical gradients associated with hydrothermal ore deposits are a few of the multiple examples where 3D mineral maps can help to resolve geological questions.

Collaborative damage mapping for emergency response: the role of Cognitive Systems Engineering

NASA Astrophysics Data System (ADS)

Kerle, N.; Hoffman, R. R.

2013-01-01

Remote sensing is increasingly used to assess disaster damage, traditionally by professional image analysts. A recent alternative is crowdsourcing by volunteers experienced in remote sensing, using internet-based mapping portals. We identify a range of problems in current approaches, including how volunteers can best be instructed for the task, ensuring that instructions are accurately understood and translate into valid results, or how the mapping scheme must be adapted for different map user needs. The volunteers, the mapping organizers, and the map users all perform complex cognitive tasks, yet little is known about the actual information needs of the users. We also identify problematic assumptions about the capabilities of the volunteers, principally related to the ability to perform the mapping, and to understand mapping instructions unambiguously. We propose that any robust scheme for collaborative damage mapping must rely on Cognitive Systems Engineering and its principal method, Cognitive Task Analysis (CTA), to understand the information and decision requirements of the map and image users, and how the volunteers can be optimally instructed and their mapping contributions merged into suitable map products. We recommend an iterative approach involving map users, remote sensing specialists, cognitive systems engineers and instructional designers, as well as experimental psychologists.

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Sorek Hamer, Meytar; Lyapustin, Alexei; Wang, Yujie

2017-01-01

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

A stable downward continuation of airborne magnetic data: A case study for mineral prospectivity mapping in Central Iran

NASA Astrophysics Data System (ADS)

Abedi, Maysam; Gholami, Ali; Norouzi, Gholam-Hossain

2013-03-01

Previous studies have shown that a well-known multi-criteria decision making (MCDM) technique called Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE II) to explore porphyry copper deposits can prioritize the ground-based exploratory evidential layers effectively. In this paper, the PROMETHEE II method is applied to airborne geophysical (potassium radiometry and magnetometry) data, geological layers (fault and host rock zones), and various extracted alteration layers from remote sensing images. The central Iranian volcanic-sedimentary belt is chosen for this study. A stable downward continuation method as an inverse problem in the Fourier domain using Tikhonov and edge-preserving regularizations is proposed to enhance magnetic data. Numerical analysis of synthetic models show that the reconstructed magnetic data at the ground surface exhibits significant enhancement compared to the airborne data. The reduced-to-pole (RTP) and the analytic signal filters are applied to the magnetic data to show better maps of the magnetic anomalies. Four remote sensing evidential layers including argillic, phyllic, propylitic and hydroxyl alterations are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in order to map the altered areas associated with porphyry copper deposits. Principal component analysis (PCA) based on six Enhanced Thematic Mapper Plus (ETM+) images is implemented to map iron oxide layer. The final mineral prospectivity map based on desired geo-data set indicates adequately matching of high potential zones with previous working mines and copper deposits.

Landslide inventory maps: New tools for an old problem

NASA Astrophysics Data System (ADS)

Guzzetti, Fausto; Mondini, Alessandro Cesare; Cardinali, Mauro; Fiorucci, Federica; Santangelo, Michele; Chang, Kang-Tsung

2012-04-01

Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Despite their importance, we estimate that landslide maps cover less than 1% of the slopes in the landmasses, and systematic information on the type, abundance, and distribution of landslides is lacking. Preparing landslide maps is important to document the extent of landslide phenomena in a region, to investigate the distribution, types, pattern, recurrence and statistics of slope failures, to determine landslide susceptibility, hazard, vulnerability and risk, and to study the evolution of landscapes dominated by mass-wasting processes. Conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography, aided by field surveys. These methods are time consuming and resource intensive. New and emerging techniques based on satellite, airborne, and terrestrial remote sensing technologies, promise to facilitate the production of landslide maps, reducing the time and resources required for their compilation and systematic update. In this work, we first outline the principles for landslide mapping, and we review the conventional methods for the preparation of landslide maps, including geomorphological, event, seasonal, and multi-temporal inventories. Next, we examine recent and new technologies for landslide mapping, considering (i) the exploitation of very-high resolution digital elevation models to analyze surface morphology, (ii) the visual interpretation and semi-automatic analysis of different types of satellite images, including panchromatic, multispectral, and synthetic aperture radar images, and (iii) tools that facilitate landslide field mapping. Next, we discuss the advantages and the limitations of the new remote sensing data and technology for the production of geomorphological, event, seasonal, and multi-temporal inventory maps. We conclude by arguing that the new tools will help to improve the quality of landslide maps, with positive effects on all derivative products and analyses, including erosion studies and landscape modeling, susceptibility and hazard assessments, and risk evaluations.

Semi-automatic mapping of geological Structures using UAV-based photogrammetric data: An image analysis approach

NASA Astrophysics Data System (ADS)

Vasuki, Yathunanthan; Holden, Eun-Jung; Kovesi, Peter; Micklethwaite, Steven

2014-08-01

Recent advances in data acquisition technologies, such as Unmanned Aerial Vehicles (UAVs), have led to a growing interest in capturing high-resolution rock surface images. However, due to the large volumes of data that can be captured in a short flight, efficient analysis of this data brings new challenges, especially the time it takes to digitise maps and extract orientation data. We outline a semi-automated method that allows efficient mapping of geological faults using photogrammetric data of rock surfaces, which was generated from aerial photographs collected by a UAV. Our method harnesses advanced automated image analysis techniques and human data interaction to rapidly map structures and then calculate their dip and dip directions. Geological structures (faults, joints and fractures) are first detected from the primary photographic dataset and the equivalent three dimensional (3D) structures are then identified within a 3D surface model generated by structure from motion (SfM). From this information the location, dip and dip direction of the geological structures are calculated. A structure map generated by our semi-automated method obtained a recall rate of 79.8% when compared against a fault map produced using expert manual digitising and interpretation methods. The semi-automated structure map was produced in 10 min whereas the manual method took approximately 7 h. In addition, the dip and dip direction calculation, using our automated method, shows a mean±standard error of 1.9°±2.2° and 4.4°±2.6° respectively with field measurements. This shows the potential of using our semi-automated method for accurate and efficient mapping of geological structures, particularly from remote, inaccessible or hazardous sites.

Distribution of near-surface permafrost in Alaska: estimates of present and future conditions

USGS Publications Warehouse

Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Nield, Shawn J.; Johnson, Kristofer D.; Finley, Andrew O.

2015-01-01

High-latitude regions are experiencing rapid and extensive changes in ecosystem composition and function as the result of increases in average air temperature. Increasing air temperatures have led to widespread thawing and degradation of permafrost, which in turn has affected ecosystems, socioeconomics, and the carbon cycle of high latitudes. Here we overcome complex interactions among surface and subsurface conditions to map nearsurface permafrost through decision and regression tree approaches that statistically and spatially extend field observations using remotely sensed imagery, climatic data, and thematic maps of a wide range of surface and subsurface biophysical characteristics. The data fusion approach generated medium-resolution (30-m pixels) maps of near-surface (within 1 m) permafrost, active-layer thickness, and associated uncertainty estimates throughout mainland Alaska. Our calibrated models (overall test accuracy of ~85%) were used to quantify changes in permafrost distribution under varying future climate scenarios assuming no other changes in biophysical factors. Models indicate that near-surface permafrost underlies 38% of mainland Alaska and that near-surface permafrost will disappear on 16 to 24% of the landscape by the end of the 21st Century. Simulations suggest that near-surface permafrost degradation is more probable in central regions of Alaska than more northerly regions. Taken together, these results have obvious implications for potential remobilization of frozen soil carbon pools under warmer temperatures. Additionally, warmer and drier conditions may increase fire activity and severity, which may exacerbate rates of permafrost thaw and carbon remobilization relative to climate alone. The mapping of permafrost distribution across Alaska is important for land-use planning, environmental assessments, and a wide-array of geophysical studies.

Preliminary Surficial Geologic Map of the Mesquite Lake 30' X 60' Quadrangle, California and Nevada

USGS Publications Warehouse

Schmidt, Kevin M.; McMackin, Matthew

2006-01-01

The Quaternary surficial geologic map of the Mesquite Lake, California-Nevada 30'X60' quadrangle depicts deposit age and geomorphic processes of erosion and deposition, as identified by a composite of remote sensing investigations, laboratory analyses, and field work, in the arid to semi-arid Mojave Desert area, straddling the California-Nevada border. Mapping was motivated by the need to address pressing scientific and social issues such as understanding and predicting the effects of climate and associated hydrologic changes, human impacts on landscapes, ecosystem function, and natural hazards at a regional scale. As the map area lies just to the south of Las Vegas, Nevada, a rapidly expanding urban center, land use pressures and the need for additional construction materials are forecasted for the region. The map contains information on the temporal and spatial patterns of surface processes and hazards that can be used to model specific landscape applications. Key features of the geologic map include: (1) spatially extensive Holocene alluvial deposits that compose the bulk of Quaternary units (~25%), (2) remote sensing and field studies that identified fault scarps or queried faults in the Kingston Wash area, Shadow Mountains, southern Pahrump Valley, Bird Spring Range, Lucy Gray Mountains and Piute Valley, (3) a lineament indicative of potential fault offset is located in Mesquite Valley, (4) active eolian dunes and sand ramps located on the east side of Mesquite, Ivanpah, and Hidden Valleys adjacent to playas, (4) groundwater discharge deposits in southern Pahrump Valley, Spring Mountains, and Lucy Gray Mountains and (5) debris-flow deposits spanning almost the entire Quaternary period in age.

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

NASA Astrophysics Data System (ADS)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

Robotic Technology Development at Ames: The Intelligent Robotics Group and Surface Telerobotics

NASA Technical Reports Server (NTRS)

Bualat, Maria; Fong, Terrence

2013-01-01

Future human missions to the Moon, Mars, and other destinations offer many new opportunities for exploration. But, astronaut time will always be limited and some work will not be feasible for humans to do manually. Robots, however, can complement human explorers, performing work autonomously or under remote supervision from Earth. Since 2004, the Intelligent Robotics Group has been working to make human-robot interaction efficient and effective for space exploration. A central focus of our research has been to develop and field test robots that benefit human exploration. Our approach is inspired by lessons learned from the Mars Exploration Rovers, as well as human spaceflight programs, including Apollo, the Space Shuttle, and the International Space Station. We conduct applied research in computer vision, geospatial data systems, human-robot interaction, planetary mapping and robot software. In planning for future exploration missions, architecture and study teams have made numerous assumptions about how crew can be telepresent on a planetary surface by remotely operating surface robots from space (i.e. from a flight vehicle or deep space habitat). These assumptions include estimates of technology maturity, existing technology gaps, and likely operational and functional risks. These assumptions, however, are not grounded by actual experimental data. Moreover, no crew-controlled surface telerobotic system has yet been fully tested, or rigorously validated, through flight testing. During Summer 2013, we conducted a series of tests to examine how astronauts in the International Space Station (ISS) can remotely operate a planetary rover across short time delays. The tests simulated portions of a proposed human-robotic Lunar Waypoint mission, in which astronauts in lunar orbit remotely operate a planetary rover on the lunar Farside to deploy a radio telescope array. We used these tests to obtain baseline-engineering data.

A manual for inexpensive methods of analyzing and utilizing remote sensor data

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barr, D. J.

1978-01-01

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Analysis

NASA Astrophysics Data System (ADS)

Abdelazeem, Maha; El-Sawy, El-Sawy K.; Gobashy, Mohamed M.

2013-06-01

Ar Rika fault zone constitutes one of the two major parts of the NW-SE Najd fault system (NFS), which is one of the most prominent structural features located in the east of the center of the Arabian Shield, Saudi Arabia. By using Enhancement Thematic Mapper data (ETM+) and Principle Component Analysis (PCA), surface geological characteristics, distribution of rock types, and the different trends of linear features and faults are determined in the study area. First and second order magnetic gradients of the geomagnetic field at the North East of Wadi Ar Rika have been calculated in the frequency domain to map both surface and subsurface lineaments and faults. Lineaments as deduced from previous studies, suggest an extension of the NFS beneath the cover rocks in the study area. In the present study, integration of magnetic gradients and remote sensing analysis that resulted in different valuable derivative maps confirm the subsurface extension of some of the surface features. The 3D Euler deconvolution, the total gradient, and the tilt angle maps have been utilized to determine accurately the distribution of shear zones, the tectonic implications, and the internal structures of the terranes in the Ar Rika quadrangle in three dimensions.

Soil water content spatial pattern estimated by thermal inertia from air-borne sensors

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Basile, Angelo; Esposito, Marco; Menenti, Massimo; Buonanno, Maurizio

2010-05-01

Remote sensing of soil water content from air- or space-borne platforms offer the possibility to provide large spatial coverage and temporal continuity. The water content can be actually monitored in a thin soil layer, usually up to a depth of 0.05m below the soil surface. To the contrary, difficulties arise in the estimation of the water content storage along the soil profile and its spatial (horizontal) distribution, which are closely connected to soil hydraulic properties and their spatial distribution. A promising approach for estimating soil water contents profiles is the integration of remote sensing of surface water content and hydrological modeling. A major goal of the scientific group is to develop a practical and robust procedure for estimating water contents throughout the soil profile from surface water content. As a first step, in this work, we will show some preliminary results from aircraft images analysis and their validation by field campaigns data. The data extracted from the airborne sensors provided the opportunity of retrieving land surface temperatures with a very high spatial resolution. The surface water content pattern, as deduced by the thermal inertia estimations, was compared to the surface water contents maps measured in situ by time domain reflectometry-based probes.

Configuration of Pluto's Volatile Ices

NASA Astrophysics Data System (ADS)

Grundy, William M.; Binzel, R. P.; Cook, J. C.; Cruikshank, D. P.; Dalle Ore, C. M.; Earle, A. M.; Ennico, K.; Jennings, D. E.; Howett, C. J. A.; Linscott, I. R.; Lunsford, A. W.; Olkin, C. B.; Parker, A. H.; Parker, J. Wm; Protopapa, S.; Reuter, D. C.; Singer, K. N.; Spencer, J. R.; Stern, S. A.; Tsang, C. C. C.; Verbiscer, A. J.; Weaver, H. A.; Young, L. A.; Berry, K.; Buie, M. W.; Stansberry, J. A.

2015-11-01

We report on near-infrared remote sensing by New Horizons' Ralph instrument (Reuter et al. 2008, Space Sci. Rev. 140, 129-154) of Pluto's N2, CO, and CH4 ices. These especially volatile ices are mobile even at Pluto's cryogenic surface temperatures. Sunlight reflected from these ices becomes imprinted with their characteristic spectral absorption bands. The detailed appearance of these absorption features depends on many aspects of local composition, thermodynamic state, and texture. Multiple-scattering radiative transfer models are used to retrieve quantitative information about these properties and to map how they vary across Pluto's surface. Using parameter maps derived from New Horizons observations, we investigate the striking regional differences in the abundances and scattering properties of Pluto's volatile ices. Comparing these spatial patterns with the underlying geology provides valuable constraints on processes actively modifying the planet's surface, over a variety of spatial scales ranging from global latitudinal patterns to more regional and local processes within and around the feature informally known as Sputnik Planum. This work was supported by the NASA New Horizons Project.

Lunar elemental analysis obtained from the Apollo gamma-ray and X-ray remote sensing experiment

NASA Technical Reports Server (NTRS)

Trombka, J. I.; Arnold, J. R.; Adler, I.; Metzger, A. E.; Reedy, R. C.

1974-01-01

Gamma ray and X-ray spectrometers carried in the service module of the Apollo 15 and 16 spacecraft were employed for compositional mapping of the lunar surface. The measurements involved the observation of the intensity and characteristics energy distribution of gamma rays and X-rays emitted from the lunar surface. A large scale compositional map of over 10 percent of the lunar surface was obtained from an analysis of the observed spectra. The objective of the X-ray experiment was to measure the K spectral lines from Mg, Al, and Si. Spectra were obtained and the data were reduced to Al/Si and Mg/Si intensity ratios and ultimately to chemical ratios. The objective of the gamma-ray experiment was to measure the natural and cosmic ray induced activity emission spectrum. At this time, the elemental abundances for Th, U, K, Fe, Ti, Si, and O have been determined over a number of major lunar regions.

NASA Fluid Lensing & MiDAR - Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

Piti's Tepungan Bay and Tumon Bay, two of five marine preserves in Guam, have not been mapped to a level of detail sufficient to support proposed management strategies. This project addresses this gap by providing high resolution maps to promote sustainable, responsible use of the area while protecting natural resources. Dr. Chirayath, a research scientist at the NASA Ames Laboratory, developed a theoretical model and algorithm called 'Fluid Lensing'. Fluid lensing removes optical distortions caused by moving water, improving the clarity of the images taken of the corals below the surface. We will also be using MiDAR, a next-generation remote sensing instrument that provides real-time multispectral video using an array of LED emitters coupled with NASA's FluidCam Imaging System, which may assist Guam's coral reef response team in understanding the severity and magnitude of coral bleaching events. This project will produce a 3D orthorectified model of the shallow water coral reef ecosystems in Tumon Bay and Piti marine preserves. These 3D models may be printed, creating a tactile diorama and increasing understanding of coral reefs among various audiences, including key decision makers. More importantly, the final data products can enable accurate and quantitative health assessment capabilities for coral reef ecosystems.

Discrimination of fluoride and phosphate contamination in central Florida for analyses of environmental effects

NASA Technical Reports Server (NTRS)

Coker, A. E.; Marshall, R.; Thomson, F.

1972-01-01

A study was made of the spatial registration of fluoride and phosphate pollution parameters in central Florida by utilizing remote sensing techniques. Multispectral remote sensing data were collected over the area and processed to produce multispectral recognition maps. These processed data were used to map land areas and waters containing concentrations of fluoride and phosphate. Maps showing distribution of affected and unaffected vegetation were produced. In addition, the multispectral data were processed by single band radiometric slicing to produce radiometric maps used to delineate areas of high ultraviolet radiance, which indicates high fluoride concentrations. The multispectral parameter maps and radiometric maps in combination showed distinctive patterns, which are correlated with areas known to be affected by fluoride and phosphate contamination. These remote sensing techniques have the potential for regional use to assess the environmental impact of fluoride and phosphate wastes in central Florida.

Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data

USGS Publications Warehouse

Rockwell, Barnaby W.

2013-01-01

This report presents results of interpretation of spectral remote sensing data covering the eastern Colorado Mineral Belt in central Colorado, USA, acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors. This study was part of a multidisciplinary mapping and data integration project at the U.S. Geological Survey that focused on long-term resource planning by land-managing entities in Colorado. The map products were designed primarily for the regional mapping and characterization of exposed surface mineralogy, including that related to hydrothermal alteration and supergene weathering of pyritic rocks. Alteration type was modeled from identified minerals based on standard definitions of alteration mineral assemblages. Vegetation was identified using the ASTER data and subdivided based on per-pixel chlorophyll content (depth of 0.68 micrometer absorption band) and dryness (fit and depth of leaf biochemical absorptions in the shortwave infrared spectral region). The vegetation results can be used to estimate the abundance of fire fuels at the time of data acquisition (2002 and 2003). The AVIRIS- and ASTER-derived mineral mapping results can be readily compared using the toggleable layers in the GeoPDF file, and by using the provided GIS-ready raster datasets. The results relating to mineral occurrence and distribution were an important source of data for studies documenting the effects of mining and un-mined, altered rocks on aquatic ecosystems at the watershed level. These studies demonstrated a high correlation between metal concentrations in streams and the presence of hydrothermal alteration and (or) pyritic mine waste as determined by analysis of the map products presented herein. The mineral mapping results were also used to delineate permissive areas for various mineral deposit types.

Mapping agroecosystem zone using remote sensing for food security analysis in Bantul district Daerah Istimewa Yogyakarta

NASA Astrophysics Data System (ADS)

Murti, Sigit Heru

2017-10-01

Food security is one of the most important issue for Indonesia. The huge population number and high population growing rate has made the food security a critical issue. This paper describe the application of remote sensing data to (1) map agroecosystem zones in Bantul District, Special Region of Yogyakarta, Indonesia in 2012 and (2) analyze the food security in the study area based on the resulting agro-ecosystem map. Bantul District is selected as the pilot area because this area is among the highest food crop production area in the Province. ALOS AVNIR-2 image accquired on 15 June 2010 was integrated with Indonesian Surface map (RBI map), soil types map, and slope steepness map. Population statistics data was also used to calculate the food needs. Field survey was conducted to obtain the crop field productivity information on each agro-ecosystem zone and assess the accuracy of the model. This research indicates that (1) Bantul District can be divided into three agroecosystem zones, where each zone has unique topograhic configuration and soil types composition, and (2) Bantul Distict is categorized as food secure area since the rice production in 2012 managed to cover the food needs of the people with the surplus of 33,208.6 tonnes of rice. However, when the analysis was conducted at sub-district level, there are four subdistrict with food insecurity where the food needs surpass the rice production. These sub-district are Kasihan Sub-district (-5,598.4 t), Banguntapan Sub-district (-2,483.4 t), Pajangan Sub-district (-1,039.6 t) and Dlingo Sub-district (-798.7 t).

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Geologic remote sensing study of the Hayden pass-Orient Mine Area, Northern Sangre de Cristo Mountains, Colorado

NASA Technical Reports Server (NTRS)

Wychgram, D. C.

1972-01-01

Remote sensor data from a NASA Convair 990 radar flight and Mission 101 and 105 have been interpreted and evaluated. Based on interpretation of the remote sensor data, a geologic map has been prepared and compared with a second geologic map, prepared from interpretation of both remote sensor data and field data. Comparison of the two maps gives one indication of the usefulness and reliability of the remote sensor data. Color and color infrared photography provided the largest amount of valuable information. Multiband photography was of lesser value and side-looking radar imagery provided no new information that was not available on small scale photography. Thermal scanner imagery proved to be a very specialized remote sensing tool that should be applied to areas of low relief and sparse vegetation where geologic features produce known or suspected thermal contrast. Low sun angle photography may be a good alternative to side-looking radar imagery but must be flown with critical timing.

a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.

2015-07-01

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.

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.

