Active Ground Optical Remote Sensing for Improved Monitoring of Seedling Stress in Nurseries

USDA-ARS?s Scientific Manuscript database

Active ground optical remote sensing (AGORS) devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and ...

Pest measurement and management

USDA-ARS?s Scientific Manuscript database

Pest scouting, whether it is done only with ground scouting methods or using remote sensing with some ground-truthing, is an important tool to aid site-specific crop management. Different pests may be monitored at different times and using different methods. Remote sensing has the potential to provi...

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Bridging the Scales from Field to Region with Practical Tools to Couple Time- and Space-Synchronized Data from Flux Towers and Networks with Proximal and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Burba, G. G.; Avenson, T.; Burkart, A.; Gamon, J. A.; Guan, K.; Julitta, T.; Pastorello, G.; Sakowska, K.

2017-12-01

Many hundreds of flux towers are presently operational as standalone projects and as parts of regional networks. However, the vast majority of these towers do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and even fewer have optical sensors for validation of remote sensing products, and upscaling from field to regional levels. In 2016-2017, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, and to streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data: GPS-driven PTP time protocol synchronizes instrumentation within the station, different stations with each other, and all of these to remote sensing data to precisely align remote sensing and flux data in time Footprint size and coordinates computed and stored with flux data help correctly align tower flux footprints and drone, aircraft or satellite motion to precisely align optical and flux data in space Full snapshot of the remote sensing pixel can then be constructed, including leaf-level, ground optical sensor, and flux tower measurements from the same footprint area, closely coupled with the remote sensing measurements to help interpret remote sensing data, validate models, and improve upscaling Additionally, current flux towers can be augmented with advanced ground optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems. Several dozens of new towers already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux towers can be updated to synchronize their data with remote sensing measurements. This presentation will show how the new tools are used by major networks, and describe how this approach can be utilized for matching remote sensing and tower data to aid in ground truthing, improve scientific interactions, and promote joint grant writing and other forms of collaboration between the flux and remote sensing communities.

Improved ground-based remote-sensing systems help monitor plant response to climate and other changes

USGS Publications Warehouse

Dye, Dennis G.; Bogle, Rian

2016-05-26

Scientists at the U.S. Geological Survey are improving and developing new ground-based remote-sensing instruments and techniques to study how Earth’s vegetation responds to changing climates. Do seasonal grasslands and forests “green up” early (or late) and grow more (or less) during unusually warm years? How do changes in temperature and precipitation affect these patterns? Innovations in ground-based remote-sensing instrumentation can help us understand, assess, and mitigate the effects of climate change on vegetation and related land resources.

Remote sensing of vegetation pattern and condition to monitor changes in everglades biogeochemistry

USGS Publications Warehouse

Jones, J.W.

2011-01-01

Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management. Copyright ?? 2011 Taylor & Francis Group, LLC.

Monitoring rice (oryza sativa L.) growth using multifrequency microwave scatterometers

USDA-ARS?s Scientific Manuscript database

Microwave remote sensing can help monitor the land surface water cycle and crop growth. This type of remote sensing has great potential over conventional remote sensing using the visible and infrared regions due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-b...

Tasseled cap transformation for HJ multispectral remote sensing data

NASA Astrophysics Data System (ADS)

Han, Ling; Han, Xiaoyong

2015-12-01

The tasseled cap transformation of remote sensing data has been widely used in environment, agriculture, forest and ecology. Tasseled cap transformation coefficients matrix of HJ multi-spectrum data has been established through Givens rotation matrix to rotate principal component transform vector to whiteness, greenness and blueness direction of ground object basing on 24 scenes year-round HJ multispectral remote sensing data. The whiteness component enhances the brightness difference of ground object, and the greenness component preserves more detailed information of vegetation change while enhances the vegetation characteristic, and the blueness component significantly enhances factory with blue plastic house roof around the town and also can enhance brightness of water. Tasseled cap transformation coefficients matrix of HJ will enhance the application effect of HJ multispectral remote sensing data in their application fields.

Use of remote sensing in agriculture

NASA Technical Reports Server (NTRS)

Pettry, D. E.; Powell, N. L.; Newhouse, M. E.

1974-01-01

Remote sensing studies in Virginia and Chesapeake Bay areas to investigate soil and plant conditions via remote sensing technology are reported ant the results given. Remote sensing techniques and interactions are also discussed. Specific studies on the effects of soil moisture and organic matter on energy reflection of extensively occurring Sassafras soils are discussed. Greenhouse and field studies investigating the effects of chlorophyll content of Irish potatoes on infrared reflection are presented. Selected ground truth and environmental monitoring data are shown in summary form. Practical demonstrations of remote sensing technology in agriculture are depicted and future use areas are delineated.

Observations in the solar spectrum interest for remote sensing purposes

NASA Technical Reports Server (NTRS)

Herman, M.; Vanderbilt, V.

1994-01-01

The polarization of the sunlight scattered by atmospheric aerosols or cloud droplets and reflected from ground surfaces or plant canopies may convey much information when used for remote sensing purposes. The typical polarization features of aerosols, cloud droplets, and plant canopies, as observed by ground based and airborne sensors, are investigated, looking especially for those invariant properties amenable to description by simple models when possible. The question of polarization measurements from space is addressed. The interest of such measurements for remote sensing purposes is investigated, and their feasibility is tested by using results obtained during field campaigns of the airborne POLDER instrument, a radiometer designed to measure the directionality and polarization of the sunlight scattered by the ground atmosphere system.

Research of BRDF effects on remote sensing imagery

NASA Astrophysics Data System (ADS)

Nina, Peng; Kun, Wang; Tao, Li; Yang, Pan

2011-08-01

The gray distribution and contrast of the optical satellite remote sensing imagery in the same kind of ground surface acquired by sensor is quite different, it depends not only on the satellite's observation and the sun incidence orientation but also the structural and optical properties of the surface. Therefore, the objectives of this research are to analyze the different BRDF characters of soil, vegetation, water and urban surface and also their BRDF effects on the quality of satellite image through 6S radiative transfer model. Furthermore, the causation of CCD blooming and spilling by ground reflectance is discussed by using QUICKBIRD image data and the corresponding ground image data. The general conclusion of BRDF effects on remote sensing imagery is proposed.

Airborne and satellite remote sensors for precision agriculture

USDA-ARS?s Scientific Manuscript database

Remote sensing provides an important source of information to characterize soil and crop variability for both within-season and after-season management despite the availability of numerous ground-based soil and crop sensors. Remote sensing applications in precision agriculture have been steadily inc...

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Educational activities of remote sensing archaeology (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasilki; Themistocleous, Kyriacos; Cuca, Branka; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter

2016-10-01

Remote sensing science is increasingly being used to support archaeological and cultural heritage research in various ways. Satellite sensors either passive or active are currently used in a systematic basis to detect buried archaeological remains and to systematic monitor tangible heritage. In addition, airborne and low altitude systems are being used for documentation purposes. Ground surveys using remote sensing tools such as spectroradiometers and ground penetrating radars can detect variations of vegetation and soil respectively, which are linked to the presence of underground archaeological features. Education activities and training of remote sensing archaeology to young people is characterized of highly importance. Specific remote sensing tools relevant for archaeological research can be developed including web tools, small libraries, interactive learning games etc. These tools can be then combined and aligned with archaeology and cultural heritage. This can be achieved by presenting historical and pre-historical records, excavated sites or even artifacts under a "remote sensing" approach. Using such non-form educational approach, the students can be involved, ask, read, and seek to learn more about remote sensing and of course to learn about history. The paper aims to present a modern didactical concept and some examples of practical implementation of remote sensing archaeology in secondary schools in Cyprus. The idea was built upon an ongoing project (ATHENA) focused on the sue of remote sensing for archaeological research in Cyprus. Through H2020 ATHENA project, the Remote Sensing Science and Geo-Environment Research Laboratory at the Cyprus University of Technology (CUT), with the support of the National Research Council of Italy (CNR) and the German Aerospace Centre (DLR) aims to enhance its performance in all these new technologies.

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Quantifying Forest Ground Flora Biomass Using Close-range Remote Sensing

Treesearch

Paul F. Doruska; Robert C. Weih; Matthew D. Lane; Don C. Bragg

2005-01-01

Close-range remote sensing was used to estimate biomass of forest ground flora in Arkansas. Digital images of a series of 1-m² plots were taken using Kodak DCS760 and Kodak DCS420CIR digital cameras. ESRI ArcGIS™ and ERDAS Imagine® software was used to calculate the Normalized Difference Vegetation Index (NDVI) and the Average Visible...

Local involvement in measuring and governing carbon stocks in China, Vietnam, Indonesia and Laos

Treesearch

Michael Køie Poulsen

2013-01-01

An important element of MRV is to ensure accurate measurements of carbon stocks. Measuring trees on the ground may be needed for ground truthing of remote sensing results. It can also provide more accurate carbon stock monitoring than remote sensing alone. Local involvement in measuring trees for monitoring of carbon stocks may be advantageous in several ways....

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

Proxies for soil organic carbon derived from remote sensing

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

A change detection method for remote sensing image based on LBP and SURF feature

NASA Astrophysics Data System (ADS)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review.

PubMed

Maes, W H; Steppe, K

2012-08-01

As evaporation of water is an energy-demanding process, increasing evapotranspiration rates decrease the surface temperature (Ts) of leaves and plants. Based on this principle, ground-based thermal remote sensing has become one of the most important methods for estimating evapotranspiration and drought stress and for irrigation. This paper reviews its application in agriculture. The review consists of four parts. First, the basics of thermal remote sensing are briefly reviewed. Second, the theoretical relation between Ts and the sensible and latent heat flux is elaborated. A modelling approach was used to evaluate the effect of weather conditions and leaf or vegetation properties on leaf and canopy temperature. Ts increases with increasing air temperature and incoming radiation and with decreasing wind speed and relative humidity. At the leaf level, the leaf angle and leaf dimension have a large influence on Ts; at the vegetation level, Ts is strongly impacted by the roughness length; hence, by canopy height and structure. In the third part, an overview of the different ground-based thermal remote sensing techniques and approaches used to estimate drought stress or evapotranspiration in agriculture is provided. Among other methods, stress time, stress degree day, crop water stress index (CWSI), and stomatal conductance index are discussed. The theoretical models are used to evaluate the performance and sensitivity of the most important methods, corroborating the literature data. In the fourth and final part, a critical view on the future and remaining challenges of ground-based thermal remote sensing is presented.

Remote sensing of high-latitude ionization profiles by ground-based and spaceborne instrumentation

NASA Technical Reports Server (NTRS)

Vondrak, R. R.

1981-01-01

Ionospheric specification and modeling are now largely based on data provided by active remote sensing with radiowave techniques (ionosondes, incoherent-scatter radars, and satellite beacons). More recently, passive remote sensing techniques have been developed that can be used to monitor quantitatively the spatial distribution of high-latitude E-region ionization. These passive methods depend on the measurement, or inference, of the energy distribution of precipitating kilovolt electrons, the principal source of the nighttime E-region at high latitudes. To validate these techniques, coordinated measurements of the auroral ionosphere have been made with the Chatanika incoherent-scatter radar and a variety of ground-based and spaceborne sensors

A Multiscale Random Field Model for Bayesian Image Segmentation

DTIC Science & Technology

1994-06-01

ATrN: Natural Resources Branch ATTN G ieCN-C3 D-E Aberden Povig Ground . MD 21005 At Aii-DI (2)AWN IS-TEOMAMr: ATZHI-DtE (2) ATTN: ISH-BECOM Fort...based remotely-sensed data and ground -level data for natural resource inventory and evaluation. Coupling remotely sensed digital data with traditional...ecological ground data could help Army land managers inventory and monitor natural resources. This study used LCTA data sets to D T IC test image

Remote sensing applications in water resources - An opportunity for research in developing countries

NASA Technical Reports Server (NTRS)

Menenti, M.

1992-01-01

A review is presented of first-hand experience with remote sensing research in developing countries to illustrate the inherent semiempirical basis of remote sensing applications. This task is accomplished by means of examples drawn from actual research work. Results of case studies in different farming systems and countries are summarized to exemplify the relative, application-dependent, weight of satellite versus ground information.

Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models

Treesearch

H. Viana; J. Aranha; D. Lopes; Warren B. Cohen

2012-01-01

Spatially crown biomass of Pinus pinaster stands and shrubland above-ground biomass (AGB) estimation was carried-out in a region located in Centre-North Portugal, by means of different approaches including forest inventory data, remotely sensed imagery and spatial prediction models. Two cover types (pine stands and shrubland) were inventoried and...

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Seasat Celebrates Landmark in Remote-Sensing History

NASA Image and Video Library

2013-06-27

Seasat, built and managed by NASA Jet Propulsion Laboratory JPL, was launched thirty-five years ago, on June 27, 1978. It was the first satellite designed for remote sensing of the Earth oceans using many ground-breaking technologies.

Indicators of international remote sensing activities

NASA Technical Reports Server (NTRS)

Spann, G. W.

1977-01-01

The extent of worldwide remote sensing activities, including the use of satellite and high/medium altitude aircraft data was studied. Data were obtained from numerous individuals and organizations with international remote sensing responsibilities. Indicators were selected to evaluate the nature and scope of remote sensing activities in each country. These indicators ranged from attendance at remote sensing workshops and training courses to the establishment of earth resources satellite ground stations and plans for the launch of earth resources satellites. Results indicate that this technology constitutes a rapidly increasing component of environmental, land use, and natural resources investigations in many countries, and most of these countries rely on the LANDSAT satellites for a major portion of their data.

Free acquisition and dissemination of data through remote sensing. [Landsat program legal aspects

NASA Technical Reports Server (NTRS)

Hosenball, S. N.

1976-01-01

Free acquisition and dissemination of data through remote sensing is discussed with reference to the Landsat program. The role of the Scientific and Technical Subcommittee of the U.N. General Assembly's Committee on the Peaceful Uses of Outer Space has made recommendations on the expansion of existing ground stations and on the establishment of an experimental center for training in remote sensing. The working group for the legal subcommittee of the same U.N. committee indicates that there are common elements in the three drafts on remote sensing submitted to it: a call for international cooperation and the belief that remote sensing should be conducted for the benefit of all mankind.

Absolute radiometric calibration of advanced remote sensing systems

NASA Technical Reports Server (NTRS)

Slater, P. N.

1982-01-01

The distinction between the uses of relative and absolute spectroradiometric calibration of remote sensing systems is discussed. The advantages of detector-based absolute calibration are described, and the categories of relative and absolute system calibrations are listed. The limitations and problems associated with three common methods used for the absolute calibration of remote sensing systems are addressed. Two methods are proposed for the in-flight absolute calibration of advanced multispectral linear array systems. One makes use of a sun-illuminated panel in front of the sensor, the radiance of which is monitored by a spectrally flat pyroelectric radiometer. The other uses a large, uniform, high-radiance reference ground surface. The ground and atmospheric measurements required as input to a radiative transfer program to predict the radiance level at the entrance pupil of the orbital sensor are discussed, and the ground instrumentation is described.

Verification of retail food outlet location data from a local health department using ground-truthing and remote-sensing technology: assessing differences by neighborhood characteristics.

PubMed

Rossen, Lauren M; Pollack, Keshia M; Curriero, Frank C

2012-09-01

Obtaining valid and accurate data on community food environments is critical for research evaluating associations between the food environment and health outcomes. This study utilized ground-truthing and remote-sensing technology to validate a food outlet retail list obtained from an urban local health department in Baltimore, Maryland in 2009. Ten percent of outlets (n=169) were assessed, and differences in accuracy were explored by neighborhood characteristics (96 census tracts) to determine if discrepancies were differential or non-differential. Inaccuracies were largely unrelated to a variety of neighborhood-level variables, with the exception of number of vacant housing units. Although remote-sensing technologies are a promising low-cost alternative to direct observation, this study demonstrated only moderate levels of agreement with ground-truthing. Published by Elsevier Ltd.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 3 : use of scanning LiDAR in structural evaluation of bridges.

DOT National Transportation Integrated Search

2009-12-01

This volume introduces several applications of remote bridge inspection technologies studied in : this Integrated Remote Sensing and Visualization (IRSV) study using ground-based LiDAR : systems. In particular, the application of terrestrial LiDAR fo...

Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

NASA Astrophysics Data System (ADS)

Dong, Chunyu

2018-06-01

Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

First observations of tropospheric δD data observed by ground- and space-based remote sensing and surface in-situ measurement techniques at MUSICA's principle reference station (Izaña Observatory, Spain)

NASA Astrophysics Data System (ADS)

González, Yenny; Schneider, Matthias; Christner, Emanuel; Rodríguez, Omaira E.; Sepúlveda, Eliezer; Dyroff, Christoph; Wiegele, Andreas

2013-04-01

The main goal of the project MUSICA (Multiplatform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi global tropospheric water vapor isototopologue dataset of a good and well-documented quality. Therefore, new ground- and space-based remote sensing observations (NDACC-FTIR and IASI/METOP) are combined with in-situ measurements. This work presents the first comparison between in-situ and remote sensing observations made at the Izaña Atmospheric Research Centre (Tenerife, Canary Islands, Spain). The in-situ measurements are made by a Picarro L2120-i water vapor isotopologue analyzer. At Izaña the in-situ data are affected by local small-scale mixing processes: during daylight, the thermally buoyant upslope flow prompts the mixing between the Marine Boundary Layer (MBL) and the low Free Troposphere (FT). However, the remote sensors detect δD values averaged over altitudes that are more representative for the free troposphere. This difference has to be considered for the comparison. In general, a good agreement between the MUSICA remote sensing and the in situ H2O-versus-δD plots is found, which demonstrates that the MUSICA δD remote sensing products add scientifically valuable information to the H2O data.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

An international organization for remote sensing

NASA Technical Reports Server (NTRS)

Helm, Neil R.; Edelson, Burton I.

1991-01-01

A recommendation is presented for the formation of a new commercially oriented international organization to acquire or develop, coordinate or manage, the space and ground segments for a global operational satellite system to furnish the basic data for remote sensing and meteorological, land, and sea resource applications. The growing numbers of remote sensing programs are examined and possible ways of reducing redundant efforts and improving the coordination and distribution of these global efforts are discussed. This proposed remote sensing organization could play an important role in international cooperation and the distribution of scientific, commercial, and public good data.

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

EVALUATION OF FUGITIVE EMISSIONS USING GROUND-BASED OPTICAL REMOTE SENSING TECHNOLOGY

EPA Science Inventory

EPA has developed and evaluated a method for characterizing fugitive emissions from large area sources. The method, known as radial plume mapping (RPM) uses multiple-beam, scanning, optical remote sensing (ORS) instrumentation such as open-path Fourier transform infrared spectro...

Strategies for using remotely sensed data in hydrologic models

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

State resource management and role of remote sensing. [California

NASA Technical Reports Server (NTRS)

Johnson, H. D.

1981-01-01

Remote sensing by satellite can provide valuable information to state officials when making decisions regarding resources management. Portions of California's investment for Prosperity program which seem likely candidates for remote sensing include: (1) surveying vegetation type, age, and density in forests and wildlife habitats; (2) controlling fires through chaparal management; (3) monitoring wetlands and measuring ocean biomass; (4) eliminating ground water overdraught; (5) locating crops in overdraught areas, assessing soil erosion and the areas of poorly drained soils and those affected by salt; (6) monitoring coastal lands and resources; (7) changes in landscapes for recreational purposes; (8) inventorying irrigated lands; (9) classifying ground cover; (10) monitoring farmland conversion; and (11) supplying data for a statewide computerized farmlands data base.

Analyzing Forest Inventory Data from Geo-Located Photographs

NASA Astrophysics Data System (ADS)

Toivanen, Timo; Tergujeff, Renne; Andersson, Kaj; Molinier, Matthieu; Häme, Tuomas

2015-04-01

Forests are widely monitored using a variety of remote sensing data and techniques. Remote sensing offers benefits compared to traditional in-situ forest inventories made by experts. One of the main benefits is that the number of ground reference plots can be significantly reduced. Remote sensing of forests can provide reduced costs and time requirement compared to full forest inventories. The availability of ground reference data has been a bottleneck in remote sensing analysis over wide forested areas, as the acquisition of this data is an expensive and slow process. In this paper we present a tool for estimating forest inventory data from geo-located photographs. The tool can be used to estimate in-situ forest inventory data including estimated biomass, tree species, tree height and diameter. The collected in-situ forest measurements can be utilized as a ground reference material for spaceborne or airborne remote sensing data analysis. The GPS based location information with measured forest data makes it possible to introduce measurements easily as in-situ reference data. The central projection geometry of digital photographs allows the use of the relascope principle [1] to measure the basal area of stems per area unit, a variable very closely associated with tree biomass. Relascope is applied all over the world for forest inventory. Experiments with independent ground reference data have shown that in-situ data analysed from photographs can be utilised as reference data for satellite image analysis. The concept was validated by comparing mobile measurements with 54 independent ground reference plots from the Hyytiälä forest research station in Finland [2]. Citizen scientists could provide the manpower for analysing photographs from forests on a global level and support researchers working on tasks related to forests. This low-cost solution can also increase the coverage of forest management plans, particularly in regions where possibilities to invest on expensive planning work are limited. References [1] Bitterlich, W. (1984) The Relascope Idea: Relative Measurements in Forestry, Commonwealth Agricultural Bureaux, Farnham Royal, 1984. [2] Molinier, M., Hame, T., Toivanen, T., Andersson, K., Mutanen, T., Relasphone -- Mobile phone and interactive applications to collect ground reference biomass data for satellite image analysis, Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, pp. 836-839, 13-18 July 2014, doi: 10.1109/IGARSS.2014.6946554

[Use of Remote Sensing for Crop and Soil Analysis

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.

1997-01-01

The primary agricultural objective of this research is to determine what soil and crop information can be verified from remotely sensed images during the growing season. Specifically: (1) Elements of crop stress due to drought, weeds, disease and nutrient deficiencies will be documented with ground truth over specific agricultural sites and (2) Use of remote sensing with GPS and GIS technology for providing a safe and environmentally friendly application of fertilizers and chemicals will be documented.

Summary: Remote sensing soil moisture research

NASA Technical Reports Server (NTRS)

Schmer, F. A.; Werner, H. D.; Waltz, F. A.

1970-01-01

During the 1969 and 1970 growing seasons research was conducted to investigate the relationship between remote sensing imagery and soil moisture. The research was accomplished under two completely different conditions: (1) cultivated cropland in east central South Dakota, and (2) rangeland in western South Dakota. Aerial and ground truth data are being studied and correlated in order to evaluate the moisture supply and water use. Results show that remote sensing is a feasible method for monitoring soil moisture.

Remote Sensing Applied to Geology (Latest Citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1996-01-01

The bibliography contains citations concerning the use of remote sensing in geological resource exploration. Technologies discussed include thermal, optical, photographic, and electronic imaging using ground-based, aerial, and satellite-borne devices. Analog and digital techniques to locate, classify, and assess geophysical features, structures, and resources are also covered. Application of remote sensing to petroleum and minerals exploration is treated in a separate bibliography. (Contains 50-250 citations and includes a subject term index and title list.)

Remote sensing for grassland management in the arid Southwest

USGS Publications Warehouse

Marsett, R.C.; Qi, J.; Heilman, P.; Biedenbender, S.H.; Watson, M.C.; Amer, S.; Weltz, M.; Goodrich, D.; Marsett, R.

2006-01-01

We surveyed a group of rangeland managers in the Southwest about vegetation monitoring needs on grassland. Based on their responses, the objective of the RANGES (Rangeland Analysis Utilizing Geospatial Information Science) project was defined to be the accurate conversion of remotely sensed data (satellite imagery) to quantitative estimates of total (green and senescent) standing cover and biomass on grasslands and semidesert grasslands. Although remote sensing has been used to estimate green vegetation cover, in arid grasslands herbaceous vegetation is senescent much of the year and is not detected by current remote sensing techniques. We developed a ground truth protocol compatible with both range management requirements and Landsat's 30 m resolution imagery. The resulting ground-truth data were then used to develop image processing algorithms that quantified total herbaceous vegetation cover, height, and biomass. Cover was calculated based on a newly developed Soil Adjusted Total Vegetation Index (SATVI), and height and biomass were estimated based on reflectance in the near infrared (NIR) band. Comparison of the remotely sensed estimates with independent ground measurements produced r2 values of 0.80, 0.85, and 0.77 and Nash Sutcliffe values of 0.78, 0.70, and 0.77 for the cover, plant height, and biomass, respectively. The approach for estimating plant height and biomass did not work for sites where forbs comprised more than 30% of total vegetative cover. The ground reconnaissance protocol and image processing techniques together offer land managers accurate and timely methods for monitoring extensive grasslands. The time-consuming requirement to collect concurrent data in the field for each image implies a need to share the high fixed costs of processing an image across multiple users to reduce the costs for individual rangeland managers.

Monitoring of "all-weather" evapotranspiration using optical and passive microwave remote sensing imagery over the River Source Region in Southwest China

NASA Astrophysics Data System (ADS)

Ma, Y.; Liu, S.

2017-12-01

Accurate estimation of surface evapotranspiration (ET) with high quality is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. However, many aspects urgently need to deeply research, such as the applicability of the ET models, the parameterization schemes optimization at the regional scale, the temporal upscaling, the selecting and developing of the spatiotemporal data fusion method and ground-based validation over heterogeneous land surfaces. This project is based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism need further investigation, including the applicability and the influencing factors, such as local environment, and heterogeneity of the landscape, for improving estimation accuracy. Due to technical and budget limitations, so far, optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions in Southwest China. Here, a multi-source remote sensing data fusion method (ESTARFM: Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) method will be proposed through blending multi-source remote sensing data acquired by optical, and passive microwave remote sensors on board polar satellite platforms. The accurate "all-weather" ET estimation will be carried out for daily ET of the River Source Region in Southwest China, and then the remotely sensed ET results are overlapped with the footprint-weighted images of EC (eddy correlation) for ground-based validation.

Remote Sensing Simulation Activities for Earthlings

ERIC Educational Resources Information Center

Krockover, Gerald H.; Odden, Thomas D.

1977-01-01

Suggested are activities using a Polaroid camera to illustrate the capabilities of remote sensing. Reading materials from the National Aeronautics and Space Administration (NASA) are suggested. Methods for (1) finding a camera's focal length, (2) calculating ground dimension photograph simulation, and (3) limiting size using film resolution are…

[Application of optical flow dynamic texture in land use/cover change detection].

PubMed

Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better performance than the post-classification change detection methods using spectral information only.

Deriving Leaf Area Index (LAI) from multiple lidar remote sensing systems

NASA Astrophysics Data System (ADS)

Tang, H.; Dubayah, R.; Zhao, F.

2012-12-01

LAI is an important biophysical variable linking biogeochemical cycles of earth systems. Observations with passive optical remote sensing are plagued by saturation and results from different passive and active sensors are often inconsistent. Recently lidar remote sensing has been applied to derive vertical canopy structure including LAI and its vertical profile. In this research we compare LAI retrievals from three different types of lidar sensors. The study areas include the La Selva Biological Station in Costa Rica and Sierra Nevada Forest in California. We first obtain independent LAI estimates from different lidar systems including airborne lidar (LVIS), spaceborne lidar (GLAS) and ground lidar (Echidna). LAI retrievals are then evaluated between sensors as a function of scale, land cover type and sensor characteristics. We also assess the accuracy of these LAI products against ground measurements. By providing a link between ground observations, ground lidar, aircraft and space-based lidar we hope to demonstrate a path for deriving more accurate estimates of LAI on a global basis, and to provide a more robust means of validating passive optical estimates of this important variable.