Estimating the age of arid-zone alluvial fan surfaces using roughness measurements from spaceborne radar backscatter

NASA Astrophysics Data System (ADS)

Hetz, G.; Mushkin, A.; Blumberg, D. G.; Baer, G.; Trabelsky, E.

2012-12-01

Alluvial fan surfaces respond to geologic and climate changes as they record the deposition and erosion processes that govern their evolution, which amongst others is manifested in the micro and meso scale topography of the surface. Remote sensing provides a regional view that is very useful for mapping. Some previous publications have demonstrated that relative dating can also be achieved by remote sensing using techniques common in planetary geology such as overlap relationships. This work focuses on the use of radar backscatter as suggested originally by Evans et al., (1992) to map ages but here we will try to provide an absolute geologic age. The objective of this paper is to demonstrate the use of radar backscatter to constrain surface roughness as a calibrated proxy for estimating age of alluvial surfaces. With the unique regional spatial perspective provided by spaceborne imaging, we aim at providing a new and complementary regional perspective for studying neotectonic and recent landscape evolution processes as well as paleoclimate. Moreover, the method (by radar backscattering measure) can be applied to the geomorphology of other planets. The current study is located in the southeastern part of the Negev desert, Israel on the late Pleistocene - Holocene Shehoret alluvial fan sequence. High resolution (0.5 cm) 3D roughness measurements were collected using a ground-based LIDAR (Leica HDS 3000) and these show a robust relationship between independently obtained OSL surface age and surface roughness; the fan surfaces become smoother with time over 103-105 yr timescales. Spaceborne backscatter radar data respond primarily to surface slope, roughness at a scale comparable to the radar wavelength, and other parameters such as dielectric properties of the surface. Therefore, radar can provide a good quantitative indication of surface roughness in arid zones, where vegetation cover is low. Preliminary results show a relationship between surface age and roughness and the radar cross section extracted from polarimetric spaceborne data. The best result is found in cross polarization (HV), L-band measured at an incidence angle of 38°.

Web GIS in practice IV: publishing your health maps and connecting to remote WMS sources using the Open Source UMN MapServer and DM Solutions MapLab

PubMed Central

Boulos, Maged N Kamel; Honda, Kiyoshi

2006-01-01

Open Source Web GIS software systems have reached a stage of maturity, sophistication, robustness and stability, and usability and user friendliness rivalling that of commercial, proprietary GIS and Web GIS server products. The Open Source Web GIS community is also actively embracing OGC (Open Geospatial Consortium) standards, including WMS (Web Map Service). WMS enables the creation of Web maps that have layers coming from multiple different remote servers/sources. In this article we present one easy to implement Web GIS server solution that is based on the Open Source University of Minnesota (UMN) MapServer. By following the accompanying step-by-step tutorial instructions, interested readers running mainstream Microsoft® Windows machines and with no prior technical experience in Web GIS or Internet map servers will be able to publish their own health maps on the Web and add to those maps additional layers retrieved from remote WMS servers. The 'digital Asia' and 2004 Indian Ocean tsunami experiences in using free Open Source Web GIS software are also briefly described. PMID:16420699

Spatial Relationship of Focal Impulses, Rotors and Low Voltage Zones in Patients With Persistent Atrial Fibrillation.

PubMed

Schade, Anja; Nentwich, Karin; Costello-Boerrigter, Lisa C; Halbfass, Philipp; Mueller, Patrick; Roos, Markus; Barth, Sebastian; Krug, Joachim; Szoelloesi, Geza-Atilla; Lapp, Harald; Deneke, Thomas

2016-05-01

Focal impulses (FI) and rotors are sources associated with the initiation and maintenance of atrial fibrillation (AF). Their ablation results in a lower recurrence rate. The aim of this study was to characterize for the first time the spatial relationship between such sources and atrial low voltage zones (LVZ) representing fibrosis. Twenty-five consecutive patients undergoing their first ablation for persistent AF were included. Voltage mapping of both atria was done during AF. Endocardial mapping of FI and rotors (sources) was performed using a basket catheter and displayed using RhythmView(TM) (Topera Inc.) before ablation. Spatial relationship of LVZ and sources was analyzed. LVZs covered 13 ± 12% of right atrial (RA) endocardial surface and 33 ± 25% of left atrial (LA) endocardial surface. The median number of sources was 1 [1-3] in RA and 3 [1-4] in LA. Of LA sources, 18 (30%) were definitely not associated with LVZs or pulmonary vein (PV) antra. Of RA sources, 32 (84%) were remote from LVZ. During ablation of such sources substantial cycle length (CL) prolongation or AF conversion occurred in 11/23 patients (48%). Altogether, 8/11 (73%) of these pertinent sources were located remotely from LVZ and PV antra. There is a wide discrepancy in distribution of LVZ areas and sites of identified rotors. Site and incidence of FIRM sources appear to be unpredictable with atrial substrate mapping. Further prospective, randomized studies are necessary to elucidate the impact of additional ablation of such sources in patients with persistent or longstanding persistent AF. © 2016 Wiley Periodicals, Inc.

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

The use of remote sensing and linear wave theory to model local wave energy around Alphonse Atoll, Seychelles

NASA Astrophysics Data System (ADS)

Hamylton, S.

2011-12-01

This paper demonstrates a practical step-wise method for modelling wave energy at the landscape scale using GIS and remote sensing techniques at Alphonse Atoll, Seychelles. Inputs are a map of the benthic surface (seabed) cover, a detailed bathymetric model derived from remotely sensed Compact Airborne Spectrographic Imager (CASI) data and information on regional wave heights. Incident energy at the reef crest around the atoll perimeter is calculated as a function of its deepwater value with wave parameters (significant wave height and period) hindcast in the offshore zone using the WaveWatch III application developed by the National Oceanographic and Atmospheric Administration. Energy modifications are calculated at constant intervals as waves transform over the forereef platform along a series of reef profile transects running into the atoll centre. Factors for shoaling, refraction and frictional attenuation are calculated at each interval for given changes in bathymetry and benthic coverage type and a nominal reduction in absolute energy is incorporated at the reef crest to account for wave breaking. Overall energy estimates are derived for a period of 5 years and related to spatial patterning of reef flat surface cover (sand and seagrass patches).

Revealing the timing of ocean stratification using remotely-sensed ocean fronts: links with marine predators

NASA Astrophysics Data System (ADS)

Miller, P. I.; Loveday, B. R.

2016-02-01

Stratification is of critical importance to the mixing and productivity of the ocean, though currently it can only be measured using in situ sampling, profiling buoys or underwater autonomous vehicles. Stratification is understood to affect the surface aggregation of pelagic fish and hence the foraging behaviour and distribution of their predators such as seabirds and cetaceans. Satellite Earth observation sensors cannot directly detect stratification, but can observe surface features related to the presence of stratification, for example shelf-sea fronts that separate tidally-mixed water from seasonally stratified water. This presentation describes a novel algorithm that accumulates evidence for stratification from a sequence of oceanic front maps, and in certain regions can reveal the timing of the seasonal onset and breakdown of stratification. Initial comparisons will be made with seabird locations acquired through GPS tagging. If successful, a remotely-sensed stratification timing index would augment the ocean front metrics already developed at PML, that have been applied in over 20 journal articles relating marine predators to ocean fronts. The figure below shows a preliminary remotely-sensed 'stratification' index, for 25-31 Jul. 2010, where red indicates water with stronger evidence for stratification.

Potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal changes in dryland environments

NASA Astrophysics Data System (ADS)

Foerster, Saskia; Wilczok, Charlotte; Brosinsky, Arlena; Kroll, Anja; Segl, Karl; Francke, Till

2014-05-01

Many drylands are characterized by strong erosion in headwater catchments, where connectivity processes play an important role in the redistribution of water and sediments. Sediment connectivity relates to the physical transfer of sediment through a drainage basin (Bracken and Croke 2007). The identification of sediment source areas and the way they connect to the channel network are essential to environmental management (Reid et al. 2007), especially where high erosion and sediment delivery rates occur. Vegetation cover and its spatial and temporal pattern is one of the main factors affecting sediment connectivity. This is particularly true for patchy vegetation covers typical for dryland environments. While many connectivity studies are based on field-derived data, the potential of remotely-sensed data for sediment connectivity analyses has not yet been fully exploited. Recent advances in remote sensing allow for quantitative, spatially explicit, catchment-wide derivation of surface information to be used in connectivity analyses. These advances include a continuous increase in spatial image resolution to comprise processes at the plot to hillslope to catchment scale, an increase in the temporal resolution to cover seasonal and long-term changes and an increase in the spectral resolution enabling the discrimination of dry and green vegetation fractions from soil surfaces in heterogeneous dryland landscapes. The utilization of remotely-sensed data for connectivity studies raises questions on what type of information is required, how scale of sediment flux and image resolution match, how the connectivity information can be incorporated into water and sediment transport models and how this improves model predictions. The objective of this study is to demonstrate the potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal change at the example of a mesoscale dryland catchment in the Spanish Pyrenees. Here, sediment connectivity pathways have been mapped for two adjacent sub-catchments (approx. 70 km²) of the Isábena River in different seasons using a quantitative connectivity index based on fractional vegetation cover and topography data. Fractional cover of green and dry vegetation, bare soil and rock were derived by applying a Multiple Endmember Spectral Mixture Analysis approach applied to a hyperspectral image dataset. Sediment connectivity was mapped using the Index of Connectivity (Borselli et al. 2008), in which the effect of land cover on runoff and sediment fluxes is expressed by a spatially distributed weighing factor (in this study, the cover and management factor of the RUSLE). The resulting connectivity maps show that areas behave very differently with regard to connectivity, depending on the land cover but also on the spatial distribution of vegetation abundances and topographic barriers. Most parts of the catchment show higher connectivity values in summer than in spring. The studied sub-catchments show a slightly different connectivity behaviour reflecting the different land cover proportions and their spatial configuration. Future work includes the incorporation of sediment connectivity information into a hydrological model (WASA-SED, Mueller et al. 2010) to better reflect connectivity processes and testing the sensitivity of the model to different input data.

Understanding Pluto's Surface: Correlations between Geology and Composition

NASA Astrophysics Data System (ADS)

Spencer, J. R.; Stern, A.; Weaver, H. A., Jr.; Young, L. A.; Olkin, C.; Ennico Smith, K.; Moore, J. M.; Grundy, W. M.

2015-12-01

New Horizons has revealed that Pluto's surface is composed of a remarkable variety of terrains that differ strikingly in their landforms, color, and near-infrared spectral characteristics. Strong correlations are seen between the morphology revealed by high-resolution imaging from the Long Range Reconnaissance Imager (LORRI), and the surface composition inferred from the spacecraft's color camera and near-infrared spectrometer, which are both included in the Ralph instrument. These correlations provide the potential for a much deeper understanding of the processes that have shaped Pluto's complex surface that was possible for Pluto's sibling Triton, for which Voyager did not provide compositional maps. We will discuss how the full suite of New Horizons remote sensing instruments reveal a surface modified by the interplay of insolation variations, meteorology, and endogenic processes.

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of wildlife areas in eastern South Dakota

NASA Technical Reports Server (NTRS)

1975-01-01

A soils map for land evaluation in Potter County (Eastern South Dakota) was developed to demonstrate the use of remote sensing technology in the area of diverse parent materials and topography. General land use and soils maps have also been developed for land planning LANDSAT, RB-57 imagery, and USGS photographs are being evaluated for making soils and land use maps. LANDSAT fulfilled the requirements for general land use and a general soils map. RB-57 imagery supplemented by large scale black and white stereo coverage was required to provide the detail needed for the final soils map for land evaluation. Color infrared prints excelled black and white coverage for this soil mapping effort. An identification and classification key for wetland types in the Lake Dakota Plain was developed for June 1975 using color infrared imagery. Wetland types in the region are now being mapped via remote sensing techniques to provide a current inventory for development of mitigation measures.

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

The Activity of Comet 67P/Churyumov-Gerasimenko as Seen by Rosetta/OSIRIS

NASA Astrophysics Data System (ADS)

Sierks, H.; Barbieri, C.; Lamy, P. L.; Rodrigo, R.; Rickman, H.; Koschny, D.

2015-12-01

The Rosetta mission of the European Space Agency arrived on August 6, 2014, at the target comet 67P/Churyumov-Gerasimenko. OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System) is the scientific imaging system onboard Rosetta. OSIRIS consists of a Narrow Angle Camera (NAC) for the nucleus surface and dust studies and a Wide Angle Camera (WAC) for the wide field gas and dust coma investigations. OSIRIS observed the coma and the nucleus of comet 67P/C-G during approach, arrival, and landing of PHILAE. OSIRIS continued comet monitoring and mapping of surface and activity in 2015 with close fly-bys with high resolution and remote, wide angle observations. The scientific results reveal a nucleus with two lobes and varied morphology. Active regions are located at steep cliffs and collapsed pits which form collimated gas jets. Dust is accelerated by the gas, forming bright jet filaments and the large scale, diffuse coma of the comet. We will present activity and surface changes observed in the Northern and Southern hemisphere and around perihelion passage.

Remote Sensing of Wind Fields and Aerosol Distribution with Airborne Scanning Doppler Lidar

NASA Technical Reports Server (NTRS)

Rothermel, Jeffry; Cutten, Dean R.; Johnson, Steven C.; Jazembski, Maurice; Arnold, James E. (Technical Monitor)

2001-01-01

The coherent Doppler laser radar (lidar), when operated from an airborne platform, is a unique tool for the study of atmospheric and surface processes and features. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are typically at a disadvantage. The atmospheric lidar remote sensing groups of several US institutions, led by Marshall Space Flight Center, have developed an airborne coherent Doppler lidar capable of mapping the wind field and aerosol structure in three dimensions. The instrument consists of an eye-safe approx. 1 Joule/pulse lidar transceiver, telescope, scanner, inertial measurement unit, and flight computer system to orchestrate all subsystem functions and tasks. The scanner is capable of directing the expanded lidar beam in a variety of ways, in order to extract vertically-resolved wind fields. Horizontal resolution is approx. 1 km; vertical resolution is even finer. Winds are obtained by measuring backscattered, Doppler-shifted laser radiation from naturally-occurring aerosol particles (of order 1 micron diameter). Measurement coverage depends on aerosol spatial distribution and composition. Velocity accuracy has been verified to be approx. 1 meter per second. A variety of applications have been demonstrated during the three flight campaigns conducted during 1995-1998. Examples will be shown during the presentation. In 1995, boundary layer winds over the ocean were mapped with unprecedented resolution. In 1996, unique measurements were made of. flow over the complex terrain of the Aleutian Islands; interaction of the marine boundary layer jet with the California coastal mountain range; a weak dry line in Texas - New Mexico; the angular dependence of sea surface scattering; and in-flight radiometric calibration using the surface of White Sands National Monument. In 1998, the first measurements of eyewall and boundary layer winds within a hurricane were made with the airborne Doppler lidar. Potential applications and plans for improvement will also be described.

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.

Spatiotemporal remote sensing of ecosystem change and causation across Alaska.

PubMed

Pastick, Neal J; Jorgenson, M Torre; Goetz, Scott J; Jones, Benjamin M; Wylie, Bruce K; Minsley, Burke J; Genet, Hélène; Knight, Joseph F; Swanson, David K; Jorgenson, Janet C

2018-05-28

Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio-environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high-latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time-series analysis of moderate-and high-resolution imagery was used to characterize land- and water-surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land-surface greening, browning, and wetness/moisture trend parameters derived from peak-growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000 ± 8700 km 2 ) of Alaska has experienced directional change in the last 32 years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface-water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high-latitude regions. © 2018 John Wiley & Sons Ltd.

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Adams, John B.; Smith, Milton O.

1993-01-01

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Alaska Testbed for the Fusion of Citizen Science and Remote Sensing of Sea Ice and Snow

NASA Astrophysics Data System (ADS)

Walsh, J. E.; Sparrow, E.; Lee, O. A.; Brook, M.; Brubaker, M.; Casas, J.

2017-12-01

Citizen science, remote sensing and related environmental information sources for the Alaskan Arctic are synthesized with the objectives of (a) placing local observations into a broader geospatial framework and (b) enabling the use of local observations to evaluate sea ice, snow and land surface products obtained from remote sensing. In its initial phase, the project instituted a coordinated set of community-based observations of sea ice and snow in three coastal communities in western and northern Alaska: Nome, Point Hope and Barrow. Satellite maps of sea ice concentration have been consolidated with the in situ reports, leading to a three-part depiction of surface conditions at each site: narrative reports, surface-based photos, and satellite products. The project has developed a prototype visualization package, enabling users to select a location and date for which the three information sources can be viewed. Visual comparisons of the satellite products and the local reports show generally consistent depictions of the sea ice concentrations in the vicinity of the coastlines, although the satellite products are generally biased low, especially in coastal regions where shorefast ice persists after the appearance of open water farther offshore. A preliminary comparison of the local snow reports and the MODIS daily North American snow cover images indicates that areas of snow persisted in the satellite images beyond the date of snow disappearance reported by the observers. The "in-town" location of most of the snow reports is a factor that must be addressed in further reporting and remote sensing comparisons.

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.

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.

Applications of multi-season hyperspectral remote sensing for acid mine water characterization and mapping of secondary iron minerals associated with acid mine drainage

NASA Astrophysics Data System (ADS)

Davies, Gwendolyn E.

Acid mine drainage (AMD) resulting from the oxidation of sulfides in mine waste is a major environmental issue facing the mining industry today. Open pit mines, tailings ponds, ore stockpiles, and waste rock dumps can all be significant sources of pollution, primarily heavy metals. These large mining-induced footprints are often located across vast geographic expanses and are difficult to access. With the continuing advancement of imaging satellites, remote sensing may provide a useful monitoring tool for pit lake water quality and the rapid assessment of abandoned mine sites. This study explored the applications of laboratory spectroscopy and multi-season hyperspectral remote sensing for environmental monitoring of mine waste environments. Laboratory spectral experiments were first performed on acid mine waters and synthetic ferric iron solutions to identify and isolate the unique spectral properties of mine waters. These spectral characterizations were then applied to airborne hyperspectral imagery for identification of poor water quality in AMD ponds at the Leviathan Mine Superfund site, CA. Finally, imagery varying in temporal and spatial resolutions were used to identify changes in mineralogy over weathering overburden piles and on dry AMD pond liner surfaces at the Leviathan Mine. Results show the utility of hyperspectral remote sensing for monitoring a diverse range of surfaces associated with AMD.

Fluid Lensing based Machine Learning for Augmenting Earth Science Coral Datasets

NASA Astrophysics Data System (ADS)

Li, A.; Instrella, R.; Chirayath, V.

2016-12-01

Recently, there has been increased interest in monitoring the effects of climate change upon the world's marine ecosystems, particularly coral reefs. These delicate ecosystems are especially threatened due to their sensitivity to ocean warming and acidification, leading to unprecedented levels of coral bleaching and die-off in recent years. However, current global aquatic remote sensing datasets are unable to quantify changes in marine ecosystems at spatial and temporal scales relevant to their growth. In this project, we employ various supervised and unsupervised machine learning algorithms to augment existing datasets from NASA's Earth Observing System (EOS), using high resolution airborne imagery. This method utilizes NASA's ongoing airborne campaigns as well as its spaceborne assets to collect remote sensing data over these afflicted regions, and employs Fluid Lensing algorithms to resolve optical distortions caused by the fluid surface, producing cm-scale resolution imagery of these diverse ecosystems from airborne platforms. Support Vector Machines (SVMs) and K-mean clustering methods were applied to satellite imagery at 0.5m resolution, producing segmented maps classifying coral based on percent cover and morphology. Compared to a previous study using multidimensional maximum a posteriori (MAP) estimation to separate these features in high resolution airborne datasets, SVMs are able to achieve above 75% accuracy when augmented with existing MAP estimates, while unsupervised methods such as K-means achieve roughly 68% accuracy, verified by manually segmented reference data provided by a marine biologist. This effort thus has broad applications for coastal remote sensing, by helping marine biologists quantify behavioral trends spanning large areas and over longer timescales, and to assess the health of coral reefs worldwide.

Central Colorado Assessment Project - Application of integrated geologic, geochemical, biologic, and mineral resource studies

USGS Publications Warehouse

Klein, T.L.; Church, S.E.; Caine, Jonathan S.; Schmidt, T.S.; deWitt, E.H.

2008-01-01

Cooperative studies by USDA Forest Service, National Park Service supported by the USGS Mineral Resources Program (MRP), and National Cooperative Geologic Mapping Programs (NCGMP) contributed to the mineral-resource assessment and included regional geologic mapping at the scale 1:100,000, collection and geochemical studies of stream sediments, surface water, and bedrock samples, macroinvertebrate and biofilm studies in the riparian environment, remote-sensing studies, and geochronology. Geoscience information available as GIS layers has improved understanding of the distribution of metallic, industrial, and aggregate resources, location of areas that have potential for their discovery or development, helped to understand the relation of tectonics, magmatism, and paleohydrology to the genesis of the metal deposits in the region, and provided insight on the geochemical and environmental effects that historical mining and natural, mineralized rock exposures have on surface water, ground water, and aquatic life.

Application of aerial photography to water-related programs in Michigan

NASA Technical Reports Server (NTRS)

Enslin, W. R.; Hill-Rowley, R.; Tilmann, S. E.

1977-01-01

Aerial photography and information system technology were used to generate information required for the effective operation of three water-related programs in Michigan. Potential mosquito breeding sites were identified from specially acquired low altitude 70 mm color photography for the city of Lansing; the inventory identified 35% more surface water areas than indicated on existing field maps. A comprehensive inventory of surface water sources and potential access sites was prepared to assist fire departments in Antrim County with fire truck water-recharge operations. Remotely-sensed land cover/use data for Windsor Township, Eaton County, were integrated with other resource data into a computer-based information system for regional water quality studies. Eleven thematic maps focusing on landscape features affecting non-point water pollution and waste disposal were generated from analyses of a four-hectare grid-based data file containing land cover/use, soils, topographic and geologic (well-log) data.

Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations

NASA Astrophysics Data System (ADS)

Zeng, Z.; Zhang, K.; Xue, X.; Hong, Y.

2016-12-01

Impervious surface areas around the globe are expanding and significantly altering the surface energy balance, hydrology cycle and ecosystem services. Many studies have underlined the importance of impervious surface, r from hydrological modeling to contaminant transport monitoring and urban development estimation. Therefore accurate estimation of the global impervious surface is important for both physical and social sciences. Given the limited coverage of high spatial resolution imagery and ground survey, using satellite remote sensing and geospatial data to estimate global impervious areas is a practical approach. Based on the previous work of area-weighted imperviousness for north branch of the Chicago River provided by HDR, this study developed a method to determine the percentage of impervious surface using latest global land cover categories from multi-source satellite observations, population density and gross domestic product (GDP) data. Percent impervious surface at 30-meter resolution were mapped. We found that 1.33% of the CONUS (105,814 km2) and 0.475% of the land surface (640,370km2) are impervious surfaces. To test the utility and practicality of the proposed method, National Land Cover Database (NLCD) 2011 percent developed imperviousness for the conterminous United States was used to evaluate our results. The average difference between the derived imperviousness from our method and the NLCD data across CONUS is 1.14%, while difference between our results and the NLCD data are within ±1% over 81.63% of the CONUS. The distribution of global impervious surface map indicates that impervious surfaces are primarily concentrated in China, India, Japan, USA and Europe where are highly populated and/or developed. This study proposes a straightforward way of mapping global imperviousness, which can provide useful information for hydrologic modeling and other applications.

Glacier Changes in the Nanga Parbat Region, NW Himalaya: A longitudinal study over 160 years (1856-2016)

NASA Astrophysics Data System (ADS)

Nüsser, Marcus; Schmidt, Susanne

2017-04-01

Against the background of the prominent Himalayan glacier debate of the past decade, global concerns were raised about the severe consequences of detected and expected changes in the South Asian cryosphere. Due to the lack of historical glaciological data in the Himalayan region, studies of glacier changes over long time periods are rare. The present study seeks to analyze and quantify glacier changes in the Nanga Parbat region between 1856 and 2016. Due to the steep topography and great vertical span, the debris-covered glaciers of the mountain massif are largely fed by avalanches of different size. This impact of snow and ice re-distribution by avalanches is often neglected in glacier mass-balances. Therefore, an integrated approach was used to investigate the glacier changes and the impact of avalanches. This approach includes (1) a re-photographic survey with images from several expeditions between 1934 and 2010, (2) mapping during own field surveys between 1992 and 2010, as well as (3) the analyses of remote sensing data (Corona, QuickBird, KompSat, Landsat, etc. and DEM) and (4) historical topographic maps. The re-photographic survey allows for direct comparisons and illustrates glacier changes over a span of seventy years. Changes of glacier lengths were quantified by using remote sensing data and the topographic map of 1934. In order to calculate glacier surface changes, a digital elevation model (DEM) with a spatial resolution of 30 x 30 m2 was derived from the digitized contour lines of the topographic map from 1934 and compared to SRTM-DEM (30 x 30 m2) and ALOS-DSM. Based on remote sensing time-series, avalanche deposits on glaciers were mapped in order to identify their magnitude and frequencies. To calculate the potential glacier catchment, area of steep rock walls and the ratio between accumulation and ablation zones were calculated for each glacier basin. Our field based investigations show that the glaciers in the Rupal Valley are characterized by small retreating rates since 1856, when Adolph Schlagintweit mapped them for the first time; others such as the Raikot Glacier on the northern side of the Nanga Parbat are fluctuating since 1934.

Fusion of multi-source remote sensing data for agriculture monitoring tasks

NASA Astrophysics Data System (ADS)

Skakun, S.; Franch, B.; Vermote, E.; Roger, J. C.; Becker Reshef, I.; Justice, C. O.; Masek, J. G.; Murphy, E.

2016-12-01

Remote sensing data is essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEO-GLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated. Here, we present several case studies of utilizing MODIS, Landsat-8 and Sentinel-2 data along with meteorological data (growing degree days - GDD) for winter wheat yield forecasting, mapping and area estimation. Archived coarse spatial resolution data, such as MODIS, VIIRS and AVHRR, can provide daily global observations that coupled with statistical data on crop yield can enable the development of empirical models for timely yield forecasting at national level. With the availability of high-temporal and high spatial resolution Landsat-8 and Sentinel-2A imagery, course resolution empirical yield models can be downscaled to provide yield estimates at regional and field scale. In particular, we present the case study of downscaling the MODIS CMG based generalized winter wheat yield forecasting model to high spatial resolution data sets, namely harmonized Landsat-8 - Sentinel-2A surface reflectance product (HLS). Since the yield model requires corresponding in season crop masks, we propose an automatic approach to extract winter crop maps from MODIS NDVI and MERRA2 derived GDD using Gaussian mixture model (GMM). Validation for the state of Kansas (US) and Ukraine showed that the approach can yield accuracies > 90% without using reference (ground truth) data sets. Another application of yearly derived winter crop maps is their use for stratification purposes within area frame sampling for crop area estimation. In particular, one can simulate the dependence of error (coefficient of variation) on the number of samples and strata size. This approach was used for estimating the area of winter crops in Ukraine for 2013-2016. The GMM-GDD approach is further extended for HLS data to provide automatic winter crop mapping at 30 m resolution for crop yield model and area estimation. In case of persistent cloudiness, addition of Sentinel-1A synthetic aperture radar (SAR) images is explored for automatic winter crop mapping.

Drone based structural mapping at Holuhraun indicates fault reactivation and complexity

NASA Astrophysics Data System (ADS)

Mueller, Daniel; Walter, Thomas R.; Steinke, Bastian; Witt, Tanja; Schoepa, Anne; Duerig, Tobi; Gudmundsson, Magnus T.

2016-04-01

Accompanied by an intense seismic swarm in August 2014, a dike laterally formed, starting under Icelands Vatnajökull glacier, propagating over a distance of more than 45 km within only two weeks, leading to the largest eruption by volume since the 1783-84 Laki eruption. Along its propagation path, the dike caused intense surface displacements up to meters. Based on seismicity, GPS and InSAR, the propagation has already been analysed and described as segmented lateral dike growth. We now focus on few smaller regions of the dike. We consider the Terrasar-X tandem digital elevation map and aerial photos and find localized zones where structural fissures formed and curved. At these localized, regions we performed a field campaign in summer 2015, applying the close range remote sensing techniques Structure from Motion (SfM) and Terrestrial Laser Scanning (TLS). Over 4 TLS scan were collected, along with over 5,000 aerial images. Point clouds from SfM and TLS are merged and compared, and local structural lineaments analysed. As a result, we obtained an unprecedentedly high-resolution digital elevation map. With this map, we analyse the structural expression of the fissure eruption at the surface and improve understanding on the conditions that influenced the magma propagation path. We elaborate scenarios that lead to complexities of the surface structures and the link to the underlying dike intrusion.

HCMM satellite follow-on investigation no. 25. Soil moisture and heat budget evalution in selected European zones of agricultural and environmental interest (TELLUS project)

NASA Technical Reports Server (NTRS)

1980-01-01

A simple procedure to evaluate actual evaporation was derived by linearizing the surface energy balance equation, using Taylor's expansion. The original multidimensional hypersurface could be reduced to a linear relationship between evaporation and surface temperature or to a surface relationship involving evaporation, surface temperature and albedo. This procedure permits a rapid sensitivity analysis of the surface energy balance equation as well as a speedy mapping of evaporation from remotely sensed surface temperatures and albedo. Comparison with experimental data yielded promising results. The validity of evapotranspiration and soil moisture models in semiarid conditions was tested. Wheat was the crop chosen for a continuous measurement campaign made in the south of Italy. Radiometric, micrometeorologic, agronomic and soil data were collected for processing and interpretation.

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

PubMed Central

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G.; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Background Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level. PMID:22235254

Mapping migratory bird prevalence using remote sensing data fusion.

PubMed

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

PRELIMINARY INVESTIGATION OF SUBMERGED AQUATIC VEGETATION MAPPING USING HYPERSPECTRAL REMOTE SENSING

EPA Science Inventory

The use of airborne hyperspectral remote sensing imagery for automated mapping of submersed aquatic vegetation in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery, together with in-situ spectral refl...

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

Satellite remote sensing has provided massive data that improve the overall accuracy and extend the time series of environmental studies. In reflective solar bands, satellite data are related to land surface properties via radiative transfer (RT) equations. These equations generally include sensor-related (calibration coefficients), atmosphere-related (aerosol optical thickness) and surface-related (surface reflectance) parameters. It is an ill-posed problem to solve three parameters with only one RT equation. Even if there are two RT equations (dual-sensor data), the problem is still unsolvable. However, a robust solution can be obtained when any two parameters are known. If surface and atmosphere are known, sensor intercalibration can be performed. For example, the Advanced Very High Resolution Radiometer (AVHRR) was calibrated to the MODerate-resolution Imaging Spectroradiometer (MODIS) in Fan and Liu (2014) [Fan, X., and Liu, Y. (2014). Quantifying the relationship between intersensor images in solar reflective bands: Implications for intercalibration. IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7727-7737.]. If sensor and surface are known, atmospheric data can be retrieved. For example, aerosol data were retrieved using tandem TERRA and AQUA MODIS images in Fan and Liu (2016a) [Fan, X., and Liu, Y. (2016a). Exploiting TERRA-AQUA MODIS relationship in the reflective solar bands for aerosol retrieval. Remote Sensing, 8(12), 996.]. If sensor and atmosphere are known, data consistency can be obtained. For example, Normalized Difference Vegetation Index (NDVI) data were intercalibrated among coarse-resolution sensors in Fan and Liu (2016b) [Fan, X., and Liu, Y. (2016b). A global study of NDVI difference among moderate-resolution satellite sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 177-191.], and among fine-resolution sensors in Fan and Liu (2017) [Fan, X., and Liu, Y. (2017). A generalized model for intersensor NDVI calibration and its comparison with regression approaches. IEEE Transactions on Geoscience and Remote Sensing, 55(3), doi: 10.1109/TGRS.2016.2635802.]. These studies demonstrate the success of multi-sensor data and novel methods in the research domain of geoscience. These data will benefit remote sensing of terrestrial parameters in decadal timescales, such as soil salinity content in Fan et al. (2016) [Fan, X., Weng, Y., and Tao, J. (2016). Towards decadal soil salinity mapping using Landsat time series data. International Journal of Applied Earth Observation and Geoinformation, 52, 32-41.].

Gravity changes, soil moisture and data assimilation

NASA Astrophysics Data System (ADS)

Walker, J.; Grayson, R.; Rodell, M.; Ellet, K.

2003-04-01

Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground-based gravity measurements will also be made on a monthly basis at each monitoring site. There will be two levels of modelling and monitoring; regional across the entire Murrumbidgee Catchment (100,000 km2), and local across a small sub-catchment (150 km2).

Landscape effects of wildfire on permafrost distribution in interior Alaska derived from remote sensing

USGS Publications Warehouse

Brown, Dana R. N.; Jorgenson, M. Torre; Kielland, Knut; Verbyla, David L.; Prakash, Anupma; Koch, Joshua C.

2016-01-01

Climate change coupled with an intensifying wildfire regime is becoming an important driver of permafrost loss and ecosystem change in the northern boreal forest. There is a growing need to understand the effects of fire on the spatial distribution of permafrost and its associated ecological consequences. We focus on the effects of fire a decade after disturbance in a rocky upland landscape in the interior Alaskan boreal forest. Our main objectives were to (1) map near-surface permafrost distribution and drainage classes and (2) analyze the controls over landscape-scale patterns of post-fire permafrost degradation. Relationships among remote sensing variables and field-based data on soil properties (temperature, moisture, organic layer thickness) and vegetation (plant community composition) were analyzed using correlation, regression, and ordination analyses. The remote sensing data we considered included spectral indices from optical datasets (Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI)), the principal components of a time series of radar backscatter (Advanced Land Observing Satellite—Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR)), and topographic variables from a Light Detection and Ranging (LiDAR)-derived digital elevation model (DEM). We found strong empirical relationships between the normalized difference infrared index (NDII) and post-fire vegetation, soil moisture, and soil temperature, enabling us to indirectly map permafrost status and drainage class using regression-based models. The thickness of the insulating surface organic layer after fire, a measure of burn severity, was an important control over the extent of permafrost degradation. According to our classifications, 90% of the area considered to have experienced high severity burn (using the difference normalized burn ratio (dNBR)) lacked permafrost after fire. Permafrost thaw, in turn, likely increased drainage and resulted in drier surface soils. Burn severity also influenced plant community composition, which was tightly linked to soil temperature and moisture. Overall, interactions between burn severity, topography, and vegetation appear to control the distribution of near-surface permafrost and associated drainage conditions after disturbance.

Remote sensing techniques for conservation and management of natural vegetation ecosystems

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

1981-01-01

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

Remote sensing algorithm for sea surface CO2 in the Baltic Sea

NASA Astrophysics Data System (ADS)

Parard, G.; Charantonis, A. A.; Rutgerson, A.

2014-08-01

Studies of coastal seas in Europe have brought forth the high variability in the CO2 system. This high variability, generated by the complex mechanisms driving the CO2 fluxes makes their accurate estimation an arduous task. This is more pronounced in the Baltic Sea, where the mechanisms driving the fluxes have not been as highly detailed as in the open oceans. In adition, the joint availability of in-situ measurements of CO2 and of sea-surface satellite data is limited in the area. In this paper, a combination of two existing methods (Self-Organizing-Maps and Multiple Linear regression) is used to estimate ocean surface pCO2 in the Baltic Sea from remotely sensed surface temperature, chlorophyll, coloured dissolved organic matter, net primary production and mixed layer depth. The outputs of this research have an horizontal resolution of 4 km, and cover the period from 1998 to 2011. The reconstructed pCO2 values over the validation data set have a correlation of 0.93 with the in-situ measurements, and a root mean square error is of 38 μatm. The removal of any of the satellite parameters degraded this reconstruction of the CO2 flux, and we chose therefore to complete any missing data through statistical imputation. The CO2 maps produced by this method also provide a confidence level of the reconstruction at each grid point. The results obtained are encouraging given the sparsity of available data and we expect to be able to produce even more accurate reconstructions in the coming years, in view of the predicted acquisitions of new data.

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.

Land surface and climate parameters and malaria features in Vietnam

NASA Astrophysics Data System (ADS)

Liou, Y. A.; Anh, N. K.

2017-12-01

Land surface parameters may affect local microclimate, which in turn alters the development of mosquito habitats and transmission risks (soil-vegetation-atmosphere-vector borne diseases). Forest malaria is a chromic issue in Southeast Asian countries, in particular, such as Vietnam (in 1991, approximate 2 million cases and 4,646 deaths were reported (https://sites.path.org)). Vietnam has lowlands, sub-tropical high humidity, and dense forests, resulting in wide-scale distribution and high biting rate of mosquitos in Vietnam, becoming a challenging and out of control scenario, especially in Vietnamese Central Highland region. It is known that Vietnam's economy mainly relies on agriculture and malaria is commonly associated with poverty. There is a strong demand to investigate the relationship between land surface parameters (land cover, soil moisture, land surface temperature, etc.) and climatic variables (precipitation, humidity, evapotranspiration, etc.) in association with malaria distribution. GIS and remote sensing have been proven their powerful potentials in supporting environmental and health studies. The objective of this study aims to analyze physical attributes of land surface and climate parameters and their links with malaria features. The outcomes are expected to illustrate how remotely sensed data has been utilized in geohealth applications, surveillance, and health risk mapping. In addition, a platform with promising possibilities of allowing disease early-warning systems with citizen participation will be proposed.

Estimation of both optical and nonoptical surface water quality parameters using Landsat 8 OLI imagery and statistical techniques

NASA Astrophysics Data System (ADS)

Sharaf El Din, Essam; Zhang, Yun

2017-10-01

Traditional surface water quality assessment is costly, labor intensive, and time consuming; however, remote sensing has the potential to assess surface water quality because of its spatiotemporal consistency. Therefore, estimating concentrations of surface water quality parameters (SWQPs) from satellite imagery is essential. Remote sensing estimation of nonoptical SWQPs, such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), and dissolved oxygen (DO), has not yet been performed because they are less likely to affect signals measured by satellite sensors. However, concentrations of nonoptical variables may be correlated with optical variables, such as turbidity and total suspended sediments, which do affect the reflected radiation. In this context, an indirect relationship between satellite multispectral data and COD, BOD, and DO can be assumed. Therefore, this research attempts to develop an integrated Landsat 8 band ratios and stepwise regression to estimate concentrations of both optical and nonoptical SWQPs. Compared with previous studies, a significant correlation between Landsat 8 surface reflectance and concentrations of SWQPs was achieved and the obtained coefficient of determination (R2)>0.85. These findings demonstrated the possibility of using our technique to develop models to estimate concentrations of SWQPs and to generate spatiotemporal maps of SWQPs from Landsat 8 imagery.

Evaluation of potential surface rupture and review of current seismic hazards program at the Los Alamos National Laboratory. Final report

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

Not Available

1991-12-09

This report summarizes the authors review and evaluation of the existing seismic hazards program at Los Alamos National Laboratory (LANL). The report recommends that the original program be augmented with a probabilistic analysis of seismic hazards involving assignment of weighted probabilities of occurrence to all potential sources. This approach yields a more realistic evaluation of the likelihood of large earthquake occurrence particularly in regions where seismic sources may have recurrent intervals of several thousand years or more. The report reviews the locations and geomorphic expressions of identified fault lines along with the known displacements of these faults and last knowmore » occurrence of seismic activity. Faults are mapped and categorized into by their potential for actual movement. Based on geologic site characterization, recommendations are made for increased seismic monitoring; age-dating studies of faults and geomorphic features; increased use of remote sensing and aerial photography for surface mapping of faults; the development of a landslide susceptibility map; and to develop seismic design standards for all existing and proposed facilities at LANL.« less

Thematic Conference on Geologic Remote Sensing, 8th, Denver, CO, Apr. 29-May 2, 1991, Proceedings. Vols. 1 & 2

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.

NASAs Evolvable Mars Campaign: Mars Moons Robotic Precursor

NASA Technical Reports Server (NTRS)

Gernhardt, Michael L.; Abercromby, Andrew F. J.; Abell, Paul A.; Love, Stanley G.; Lee, David E.; Chappell, Steven P.; Howe, A. Scott; Friedensen, Victoria

2015-01-01

Human exploration missions to the moons of Mars are being considered within NASA's Evolvable Mars Campaign (EMC) as an intermediate step for eventual human exploration and pioneering of the surface of Mars. A range of mission architectures is being evaluated in which human crews would explore one or both moons for as little as 14 days or for as long as 500 days with a variety of orbital and surface habitation and mobility options being considered. Relatively little is known about the orbital, surface, or subsurface characteristics of either moon. This makes them interesting but challenging destinations for human exploration missions during which crewmembers must be able to effectively conduct scientific exploration without being exposed to undue risks due to radiation, dust, micrometeoroids, or other hazards. A robotic precursor mission to one or both moons will be required to provide data necessary for the design and operation of subsequent human systems and for the identification and prioritization of scientific exploration objectives. This paper identifies and discusses considerations for the design of such a precursor mission based on current human mission architectures. Objectives of a Mars' moon precursor in support of human missions are expected to include: 1) identifying hazards on the surface and the orbital environment at up to 50-km distant retrograde orbits; 2) collecting data on physical characteristics for planning of detailed human proximity and surface operations; 3) performing remote sensing and in situ science investigations to refine and focus future human scientific activities; and 4) prospecting for in situ resource utilization. These precursor objectives can be met through a combination or remote sensing (orbital) and in-situ (surface) measurements. Analysis of spacecraft downlink signals using radio science techniques would measure the moon's mass, mass distribution, and gravity field, which will be necessary to enable trajectory planning. Laser altimetry would precisely measure the moon's shape and improve the accuracy of radio science measurements. A telescopic imaging camera would map the moon at submeter resolution and photograph selected areas of interest at subcentimeter resolution and a visible and near-infrared (0.4-3.0 mm) imaging spectrograph would produce a global map of mineral composition variations at a resolution of tens of meters and maps of selected areas of interest at meter resolution. Additional remote sensing capabilities could include a thermal infrared imager (heat flow, thermal inertia, and grain size distributions), a gamma-ray and neutron detector (atomic composition), a ground-penetrating radar (internal structure), and a magnetometer and Langmuir probe (magnetic properties and plasma field). Once on the surface of Phobos or Deimos, necessary instrumentation would include a penetrometer (regolith compressive strength), a motion-imagery camera (to observe the penetrometer tests before, during, and after contact), a dust-adhesion witness plate and camera (dust levitation), a microimager (dust particle sizes and shapes), and an alpha-proton-X-ray, X-ray fluorescence, Mossbauer, or Raman spectrometer (atomic and mineral composition of surface materials) and an optional temperature probe (regolith thermal properties). A variety of robotic mission design options to enable both orbital and surface measurements are being considered that include fully integrated and modular approaches. In-situ measurements from at least one surface location would be required, with additional measurement locations possible through use of multiple landers, through propulsive relocation of a single lander, or through electromechanical surface translation by a walking or hopping lander vehicle, which could also serve to evaluate such mobility capabilities for subsequent human missions. Preliminary orbital analysis suggests that remote sensing would likely be performed while in a distant retrograde orbit around the target moon. Mission design options to enable characterization of both Mars’ moons in a single mission are also being studied.

Determination of lunar ilmentite abundances from remotely sensed data

NASA Technical Reports Server (NTRS)

Johnson, J. R.; Larson, S. M.; Singer, Robert B.

1990-01-01

The mapping of ilmenite on the surface of the moon is a necessary precursor to the investigation of prospective lunar base sites. Telescopic observations of the moon using a variety of narrow bandpass optical interference filters are being performed as a preliminary means of achieving this goal. Specifically, ratios of images obtained using filters centered at 0.40 and 0.56 microns provide quantitative estimates of TiO2 abundances. Analysis of preliminary distribution maps of TiO2 concentrations allows identification of specific high-Ti areas. Investigations of these areas using slit spectra in the range 0.03 to 0.85 microns are underway to search for discrete spectral signatures attributable to ilmenite.