Assessment of remote sensing technologies to discover and characterize waste sites

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

NONE

1992-03-11

This report presents details about waste management practices that are being developed using remote sensing techniques to characterize DOE waste sites. Once the sites and problems have been located and characterized and an achievable restoration and remediation program have been established, efforts to reclaim the environment will begin. Special problems to be considered are: concentrated waste forms in tanks and pits; soil and ground water contamination; ground safety hazards for workers; and requirement for long-term monitoring.

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.

Measurement of Oil and Natural Gas Well Pad Enclosed Combustor Emissions Using Optical Remote Sensing Technologies

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA), Office of Research and Development (ORD) and EPA Region 8 are collaborating under the EPA’s Regional Applied Research Effort (RARE) program to evaluate ground-based remote sensing technologies that could be used to characterize emis...

A star-pointing UV-visible spectrometer for remote-sensing of the stratosphere

NASA Technical Reports Server (NTRS)

Roscoe, Howard K.; Freshwater, Ray A.; Jones, Rod L.; Fish, Debbie J.; Harries, John E.; Wolfenden, Roger; Stone, Phillip

1994-01-01

We have constructed a novel instrument for ground-based remote sensing, by mounting a UV-visible spectrometer on a telescope and observing the absorption by atmospheric constituents of light from stars. Potentially, the instrument can observe stratospheric O3, NO3, NO2, and OClO.

Coupling fine-scale root and canopy structure using ground-based remote sensing

Treesearch

Brady Hardiman; Christopher Gough; John Butnor; Gil Bohrer; Matteo Detto; Peter Curtis

2017-01-01

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in...

Testing an Energy Balance Model for Estimating Actual Evapotranspiration Using Remotely Sensed Data. [Hannover, West Germany barley and wheat fields

NASA Technical Reports Server (NTRS)

Gurney, R. J.; Camillo, P. J.

1985-01-01

An energy-balance model is used to estimate daily evapotranspiration for 3 days for a barley field and a wheat field near Hannover, Federal Republic of Germany. The model was calibrated using once-daily estimates of surface temperatures, which may be remotely sensed. The evaporation estimates were within the 95% error bounds of independent eddy correlation estimates for the daytime periods for all three days for both sites, but the energy-balance estimates are generally higher; it is unclear which estimate is biassed. Soil moisture in the top 2 cm of soil, which may be remotely sensed, may be used to improve these evaporation estimates under partial ground cover. Sensitivity studies indicate the amount of ground data required is not excessive.

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Physical Characteristics of Arctic Clouds from Ground-based Remote-sensing with a Polarized Micro-Pulse Lidar and a 95-GHz Cloud Radar in Ny-Ålesund, Svalbard

NASA Astrophysics Data System (ADS)

Shiobara, M.; Takano, T.; Okamoto, H.; Yabuki, M.

2015-12-01

Clouds and aerosols are key elements having a potential to change climate by their radiative effects on the energy balance in the global climate system. In the Arctic, we have been continuing ground-based remote-sensing measurements for clouds and aerosols using a sky-radiometer, a micro-pulse lidar (MPL) and an all-sky camera in Ny-Ålesund (78.9N, 11.9E), Svalbard since early 2000's. In addition to such regular operations, several new measurements have been performed with a polarization MPL since August 2013, a 95GHz Doppler cloud radar since September 2013, and a dual frequency microwave radiometer since June 2014. An intensive field experiment for cloud-aerosol-radiation interaction study named A-CARE (PI: J. Ukita) was conducted for water clouds in the period of 23 June - 13 July 2014 and for mixed phase clouds in the period of 30 March - 23 April 2015 in Ny-Alesund. The experiment consisted of ground-based remote-sensing and in-situ cloud microphysics measurements. In this paper, preliminary results from these remote-sensing measurements will be presented, particularly in regard to physical characteristics of Arctic clouds based on radar-lidar collocated observation in Ny-Ålesund.

High Data Rate Satellite Communications for Environmental Remote Sensing

NASA Astrophysics Data System (ADS)

Jackson, J. M.; Munger, J.; Emch, P. G.; Sen, B.; Gu, D.

2014-12-01

Satellite to ground communication bandwidth limitations place constraints on current earth remote sensing instruments which limit the spatial and spectral resolution of data transmitted to the ground for processing. Instruments such as VIIRS, CrIS and OMPS on the Soumi-NPP spacecraft must aggregate data both spatially and spectrally in order to fit inside current data rate constraints limiting the optimal use of the as-built sensors. Future planned missions such as HyspIRI, SLI, PACE, and NISAR will have to trade spatial and spectral resolution if increased communication band width is not made available. A number of high-impact, environmental remote sensing disciplines such as hurricane observation, mega-city air quality, wild fire detection and monitoring, and monitoring of coastal oceans would benefit dramatically from enabling the downlinking of sensor data at higher spatial and spectral resolutions. The enabling technologies of multi-Gbps Ka-Band communication, flexible high speed on-board processing, and multi-Terabit SSRs are currently available with high technological maturity enabling high data volume mission requirements to be met with minimal mission constraints while utilizing a limited set of ground sites from NASA's Near Earth Network (NEN) or TDRSS. These enabling technologies will be described in detail with emphasis on benefits to future remote sensing missions currently under consideration by government agencies.

Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

NASA Technical Reports Server (NTRS)

Mcelroy, James L. (Editor); Mcneal, Robert J. (Editor)

1991-01-01

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States

USGS Publications Warehouse

Reitz, Meredith; Senay, Gabriel; Sanford, Ward E.

2017-01-01

Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.

Polarization Remote Sensing Physical Mechanism, Key Methods and Application

NASA Astrophysics Data System (ADS)

Yang, B.; Wu, T.; Chen, W.; Li, Y.; Knjazihhin, J.; Asundi, A.; Yan, L.

2017-09-01

China's long-term planning major projects "high-resolution earth observation system" has been invested nearly 100 billion and the satellites will reach 100 to 2020. As to 2/3 of China's area covered by mountains it has a higher demand for remote sensing. In addition to light intensity, frequency, phase, polarization is also the main physical characteristics of remote sensing electromagnetic waves. Polarization is an important component of the reflected information from the surface and the atmospheric information, and the polarization effect of the ground object reflection is the basis of the observation of polarization remote sensing. Therefore, the effect of eliminating the polarization effect is very important for remote sensing applications. The main innovations of this paper is as follows: (1) Remote sensing observation method. It is theoretically deduced and verified that the polarization can weaken the light in the strong light region, and then provide the polarization effective information. In turn, the polarization in the low light region can strengthen the weak light, the same can be obtained polarization effective information. (2) Polarization effect of vegetation. By analyzing the structure characteristics of vegetation, polarization information is obtained, then the vegetation structure information directly affects the absorption of biochemical components of leaves. (3) Atmospheric polarization neutral point observation method. It is proved to be effective to achieve the ground-gas separation, which can achieve the effect of eliminating the atmospheric polarization effect and enhancing the polarization effect of the object.

Scintillometer networks for calibration and validation of energy balance and soil moisture remote sensing algorithms

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Kleissl, Jan; Gómez Vélez, Jesús D.; Hong, Sung-ho; Fábrega Duque, José R.; Vega, David; Moreno Ramírez, Hernán A.; Ogden, Fred L.

2007-04-01

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

Remote sensing the plasmasphere, plasmapause, plumes and other features using ground-based magnetometers

NASA Astrophysics Data System (ADS)

Menk, Frederick; Kale, Zoë; Sciffer, Murray; Robinson, Peter; Waters, Colin; Grew, Russell; Clilverd, Mark; Mann, Ian

2014-11-01

The plasmapause is a highly dynamic boundary between different magnetospheric particle populations and convection regimes. Some of the most important space weather processes involve wave-particle interactions in this region, but wave properties may also be used to remote sense the plasmasphere and plasmapause, contributing to plasmasphere models. This paper discusses the use of existing ground magnetometer arrays for such remote sensing. Using case studies we illustrate measurement of plasmapause location, shape and movement during storms; refilling of flux tubes within and outside the plasmasphere; storm-time increase in heavy ion concentration near the plasmapause; and detection and mapping of density irregularities near the plasmapause, including drainage plumes, biteouts and bulges. We also use a 2D MHD model of wave propagation through the magnetosphere, incorporating a realistic ionosphere boundary and Alfvén speed profile, to simulate ground array observations of power and cross-phase spectra, hence confirming the signatures of plumes and other density structures.

Natural Resource Monitoring of Rheum tanguticum by Multilevel Remote Sensing

PubMed Central

Xie, Caixiang; Song, Jingyuan; Suo, Fengmei; Li, Xiwen; Li, Ying; Yu, Hua; Xu, Xiaolan; Luo, Kun; Li, Qiushi; Xin, Tianyi; Guan, Meng; Xu, Xiuhai; Miki, Eiji; Takeda, Osami; Chen, Shilin

2014-01-01

Remote sensing has been extensively applied in agriculture for its objectiveness and promptness. However, few applications are available for monitoring natural medicinal plants. In the paper, a multilevel monitoring system, which includes satellite and aerial remote sensing, as well as ground investigation, was initially proposed to monitor natural Rheum tanguticum resource in Baihe Pasture, Zoige County, Sichuan Province. The amount of R. tanguticum from images is M = S*ρ and S is vegetation coverage obtained by satellite imaging, whereas ρ is R. tanguticum density obtained by low-altitude imaging. Only the R. tanguticum which coverages exceeded 1 m2 could be recognized from the remote sensing image because of the 0.1 m resolution of the remote sensing image (called effective resource at that moment), and the results of ground investigation represented the amounts of R. tanguticum resource in all sizes (called the future resource). The data in paper showed that the present available amount of R. tanguticum accounted for 4% to 5% of the total quantity. The quantity information and the population structure of R. tanguticum in the Baihe Pasture were initially confirmed by this system. It is feasible to monitor the quantitative distribution for natural medicinal plants with scattered distribution. PMID:25101134

Using multi-level remote sensing and ground data to estimate forest biomass resources in remote regions: a case study in the boreal forests of interior Alaska

Treesearch

Hans-Erik Andersen; Strunk Jacob; Hailemariam Temesgen; Donald Atwood; Ken Winterberger

2012-01-01

The emergence of a new generation of remote sensing and geopositioning technologies, as well as increased capabilities in image processing, computing, and inferential techniques, have enabled the development and implementation of increasingly efficient and cost-effective multilevel sampling designs for forest inventory. In this paper, we (i) describe the conceptual...

Literature review of the remote sensing of natural resources. [bibliography

NASA Technical Reports Server (NTRS)

Fears, C. B. (Editor); Inglis, M. H. (Editor)

1977-01-01

Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided.

Medium Spatial Resolution Satellite Characterization

NASA Technical Reports Server (NTRS)

Stensaas, Greg

2007-01-01

This project provides characterization and calibration of aerial and satellite systems in support of quality acquisition and understanding of remote sensing data, and verifies and validates the associated data products with respect to ground and and atmospheric truth so that accurate value-added science can be performed. The project also provides assessment of new remote sensing technologies.

EVALUATION OF A FORMER LANDFILL SITE IN FORT COLLINS, COLORADO USING GROUND-BASED OPTICAL REMOTE SENSING TECHNOLOGY

EPA Science Inventory

This report details a measurement campaign conducted using the Radial Plume Mapping (RPM) method and optical remote sensing technologies to characterize fugitive emissions. This work was funded by EPA′s Monitoring and Measurement for the 21st Century Initiative, or 21M2. The si...

The use of remote sensing in mosquito control

NASA Technical Reports Server (NTRS)

1973-01-01

The technology of remote sensing, developed by the space program for identification of surface features from the vantage point of an aircraft or satellite, has substantial application in precisely locating mosquito breeding grounds. Preliminary results of the NASA technology working cooperatively with a city government agency in solving this problem are discussed.

Remote sensing techniques in cultural resource management archaeology

NASA Astrophysics Data System (ADS)

Johnson, Jay K.; Haley, Bryan S.

2003-04-01

Cultural resource management archaeology in the United States concerns compliance with legislation set in place to protect archaeological resources from the impact of modern activities. Traditionally, surface collection, shovel testing, test excavation, and mechanical stripping are used in these projects. These methods are expensive, time consuming, and may poorly represent the features within archaeological sites. The use of remote sensing techniques in cultural resource management archaeology may provide an answer to these problems. Near-surface geophysical techniques, including magnetometry, resistivity, electromagnetics, and ground penetrating radar, have proven to be particularly successful at efficiently locating archaeological features. Research has also indicated airborne and satellite remote sensing may hold some promise in the future for large-scale archaeological survey, although this is difficult in many areas of the world where ground cover reflect archaeological features in an indirect manner. A cost simulation of a hypothetical data recovery project on a large complex site in Mississippi is presented to illustrate the potential advantages of remote sensing in a cultural resource management setting. The results indicate these techniques can save a substantial amount of time and money for these projects.

Remote sensing evaluation of the Klondike Mining District, Nevada. Part 1: Geology, photography and infrared

NASA Technical Reports Server (NTRS)

Brennan, P. A.; Chapman, P. E.; Chipp, E. R.

1971-01-01

During August of 1970 Mission 140 was flown with the NASA P3A aircraft over the Klondike Mining District, Nevada. High quality metric photography, thermal infrared imagery, multispectral photography and multichannel microwave radiometry were obtained. Geology and ground truth data are presented and relationships of the physical attributes of geologic materials to remotely sensed data is discussed. It is concluded that remote sensing data was valuable in the geologic evaluation of the Klondike Mining District and would be of value in other mining districts.

U. S. GEOLOGICAL SURVEY LAND REMOTE SENSING ACTIVITIES.

USGS Publications Warehouse

Frederick, Doyle G.

1983-01-01

USGS uses all types of remotely sensed data, in combination with other sources of data, to support geologic analyses, hydrologic assessments, land cover mapping, image mapping, and applications research. Survey scientists use all types of remotely sensed data with ground verifications and digital topographic and cartographic data. A considerable amount of research is being done by Survey scientists on developing automated geographic information systems that can handle a wide variety of digital data. The Survey is also investigating the use of microprocessor computer systems for accessing, displaying, and analyzing digital data.

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

Intercomparison of Remotely Sensed Vegetation Indices, Ground Spectroscopy, and Foliar Chemistry Data from NEON

NASA Astrophysics Data System (ADS)

Hulslander, D.; Warren, J. N.; Weintraub, S. R.

2017-12-01

Hyperspectral imaging systems can be used to produce spectral reflectance curves giving rich information about composition, relative abundances of materials, mixes and combinations. Indices based on just a few spectral bands have been used for over 40 years to study vegetation health, mineral abundance, and more. These indices are much simpler to visualize and use than a full hyperspectral data set which may contain over 400 bands. Yet historically, it has been difficult to directly relate remotely sensed spectral indices to quantitative biophysical properties significant to forest ecology such as canopy nitrogen, lignin, and chlorophyll. This linkage is a critical piece in enabling the detection of high value ecological information, usually only available from labor-intensive canopy foliar chemistry sampling, to the geographic and temporal coverage available via remote sensing. Previous studies have shown some promising results linking ground-based data and remotely sensed indices, but are consistently limited in time, geographic extent, and land cover type. Moreover, previous studies are often focused on tuning linkage algorithms for the purpose of achieving good results for only one study site or one type of vegetation, precluding development of more generalized algorithms. The National Ecological Observatory Network (NEON) is a unique system of 47 terrestrial sites covering all of the major eco-climatic domains of the US, including AK, HI, and Puerto Rico. These sites are regularly monitored and sampled using uniform instrumentation and protocols, including both foliar chemistry sampling and remote sensing flights for high resolution hyperspectral, LiDAR, and digital camera data acquisition. In this study we compare the results of foliar chemistry analysis to the remote sensing vegetation indices and investigate possible sources for variance and difference through the use of the larger hyperspectral dataset as well as ground based spectrometer measurements of samples subsequently analyzed for foliar chemistry.

AgRISTARS: Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing. Enumerator's manual, 1981 ground data survey

NASA Technical Reports Server (NTRS)

1981-01-01

General information and administrative instructions are provided for individuals gathering ground truth data to support research and development techniques for estimating crop acreage and production by remote sensing by satellite. Procedures are given for personal safety with regards to organophosphorus insecticides, for conducting interviews for periodic observations, for coding the crops identified and their growth stages, and for selecting sites for placing rain gages. Forms are included for those citizens agreeing to monitor the gages and record the rainfall. Segment selection is also considered.

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

Portable Laser Spectrometer for Airborne and Ground-Based Remote Sensing of Geological CO2 Emissions

NASA Technical Reports Server (NTRS)

Queisser, Manuel; Burton, Mike; Allan, Graham R.; Chiarugi, Antonio

2017-01-01

A 24 kilogram, suitcase-sized, CW (Continuous Wave) Laser Remote Sensing Spectrometer (LARSS) with an approximately 2-kilometer range has been developed. It has demonstrated its flexibility in measuring both atmospheric CO2 from an airborne platform and terrestrial emission of CO2 from a remote mud volcano, Bledug Kuwu, Indonesia, from a ground-based sight. This system scans the CO2 absorption line with 20 discrete wavelengths, as opposed to the typical two-wavelength online-offline instrument. This multi-wavelength approach offers an effective quality control, bias control, and confidence estimate of measured CO2 concentrations via spectral fitting. The simplicity, ruggedness, and flexibility in the design allow for easy transportation and use on different platforms with a quick setup in some of the most challenging climatic conditions. While more refinement is needed, the results represent a stepping stone towards widespread use of active one-sided gas remote sensing in the earth sciences.

Portable laser spectrometer for airborne and ground-based remote sensing of geological CO₂ emissions.

PubMed

Queisser, Manuel; Burton, Mike; Allan, Graham R; Chiarugi, Antonio

2017-07-15

A 24 kg, suitcase sized, CW laser remote sensing spectrometer (LARSS) with a ~2 km range has been developed. It has demonstrated its flexibility in measuring both atmospheric CO₂ from an airborne platform and terrestrial emission of CO₂ from a remote mud volcano, Bledug Kuwu, Indonesia, from a ground-based sight. This system scans the CO₂ absorption line with 20 discrete wavelengths, as opposed to the typical two-wavelength online offline instrument. This multi-wavelength approach offers an effective quality control, bias control, and confidence estimate of measured CO₂ concentrations via spectral fitting. The simplicity, ruggedness, and flexibility in the design allow for easy transportation and use on different platforms with a quick setup in some of the most challenging climatic conditions. While more refinement is needed, the results represent a stepping stone towards widespread use of active one-sided gas remote sensing in the earth sciences.

Study of Diagenetic Features in Rudist Buildups of Cretaceous Edwards Formation Using Ground Based Hyperspectral Scanning and Terrestrial LiDAR

NASA Astrophysics Data System (ADS)

Krupnik, D.; Khan, S.; Okyay, U.; Hartzell, P. J.; Biber, K.

2015-12-01

Ground based remote sensing is a novel technique for development of digital outcrop models which can be instrumental in performing detailed qualitative and quantitative sedimentological analysis for the study of depositional environment, diagenetic processes, and hydrocarbon reservoir characterization. For this investigation, ground-based hyperspectral data collection is combined with terrestrial LiDAR to study outcrops of Late Albian rudist buildups of the Edwards formation in the Lake Georgetown Spillway in Williamson County, Texas. The Edwards formation consists of shallow water deposits of reef and associated inter-reef facies, including rudist bioherms and biostromes. It is a significant aquifer and was investigated as a hydrocarbon play in south central Texas. Hyperspectral data were used to map compositional variation in the outcrop by distinguishing spectral properties unique to each material. Lithological variation was mapped in detail to investigate the structure and composition of rudist buildups. Hyperspectral imagery was registered to a 3D model produced from the LiDAR point cloud with an accuracy of up to one pixel. Flat-topped toucasid-rich bioherm facies were distinguished from overlying toucasid-rich biostrome facies containing chert nodules, overlying sucrosic dolostones, and uppermost peloid wackestones and packstones of back-reef facies. Ground truth was established by petrographic study of samples from this area and has validated classification products of remote sensing data. Several types of porosity were observed and have been associated with increased dolomitization. This ongoing research involves integration of remotely sensed datasets to analyze geometrical and compositional properties of this carbonate formation at a finer scale than traditional methods have achieved and seeks to develop a workflow for quick and efficient ground based remote sensing-assisted outcrop studies.

What is a picture worth? A history of remote sensing

USGS Publications Warehouse

Moore, Gerald K.

1979-01-01

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.

A comparison between evapotranspiration estimates based on remotely sensed surface energy balance and ground-based soil water balance analyses

USDA-ARS?s Scientific Manuscript database

Remotely sensed and in-situ data were used to investigate dynamics of root zone soil moisture and evapotranspiration (ET) at four Mesonet stations in north-central Oklahoma over an 11-year period (2000-2010). Two moisture deficit indicators based on soil matric potential had spatial and temporal pat...

EVALUATION OF FUGITIVE EMISSIONS AT A FORMER LANDFILL SITE IN COLORADO SPRINGS, COLORADO, USING GROUND-BASED OPTICAL REMOTE SENSING TECHNOLOGY

EPA Science Inventory

This report details a measurement campaign conducted using the Radial Plume Mapping (RPM) method and optical remote sensing technologies to characterize fugitive emissions. This work was funded by EPAs Monitoring and Measurement for the 21st Century Initiative, or 21M2. The si...

Ground zero and up; Nebraska's resources and land use. [using LANDSAT and Skylab data

NASA Technical Reports Server (NTRS)

Edwards, D. M.; Macklem, R.

1975-01-01

A one-semester high school course was developed about the use of remote sensing techniques for land earth resources planning and management. The slide-tape-workbook program was field tested with high school students to show a substantial increase in gain of knowledge and an attitude change in application of remote sensing techniques.

Lidar remote sensing of above-ground biomass in three biomes.

Treesearch

Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas Gower

2002-01-01

Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

Remote Sensing of Water Pollution

NASA Technical Reports Server (NTRS)

White, P. G.

1971-01-01

Remote sensing, as a tool to aid in the control of water pollution, offers a means of making rapid, economical surveys of areas that are relatively inaccessible on the ground. At the same time, it offers the only practical means of mapping pollution patterns that cover large areas. Detection of oil slicks, thermal pollution, sewage, and algae are discussed.

Remote Sensing of Vegetation Recovery from Disturbance in Drylands

NASA Astrophysics Data System (ADS)

Poitras, T. B.; Villarreal, M. L.; Waller, E.; Duniway, M.; Nauman, T.

2016-12-01

Characteristics of dryland ecosystems such as climatic extremes and water limitations render semi-arid regions vulnerable to disturbance and slow to recover. Land surface monitoring over time through the use of remote sensing may have potential for identifying dryland ecosystem recovery after anthropogenic and natural disturbance. However, semi-arid vegetation cover is challenging to measure using remote sensing techniques due to low vegetation cover and confusion between bright and variable soils and non-photosynthetic vegetation (NPV). We therefore evaluated the ability of various multispectral indices to distinguish bare ground from total vegetation cover, in order to determine those that can detect changes over time in heavily disturbed sites. We calculated nine spectral indices from Landsat TM using Google Earth Engine (March through October, 2006 through 2008) and tested relationships between index values and ground measurements from long-term monitoring data collected in and around Canyonlands National Park in Utah. We also tested multivariate models, with some showing improvement under cross-validation. We found that indices that included shortwave infrared bands and soil brightness were important for capturing gradients in bare ground, and vegetation cover was best quantified with near-infrared bands. These results will be used to help assess the landscape-scale impacts of oil and gas development in dryland ecosystems and to measure response to restoration efforts. Keywords: remote sensing, landsat, drylands

Application of Remote Sensing in Building Damages Assessment after Moderate and Strong Earthquake

NASA Astrophysics Data System (ADS)

Tian, Y.; Zhang, J.; Dou, A.

2003-04-01

- Earthquake is a main natural disaster in modern society. However, we still cannot predict the time and place of its occurrence accurately. Then it is of much importance to survey the damages information when an earthquake occurs, which can help us to mitigate losses and implement fast damage evaluation. In this paper, we use remote sensing techniques for our purposes. Remotely sensed satellite images often view a large scale of land at a time. There are several kinds of satellite images, which of different spatial and spectral resolutions. Landsat-4/5 TM sensor can view ground at 30m resolution, while Landsat-7 ETM Plus has a resolution of 15m in panchromatic waveband. SPOT satellite can provide images with higher resolutions. Those images obtained pre- and post-earthquake can help us greatly in identifying damages of moderate and large-size buildings. In this paper, we bring forward a method to implement quick damages assessment by analyzing both pre- and post-earthquake satellite images. First, those images are geographically registered together with low RMS (Root Mean Square) error. Then, we clip out residential areas by overlaying images with existing vector layers through Geographic Information System (GIS) software. We present a new change detection algorithm to quantitatively identify damages degree. An empirical or semi-empirical model is then established by analyzing the real damage degree and changes of pixel values of the same ground objects. Experimental result shows that there is a good linear relationship between changes of pixel values and ground damages, which proves the potentials of remote sensing in post-quake fast damage assessment. Keywords: Damages Assessment, Earthquake Hazard, Remote Sensing

Ground-based Remote Sensing for Quantifying Subsurface and Surface Co-variability to Scale Arctic Ecosystem Functioning

NASA Astrophysics Data System (ADS)

Oktem, R.; Wainwright, H. M.; Curtis, J. B.; Dafflon, B.; Peterson, J.; Ulrich, C.; Hubbard, S. S.; Torn, M. S.

2016-12-01

Predicting carbon cycling in Arctic requires quantifying tightly coupled surface and subsurface processes including permafrost, hydrology, vegetation and soil biogeochemistry. The challenge has been a lack of means to remotely sense key ecosystem properties in high resolution and over large areas. A particular challenge has been characterizing soil properties that are known to be highly heterogeneous. In this study, we exploit tightly-coupled above/belowground ecosystem functioning (e.g., the correlations among soil moisture, vegetation and carbon fluxes) to estimate subsurface and other key properties over large areas. To test this concept, we have installed a ground-based remote sensing platform - a track-mounted tram system - along a 70 m transect in the ice-wedge polygonal tundra near Barrow, Alaska. The tram carries a suite of near-surface remote sensing sensors, including sonic depth, thermal IR, NDVI and multispectral sensors. Joint analysis with multiple ground-based measurements (soil temperature, active layer soil moisture, and carbon fluxes) was performed to quantify correlations and the dynamics of above/belowground processes at unprecedented resolution, both temporally and spatially. We analyzed the datasets with particular focus on correlating key subsurface and ecosystem properties with surface properties that can be measured by satellite/airborne remote sensing over a large area. Our results provided several new insights about system behavior and also opens the door for new characterization approaches. We documented that: (1) soil temperature (at >5 cm depth; critical for permafrost thaw) was decoupled from soil surface temperature and was influenced strongly by soil moisture, (2) NDVI and greenness index were highly correlated with both soil moisture and gross primary productivity (based on chamber flux data), and (3) surface deformation (which can be measured by InSAR) was a good proxy for thaw depth dynamics at non-inundated locations.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

Air pollution linked to Remote Sensing tools - Science training using a Master's Level e-Learning Tool

NASA Astrophysics Data System (ADS)

Ladstaetter-Weissenmayer, A.; Kanakidou, M.; Richter, A.; Wagner, T.; Borrell, P.; Law, R. J.; Burrows, J. P.

2009-09-01

As we know it today air pollution is a release into the atmosphere of any substances, chemicals or particles, which are harmful both to the human and animal health as well as the health of the wider environment. The use of satellite based instruments is a young and developing research field and excellent for studying air pollution events over large areas at high spatial-temporal resolutions, especially when ground measurements, which are limited in spatial-temporal coverage, are not available. Students on postgraduate level should be trained in using, and analysing remote sensing data from both ground and satellite based or in interpreting the high variety in remote sensing e.g satellite images or maps. As follows an e-learning online module has been devised and constructed to facilitate the teaching of Remote Sensing of Troposphere from Space to research students at a Master's level. The module, which is essentially an interactive on-line text book, is stand alone, although it could be encompassed within a standard course management system. The scientific content is presented as study pages under three headings: remote sensing from space, the basics of radiation transfer, and retrieval procedures for tropospheric satellite data.The student is encouraged to test his or her comprehension of the material through exercises on the scientific topics.

Air pollution linked to Remote Sensing tools - Science training using a Master's Level e-Learning Tool

NASA Astrophysics Data System (ADS)

Ladstätter-Weißenmayer, A.; Kanakidou, M.; Richter, A.; Wagner, T.; Borrell, P.; Law, R. J.; Burrows, J. P.

2009-04-01

As we know it today air pollution is a release into the atmosphere of any substances, chemicals or particles, which are harmful both to the human and animal health as well as the health of the wider environment. The use of satellite based instruments is a young and developing research field and excellent for studying air pollution events over large areas at high spatial-temporal resolutions, especially when ground measurements, which are limited in spatial-temporal coverage, are not available. Students on postgraduate level should be trained in using, and analysing remote sensing data from both ground and satellite based or in interpreting the high variety in remote sensing e.g satellite images or maps. As follows an e-learning online module has been devised and constructed to facilitate the teaching of Remote Sensing of Troposphere from Space to research students at a Master's level. The module, which is essentially an interactive on-line text book, is stand alone, although it could be encompassed within a standard course management system. The scientific content is presented as study pages under three headings: remote sensing from space, the basics of radiation transfer, and retrieval procedures for tropospheric satellite data.The student is encouraged to test his or her comprehension of the material through exercises on the scientific topics.

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

USGS Publications Warehouse

Vierling, L.A.; Fersdahl, M.; Chen, X.; Li, Z.; Zimmerman, P.

2006-01-01

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Multi-source and multi-angle remote sensing image data collection, application and sharing of Beichuan National Earthquake Ruins Museum

NASA Astrophysics Data System (ADS)

Lin, Yueguan; Wang, Wei; Wen, Qi; Huang, He; Lin, Jingli; Zhang, Wei

2015-12-01

Ms8.0 Wenchuan earthquake that occurred on May 12, 2008 brought huge casualties and property losses to the Chinese people, and Beichuan County was destroyed in the earthquake. In order to leave a site for commemorate of the people, and for science propaganda and research of earthquake science, Beichuan National Earthquake Ruins Museum has been built on the ruins of Beichuan county. Based on the demand for digital preservation of the earthquake ruins park and collection of earthquake damage assessment of research and data needs, we set up a data set of Beichuan National Earthquake Ruins Museum, including satellite remote sensing image, airborne remote sensing image, ground photogrammetry data and ground acquisition data. At the same time, in order to make a better service for earthquake science research, we design the sharing ideas and schemes for this scientific data set.

Monitoring water quality by remote sensing

NASA Technical Reports Server (NTRS)

Brown, R. L. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A limited study was conducted to determine the applicability of remote sensing for evaluating water quality conditions in the San Francisco Bay and delta. Considerable supporting data were available for the study area from other than overflight sources, but short-term temporal and spatial variability precluded their use. The study results were not sufficient to shed much light on the subject, but it did appear that, with the present state of the art in image analysis and the large amount of ground truth needed, remote sensing has only limited application in monitoring water quality.

Overview of Ground Air Quality Measurements and Their Links to Airborne, Remote Sensing and Model Studies during the KORUS-AQ Campaign

NASA Astrophysics Data System (ADS)

Lee, G.; Ahn, J. Y.; Chang, L. S.; Kim, J.; Park, R.

2017-12-01

During the KORUS-AQ, extensive sets of chemical measurements for reactive gases and aerosol species were made at 3 major sites on upwind island (Baengyeong Island), urban (Olympic Park in Seoul) and downwind rural forest location (Taewha Forest). Also, intensive aerosol size and composition observations from 5 NIER super sites, 3 NIMR monitoring sites, and 5 other university sites were currently facilitated in the KORUS-AQ data set. In addition, air quality criteria species data from 264 nation-wide ground monitoring sites with 5 minute temporal resolution during the whole campaign period were supplemented to cover mostly in densely populated urban areas, but sparsely in rural areas. The specific objectives of these ground sites were to provide highly comprehensive data set to coordinate the close collaborations among other research platforms including airborne measurements, remote sensing, and model studies. The continuous measurements at ground sites were well compared with repetitive low-level aircraft observations of NASA's DC-8 over Olympic Park and Taewha Forest site. Similarly, many ground measurements enabled the validation of chemical transport models and the remote sensing observations from ground and NASA's King Air. The observed results from inter-comparison studies in many reactive gases and aerosol compositions between different measurement methods and platforms will be presented. Compiling data sets from ground sites, source-wise analysis for ozone and aerosol, their in-situ formations, and transport characteristics by local/regional circulation will be discussed, too.

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

NASA Technical Reports Server (NTRS)

2002-01-01

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Proceedings of the 8th International Symposium on Remote Sensing of Environment, volume 1

NASA Technical Reports Server (NTRS)

Cook, J. J.

1972-01-01

These Proceedings contain papers presented at the Eighth International Symposium on Remote Sensing of Environment, held October 2nd through 6th, 1972, on the campus of the University of Michigan. The symposium was conducted by the Center for Remote Sensing Information and Analysis of the Environmental Research Institute of Michigan (formerly the University of Michigan's Willow Run Laboratories) as a part of a continuing program investigating current activities in the field of remote sensing. Presentations include those on the use of this technology by regional governmental units and by federal governmental agencies, as well as various applications in monitoring and managing the earth's resources and man's global environment. Ground-based, airborne, and spaceborne sensor systems and manual and machine-assisted data analysis and interpretation are included.

Overall design of imaging spectrometer on-board light aircraft

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

Zhongqi, H.; Zhengkui, C.; Changhua, C.

1996-11-01

Aerial remote sensing is the earliest remote sensing technical system and has gotten rapid development in recent years. The development of aerial remote sensing was dominated by high to medium altitude platform in the past, and now it is characterized by the diversity platform including planes of high-medium-low flying altitude, helicopter, airship, remotely controlled airplane, glider, and balloon. The widely used and rapidly developed platform recently is light aircraft. Early in the close of 1970s, Beijing Research Institute of Uranium Geology began aerial photography and geophysical survey using light aircraft, and put forward the overall design scheme of light aircraftmore » imaging spectral application system (LAISAS) in 19905. LAISAS is comprised of four subsystem. They are called measuring platform, data acquiring subsystem, ground testing and data processing subsystem respectively. The principal instruments of LAISAS include measuring platform controlled by inertia gyroscope, aerial spectrometer with high spectral resolution, imaging spectrometer, 3-channel scanner, 128-channel imaging spectrometer, GPS, illuminance-meter, and devices for atmospheric parameters measuring, ground testing, data correction and processing. LAISAS has the features of integrity from data acquisition to data processing and to application; of stability which guarantees the image quality and is comprised of measuring, ground testing device, and in-door data correction system; of exemplariness of integrated the technology of GIS, GPS, and Image Processing System; of practicality which embodied LAISAS with flexibility and high ratio of performance to cost. So, it can be used in the fields of fundamental research of Remote Sensing and large-scale mapping for resource exploration, environmental monitoring, calamity prediction, and military purpose.« less

The Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX): a multidisciplinary project to develop a robust remote sensing-based ET modeling tool for vineyards

USDA-ARS?s Scientific Manuscript database

The recent drought in much of California, particularly in the Central Valley region, has caused severe reduction in water reservoir levels and a major depletion of ground water by agriculture. Dramatic improvements in water and irrigation management practices are critical for agriculture to remain s...

Utility of remotely sensed imagery for assessing the impact of salvage logging after forest fires

Treesearch

Sarah A. Lewis; Peter R. Robichaud; Andrew T. Hudak; Brian Austin; Robert J. Liebermann

2012-01-01

Remotely sensed imagery provides a useful tool for land managers to assess the extent and severity of post-wildfire salvage logging disturbance. This investigation uses high resolution QuickBird and National Agricultural Imagery Program (NAIP) imagery to map soil exposure after ground-based salvage operations. Three wildfires with varying post-fire salvage activities...

Use of Landsat and environmental satellite data in evapotranspiration estimation from a wildland area

NASA Technical Reports Server (NTRS)

Khorram, S.; Smith, H. G.

1979-01-01

A remote sensing-aided procedure was applied to the watershed-wide estimation of water loss to the atmosphere (evapotranspiration, ET). The approach involved a spatially referenced databank based on both remotely sensed and ground-acquired information. Physical models for both estimation of ET and quantification of input parameters are specified, and results of the investigation are outlined.

Integration of remote sensing and hydrologic modeling through multi-disciplinary semiarid field campaigns: Moonsoon 1990, Walnut Gulch 1992, and SALSA-MEX

NASA Technical Reports Server (NTRS)

Moran, M. S.; Goodrich, D. C.; Kustas, W. P.

1994-01-01

A research and modeling strategy is presented for development of distributed hydrologic models given by a combination of remotely sensed and ground based data. In support of this strategy, two experiments Moonsoon'90 and Walnut Gulch'92 were conducted in a semiarid rangeland southeast of Tucson, Arizona, (U.S.) and a third experiment, the SALSA-MEX (Semi Arid Land Surface Atmospheric Mountain Experiment) was proposed. Results from the Moonsoon'90 experiment substantially advanced the understanding of the hydrologic and atmospheric fluxes in an arid environment and provided insight into the use of remote sensing data for hydrologic modeling. The Walnut Gulch'92 experiment addressed the seasonal hydrologic dynamics of the region and the potential of combined optical microwave remote sensing for hydrologic applications. SALSA-MEX will combine measurements and modeling to study hydrologic processes influenced by surrounding mountains, such as enhanced precipitation, snowmelt and recharge to ground water aquifers. The results from these experiments, along with the extensive experimental data bases, should aid the research community in large scale modeling of mass and energy exchanges across the soil-plant-atmosphere interface.

NASA Remote Sensing Research as Applied to Archaeology

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Thomas, Michael R.

2002-01-01

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

Ground Truth Sampling and LANDSAT Accuracy Assessment

NASA Technical Reports Server (NTRS)

Robinson, J. W.; Gunther, F. J.; Campbell, W. J.

1982-01-01

It is noted that the key factor in any accuracy assessment of remote sensing data is the method used for determining the ground truth, independent of the remote sensing data itself. The sampling and accuracy procedures developed for nuclear power plant siting study are described. The purpose of the sampling procedure was to provide data for developing supervised classifications for two study sites and for assessing the accuracy of that and the other procedures used. The purpose of the accuracy assessment was to allow the comparison of the cost and accuracy of various classification procedures as applied to various data types.

Earth science research

NASA Technical Reports Server (NTRS)

Botkin, Daniel B.

1987-01-01

The analysis of ground-truth data from the boreal forest plots in the Superior National Forest, Minnesota, was completed. Development of statistical methods was completed for dimension analysis (equations to estimate the biomass of trees from measurements of diameter and height). The dimension-analysis equations were applied to the data obtained from ground-truth plots, to estimate the biomass. Classification and analyses of remote sensing images of the Superior National Forest were done as a test of the technique to determine forest biomass and ecological state by remote sensing. Data was archived on diskette and tape and transferred to UCSB to be used in subsequent research.

Public health applications of remote sensing of vector borne and parasitic diseases

NASA Technical Reports Server (NTRS)

1976-01-01

Results of an investigation of the potential application of remote sensing to various fields of public health are presented. Specific topics discussed include: detection of snail habitats in connection with the epidemiology of schistosomiasis; the detection of certain Anopheles breeding sites, and location of transient human populations, both in connection with malaria eradication programs; and detection of overwintering population sites for the primary screwworm (Cochliomyia americana). Emphasis was placed on the determination of ground truth data on the biological, chemical, and physical characteristics of ground waters which would or would not support the growth of significant populations of mosquitoes.

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.

Applications of thermal remote sensing to detailed ground water studies

NASA Technical Reports Server (NTRS)

Souto-Maior, J.

1973-01-01

Three possible applications of thermal (8-14 microns) remote sensing to detailed hydrogeologic studies are discussed in this paper: (1) the direct detection of seeps and springs, (2) the indirect evaluation of shallow ground water flow through its thermal effects on the land surface, and (3) the indirect location of small volumes of ground water inflow into surface water bodies. An investigation carried out with this purpose in an area containing a complex shallow ground water flow system indicates that the interpretation of the thermal imageries is complicated by many factors, among which the most important are: (1) altitude, angle of view, and thermal-spatial resolution of the sensor; (2) vegetation type, density, and vigor; (3) topography; (4) climatological and micrometeorological effects; (5) variation in soil type and soil moisture; (6) variation in volume and temperature of ground water inflow; (7) the hydraulic characteristics of the receiving water body, and (8) the presence of decaying organic material.

Quantifying biological integrity of California sage scrub communities using plant life-form cover.

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

Hamada, Y.; Stow, D. A.; Franklin, J.

2010-01-01

The California sage scrub (CSS) community type in California's Mediterranean-type ecosystems supports a large number of rare, threatened, and endangered species, and is critically degraded and endangered. Monitoring ecological variables that provide information about community integrity is vital to conserving these biologically diverse communities. Fractional cover of true shrub, subshrub, herbaceous vegetation, and bare ground should fill information gaps between generalized vegetation type maps and detailed field-based plot measurements of species composition and provide an effective means for quantifying CSS community integrity. Remote sensing is the only tool available for estimating spatially comprehensive fractional cover over large extent, and fractionalmore » cover of plant life-form types is one of the measures of vegetation state that is most amenable to remote sensing. The use of remote sensing does not eliminate the need for either field surveying or vegetation type mapping; rather it will likely require a combination of approaches to reliably estimate life-form cover and to provide comprehensive information for communities. According to our review and synthesis, life-form fractional cover has strong potential for providing ecologically meaningful intermediate-scale information, which is unattainable from vegetation type maps and species-level field measurements. Thus, we strongly recommend incorporating fractional cover of true shrub, subshrub, herb, and bare ground in CSS community monitoring methods. Estimating life-form cover at a 25 m x 25 m spatial scale using remote sensing would be an appropriate approach for initial implementation. Investigation of remote sensing techniques and an appropriate spatial scale; collaboration of resource managers, biologists, and remote sensing specialists, and refinement of protocols are essential for integrating life-form fractional cover mapping into strategies for sustainable long-term CSS community management.« less

Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

NASA Astrophysics Data System (ADS)

Schneider, M.; Barthlott, S.; Hase, F.; González, Y.; Yoshimura, K.; García, O. E.; Sepúlveda, E.; Gomez-Pelaez, A.; Gisi, M.; Kohlhepp, R.; Dohe, S.; Blumenstock, T.; Wiegele, A.; Christner, E.; Strong, K.; Weaver, D.; Palm, M.; Deutscher, N. M.; Warneke, T.; Notholt, J.; Lejeune, B.; Demoulin, P.; Jones, N.; Griffith, D. W. T.; Smale, D.; Robinson, J.

2012-12-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

NASA Astrophysics Data System (ADS)

Schneider, M.; Barthlott, S.; Hase, F.; González, Y.; Yoshimura, K.; García, O. E.; Sepúlveda, E.; Gomez-Pelaez, A.; Gisi, M.; Kohlhepp, R.; Dohe, S.; Blumenstock, T.; Strong, K.; Weaver, D.; Palm, M.; Deutscher, N. M.; Warneke, T.; Notholt, J.; Lejeune, B.; Demoulin, P.; Jones, N.; Griffith, D. W. T.; Smale, D.; Robinson, J.

2012-08-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologues data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and interferences from humidity are the leading error sources. We introduce an a posteriori correction method of the humidity interference error and we recommend applying it for isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

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

Polarimetric Remote Sensing of Atmospheric Particulate Pollutants

NASA Astrophysics Data System (ADS)

Li, Z.; Zhang, Y.; Hong, J.

2018-04-01

Atmospheric particulate pollutants not only reduce atmospheric visibility, change the energy balance of the troposphere, but also affect human and vegetation health. For monitoring the particulate pollutants, we establish and develop a series of inversion algorithms based on polarimetric remote sensing technology which has unique advantages in dealing with atmospheric particulates. A solution is pointed out to estimate the near surface PM2.5 mass concentrations from full remote sensing measurements including polarimetric, active and infrared remote sensing technologies. It is found that the mean relative error of PM2.5 retrieved by full remote sensing measurements is 35.5 % in the case of October 5th 2013, improved to a certain degree compared to previous studies. A systematic comparison with the ground-based observations further indicates the effectiveness of the inversion algorithm and reliability of results. A new generation of polarized sensors (DPC and PCF), whose observation can support these algorithms, will be onboard GF series satellites and launched by China in the near future.

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

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data

NASA Astrophysics Data System (ADS)

Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H.

2018-04-01

Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

[Review of digital ground object spectral library].

PubMed

Zhou, Xiao-Hu; Zhou, Ding-Wu

2009-06-01

A higher spectral resolution is the main direction of developing remote sensing technology, and it is quite important to set up the digital ground object reflectance spectral database library, one of fundamental research fields in remote sensing application. Remote sensing application has been increasingly relying on ground object spectral characteristics, and quantitative analysis has been developed to a new stage. The present article summarized and systematically introduced the research status quo and development trend of digital ground object reflectance spectral libraries at home and in the world in recent years. Introducing the spectral libraries has been established, including desertification spectral database library, plants spectral database library, geological spectral database library, soil spectral database library, minerals spectral database library, cloud spectral database library, snow spectral database library, the atmosphere spectral database library, rocks spectral database library, water spectral database library, meteorites spectral database library, moon rock spectral database library, and man-made materials spectral database library, mixture spectral database library, volatile compounds spectral database library, and liquids spectral database library. In the process of establishing spectral database libraries, there have been some problems, such as the lack of uniform national spectral database standard and uniform standards for the ground object features as well as the comparability between different databases. In addition, data sharing mechanism can not be carried out, etc. This article also put forward some suggestions on those problems.

Cloud Optical Depth Measured with Ground-Based, Uncooled Infrared Imagers

NASA Technical Reports Server (NTRS)

Shaw, Joseph A.; Nugent, Paul W.; Pust, Nathan J.; Redman, Brian J.; Piazzolla, Sabino

2012-01-01

Recent advances in uncooled, low-cost, long-wave infrared imagers provide excellent opportunities for remotely deployed ground-based remote sensing systems. However, the use of these imagers in demanding atmospheric sensing applications requires that careful attention be paid to characterizing and calibrating the system. We have developed and are using several versions of the ground-based "Infrared Cloud Imager (ICI)" instrument to measure spatial and temporal statistics of clouds and cloud optical depth or attenuation for both climate research and Earth-space optical communications path characterization. In this paper we summarize the ICI instruments and calibration methodology, then show ICI-derived cloud optical depths that are validated using a dual-polarization cloud lidar system for thin clouds (optical depth of approximately 4 or less).

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-04-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in-situ datasets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing dataset is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, mid-latitudes, and arctic) and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier-Transform InfraRed) remote sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study is both, a theoretical and an empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR data

NASA Astrophysics Data System (ADS)

Wiegele, A.; Schneider, M.; Hase, F.; Barthlott, S.; García, O. E.; Sepúlveda, E.; González, Y.; Blumenstock, T.; Raffalski, U.; Gisi, M.; Kohlhepp, R.

2014-08-01

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote-sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

Onboard utilization of ground control points for image correction. Volume 2: Analysis and simulation results

NASA Technical Reports Server (NTRS)

1981-01-01

An approach to remote sensing that meets future mission requirements was investigated. The deterministic acquisition of data and the rapid correction of data for radiometric effects and image distortions are the most critical limitations of remote sensing. The following topics are discussed: onboard image correction systems, GCP navigation system simulation, GCP analysis, and image correction analysis measurement.

Remote sensing of selective logging in Amazonia Assessing limitations based on detailed field observations, Landsat ETM+, and textural analysis.

Treesearch

Gregory P. Asner; Michael Keller; Rodrigo Pereira; Johan C. Zweede

2002-01-01

We combined a detailed field study of forest canopy damage with calibrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) reflectance data and texture analysis to assess the sensitivity of basic broadband optical remote sensing to selective logging in Amazonia. Our field study encompassed measurements of ground damage and canopy gap fractions along a chronosequence of...

A remote-sensing, GIS-based approach to identify, characterize, and model spawning habitat for fall-run chum salmon in a sub-arctic, glacially fed river

USGS Publications Warehouse

Wirth, Lisa; Rosenberger, Amanda; Prakash, Anupma; Gens, Rudiger; Margraf, F. Joseph; Hamazaki, Toshihide

2012-01-01

At northern limits of a species’ distribution, fish habitat requirements are often linked to thermal preferences, and the presence of overwintering habitat. However, logistical challenges and hydrologic processes typical of glacial systems could compromize the identification of these habitats, particularly in large river environments. Our goal was to identify and characterize spawning habitat for fall-run chum salmon Oncorhynchus keta and model habitat selection from spatial distributions of tagged individuals in the Tanana River, Alaska using an approach that combined ground surveys with remote sensing. Models included braiding, sinuosity, ice-free water surface area (indicating groundwater influence), and persistent ice-free water (i.e., consistent presence of ice-free water for a 12-year period according to satellite imagery). Candidate models containing persistent ice-free water were selected as most likely, highlighting the utility of remote sensing for monitoring and identifying salmon habitat in remote areas. A combination of ground and remote surveys revealed spatial and temporal thermal characteristics of these habitats that could have strong biological implications. Persistent ice-free sites identified using synthetic aperture radar appear to serve as core areas for spawning fall chum salmon, and the importance of stability through time suggests a legacy of successful reproductive effort for this homing species. These features would not be captured with a one-visit traditional survey but rather required remote-sensing monitoring of the sites through time.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

Characterization of air pollution in Mexico City by remote sensing

NASA Astrophysics Data System (ADS)

Grutter, Michel; Arellano, Josue; Bezanilla, Alejandro; Friedrich, Martina; Plaza, Eddy; Rivera, Claudia; Stremme, Wolfgang

2014-05-01

Megacities, like the Mexico City Metropolitan Area, are home to a large fraction of the population of the world and a consequence is that they are one of the biggest sources of contaminants and greenhouse gases emitted to the atmosphere. The pollution is visible form space through remote sensing instruments, however, satellite observations like those with NADIR viewing geometries have decreased sensitivity near the Earth's surface and the analytical algorithms are in generally optimized to detect pollution plumes in the free troposphere or above. Ground-based observations are thus necessary in order to reduce uncertainties from satellite products. As we will show, Mexico City and its surroundings is well characterized by ground-based remote sensing measurements like from two stations with solar-absorption FTIR spectrometers and a newly formed network of MAX-DOAS and LIDAR instruments. Examples will be provided of how the evolution of the mixing-layer height is characterized and the vertical column densities and profiles of gases in and outside the urban area are continuously monitored. The combination of ground-based and space-borne measurements are used to improve the current knowledge in the spatial and temporal distribution of key pollutants from this megacity.

Ground observations and remote sensing data for integrated modelisation of water budget in the Merguellil catchment, Tunisia

NASA Astrophysics Data System (ADS)

Mougenot, Bernard

2016-04-01

The Mediterranean region is affected by water scarcity. Some countries as Tunisia reached the limit of 550 m3/year/capita due overexploitation of low water resources for irrigation, domestic uses and industry. A lot of programs aim to evaluate strategies to improve water consumption at regional level. In central Tunisia, on the Merguellil catchment, we develop integrated water resources modelisations based on social investigations, ground observations and remote sensing data. The main objective is to close the water budget at regional level and to estimate irrigation and water pumping to test scenarios with endusers. Our works benefit from French, bilateral and European projects (ANR, MISTRALS/SICMed, FP6, FP7…), GMES/GEOLAND-ESA) and also network projects as JECAM and AERONET, where the Merguellil site is a reference. This site has specific characteristics associating irrigated and rainfed crops mixing cereals, market gardening and orchards and will be proposed as a new environmental observing system connected to the OMERE, TENSIFT and OSR systems respectively in Tunisia, Morocco and France. We show here an original and large set of ground and remote sensing data mainly acquired from 2008 to present to be used for calibration/validation of water budget processes and integrated models for present and scenarios: - Ground data: meteorological stations, water budget at local scale: fluxes tower, soil fluxes, soil and surface temperature, soil moisture, drainage, flow, water level in lakes, aquifer, vegetation parameters on selected fieds/month (LAI, height, biomass, yield), land cover: 3 times/year, bare soil roughness, irrigation and pumping estimations, soil texture. - Remote sensing data: remote sensing products from multi-platform (MODIS, SPOT, LANDSAT, ASTER, PLEIADES, ASAR, COSMO-SkyMed, TerraSAR X…), multi-wavelength (solar, micro-wave and thermal) and multi-resolution (0.5 meters to 1 km). Ground observations are used (1) to calibrate soil-vegetation-atmosphere models at field scale on different compartment and irrigated and rainfed land during a limited time (seasons or set of dry and wet years), (2) to calibrate and validate particularly evapotranspiration derived from multi-wavelength satellite data at watershed level in relationships with the aquifer conditions: pumping and recharge rate. We will point out some examples.

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the image-processing based evaluation of the acquired images to characterize spatial and temporal details of landslide behaviour. We will also sketch first schemes of joint interpretation or 'data fusion' of UAV-based remote sensing with the results from geophysical mapping of underground distribution of soil moisture and fracture processes (Walter & Joswig, EGU 2009).

A new approach for automatic matching of ground control points in urban areas from heterogeneous images

NASA Astrophysics Data System (ADS)

Cong, Chao; Liu, Dingsheng; Zhao, Lingjun

2008-12-01

This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie point pairs according to geographic characters from such heterogeneous images. Since there are big differences between such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.

Radiative transfer model for aerosols in infrared wavelengths for passive remote sensing applications.

PubMed

Ben-David, Avishai; Embury, Janon F; Davidson, Charles E

2006-09-10

A comprehensive analytical radiative transfer model for isothermal aerosols and vapors for passive infrared remote sensing applications (ground-based and airborne sensors) has been developed. The theoretical model illustrates the qualitative difference between an aerosol cloud and a chemical vapor cloud. The model is based on two and two/four stream approximations and includes thermal emission-absorption by the aerosols; scattering of diffused sky radiances incident from all sides on the aerosols (downwelling, upwelling, left, and right); and scattering of aerosol thermal emission. The model uses moderate resolution transmittance ambient atmospheric radiances as boundary conditions and provides analytical expressions for the information on the aerosol cloud that is contained in remote sensing measurements by using thermal contrasts between the aerosols and diffused sky radiances. Simulated measurements of a ground-based sensor viewing Bacillus subtilis var. niger bioaerosols and kaolin aerosols are given and discussed to illustrate the differences between a vapor-only model (i.e., only emission-absorption effects) and a complete model that adds aerosol scattering effects.

Remote distinction of a noxious weed (musk thistle: Carduus nutans) using airborne hyperspectral imagery and the support vector machine classifier

USDA-ARS?s Scientific Manuscript database

Remote detection of invasive plant species using geospatial imagery may significantly improve monitoring, planning, and management practices by eliminating shortfalls such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion ex...