Magnetic navigation and catheter ablation of right atrial ectopic tachycardia in the presence of a hemi-azygos continuation: a magnetic navigation case using 3D electroanatomical mapping.

PubMed

Ernst, Sabine; Chun, Julian K R; Koektuerk, Buelent; Kuck, Karl-Heinz

2009-01-01

We report on a 63-year-old female patient in whom an electrophysiologic study discovered a hemi-azygos continuation. Using the magnetic navigation system, remote-controlled ablation was performed in conjunction with the 3D electroanatomical mapping system. Failing the attempt to advance a diagnostic catheter from the femoral vein, a diagnostic catheter was advanced via the left subclavian vein into the coronary sinus. The soft magnetic catheter was positioned in the right atrium via the hemi-azygos vein, and 3D mapping demonstrated an ectopic atrial tachycardia. Successful ablation was performed entirely remote controlled. Fluoroscopy time was only 7.1 minutes, of which 45 seconds were required during remote navigation. Remote-controlled catheter ablation using magnetic navigation in conjunction with the electroanatomical mapping system proved to be a valuable tool to perform successful ablation in the presence of a hemi-azygos continuation.

Exploration of the Moon with Remote Sensing, Ground-Penetrating Radar, and the Regolith-Evolved Gas Analyzer (REGA)

NASA Technical Reports Server (NTRS)

Cooper, B. L.; Hoffman, J. H.; Allen, Carlton C.; McKay, David S.

1998-01-01

There are two important reasons to explore the Moon. First, we would like to know more about the Moon itself: its history, its geology, its chemistry, and its diversity. Second, we would like to apply this knowledge to a useful purpose. namely finding and using lunar resources. As a result of the recent Clementine and Lunar Prospector missions, we now have global data on the regional surface mineralogy of the Moon, and we have good reason to believe that water exists in the lunar polar regions. However, there is still very little information about the subsurface. If we wish to go to the lunar polar regions to extract water, or if we wish to go anywhere else on the Moon and extract (or learn) anything at all, we need information in three dimensions an understanding of what lies below the surface, both shallow and deep. The terrestrial mining industry provides an example of the logical steps that lead to an understanding of where resources are located and their economic significance. Surface maps are examined to determine likely locations for detailed study. Geochemical soil sample surveys, using broad or narrow grid patterns, are then used to gather additional data. Next, a detailed surface map is developed for a selected area, along with an interpretation of the subsurface structure that would give rise to the observed features. After that, further sampling and geophysical exploration are used to validate and refine the original interpretation, as well as to make further exploration/ mining decisions. Integrating remotely sensed, geophysical, and sample datasets gives the maximum likelihood of a correct interpretation of the subsurface geology and surface morphology. Apollo-era geophysical and automated sampling experiments sought to look beyond the upper few microns of the lunar surface. These experiments, including ground-penetrating radar and spectrometry, proved the usefulness of these methods for determining the best sites for lunar bases and lunar mining operations.

Improved Mapping of Carbon, Water and Energy Land-Surface Fluxes Using Remotely Sensed Indicators of Canopy Light Use Efficiency

NASA Astrophysics Data System (ADS)

Schull, M. A.; Anderson, M. C.; Kustas, W.; Cammalleri, C.; Houborg, R.

2012-12-01

A light-use-efficiency (LUE) based model of canopy resistance has been embedded into a thermal-based Two-Source Energy Balance (TSEB) model to facilitate coupled simulations of transpiration and carbon assimilation. The model assumes that deviations of the observed canopy LUE from a nominal stand-level value (LUEn - typically indexed by vegetation class) are due to varying conditions of light, humidity, CO2 concentration and leaf temperature. The deviations are accommodated by adjusting an effective LUE that responds to the varying conditions. The challenge to monitoring fluxes on a larger scale is to capture the physiological responses due to changing conditions. This challenge can be met using remotely sensed leaf chlorophyll (Cab). Since Cab is a vital pigment for absorbing light for use in photosynthesis, it has been recognized as a key parameter for quantifying photosynthetic functioning that are sensitive to these conditions. Recent studies have shown that it is sensitive to changes in LUE, which defines how efficiently a plant can assimilate carbon dioxide (CO2) given the absorbed Photosynthetically Active Radiation (PAR) and is therefore useful for monitoring carbon fluxes. We investigate the feasibility of leaf chlorophyll to capture these variations in LUEn using remotely sensed data. To retrieve Cab from remotely sensed data we use REGFLEC, a physically based tool that translates at-sensor radiances in the green, red and NIR spectral regions from multiple satellite sensors into realistic maps of LAI and Cab. Initial results show that Cab is exponentially correlated to light use efficiency. Incorporating nominal light use efficiency estimated from Cab is shown to improve fluxes of carbon, water and energy most notably in times of stressed vegetation. The result illustrates that Cab is sensitive to changes in plant physiology and can capture plant stress needed for improved estimation of fluxes. The observed relationship and initial results demonstrate the need for integrating remotely sensed Cab to facilitate improved mapping of coupled carbon, water, and energy fluxes across vegetated landscapes.

Husbandry Trace Gas Emissions from a Dairy Complex By Mobile in Situ and Airborne and Spaceborne Remote Sensing: A Comex Campaign Focus

NASA Astrophysics Data System (ADS)

Leifer, I.; Tratt, D. M.; Bovensmann, H.; Buckland, K. N.; Burrows, J. P.; Frash, J.; Gerilowski, K.; Iraci, L. T.; Johnson, P. D.; Kolyer, R.; Krautwurst, S.; Krings, T.; Leen, J. B.; Hu, C.; Melton, C.; Vigil, S. A.; Yates, E. L.; Zhang, M.

2014-12-01

Recent field study reviews on the greenhouse gas methane (CH4) found significant underestimation from fossil fuel industry and husbandry. The 2014 COMEX campaign seeks to develop methods to derive CH4 and carbon dioxide (CO2) from remote sensing data by combining hyperspectral imaging (HSI) and non-imaging spectroscopy (NIS) with in situ airborne and surface data. COMEX leverages synergies between high spatial resolution HSI column abundance maps and moderate spectral/spatial resolution NIS. Airborne husbandry data were collected for the Chino dairy complex (East Los Angeles Basin) by NIS-MAMAP, HSI-Mako thermal-infrared (TIR); AVIRIS NG shortwave IR (SWIR), with in situ surface mobile-AMOG Surveyor (AutoMObile greenhouse Gas)-and airborne in situ from a Twin Otter and the AlphaJet. AMOG Surveyor uses in situ Integrated Cavity Off Axis Spectroscopy (OA-ICOS) to measure CH4, CO2, H2O, H2S and NH3 at 5-10 Hz, 2D winds, and thermal anomaly in an adapted commuter car. OA-ICOS provides high precision and accuracy with excellent stability. NH3 and CH4 emissions were correlated at dairy size-scales but not sub-dairy scales in surface and Mako data, showing fine-scale structure and large variations between the numerous dairies in the complex (herd ~200,000-250,000) embedded in an urban setting. Emissions hotspots were consistent between surface and airborne surveys. In June, surface and MAMAP data showed a weak overall plume, while surface and Mako data showed a stronger plume in late (hotter) July. Multiple surface plume transects using NH3 fingerprinting showed East and then NE advection out of the LA Basin consistent with airborne data. Long-term trends were investigated in satellite data. This study shows the value of synergistically combined NH3 and CH4 remote sensing data to the task of CH4 source attribution using airborne and space-based remote sensing (IASI for NH3) and top of atmosphere sensitivity calculations for Sentinel V and Carbon Sat (CH4).

Cultural Resource Protection Plan for the Remote-Handled Low-Level Waste Disposal Facility at the Idaho National Laboratory

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

Pace, Brenda Ringe; Gilbert, Hollie Kae

2015-05-01

This plan addresses cultural resource protection procedures to be implemented during construction of the Remote Handled Low Level Waste project at the Idaho National Laboratory. The plan proposes pre-construction review of proposed ground disturbing activities to confirm avoidance of cultural resources. Depending on the final project footprint, cultural resource protection strategies might also include additional survey, protective fencing, cultural resource mapping and relocation of surface artifacts, collection of surface artifacts for permanent curation, confirmation of undisturbed historic canal segments outside the area of potential effects for construction, and/or archaeological test excavations to assess potential subsurface cultural deposits at known culturalmore » resource locations. Additionally, all initial ground disturbing activities will be monitored for subsurface cultural resource finds, cultural resource sensitivity training will be conducted for all construction field personnel, and a stop work procedure will be implemented to guide assessment and protection of any unanticipated discoveries after initial monitoring of ground disturbance.« less

Analysis Of Landslide Materials Spreading In Bendan Dhuwur Village Gajahmungkur Subdistrict Semarang City

NASA Astrophysics Data System (ADS)

Trisnawati, Devina; Najib; Kusuma, Istiqomah Ari; Husna, Anissa Fitratul

2018-02-01

Bendan Dhuwur is one of area in Semarang city, which continuously has landslide problem. This problem resulted in damage of some buildings and main road. Landslide materials/coluvial have been estimated lays on under those infrastructures and tend to move during rainy season. Therefore, it needs to understand the spread of coluvial to minimize the effect of landslide. Remote sensing method has been used to analyze multi temporal image for mapping landslide materials from different years recorded direction of creep and spread of coluvials. This method has been combined with surface and subsurface data from mapping and resistivity data. The analysis result on map which show that the coluvial material spreads on the south side, beneath the University of Tujuh Belas Agustus construction and Pawiyatan Luhur road. Its move to east leads to the Kaligarang river.

High Resolution Mapping of Soils and Landforms for the Desert Renewable Energy Conservation Plan (DRECP)

NASA Technical Reports Server (NTRS)

Potter, Christopher S.; Li, Shuang

2014-01-01

The Desert Renewable Energy Conservation Plan (DRECP), a major component of California's renewable energy planning efforts, is intended to provide effective protection and conservation of desert ecosystems, while allowing for the sensible development of renewable energy projects. This NASA mapping report was developed to support the DRECP and the Bureau of Land Management (BLM). We outline in this document remote sensing image processing methods to deliver new maps of biological soils crusts, sand dune movements, desert pavements, and sub-surface water sources across the DRECP area. We focused data processing first on the largely unmapped areas most likely to be used for energy developments, such as those within Renewable Energy Study Areas (RESA) and Solar Energy Zones (SEZs). We used imagery (multispectral and radar) mainly from the years 2009-2011.

Integrated landscape-based approach of remote sensing, GIS, and physical modelling to study the hydrological connectivity of wetlands to the downstream water: progress and challenge

NASA Astrophysics Data System (ADS)

Yeo, I. Y.

2015-12-01

We report the recent progress on our effort to improve the mapping of wetland dynamics and the modelling of its functioning and hydrological connection to the downstream waters. Our study focused on the Coastal Plain of the Chesapeake Bay Watershed (CBW), the Delmarva Peninsula, where the most of wetlands in CBW are densely distributed. The wetland ecosystem plays crucial roles in improving water quality and ecological integrity for the downstream waters and the Chesapeake Bay, and headwater wetlands in the region, such as Delmarva Bay, are now subject to the legal protection under the Clean Water Rules. We developed new wetland maps using time series Landsat images and a highly accurate LiDAR map over last 30 years. These maps show the changes in surface water fraction at a 30-m grid cell at annual time scale. Using GIS, we analyse these maps to characterize changing dynamics of wetland inundation due to the physical environmental factors (e.g., weather variability, tide) and assessed the hydrological connection of wetlands to the downstream water at the watershed scale. Focusing on the two adjacent watersheds in the upper region of the Choptank River Basin, we study how wetland inundation dynamics and the hydrologic linkage of wetlands to downstream water would vary by the local hydrogeological setting and attempt to identify the key landscape factors affecting the wetland ecosystems and functioning. We then discuss the potential of using remote sensing products to improve the physical modelling of wetlands from our experience with SWAT (Soil and Water Assessment Tool).

Mapping temperature and radiant geothermal heat flux anomalies in the Yellowstone geothermal system using ASTER thermal infrared data

USGS Publications Warehouse

Vaughan, R. Greg; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.; Jaworowski, Cheryl; Heasler, Henry

2012-01-01

The purpose of this work was to use satellite-based thermal infrared (TIR) remote sensing data to measure, map, and monitor geothermal activity within the Yellowstone geothermal area to help meet the missions of both the U.S. Geological Survey Yellowstone Volcano Observatory and the Yellowstone National Park Geology Program. Specifically, the goals were to: 1) address the challenges of remotely characterizing the spatially and temporally dynamic thermal features in Yellowstone by using nighttime TIR data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and 2) estimate the temperature, geothermal radiant emittance, and radiant geothermal heat flux (GHF) for Yellowstone’s thermal areas (both Park wide and for individual thermal areas). ASTER TIR data (90-m pixels) acquired at night during January and February, 2010, were used to estimate surface temperature, radiant emittance, and radiant GHF from all of Yellowstone’s thermal features, produce thermal anomaly maps, and update field-based maps of thermal areas. A background subtraction technique was used to isolate the geothermal component of TIR radiance from thermal radiance due to insolation. A lower limit for the Yellowstone’s total radiant GHF was established at ~2.0 GW, which is ~30-45% of the heat flux estimated through geochemical (Cl-flux) methods. Additionally, about 5 km2 was added to the geodatabase of mapped thermal areas. This work provides a framework for future satellite-based thermal monitoring at Yellowstone as well as exploration of other volcanic / geothermal systems on a global scale.

Effectiveness of Vegetation Index Transformation for Land Use Identifying and Mapping in the Area of Oil palm Plantation based on SPOT-6 Imagery (Case Study: PT.Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu)

NASA Astrophysics Data System (ADS)

Setyowati, H. A.; S, S. H. Murti B.; Sukentyas, E. S.

2016-11-01

The reflection of land surface, atmosphere and vegetation conditions affect the reflectance value of the object is recorded on remote sensing image so that it can affect the outcome of information extraction from remote sensing imagery one multispectral classification. This study aims to assess the ability of the transformation of generic vegetation index (Wide Dynamic Range Vegetation Index), the vegetation index transformation that is capable reducing the influence of the atmosphere (Atmospherically Resistant Vegetation Index), and the transformation of vegetation index that is capable of reducing the influence of the background soil (Second Modified Soil Adjusted Vegetation Index) for the identification and mapping of land use in the oil palm plantation area based on SPOT-6 archived on June 13, 2013 from LAPAN. The study area selected oil palm plantations PT. Tunggal Perkasa Plantations, Air Molek, Indragiri Hulu, Riau Province. The method is using the transformation of the vegetation index ARVI, MSAVI2, and WDRVI. Sample selection method used was stratified random sampling. The test method used mapping accuracy of the confusion matrix. The results showed that the best transformation of the vegetation index for the identification and mapping of land use in the plantation area is ARVI transformation with a total of accuracy is 96%. Accuracy of mapping land use settlements 100%, replanting 82.35%, 81.25% young oil palm, old oil palm 99.46%, 100% bush, body of water 100%, and 100% bare-soil.

The workshop. [use and application of remotely sensed data

NASA Technical Reports Server (NTRS)

Wake, W. H.

1981-01-01

The plan is presented for a two day workshop held to provide educational and training experience in the reading, interpretation, and application of LANDSAT and correlated larger scale imagery, digital printout maps, and other collateral material for a large number of participants with widely diverse levels of expertise, backgrounds, and occupations in government, industry, and education. The need for using surface truth field studies with correlated aerial imagery in solving real world problems was demonstrated.

Mapping of Coral Reef Environment in the Arabian Gulf Using Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Ben-Romdhane, H.; Marpu, P. R.; Ghedira, H.; Ouarda, T. B. M. J.

2016-06-01

Coral reefs of the Arabian Gulf are subject to several pressures, thus requiring conservation actions. Well-designed conservation plans involve efficient mapping and monitoring systems. Satellite remote sensing is a cost-effective tool for seafloor mapping at large scales. Multispectral remote sensing of coastal habitats, like those of the Arabian Gulf, presents a special challenge due to their complexity and heterogeneity. The present study evaluates the potential of multispectral sensor DubaiSat-2 in mapping benthic communities of United Arab Emirates. We propose to use a spectral-spatial method that includes multilevel segmentation, nonlinear feature analysis and ensemble learning methods. Support Vector Machine (SVM) is used for comparison of classification performances. Comparative data were derived from the habitat maps published by the Environment Agency-Abu Dhabi. The spectral-spatial method produced 96.41% mapping accuracy. SVM classification is assessed to be 94.17% accurate. The adaptation of these methods can help achieving well-designed coastal management plans in the region.

Preliminary study of near surface detections at geothermal field using optic and SAR imageries

NASA Astrophysics Data System (ADS)

Kurniawahidayati, Beta; Agoes Nugroho, Indra; Syahputra Mulyana, Reza; Saepuloh, Asep

2017-12-01

Current remote sensing technologies shows that surface manifestation of geothermal system could be detected with optical and SAR remote sensing, but to assess target beneath near the surface layer with the surficial method needs a further study. This study conducts a preliminary result using Optic and SAR remote sensing imagery to detect near surface geothermal manifestation at and around Mt. Papandayan, West Java, Indonesia. The data used in this study were Landsat-8 OLI/TIRS for delineating geothermal manifestation prospect area and an Advanced Land Observing Satellite(ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) level 1.1 for extracting lineaments and their density. An assumption was raised that the lineaments correlated with near surface structures due to long L-band wavelength about 23.6 cm. Near surface manifestation prospect area are delineated using visual comparison between Landsat 8 RGB True Colour Composite band 4,3,2 (TCC), False Colour Composite band 5,6,7 (FCC), and lineament density map of ALOS PALSAR. Visual properties of ground object were distinguished from interaction of the electromagnetic radiation and object whether it reflect, scatter, absorb, or and emit electromagnetic radiation based on characteristic of their molecular composition and their macroscopic scale and geometry. TCC and FCC composite bands produced 6 and 7 surface manifestation zones according to its visual classification, respectively. Classified images were then compared to a Normalized Different Vegetation Index (NDVI) to obtain the influence of vegetation at the ground surface to the image. Geothermal area were classified based on vegetation index from NDVI. TCC image is more sensitive to the vegetation than FCC image. The later composite produced a better result for identifying visually geothermal manifestation showed by detail-detected zones. According to lineament density analysis high density area located on the peak of Papandayan overlaid with zone 1 and 2 of FCC. Comparing to the extracted lineament density, we interpreted that the near surface manifestation is located at zone 1 and 2 of FCC image.

Using electrical resistance tomography to map subsurface temperatures

DOEpatents

Ramirez, A.L.; Chesnut, D.A.; Daily, W.D.

1994-09-13

A method is provided for measuring subsurface soil or rock temperatures remotely using electrical resistivity tomography (ERT). Electrical resistivity measurements are made using electrodes implanted in boreholes driven into the soil and/or at the ground surface. The measurements are repeated as some process changes the temperatures of the soil mass/rock mass. Tomographs of electrical resistivity are calculated based on the measurements using Poisson's equation. Changes in the soil/rock resistivity can be related to changes in soil/rock temperatures when: (1) the electrical conductivity of the fluid trapped in the soil's pore space is low, (2) the soil/rock has a high cation exchange capacity and (3) the temperature changes are sufficiently high. When these three conditions exist the resistivity changes observed in the ERT tomographs can be directly attributed to changes in soil/rock temperatures. This method provides a way of mapping temperature changes in subsurface soils remotely. Distances over which the ERT method can be used to monitor changes in soil temperature range from tens to hundreds of meters from the electrode locations. 1 fig.

Using electrical resistance tomography to map subsurface temperatures

DOEpatents

Ramirez, Abelardo L.; Chesnut, Dwayne A.; Daily, William D.

1994-01-01

A method is provided for measuring subsurface soil or rock temperatures remotely using electrical resistivity tomography (ERT). Electrical resistivity measurements are made using electrodes implanted in boreholes driven into the soil and/or at the ground surface. The measurements are repeated as some process changes the temperatures of the soil mass/rock mass. Tomographs of electrical resistivity are calculated based on the measurements using Poisson's equation. Changes in the soil/rock resistivity can be related to changes in soil/rock temperatures when: (1) the electrical conductivity of the fluid trapped in the soil's pore space is low, (2) the soil/rock has a high cation exchange capacity and (3) the temperature changes are sufficiently high. When these three conditions exist the resistivity changes observed in the ERT tomographs can be directly attributed to changes in soil/rock temperatures. This method provides a way of mapping temperature changes in subsurface soils remotely. Distances over which the ERT method can be used to monitor changes in soil temperature range from tens to hundreds of meters from the electrode locations.

Groundwater resource exploration in Salem district, Tamil Nadu using GIS and remote sensing

NASA Astrophysics Data System (ADS)

Maheswaran, G.; Selvarani, A. Geetha; Elangovan, K.

2016-03-01

Since last decade, the value per barrel of potable groundwater has outpaced the value of a barrel of oil in many areas of the world. Hence, proper assessment of groundwater potential and management practices are the needs of the day. Establishing relationship between remote sensing data and hydrologic phenomenon can maximize the efficiency of water resources development projects. Present study focuses on groundwater potential assessment in Salem district, Tamil Nadu to investigate groundwater resource potential. At the same, all thematic layers important from ground water occurrence and movement point of view were digitized and integrated in the GIS environment. The weights of different parameters/themes were computed using weighed index overlay analysis (WIOA), analytic hierarchy process (AHP) and fuzzy logic technique. Through this integrated GIS analysis, groundwater prospect map of the study area was prepared qualitatively. Field verification at observation wells was used to verify identified potential zones and depth of water measured at observation wells. Generated map from weighed overlay using AHP performed very well in predicting the groundwater surface and hence this methodology proves to be a promising tool for future.

Sugarcane Crop Extraction Using Object-Oriented Method from ZY-3 High Resolution Satellite Tlc Image

NASA Astrophysics Data System (ADS)

Luo, H.; Ling, Z. Y.; Shao, G. Z.; Huang, Y.; He, Y. Q.; Ning, W. Y.; Zhong, Z.