A Comparison of AIS Data with Other Aircraft and Ground Data for the Geobotanical Discrimination of Rock Types in Southwest Oregon

NASA Technical Reports Server (NTRS)

Mouat, D. A.

1985-01-01

The use of remote sensing techniques for the geobotanical discrimination of rock types is predicated upon a number of factors. These include an understanding of vegetation response to environmental (especially geochemical) conditions, the establishment of correlations between those vegetation factors and environmental factors, and the use of appropriate remote sensing techniques to discriminate the vegetation.

Earth Resources. A Continuing Bibliography with Indexes

DTIC Science & Technology

1987-11-01

Airborne microwave Doppler measurements of ocean of Guinea according to ground-based and satellite Coral reef remote sensing applications wave directional...understanding of internal Coral reef remote sensing applications an earth-to-satellite Hadamard transform laser long-path waves in the ocean p 20 A87-32951...classifications of coral reefs , and an are provided and new topographic features that are revealed are autocorrelation technique is being developed to

Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

NASA Astrophysics Data System (ADS)

Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

2015-01-01

The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

Practical Approach To Building A Mid-Wave Remote Sensing System

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

Pyke, Benjamin J.

The purpose of this project, Laser Active Transmitter & Receiver (LATR), was to build a mobile ground based remote sensing system that can detect, identify and quantify a specific gaseous species using Differential Absorption LIDAR (DIAL). This thesis project is concerned with the development and field testing of a mid-wave infrared active remote sensing system, capable of identifying and quantifying emissions in the 3.2 – 3.5 micron range. The goal is to give a brief description of what remote sensing is about and the specific technique used to analyze the collected data. The thesis will discuss the transmitter and themore » associated subsystems used to create the required wavelength, and the receiver used to collect the returns. And finally, the thesis will discuss the process of collecting the data and some of the results from field and lab collections.« less

Filtering method of star control points for geometric correction of remote sensing image based on RANSAC algorithm

NASA Astrophysics Data System (ADS)

Tan, Xiangli; Yang, Jungang; Deng, Xinpu

2018-04-01

In the process of geometric correction of remote sensing image, occasionally, a large number of redundant control points may result in low correction accuracy. In order to solve this problem, a control points filtering algorithm based on RANdom SAmple Consensus (RANSAC) was proposed. The basic idea of the RANSAC algorithm is that using the smallest data set possible to estimate the model parameters and then enlarge this set with consistent data points. In this paper, unlike traditional methods of geometric correction using Ground Control Points (GCPs), the simulation experiments are carried out to correct remote sensing images, which using visible stars as control points. In addition, the accuracy of geometric correction without Star Control Points (SCPs) optimization is also shown. The experimental results show that the SCPs's filtering method based on RANSAC algorithm has a great improvement on the accuracy of remote sensing image correction.

Autonomous Exploration for Gathering Increased Science

NASA Technical Reports Server (NTRS)

Bornstein, Benjamin J.; Castano, Rebecca; Estlin, Tara A.; Gaines, Daniel M.; Anderson, Robert C.; Thompson, David R.; DeGranville, Charles K.; Chien, Steve A.; Tang, Benyang; Burl, Michael C.;

China national space remote sensing infrastructure and its application

NASA Astrophysics Data System (ADS)

Li, Ming

2016-07-01

Space Infrastructure is a space system that provides communication, navigation and remote sensing service for broad users. China National Space Remote Sensing Infrastructure includes remote sensing satellites, ground system and related systems. According to the principle of multiple-function on one satellite, multiple satellites in one constellation and collaboration between constellations, series of land observation, ocean observation and atmosphere observation satellites have been suggested to have high, middle and low resolution and fly on different orbits and with different means of payloads to achieve a high ability for global synthetically observation. With such an infrastructure, we can carry out the research on climate change, geophysics global surveying and mapping, water resources management, safety and emergency management, and so on. I This paper gives a detailed introduction about the planning of this infrastructure and its application in different area, especially the international cooperation potential in the so called One Belt and One Road space information corridor.

Remote sensing of the marginal ice zone during Marginal Ice Zone Experiment (MIZEX) 83

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Campbell, W. J.; Burns, B. A.; Ellingsen, E.; Farrelly, B. A.; Gloersen, P.; Grenfell, T. C.; Hollinger, J.; Horn, D.; Johannessen, J. A.

1984-01-01

The remote sensing techniques utilized in the Marginal Ice Zone Experiment (MIZEX) to study the physical characteristics and geophysical processes of the Fram Strait Region of the Greenland Sea are described. The studies, which utilized satellites, aircraft, helicopters, and ship and ground-based remote sensors, focused on the use of microwave remote sensors. Results indicate that remote sensors can provide marginal ice zone characteristics which include ice edge and ice boundary locations, ice types and concentration, ice deformation, ice kinematics, gravity waves and swell (in the water and the ice), location of internal wave fields, location of eddies and current boundaries, surface currents and sea surface winds.

The International Space Station: A Unique Platform For Terrestrial Remote Sensing

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Evans, Cynthia A.

2012-01-01

The International Space Station (ISS) became operational in November of 2000, and until recently remote sensing activities and operations have focused on handheld astronaut photography of the Earth. This effort builds from earlier NASA and Russian space programs (e.g. Evans et al. 2000; Glazovskiy and Dessinov 2000). To date, astronauts have taken more than 600,000 images of the Earth s land surface, oceans, and atmospheric phenomena from orbit using film and digital cameras as part two payloads: NASA s Crew Earth Observations experiment (http://eol.jsc.nasa.gov/) and Russia s Uragan experiment (Stefanov et al. 2012). Many of these images have unique attributes - varying look angles, ground resolutions, and illumination - that are not available from other remote sensing platforms. Despite this large volume of imagery and clear capability for Earth remote sensing, the ISS historically has not been perceived as an Earth observations platform by many remote sensing scientists. With the recent installation of new facilities and sophisticated sensor systems, and additional systems manifested and in development, that perception is changing to take advantage of the unique capabilities and viewing opportunities offered by the ISS.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

PubMed Central

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101

Remote sensing for studying atmospheric aerosols in Malaysia

NASA Astrophysics Data System (ADS)

Kanniah, Kasturi D.; Kamarul Zaman, Nurul A. F.

2015-10-01

The aerosol system is Southeast Asia is complex and the high concentrations are due to population growth, rapid urbanization and development of SEA countries. Nevertheless, only a few studies have been carried out especially at large spatial extent and on a continuous basis to study atmospheric aerosols in Malaysia. In this review paper we report the use of remote sensing data to study atmospheric aerosols in Malaysia and document gaps and recommend further studies to bridge the gaps. Satellite data have been used to study the spatial and seasonal patterns of aerosol optical depth (AOD) in Malaysia. Satellite data combined with AERONET data were used to delineate different types and sizes of aerosols and to identify the sources of aerosols in Malaysia. Most of the aerosol studies performed in Malaysia was based on station-based PM10 data that have limited spatial coverage. Thus, satellite data have been used to extrapolate and retrieve PM10 data over large areas by correlating remotely sensed AOD with ground-based PM10. Realising the critical role of aerosols on radiative forcing numerous studies have been conducted worldwide to assess the aerosol radiative forcing (ARF). Such studies are yet to be conducted in Malaysia. Although the only source of aerosol data covering large region in Malaysia is remote sensing, satellite observations are limited by cloud cover, orbital gaps of satellite track, etc. In addition, relatively less understanding is achieved on how the atmospheric aerosol interacts with the regional climate system. These gaps can be bridged by conducting more studies using integrated approach of remote sensing, AERONET and ground based measurements.

Analysis of 2015 Winter In-Flight Icing Case Studies with Ground-Based Remote Sensing Systems Compared to In-Situ SLW Sondes

NASA Technical Reports Server (NTRS)

Serke, David J.; King, Michael Christopher; Hansen, Reid; Reehorst, Andrew L.

2016-01-01

National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage utilizes a vertical pointing cloud radar, a multi-frequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport. To date, statistical comparisons of the vertical profiling technology have been made to Pilot Reports and Icing Forecast Products. With the extension into relatively large area coverage and the output of microphysical properties in addition to icing severity, the use of these comparators is not appropriate and a more rigorous assessment is required. NASA conducted a field campaign during the early months of 2015 to develop a database to enable the assessment of the new terminal area icing remote sensing system and further refinement of terminal area icing weather information technologies in general. In addition to the ground-based remote sensors listed earlier, in-situ icing environment measurements by weather balloons were performed to produce a comprehensive comparison database. Balloon data gathered consisted of temperature, humidity, pressure, super-cooled liquid water content, and 3-D position with time. Comparison data plots of weather balloon and remote measurements, weather balloon flight paths, bulk comparisons of integrated liquid water content and icing cloud extent agreement, and terminal-area hazard displays are presented. Discussions of agreement quality and paths for future development are also included.

Instrumental sensing of stationary source emissions. [sulphur dioxide remote sensing for coal-burning power plants

NASA Technical Reports Server (NTRS)

Herget, W. F.; Conner, W. D.

1977-01-01

A variety of programs have been conducted within EPA to evaluate the capability of various ground-based remote-sensing techniques for measuring the SO2 concentration, velocity, and opacity of effluents from coal-burning power plants. The results of the remote measurements were compared with the results of instack measurements made using EPA reference methods. Attention is given to infrared gas-filter correlation radiometry for SO2 concentration, Fourier-transform infrared spectroscopy for SO2 concentration, ultraviolet matched-filter correlation spectroscopy for SO2 concentration, infrared and ultraviolet television for velocity and SO2 concentration, infrared laser-Doppler velocimetry for plume velocity, and visible laser radar for plume opacity.

Fusion of remotely sensed data from airborne and ground-based sensors for cotton regrowth study

USDA-ARS?s Scientific Manuscript database

The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

Vegetation changes caused by fire in the Florida flatwoods as observed by remote sensing

NASA Technical Reports Server (NTRS)

Mealor, W. T., Jr.; Prunty, M. C., Jr.

1969-01-01

The nature of the flatwoods and the role that ground fires have played in maintaining them are discussed. Emphasis is placed on the areal and temporal extent of burns as recorded uniformly by remote sensors. Thermal infrared, color infrared, and Ektachrome imagery were obtained from sensors flown by a NASA aircraft at 15,000 feet over a test site in Osceola County, Florida, in March 1968. The overall pattern of burning can be sequenced and mapped uniformly from the imagery. By comparing the various imagery, areal and temporal extent of burned areas can be determined. It was concluded that remote sensed imagery provides more accurate and areally comprehensive media for assessing the impact of ground fires on the landscape of the flatwoods region than are available from any other data source.

SLAPex Freeze/Thaw 2015: The First Dedicated Soil Freeze/Thaw Airborne Campaign

NASA Technical Reports Server (NTRS)

Kim, Edward; Wu, Albert; DeMarco, Eugenia; Powers, Jarrett; Berg, Aaron; Rowlandson, Tracy; Freeman, Jacqueline; Gottfried, Kurt; Toose, Peter; Roy, Alexandre;

Development of Ground Reference GIS for Assessing Land Cover Maps of Northeast Yellowstone National Park

NASA Technical Reports Server (NTRS)

Spruce, Joe; Warner, Amanda; Terrie, Greg; Davis, Bruce

2001-01-01

GIS technology and ground reference data often play vital roles in assessing land cover maps derived from remotely sensed data. This poster illustrates these roles, using results from a study done in Northeast Yellowstone National Park. This area holds many forest, range, and wetland cover types of interest to park managers. Several recent studies have focused on this locale, including the NASA Earth Observations Commercial Applications Program (EOCAP) hyperspectral project performed by Yellowstone Ecosystems Studies (YES) on riparian and in-stream habitat mapping. This poster regards a spin-off to the EOCAP project in which YES and NASA's Earth Science Applications Directorate explored the potential for synergistic use of hyperspecral, synthetic aperture radar, and multiband thermal imagery in mapping land cover types. The project included development of a ground reference GIS for site-specific data needed to evaluate maps from remotely sensed imagery. Field survey data included reflectance of plant communities, native and exotic plant species, and forest health conditions. Researchers also collected GPS points, annotated aerial photographs, and took hand held photographs of reference sites. The use of ESRI, ERDAS, and ENVI software enabled reference data entry into a GIS for comparision to georeferenced imagery and thematic maps. The GIS-based ground reference data layers supported development and assessment of multiple maps from remotely sensed data sets acquired over the study area.

A Ground Systems Template for Remote Sensing Systems

NASA Astrophysics Data System (ADS)

McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

2002-10-01

Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS.

A New Airborne Lidar for Remote Sensing of Canopy Fluorescence and Vertical Profile

NASA Astrophysics Data System (ADS)

Ounis, A.; Bach, J.; Mahjoub, A.; Daumard, F.; Moya, I.; Goulas, Y.

2016-06-01

We report the development of a new lidar system for airborne remote sensing of chlorophyll fluorescence (ChlF) and vertical profile of canopies. By combining laserinduced fluorescence (LIF), sun-induced fluorescence (SIF) and canopy height distribution, the new instrument will low the simultaneous assessment of gross primary production (GPP), photosynthesis efficiency and above ground carbon stocks. Technical issues of the lidar development are discussed and expected performances are presented.

Monitoring, analysis and classification of vegetation and soil data collected by a small and lightweight hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Mönnig, Carsten

2014-05-01

The increasing precision of modern farming systems requires a near-real-time monitoring of agricultural crops in order to estimate soil condition, plant health and potential crop yield. For large sized agricultural plots, satellite imagery or aerial surveys can be used at considerable costs and possible time delays of days or even weeks. However, for small to medium sized plots, these monitoring approaches are cost-prohibitive and difficult to assess. Therefore, we propose within the INTERREG IV A-Project SMART INSPECTORS (Smart Aerial Test Rigs with Infrared Spectrometers and Radar), a cost effective, comparably simple approach to support farmers with a small and lightweight hyperspectral imaging system to collect remotely sensed data in spectral bands in between 400 to 1700nm. SMART INSPECTORS includes the whole remote sensing processing chain of small scale remote sensing from sensor construction, data processing and ground truthing for analysis of the results. The sensors are mounted on a remotely controlled (RC) Octocopter, a fixed wing RC airplane as well as on a two-seated Autogyro for larger plots. The high resolution images up to 5cm on the ground include spectra of visible light, near and thermal infrared as well as hyperspectral imagery. The data will be analyzed using remote sensing software and a Geographic Information System (GIS). The soil condition analysis includes soil humidity, temperature and roughness. Furthermore, a radar sensor is envisaged for the detection of geomorphologic, drainage and soil-plant roughness investigation. Plant health control includes drought stress, vegetation health, pest control, growth condition and canopy temperature. Different vegetation and soil indices will help to determine and understand soil conditions and plant traits. Additional investigation might include crop yield estimation of certain crops like apples, strawberries, pasture land, etc. The quality of remotely sensed vegetation data will be tested with ground truthing tools like a spectrometer, visual inspection and ground control panel. The soil condition will also be monitored with a wireless sensor network installed on the examined plots of interest. Provided with this data, a farmer can respond immediately to potential threats with high local precision. In this presentation, preliminary results of hyperspectral images of distinctive vegetation cover and soil on different pasture test plots are shown. After an evaluation period, the whole processing chain will offer farmers a unique, near real- time, low cost solution for small to mid-sized agricultural plots in order to easily assess crop and soil quality and the estimation of harvest. SMART INSPECTORS remotely sensed data will form the basis for an input in a decision support system which aims to detect crop related issues in order to react quickly and efficiently, saving fertilizer, water or pesticides.

Volcanology 2020: How will thermal remote sensing of volcanic surface activity evolve over the next decade?

NASA Astrophysics Data System (ADS)

Ramsey, Michael S.; Harris, Andrew J. L.

2013-01-01

Volcanological remote sensing spans numerous techniques, wavelength regions, data collection strategies, targets, and applications. Attempting to foresee and predict the growth vectors in this broad and rapidly developing field is therefore exceedingly difficult. However, we attempted to make such predictions at both the American Geophysical Union (AGU) meeting session entitled Volcanology 2010: How will the science and practice of volcanology change in the coming decade? held in December 2000 and the follow-up session 10 years later, Looking backward and forward: Volcanology in 2010 and 2020. In this summary paper, we assess how well we did with our predictions for specific facets of volcano remote sensing in 2000 the advances made over the most recent decade, and attempt a new look ahead to the next decade. In completing this review, we only consider the subset of the field focused on thermal infrared remote sensing of surface activity using ground-based and space-based technology and the subsequent research results. This review keeps to the original scope of both AGU presentations, and therefore does not address the entire field of volcanological remote sensing, which uses technologies in other wavelength regions (e.g., ultraviolet, radar, etc.) or the study of volcanic processes other than the those associated with surface (mostly effusive) activity. Therefore we do not consider remote sensing of ash/gas plumes, for example. In 2000, we had looked forward to a "golden age" in volcanological remote sensing, with a variety of new orbital missions both planned and recently launched. In addition, exciting field-based sensors such as hand-held thermal cameras were also becoming available and being quickly adopted by volcanologists for both monitoring and research applications. All of our predictions in 2000 came true, but at a pace far quicker than we predicted. Relative to the 2000-2010 timeframe, the coming decade will see far fewer new orbital instruments with direct applications to volcanology. However ground-based technologies and applications will continue to proliferate, and unforeseen technology promises many exciting possibilities that will advance volcano thermal monitoring and science far beyond what we can currently envision.

Analysis and modeling of atmospheric turbulence on the high-resolution space optical systems

NASA Astrophysics Data System (ADS)

Lili, Jiang; Chen, Xiaomei; Ni, Guoqiang

2016-09-01

Modeling and simulation of optical remote sensing system plays an unslightable role in remote sensing mission predictions, imaging system design, image quality assessment. It has already become a hot research topic at home and abroad. Atmospheric turbulence influence on optical systems is attached more and more importance to as technologies of remote sensing are developed. In order to study the influence of atmospheric turbulence on earth observation system, the atmospheric structure parameter was calculated by using the weak atmospheric turbulence model; and the relationship of the atmospheric coherence length and high resolution remote sensing optical system was established; then the influence of atmospheric turbulence on the coefficient r0h of optical remote sensing system of ground resolution was derived; finally different orbit height of high resolution optical system imaging quality affected by atmospheric turbulence was analyzed. Results show that the influence of atmospheric turbulence on the high resolution remote sensing optical system, the resolution of which has reached sub meter level meter or even the 0.5m, 0.35m and even 0.15m ultra in recent years, image quality will be quite serious. In the above situation, the influence of the atmospheric turbulence must be corrected. Simulation algorithms of PSF are presented based on the above results. Experiment and analytical results are posted.

Remote sensing in Virginia agriculture

NASA Technical Reports Server (NTRS)

Pettry, D. E.; Newhouse, M. E.; Dunton, E. M., Jr.; Scott, J. H., Jr.

1972-01-01

An experimental investigation, designed to develop and evaluate multispectral sensing techniques used in sensing agricultural crops, is described. Initial studies were designed to detect plant species and associated diseases, soil variations, and cultural practices under natural environment conditions. In addition, crop varieties, age, spacing, plant height, percentage of ground cover, and plant vigor are determined.

Review of Remote Sensing Needs and Applications in Africa

NASA Technical Reports Server (NTRS)

Brown, Molly E.

2007-01-01

Remote sensing data has had an important role in identifying and responding to inter-annual variations in the African environment during the past three decades. As a largely agricultural region with diverse but generally limited government capacity to acquire and distribute ground observations of rainfall, temperature and other parameters, remote sensing is sometimes the only reliable measure of crop growing conditions in Africa. Thus, developing and maintaining the technical and scientific capacity to analyze and utilize satellite remote sensing data in Africa is critical to augmenting the continent's local weather/climate observation networks as well as its agricultural and natural resource development and management. The report Review of Remote Sensing Needs and Applications in Africa' has as its central goal to recommend to the US Agency for International Development an appropriate approach to support sustainable remote sensing applications at African regional remote sensing centers. The report focuses on "RS applications" to refer to the acquisition, maintenance and archiving, dissemination, distribution, analysis, and interpretation of remote sensing data, as well as the integration of interpreted data with other spatial data products. The report focuses on three primary remote sensing centers: (1) The AGRHYMET Regional Center in Niamey, Niger, created in 1974, is a specialized institute of the Permanent Interstate Committee for Drought Control in the Sahel (CILSS), with particular specialization in science and techniques applied to agricultural development, rural development, and natural resource management. (2) The Regional Centre for Maiming of Resources for Development (RCMRD) in Nairobi, Kenya, established in 1975 under the auspices of the United Nations Economic Commission for Africa and the Organization of African Unity (now the African Union), is an intergovernmental organization, with 15 member states from eastern and southern Africa. (3) The Regional Remote Sensing Unit (RRSU) in Gaborone, Botswana, began work in June 1988 and operates under the Agriculture Information Management System (AIMS), as part of the Food, Agriculture and Natural Resources (FANR) Directorate, based at the Southern Africa Development Community (SADC) Secretariat.

A Ground Truthing Method for AVIRIS Overflights Using Canopy Absorption Spectra

NASA Technical Reports Server (NTRS)

Gamon, John A.; Serrano, Lydia; Roberts, Dar A.; Ustin, Susan L.

1996-01-01

Remote sensing for ecological field studies requires ground truthing for accurate interpretation of remote imagery. However, traditional vegetation sampling methods are time consuming and hard to relate to the scale of an AVIRIS scene. The large errors associated with manual field sampling, the contrasting formats of remote and ground data, and problems with coregistration of field sites with AVIRIS pixels can lead to difficulties in interpreting AVIRIS data. As part of a larger study of fire risk in the Santa Monica Mountains of southern California, we explored a ground-based optical method of sampling vegetation using spectrometers mounted both above and below vegetation canopies. The goal was to use optical methods to provide a rapid, consistent, and objective means of "ground truthing" that could be related both to AVIRIS imagery and to conventional ground sampling (e.g., plot harvests and pigment assays).

Airborne and Ground-Based Optical Characterization of Legacy Underground Nuclear Test Sites

NASA Astrophysics Data System (ADS)

Vigil, S.; Craven, J.; Anderson, D.; Dzur, R.; Schultz-Fellenz, E. S.; Sussman, A. J.

2015-12-01

Detecting, locating, and characterizing suspected underground nuclear test sites is a U.S. security priority. Currently, global underground nuclear explosion monitoring relies on seismic and infrasound sensor networks to provide rapid initial detection of potential underground nuclear tests. While seismic and infrasound might be able to generally locate potential underground nuclear tests, additional sensing methods might be required to further pinpoint test site locations. Optical remote sensing is a robust approach for site location and characterization due to the ability it provides to search large areas relatively quickly, resolve surface features in fine detail, and perform these tasks non-intrusively. Optical remote sensing provides both cultural and surface geological information about a site, for example, operational infrastructure, surface fractures. Surface geological information, when combined with known or estimated subsurface geologic information, could provide clues concerning test parameters. We have characterized two legacy nuclear test sites on the Nevada National Security Site (NNSS), U20ak and U20az using helicopter-, ground- and unmanned aerial system-based RGB imagery and light detection and ranging (lidar) systems. The multi-faceted information garnered from these different sensing modalities has allowed us to build a knowledge base of how a nuclear test site might look when sensed remotely, and the standoff distances required to resolve important site characteristics.

Ground Truth Studies - A hands-on environmental science program for students, grades K-12

NASA Technical Reports Server (NTRS)

Katzenberger, John; Chappell, Charles R.

1992-01-01

The paper discusses the background and the objectives of the Ground Truth Studies (GTSs), an activity-based teaching program which integrates local environmental studies with global change topics, utilizing remotely sensed earth imagery. Special attention is given to the five key concepts around which the GTS programs are organized, the pilot program, the initial pilot study evaluation, and the GTS Handbook. The GTS Handbook contains a primer on global change and remote sensing, aerial and satellite images, student activities, glossary, and an appendix of reference material. Also described is a K-12 teacher training model. International participation in the program is to be initiated during the 1992-1993 school year.

Radar activities of the DFVLR Institute for Radio Frequency Technology

NASA Technical Reports Server (NTRS)

Keydel, W.

1983-01-01

Aerospace research and the respective applications microwave tasks with respect to remote sensing, position finding and communication are discussed. The radar activities are directed at point targets, area targets and volume targets; they center around signature research for earth and ocean remote sensing, target recognition, reconnaissance and camouflage and imaging and area observation radar techniques (SAR and SLAR). The radar activities cover a frequency range from 1 GHz up to 94 GHz. The radar program is oriented to four possible application levels: ground, air, shuttle orbits and satellite orbits. Ground based studies and measurements, airborne scatterometers and imaging radars, a space shuttle radar, the MRSE, and follow on experiments are considered.

Hydrological research in Ethiopia

NASA Astrophysics Data System (ADS)

Gebremichael, M.

2012-12-01

Almost all major development problems in Ethiopia are water-related: food insecurity, low economic development, recurrent droughts, disastrous floods, poor health conditions, and low energy condition. In order to develop and manage existing water resources in a sustainable manner, knowledge is required about water availability, water quality, water demand in various sectors, and the impacts of water resource projects on health and the environment. The lack of ground-based data has been a major challenge for generating this knowledge. Current advances in remote sensing and computer simulation technology could provide alternative source of datasets. In this talk, I will present the challenges and opportunities in using remote sensing datasets and hydrological models in regions such as Africa where ground-based datasets are scarce.

Brazilian remote sensing receiving, recording and processing ground systems in the 1980's

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator)

1984-01-01

A ground station was built in Brazil to receive, record, and process TM data from LANDSAT satellites. The receiving/recording subsystem and the processing subsystem are discussed. Functional design specifications for the facility are addressed.

[A review of atmospheric aerosol research by using polarization remote sensing].

PubMed

Guo, Hong; Gu, Xing-Fa; Xie, Dong-Hai; Yu, Tao; Meng, Qing-Yan

2014-07-01

In the present paper, aerosol research by using polarization remote sensing in last two decades (1993-2013) was reviewed, including aerosol researches based on POLDER/PARASOL, APS(Aerosol Polarimetry Sensor), Polarized Airborne camera and Ground-based measurements. We emphasize the following three aspects: (1) The retrieval algorithms developed for land and marine aerosol by using POLDER/PARASOL; The validation and application of POLDER/PARASOL AOD, and cross-comparison with AOD of other satellites, such as MODIS AOD. (2) The retrieval algorithms developed for land and marine aerosol by using MICROPOL and RSP/APS. We also introduce the new progress in aerosol research based on The Directional Polarimetric Camera (DPC), which was produced by Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (CAS). (3) The aerosol retrieval algorithms by using measurements from ground-based instruments, such as CE318-2 and CE318-DP. The retrieval results from spaceborne sensors, airborne camera and ground-based measurements include total AOD, fine-mode AOD, coarse-mode AOD, size distribution, particle shape, complex refractive indices, single scattering albedo, scattering phase function, polarization phase function and AOD above cloud. Finally, based on the research, the authors present the problems and prospects of atmospheric aerosol research by using polarization remote sensing, and provide a valuable reference for the future studies of atmospheric aerosol.

Rice Crop Monitoring Using Microwave and Optical Remotely Sensed Image Data

NASA Astrophysics Data System (ADS)

Suga, Y.; Konishi, T.; Takeuchi, S.; Kitano, Y.; Ito, S.