2018-04-01

Sugarcane is one of the most important crops in Guangxi, China. As the development of satellite remote sensing technology, more remotely sensed images can be used for monitoring sugarcane crop. With the help of Three Line Camera (TLC) images, wide coverage and stereoscopic mapping ability, Chinese ZY-3 high resolution stereoscopic mapping satellite is useful in attaining more information for sugarcane crop monitoring, such as spectral, shape, texture difference between forward, nadir and backward images. Digital surface model (DSM) derived from ZY-3 TLC images are also able to provide height information for sugarcane crop. In this study, we make attempt to extract sugarcane crop from ZY-3 images, which are acquired in harvest period. Ortho-rectified TLC images, fused image, DSM are processed for our extraction. Then Object-oriented method is used in image segmentation, example collection, and feature extraction. The results of our study show that with the help of ZY-3 TLC image, the information of sugarcane crop in harvest time can be automatic extracted, with an overall accuracy of about 85.3 %.

Lidar-based fracture characterization: An outcrop-scale study of the Woodford Shale, McAlister Shale Pit, Oklahoma

NASA Astrophysics Data System (ADS)

Hanzel, Jason

The use of lidar (light detection and ranging), a remote sensing tool based on principles of laser optometry, in mapping complex, multi-scale fracture networks had not been rigorously tested prior to this study despite its foreseeable utility in interpreting rock fabric with imprints of complex tectonic evolution. This thesis demonstrates lidar-based characterization of the Woodford Shale where intense fracturing could be due to both tectonism and mineralogy. The study area is the McAlister Shale Pit in south-central Oklahoma where both the upper and middle sections of the Woodford Shale are exposed and can be lidar-mapped. Lidar results are validated using hand-measured strike and dips of fracture planes, thin sections and mineral chemistry of selected samples using X-ray diffraction (XRD). Complexity of the fracture patterns as well as inaccessibility of multiple locations within the shale pit makes hand-measurement prone to errors and biases; lidar provides an opportunity for less biased and more efficient field mapping. Fracture mapping with lidar is a multi-step process. The lidar data are converted from point clouds into a mesh through triangulation. User-defined parameters such as size and orientation of the individual triangular elements are then used to group similar elements into surfaces. The strike and dip attribute of the simulated surfaces are visualized in an equal area lower hemisphere projection stereonet. Three fracture sets were identified in the upper and middle sections with common orientation but substantially different spatial density. Measured surface attributes and spatial density relations from lidar were validated using their hand-measured counterparts. Thin section analysis suggests that high fracture density in the upper Woodford measured by both the lidar and the hand-measured data could be due to high quartz. A significant finding of this study is the reciprocal relation between lidar intensity and gamma-ray (GR), which is generally used to infer outcrop mineralogy. XRD analysis of representative samples along the common profiles show that both GR and lidar intensity were influenced by the same minerals in essentially opposite ways. Results strongly suggest that the lidar cannot only remotely map the geomorphology, but also the relative mineralogical variations to the first order of approximation.

Testing a small UAS for mapping artisanal diamond mining sites in Africa

USGS Publications Warehouse

Malpeli, Katherine C.; Chirico, Peter G.

2015-01-01

Remote sensing technology is advancing at an unprecedented rate. At the forefront of the new technological developments are unmanned aircraft systems (UAS). The advent of small, lightweight, low-cost, and user-friendly UAS is greatly expanding the potential applications of remote sensing technology and improving the set of tools available to researchers seeking to map and monitor terrain from above. In this article, we explore the applications of a small UAS for mapping informal diamond mining sites in Africa. We found that this technology provides aerial imagery of unparalleled resolution in a data-sparse, difficult to access, and remote terrain.

Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

NASA Astrophysics Data System (ADS)

Serafimovich, Andrei; Metzger, Stefan; Hartmann, Jörg; Kohnert, Katrin; Zona, Donatella; Sachs, Torsten

2018-03-01

The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June-July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

Integration of Remote Sensing and Geophysical Applications for Delineation of Geological Structures: Implication for Water Resources in Egypt

NASA Astrophysics Data System (ADS)

Mohamed, L.; Farag, A. Z. A.

2017-12-01

North African countries struggle with insufficient, polluted, oversubscribed, and increasingly expensive water. This natural water shortage, in addition to the lack of a comprehensive scheme for the identification of new water resources challenge the political settings in north Africa. Groundwater is one of the main water resources and its occurrence is controlled by the structural elements which are still poorly understood. Integration of remote sensing images and geophysical tools enable us to delineate the surface and subsurface structures (i.e. faults, joints and shear zones), identify the role of these structures on groundwater flow and then to define the proper locations for groundwater wells. This approach were applied to three different areas in Egypt; southern Sinai, north eastern Sinai and the Eastern Desert using remote sensing, geophysical and hydrogeological datasets as follows: (1) identification of the spatial and temporal rainfall events using meteorological station data and Tropical Rainfall Measuring Mission data; (2) delineation of major faults and shear zones using ALOS Palsar, Landsat 8 and ASTER images, geological maps and field investigation; (3) generation of a normalized difference ratio image using Envisat radar images before and after the rain events to identify preferential water-channeling discontinuities in the crystalline terrain; (4) analysis of well data and derivations of hydrological parameters; (5) validation of the water-channeling discontinuities using Very Low Frequency, testing the structural elements (pre-delineated by remote sensing data) and their depth using gravity, magnetic and Vertical Electrical Sounding methods; (6) generation of regional groundwater flow and isotopic (18O and 2H) distribution maps for the sedimentary aquifer and an approximation flow map for the crystalline aquifer. The outputs include: (1) a conceptual/physical model for the groundwater flow in fractured crystalline and sedimentary aquifers; (2) locations of suggested new wells in light of the findings.

Hyperspectral sensors and the conservation of monumental buildings

NASA Astrophysics Data System (ADS)

Camaiti, Mara; Benvenuti, Marco; Chiarantini, Leandro; Costagliola, Pilar; Moretti, Sandro; Paba, Francesca; Pecchioni, Elena; Vettori, Silvia

2010-05-01

The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties including moisture, organic content and salinity (2). Among the existing VNIR techniques (Laboratory Spectroscopy - LS, Portable Spectroscopy - PS and Imaging Spectroscopy - IS), PS and IS can play a crucial role in the characterization of components of exposed stone surfaces. In particular, the Imaging Spectroscopic (remote sensing), which uses sensors placed both on land or airborne, may contribute to the monitoring of large areas in consideration of its ability to produce large areal maps at relatively low costs. In this presentation the application of hyperspectral instruments (mainly PS and IS, not applied before in the field of monumental building diagnostic) to quantify the degradation of carbonate surfaces will be discussed. In particular, considering gypsum as the precursor symptom of damage, many factors which may affect the estimation of gypsum content on the surface will be taken into consideration. Two hyperspectral sensors will be considered: 1) A portable radiometer (ASD-FieldSpec FP Pro spectroradiometer), which continuously acquires punctual reflectance spectra in the range 350-2500 nm, both in natural light conditions and by a contact probe (fixed geometry of shot). This instrument is used on field for the identification of different materials, as well as for the definition of maps (e.g geological maps) if coupled with other hyperspectral instruments. 2) Hyperspectral sensor SIM-GA (Selex Galileo Multisensor Hyperspectral System), a system with spatial acquisition of data which may be used on an earth as well as on an airborne platform. SIM-GA consists of two electro-optical heads, which operate in the VNIR and SWIR regions, respectively, between 400-1000 nm and 1000-2500 nm (3). Although the spectral signature in the VNIR of many minerals is known, the co-presence of more minerals on a surface can affect the quantitative analysis of gypsum. Different minerals, such as gypsum, calcite, weddellite, whewellite, and other components (i.e. carbon particles in black crusts) are, in fact, commonly found on historical surfaces. In order to illustrate the complexity, but also the potentiality of hyperspectral sensors (portable or remote sensing) for the characterization of stone surfaces, a case study, the Facade of Santa Maria Novella in Florence - Italy, will be presented. References 1) R.N. Clark and G.A. Swayze, 1995, "Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice, and snow, and other materials: The USGS Tricorder Algorithm", in "Summaries of the Fifth Annual JPL Airborne Earth Science Workshop", JPL Publication 95-1,1,39-40 2) E. Ben-Dor, K. Patin, A. Banin and A. Karnieli, 2002, "Mapping of several soil properties using DATS-7915 hyperspectral scanner data. A case study over clayely soils in Israel", International Journal of Remote Sensing, 23(6), 1043-1062 3) S. Vettori, M. Benvenuti, M. Camaiti, L. Chiarantini, P. Costagliola, S. Moretti, E. Pecchioni, 2008, "Assessment of the deterioration status of historical buildings by Hyperspectral Imaging techniques", in Proceedings of the "In situ Monitoring of Monumental Surfaces -SMS/08" Congress, Edifir-Edizioni Firenze 2008, 55-64

The Phobos Atlas and Geo-portal: geodesy and cartography approach for planetary exploration

NASA Astrophysics Data System (ADS)

Karachevtseva, Irina; Kozlova, Natalia; Kokhanov, Alexander; Oberst, Jürgen; Zubarev, Anatoliy; Nadezhdina, Irina; Patraty, Vyacheslav; Konopikhin, Anatoliy; Garov, Andrey

New Phobos mapping. Methods of image processing and modern GIS technologies provide the opportunity for high quality planetary mapping. The new Phobos DTM and global orthomosaic have been used for developing a geodatabase (Karachevtseva et al., 2012) which provides data for various surface spatial analyses: statistics of crater density, as well as studies of gravity field, geomorphology, and photometry. As mapping is the best way to visualize results of research based on spatial context we created the Phobos atlas. The new Phobos atlas includes: control points network which were calculated during photogrammetry processing of SRC images (Zubarev et al., 2012) and fundamental body parameters as a reference basis for Phobos research as well as GIS analyses of surface objects and geomorphologic studies. According to the structure of the atlas we used various scales and projections based on different coordinate system, including three-axial ellipsoid which parameters (a=13.24 km, b=11.49 km, c=9.48 km) derived from new Phobos shape model (Nadezhdina and Zubarev, 2014). The new Phobos atlas includes about 30 thematic original maps that illustrate the surface of the small body based on Mars Express data (Oberst et al., 2008) and illustrates results of various studies of Phobos:, geomorphology parameters of craters (Basilevsky et al., 2014), morphometry studies (Koknanov et al., 2012), statistics of crater size-frequency distributions based on multi-fractal approach (Uchaev Dm. et al., 2012). Phobos Geo-portal. The spatial data products which used for preparing maps for the Phobos atlas are available at the planetary data storage with access via Geo-portal (http://cartsrv.mexlab.ru/geoportal/), based on modern spatial and web-based technologies (Karachevtseva et al., 2013). Now we are developing Geodesy and Cartography node which can integrate various types of information not only for Phobos data, but other planets and their satellites, and it can be used for geo-spatial support of future missions to celestial bodies. Our technological solutions are open-source, which makes it possible to increase the functionality of the system, for example, using 3D-modeling. Phobos Geo-portal provides access to results of calculation of the gravity field parameters (Uchaev Dm. et al., 2013); catalog of craters and calculations of surface roughness (Karachevtseva et al., 2012); surface compositional studies based on HRSC color-channel data (Patsyn et al., 2012). Acknowledgments: The Phobos study was supported by RBRF under grant for “Geodesy, cartography and research satellites Phobos and Deimos” (Helmholtz-Russia Joint Research Group), grant agreement No. 11-05-91323. References: Basilevsky A.T., Lorenz C.A., Shingareva T.V., Head J.W., Ramsley K.R., Zubarev A.E. Surface Geology and Geomorphology of Phobos, 2014, Elsevier, Planetary and Space Science, in press. Karachevtseva I. P., Shingareva K. B., Konopikhin A. A., Mukabenova B. V., Nadezhdina I. E., Zubarev A. E., 2012. GIS mapping of Phobos on the results of data processing of remote sensing satellite Mars Express, Modern problems of remote sensing of the Earth from Space. Space Research Institute, Moscow, 304-311 (in Russian). Karachevtseva I.P., Oberst J., Zubarev A.E., Nadezhdina I.E., Kokhanov A.A., Garov A. S. Uchaev D.V., Uchaev Dm.V., Malinnikov V.A., Klimkin N.D. 2014, The Phobos information system. Elsevier, Planetary and Space Science. http://dx.doi.org/10.1016/j.pss.2013.12.015 Kokhanov A.A., Basilevsky A.T., Karachevtseva I.P., Nadezhdina I.E., Zubarev A.E. Depth/Diameter Ratio and Inner Walls Steepness of Large Phobos Craters. The 44th Lunar and Planetary Science Conference, The Woodlands, Texas, USA, March 18-22, 2013. Abstracts [#2289]. Nadezhdina I.E., Zubarev A.E. Create reference coordinate network as a basis for studying the physical parameters of Phobos. 2014, Solar System Research, Moscow, Nauka, in press. Oberst J., Schwarz, G., Behnke, T., Hoffmann, H., Matz, K.-D., Flohrer, J., Hirsch, H., Roatsch, T., Scholten, F., Hauber, E., Brinkmann, B., Jaumann, R., Williams, D., Kirk, R., Duxbury, T., Leu, C., Neukum, G., 2008. The imaging performance of the SRC on Mars Express. Planet. Space Sci. 56, 473-491. Patsyn V.S, Malinnikov V.A., Grechishev A.V. Research of spectrometric characteristics of the surface of Phobos on the HRSC data from the Mars Express spacecraft // Modern problems of remote the earth sensing from space, Space Research Institute, Moscow, 2012, V. 9, No. 4, pp. 312-318. (in Russian). Uchaev, Dm.V., Malinnikov, V.A., Oberst, J., 2012. Multifractal approach to crater distribution modelling according to their diameters. Izv. Vyssh. Uchevn. Zaved., Geod. Aerofotos"emka 6, 3-8. (in Russian). Uchaev, Dm.V., Uchaev, D. V., Prutov, I., 2013. Multiscale representation of gravitational fields of small celestial bodies. Izv. Vyssh. Uchevn. Zaved., Geod. Aerofotos"emka 4, 3-8. (In Russian). Zubarev, A. E., Nadezhdina, I.E., Konopikhin, A. A., 2012. Problems of processing of remote sensing data for modeling shapes of small bodies in the Solar system, Modern problems of remote sensing of the Earth from Space. Space Research Institute, Moscow, 277-285 (in Russian).

Using Remote Sensing Platforms to Estimate Near-Surface Soil Properties

NASA Technical Reports Server (NTRS)

Sullivan, D. G.; Shaw, J. N.; Rickman, D.; Mask, P. L.; Wersinger, J. M.; Luvall, J.

2003-01-01

Evaluation of near-surface soil properties via remote sensing (RS) could facilitate soil survey mapping, erosion prediction, fertilization regimes, and allocation of agrochemicals. The objective of this study was to evaluate the relationship between soil spectral signature and near surface soil properties in conventionally managed row crop systems. High resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil water content, soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Surface roughness, soil water content, and crusting were also measured at sampling. Results showed RS data acquired from lands with less than 4 % surface soil water content best approximated near-surface soil properties at the Coastal Plain site where loamy sand textured surfaces were predominant. Utilizing a combination of band ratios in stepwise regression, Fed (r2 = 0.61), SOC (r2 = 0.36), sand (r2 = 0.52), and clay (r2 = 0.76) were related to RS data at the Coastal Plain site. In contrast, the more clayey Ridge and Valley soils had r-squares of 0.50, 0.36, 0.17, and 0.57. for Fed, SOC, sand and clay, respectively. Use of estimated eEmissivity did not generally improve estimates of near-surface soil attributes.

RADIAL COMPUTED TOMOGRAPHY OF AIR CONTAMINANTS USING OPTICAL REMOTE SENSING

EPA Science Inventory

The paper describes the application of an optical remote-sensing (ORS) system to map air contaminants and locate fugitive emissions. Many ORD systems may utilize radial non-overlapping beam geometry and a computed tomography (CT) algorithm to map the concentrations in a plane. In...

A data fusion framework for floodplain analysis using GIS and remotely sensed data

NASA Astrophysics Data System (ADS)

Necsoiu, Dorel Marius

Throughout history floods have been part of the human experience. They are recurring phenomena that form a necessary and enduring feature of all river basin and lowland coastal systems. In an average year, they benefit millions of people who depend on them. In the more developed countries, major floods can be the largest cause of economic losses from natural disasters, and are also a major cause of disaster-related deaths in the less developed countries. Flood disaster mitigation research was conducted to determine how remotely sensed data can effectively be used to produce accurate flood plain maps (FPMs), and to identify/quantify the sources of error associated with such data. Differences were analyzed between flood maps produced by an automated remote sensing analysis tailored to the available satellite remote sensing datasets (rFPM), the 100-year flooded areas "predicted" by the Flood Insurance Rate Maps, and FPMs based on DEM and hydrological data (aFPM). Landuse/landcover was also examined to determine its influence on rFPM errors. These errors were identified and the results were integrated in a GIS to minimize landuse/landcover effects. Two substantial flood events were analyzed. These events were selected because of their similar characteristics (i.e., the existence of FIRM or Q3 data; flood data which included flood peaks, rating curves, and flood profiles; and DEM and remote sensing imagery). Automatic feature extraction was determined to be an important component for successful flood analysis. A process network, in conjunction with domain specific information, was used to map raw remotely sensed data onto a representation that is more compatible with a GIS data model. From a practical point of view, rFPM provides a way to automatically match existing data models to the type of remote sensing data available for each event under investigation. Overall, results showed how remote sensing could contribute to the complex problem of flood management by providing an efficient way to revise the National Flood Insurance Program maps.

Development of a High Level Waste Tank Inspection System

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

Appel, D.K.; Loibl, M.W.; Meese, D.C.

1995-03-21

The Westinghouse Savannah River Technology Center was requested by it`s sister site, West Valley Nuclear Service (WVNS), to develop a remote inspection system to gather wall thickness readings of their High Level Waste Tanks. WVNS management chose to take a proactive approach to gain current information on two tanks t hat had been in service since the early 70`s. The tanks contain high level waste, are buried underground, and have only two access ports to an annular space between the tank and the secondary concrete vault. A specialized remote system was proposed to provide both a visual surveillance and ultrasonicmore » thickness measurements of the tank walls. A magnetic wheeled crawler was the basis for the remote delivery system integrated with an off-the-shelf Ultrasonic Data Acquisition System. A development program was initiated for Savannah River Technology Center (SRTC) to design, fabricate, and test a remote system based on the Crawler. The system was completed and involved three crawlers to perform the needed tasks, an Ultrasonic Crawler, a Camera Crawler, and a Surface Prep Crawler. The crawlers were computer controlled so that their operation could be done remotely and their position on the wall could be tracked. The Ultrasonic Crawler controls were interfaced with ABB Amdata`s I-PC, Ultrasonic Data Acquisition System so that thickness mapping of the wall could be obtained. A second system was requested by Westinghouse Savannah River Company (WSRC), to perform just ultrasonic mapping on their similar Waste Storage Tanks; however, the system needed to be interfaced with the P-scan Ultrasonic Data Acquisition System. Both remote inspection systems were completed 9/94. Qualifications tests were conducted by WVNS prior to implementation on the actual tank and tank development was achieved 10/94. The second inspection system was deployed at WSRC 11/94 with success, and the system is now in continuous service inspecting the remaining high level waste tanks at WSRC.« less

High Resolution Mapping of Drought Impacts on Small Waterbodies using Sentinel 1 SAR and Landsat Observations

NASA Astrophysics Data System (ADS)

Slinski, K.; Hogue, T. S.; McCray, J. E.

2017-12-01

Drought in semi-arid areas can have substantial impact on ephemeral and small water bodies, which provide critical ecological habitat and have important socio-economic value. This is particularly true in the pastoral areas of East Africa, where these ecosystems provide local communities with water for human and animal consumption and pasture for livestock. However, monitoring the impact of drought on ephemeral and small water bodies in East Africa is challenging because of sparse in situ observational systems. Satellite remote sensing observations have been shown to be a viable option for monitoring surface water change in data-poor regions. Landsat data is widely used to detect open water, but the use of Landsat data in small waterbody studies is limited by its 30-meter spatial resolution. New remote sensing-based tools are necessary to better understand the vulnerability of ephemeral and small waterbodies in semi-arid areas to drought and to monitor drought impacts. This study combines Landsat and Sentinel 1 SAR observations to create a series of monthly waterbody maps over the Awash River basin in Ethiopia depicting the change in surface water from October 2014 to March 2017. The study time period corresponds with a major drought event in the area. Waterbody maps were generated using a 10-meter resolution and utilized to monitor drought impacts on ephemeral and small waterbodies in the Awash River basin over the course of the drought event. Initial results show that surface waterbodies in the lower catchments of the Awash basin were more severely impacted by the drought event than the upper catchments. It is anticipated that the new information provided by this tool will inform decisions affecting the water, energy, agriculture and other sectors in East Africa reliant on water resources, enabling water authorities to better manage future drought events.

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.

Operational aspects of remote sensing and gis for water resources conservation and management: few examples from Haryana state, India

NASA Astrophysics Data System (ADS)

Chaudhary, B. S.

Remote Sensing as the term signifies is the technique of gathering information about an object or surface phenomenon without being in physical contact with it and essentially by using electromagnetic radiation. The principle of remote sensing is based on the solar radiation reflected or emitted from the surface of the earth. As different objects behave differently for the incoming solar radiation and have different thermal properties, the amount of solar radiation reflected, absorbed or emitted is also different. GIS is defined as an information system that is used to input, store, retrieve, manipulate, analyze and output geographically referenced data or geospatial data in order to support decision making for planning and management of natural resources. It has four essential components - hardware, software, geospatial data and the users. GIS is needed because of some inherent demerits in the manual methods. The conventional methods of surveying and mapping are time consuming, labour intensive and tedious. The techniques of Remote Sensing (RS) and GIS are effective in timely and efficient generation of database of various resources. The synoptic view and multi resolution satellite data is helpful in generating information at various scales. The mapping and monitoring of dynamic phenomenon such as floods, water logging, deforestation can be done very effectively with the aid of RS and GIS. The effective planning for water resources conservation and management at district level can be made if the data is generated on 1:50,000 scale. Hydrogeomorphological maps on 1:50,000 scale showing different ground water prospect zones have been prepared for different districts in Haryana State, India. This information has been supplemented with the available inputs from existing sources about the depth to water level and ground water quality. The other maps prepared under National (Natural) Resources Information System (NRIS) such as land use/ land cover, geomorphology, drainage/ canal network and soils etc have also been consulted for preparing water resources action plan. The maps thus prepared depict different units for further ground water prospecting. It is to mention here that some of the Palaeo-channels have been picked up first time. Various sites has been suggested for site specific water resources conservation measures such check dams/ gully plugging, earthen dams etc for recharging the ground water. The information thus developed has been submitted to PWD (Public Health) Department, Govt. of Haryana as well as other district agencies involved in the planning and management of natural resources, for further implementation of the activities suggested in different areas. During visit to different areas, it was found that the water resources action plans suggested are being implemented in the field to its maximum possibility both in the direction of fresh ground water areas exploration as well as water resources conservation. The ground water in the areas suggested is being recharged and the people are taking good crops.

Comparison of hyperspectral transformation accuracies of multispectral Landsat TM, ETM+, OLI and EO-1 ALI images for detecting minerals in a geothermal prospect area

NASA Astrophysics Data System (ADS)

Hoang, Nguyen Tien; Koike, Katsuaki

2018-03-01

Hyperspectral remote sensing generally provides more detailed spectral information and greater accuracy than multispectral remote sensing for identification of surface materials. However, there have been no hyperspectral imagers that cover the entire Earth surface. This lack points to a need for producing pseudo-hyperspectral imagery by hyperspectral transformation from multispectral images. We have recently developed such a method, a Pseudo-Hyperspectral Image Transformation Algorithm (PHITA), which transforms Landsat 7 ETM+ images into pseudo-EO-1 Hyperion images using multiple linear regression models of ETM+ and Hyperion band reflectance data. This study extends the PHITA to transform TM, OLI, and EO-1 ALI sensor images into pseudo-Hyperion images. By choosing a part of the Fish Lake Valley geothermal prospect area in the western United States for study, the pseudo-Hyperion images produced from the TM, ETM+, OLI, and ALI images by PHITA were confirmed to be applicable to mineral mapping. Using a reference map as the truth, three main minerals (muscovite and chlorite mixture, opal, and calcite) were identified with high overall accuracies from the pseudo-images (> 95% and > 42% for excluding and including unclassified pixels, respectively). The highest accuracy was obtained from the ALI image, followed by ETM+, TM, and OLI images in descending order. The TM, OLI, and ALI images can be alternatives to ETM+ imagery for the hyperspectral transformation that aids the production of pseudo-Hyperion images for areas without high-quality ETM+ images because of scan line corrector failure, and for long-term global monitoring of land surfaces.

Understanding the climate-included variations in the seasonal water demands of irrigated crops in Northern India

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Jain, M.

2016-12-01

Expected changes in temperature and precipitation patterns in the rice-wheat belt of Northern India have implications for balancing crop water demand and available water resources. Because the impacts of water scarcity and reduced crop production are realized at a local scale, water-saving interventions are most effective when implemented locally. However, a paucity of fine-scale studies on the relationship between variations in climate and crop water demand has limited our ability to effectively implement such interventions. In an effort to better understand the responses of irrigated crops to changing climate in Northern India at finer-scales, we propose a remote sensing based semi-empirical approach. First, we employ a multi-model surface energy balance (SEB) approach to map seasonal evapotranspiration (ET)/water use (1995-2015) at 30 to 100 m resolution from space and investigate how seasonal and inter-annual variations in temperature and precipitation are associated with regional surface-energy budgets. Second, using remote estimates of ET and other biophysical variables, such as vegetation indices, land surface temperature, and albedo, we will explain the possible relationships between climate change and seasonal water demands of crops. Our estimates of high/moderate resolution (30 to 100 m) seasonal ET maps can make clear distinctions between impacts of climate variations on crop water demand at field, plot, and regional scales in Northern India. Finally, by improving our ability to identify targeted area for water-saving interventions, this study supports agricultural resiliency of Northern India in the face of climate change.

Mapping the impact of river regulation on carbon dynamics using coupled field surveys and remotely-sensed optical properties

NASA Astrophysics Data System (ADS)

Kuhn, C.; Butman, D. E.

2016-12-01

Many river-reservoir networks are already managed for ecological targets such as stream temperature regulation, but less is known about how management choices alter the quantity and composition of dissolved organic carbon as well as the concentration of dissolved carbon gases. Understanding these ecological impacts is critical to informing water resources management, especially in light of the global hydropower boom and the increased interest in dam removal in the United States. Here we present results from a field survey and remote sensing imagery analysis quantifying a suite of water quality variables. With this approach, we evaluate spatial differences in carbon signals above, and below eight mainstem dams located on the Columbia and Snake Rivers. Dissolved methane and carbon dioxide concentrations were in excess of atmospheric levels with occasional carbon dioxide undersaturation being observed in the Snake River. CH4 and CO2 δ13C values shifted between the mainstem and the tributaries reflecting changes in carbon sources and processes. Satellite-retrieved estimates of CDOM and chlorophyll-a were compared to in situ measurements to enable surface mapping of concentrations at broader spatial scales. Our technical approach blends cloud-based data fusion techniques and machine learning to link ground-collected observations to remote sensing imagery in order to produce spatially-explicit, cross-scale estimates of carbon dynamics in a large, highly regulated river system. These findings test the feasibility of coupling remote sensing with field-based measurements to observe the complex impacts of run-of-the river impoundments to aquatic carbon cycling.

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object-oriented segmentation data, and finally get the rice extent map. At last, by using the time series analysis, the peak count was obtained for each rice area to ensure the crop intensity. In this work, the rice ground point from a GVG crowdsourcing smartphone and rice area statistical results from National Bureau of Statistics were used to validate and evaluate our result.

Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

PubMed

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes

PubMed Central

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J.; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales. PMID:24069206

Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Rosen, Paul A.

2012-01-01

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

NASA Technical Reports Server (NTRS)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Satellite remote sensing of isolated wetlands using object-oriented classification of LANDSAT-7 data

EPA Science Inventory

There has been an increasing interest in characterizing and mapping isolated depressional wetlands due to a 2001 U.S. Supreme Court decision that effectively removed their protected status. Our objective was to determine the utility of satellite remote sensing to accurately map ...

Remote sensing. [land use mapping

NASA Technical Reports Server (NTRS)

Jinich, A.

1979-01-01

Various imaging techniques are outlined for use in mapping, land use, and land management in Mexico. Among the techniques discussed are pattern recognition and photographic processing. The utilization of information from remote sensing devices on satellites are studied. Multispectral band scanners are examined and software, hardware, and other program requirements are surveyed.

Monitoring monthly surface water dynamics of Dongting Lake using Sentinel-1 data at 10 m.

PubMed

Xing, Liwei; Tang, Xinming; Wang, Huabin; Fan, Wenfeng; Wang, Guanghui

2018-01-01

High temporal resolution water distribution maps are essential for surface water monitoring because surface water exhibits significant inner-annual variation. Therefore, high-frequency remote sensing data are needed for surface water mapping. Dongting Lake, the second-largest freshwater lake in China, is famous for the seasonal fluctuations of its inundation extents in the middle reaches of the Yangtze River. It is also greatly affected by the Three Gorges Project. In this study, we used Sentinel-1 data to generate surface water maps of Dongting Lake at 10 m resolution. First, we generated the Sentinel-1 time series backscattering coefficient for VH and VV polarizations at 10 m resolution by using a monthly composition method. Second, we generated the thresholds for mapping surface water at 10 m resolution with monthly frequencies using Sentinel-1 data. Then, we derived the monthly surface water distribution product of Dongting Lake in 2016, and finally, we analyzed the inner-annual surface water dynamics. The results showed that: (1) The thresholds were -21.56 and -15.82 dB for the backscattering coefficients for VH and VV, respectively, and the overall accuracy and Kappa coefficients were above 95.50% and 0.90, respectively, for the VH backscattering coefficient, and above 94.50% and 0.88, respectively, for the VV backscattering coefficient. The VV backscattering coefficient achieved lower accuracy due to the effect of the wind causing roughness on the surface of the water. (2) The maximum and minimum areas of surface water were 2040.33 km 2 in July, and 738.89 km 2 in December. The surface water area of Dongting Lake varied most significantly in April and August. The permanent water acreage in 2016 was 556.35 km 2 , accounting for 19.65% of the total area of Dongting Lake, and the acreage of seasonal water was 1525.21 km 2 . This study proposed a method to automatically generate monthly surface water at 10 m resolution, which may contribute to monitoring surface water in a timely manner.

Effective water surface mapping in macrophyte-covered reservoirs in NE Brazil based on TerraSAR-X time series

NASA Astrophysics Data System (ADS)

Zhang, Shuping; Foerster, Saskia; Medeiros, Pedro; de Araújo, José Carlos; Waske, Bjoern

2018-07-01

Water supplies in northeastern Brazil strongly depend on the numerous surface water reservoirs of various sizes there. However, the seasonal and long-term water surface dynamics of these reservoirs, particularly the large number of small ones, remain inadequately known. Remote sensing techniques have shown great potentials in water bodies mapping. Yet, the widespread presence of macrophytes in most of the reservoirs often impedes the delineation of the effective water surfaces. Knowledge of the dynamics of the effective water surfaces in the reservoirs is essential for understanding, managing, and modelling the local and regional water resources. In this study, a two-year time series of TerraSAR-X (TSX) satellite data was used to monitor the effective water surface areas in nine reservoirs in NE Brazil. Calm open water surfaces were obtained by segmenting the backscattering coefficients of TSX images with minimum error thresholding. Linear unmixing was implemented on the distributions of gray-level co-occurrence matrix (GLCM) variance in the reservoirs to quantify the proportions of sub-populations dominated by different types of scattering along the TSX time series. By referring to the statistics and the seasonal proportions of the GLCM variance sub-populations the GLCM variance was segmented to map the vegetated water surfaces. The effective water surface areas that include the vegetation-covered waters as well as calm open water in the reservoirs were mapped with accuracies >77%. The temporal and spatial change patterns of water surfaces in the nine reservoirs over a period of two consecutive dry and wet seasons were derived. Precipitation-related soil moisture changes, topography and the dense macrophyte canopies are the main sources of errors in the such-derived effective water surfaces. Independent from in-situ data, the approach employed in this study shows great potential in monitoring water surfaces of different complexity and macrophyte coverage. The effective water surface areas obtained for the reservoirs can provide valuable input for efficient water management and improve the hydrological modelling in this region.

Surface mapping via unsupervised classification of remote sensing: application to MESSENGER/MASCS and DAWN/VIRS data.

NASA Astrophysics Data System (ADS)

D'Amore, M.; Le Scaon, R.; Helbert, J.; Maturilli, A.

2017-12-01

Machine-learning achieved unprecedented results in high-dimensional data processing tasks with wide applications in various fields. Due to the growing number of complex nonlinear systems that have to be investigated in science and the bare raw size of data nowadays available, ML offers the unique ability to extract knowledge, regardless the specific application field. Examples are image segmentation, supervised/unsupervised/ semi-supervised classification, feature extraction, data dimensionality analysis/reduction.The MASCS instrument has mapped Mercury surface in the 400-1145 nm wavelength range during orbital observations by the MESSENGER spacecraft. We have conducted k-means unsupervised hierarchical clustering to identify and characterize spectral units from MASCS observations. The results display a dichotomy: a polar and equatorial units, possibly linked to compositional differences or weathering due to irradiation. To explore possible relations between composition and spectral behavior, we have compared the spectral provinces with elemental abundance maps derived from MESSENGER's X-Ray Spectrometer (XRS).For the Vesta application on DAWN Visible and infrared spectrometer (VIR) data, we explored several Machine Learning techniques: image segmentation method, stream algorithm and hierarchical clustering.The algorithm successfully separates the Olivine outcrops around two craters on Vesta's surface [1]. New maps summarizing the spectral and chemical signature of the surface could be automatically produced.We conclude that instead of hand digging in data, scientist could choose a subset of algorithms with well known feature (i.e. efficacy on the particular problem, speed, accuracy) and focus their effort in understanding what important characteristic of the groups found in the data mean. [1] E Ammannito et al. "Olivine in an unexpected location on Vesta's surface". In: Nature 504.7478 (2013), pp. 122-125.

Tactile Robotic Topographical Mapping Without Force or Contact Sensors

NASA Technical Reports Server (NTRS)

Burke, Kevin; Melko, Joseph; Krajewski, Joel; Cady, Ian

2008-01-01

A method of topographical mapping of a local solid surface within the range of motion of a robot arm is based on detection of contact between the surface and the end effector (the fixture or tool at the tip of the robot arm). The method was conceived to enable mapping of local terrain by an exploratory robot on a remote planet, without need to incorporate delicate contact switches, force sensors, a vision system, or other additional, costly hardware. The method could also be used on Earth for determining the size and shape of an unknown surface in the vicinity of a robot, perhaps in an unanticipated situation in which other means of mapping (e.g., stereoscopic imaging or laser scanning with triangulation) are not available. The method uses control software modified to utilize the inherent capability of the robotic control system to measure the joint positions, the rates of change of the joint positions, and the electrical current demanded by the robotic arm joint actuators. The system utilizes these coordinate data and the known robot-arm kinematics to compute the position and velocity of the end effector, move the end effector along a specified trajectory, place the end effector at a specified location, and measure the electrical currents in the joint actuators. Since the joint actuator current is approximately proportional to the actuator forces and torques, a sudden rise in joint current, combined with a slowing of the joint, is a possible indication of actuator stall and surface contact. Hence, even though the robotic arm is not equipped with contact sensors, it is possible to sense contact (albeit with reduced sensitivity) as the end effector becomes stalled against a surface that one seeks to measure.

Special Software for Planetary Image Processing and Research

NASA Astrophysics Data System (ADS)

Zubarev, A. E.; Nadezhdina, I. E.; Kozlova, N. A.; Brusnikin, E. S.; Karachevtseva, I. P.

2016-06-01

The special modules of photogrammetric processing of remote sensing data that provide the opportunity to effectively organize and optimize the planetary studies were developed. As basic application the commercial software package PHOTOMOD™ is used. Special modules were created to perform various types of data processing: calculation of preliminary navigation parameters, calculation of shape parameters of celestial body, global view image orthorectification, estimation of Sun illumination and Earth visibilities from planetary surface. For photogrammetric processing the different types of data have been used, including images of the Moon, Mars, Mercury, Phobos, Galilean satellites and Enceladus obtained by frame or push-broom cameras. We used modern planetary data and images that were taken over the years, shooting from orbit flight path with various illumination and resolution as well as obtained by planetary rovers from surface. Planetary data image processing is a complex task, and as usual it can take from few months to years. We present our efficient pipeline procedure that provides the possibilities to obtain different data products and supports a long way from planetary images to celestial body maps. The obtained data - new three-dimensional control point networks, elevation models, orthomosaics - provided accurate maps production: a new Phobos atlas (Karachevtseva et al., 2015) and various thematic maps that derived from studies of planetary surface (Karachevtseva et al., 2016a).

Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Roberts, Dar A.; Smith, Milton O.; Adams, John B.

1992-01-01

The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared.

Discrimination of common Mediterranean plant species using field spectroradiometry

NASA Astrophysics Data System (ADS)

Manevski, Kiril; Manakos, Ioannis; Petropoulos, George P.; Kalaitzidis, Chariton

2011-12-01

Field spectroradiometry of land surface objects supports remote sensing analysis, facilitates the discrimination of vegetation species, and enhances the mapping efficiency. Especially in the Mediterranean, spectral discrimination of common vegetation types, such as phrygana and maquis species, remains a challenge. Both phrygana and maquis may be used as a direct indicator for grazing management, fire history and severity, and the state of the wider ecosystem equilibrium. This study aims to investigate the capability of field spectroradiometry supporting remote sensing analysis of the land cover of a characteristic Mediterranean area. Five common Mediterranean maquis and phrygana species were examined. Spectra acquisition was performed during an intensive field campaign deployed in spring 2010, supported by a novel platform MUFSPEM@MED (Mobile Unit for Field SPEctral Measurements at the MEDiterranean) for high canopy measurements. Parametric and non-parametric statistical tests have been applied to the continuum-removed reflectance of the species in the visible to shortwave infrared spectral range. Interpretation of the results indicated distinct discrimination between the studied species at specific spectral regions. Statistically significant wavelengths were principally found in both the visible and the near infrared regions of the electromagnetic spectrum. Spectral bands in the shortwave infrared demonstrated significant discrimination features for the examined species adapted to Mediterranean drought. All in all, results confirmed the prospect for a more accurate mapping of the species spatial distribution using remote sensing imagery coupled with in situ spectral information.

Spatial Observation and Models for Crop Water Use in Australia (Invited)

NASA Astrophysics Data System (ADS)

Hafeez, M. M.; Chemin, Y.; Rabbani, U.

2009-12-01

Recent drought in Australia and concerns about climate change have highlighted the need to manage agricultural water resources more sustainably, especially in the Murray Darling Basin which accounts for more than 70% of water for crop production. For Australian continent, approximately 90% of the precipitation that falls on the land is returned back to the atmosphere through actual evapotranspiration (ET) process. However, despite its significance nationally, it is almost impossible to measure or observe it directly at a meaningful scale in space and time through traditional point-based methods. Since late 1990's, the optical-thermal remote sensing satellite data has been extensively used for mapping of actual ET from farm to catchment scales in Australia. Numerous ET algorithms have been developed to make use of remote sensing data acquired by optical-thermal sensors mounted on airborne and satellite platforms. This article concentrates on the Murrumbidgee catchment, where ground truth data has been collected on a fortnightly basis since 2007 using two Eddy Covariance Systems (ECS) and two Large Aperture Scintillometers (LAS). Their setup absorbed variability in the landscape to measure ET-related fluxes. The ground truthing measurement data includes leaf area index (LAI) from LICOR 2000, soil heat fluxes from HuskeFlux, crop reflectance data from CROPScan and from a thermal radiometer. UAV drone equipped with multispectral scanner and thermal imager was used to get very high spatial resolution NDVI and surface temperature maps over the selected farms. This large array of high technology instruments have been used to collect specific measurements within various micro-ecosystems available in our study area. This article starts by an overview of common ET estimation algorithms based on satellite remote sensing data. The algorithms are SEBAL, METRIC, Simplified Surface Energy Balance, Two Source Energy Balance and SEBS. They are used in Australia at both regional and catchment scale for mapping actual ET using imagery from Landsat 5TM/7ETM+ and Terra-MODIS sensors. Results of ET derived from various remote sensing algorithms are matched well against the ECS and LAS data sets. These high-tech observation system are used to collect specific ground truth data to develop new empirical and semi-empirical relationship for creating a Spatial Algorithm for Mapping ET (SAM-ET) dedicated to Australian agro-ecosystems. Such estimates can underpin crop water use, crop water productivity, food security, carbon sequestration and environmental flow requirements to enhance the sustainability of agricultural systems. The next frontier is to integrate these data and models to deliver a decision support system to irrigation managers for coordinating water supply and demand, to help match crop water requirement closely in near real time environment.

Application of remote sensor data to geologic analysis of the Bonanza Test Site Colorado

NASA Technical Reports Server (NTRS)

Lee, K. (Compiler)

1973-01-01

A geologic map of the Bonanza Test Site is nearing completion. Using published large scale geologic maps from various sources, the geology of the area is being compiled on a base scaled at 1:250,000. Sources of previously published geologic mapping include: (1) USGS Bulletins; (2) professional papers and geologic quadrangle maps; (3) Bureau of Mines reports; (4) Colorado School of Mines quarterlies; and (5) Rocky Mountain Association of Geologist Guidebooks. This compilation will be used to evaluate ERTS, Skylab, and remote sensing underflight data.

Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

2009-01-01

The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Towards improved characterization of northern wetlands (or other landscapes) by remote sensing - a rapid approach to collect ground truth data

NASA Astrophysics Data System (ADS)

Gålfalk, Magnus; Karlson, Martin; Crill, Patrick; Bastviken, David

2017-04-01

The calibration and validation of remote sensing land cover products is highly dependent on accurate ground truth data, which are costly and practically challenging to collect. This study evaluates a novel and efficient alternative to field surveys and UAV imaging commonly applied for this task. The method consists of i) a light weight, water proof, remote controlled RGB-camera mounted on an extendable monopod used for acquiring wide-field images of the ground from a height of 4.5 meters, and ii) a script for semi-automatic image classification. In the post-processing, the wide-field images are corrected for optical distortion and geometrically rectified so that the spatial resolution is the same over the surface area used for classification. The script distinguishes land surface components by color, brightness and spatial variability. The method was evaluated in wetland areas located around Abisko, northern Sweden. Proportional estimates of the six main surface components in the wetlands (wet and dry Sphagnum, shrub, grass, water, rock) were derived for 200 images, equivalent to 10 × 10 m field plots. These photo plots were then used as calibration data for a regional scale satellite based classification which separates the six wetland surface components using a Sentinel-1 time series. The method presented in this study is accurate, rapid, robust and cost efficient in comparison to field surveys (time consuming) and drone mapping (which require low wind speeds and no rain, suffer from battery limited flight times, have potential GPS/compass errors far north, and in some areas are prohibited by law).

Utilizing GNSS Reflectometry to Assess Surface Inundation Dynamics in Tropical Wetlands

NASA Astrophysics Data System (ADS)

Jensen, K.; McDonald, K. C.; Podest, E.; Chew, C. C.

2017-12-01

Tropical wetlands play a significant role in global atmospheric methane and terrestrial water storage. Despite the growing number of remote sensing products from satellite sensors, both spatial distribution and temporal variability of wetlands remain highly uncertain. An emerging innovative approach to mapping wetlands is offered by GNSS reflectometry (GNSS-R), a bistatic radar concept that takes advantage of GNSS transmitting satellites to yield observations with global coverage and rapid revisit time. This technology offers the potential to capture dynamic inundation changes in wetlands at higher temporal fidelity and sensitivity under the canopy than presently possible. We present an integrative analysis of radiometric modeling, ground measurements, and several microwave remote sensing datasets traditionally used for wetland observations. From a theoretical standpoint, GNSS-R sensitivities for vegetation and wetlands are investigated with a bistatic radar model in order to understand the interactions of the signal with various land surface components. GNSS reflections from the TechDemoSat-1 (TDS-1), Soil Moisture Active Passive (SMAP), and Cyclone GNSS (CYGNSS) missions are tested experimentally with contemporaneous (1) field measurements collected from the Pacaya Samiria National Reserve in the Peruvian Amazon, (2) imaging radar from Sentinel-1 and PALSAR-2 observed over a variety of tropical wetland systems, and (3) pan-tropical coarse-resolution (25km) microwave datasets (Surface Water Microwave Product Series). We find that GNSS-R data provide the potential to extend capabilities of current remote sensing techniques to characterize surface inundation extent, and we explore how to maximize synergism between different satellite sensors to produce an enhanced wetland monitoring product.