Hiroshima Institute of Technology HIT is operating the direct down-links of microwave and optical satellite data in Japan This study focuses on the validation for rice crop monitoring using microwave and optical remotely sensed image data acquired by satellites referring to ground truth data such as height of crop ratio of crop vegetation cover and leaf area index in the test sites of Japan ENVISAT-1 ASAR data has a capability to capture regularly and to monitor during the rice growing cycle by alternating cross polarization mode images However ASAR data is influenced by several parameters such as landcover structure direction and alignment of rice crop fields in the test sites In this study the validation was carried out combined with microwave and optical satellite image data and ground truth data regarding rice crop fields to investigate the above parameters Multi-temporal multi-direction descending and ascending and multi-angle ASAR alternating cross polarization mode images were used to investigate rice crop growing cycle LANDSAT data were used to detect landcover structure direction and alignment of rice crop fields corresponding to the backscatter of ASAR As the result of this study it was indicated that rice crop growth can be precisely monitored using multiple remotely sensed data and ground truth data considering with spatial spectral temporal and radiometric resolutions

Effects of land use/cover change and harvests on forest carbon dynamics in northern states of the United States from remote sensing and inventory data: 1992-2001

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2011-01-01

We examined spatial patterns of changes in forest area and nonsoil carbon (C) dynamics affected by land use/cover change (LUC) and harvests in 24 northern states of the United States using an integrated methodology combining remote sensing and ground inventory data between 1992 and 2001. We used the Retrofit Change Product from the Multi-Resolution Land Characteristics...

Integrating remote sensing techniques at Cuprite, Nevada: AVIRIS, Thematic Mapper, and field spectroscopy

NASA Technical Reports Server (NTRS)

Hill, Bradley; Nash, Greg; Ridd, Merrill; Hauff, Phoebe L.; Ebel, Phil

1992-01-01

The Cuprite mining district in southwestern Nevada has become a test site for remote sensing studies with numerous airborne scanners and ground sensor data sets collected over the past fifteen years. Structurally, the Cuprite region can be divided into two areas with slightly different alteration and mineralogy. These zones lie on either side of a postulated low-angle structural discontinuity that strikes nearly parallel to US Route 95. Hydrothermal alternation at Cuprite was classified into three major zones: silicified, opalized, and argillized. These alteration types form a bulls-eye pattern east of the highway and are more linear on the west side of the highway making a striking contrast from the air and the imagery. Cuprite is therefore an ideal location for remote sensing research as it exhibits easily identified hydrothermal zoning, is relatively devoid of vegetation, and contains a distinctive spectrally diagnostic mineral suite including the ammonium feldspar buddingtonite, several types of alunite, different jarosites, illite, kaolinite, smectite, dickite, and opal. This present study brings a new dimension to these previous remote sensing and ground data sets compiled for Cuprite. The development of a higher resolution field spectrometer now provides the capability to combine extensive in-situ mineralogical data with a new geologic field survey and detailed Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) images. The various data collection methods and the refinement of the integrated techniques are discussed.

Biodiversity and agriculture in dynamic landscapes: Integrating ground and remotely-sensed baseline surveys.

PubMed

Gillison, Andrew N; Asner, Gregory P; Fernandes, Erick C M; Mafalacusser, Jacinto; Banze, Aurélio; Izidine, Samira; da Fonseca, Ambrósio R; Pacate, Hermenegildo

2016-07-15

Sustainable biodiversity and land management require a cost-effective means of forecasting landscape response to environmental change. Conventional species-based, regional biodiversity assessments are rarely adequate for policy planning and decision making. We show how new ground and remotely-sensed survey methods can be coordinated to help elucidate and predict relationships between biodiversity, land use and soil properties along complex biophysical gradients that typify many similar landscapes worldwide. In the lower Zambezi valley, Mozambique we used environmental, gradient-directed transects (gradsects) to sample vascular plant species, plant functional types, vegetation structure, soil properties and land-use characteristics. Soil fertility indices were derived using novel multidimensional scaling of soil properties. To facilitate spatial analysis, we applied a probabilistic remote sensing approach, analyzing Landsat 7 satellite imagery to map photosynthetically active and inactive vegetation and bare soil along each gradsect. Despite the relatively low sample number, we found highly significant correlations between single and combined sets of specific plant, soil and remotely sensed variables that permitted testable spatial projections of biodiversity and soil fertility across the regional land-use mosaic. This integrative and rapid approach provides a low-cost, high-return and readily transferable methodology that permits the ready identification of testable biodiversity indicators for adaptive management of biodiversity and potential agricultural productivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Overview of the NASA tropospheric environmental quality remote sensing program

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Application of airborne remote sensing to the ancient Pompeii site

NASA Astrophysics Data System (ADS)

Vitiello, Fausto; Giordano, Antonio; Borfecchia, Flavio; Martini, Sandro; De Cecco, Luigi

1996-12-01

The ancient Pompeii site is in the Sarno Valley, an area of about 400 km2 in the South of Italy near Naples, that was utilized by man since old time (thousands of years ago). Actually the valley is under critical environmental conditions because of the relevant industrial development. ENEA is conducting various studies and research in the valley. ENEA is employing historical research, ground campaigns, cartography and up-to-date airborne multispectral remote sensing technologies to make a geographical information system. Airborne remote sensing technologies are very suitable for situations as that of the Sarno Valley. The paper describes the archaeological application of the research in progress as regarding the ancient site of Pompeii and its fluvial port.

Effective use of remote sensing products in litigation

NASA Technical Reports Server (NTRS)

Jaynes, R. A.

1983-01-01

A boiled-down version of major legal principles affecting the admissibility of data and products from remote sensing devices is presented. It is suggested that enhancements or classifications of digital data (from scanning devices or from digitized aerial photography) be proffered as evidence in a fashion similar to the manner in which maps from photogrammetric techniques are introduced as evidence. Every effort should be made to illucidate the processes by which digital data are analytically treated or manipulated. Remote sensing expert witnesses should be practiced in providing concise and clear explanations of both data and methods. Special emphasis should be placed on being prepared to provide a detailed accounting of steps taken to calibrate and verify spectral characteristics with ground truth.

Evapotranspiration and remote sensing

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Gurney, R.

1982-01-01

There are three things required for evapotranspiration to occur: (1) energy (580 cal/gm) for the change of phase of the water; (2) a source of the water, i.e., adequate soil moisture in the surface layer or in the root zone of the plant; and (3) a sink for the water, i.e., a moisture deficit in the air above the ground. Remote sensing can contribute information to the first two of these conditions by providing estimates of solar insolation, surface albedo, surface temperature, vegetation cover, and soil moisture content. In addition there have been attempts to estimate precipitation and shelter air temperature from remotely sensed data. The problem remains to develop methods for effectively using these sources of information to make large area estimates of evapotranspiration.

Annual Symposium on Machine Processing of Remotely Sensed Data, 4th, Purdue University, West Lafayette, Ind., June 21-23, 1977, Proceedings

NASA Technical Reports Server (NTRS)

Morrison, D. B. (Editor); Scherer, D. J.

1977-01-01

Papers are presented on a variety of techniques for the machine processing of remotely sensed data. Consideration is given to preprocessing methods such as the correction of Landsat data for the effects of haze, sun angle, and reflectance and to the maximum likelihood estimation of signature transformation algorithm. Several applications of machine processing to agriculture are identified. Various types of processing systems are discussed such as ground-data processing/support systems for sensor systems and the transfer of remotely sensed data to operational systems. The application of machine processing to hydrology, geology, and land-use mapping is outlined. Data analysis is considered with reference to several types of classification methods and systems.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

A review of the remote sensing of lower tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles: REMOTE SENSING OF THERMODYNAMIC PROFILES

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

Wulfmeyer, Volker; Hardesty, R. Michael; Turner, David D.

A review of remote sensing technology for lower tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer—usually characterized by an inversion—and the lowermore » troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global navigation satellite system, as well as water vapor and temperature Raman lidar and water vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

Validation of a remote sensing model to identify Simulium damnosum s.l. breeding sites in Sub-Saharan Africa.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent D; Sanfo, Moussa; Griffith, Daniel A; Lakwo, Thomson L; Habomugisha, Peace; Katabarwa, Moses N; Unnasch, Thomas R

2013-01-01

Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.

Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa

PubMed Central

Jacob, Benjamin G.; Novak, Robert J.; Toe, Laurent D.; Sanfo, Moussa; Griffith, Daniel A.; Lakwo, Thomson L.; Habomugisha, Peace; Katabarwa, Moses N.; Unnasch, Thomas R.

2013-01-01

Background Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Methodology/Principal Findings Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. Conclusions/Significance This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement. PMID:23936571

Development of a Near Ground Remote Sensing System

PubMed Central

Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong

2016-01-01

Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies. PMID:27164111

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

Integrationof Remote Sensing and Geographic information system in Ground Water Quality Assessment and Management

NASA Astrophysics Data System (ADS)

Shakak, N.

2015-04-01

Spatial variations in ground water quality in the Khartoum state, Sudan, have been studied using geographic information system (GIS) and remote sensing technique. Gegraphical informtion system a tool which is used for storing, analyzing and displaying spatial data is also used for investigating ground water quality information. Khartoum landsat mosac image aquired in 2013was used, Arc/Gis software applied to extract the boundary of the study area, the image was classified to create land use/land cover map. The land use map,geological and soil map are used for correlation between land use , geological formations, and soil types to understand the source of natural pollution that can lower the ground water quality. For this study, the global positioning system (GPS), used in the field to identify the borehole location in a three dimentional coordinate (Latitude, longitude, and altitude), water samples were collected from 156 borehole wells, and analyzed for physico-chemical parameters like electrical conductivity, Total dissolved solid,Chloride, Nitrate, Sodium, Magnisium, Calcium,and Flouride, using standard techniques in the laboratory and compared with the standards.The ground water quality maps of the entire study area have been prepared using spatial interpolation technique for all the above parameters.then the created maps used to visualize, analyze, and understand the relationship among the measured points. Mapping was coded for potable zones, non-potable zones in the study area, in terms of water quality sutability for drinking water and sutability for irrigation. In general satellite remote sensing in conjunction with geographical information system (GIS) offers great potential for water resource development and management.

Remote sensing techniques applied to multispectral recognition of the Aranjuez pilot zone

NASA Technical Reports Server (NTRS)

Lemos, G. L.; Salinas, J.; Rebollo, M.

1977-01-01

A rectangular (7 x 14 km) area 40 km S of Madrid was remote-sensed with a three-stage recognition process. Ground truth was established in the first phase, airborne sensing with a multispectral scanner and photographic cameras were used in the second phase, and Landsat satellite data were obtained in the third phase. Agronomic and hydrological photointerpretation problems are discussed. Color, black/white, and labeled areas are displayed for crop recognition in the land-use survey; turbidity, concentrations of pollutants and natural chemicals, and densitometry of the water are considered in the evaluation of water resources.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

PubMed Central

Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

2018-01-01

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

PubMed

Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

2018-04-25

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data

NASA Astrophysics Data System (ADS)

Song, Yi; Wang, Jiemin; Yang, Kun; Ma, Mingguo; Li, Xin; Zhang, Zhihui; Wang, Xufeng

2012-07-01

Estimating evapotranspiration (ET) is required for many environmental studies. Remote sensing provides the ability to spatially map latent heat flux. Many studies have developed approaches to derive spatially distributed surface energy fluxes from various satellite sensors with the help of field observations. In this study, remote-sensing-based λE mapping was conducted using a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image. The remotely sensed data and field observations employed in this study were obtained from Watershed Allied Telemetry Experimental Research (WATER). A biophysics-based surface resistance model was revised to account for water stress and temperature constraints. The precision of the results was validated using 'ground truth' data obtained by eddy covariance (EC) system. Scale effects play an important role, especially for parameter optimisation and validation of the latent heat flux (λE). After considering the footprint of EC, the λE derived from the remote sensing data was comparable to the EC measured value during the satellite's passage. The results showed that the revised surface resistance parameterisation scheme was useful for estimating the latent heat flux over cropland in arid regions.

[Study on artificial neural network combined with multispectral remote sensing imagery for forest site evaluation].

PubMed

Gong, Yin-Xi; He, Cheng; Yan, Fei; Feng, Zhong-Ke; Cao, Meng-Lei; Gao, Yuan; Miao, Jie; Zhao, Jin-Long

2013-10-01

Multispectral remote sensing data containing rich site information are not fully used by the classic site quality evaluation system, as it merely adopts artificial ground survey data. In order to establish a more effective site quality evaluation system, a neural network model which combined remote sensing spectra factors with site factors and site index relations was established and used to study the sublot site quality evaluation in the Wangyedian Forest Farm in Inner Mongolia Province, Chifeng City. Based on the improved back propagation artificial neural network (BPANN), this model combined multispectral remote sensing data with sublot survey data, and took larch as example, Through training data set sensitivity analysis weak or irrelevant factor was excluded, the size of neural network was simplified, and the efficiency of network training was improved. This optimal site index prediction model had an accuracy up to 95.36%, which was 9.83% higher than that of the neural network model based on classic sublot survey data, and this shows that using multi-spectral remote sensing and small class survey data to determine the status of larch index prediction model has the highest predictive accuracy. The results fully indicate the effectiveness and superiority of this method.

Vasu Kilaru

EPA Pesticide Factsheets

Vasu Kilaru's expertise is in Geographic Information Systems, Spatial Analysis, and satellite remote sensing particularly with respect to trying to detect ground-level fine particles using space borne instruments.

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.

Nasa's Land Remote Sensing Plans for the 1980's

NASA Technical Reports Server (NTRS)

Higg, H. C.; Butera, K. M.; Settle, M.

1985-01-01

Research since the launch of LANDSAT-1 has been primarily directed to the development of analysis techniques and to the conduct of applications studies designed to address resource information needs in the United States and in many other countries. The current measurement capabilities represented by MSS, TM, and SIR-A and B, coupled with the present level of remote sensing understanding and the state of knowledge in the discipline earth sciences, form the foundation for NASA's Land Processes Program. Science issues to be systematically addressed include: energy balance, hydrologic cycle, biogeochemical cycles, biological productivity, rock cycle, landscape development, geological and botanical associations, and land surface inventory, monitoring, and modeling. A global perspective is required for using remote sensing technology for problem solving or applications context. A successful model for this kind of activity involves joint research with a user entity where the user provides a test site and ground truth and NASA provides the remote sensing techniques to be tested.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

PubMed Central

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

Future Applications of Remote Sensing to Archeological Research

NASA Technical Reports Server (NTRS)

Sever, Thomas L.

2003-01-01

Archeology was one of the first disciplines to use aerial photography in its investigations at the turn of the 20th century. However, the low resolution of satellite technology that became available in the 1970 s limited their application to regional studies. That has recently changed. The arrival of the high resolution, multi-spectral capabilities of the IKONOS and QUICKBIRD satellites and the scheduled launch of new satellites in the next few years provides an unlimited horizon for future archeological research. In addition, affordable aerial and ground-based remote sensing instrumentation are providing archeologists with information that is not available through traditional methodologies. Although many archeologists are not yet comfortable with remote sensing technology a new generation has embraced it and is accumulating a wealth of new evidence. They have discovered that through the use of remote sensing it is possible to gather information without disturbing the site and that those cultural resources can be monitored and protected for the future.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards.

PubMed

Wright, Daniel B; Mantilla, Ricardo; Peters-Lidard, Christa D

2017-04-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions.

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

NASA Technical Reports Server (NTRS)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2017-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

Progress in the Development of Practical Remote Detection of Icing Conditions

NASA Technical Reports Server (NTRS)

Reehorst, Andrew; Politovich, Marcia K.; Zednik, Stephan; Isaac, George A.; Cober, Stewart

2006-01-01

The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has teamed with NCAR to develop software to fuse data from multiple instruments into a single detected icing condition product. The multiple instrument approach utilizes a X-band vertical staring radar, a multifrequency microwave, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled liquid water profile and aircraft hazard depiction. Ground-based, remotely-sensed measurements and in-situ measurements from research aircraft were gathered during the international 2003-2004 Alliance Icing Research Study (AIRS II). Comparisons between the remote sensing system s fused icing product and the aircraft measurements are reviewed here. While there are areas where improvement can be made, the cases examined suggest that the fused sensor remote sensing technique appears to be a valid approach.

Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization

PubMed Central

Gracia-Romero, Adrian; Kefauver, Shawn C.; Vergara-Díaz, Omar; Zaman-Allah, Mainassara A.; Prasanna, Boddupalli M.; Cairns, Jill E.; Araus, José L.

2017-01-01

Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However, these correlations were clearly weaker than against grain yield and only under low phosphorous conditions. This work reinforces the effectiveness of canopy remote sensing for plant phenotyping and crop management of maize under different phosphorus nutrient conditions and suggests that the RGB indices are the best option. PMID:29230230

Remote sensing of sagebrush canopy nitrogen

USGS Publications Warehouse

Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.

2012-01-01

This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

DTIC Science & Technology

2011-01-01

the relationship between reflec- tance and soil moisture where there is ground cover and ascertain the Normalized Difference Vegetation Index ( NDVI ...in those areas. This could establish a minimum NDVI for ground cover that would allow for estimation of soil moisture. Alternatively, they could

Inferring nutrient loading of estuarine systems by remote sensing of aquatic vegetation

NASA Technical Reports Server (NTRS)

Anderson, R. R.

1978-01-01

THe use of remote sensing to record algal and vascular aquatic plant growths in estuarine waters is discussed. A technique is proposed that uses a combination of data to hierarchically classify watersheds with regard to severity of potential pollution. Specific nonpoint sources of nutrients in tributaries of the watershed are identified with lower altitude photography of vegetation and selected ground sampling. It is concluded that excessive growths of some aquatic plants may be related to nutrient pollution.

Remote sensing and disease control in China: past, present and future

PubMed Central

2013-01-01

Satellite measurements have distinct advantages over conventional ground measurements because they can collect the information repeatedly and automatically. Since 1970 globally and 1985 in China, the availability of remote sensing (RS) techniques has steadily grown and they are becoming increasingly important to improve our understanding of human health. This paper gives the first detailed overview on the developments of RS applications for disease control in China. The problems, challenges and future directions are also discussed with an aim of guiding prospective studies. PMID:23311958

Studies on mineral dust using airborne lidar, ground-based remote sensing, and in situ instrumentation

NASA Astrophysics Data System (ADS)

Marenco, Franco; Ryder, Claire; Estellés, Victor; Segura, Sara; Amiridis, Vassilis; Proestakis, Emmanouil; Marinou, Eleni; Tsekeri, Alexandra; Smith, Helen; Ulanowski, Zbigniew; O'Sullivan, Debbie; Brooke, Jennifer; Pradhan, Yaswant; Buxmann, Joelle

2018-04-01

In August 2015, the AER-D campaign made use of the FAAM research aircraft based in Cape Verde, and targeted mineral dust. First results will be shown here. The campaign had multiple objectives: (1) lidar dust mapping for the validation of satellite and model products; (2) validation of sunphotometer remote sensing with airborne measurements; (3) coordinated measurements with the CATS lidar on the ISS; (4) radiative closure studies; and (5) the validation of a new model of dustsonde.

Sea Ice Remote Sensing Using Surface Reflected GPS Signals

NASA Technical Reports Server (NTRS)

Komjathy, Attila; Maslanik, James; Zavorotny, Valery U.; Axelrad, Penina; Katzberg, Stephen J.

2000-01-01

This paper describes a new research effort to extend the application of Global Positioning System (GPS) signal reflections, received by airborne instruments, to cryospheric remote sensing. Our experimental results indicate that reflected GPS signals have potential to provide information on the presence and condition of sea and freshwater ice as well as the freeze/thaw state of frozen ground. In this paper we show results from aircraft experiments over the ice pack near Barrow, Alaska indicating correlation between forward-scattered GPS returns and RADARSAT backscattered measurements.

Some applications of remote sensing in atmospheric monitoring programs

NASA Technical Reports Server (NTRS)

Heller, A. N.; Bryson, J. C.; Vasuki, N. C.

1972-01-01

The applications of remote sensing in atmospheric monitoring programs are described. The organization, operations, and functions of an air quality monitoring network at New Castle County, Delaware is discussed. The data obtained by the air quality monitoring network ground stations and the equipment used to obtain atmospheric data are explained. It is concluded that correlation of the information obtained by the network will make it possible to anticipate air pollution problems in the Chesapeake Bay area before a crisis develops.

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.

Atmospheric effects on cluster analyses. [for remote sensing application

NASA Technical Reports Server (NTRS)

Kiang, R. K.

1979-01-01

Ground reflected radiance, from which information is extracted through techniques of cluster analyses for remote sensing application, is altered by the atmosphere when it reaches the satellite. Therefore it is essential to understand the effects of the atmosphere on Landsat measurements, cluster characteristics and analysis accuracy. A doubling model is employed to compute the effective reflectivity, observed from the satellite, as a function of ground reflectivity, solar zenith angle and aerosol optical thickness for standard atmosphere. The relation between the effective reflectivity and ground reflectivity is approximately linear. It is shown that for a horizontally homogeneous atmosphere, the classification statistics from a maximum likelihood classifier remains unchanged under these transforms. If inhomogeneity is present, the divergence between clusters is reduced, and correlation between spectral bands increases. Radiance reflected by the background area surrounding the target may also reach the satellite. The influence of background reflectivity on effective reflectivity is discussed.

Precise tracking of remote sensing satellites with the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong; Thornton, Catherine L.

1990-01-01

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

NASA Technical Reports Server (NTRS)

Korram, S.

1977-01-01

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

NASA Technical Reports Server (NTRS)

Zobler, L.; Lewis, R.

1988-01-01

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review.

PubMed

Lees, K J; Quaife, T; Artz, R R E; Khomik, M; Clark, J M

2018-02-15

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Grounding Lines Detecting Using LANDSAT8 Oli and CRYOSAT-2 Data Fusion

NASA Astrophysics Data System (ADS)

Li, F.; Guo, Y.; Zhang, Y.; Zhang, S.

2018-04-01

The grounding zone is the region where ice transitions from grounded ice sheet to freely floating ice shelf, grounding lines are actually more of a zone, typically over several kilometers. The mass loss from Antarctica is strongly linked to changes in the ice shelves and their grounding lines, since the variation in the grounding line can result in very rapid changes in glacier and ice-shelf behavior. Based on remote sensing observations, five global Antarctic grounding line products have been released internationally, including MOA, ASAID, ICESat, MEaSUREs, and Synthesized grounding lines. However, the five products could not provide the annual grounding line products of the whole Antarctic, even some products have stopped updating, which limits the time series analysis of Antarctic material balance to a certain extent. Besides, the accurate of single remote-sensing data based grounding line products is far from satisficed. Therefore, we use algorithms to extract grounding lines with SAR and Cryosat-2 data respectively, and combine the results of two kinds of grounding lines to obtain new products, we obtain a mature grounding line extraction algorithm process, so that we can realize the extraction of grounding line of the Antarctic each year in the future. The comparison between fusion results and the MOA product results indicate that there is a maximum deviation of 188.67 meters between the MOA product and the fusion result.

Preliminary data for the 20 May 1974, simultaneous evaluation of remote sensors experiment. [water pollution monitoring

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Batten, C. E.; Bowker, D. E.; Bressette, W. E.; Grew, G. W.

1975-01-01

Several remote sensors were simultaneously used to collect data over the tidal James River from Hopewell to Norfolk, Virginia. Sensors evaluated included the Multichannel-Ocean Color Sensor, multispectral scanners, and multispectral photography. Ground truth measurements and remotely sensed data are given. Preliminary analysis indicates that suspended sediment and concentrated industrial effluent are observable from all sensors.

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...

Scaling forest phenology from trees to the landscape using an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Klosterman, S.; Melaas, E. K.; Martinez, A.; Richardson, A. D.

2013-12-01

Vegetation phenology monitoring has yielded a decades-long archive documenting the impacts of global change on the biosphere. However, the coarse spatial resolution of remote sensing obscures the organismic level processes driving phenology, while point measurements on the ground limit the extent of observation. Unmanned aerial vehicles (UAVs) enable low altitude remote sensing at higher spatial and temporal resolution than available from space borne platforms, and have the potential to elucidate the links between organism scale processes and landscape scale analyses of terrestrial phenology. This project demonstrates the use of a low cost multirotor UAV, equipped with a consumer grade digital camera, for observation of deciduous forest phenology and comparison to ground- and tower-based data as well as remote sensing. The UAV was flown approximately every five days during the spring green-up period in 2013, to obtain aerial photography over an area encompassing a 250m resolution MODIS (Moderate Resolution Imaging Spectroradiometer) pixel at Harvard Forest in central Massachusetts, USA. The imagery was georeferenced and tree crowns were identified using a detailed species map of the study area. Image processing routines were used to extract canopy 'greenness' time series, which were used to calculate phenology transition dates corresponding to early, middle, and late stages of spring green-up for the dominant canopy trees. Aggregated species level phenology estimates from the UAV data, including the mean and variance of phenology transition dates within species in the study area, were compared to model predictions based on visual assessment of a smaller sample size of individual trees, indicating the extent to which limited ground observations represent the larger landscape. At an intermediate scale, the UAV data was compared to data from repeat digital photography, integrating over larger portions of canopy within and near the study area, as a validation step and to see how well tower-based approaches characterize the surrounding landscape. Finally, UAV data was compared to MODIS data to determine how tree crowns within a remote sensing pixel combine to create the aggregate landscape phenology measured by remote sensing, using an area weighted average of the phenology of all dominant crowns.

Remote sensing of water and nitrogen stress in broccoli

NASA Astrophysics Data System (ADS)

Elsheikha, Diael-Deen Mohamed

Remote sensing is being used in agriculture for crop management. Ground based remote sensing data acquisition system was used for collection of high spatial and temporal resolution data for irrigated broccoli crop. The system was composed of a small cart that ran back and forth on a rail system that was mounted on a linear move irrigation system. The cart was equipped with a sensor that had 4 discrete wavelengths; 550 nm, 660 nm, 720 nm, and 810 nm, and an infrared thermometer, all had 10 nm bandwidth. A global positioning system was used to indicate the cart position. The study consisted of two parts; the first was to evaluate remotely sensed reflectance and indices in broccoli during the growing season, and determine whether remotely sensed indices or standard deviation of indices can distinguish between nitrogen and water stress in broccoli, and the second part of the study was to evaluate remotely sensed indices and standard deviation of remotely sensed indices in broccoli during daily changes in solar zenith angle. Results indicated that nitrogen was detected using Ratio Vegetation index, RVI, Normalized Difference Vegetation Index, NDVI, Canopy Chlorophyll Concentration Index, CCCI, and also using the reflectance in the Near-Infrared, NIR, bands. The Red reflectance band capability of showing stress was not as clear as the previous indices and bands reflectance. The Canopy Chlorophyll Concentration Index, CCCI, was the most successful index. The Crop Water Stress Index was able to detect water stress but it was highly affected by the solar zenith angle change along the day.

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The accuracy achieved in the second and third manuscripts demonstrates that reasonably priced, high resolution remote sensing via RPVs and UAVs is practical for agriculture and natural resource professionals.

Analysis of remote sensing data for evaluating vegetation resources

NASA Technical Reports Server (NTRS)

1971-01-01

Increased utilization studies for current remote sensor and analysis capabilities included: (1) a review of testing procedures for quantifying the accuracy of photointerpretation; (2) field tests of a fully portable spectral data gathering system, both on the ground and from a helicopter; and (3) a comparison of three methods for obtaining ground information necessary for regional agricultural inventories. A version of the LARS point-by-point classification system was upgraded by the addition of routines to analyze spatial data information.

Remote Sensing, New Media and Scientific Literacy for Competence Oriented School Education - A New Integrated Learning Portal

NASA Astrophysics Data System (ADS)

Hodam, H.; Goetzke, R.; Rinow, A.; Voß, K.

2012-04-01

The project FIS - Fernerkundung in Schulen (German for "Remote Sensing in Schools") - aims at a better integration of remote sensing in school lessons. Respectively, the overall ob-jective is to teach pupils from primary school up to high-school graduation basics and fields of application of remote sensing. Working with remote sensing data opens up new and modern ways of teaching. Therefore many teachers have great interest in the subject "remote sensing", being motivated to integrate this topic into teaching, provided that the curriculum is con-sidered. In many cases, this encouragement fails because of confusing information, which ruins all good intentions. For this reason, a comprehensive and well structured learning portal on the subject remote sensing is developed. This will allow teachers and pupils to have a structured initial understanding of the topic. Recognizing that in-depth use of satellite imagery can only be achieved by the means of computer aided learning methods, a sizeable number of e-Learning contents have been created throughout the last 5 years since the project's kickoff which are now integrated into the learning portal. Three main sections form the backbone of the developed learning portal. 1. The "Teaching Materials" section provides registered teachers with interactive lessons to convey curriculum relevant topics through remote sensing. They are able to use the implemented management system to create classes and enregister pupils, keep track of their progresses and control results of the conducted lessons. Abandoning the functio-nalities of the management system the lessons are also available to non-registered us-ers. 2. Pupils and Teachers can investigate further into remote sensing in the "Research" sec-tion, where a knowledge base alongside a satellite image gallery offer general back-ground information on remote sensing and the provided lessons in a semi interactive manner. 3. The "Analysis Tools" section offers means to further experiment with satellite images by working with predefined sets of Images and Tools. All three sections of the platform are presented exemplary explaining the underlying didactical and technical concepts of the project, showing how they are realized and what their potentials are when put to use in school lessons.

NASA programs in technology transfer and their relation to remote sensing education

NASA Technical Reports Server (NTRS)

Weinstein, R. H.

1980-01-01

Technology transfer to users is a central feature of NASA programs. In each major area of responsibility, a variety of mechanisms was established to provide for this transfer of operational capability to the proper end user, be it a Federal agency, industry, or other public sector users. In addition, the Technology Utilization program was established to cut across all program areas and to make available a wealth of 'spinoff' technology (i.e., secondary applications of space technology to ground-based use). The transfer of remote sensing technology, particularly to state and local users, presents some real challenges in application and education for NASA and the university community. The agency's approach to the transfer of remote sensing technology and the current and potential role of universities in the process are considered.

Intercomparison of in-situ and remote sensing δD signals in tropospheric water vapour

NASA Astrophysics Data System (ADS)

Schneider, Matthias; González, Yenny; Dyroff, Christoph; Christner, Emanuel; García, Omaira; Wiegele, Andreas; Andrey, Javier; Barthlott, Sabine; Blumenstock, Thomas; Guirado, Carmen; Hase, Frank; Ramos, Ramon; Rodríguez, Sergio; Sepúveda, Eliezer

2014-05-01

The main mission of the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi-global tropospheric water vapour isototopologue dataset of a good and well-documented quality. We present a first empirical validation of MUSICA's remote sensing δD products (ground-based FTIR within NDACC, Network for the Detection of Atmospheric Composition Change, and space-based with IASI, Infrared Atmospheric Sounding Interferometer, flown on METOP). As reference we use in-situ measurements made on the island of Tenerife at two different altitudes (2370 and 3550 m a.s.l., using two Picarro L2120-i water isotopologue analyzers) and aboard an aircraft (between 200 and 6800 m a.s.l., using the homemade ISOWAT instrument).

Remote sensing of vegetation canopy photosynthetic and stomatal conductance efficiencies

NASA Technical Reports Server (NTRS)

Myneni, R. B.; Ganapol, B. D.; Asrar, G.

1992-01-01

The problem of remote sensing the canopy photosynthetic and stomatal conductance efficiencies is investigated with the aid of one- and three-dimensional radiative transfer methods coupled to a semi-empirical mechanistic model of leaf photosynthesis and stomatal conductance. Desertlike vegetation is modeled as clumps of leaves randomly distributed on a bright dry soil with partial ground cover. Normalized difference vegetation index (NDVI), canopy photosynthetic (Ep), and stomatal efficiencies (Es) are calculated for various geometrical, optical, and illumination conditions. The contribution of various radiative fluxes to estimates of Ep is evaluated and the magnitude of errors in bulk canopy formulation of problem parameters are quantified. The nature and sensitivity of the relationship between Ep and Es to NDVI is investigated, and an algorithm is proposed for use in operational remote sensing.

Remote sensing to detect the movement of wheat curl mites through the spatial spread of virus symptoms, and identification of thrips as predators of wheat curl mites

NASA Astrophysics Data System (ADS)

Stilwell, Abby R.

The wheat curl mite (WCM), Aceria tosichella Keifer, transmits three viruses to winter wheat: wheat streak mosaic virus, High Plains virus, and Triticum mosaic virus. This virus complex causes yellowing of the foliage and stunting of plants. WCMs disperse by wind, and an increased understanding of mite movement and subsequent virus spread is necessary in determining the risk of serious virus infections in winter wheat. These risk parameters will help growers make better decisions regarding WCM management. The objectives of this study were to evaluate the capabilities of remote sensing to identify virus infected plants and to establish the potential of using remote sensing to track virus spread and consequently, mite movement. Although the WCM is small and very hard to track, the viruses it vectors produce symptoms that can be detected with remote sensing. Field plots of simulated volunteer wheat were established between 2006 and 2009, infested with WCMs, and spread mites and virus into adjacent winter wheat. The virus gradients created by WCM movement allowed for the measurement of mite movement potential with both proximal and aerial remote sensing instruments. The ability to detect WCM-vectored viruses with remote sensing was investigated by comparing vegetation indices calculated from proximal remote sensing data to ground truth data obtained in the field. Of the ten vegetation indices tested, the red edge position (REP) index had the best relationship with ground truth data. The spatial spread of virus from WCM source plots was modeled with cokriging. Virus symptoms predicted by cokriging occurred in an oval pattern displaced to the southeast. Data from the spatial spread in small plots of this study were used to estimate the potential sphere of influence for volunteer wheat fields. The impact of thrips on WCM populations was investigated by a series of greenhouse, field, and observational studies. WCM populations in winter wheat increased more slowly when thrips populations were higher, both in the field and in the greenhouse. Two species of thrips, Thrips tabaci Lindeman and Frankliniella occidentalis (Pergande) were observed to feed directly on WCMs. The collective results from this study identify thrips as a regulating factor for WCM populations.

Hyperspectral remote sensing application for monitoring and preservation of plant ecosystems

NASA Astrophysics Data System (ADS)

Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas; Petrov, Nikolay; Stoev, Antoniy

Remote sensing technologies have advanced significantly at last decade and have improved the capability to gather information about Earth’s resources and environment. They have many applications in Earth observation, such as mapping and updating land-use and cover, weather forecasting, biodiversity determination, etc. Hyperspectral remote sensing offers unique opportunities in the environmental monitoring and sustainable use of natural resources. Remote sensing sensors on space-based platforms, aircrafts, or on ground, are capable of providing detailed spectral, spatial and temporal information on terrestrial ecosystems. Ground-based sensors are used to record detailed information about the land surface and to create a data base for better characterizing the objects which are being imaged by the other sensors. In this paper some applications of two hyperspectral remote sensing techniques, leaf reflectance and chlorophyll fluorescence, for monitoring and assessment of the effects of adverse environmental conditions on plant ecosystems are presented. The effect of stress factors such as enhanced UV-radiation, acid rain, salinity, viral infections applied to some young plants (potato, pea, tobacco) and trees (plums, apples, paulownia) as well as of some growth regulators were investigated. Hyperspectral reflectance and fluorescence data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (450-850 nm and 600-900 nm), respectively. The differences between the reflectance data of healthy (control) and injured (stressed) plants were assessed by means of statistical (Student’s t-criterion), first derivative, and cluster analysis and calculation of some vegetation indices in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm). Fluorescence spectra were analyzed at five characteristic wavelengths located at the maximums of the emitted radiation and at the forefronts and rear slopes. The strong relationship, which was found between the results from the two remote sensing techniques and some biochemical and serological analyses (stress markers, DAS-ELISA test), indicates the importance of hyperspectral reflectance and fluorescence techniques for conducting, easily and without damage, rapid health condition assessments of vegetation. This study fills in the existed spectral data base and exemplifies the benefits of integrating remote sensing, Earth observation, plant physiology, ecology, and conducting of interdisciplinary investigations of terrestrial ecosystems.

Monitoring crop coefficient of orange orchards using energy balance and the remote sensed NDVI

NASA Astrophysics Data System (ADS)

Consoli, Simona; Cirelli, Giuseppe Luigi; Toscano, Attilio

2006-09-01

The structure of vegetation is paramount in regulating the exchange of mass and energy across the biosphereatmosphere interface. In particular, changes in vegetation density affected the partitioning of incoming solar energy into sensible and latent heat fluxes that may result in persistent drought through reductions in agricultural productivity and in the water resources availability. Limited research with citrus orchards has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigation when crop coefficient (Kc) estimate, derived from remotely sensed multispectral vegetation indices (VIs), are incorporated into irrigation-scheduling algorithms. The purpose of this article is the application of an empirical reflectance-based model for the estimation of Kc and evapotranspiration fluxes (ET) using ground observations on climatic data and high-resolution VIs from ASTER TERRA satellite imagery. The remote sensed Kc data were used in developing the relationship with the normalized difference vegetation index (NDVI) for orange orchards during summer periods. Validation of remote sensed data on ET, Kc and vegetation features was deal through ground data observations and the resolution of the energy balance to derive latent heat flux density (λE), using measures of net radiation (Rn) and soil heat flux density (G) and estimate of sensible heat flux density (H) from high frequency temperature measurements (Surface Renewal technique). The chosen case study is that of an irrigation area covered by orange orchards located in Eastern Sicily, Italy) during the irrigation seasons 2005 and 2006.

Airborne in situ vertical profiling of HDO/H216O in the subtropical troposphere during the MUSICA remote sensing validation campaign

NASA Astrophysics Data System (ADS)

Dyroff, C.; Sanati, S.; Christner, E.; Zahn, A.; Balzer, M.; Bouquet, H.; McManus, J. B.; González-Ramos, Y.; Schneider, M.

2015-01-01

Vertical profiles of water vapor (H2O) and its isotope ratio D / H expressed as δ D(H2O were measured in situ by the ISOWAT II diode-laser spectrometer during the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) airborne campaign. We present recent modifications of the instrument design. The instrument calibration on the ground as well as in flight is described. Based on the calibration measurements, the humidity-dependent uncertainty of our airborne data is determined. For the majority of the airborne data we achieved an accuracy (uncertainty of the mean) of Δ(δ D) ≈ 10‰. Vertical profiles between 150 and ~7000 m were obtained during 7 days in July and August 2013 over the subtropical North Atlantic Ocean near Tenerife. The flights were coordinated with ground-based (Network for the Detection of Atmospheric Composition Change, NDACC) and space-based (Infrared Atmospheric Sounding Interferometer, IASI) FTIR remote-sensing measurements of δ D(H2O) as a means to validate the remote sensing humidity and δ D(H2O) data products. The results of the validation are presented in detail in a separate paper (Schneider et al., 2014). The profiles were obtained with a high vertical resolution of around 3 m. By analyzing humidity and δ D(H2O) correlations we were able to identify different layers of airmasses with specific isotopic signatures. The results are discussed.

Development of analysis techniques for remote sensing of vegetation resources

NASA Technical Reports Server (NTRS)

Draeger, W. C.

1972-01-01

Various data handling and analysis techniques are summarized for evaluation of ERTS-A and supporting high flight imagery. These evaluations are concerned with remote sensors applied to wildland and agricultural vegetation resource inventory problems. Monitoring California's annual grassland, automatic texture analysis, agricultural ground data collection techniques, and spectral measurements are included.

AERIAL PHOTOGRAPHY AND GROUND VERIFICATION AT POWER PLANT SITES: WISCONSIN POWER PLANT IMPACT STUDY

EPA Science Inventory

This study demonstrated and evaluated nine methods for monitoring the deterioration of a large wetland on the site of a newly-constructed coal-fired power plant in Columbia, County, Wisconsin. Four of the nine methods used data from ground sampling; two were remote sensing method...

A remote-sensing driven tool for estimating crop stress and yields

USDA-ARS?s Scientific Manuscript database

Biophysical crop simulation models are normally forced with precipitation data recorded with either gages or ground-based radar. However, ground based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would...

Ground Truth Studies. Teacher Handbook. Second Edition.

ERIC Educational Resources Information Center

Boyce, Jesse; And Others

Ground Truth Studies is an interdisciplinary activity-based program that draws on the broad range of sciences that make up the study of global change and the complementary technology of remote sensing. It integrates local environmental issues with global change topics, such as the greenhouse effect, loss of biological diversity, and ozone…

SATELLITE REMOTE SENSING AND GROUND-BASED ESTIMATES OF FOREST BIOMASS AND CANOPY STRUCTURE

EPA Science Inventory

MODIS (Moderate Resolution Imaging Spectroradiometer) launched in 1999 is the first satellite sensor to provide the kind of data necessary to intensively probe the global landscape for LAl. Because it is a new sensor, its data products must be validated with ground data. This res...

CO Seasonal Variability and Trend over Paris Megacity Using Ground-Based QualAir FTS and Satellite IASI-MetOp Measurements

NASA Astrophysics Data System (ADS)

Te, Yao; Jeseck, Pascal; Hadji-Lazaro, Juliette

2012-11-01

In a growing world with more than 7 billion inhabitants and big emerging countries such as China, Brazil and India, emissions of anthropogenic pollutants are increasing continuously. Monitoring and control of atmospheric pollutants in megacities have become a major challenge for scientists and public health authorities in environmental research area. The QualAir platform at University Pierre et Marie Curie (UPMC), is an innovating experimental research platform dedicated to survey urban atmospheric pollution and air quality. A Bruker Optics IFS 125HR Fourier transform spectrometer belonged to the Laboratoire de Physique Moléculaire pour l'Atmosphère et l'Astrophysique (LPMAA), was adapted for ground-based atmospheric measurements. As one of the major instruments of the QualAir platform, this ground-based Fourier transform spectrometer (QualAir FTS) analyses the composition of the urban atmosphere of Paris, which is the third largest European megacity. The continuous monitoring of atmospheric pollutants is essential to improve the understanding of urban air pollution processes. Associated with a sun-tracker, the QualAir remote sensing FTS operates in solar infrared absorption and enables to monitor many trace gases, and to follow up their variability in the Ile-de-France region. Concentrations of atmospheric pollutants are retrieved by the radiative transfer model PROFFIT. These ground-based remote sensing measurements are compared to ground in-situ measurements and to satellite data from IASI-MetOp (Infrared Atmospheric Sounding Interferometer). The remote sensing total column of the carbon monoxide (CO) obtained from January 2009 to June 2012, has a seasonal variability with a maximum in April and a minimum in October. While, after 2008, the mean CO level is quite stable (no significant decrease as before 2008).

SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

NASA Astrophysics Data System (ADS)

Snider, G.; Weagle, C. L.; Martin, R. V.; van Donkelaar, A.; Conrad, K.; Cunningham, D.; Gordon, C.; Zwicker, M.; Akoshile, C.; Artaxo, P.; Anh, N. X.; Brook, J.; Dong, J.; Garland, R. M.; Greenwald, R.; Griffith, D.; He, K.; Holben, B. N.; Kahn, R.; Koren, I.; Lagrosas, N.; Lestari, P.; Ma, Z.; Vanderlei Martins, J.; Quel, E. J.; Rudich, Y.; Salam, A.; Tripathi, S. N.; Yu, C.; Zhang, Q.; Zhang, Y.; Brauer, M.; Cohen, A.; Gibson, M. D.; Liu, Y.

2015-01-01

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

Comparison of tropospheric NO2 vertical columns in an urban environment using satellite, multi-axis differential optical absorption spectroscopy, and in situ measurements

NASA Astrophysics Data System (ADS)

Mendolia, D.; D'Souza, R. J. C.; Evans, G. J.; Brook, J.

2013-10-01

Tropospheric NO2 vertical column densities have been retrieved and compared for the first time in Toronto, Canada, using three methods of differing spatial scales. Remotely sensed NO2 vertical column densities, retrieved from multi-axis differential optical absorption spectroscopy and satellite remote sensing, were evaluated by comparison with in situ vertical column densities estimated using a pair of chemiluminescence monitors situated 0.01 and 0.5 km a.g.l. (above ground level). The chemiluminescence measurements were corrected for the influence of NOz, which reduced the NO2 concentrations at 0.01 and 0.5 km by an average of 8 ± 1% and 12 ± 1%, respectively. The average absolute decrease in the chemiluminescence NO2 measurement as a result of this correction was less than 1 ppb. The monthly averaged ratio of the NO2 concentration at 0.5 to 0.01 km varied seasonally, and exhibited a negative linear dependence on the monthly average temperature, with Pearson's R = 0.83. During the coldest month, February, this ratio was 0.52 ± 0.04, while during the warmest month, July, this ratio was 0.34 ± 0.04, illustrating that NO2 is not well mixed within 0.5 km above ground level. Good correlation was observed between the remotely sensed and in situ NO2 vertical column densities (Pearson's R value ranging from 0.72 to 0.81), but the in situ vertical column densities were 52 to 58% greater than the remotely sensed columns. These results indicate that NO2 horizontal heterogeneity strongly impacted the magnitude of the remotely sensed columns. The in situ columns reflected an urban environment with major traffic sources, while the remotely sensed NO2 vertical column densities were representative of the region, which included spatial heterogeneity introduced by residential neighbourhoods and Lake Ontario. Despite the difference in absolute values, the reasonable correlation between the vertical column densities determined by three distinct methods increased confidence in the validity of the values provided by each measurement technique.

Analysis on the application of background parameters on remote sensing classification

NASA Astrophysics Data System (ADS)

Qiao, Y.

Drawing accurate crop cultivation acreage, dynamic monitoring of crops growing and yield forecast are some important applications of remote sensing to agriculture. During the 8th 5-Year Plan period, the task of yield estimation using remote sensing technology for the main crops in major production regions in China once was a subtopic to the national research task titled "Study on Application of Remote sensing Technology". In 21 century in a movement launched by Chinese Ministry of Agriculture to combine high technology to farming production, remote sensing has given full play to farm crops' growth monitoring and yield forecast. And later in 2001 Chinese Ministry of Agriculture entrusted the Northern China Center of Agricultural Remote Sensing to forecast yield of some main crops like wheat, maize and rice in rather short time to supply information for the government decision maker. Present paper is a report for this task. It describes the application of background parameters in image recognition, classification and mapping with focuses on plan of the geo-science's theory, ecological feature and its cartographical objects or scale, the study of phrenology for image optimal time for classification of the ground objects, the analysis of optimal waveband composition and the application of background data base to spatial information recognition ;The research based on the knowledge of background parameters is indispensable for improving the accuracy of image classification and mapping quality and won a secondary reward of tech-science achievement from Chinese Ministry of Agriculture. Keywords: Spatial image; Classification; Background parameter

Hyperspectral remote sensing study of harmful algal blooms in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Nie, Yixiang

Recent development of hyperspectral remote sensing provides capability to identify and classify harmful algal blooms beyond the estimation of chlorophyll concentrations. This study uses hyperspectral data to extract spectral signatures, classify algal blooms, and map the spatial distribution of the algal blooms in the upper Chesapeake Bay. Furthermore, water quality parameters from ground stations have been used together with remote sensing data to provide better understanding of the formation and transformation of the life cycle of harmful algal blooms, and the cause of their outbreaks in the upper Chesapeake Bay. The present results show a strong and significant positive correlation between chlorophyll concentrations and total organic nitrogen concentrations. This relation suggests that total organic nitrogen played an important role in triggering the harmful algal blooms in the upper Chesapeake Bay in this study. This study establishes an integrated approach which combines hyperspectral imaging with multispectral ocean color remote sensing data and traditional water quality monitoring system in the study of harmful algal blooms in small water bodies such as the Chesapeake Bay. Presently, remote sensing is well integrated into the research community, but is less commonly used by resource managers. This dissertation couples remote sensing technologies with specific monitoring programs. The present results will help natural resource managers, local authorities, and the public to utilize an integrated approach in order to better understand, evaluate, preserve, and restore the health of the Chesapeake Bay waters and habitats.

A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective

NASA Astrophysics Data System (ADS)

Shafique, Muhammad; van der Meijde, Mark; Khan, M. Asif

2016-03-01

The 8th October 2005 Kashmir earthquake, in northern Pakistan has triggered thousands of landslides, which was the second major factor in the destruction of the build-up environment, after earthquake-induced ground shaking. Subsequent to the earthquake, several researchers from home and abroad applied a variety of remote sensing techniques, supported with field observations, to develop inventories of the earthquake-triggered landslides, analyzed their spatial distribution and subsequently developed landslide-susceptibility maps. Earthquake causative fault rupture, geology, anthropogenic activities and remote sensing derived topographic attributes were observed to have major influence on the spatial distribution of landslides. These were subsequently used to develop a landslide susceptibility map, thereby demarcating the areas prone to landsliding. Temporal studies monitoring the earthquake-induced landslides shows that the earthquake-induced landslides are stabilized, contrary to earlier belief, directly after the earthquake. The biggest landslide induced dam, as a result of the massive Hattian Bala landslide, is still posing a threat to the surrounding communities. It is observed that remote sensing data is effectively and efficiently used to assess the landslides triggered by the Kashmir earthquake, however, there is still a need of more research to understand the mechanism of intensity and distribution of landslides; and their continuous monitoring using remote sensing data at a regional scale. This paper, provides an overview of remote sensing and GIS applications, for the Kashmir-earthquake triggered landslides, derived outputs and discusses the lessons learnt, advantages, limitations and recommendations for future research.

Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

2015-08-01

GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

Remote sensing in the coming decade: the vision and the reality

NASA Astrophysics Data System (ADS)

Gail, William B.

2006-08-01

Investment in understanding the Earth pays off twice. It enables pursuit of scientific questions that rank among the most interesting and profound of our time. It also serves society's practical need for increased prosperity and security. Over the last half-century, we have built a sophisticated network of satellites, aircraft, and ground-based remote sensing systems to provide the raw information from which we derive Earth knowledge. This network has served us well in the development of science and the provision of operational services. In the next decade, the demand for such information will grow dramatically. New remote sensing capabilities will emerge. Rapid evolution of Internet geospatial and location-based services will make communication and sharing of Earth knowledge much easier. Governments, businesses, and consumers will all benefit. But this exciting future is threatened from many directions. Risks range from technology and market uncertainties in the private sector to budget cuts and project setbacks in the public sector. The coming decade will see a dramatic confrontation between the vision of what needs to be accomplished in Earth remote sensing and the reality of our resources and commitment. The outcome will have long-term implications for both the remote sensing community and society as a whole.

The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina

NASA Technical Reports Server (NTRS)

Shain, W.; Nix, L.

1982-01-01

Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

NASA Astrophysics Data System (ADS)

Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

2016-05-01

Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

Radar remote sensing for archaeology in Hangu Frontier Pass in Xin’an, China

NASA Astrophysics Data System (ADS)

Jiang, A. H.; Chen, F. L.; Tang, P. P.; Liu, G. L.; Liu, W. K.; Wang, H. C.; Lu, X.; Zhao, X. L.

2017-02-01

As a non-invasive tool, remote sensing can be applied to archaeology taking the advantage of large scale covering, in-time acquisition, high spatial-temporal resolution and etc. In archaeological research, optical approaches have been widely used. However, the capability of Synthetic Aperture Radar (SAR) for archaeological detection has not been fully exploded so far. In this study, we chose Hangu Frontier Pass of Han Dynasty located in Henan Province as the experimental site (included into the cluster of Silk Roads World Heritage sites). An exploratory study to detect the historical remains was conducted. Firstly, TanDEM-X SAR data were applied to generate high resolution DEM of Hangu Frontier Pass; and then the relationship between the pass and derived ridge lines was analyzed. Second, the temporal-averaged amplitude SAR images highlighted archaeological traces owing to the depressed speckle noise. For instance, the processing of 20-scene PALSAR data (spanning from 2007 to 2011) enabled us to detect unknown archaeological features. Finally, the heritage remains detected by SAR data were verified by Ground Penetrating Radar (GPR) prospecting, implying the potential of the space-to-ground radar remote sensing for archaeological applications.

Ground based remote sensing retrievals and observations of snowfall in the Telemark region of Norway

NASA Astrophysics Data System (ADS)

Pettersen, C.; L'Ecuyer, T. S.; Wood, N.; Cooper, S.; Wolff, M. A.; Petersen, W. A.; Bliven, L. F.; Tushaus, S. A.

2017-12-01

Snowfall can be broadly categorized into deep and shallow events, based on the vertical extent of the frozen precipitation in the column. The two categories are driven by different thermodynamic and physical mechanisms in the atmosphere and surface. Though satellites can observe and recognize these patterns in snowfall, these measurements are limited - particularly in cases of shallow and light precipitation and over complex terrain. By enhancing satellite measurements with ground-based instrumentation, whether with limited-term field campaigns or long-term strategic sites, we can further our understanding and assumptions about different snowfall modes. We present data collected in a recently deployed ground suite of instruments based in Norway. The Meteorological Institute of Norway has a snow measurement suite in Haukeliseter located in the orographically complex Telemark region. This suite consists of several snow accumulation instruments as well as meteorological data (temperature, dew point, wind speeds and directions). A joint project between University of Wisconsin and University of Utah augmented this suite with a 24 GHz radar MicroRain Radar (MRR), a NASA Particle Imaging Package (PIP), and a Multi-Angle Snowflake Camera (MASC). Preliminary data from this campaign are presented along with coincident overpasses from the GPM satellite. We compare the ground-based and spaceborne remotely sensed estimates of snowfall with snow gauge observations from the Haukeliseter site. Finally, we discuss how particle size distribution and fall velocity observations from the PIP and MASC can be used to improve remotely-sensed snowfall retrievals as a function of environmental conditions at Haukeliseter.

A review of the remote sensing of lower-tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles

DOE PAGES

Wulfmeyer, Volker; Hardesty, Mike; Turner, David D.; ...

2015-07-08

A review of remote sensing technology for lower-tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land-surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer – usually characterized by an inversion – andmore » the lower troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global positioning system as well as water-vapor and temperature Raman lidar and water-vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

A review of the remote sensing of lower-tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles

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

Wulfmeyer, Volker; Hardesty, Mike; Turner, David D.

A review of remote sensing technology for lower-tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land-surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer – usually characterized by an inversion – andmore » the lower troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global positioning system as well as water-vapor and temperature Raman lidar and water-vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.« less

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.; Ambrosia, Vincent G.

1996-01-01

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

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.

Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

NASA Astrophysics Data System (ADS)

Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

2016-08-01

Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

Remote sensing of forest canopy and leaf biochemical contents

NASA Technical Reports Server (NTRS)

Peterson, David L.; Matson, Pamela A.; Card, Don H.; Aber, John D.; Wessman, Carol; Swanberg, Nancy; Spanner, Michael

1988-01-01

Recent research on the remote sensing of forest leaf and canopy biochemical contents suggests that the shortwave IR region contains this information; laboratory analyses of dry ground leaves have yielded reliable predictive relationships between both leaf nitrogen and lignin with near-IR spectra. Attention is given to the application of these laboratory techniques to a limited set of spectra from fresh, whole leaves of conifer species. The analysis of Airborne Imaging Spectrometer data reveals that total water content variations in deciduous forest canopies appear as overall shifts in the brightness of raw spectra.