An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2006-01-01

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

Shifting Environmental Ranges and Biome Potential According to the Whittaker Relationship

NASA Astrophysics Data System (ADS)

de Jong, R.; Garonna, I.; Schaepman, M. E.

2015-12-01

Robert H. Whittaker classified biome types mainly as a function of Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP), resulting in the well-known Whittaker plot1. This relationship is still being used to map biomes globally2. The same inputs (MAT and MAP), augmented with a radiation proxy, are used in the resource-balance perspective for modeling large-scale vegetation productivity as a function of abiotic factors3. These two approaches, used in a temporally dynamic manner, provided us indicators of shifts in growth-limiting factors4 and associated environmental ranges of vegetation, which, in turn, are key indicators for the study of global change and biodiversity5. We present a study in which we used the Whittaker relationship and CRU TS 3.22 climatic data to map regions that showed variable biome potential. These regions are likely to indicate ecotones - i.e. interactions zones between biomes - that have been subject to abiotic change and where a change in the vegetation system can be anticipated. At the same time, we used remotely sensed data (GIMMS v3g 1982-2012) to study gradients in vegetation dynamics in these zones. Preliminary results show strongest environmental shifts in northern ecotones, e.g. on the tundra - boreal boundary, and associated changes in climatic growth-limiting factors4. [1] Whittaker RH (1975) Communities and Ecosystems, Macmillan, 385p.[2] Ricklefs RE (2008) The Economy of Nature, W. H. Freeman, 620p.[3] Field CB, Randerson JT, Malmström CM (1995) Global net primary production: Combining ecology and remote sensing. Remote Sensing of Environment, 51, 74-88.[4] Schenkel D, Garonna I, De Jong R, Schaepman ME (this conference) Linking Land Surface Phenology and Growth Limiting Factor Shifts over the Past 30 Years.[5] University of Zurich Research Priority Program on Global Change and Biodiversity, http://www.gcb.uzh.ch

The application of remote sensing techniques to the study of ophiolites

NASA Astrophysics Data System (ADS)

Khan, Shuhab D.; Mahmood, Khalid

2008-08-01

Satellite remote sensing methods are a powerful tool for detailed geologic analysis, especially in inaccessible regions of the earth's surface. Short-wave infrared (SWIR) bands are shown to provide spectral information bearing on the lithologic, structural, and geochemical character of rock bodies such as ophiolites, allowing for a more comprehensive assessment of the lithologies present, their stratigraphic relationships, and geochemical character. Most remote sensing data are widely available for little or no cost, along with user-friendly software for non-specialists. In this paper we review common remote sensing systems and methods that allow for the discrimination of solid rock (lithologic) components of ophiolite complexes and their structural relationships. Ophiolites are enigmatic rock bodies which associated with most, if not all, plate collision sutures. Ophiolites are ideal for remote sensing given their widely recognized diversity of lithologic types and structural relationships. Accordingly, as a basis for demonstrating the utility of remote sensing techniques, we briefly review typical ophiolites in the Tethyan tectonic belt. As a case study, we apply integrated remote sensing studies of a well-studied example, the Muslim Bagh ophiolite, located in Balochistan, western Pakistan. On this basis, we attempt to demonstrate how remote sensing data can validate and reconcile existing information obtained from field studies. The lithologic and geochemical diversity of Muslim Bagh are representative of Tethyan ophiolites. Despite it's remote location it has been extensively mapped and characterized by structural and geochemical studies, and is virtually free of vegetative cover. Moreover, integrating the remote sensing data with 'ground truth' information thus offers the potential of an improved template for interpreting remote sensing data sets of other ophiolites for which little or no field information is available.

Singularity Analysis: a powerful image processing tool in remote sensing of the oceans

NASA Astrophysics Data System (ADS)

Turiel, A.; Umbert, M.; Hoareau, N.; Ballabrera-Poy, J.; Portabella, M.

2012-04-01

The study of fully developed turbulence has given rise to the development of new methods to describe real data of scalars submitted to the action of a turbulent flow. The application of this brand of methodologies (known as Microcanonical Multifractal Formalism, MMF) on remote sensing ocean maps open new ways to exploit those data for oceanographic purposes. The main technique in MMF is that of Singularity Analysis (SA). By means of SA a singularity exponents is assigned to each point of a given image. The singularity exponent of a given point is a dimensionless measure of the regularity or irregularity of the scalar at that point. Singularity exponents arrange in singularity lines, which accurately track the flow streamlines from any scalar, as we have verified with remote sensing and simulated data. Applications of SA include quality assessment of different products, the estimation of surface velocities, the development of fusion techniques for different types of scalars, comparison with measures of ocean mixing, and improvement in assimilation schemes.

The Use of a Geographic Information System and Remote Sensing Technology for Monitoring Land Use and Soil Carbon Change in the Subtropical Dry Forest Life Zone of Puerto Rico

NASA Technical Reports Server (NTRS)

Velez-Rodriguez, Linda L. (Principal Investigator)

1996-01-01

Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.

Determination of Winter Wheat Phenology in Bavaria- A Contribution to Regional Crop Health Monitoring from Space

NASA Astrophysics Data System (ADS)

Bruggemann, Lena; Bach, Heike; Ruf, Tobias; Appel, Florian; Migdall, Silke; Hank, Tobias; Mauser, Wolfram; Eiblmeier, Peter

2016-08-01

The central topic of this study is the monitoring of winter wheat phenology and the detection of anthesis (flowering) using remotely sensed data as well as crop growth modeling. It is not possible to directly observe the flowering of wheat with optical satellite sensors. Thus, an approach that combines crop growth modeling with remote sensing data covering optical and microwave spectral ranges was developed. This was done in three steps: The hydro-agroecological land surface model PROMET was first run in a stand-alone version for selected sites distributed throughout Bavaria using only static input parameters (e.g. soil map) and current meteorological data as driving factors. Thus, multitemporal information from optical remote sensing data was assimilated into the model runs in a second step to improve the accuracy of the results. Finally, the use of radar data for anthesis detection in winter wheat was tested using Sentinel-1 data of 2015 in dual polarization mode (VV+VH).

Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0-14.0 μm)

USGS Publications Warehouse

Ribeiro da Luz, Beatriz; Crowley, James K.

2007-01-01

In contrast to visible and short-wave infrared data, thermal infrared spectra of broad leaf plants show considerable spectral diversity, suggesting that such data eventually could be utilized to map vegetation composition. However, remotely measuring the subtle emissivity features of leaves still presents major challenges. To be successful, sensors operating in the 8–14 μm atmospheric window must have high signal-to-noise and a small enough instantaneous field of view to allow measurements of only a few leaf surfaces. Methods for atmospheric compensation, temperature–emissivity separation, and spectral feature analysis also will need to be refined to allow the recognition, and perhaps, exploitation of leaf thermal infrared spectral properties.

Sub-parcel terroir mapping supported by UAV-based hyperspectral imagery

NASA Astrophysics Data System (ADS)

Takács, Katalin; Árvai, Mátyás; Koós, Sándor; Deák, Márton; Bakacsi, Zsófia; László, Péter; Pásztor, László

2017-04-01

There is a greater need to better understand the regional-to-parcel variations in viticultural potential. The differentiation and mapping of the variability of grape and wine quality require comprehensive spatial modelling of climatic, topographic and soil properties and a "terroir-based approach". Using remote and proximal sensing sensors and instruments are the most effective way for surveying vineyard status, such as geomorphologic and soil conditions, plant water and nutrient availability, plant health. UAV (Unmanned Aerial Vechicle) platforms are ideal for the remote monitoring of small and medium size vineyards, because flight planning is flexible and very high spatial ground resolution (even centimeters) can be achieved. Using hyperspectral remote sensing techniques the spectral response of the vegetation and the bare soil surface can be analyzed in very high spectral resolution, which can support terroir mapping on a sub-parcel level. Our study area is located in Hungary, in the Tokaj Wine Region, which is a historical region for botrityzed dessert wine making. The area of Tokaj Wine Region was formed mostly by Miocene volcanic activity, where andesite, rhyolite lavas and tuffs are characteristic and loess cover also occurs in some regions. The various geology and morphology of this area result diversity in soil types and soil properties as well. The study site was surveyed by a Cubert UHD-185 hyperspectral camera set on a Cortex Octocopter platform. The hyperspectral images were acquired in VIS-NIR (visible and near-infrared; 450-950 nm), with 4 nm sampling interval. The image acquisition was carried out at bare soil conditions, therefore the most important soil properties, which has dominant role by the delineation of terroir, can be predicted. In our paper we will present the first results of the hyperspectral survey.

Euro-Maps 3D- A Transnational, High-Resolution Digital Surface Model For Europe

NASA Astrophysics Data System (ADS)

Uttenthaler, A.; Barner, F.; Hass, T.; Makiola, J.; d'Angelo, P.; Reinartz, P.; Carl, S.; Steiner, K.

2013-12-01

Euro-Maps 3D is a homogeneous 5 m spaced digital surface model (DSM) semi-automatically derived by Euromap from 2.5 m in-flight stereo data provided by the Indian IRS-P5 Cartosat-1 satellite. This new and innovative product has been developed in close co- operation with the Remote Sensing Technology Institute (IMF) of the German Aerospace Center (DLR) and is being jointly exploited. The very detailed and accurate representation of the surface is achieved by using a sophisticated and well adapted algorithm implemented on the basis of the Semi-Global Matching approach. In addition, the final product includes detailed flanking information consisting of several pixel-based quality and traceability layers also including an ortho layer. The product is believed to provide maximum accuracy and transparency. The DSM product meets and exceeds HRE80 qualification standards. The DSM product will be made available transnational in a homogeneous quality for most parts of Europe, North Africa and Turkey by Euromap step-by-step. Other areas around the world are processed on demand.

ROLES OF REMOTE SENSING AND CARTOGRAPHY IN THE USGS NATIONAL MAPPING DIVISION.

USGS Publications Warehouse

Southard, Rupert B.; Salisbury, John W.

1983-01-01

The inseparable roles of remote sensing and photogrammetry have been recognized to be consistent with the aims and interests of the American Society of Photogrammetry. In particular, spatial data storage, data merging and manipulation methods and other techniques originally developed for remote sensing applications also have applications for digital cartography. Also, with the introduction of much improved digital processing techniques, even relatively low resolution (80 m) traditional Landsat images can now be digitally mosaicked into excellent quality 1:250,000-scale image maps.

1994 ASPRS/ACSM annual convention exposition. Volume 2

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

Not Available

1994-01-01

This report is Volume II of presented papers at the joint 1994 convention of the American Society for Photgrammetry and Remote Sensing and American Congress on Surveying and Mapping. Topic areas covered include the following: Data Base/GPS Issues; Survey Management Issues; Surveying computations; Surveying education; Digital mapping; global change, EOS and NALC issues; GPS issues; Battelle Research in Remote Sensing and in GIS; Advanced Image Processing;GIS Issues; Surveying and Geodesy Issues; water resource issues; Advanced applications of remote sensing; Landsat Pathfinder I.

War Damage Assessment

NASA Technical Reports Server (NTRS)

1994-01-01

During and after the Persian Gulf war, hundreds of "oil lakes" were created in Kuwait by oil released from damaged wells. The lakes are a hazard to the Kuwait atmosphere, soil and ground water and must be carefully monitored. Boston University Center for Remote Sensing, assisted by other organizations, has accurately mapped the lakes using Landsat and Spot imagery. The war damage included the formation of over 300 oil lakes, oil pollution and sand dune movement. Total damage area is over 5,400 square kilometers - 30 percent of Kuwait's total surface area.

Remote sensing of forest insect disturbances: Current state and future directions

NASA Astrophysics Data System (ADS)

Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

2017-08-01

Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

Remote sensing of forest insect disturbances: Current state and future directions.

PubMed

Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

2017-08-01

Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

Global Operational Remotely Sensed Evapotranspiration System for Water Resources Management: Case Study for the State of New Mexico

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Magnuson, M.; John, L.

2017-12-01

An operational system to produce and disseminate remotely sensed evapotranspiration using the PT-JPL model and support its analysis and use in water resources decision making is being integrated into the New Mexico state government. A partnership between the NASA Western Water Applications Office (WWAO), the Jet Propulsion Laboratory (JPL), and the New Mexico Office of the State Engineer (NMOSE) has enabled collaboration with a variety of state agencies to inform decision making processes for agriculture, rangeland, and forest management. This system improves drought understanding and mobilization, litigation support, and economic, municipal, and ground-water planning through interactive mapping of daily rates of evapotranspiration at 1 km spatial resolution with near real-time latency. This is facilitated by daily remote sensing acquisitions of land-surface temperature and near-surface air temperature and humidity from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite as well as the short-term composites of Normalized Difference Vegetation Index (NDVI) and albedo provided by MODIS. Incorporating evapotranspiration data into agricultural water management better characterizes imbalances between water requirements and supplies. Monitoring evapotranspiration over rangeland areas improves remediation and prevention of aridification. Monitoring forest evapotranspiration improves wildlife management and response to wildfire risk. Continued implementation of this decision support system should enhance water and food security.

Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data

USGS Publications Warehouse

Kolden, Crystal A.; Rogan, John

2013-01-01

Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.

An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks

PubMed Central

Zhang, Jialin; Li, Xiuhong; Yang, Rongjin; Liu, Qiang; Zhao, Long; Dou, Baocheng

2017-01-01

In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory results because of the heterogeneity of soil moisture and its low correlation with the auxiliary variables. This study developed an Extended Kriging method to interpolate with the aid of remote sensing images. The underlying idea is to extend the traditional Kriging by introducing spectral variables, and operating on spatial and spectral combined space. The algorithm has been applied to WSN-measured soil moisture data in HiWATER campaign to generate daily maps from 10 June to 15 July 2012. For comparison, three traditional Kriging methods are applied: Ordinary Kriging (OK), which used WSN data only, Co-kriging and KED, both of which integrated remote sensing data as covariate. Visual inspections indicate that the result from Extended Kriging shows more spatial details than that of OK, Co-kriging, and KED. The Root Mean Square Error (RMSE) of Extended Kriging was found to be the smallest among the four interpolation results. This indicates that the proposed method has advantages in combining remote sensing information and ground measurements in soil moisture interpolation. PMID:28617351

Remote sensing for detecting and mapping whitefly (Bemisia tabaci) infestations

USDA-ARS?s Scientific Manuscript database

Remote sensing technology has long been used for detecting insect infestations on agricultural crops. With recent advances in remote sensing sensors and other spatial information technologies such as Global Position Systems (GPS) and Geographic Information Systems (GIS), remote sensing is finding mo...

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Commerical Remote Sensing Data Contract

USGS Publications Warehouse

,

2005-01-01

The U. S. Geological Survey's (USGS) Commercial Remote Sensing Data Contracts (CRSDCs) provide government agencies with access to a broad range of commercially available remotely sensed airborne and satellite data. These contracts were established to support The National Map partners, other Federal Civilian agency programs, and Department of Defense programs that require data for the United States and its territories. Experience shows that centralized procurement of remotely sensed data leads to considerable cost savings to the Federal government through volume discounts, reduction of redundant contract administrative costs, and avoidance of duplicate purchases. These contracts directly support the President's Commercial Remote Sensing Space Policy, signed in 2003, by providing a centralized mechanism for civil agencies to acquire commercial remote sensing products to support their mission needs in an efficient and coordinated way. CRSDC administration is provided by the USGS Mid-Continent Mapping Center in Rolla, Missouri.

Comparison of Image Restoration Methods for Lunar Epithermal Neutron Emission Mapping

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Ivatury, V.; Milikh, G.; Nandikotkur, G.; Puetter, R. C.; Sagdeev, R. Z.; Usikov, D.; Mitrofanov, I. G.

2009-01-01

Orbital measurements of neutrons by the Lunar Exploring Neutron Detector (LEND) onboard the Lunar Reconnaissance Orbiter are being used to quantify the spatial distribution of near surface hydrogen (H). Inferred H concentration maps have low signal-to-noise (SN) and image restoration (IR) techniques are being studied to enhance results. A single-blind. two-phase study is described in which four teams of researchers independently developed image restoration techniques optimized for LEND data. Synthetic lunar epithermal neutron emission maps were derived from LEND simulations. These data were used as ground truth to determine the relative quantitative performance of the IR methods vs. a default denoising (smoothing) technique. We review and used factors influencing orbital remote sensing of neutrons emitted from the lunar surface to develop a database of synthetic "true" maps for performance evaluation. A prior independent training phase was implemented for each technique to assure methods were optimized before the blind trial. Method performance was determined using several regional root-mean-square error metrics specific to epithermal signals of interest. Results indicate unbiased IR methods realize only small signal gains in most of the tested metrics. This suggests other physically based modeling assumptions are required to produce appreciable signal gains in similar low SN IR applications.

Airborne Remote Observations of L-Band Radio Frequency Interference and Implications for Satellite Missions

NASA Technical Reports Server (NTRS)

Laymon, Charles; Srinivasan, Karthik; Limaye, Ashutosh

2011-01-01

Passive remote sensing of the Earth s surface and atmosphere from space has significant importance in operational and research environmental studies, in particular for the scientific understanding, monitoring and prediction of climate change and its impacts. Passive remote sensing requires the measurement of naturally occurring radiations, usually of very low power levels, which contain essential information on the physical process under investigation. As such, these sensed radio frequency bands are a unique natural resource enabling space borne passive sensing of the atmosphere and the Earth s surface that deserves adequate allocation to the Earth Exploration Satellite Service and absolute protection from interference. Unfortunately, radio frequency interference (RFI) is an increasing problem for Earth remote sensing, particularly for passive observations of natural emissions. Because these natural signals tend to be very weak, even low levels of interference received by a passive sensor may degrade the fidelity of scientific data. The characteristics of RFI (low-level interference and radar-pulse noise) are not well known because there has been no systematic surveillance, spectrum inventory or mapping of RFI. While conducting a flight experiment over central Tennessee in May 2010, RFI, a concern for any instrument operating in the passive L band frequency, was observed across 16 subbands between 1402-1427 MHz. Such a survey provides rare characterization data from which to further develop mitigation technologies as well as to identify bandwidths to avoid in future sensor formulation.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

American Society for Photogrammetry and Remote Sensing and ACSM, Fall Convention, Reno, NV, Oct. 4-9, 1987, ASPRS Technical Papers

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

Not Available

1987-01-01

Recent advances in remote-sensing technology and applications are examined in reviews and reports. Topics addressed include the use of Landsat TM data to assess suspended-sediment dispersion in a coastal lagoon, the use of sun incidence angle and IR reflectance levels in mapping old-growth coniferous forests, information-management systems, Large-Format-Camera soil mapping, and the economic potential of Landsat TM winter-wheat crop-condition assessment. Consideration is given to measurement of ephemeral gully erosion by airborne laser ranging, the creation of a multipurpose cadaster, high-resolution remote sensing and the news media, the role of vegetation in the global carbon cycle, PC applications in analytical photogrammetry,more » multispectral geological remote sensing of a suspected impact crater, fractional calculus in digital terrain modeling, and automated mapping using GP-based survey data.« less

Application of remote sensing to monitoring and studying dispersion in ocean dumping

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Ohlhorst, C. W.

1981-01-01

Remotely sensed wide area synoptic data provides information on ocean dumping that is not readily available by other means. A qualitative approach has been used to map features, such as river plumes. Results of quantitative analyses have been used to develop maps showing quantitative distributions of one or more water quality parameters, such as suspended solids or chlorophyll a. Joint NASA/NOAA experiments have been conducted at designated dump areas in the U.S. coastal zones to determine the applicability of aircraft remote sensing systems to map plumes resulting from ocean dumping of sewage sludge and industrial wastes. A second objective is related to the evaluation of previously developed quantitative analysis techniques for studying dispersion of materials in these plumes. It was found that plumes resulting from dumping of four waste materials have distinctive spectral characteristics. The development of a technology for use in a routine monitoring system, based on remote sensing techniques, is discussed.

Use of remote sensing techniques for inventorying and planning utilization of land resources in South Dakota

NASA Technical Reports Server (NTRS)

Myers, V. I.; Frazee, C. J.; Rusche, A. E.; Moore, D. G.; Nelson, G. D.; Westin, F. C.

1974-01-01

The basic procedures for interpreting remote sensing imagery to rapidly develop general soils and land use inventories were developed and utilized in Pennington County, South Dakota. These procedures and remote sensing data products were illustrated and explained to many user groups, some of whom are interested in obtaining similar data. The general soils data were integrated with land soils data supplied by the county director of equalization to prepare a land value map. A computer print-out of this map indicating a land value for each quarter section is being used in tax reappraisal of Pennington County. The land use data provided the land use planners with the present use of land in Pennington County. Additional uses of remote sensing applications are also discussed including tornado damage assessment, hail damage evaluation, and presentation of soil and land value information on base maps assembled from ERTS-1 imagery.

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods.

PubMed

Goetz, Scott J; Baccini, Alessandro; Laporte, Nadine T; Johns, Tracy; Walker, Wayne; Kellndorfer, Josef; Houghton, Richard A; Sun, Mindy

2009-03-25

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets.

Hyper-temporal remote sensing for digital soil mapping: Characterizing soil-vegetation response to climatic variability

USDA-ARS?s Scientific Manuscript database

Indices derived from remotely-sensed imagery are commonly used to predict soil properties with digital soil mapping (DSM) techniques. The use of images from single dates or a small number of dates is most common for DSM; however, selection of the appropriate images is complicated by temporal variabi...

Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications

USDA-ARS?s Scientific Manuscript database

Remote sensing based evapotranspiration (ET) mapping is an important improvement for water resources management. Hourly climatic data and reference ET are crucial for implementing remote sensing based ET models such as METRIC and SEBAL. In Turkey, data on all climatic variables may not be available ...

Hyperspectral remote sensing of canopy biodiversity in Hawaiian lowland rainforests

Treesearch

Kimberly M. Carlson; Gregory P. Asner; R. Flint Hughes; Rebecca Ostertag; Roberta E. Martin

2007-01-01

Mapping biological diversity is a high priority for conservation research, management and policy development, but few studies have provided diversity data at high spatial resolution from remote sensing. We used airborne imaging spectroscopy to map woody vascular plant species richness in lowland tropical forest ecosystems in Hawaii. Hyperspectral signatures spanning...

Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

NASA Astrophysics Data System (ADS)

Trinh, R. C.; Holt, B.; Gierach, M.

2016-02-01

Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also obtained to determine SST anomalies associated with surfaced wastewater at a higher resolution than MODIS. SAR data from ALOS-2, and Sentinel-1 were used to identify surfaced wastewater plumes. In situ drifter, chl-a, SST, and hyperspectral water quality measurements from the diversion were also compared with those obtained by satellite sensors.

Relationship of surface fuels to fire radiative energy as estimated from airborne lidar and thermal infrared imaging

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Dickinson, M. B.; Kremens, R.; Loudermilk, L.; O'Brien, J.; Satterberg, K.; Strand, E. K.; Ottmar, R. D.

2013-12-01

Longleaf pine stand structure and function are dependent on frequent fires, so fire managers maintain healthy longleaf pine ecosystems by frequently burning surface fuels with prescribed fires. Eglin Air Force Base (AFB) in the Florida panhandle boasts the largest remnant of longleaf pine forest, providing a productive setting for fire scientists to make multi-scale measurements of fuels, fire behavior, and fire effects in collaboration with Eglin AFB fire managers. Data considered in this analysis were collected in five prescribed burn units: two forested units burned in 2011 and a forested unit and two grassland units burned in 2012. Our objective was to demonstrate the linear relationship between biomass and fire energy that has been shown in the laboratory, but using two independent remotely sensed airborne datasets collected at the unit level: 1) airborne lidar flown over the burn units immediately prior to the burns, and 2) thermal infrared image time series flown over the burn units at 2-3 minute intervals. Airborne lidar point cloud data were reduced to 3 m raster metrics of surface vegetation height and cover, which were in turn used to map surface fuel loads at 3 m resolution. Plot-based measures of prefire surface fuels were used for calibration/validation. Preliminary results based on 2011 data indicate airborne lidar can explain ~30% of variation in surface fuel loads. Multi-temporal thermal infrared imagery (WASP) collected at 3 m resolution were calibrated to units of fire radiative power (FRP), using simultaneous FRP measures from ground-based radiometers, and then temporally integrated to estimate fire radiative energy (FRE) release at the unit level. Prior to AGU, FRP and FRE will be compared to estimates of the same variables derived from ground-based FLIR thermal infrared imaging cameras, each deployed with a nadir view from a tripod, at three sites per burn unit. A preliminary proof-of-concept, comparing FRE derived from a tripod-based FLIR (3.2 MW), to another FLIR deployed with an oblique view from atop a 36 m boom lift (2.1 MW), demonstrated reasonable agreement. Unit-level estimates of FRE will also be compared to estimates of surface fuel consumption (~5 Mg/ha) that were summarized at the unit level from pre- and post-fire clip plots of surface fuel biomass. At AGU, we will also compare predictions of surface fuel loads to estimates of energy release, as mapped at 3 m resolution from these independent remotely sensed data sources. These results will serve to demonstrate our ability to remotely measure and relate fuel loads to fire behavior at a landscape level.

a Framework for Capacity Building in Mapping Coastal Resources Using Remote Sensing in the Philippines

NASA Astrophysics Data System (ADS)

Tamondong, A.; Cruz, C.; Ticman, T.; Peralta, R.; Go, G. A.; Vergara, M.; Estabillo, M. S.; Cadalzo, I. E.; Jalbuena, R.; Blanco, A.

2016-06-01

Remote sensing has been an effective technology in mapping natural resources by reducing the costs and field data gathering time and bringing in timely information. With the launch of several earth observation satellites, an increase in the availability of satellite imageries provides an immense selection of data for the users. The Philippines has recently embarked in a program which will enable the gathering of LiDAR data in the whole country. The capacity of the Philippines to take advantage of these advancements and opportunities is lacking. There is a need to transfer the knowledge of remote sensing technology to other institutions to better utilize the available data. Being an archipelagic country with approximately 36,000 kilometers of coastline, and most of its people depending on its coastal resources, remote sensing is an optimal choice in mapping such resources. A project involving fifteen (15) state universities and colleges and higher education institutions all over the country headed by the University of the Philippines Training Center for Applied Geodesy and Photogrammetry and funded by the Department of Science and Technology was formed to carry out the task of capacity building in mapping the country's coastal resources using LiDAR and other remotely sensed datasets. This paper discusses the accomplishments and the future activities of the project.

Development of a generalized multi-pixel and multi-parameter satellite remote sensing algorithm for aerosol properties

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Takenaka, H.; Higurashi, A.

2013-12-01

We develop a new satellite remote sensing algorithm to retrieve the properties of aerosol particles in the atmosphere. In late years, high resolution and multi-wavelength, and multiple-angle observation data have been obtained by grand-based spectral radiometers and imaging sensors on board the satellite. With this development, optimized multi-parameter remote sensing methods based on the Bayesian theory have become popularly used (Turchin and Nozik, 1969; Rodgers, 2000; Dubovik et al., 2000). Additionally, a direct use of radiation transfer calculation has been employed for non-linear remote sensing problems taking place of look up table methods supported by the progress of computing technology (Dubovik et al., 2011; Yoshida et al., 2011). We are developing a flexible multi-pixel and multi-parameter remote sensing algorithm for aerosol optical properties. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, we include a radiation transfer calculation code, Rstar (Nakajima and Tanaka, 1986, 1988), numerically solved each time in iteration for solution search. The Rstar-code has been directly used in the AERONET operational processing system (Dubovik and King, 2000). Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode, sea salt, and dust particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. In this test, we simulated satellite-observed radiances for a sub-domain consisting of 5 by 5 pixels by the Rstar code assuming wavelengths of 380, 674, 870 and 1600 [nm], atmospheric condition of the US standard atmosphere, and the several aerosol and ground surface conditions. The result of the experiment showed that AOTs of fine mode and dust particles, soot fraction and ground surface albedo at the wavelength of 674 [nm] are retrieved within absolute value differences of 0.04, 0.01, 0.06 and 0.006 from the true value, respectively, for the case of dark surface, and also, for the case of blight surface, 0.06, 0.03, 0.04 and 0.10 from the true value, respectively. We will conduct more tests to study the information contents of parameters needed for aerosol and land surface remote sensing with different boundary conditions among sub-domains.

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

PubMed

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods.

PubMed

de Klerk, Helen M; Gilbertson, Jason; Lück-Vogel, Melanie; Kemp, Jaco; Munch, Zahn

2016-11-01

Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single 'best performer' from which the final map is made. We use a combination of an omission/commission plot to evaluate various results and compile a probability map based on consistently strong performing models across a range of standard accuracy measures. We suggest that this easy-to-use approach can be applied in any study using remote sensing to map natural features for management action. We demonstrate this approach using optical remote sensing products of different spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral resolution). Of the variety of classification algorithms available, we tested maximum likelihood and support vector machine, and applied these to raw spectral data, the first three PCA summaries of the data, and the standard normalised difference vegetation index. We found that there is no 'one size fits all' solution to the choice of a 'best fit' model (i.e. combination of classification algorithm or data sets), which is in agreement with the literature that classifier performance will vary with data properties. We feel this lends support to our suggestion that rather than the identification of a 'single best' model and a map based on this result alone, a probability map based on the range of consistently top performing models provides a rigorous solution to environmental mapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing.

PubMed

William, David J; Rybicki, Nancy B; Lombana, Alfonso V; O'Brien, Tim M; Gomez, Richard B

2003-01-01

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.

Nasa's Operation Icebridge and Remote Sensing Techniques in the K-12 Classroom as a STEM Integration Project

NASA Astrophysics Data System (ADS)

McCarthy, K.

2017-12-01

NASA's Operation IceBridge (OIB), the largest airborne survey of Earth's polar ice uses remote sensing methods to collect data on changing sea and land ice. PolarTREC teacher Kelly McCarthy joined the team during the 2016 Spring Arctic Campaign. This presentation explores ways in which k-12 students were engaged in the work being done by OIB through classroom learning experiences, digital communications, and independent research. Initially, digital communication including chats via NASA's Mission Tools Suite for Education (MTSE) platform was leveraged to engage students in the daily work of OIB. Two lessons were piloted with student groups during the 2016-2017 academic year both for students who actively engaged in communications with the team during the expedition and those who had no prior connections to the field. All of the data collected on OIB missions is stored for public use in a digital portal on the National Snow and Ice Data Center (NSIDC) website. In one lesson, 10th-12th grade students were guided through a tutorial to learn how to access data and begin to develop a story about Greenland's Jakobshavn Glacier using pre-selected data sets, Google's MyMaps app, and independent research methods. In the second lesson, 8th grade students were introduced to remote sensing, first through a discussion on vocabulary using productive talk moves and then via a demonstration using Vernier motion detectors and a graph matching simulation. Students worked in groups to develop procedures to map a hidden surface region (boxed assortment of miscellaneous objects) using a Vernier motion sensor to simulate sonar. Students translated data points collected from the motion sensor into a vertical profile of the simulated surface region. Both lessons allowed students a way to engage in two of the most important components of OIB. The ability to work with real data collected by the OIB team provided a unique context through which students gained skill and overcame challenges in Excel, Google Apps, construction of graphs, and data analysis. The remote sensing simulation allowed students to practice and gain hands-on knowledge of the components of OIB discussed in the digital communications that may have felt unclear to students who have had limited or no exposure to remote sensing technologies or the science behind them.

Titan Orbiter with Aerorover Mission (TOAM)

NASA Astrophysics Data System (ADS)

Sittler, Edward C.; Cooper, J. F.; Mahaffey, P.; Esper, J.; Fairbrother, D.; Farley, R.; Pitman, J.; Kojiro, D. R.; TOAM Team

2006-12-01

We propose to develop a new mission to Titan called Titan Orbiter with Aerorover Mission (TOAM). This mission is motivated by the recent discoveries of Titan, its atmosphere and its surface by the Huygens Probe, and a combination of in situ, remote sensing and radar mapping measurements of Titan by the Cassini orbiter. Titan is a body for which Astrobiology (i.e., prebiotic chemistry) will be the primary science goal of any future missions to it. TOAM is planned to use an orbiter and balloon technology (i.e., aerorover). Aerobraking will be used to put payload into orbit around Titan. The Aerorover will probably use a hot air balloon concept using the waste heat from the MMRTG 500 watts. Orbiter support for the Aerorover is unique to our approach for Titan. Our strategy to use an orbiter is contrary to some studies using just a single probe with balloon. Autonomous operation and navigation of the Aerorover around Titan will be required, which will include descent near to the surface to collect surface samples for analysis (i.e., touch and go technique). The orbiter can provide both relay station and GPS roles for the Aerorover. The Aerorover will have all the instruments needed to sample Titan’s atmosphere, surface, possible methane lakes-rivers, use multi-spectral imagers for surface reconnaissance; to take close up surface images; take core samples and deploy seismometers during landing phase. Both active and passive broadband remote sensing techniques will be used for surface topography, winds and composition measurements.

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes. Version 1.9

NASA Technical Reports Server (NTRS)

Arain, Altaf M.; Shuttleworth, W. James; Yang, Z-Liang; Michaud, Jene; Dolman, Johannes

1997-01-01

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.

Mapping alteration using imagery from the Tiangong-1 hyperspectral spaceborne system: Example for the Jintanzi gold province, China

NASA Astrophysics Data System (ADS)

Liu, Lei; Feng, Jilu; Rivard, Benoit; Xu, Xinliang; Zhou, Jun; Han, Ling; Yang, Junlu; Ren, Guangli

2018-02-01

The Tiangong-1 Hyperspectral Imager (HSI) is a relatively new spaceborne hyperspectral remote sensing system that was launched by the Chinese government on September 29th 2011. The system has 64 shortwave infrared (SWIR) spectral bands (1000-2500 nm) and imagery is at a spatial resolution of 20 m. This study represents an evaluation of Tiangong-1 data for the production of alteration mineral maps. Alteration mineral maps resulting from the analysis of Tiangong-1 HSI data and airborne SASI (Shortwave infrared Airborne Spectrographic Imager) data are compared for the Jintanzi area, Beishan, Gansu province, northwest China where gold bearing veins are documented. The results illustrate the detection of muscovite, kaolinite, chlorite, epidote, calcite and dolomite from Tiangong-1 HSI data and most anomalies seen in the airborne SASI data are captured. The Tiangong-1 data appears to be well suited for the detection of surface mineralogy in support of regional mapping and exploration. The data complements that which will be offered by the Chinese GF-5 Hyperspectral Imager and the German EnMAP system, both scheduled for launch in 2018.

Regional Geological Mapping in the Graham Land of Antarctic Peninsula Using LANDSAT-8 Remote Sensing Data

NASA Astrophysics Data System (ADS)

Pour, A. B.; Hashim, M.; Park, Y.

2017-10-01

Geological investigations in Antarctica confront many difficulties due to its remoteness and extreme environmental conditions. In this study, the applications of Landsat-8 data were investigated to extract geological information for lithological and alteration mineral mapping in poorly exposed lithologies in inaccessible domains such in Antarctica. The north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. Continuum Removal (CR) spectral mapping tool and Independent Components Analysis (ICA) were applied to Landsat-8 spectral bands to map poorly exposed lithologies at regional scale. Pixels composed of distinctive absorption features of alteration mineral assemblages associated with poorly exposed lithological units were detected by applying CR mapping tool to VNIR and SWIR bands of Landsat-8.Pixels related to Si-O bond emission minima features were identified using CR mapping tool to TIR bands in poorly mapped andunmapped zones in north-eastern Graham Land at regional scale. Anomaly pixels in the ICA image maps related to spectral featuresof Al-O-H, Fe, Mg-O-H and CO3 groups and well-constrained lithological attributions from felsic to mafic rocks were detectedusing VNIR, SWIR and TIR datasets of Landsat-8. The approach used in this study performed very well for lithological andalteration mineral mapping with little available geological data or without prior information of the study region.

Circular polarization of light by planet Mercury and enantiomorphism of its surface minerals.

PubMed

Meierhenrich, Uwe J; Thiemann, Wolfram H P; Barbier, Bernard; Brack, André; Alcaraz, Christian; Nahon, Laurent; Wolstencroft, Ray

2002-04-01

Different mechanisms for the generation of circular polarization by the surface of planets and satellites are described. The observed values for Venus, the Moon, Mars, and Jupiter obtained by photo-polarimetric measurements with Earth based telescopes, showed accordance with theory. However, for planet Mercury asymmetric parameters in the circular polarization were measured that do not fit with calculations. For BepiColombo, the ESA cornerstone mission 5 to Mercury, we propose to investigate this phenomenon using a concept which includes two instruments. The first instrument is a high-resolution optical polarimeter, capable to determine and map the circular polarization by remote scanning of Mercury's surface from the Mercury Planetary Orbiter MPO. The second instrument is an in situ sensor for the detection of the enantiomorphism of surface crystals and minerals, proposed to be included in the Mercury Lander MSE.

Correlating sea level rise still-stands to marine terraces and undiscovered submerged shoreline features in the Channel Islands (USA) using autonomous and remotely operated systems

NASA Astrophysics Data System (ADS)

Raineault, N.; Ballard, R. D.; Fahy, J.; Mayer, L. A.; Heffron, E.; Krasnosky, K.; Roman, C.; Schmidt, V. E.; McLeod, A.; Bursek, J.; Broad, K.

2017-12-01

In 2017, the Ocean Exploration Trust aggregated onboard and autonomous mapping technologies to identify and explore paleo shorelines and discover previously undocumented submerged shoreline features in and around the Channel Islands offshore of California. Broad area mapping was conducted with the hull mounted multibeam echosounder aboard the E/V Nautilus. This Kongsberg EM302 provided maps at 2-10 m resolution, at depths generally greater than 50 m. From this data marine terraces were identified for higher resolution mapping via an Autonomous Surface Vehicle (ASV). The precision data from the ASV's Kongsberg EM2040p echosounder allowed identification of the knickpoints associated with cliffs on the landward extent of each terrace. Sub-sea cave targets were identified using backscatter and slope maps from a combination of both the broad area and high resolution multibeam data. To ground-truth the targets identified through mapping, remotely operated vehicles (ROVs) and a highly specialized team of cave divers explored these targets. The results from the visual inspection were then fed back into the analysis fostering the rapid iteration of the onboard identification criteria and resulted in locating submerged shorelines containing numerous large caves, arches, and concretions. Caves were found at still-stands at 8, 33, 66, and 103 m depth at Santa Cruz Island, Santa Barbara Island platform, and Osborn Bank, along the vertical escarpment at the cliff-face and aligned with the strike of fractures in the volcanic rock. These terraces correspond to different sea level still-stands. ROV grab samples of fossiliferous marine terraces will provide ages and aid in reconstructions of sea level change and tectonic history for each location. Finally, caves were mapped in sub-cm resolution using a Kongsberg M3 sonar mounted vertically on the front of the ROV to test the capabilities of the system to provide accurate information about exterior dimensions and morphology.

Autonomous exploration and mapping of unknown environments

NASA Astrophysics Data System (ADS)

Owens, Jason; Osteen, Phil; Fields, MaryAnne

2012-06-01

Autonomous exploration and mapping is a vital capability for future robotic systems expected to function in arbitrary complex environments. In this paper, we describe an end-to-end robotic solution for remotely mapping buildings. For a typical mapping system, an unmanned system is directed to enter an unknown building at a distance, sense the internal structure, and, barring additional tasks, while in situ, create a 2-D map of the building. This map provides a useful and intuitive representation of the environment for the remote operator. We have integrated a robust mapping and exploration system utilizing laser range scanners and RGB-D cameras, and we demonstrate an exploration and metacognition algorithm on a robotic platform. The algorithm allows the robot to safely navigate the building, explore the interior, report significant features to the operator, and generate a consistent map - all while maintaining localization.

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.

Threshold Determination for Local Instantaneous Sea Surface Height Derivation with Icebridge Data in Beaufort Sea

NASA Astrophysics Data System (ADS)

Zhu, C.; Zhang, S.; Xiao, F.; Li, J.; Yuan, L.; Zhang, Y.; Zhu, T.

2018-05-01

The NASA Operation IceBridge (OIB) mission is the largest program in the Earth's polar remote sensing science observation project currently, initiated in 2009, which collects airborne remote sensing measurements to bridge the gap between NASA's ICESat and the upcoming ICESat-2 mission. This paper develop an improved method that optimizing the selection method of Digital Mapping System (DMS) image and using the optimal threshold obtained by experiments in Beaufort Sea to calculate the local instantaneous sea surface height in this area. The optimal threshold determined by comparing manual selection with the lowest (Airborne Topographic Mapper) ATM L1B elevation threshold of 2 %, 1 %, 0.5 %, 0.2 %, 0.1 % and 0.05 % in A, B, C sections, the mean of mean difference are 0.166 m, 0.124 m, 0.083 m, 0.018 m, 0.002 m and -0.034 m. Our study shows the lowest L1B data of 0.1 % is the optimal threshold. The optimal threshold and manual selections are also used to calculate the instantaneous sea surface height over images with leads, we find that improved methods has closer agreement with those from L1B manual selections. For these images without leads, the local instantaneous sea surface height estimated by using the linear equations between distance and sea surface height calculated over images with leads.

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Integrating seasonal optical and thermal infrared spectra to characterize urban impervious surfaces with extreme spectral complexity: a Shanghai case study

NASA Astrophysics Data System (ADS)

Wang, Wei; Yao, Xinfeng; Ji, Minhe

2016-01-01

Despite recent rapid advancement in remote sensing technology, accurate mapping of the urban landscape in China still faces a great challenge due to unusually high spectral complexity in many big cities. Much of this complication comes from severe spectral confusion of impervious surfaces with polluted water bodies and bright bare soils. This paper proposes a two-step land cover decomposition method, which combines optical and thermal spectra from different seasons to cope with the issue of urban spectral complexity. First, a linear spectral mixture analysis was employed to generate fraction images for three preliminary endmembers (high albedo, low albedo, and vegetation). Seasonal change analysis on land surface temperature induced from thermal infrared spectra and coarse component fractions obtained from the first step was then used to reduce the confusion between impervious surfaces and nonimpervious materials. This method was tested with two-date Landsat multispectral data in Shanghai, one of China's megacities. The results showed that the method was capable of consistently estimating impervious surfaces in highly complex urban environments with an accuracy of R2 greater than 0.70 and both root mean square error and mean average error less than 0.20 for all test sites. This strategy seemed very promising for landscape mapping of complex urban areas.

Low-Cost Ultra-High Spatial and Temporal Resolution Mapping of Intertidal Rock Platforms

NASA Astrophysics Data System (ADS)

Bryson, M.; Johnson-Roberson, M.; Murphy, R.

2012-07-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Remote Sensing.

ERIC Educational Resources Information Center

Williams, Richard S., Jr.; Southworth, C. Scott

1983-01-01

The Landsat Program became the major event of 1982 in geological remote sensing with the successful launch of Landsat 4. Other 1982 remote sensing accomplishments, research, publications, (including a set of Landsat worldwide reference system index maps), and conferences are highlighted. (JN)

Remote infrared audible signage (RIAS) pilot program report.

DOT National Transportation Integrated Search

2011-07-01

The Remote Infrared Audible Sign Model Accessibility Program (RIAS MAP) is a program funded by the Federal Transit Administration (FTA) to evaluate the effectiveness of remote infrared audible sign systems in enabling persons with visual and cognitiv...