AgRISTARS: Foreign commodity production forecasting. Country summary report, Australia

NASA Technical Reports Server (NTRS)

Henninger, D. L.; Reed, C. R. (Principal Investigator)

1981-01-01

Australia is one of the world's major growers and exporters of wheat and as such is one of the countries of interest in the AgRISTARS program which endeavors to develop technology to estimate crop production using aerospace remote sensing. A compilation of geographic, political, and agricultural information on Australia is presented. Also included is a summary of the aerospace remote sensing, meteorological, and ground-observed data which were collected with respect to Australia, as well as a summary of contacts between AgRISTARS and Australia personnel.

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Kimes, Daniel S.; Kharuk, Vyetcheslav I.

2007-01-01

Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.

A micro-vibration generated method for testing the imaging quality on ground of space remote sensing

NASA Astrophysics Data System (ADS)

Gu, Yingying; Wang, Li; Wu, Qingwen

2018-03-01

In this paper, a novel method is proposed, which can simulate satellite platform micro-vibration and test the impact of satellite micro-vibration on imaging quality of space optical remote sensor on ground. The method can generate micro-vibration of satellite platform in orbit from vibrational degrees of freedom, spectrum, magnitude, and coupling path. Experiment results show that the relative error of acceleration control is within 7%, in frequencies from 7Hz to 40Hz. Utilizing this method, the system level test about the micro-vibration impact on imaging quality of space optical remote sensor can be realized. This method will have an important applications in testing micro-vibration tolerance margin of optical remote sensor, verifying vibration isolation and suppression performance of optical remote sensor, exploring the principle of micro-vibration impact on imaging quality of optical remote sensor.

An algorithm for retrieving rock-desertification from multispectral remote sensing images

NASA Astrophysics Data System (ADS)

Xia, Xueqi; Tian, Qingjiu; Liao, Yan

2009-06-01

Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

Comparison of Balloonsonde and Remote Sensing Atmospheric Measurements

NASA Technical Reports Server (NTRS)

Brinker, David J.; Reehorst, Andrew L.; Power, Jack

2006-01-01

As part of its aircraft icing research program, the NASA Glenn Research Center is conducting a program to develop technologies for the remote sensing of atmospheric conditions. A suite of instruments, currently ground-based, are used to identify a region of supercooled liquid water which is labeled as hazardous if its liquid water content is sufficiently high. During the recently completed Alliance Icing Research Study (AIRS II), these instruments were deployed in conjunction with those of other U.S. and Canadian researchers at the Mirabel Airport near Montreal. As part of the study, balloonsondes were employed to provide in-situ measurement of the atmospheric conditions that were being concurrently remotely sensed. Balloonsonde launches occurred daily at 1200 GMT to provide AIRS forecasters with local data and additionally when research aircraft were present in the airspace. In this paper, we compare the processed data from the NASA remote sensing instruments, which included an X-band radar, lidar and two radiometers, to the data gathered from the 70 soundings conducted while the NASA instruments were active. Among the parameters compared are cloud upper and lower boundaries, temperature and humidity profiles and freezing levels.

Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

Remote sensing is widely applied to provide information of areas with limited ground access with applications such as to assess the destruction from natural disasters and to plan relief and recovery operations. However, the data collection of aerial digital images is constrained by bad weather, atmospheric conditions, and unstable camera or camcorder. Therefore, how to recover the information from the low-quality remote sensing images and how to enhance the image quality becomes very important for many visual understanding tasks, such like feature detection, object segmentation, and object recognition. The quality of remote sensing imagery can be improved through meaningful combination of the employed images captured from different sensors or from different conditions through information fusion. Here we particularly address information fusion to remote sensing images under multi-resolution analysis in the employed image sequences. The image fusion is to recover complete information by integrating multiple images captured from the same scene. Through image fusion, a new image with high-resolution or more perceptive for human and machine is created from a time series of low-quality images based on image registration between different video frames.

Remote Sensing of Water Quality in Multipurpose Reservoirs: Case Study Applications in Indonesia, Mexico, and Uruguay

NASA Astrophysics Data System (ADS)

Miralles-Wilhelm, F.; Serrat-Capdevila, A.; Rodriguez, D.

2017-12-01

This research is focused on development of remote sensing methods to assess surface water pollution issues, particularly in multipurpose reservoirs. Three case study applications are presented to comparatively analyze remote sensing techniquesforo detection of nutrient related pollution, i.e., Nitrogen, Phosphorus, Chlorophyll, as this is a major water quality issue that has been identified in terms of pollution of major water sources around the country. This assessment will contribute to a better understanding of options for nutrient remote sensing capabilities and needs and assist water agencies in identifying the appropriate remote sensing tools and devise an application strategy to provide information needed to support decision-making regarding the targeting and monitoring of nutrient pollution prevention and mitigation measures. A detailed review of the water quality data available from ground based measurements was conducted in order to determine their suitability for a case study application of remote sensing. In the first case study, the Valle de Bravo reservoir in Mexico City reservoir offers a larger database of water quality which may be used to better calibrate and validate the algorithms required to obtain water quality data from remote sensing raw data. In the second case study application, the relatively data scarce Lake Toba in Indonesia can be useful to illustrate the value added of remote sensing data in locations where water quality data is deficient or inexistent. The third case study in the Paso Severino reservoir in Uruguay offers a combination of data scarcity and persistent development of harmful algae blooms. Landsat-TM data was obteined for the 3 study sites and algorithms for three key water quality parameters that are related to nutrient pollution: Chlorophyll-a, Total Nitrogen, and Total Phosphorus were calibrated and validated at the study sites. The three case study applications were developed into capacity building/training workshops for water resources students, applied scientists, practitioners, reservoir and water quality managers, and other interested stakeholders.

Remote sensing strategies for global resource exploration and environmental management

NASA Astrophysics Data System (ADS)

Henderson, Frederick B.

Since 1972, satellite remote sensing, when integrated with other exploration techniques, has demonstrated operational exploration and engineering cost savings and reduced exploration risks through improved geological mapping. Land and ocean remote sensing satellite systems under development for the 1990's by the United States, France, Japan, Canada, ESA, Russia, China, and others, will significantly increase our ability to explore for, develop, and manage energy and mineral resources worldwide. A major difference between these systems is the "Open Skies" and "Non-Discriminatory Access to Data" policies as have been practiced by the U.S. and France and the restrictive nationalistic data policies as have been practiced by Russia and India. Global exploration will use satellite remote sensing to better map regional structural and basin-like features that control the distribution of energy and mineral resources. Improved sensors will better map lithologic and stratigraphic units and identify alteration effects in rocks, soils, and vegetation cover indicative of undiscovered subsurface resources. These same sensors will also map and monitor resource development. The use of satellite remote sensing data will grow substantially through increasing integration with other geophysical, geochemical, and geologic data using improved geographic information systems (GIS). International exploration will focus on underdeveloped countries rather than on mature exploration areas such as the United States, Europe, and Japan. Energy and mineral companies and government agencies in these countries and others will utilize available remote sensing data to acquire economic intelligence on global resources. If the "Non-Discriminatory Access to Data" principle is observed by satellite producing countries, exploration will remain competitive "on the ground". In this manner, remote sensing technology will continue to be developed to better explore for and manage the world's needed resources. If, however, satellite producing countries follow the Russian and Indian lead and restrict civil satellite data as tools of their national security and economic policies, remote sensing technology may become internationally competitive in space, redundant, prohibitively expensive, and generally unavailable to the world community.

The investigation of advanced remote sensing, radiative transfer and inversion techniques for the measurement of atmospheric constituents

NASA Technical Reports Server (NTRS)

Deepak, Adarsh; Wang, Pi-Huan

1985-01-01

The research program is documented for developing space and ground-based remote sensing techniques performed during the period from December 15, 1977 to March 15, 1985. The program involved the application of sophisticated radiative transfer codes and inversion methods to various advanced remote sensing concepts for determining atmospheric constituents, particularly aerosols. It covers detailed discussions of the solar aureole technique for monitoring columnar aerosol size distribution, and the multispectral limb scattered radiance and limb attenuated radiance (solar occultation) techniques, as well as the upwelling scattered solar radiance method for determining the aerosol and gaseous characteristics. In addition, analytical models of aerosol size distribution and simulation studies of the limb solar aureole radiance technique and the variability of ozone at high altitudes during satellite sunrise/sunset events are also described in detail.

The promise of remote sensing in the atmospheric sciences

NASA Technical Reports Server (NTRS)

Atlas, D.

1981-01-01

The applications and advances in remote sensing technology for weather prediction, mesoscale meteorology, severe storms, and climate studies are discussed. Doppler radar permits tracking of the three-dimensional field of motion within storms, thereby increasing the accuracy of convective storm modeling. Single Doppler units are also employed for detecting mesoscale storm vortices and tornado vortex signatures with lead times of 30 min. Clear air radar in pulsed and high resolution FM-CW forms reveals boundary layer convection, Kelvin-Helmoltz waves, shear layer turbulence, and wave motions. Lidar is successfully employed for stratospheric aerosol measurements, while Doppler lidar provides data on winds from the ground and can be based in space. Sodar is useful for determining the structure of the PBL. Details and techniques of satellite-based remote sensing are presented, and results from the GWE and FGGE experiments are discussed.

Preliminary Findings of Inflight Icing Field Test to Support Icing Remote Sensing Technology Assessment

NASA Technical Reports Server (NTRS)

King, Michael; Reehorst, Andrew; Serke, Dave

2015-01-01

NASA and the National Center for Atmospheric Research have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize a vertical pointing cloud radar, a multifrequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport.

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.

Middle Term Achievements of Project 5322: Retrieval Of Key Eco-Hydrological Parameters From Remote Sensing In The Watershed Allied Telemetry Experimental Research (Water)

NASA Astrophysics Data System (ADS)

Li, Xin; Menenti, Massimo

2010-10-01

The general objective of project 5322 in the Dragon 2 programme is to quantitatively retrieve some key eco- hydrological parameters by using remote sensed data, especially from ESA, Chinese, and the Third Party Mission (TPM). To achieve this goal, a comprehensive observation experiment, Watershed Allied Telemetry Experimental Research (WATER) was carried out. WARER is a simultaneously airborne, satellite-borne, and ground-based remote sensing experiment took place in the Heihe River Basin, a typical inland river basin in the northwest of China. This paper introduces the background and implementation of WATER. Data have been obtained so far are described in details. After a period of data analysis for two years, numerous results have also been achieved. This paper presents some early results of WATER as well.

Remote sensing for prediction of 1-year post-fire ecosystem condition

Treesearch

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

2009-01-01

Appropriate use of satellite data in predicting >1 year post-fire effects requires remote measurement of surface properties that can be mechanistically related to ground measures of post-fire condition. The present study of burned ponderosa pine (Pinus ponderosa) forests in the Black Hills of South Dakota evaluates whether immediate fractional cover estimates of...

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Kimes, Daniel; Sun, Guoqing; Kharuk, Viatcheslav; Hyde, Peter; Nelson, Ross

2007-01-01

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Remote sensing of natural resources

NASA Technical Reports Server (NTRS)

1976-01-01

Quarterly literature review compiles citations and abstracts from eight major abstracting and indexing services. Each issue contains author/keyword index. Includes data obtained or techniques used from space, aircraft, or ground-based stations.

Application of remote sensing in agriculture and forestry and ground truth documentation in resource planning

NASA Technical Reports Server (NTRS)

1974-01-01

Varied small scale imagery was used for detecting and assessing damage by the southern pine beetle. The usefulness of ERTS scanner imagery for vegetation classification and pine beetle damage detection and assessment is evaluated. Ground truth acquisition for forest identification using multispectral aerial photographs is reviewed.

Cover estimations using object-based image analysis rule sets developed across multiple scales in pinyon-juniper woodlands

USDA-ARS?s Scientific Manuscript database

Numerous studies have been conducted that evaluate the utility of remote sensing for monitoring and assessing vegetation and ground cover to support land management decisions and complement ground-measurements. However, few land cover comparisons have been made using high-resolution imagery and obj...

Irrigation management with remote sensing. [alfalfa plots in new mexico

NASA Technical Reports Server (NTRS)

Heilman, J.; Moore, D.; Myers, V.

1980-01-01

A ground study conducted utilizing hand held radiometers to collect visible, near infrared and thermal infrared measurements. The data was analyzed and evaluated in terms of the ground measurements, which included percent crop canopy cover. The results used to recommend future action regarding use of satellite data in irrigation management.

Postfire soil burn severity mapping with hyperspectral image unmixing

Treesearch

Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

2017-08-01

Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms should be developed to retrieve snow depth with higher spatial resolution and should consider the variation in brightness temperatures at different frequencies emitted from ground with changing ground features.

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).

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

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

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

1993-04-01

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

Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status

NASA Astrophysics Data System (ADS)

Schmidt, Johannes; Fassnacht, Fabian Ewald; Neff, Christophe; Lausch, Angela; Kleinschmit, Birgit; Förster, Michael; Schmidtlein, Sebastian

2017-08-01

Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing. Hence, the transfer of field guidelines to remote sensing indicators was rather successful in this case but needs further evaluation for other habitats.

Non-Lambertian effects on remote sensing of surface reflectance and vegetation index

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kaufman, Y. J.

1986-01-01

This paper discusses the effects of non-Lambertian reflection from a homogeneous surface on remote sensing of the surface reflectance and vegetation index from a satellite. Remote measurement of the surface characteristics is perturbed by atmospheric scattering of sun light. This scattering tends to smooth the angular dependence of non-Lambertian surface reflectances, an effect that is not present in the case of Lambertian surfaces. This effect is calculated to test the validity of a Lambertian assumption used in remote sensing. For the three types of vegetations considered in this study, the assumption of Lambertian surface can be used satisfactorily in the derivation of surface reflectance from remotely measured radiance for a view angle outside the backscattering region. Within the backscattering region, however, the use of the assumption can result in a considerable error in the derived surface reflectance. Accuracy also deteriorates with increasing solar zenith angle. The angular distribution of the surface reflectance derived from remote measurements is smoother than that at the surface. The effect of surface non-Lambertianity on remote sensing of vegetation index is very weak. Since the effect is similiar in the visible and near infrared part of the solar spectrum for the vegetations treated in this study, it is canceled in deriving the vegetation index. The effect of the diffuse skylight on surface reflectance measurements at ground level is also discussed.

Overview of SnowEx Year 1 Activities

NASA Technical Reports Server (NTRS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Newlin, Jerry; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Heimstra, Chris; Brucker, Ludovic; De Marco, Eugenia;

Aerosol Remote Sensing from AERONET, the Ground-Based Satellite

NASA Technical Reports Server (NTRS)

Holben, Brent N.

2012-01-01

Atmospheric particles including mineral dust, biomass burning smoke, pollution from carbonaceous aerosols and sulfates, sea salt, impact air quality and climate. The Aerosol Robotic Network (AERONET) program, established in the early 1990s, is a federation of ground-based remote sensing aerosol networks of Sun/sky radiometers distributed around the world, which provides a long-term, continuous and readily accessible public domain database of aerosol optical (e.g., aerosol optical depth) and microphysical (e.g., aerosol volume size distribution) properties for aerosol characterization, validation of satellite retrievals, and synergism with Earth science databases. Climatological aerosol properties will be presented at key worldwide locations exhibiting discrete dominant aerosol types. Further, AERONET's temporary mesoscale network campaign (e.g., UAE2, TIGERZ, DRAGON-USA.) results that attempt to quantify spatial and temporal variability of aerosol properties, establish validation of ground-based aerosol retrievals using aircraft profile measurements, and measure aerosol properties on compatible spatial scales with satellite retrievals and aerosol transport models allowing for more robust validation will be discussed.

Operational considerations for the application of remotely sensed forest data from LANDSAT or other airborne platforms

NASA Technical Reports Server (NTRS)

Baker, G. R.; Fethe, T. P.

1975-01-01

Research in the application of remotely sensed data from LANDSAT or other airborne platforms to the efficient management of a large timber based forest industry was divided into three phases: (1) establishment of a photo/ground sample correlation, (2) investigation of techniques for multi-spectral digital analysis, and (3) development of a semi-automated multi-level sampling system. To properly verify results, three distinct test areas were selected: (1) Jacksonville Mill Region, Lower Coastal Plain, Flatwoods, (2) Pensacola Mill Region, Middle Coastal Plain, and (3) Mississippi Mill Region, Middle Coastal Plain. The following conclusions were reached: (1) the probability of establishing an information base suitable for management requirements through a photo/ground double sampling procedure, alleviating the ground sampling effort, is encouraging, (2) known classification techniques must be investigated to ascertain the level of precision possible in separating the many densities involved, and (3) the multi-level approach must be related to an information system that is executable and feasible.

Need for expanded environmental measurement capabilities in geosynchronous Earth orbit

NASA Technical Reports Server (NTRS)

Mercanti, Enrico P.

1991-01-01

The proliferation of environmental satellites in low altitude earth orbit (LEO) has demonstrated the usefulness of earth remote sensing from space. As use of the technology grows, the limitations of LEO missions become more apparent. Many inadequacies can be met by remote sensing from geosynchronous earth orbits (GEO) that can provide high temporal resolution, consistent viewing of specific earth targets, long sensing dwell times with varying sun angles, stereoscopic coverage, and correlative measurements with ground and LEO observations. An environmental platform in GEO is being studied by NASA. Small research satellite missions in GEO were studied (1990) at GSFC. Some recent independent assessments of NASA Earth Science Programs recommend accelerating the earlier deployment of smaller missions.

Lagrange constraint neural networks for massive pixel parallel image demixing

NASA Astrophysics Data System (ADS)

Szu, Harold H.; Hsu, Charles C.

2002-03-01

We have shown that the remote sensing optical imaging to achieve detailed sub-pixel decomposition is a unique application of blind source separation (BSS) that is truly linear of far away weak signal, instantaneous speed of light without delay, and along the line of sight without multiple paths. In early papers, we have presented a direct application of statistical mechanical de-mixing method called Lagrange Constraint Neural Network (LCNN). While the BSAO algorithm (using a posteriori MaxEnt ANN and neighborhood pixel average) is not acceptable for remote sensing, a mirror symmetric LCNN approach is all right assuming a priori MaxEnt for unknown sources to be averaged over the source statistics (not neighborhood pixel data) in a pixel-by-pixel independent fashion. LCNN reduces the computation complexity, save a great number of memory devices, and cut the cost of implementation. The Landsat system is designed to measure the radiation to deduce surface conditions and materials. For any given material, the amount of emitted and reflected radiation varies by the wavelength. In practice, a single pixel of a Landsat image has seven channels receiving 0.1 to 12 microns of radiation from the ground within a 20x20 meter footprint containing a variety of radiation materials. A-priori LCNN algorithm provides the spatial-temporal variation of mixture that is hardly de-mixable by other a-posteriori BSS or ICA methods. We have already compared the Landsat remote sensing using both methods in WCCI 2002 Hawaii. Unfortunately the absolute benchmark is not possible because of lacking of the ground truth. We will arbitrarily mix two incoherent sampled images as the ground truth. However, the constant total probability of co-located sources within the pixel footprint is necessary for the remote sensing constraint (since on a clear day the total reflecting energy is constant in neighborhood receiving pixel sensors), we have to normalized two image pixel-by-pixel as well. Then, the result is indeed as expected.

Tephra dispersal and fallout reconstructed integrating field, ground-based and satellite-based data: Application to the 23rd November 2013 Etna paroxysm

NASA Astrophysics Data System (ADS)

Poret, M.; Corradini, S.; Merucci, L.; Costa, A.; Andronico, D.; Montopoli, M.; Vulpiani, G.; Scollo, S.; Freret-Lorgeril, V.

2017-12-01

On the 23rd November 2013, Etna erupted giving one of the most intense lava fountain recorded. The eruption produced a buoyant plume that rose higher than 10 km a.s.l. from which two volcanic clouds were observed from satellite at two different atmospheric levels. A Previous study described one of the two clouds as mainly composed by ash making use of remote sensing instruments. Besides, the second cloud is made of ice/SO2 droplets and is not measurable in terms of ash mass. Both clouds spread out under north-easterly winds transporting the tephra from Etna towards the Puglia region. The untypical meteorological conditions permit to collect tephra samples in proximal areas to the Etna emission source as well as far away in the Calabria region. The eruption was observed by satellite (MSG-SEVIRI, MODIS) and ground-based (X-band weather radar, VIS/IR cameras and L-band Doppler radar) remote sensing systems. This study uses the FALL3D code to model the evolution of the plume and the tephra deposition by constraining the simulation results with remote sensing products for volcanic cloud (cloud height, fine ash Mass - Ma, Aerosol Optical Depth at 0.55 mm - AOD). Among the input parameters, the Total Grain-Size Distribution (TGSD) is reconstructed by integrating field deposits with estimations from the X-band radar data. The optimal TGSD was selected through an inverse problem method that best-fits both the field deposits and airborne measurements. The results of the simulations capture the main behavior of the two volcanic clouds at their altitudes. The best agreement between the simulated Ma and AOD and the SEVIRI retrievals indicates a PM20 fraction of 3.4 %. The total erupted mass is estimated at 1.6 × 109 kg in consistency with the estimations made from remote sensing data (3.0 × 109 kg) and ground deposit (1.3 × 109 kg).

Remote Sensing of Vegetation Species Diversity: The Utility of Integrated Airborne Hyperspectral and Lidar Data

NASA Astrophysics Data System (ADS)

Krause, Keith Stuart

The change, reduction, or extinction of species is a major issue currently facing the Earth. Efforts are underway to measure, monitor, and protect habitats that contain high species diversity. Remote sensing technology shows extreme value for monitoring species diversity by mapping ecosystems and using those land cover maps or other derived data as proxies to species number and distribution. The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) consists of remote sensing instruments such as an imaging spectrometer, a full-waveform lidar, and a high-resolution color camera. AOP collected data over the Ordway-Swisher Biological Station (OSBS) in May 2014. A majority of the OSBS site is covered by the Sandhill ecosystem, which contains a very high diversity of vegetation species and is a native habitat for several threatened fauna species. The research presented here investigates ways to analyze the AOP data to map ecosystems at the OSBS site. The research attempts to leverage the high spatial resolution data and study the variability of the data within a ground plot scale along with integrating data from the different sensors. Mathematical features are derived from the data and brought into a decision tree classification algorithm (rpart), in order to create an ecosystem map for the site. The hyperspectral and lidar features serve as proxies for chemical, functional, and structural differences in the vegetation types for each of the ecosystems. K-folds cross validation shows a training accuracy of 91%, a validation accuracy of 78%, and a 66% accuracy using independent ground validation. The results presented here represent an important contribution to utilizing integrated hyperspectral and lidar remote sensing data for ecosystem mapping, by relating the spatial variability of the data within a ground plot scale to a collection of vegetation types that make up a given ecosystem.

In situ Volcanic Plume Monitoring with small Unmanned Aerial Systems for Cal/Val of Satellite Remote Sensing Data: CARTA-UAV 2013 Mission (Invited)

NASA Astrophysics Data System (ADS)

Diaz, J. A.; Pieri, D. C.; Bland, G.; Fladeland, M. M.

2013-12-01

The development of small unmanned aerial systems (sUAS) with a variety of sensor packages, enables in situ and proximal remote sensing measurements of volcanic plumes. Using Costa Rican volcanoes as a Natural Laboratory, the University of Costa Rica as host institution, in collaboration with four NASA centers, have started an initiative to develop low-cost, field-deployable airborne platforms to perform volcanic gas & ash plume research, and in-situ volcanic monitoring in general, in conjunction with orbital assets and state-of-the-art models of plume transport and composition. Several gas sensors have been deployed into the active plume of Turrialba Volcano including a miniature mass spectrometer, and an electrochemical SO2 sensor system with temperature, pressure, relative humidity, and GPS sensors. Several different airborne platforms such as manned research aircraft, unmanned aerial vehicles, tethered balloons, as well as man-portable in-situ ground truth systems are being used for this research. Remote sensing data is also collected from the ASTER and OMI spaceborne instruments and compared with in situ data. The CARTA-UAV 2013 Mission deployment and follow up measurements successfully demonstrated a path to study and visualize gaseous volcanic emissions using mass spectrometer and gas sensor based instrumentation in harsh environment conditions to correlate in situ ground/airborne data with remote sensing satellite data for calibration and validation purposes. The deployment of such technology improves on our current capabilities to detect, analyze, monitor, model, and predict hazards presented to aircraft by volcanogenic ash clouds from active and impending volcanic eruptions.

Airborne in situ vertical profiling of HDO / H216O in the subtropical troposphere during the MUSICA remote sensing validation campaign

NASA Astrophysics Data System (ADS)

Dyroff, C.; Sanati, S.; Christner, E.; Zahn, A.; Balzer, M.; Bouquet, H.; McManus, J. B.; Gonzalez-Ramos, Y.; Schneider, M.

2015-05-01

Vertical profiles of water vapor (H2O) and its isotope ratio D / H expressed as δD(H2O) were measured in situ by the ISOWAT II diode-laser spectrometer during the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) airborne campaign. We present recent modifications of the instrument design. The instrument calibration on the ground as well as in flight is described. Based on the calibration measurements, the humidity-dependent uncertainty of our airborne data is determined. For the majority of the airborne data we achieved an accuracy (uncertainty of the mean) of Δ(δD) ≈10‰. Vertical profiles between 150 and ~7000 m were obtained during 7 days in July and August 2013 over the subtropical North Atlantic Ocean near Tenerife. The flights were coordinated with ground-based (Network for the Detection of Atmospheric Composition Change, NDACC) and space-based (Infrared Atmospheric Sounding Interferometer, IASI) FTIR remote sensing measurements of δD(H2O) as a means to validate the remote sensing humidity and δD(H2O) data products. The results of the validation are presented in detail in a separate paper (Schneider et al., 2014). The profiles were obtained with a high vertical resolution of around 3 m. By analyzing humidity and δD(H2O) correlations we were able to identify different layers of air masses with specific isotopic signatures. The results are discussed.

The Feasibility Evaluation of Land Use Change Detection Using GAOFEN-3 Data

NASA Astrophysics Data System (ADS)

Huang, G.; Sun, Y.; Zhao, Z.

2018-04-01

GaoFen-3 (GF-3) satellite, is the first C band and multi-polarimetric Synthetic Aperture Radar (SAR) satellite in China. In order to explore the feasibility of GF-3 satellite in remote sensing interpretation and land-use remote sensing change detection, taking Guangzhou, China as a study area, the full polarimetric image of GF-3 satellite with 8 m resolution of two temporal as the data source. Firstly, the image is pre-processed by orthorectification, image registration and mosaic, and the land-use remote sensing digital orthophoto map (DOM) in 2017 is made according to the each county. Then the classification analysis and judgment of ground objects on the image are carried out by means of ArcGIS combining with the auxiliary data and using artificial visual interpretation, to determine the area of changes and the category of change objects. According to the unified change information extraction principle to extract change areas. Finally, the change detection results are compared with 3 m resolution TerraSAR-X data and 2 m resolution multi-spectral image, and the accuracy is evaluated. Experimental results show that the accuracy of the GF-3 data is over 75 % in detecting the change of ground objects, and the detection capability of new filling soil is better than that of TerraSAR-X data, verify the detection and monitoring capability of GF-3 data to the change information extraction, also, it shows that GF-3 can provide effective data support for the remote sensing detection of land resources.

Long-term remote monitoring of salt marsh biomass

NASA Astrophysics Data System (ADS)

Gross, M. F.; Klemas, V.; Hardisky, M. A.

1990-12-01

An objective of NASA's Biospheric Research Program is to understand biogeochemical cycling on a global scale. Being both very biologically productive and anoxic, wetlands are major sites of carbon dioxide, mean, and sulfur gas flux on a per area basis. Biogeochemical cycling in wetlands is intricately linked to vegetation biomass production. We have been monitoring biomass dynamics of the dominant salt marsh grass Spartina alterniflora for over ten years using remote sensing. Live above ground biomass is highly correlated (r = .79) with Laridsat Thematic Mapper ('IN) and SPOT spectral data transformed into normalized difference vegetation indices. Live belowg round biomass is, in turn, highly correlated (r = .86) with live above ground biomass. Therefore, below ground biomass, a source of carbon substrates for microbial gas production, can be measured using remote sensing indirectly. These relationships have been tested over a wide latitudinal range (from Georgia to Nova Scotia). Analysis of TM and SPOT satellite images from several years has revealed substantial interannual variability in mean live aerial biomass of this species in a 580ha Delaware marsh. Additionally, interannual spatial variability in biomass distribution within the marsh is evident and seems to be linked to precipitation. The aerial biomass of high salinity areas least influenced by upland runoff is the most sensitive to precipitation, whereas marsh areas adjacent to large upland areas or freshwater creeks are the least sensitive. In summary, remote sensing is an effective tool for studying aboveground and belowground biomass in salt marshes. Once the relationship between gas flux data and vegetation biomass is better understood, satellite data could be used to estimate biomass arid gas flux over large regions of the world.

Estimation of Regional Evapotranspiration Using Remotely Sensed Land Surface Temperature. Part 1: Measurement of Evapotranspiration at the Environmental Research Center and Determination of Priestley-taylor Parameter

NASA Technical Reports Server (NTRS)

Kotada, K.; Nakagawa, S.; Kai, K.; Yoshino, M. M.; Takeda, K.; Seki, K.

1985-01-01

In order to study the distribution of evapotranspiration in the humid region using remote sensing technology, the parameter (alpha) in the Priestley-Taylor model was determined. The daily means of the parameter alpha = 1.14 can be available from summer to autumn and alpha = to approximately 2.0 in winter. The results of the satellite and the airborne sensing done on 21st and 22nd January, 1983, are described. Using the vegetation distribution in the Tsukuba Academic New Town, as well as the radiation temperature obtained by remote sensing and the radiation data observed at the ground surface, the evapotranspiration was calculated for each vegetation type by the Priestley-Taylor method. The daily mean evapotranspiration on 22nd January, 1983, was approximately 0.4 mm/day. The differences in evapotranspiration between the vegetation types were not detectable, because the magnitude of evapotranspiration is very little in winter.

Remote sensing of effects of land-use practices on water quality. [environmental surveys using Landsat satellites

NASA Technical Reports Server (NTRS)

Graves, D. H.

1975-01-01

Research efforts are presented for the use of remote sensing in environmental surveys in Kentucky. Ground truth parameters were established that represent the vegetative cover of disturbed and undisturbed watersheds in the Cumberland Plateau of eastern Kentucky. Several water quality parameters were monitored of the watersheds utilized in the establishment of ground truth data. The capabilities of multistage-multispectral aerial photography and satellite imagery were evaluated in detecting various land use practices. The use of photographic signatures of known land use areas utilizing manually-operated spot densitometers was studied. The correlation of imagery signature data to water quality data was examined. Potential water quality predictions were developed from forested and nonforested watersheds based upon the above correlations. The cost effectiveness of predicting water quality values was evaluated using multistage and satellite imagery sampling techniques.

NASA Computational Case Study SAR Data Processing: Ground-Range Projection

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Rincon, Rafael

2013-01-01

Radar technology is used extensively by NASA for remote sensing of the Earth and other Planetary bodies. In this case study, we learn about different computational concepts for processing radar data. In particular, we learn how to correct a slanted radar image by projecting it on the surface that was sensed by a radar instrument.

Initial Results from Radiometer and Polarized Radar-Based Icing Algorithms Compared to In-Situ Data

NASA Technical Reports Server (NTRS)

Serke, David; Reehorst, Andrew L.; King, Michael

2015-01-01

In early 2015, a field campaign was conducted at the NASA Glenn Research Center in Cleveland, Ohio, USA. The purpose of the campaign is to test several prototype algorithms meant to detect the location and severity of in-flight icing (or icing aloft, as opposed to ground icing) within the terminal airspace. Terminal airspace for this project is currently defined as within 25 kilometers horizontal distance of the terminal, which in this instance is Hopkins International Airport in Cleveland. Two new and improved algorithms that utilize ground-based remote sensing instrumentation have been developed and were operated during the field campaign. The first is the 'NASA Icing Remote Sensing System', or NIRSS. The second algorithm is the 'Radar Icing Algorithm', or RadIA. In addition to these algorithms, which were derived from ground-based remote sensors, in-situ icing measurements of the profiles of super-cooled liquid water (SLW) collected with vibrating wire sondes attached to weather balloons produced a comprehensive database for comparison. Key fields from the SLW-sondes include air temperature, humidity and liquid water content, cataloged by time and 3-D location. This work gives an overview of the NIRSS and RadIA products and results are compared to in-situ SLW-sonde data from one icing case study. The location and quantity of super-cooled liquid as measured by the in-situ probes provide a measure of the utility of these prototype hazard-sensing algorithms.

Watershed Allied Telemetry Experimental Research

NASA Astrophysics Data System (ADS)

Li, Xin; Li, Xiaowen; Li, Zengyuan; Ma, Mingguo; Wang, Jian; Xiao, Qing; Liu, Qiang; Che, Tao; Chen, Erxue; Yan, Guangjian; Hu, Zeyong; Zhang, Lixin; Chu, Rongzhong; Su, Peixi; Liu, Qinhuo; Liu, Shaomin; Wang, Jindi; Niu, Zheng; Chen, Yan; Jin, Rui; Wang, Weizhen; Ran, Youhua; Xin, Xiaozhou; Ren, Huazhong

2009-11-01

The Watershed Allied Telemetry Experimental Research (WATER) is a simultaneous airborne, satellite-borne, and ground-based remote sensing experiment aiming to improve the observability, understanding, and predictability of hydrological and related ecological processes at a catchment scale. WATER consists of the cold region, forest, and arid region hydrological experiments as well as a hydrometeorology experiment and took place in the Heihe River Basin, a typical inland river basin in the northwest of China. The field campaigns have been completed, with an intensive observation period lasting from 7 March to 12 April, from 15 May to 22 July, and from 23 August to 5 September 2008: in total, 120 days. Twenty-five airborne missions were flown. Airborne sensors including microwave radiometers at L, K, and Ka bands, imaging spectrometer, thermal imager, CCD, and lidar were used. Various satellite data were collected. Ground measurements were carried out at four scales, that is, key experimental area, foci experimental area, experiment site, and elementary sampling plot, using ground-based remote sensing instruments, densified network of automatic meteorological stations, flux towers, and hydrological stations. On the basis of these measurements, the remote sensing retrieval models and algorithms of water cycle variables are to be developed or improved, and a catchment-scale land/hydrological data assimilation system is being developed. This paper reviews the background, scientific objectives, experiment design, filed campaign implementation, and current status of WATER. The analysis of the data will continue over the next 2 years, and limited revisits to the field are anticipated.

Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

DOE PAGES

Sarna, Karolina; Russchenberg, Herman W. J.

2016-03-14

A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius ( r e) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m -2 wide. For every LWP bin we present the correlation coefficient between ln r e and ln ATB, as well as ACI r (defined as ACI r = -d ln r e d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACI r are in the range 0.01–0.1. In conclusion, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

Impact of NO2 horizontal heterogeneity on tropospheric NO2 vertical columns retrieved from satellite, multi-axis differential optical absorption spectroscopy, and in situ measurements

NASA Astrophysics Data System (ADS)

Mendolia, D.; D'Souza, R. J. C.; Evans, G. J.; Brook, J.

2013-01-01

Tropospheric NO2 vertical column densities were retrieved for the first time in Toronto, Canada using three methods of differing spatial scales. Remotely-sensed NO2 vertical column densities, retrieved from multi-axis differential optical absorption spectroscopy and satellite remote sensing, were evaluated by comparison with in situ vertical column densities derived using a pair of chemiluminescence monitors situated 0.01 and 0.5 km above ground level. The chemiluminescence measurements were corrected for the influence of NOz, which reduced the NO2 concentrations at 0.01 and 0.5 km by 8 ± 1% and 12 ± 1%, respectively. The average absolute decrease in the chemiluminescence NO2 measurement as a result of this correction was less than 1 ppb. Good correlation was observed between the remotely sensed and in situ NO2 vertical column densities (Pearson R ranging from 0.68 to 0.79), but the in situ vertical column densities were 27% to 55% greater than the remotely-sensed columns. These results indicate that NO2 horizontal heterogeneity strongly impacted the magnitude of the remotely-sensed columns. The in situ columns reflected an urban environment with major traffic sources, while the remotely-sensed NO2 vertical column densities were representative of the region, which included spatial heterogeneity introduced by residential neighbourhoods and Lake Ontario. Despite the difference in absolute values, the reasonable correlation between the vertical column densities determined by three distinct methods increased confidence in the validity of the values provided by each of the methods.

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Challenges of Remote Sensing and Spatial Information Education and Technology Transfer in a Fast Developing Industry

NASA Astrophysics Data System (ADS)

Tsai, F.; Chen, L.-C.

2014-04-01

During the past decade, Taiwan has experienced an unusual and fast growing in the industry of mapping, remote sensing, spatial information and related markets. A successful space program and dozens of advanced airborne and ground-based remote sensing instruments as well as mobile mapping systems have been implemented and put into operation to support the vast demands of geospatial data acquisition. Moreover, in addition to the government agencies and research institutes, there are also tens of companies in the private sector providing geo-spatial data and services. However, the fast developing industry is also posing a great challenge to the education sector in Taiwan, especially the higher education for geo-spatial information. Facing this fast developing industry, the demands of skilled professionals and new technologies in order to address diversified needs are indubitably high. Consequently, while delighting in the expanding and prospering benefitted from the fast growing industry, how to fulfill these demands has become a challenge for the remote sensing and spatial information disciplines in the higher education institutes in Taiwan. This paper provides a brief insight into the status of the remote sensing and spatial information industry in Taiwan as well as the challenges of the education and technology transfer to support the increasing demands and to ensure the continuous development of the industry. In addition to the report of the current status of the remote sensing and spatial information related courses and programs in the colleges and universities, current and potential threatening issues and possible resolutions are also discussed in different points of view.

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.

Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

NASA Astrophysics Data System (ADS)

Schneider, M.; González, Y.; Dyroff, C.; Christner, E.; Wiegele, A.; Barthlott, S.; García, O. E.; Sepúlveda, E.; Hase, F.; Andrey, J.; Blumenstock, T.; Guirado, C.; Ramos, R.; Rodríguez, S.

2015-01-01

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isotopologue remote sensing and in situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products, generated from ground-based FTIR (Fourier transform infrared), spectrometer and space-based IASI (infrared atmospheric sounding interferometer) observation. The study is made in the area of the Canary Islands in the subtropical northern Atlantic. As reference we use well calibrated in situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues, and the scatter with respect to the in situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In both remote sensing data sets we find a positive δD bias of 30-70‰. Complementing H2O observations with δD data allows moisture transport studies that are not possible with H2O observations alone. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data. We document that the δD-H2O curves obtained from the different in situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought

Treesearch

Steve Frolking; Stephen Hagen; Bobby Braswell; Tom Milliman; Christina Herrick; Seth Peterson; Dar Roberts; Michael Keller; Michael Palace; Krishna Prasad Vadrevu

2017-01-01

Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon’s vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave...

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Ground-Based Network and Supersite Observations to Complement and Enrich EOS Research

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Holben, Brent N.; Welton, Ellsworth J.

2011-01-01

Since 1997 NASA has been successfully launching a series of satellites - the Earth Observing System (EOS) - to intensively study, and gain a better understanding of, the Earth as an integrated system. Space-borne remote sensing observations, however, are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. Through numerous participations, particularly but not limited to the EOS remote-sensing/retrieval and validation projects over the years, NASA/GSFC has developed and continuously refined ground-based networks and mobile observatories that proved to be vital in providing high temporal measurements, which complement and enrich the satellite observations. These are: the AERO NET (AErosol RObotic NETwork) a federation of ground-based globally distributed network of spectral sun-sky photometers; the MPLNET (Micro-Pulse Lidar NETwork, a similarly organized network of micro-pulse lidar systems measuring aerosol and cloud vertical structure continuously; and the SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere, mobile observatories, a suite of spectral radiometers and in-situ probes acquiring supersite measurements. Most MPLNET sites are collocated with those of AERONET, and both networks always support the deployment of SMART-COMMIT worldwide. These data products follow the data structure of EOS conventions: Level-0, instrument archived raw data; Level-1 (or 1.5), real-time data with no (or limited) quality assurance; Level-2, not real high temporal and spectral resolutions. In this talk, we will present NASA/GSFC groundbased facilities, serving as network or supersite observations, which have been playing key roles in major international research projects over diverse aerosol regimes to complement and enrich the EOS scientific research.

Application of Multi-Source Remote Sensing Image in Yunnan Province Grassland Resources Investigation

NASA Astrophysics Data System (ADS)

Li, J.; Wen, G.; Li, D.

2018-04-01

Trough mastering background information of Yunnan province grassland resources utilization and ecological conditions to improves grassland elaborating management capacity, it carried out grassland resource investigation work by Yunnan province agriculture department in 2017. The traditional grassland resource investigation method is ground based investigation, which is time-consuming and inefficient, especially not suitable for large scale and hard-to-reach areas. While remote sensing is low cost, wide range and efficient, which can reflect grassland resources present situation objectively. It has become indispensable grassland monitoring technology and data sources and it has got more and more recognition and application in grassland resources monitoring research. This paper researches application of multi-source remote sensing image in Yunnan province grassland resources investigation. First of all, it extracts grassland resources thematic information and conducts field investigation through BJ-2 high space resolution image segmentation. Secondly, it classifies grassland types and evaluates grassland degradation degree through high resolution characteristics of Landsat 8 image. Thirdly, it obtained grass yield model and quality classification through high resolution and wide scanning width characteristics of MODIS images and sample investigate data. Finally, it performs grassland field qualitative analysis through UAV remote sensing image. According to project area implementation, it proves that multi-source remote sensing data can be applied to the grassland resources investigation in Yunnan province and it is indispensable method.

Capturing Micro-topography of an Arctic Tundra Landscape through Digital Elevation Models (DEMs) Acquired from Various Remote Sensing Platforms

NASA Astrophysics Data System (ADS)

Vargas, S. A., Jr.; Tweedie, C. E.; Oberbauer, S. F.

2013-12-01

The need to improve the spatial and temporal scaling and extrapolation of plot level measurements of ecosystem structure and function to the landscape level has been identified as a persistent research challenge in the arctic terrestrial sciences. Although there has been a range of advances in remote sensing capabilities on satellite, fixed wing, helicopter and unmanned aerial vehicle platforms over the past decade, these present costly, logistically challenging (especially in the Arctic), technically demanding solutions for applications in an arctic environment. Here, we present a relatively low cost alternative to these platforms that uses kite aerial photography (KAP). Specifically, we demonstrate how digital elevation models (DEMs) were derived from this system for a coastal arctic landscape near Barrow, Alaska. DEMs of this area acquired from other remote sensing platforms such as Terrestrial Laser Scanning (TLS), Airborne Laser Scanning, and satellite imagery were also used in this study to determine accuracy and validity of results. DEMs interpolated using the KAP system were comparable to DEMs derived from the other platforms. For remotely sensing acre to kilometer square areas of interest, KAP has proven to be a low cost solution from which derived products that interface ground and satellite platforms can be developed by users with access to low-tech solutions and a limited knowledge of remote sensing.

Data Collection for Disaster Response from the International Space Station

NASA Astrophysics Data System (ADS)

Stefanov, W. L.; Evans, C. A.

2015-04-01

Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 90 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous sensor systems in higher altitude polar orbits. NASA remote sensing assets on the station began collecting International Charter, Space and Major Disasters, also known informally as the International Disaster Charter (IDC) response data in May 2012. Since the start of IDC response in 2012, and as of late March 2015, there have been 123 IDC activations; NASA sensor systems have collected data for thirty-four of these events. Of the successful data collections, eight involved two or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program.

The micron- to kilometer-scale Moon: linking samples to orbital observations, Apollo to LRO

NASA Astrophysics Data System (ADS)

Crites, S.; Lucey, P. G.; Taylor, J.; Martel, L.; Sun, L.; Honniball, C.; Lemelin, M.

2017-12-01

The Apollo missions have shaped the field of lunar science and our understanding of the Moon, from global-scale revelations like the magma ocean hypothesis, to providing ground truth for compositional remote sensing and absolute ages to anchor cratering chronologies. While lunar meteorite samples can provide a global- to regional-level view of the Moon, samples returned from known locations are needed to directly link orbital-scale observations with laboratory measurements-a link that can be brought to full fruition with today's extremely high spatial resolution observations from Lunar Reconnaissance Orbiter and other recent missions. Korotev et al. (2005) described a scenario of the Moon without Apollo to speculate about our understanding of the Moon if our data were confined to lunar meteorites and remote sensing. I will review some of the major points discussed by Korotev et al. (2005), and focus on some of the ways in which spectroscopic remote sensing in particular has benefited from the Apollo samples. For example, could the causes and effects of lunar-style space weathering have been unraveled without the Apollo samples? What would be the limitations on remote sensing compositional measurements that rely on Apollo samples for calibration and validation? And what new opportunities to bring together orbital and sample analyses now exist, in light of today's high spatial and spectral resolution remote sensing datasets?

[Remote sensing monitoring and screening for urban black and odorous water body: A review.

PubMed

Shen, Qian; Zhu, Li; Cao, Hong Ye

2017-10-01

Continuous improvement of urban water environment and overall control of black and odorous water body are not merely national strategic needs with the action plan for prevention and treatment of water pollution, but also the hot issues attracting the attention of people. Most previous researches concentrated on the study of cause, evaluation and treatment measures of this phenomenon, and there are few researches on the monitoring using remote sensing, which is often a strain to meet the national needs of operational monitoring. This paper mainly summarized the urgent research problems, mainly including the identification and classification standard, research on the key technologies, and the frame of remote sensing screening systems for the urban black and odorous water body. The main key technologies were concluded too, including the high spatial resolution image preprocessing and extraction technique for black and odorous water body, the extraction of water information in city zones, the classification of the black and odorous water, and the identification and classification technique based on satellite-sky-ground remote sensing. This paper summarized the research progress and put forward research ideas of monitoring and screening urban black and odorous water body via high spatial resolution remote sensing technology, which would be beneficial to having an overall grasp of spatial distribution and improvement progress of black and odorous water body, and provide strong technical support for controlling urban black and odorous water body.

The Use of Remote Sensing to Resolve the Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Tanre, D.; Remer, Lorraine

1999-01-01

Satellites are used for remote sensing of aerosol optical thickness and optical properties in order to derive the aerosol direct and indirect radiative forcing of climate. Accuracy of the derived aerosol optical thickness is used as a measure of the accuracy in deriving the aerosol radiative forcing. Several questions can be asked to challenge this concept. Is the accuracy of the satellite-derived aerosol direct forcing limited to the accuracy of the measured optical thickness? What are the spectral bands needed to derive the total aerosol forcing? Does most of the direct or indirect aerosol forcing of climate originate from regions with aerosol concentrations that are high enough to be detected from space? What should be the synergism ground-based and space-borne remote sensing to solve the problem? We shall try to answer some of these questions, using AVIRIS airborne measurements and simulations.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Characterizing water resources of the Nile Basin using remotely sensed data

NASA Astrophysics Data System (ADS)

Mekonnen, Z. T.; Gebremichael, M.; Demissie, S. S.

2015-12-01

The Nile is one of the largest river basin in the world with a rich biodiversity as well supporting the lives of 450 million people residing within the 11 riparian countries. This vital resource is under a growing stress due to population growth, rapid development and climate change. In this work, we explore the use of the latest various remote sensing products to capture the water resource of the basin: rainfall from GPM and TRMM, soil moisture from SMAP and SMOS, evapotranspiration from MODIS and EUMETSAT LSA-SAF, and total water storage variations from GRACE. The satellite estimates were supplemented and checked by ground measurements whenever possible. Our results show that spatiotemporal variations of the basin's water resources characteristics are well captured by remote sensing products rather than the scarce point measurements that currently exist. Several aspects of our results will be presented and discussed.

Estimating population size of Pygoscelid Penguins from TM data

NASA Technical Reports Server (NTRS)

Olson, Charles E., Jr.; Schwaller, Mathew R.; Dahmer, Paul A.

1987-01-01

An estimate was made toward a continent wide population of penguins. The results indicate that Thematic Mapper data can be used to identify penguin rookeries due to the unique reflectance properties of guano. Strong correlations exist between nesting populations and rookery area occupied by the birds. These correlations allow estimation of the number of nesting pairs in colonies. The success of remote sensing and biometric analyses leads one to believe that a continent wide estimate of penguin populations is possible based on a timely sample employing ground based and remote sensing techniques. Satellite remote sensing along the coastline may well locate previously undiscovered penguin nesting sites, or locate rookeries which have been assumed to exist for over a half century, but never located. Observations which found that penguins are one of the most sensitive elements in the complex of Southern Ocean ecosystems motivated this study.

Simple and Multiple Endmember Mixture Analysis in the Boreal Forest

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Gamon, John A.; Qiu, Hong-Lie

2000-01-01

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 was 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 California Cooperative Remote Sensing Project

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Sheffner, Edwin J.

1988-01-01

The USDA, the California Department of Water Resources (CDWR), the Remote Sensing Research Program of the University of California (UCB) and NASA have completed a 4-yr cooperative project on the use of remote sensing in monitoring California agriculture. This report is a summary of the project and the final report of NASA's contribution to it. The cooperators developed procedures that combined the use of LANDSAT Multispectral Scanner imagery and digital data with good ground survey data for area estimation and mapping of the major crops in California. An inventory of the Central Valley was conducted as an operational test of the procedures. The satellite and survey data were acquired by USDA and UCB and processed by CDWR and NASA. The inventory was completed on schedule, thus demonstrating the plausibility of the approach, although further development of the data processing system is necessary before it can be used efficiently in an operational environment.

Research on airborne infrared leakage detection of natural gas pipeline

NASA Astrophysics Data System (ADS)

Tan, Dongjie; Xu, Bin; Xu, Xu; Wang, Hongchao; Yu, Dongliang; Tian, Shengjie

2011-12-01

An airborne laser remote sensing technology is proposed to detect natural gas pipeline leakage in helicopter which carrying a detector, and the detector can detect a high spatial resolution of trace of methane on the ground. The principle of the airborne laser remote sensing system is based on tunable diode laser absorption spectroscopy (TDLAS). The system consists of an optical unit containing the laser, camera, helicopter mount, electronic unit with DGPS antenna, a notebook computer and a pilot monitor. And the system is mounted on a helicopter. The principle and the architecture of the airborne laser remote sensing system are presented. Field test experiments are carried out on West-East Natural Gas Pipeline of China, and the results show that airborne detection method is suitable for detecting gas leak of pipeline on plain, desert, hills but unfit for the area with large altitude diversification.

Methods for improving accuracy and extending results beyond periods covered by traditional ground-truth in remote sensing classification of a complex landscape

USDA-ARS?s Scientific Manuscript database

Successful development of approaches to quantify impacts of diverse landuse and associated agricultural management practices on ecosystem services is frequently limited by lack of historical and contemporary landuse data. We hypothesized that recent ground truth data could be used to extrapolate pre...

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

NASA Technical Reports Server (NTRS)

Ryerson, Charles C.

2000-01-01

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Status of the undisturbed mangroves at Brunei Bay, East Malaysia: a preliminary assessment based on remote sensing and ground-truth observations

PubMed Central

Izzaty Horsali, Nurul Amira; Mat Zauki, Nurul Ashikin; Otero, Viviana; Nadzri, Muhammad Izuan; Ibrahim, Sulong; Husain, Mohd-Lokman; Dahdouh-Guebas, Farid

2018-01-01

Brunei Bay, which receives freshwater discharge from four major rivers, namely Limbang, Sundar, Weston and Menumbok, hosts a luxuriant mangrove cover in East Malaysia. However, this relatively undisturbed mangrove forest has been less scientifically explored, especially in terms of vegetation structure, ecosystem services and functioning, and land-use/cover changes. In the present study, mangrove areal extent together with species composition and distribution at the four notified estuaries was evaluated through remote sensing (Advanced Land Observation Satellite—ALOS) and ground-truth (Point-Centred Quarter Method—PCQM) observations. As of 2010, the total mangrove cover was found to be ca. 35,183.74 ha, of which Weston and Menumbok occupied more than two-folds (58%), followed by Sundar (27%) and Limbang (15%). The medium resolution ALOS data were efficient for mapping dominant mangrove species such as Nypa fruticans, Rhizophora apiculata, Sonneratia caseolaris, S. alba and Xylocarpus granatum in the vicinity (accuracy: 80%). The PCQM estimates found a higher basal area at Limbang and Menumbok—suggestive of more mature vegetation, compared to Sundar and Weston. Mangrove stand structural complexity (derived from the complexity index) was also high in the order of Limbang > Menumbok > Sundar > Weston and supporting the perspective of less/undisturbed vegetation at two former locations. Both remote sensing and ground-truth observations have complementarily represented the distribution of Sonneratia spp. as pioneer vegetation at shallow river mouths, N. fruticans in the areas of strong freshwater discharge, R. apiculata in the areas of strong neritic incursion and X. granatum at interior/elevated grounds. The results from this study would be able to serve as strong baseline data for future mangrove investigations at Brunei Bay, including for monitoring and management purposes locally at present. PMID:29479500

Urban land use: Remote sensing of ground-basin permeability

NASA Technical Reports Server (NTRS)

Tinney, L. R.; Jensen, J. R.; Estes, J. E.

1975-01-01

A remote sensing analysis of the amount and type of permeable and impermeable surfaces overlying an urban recharge basin is discussed. An effective methodology for accurately generating this data as input to a safe yield study is detailed and compared to more conventional alternative approaches. The amount of area inventoried, approximately 10 sq. miles, should provide a reliable base against which automatic pattern recognition algorithms, currently under investigation for this task, can be evaluated. If successful, such approaches can significantly reduce the time and effort involved in obtaining permeability data, an important aspect of urban hydrology dynamics.

Measuring thermal budgets of active volcanoes by satellite remote sensing

NASA Technical Reports Server (NTRS)

Glaze, L.; Francis, P. W.; Rothery, D. A.

1989-01-01

Thematic Mapper measurements of the total radiant energy flux Q at Lascar volcano in north Chile for December 1984 are reported. The results are consistent with the earlier suggestion that a lava lake is the source of a reported thermal budget anomaly, and with values for 1985-1986 that are much lower, suggesting that fumarolic activity was then a more likely heat source. The results show that satellite remote sensing may be used to monitor the activity of a volcano quantitatively, in a way not possible by conventional ground studies, and may provide a method for predicting eruptions.

Prospects and limitations for use of frequency spectrum from 40 to 300 GHz

NASA Technical Reports Server (NTRS)

Catoe, C. E.

1979-01-01

The existing and future use of the electromagnetic spectrum from 40 to 300 gigahertz is discussed. The activities envisioned for this segment of the electromagnetic spectrum fall generically into two basic categories: communications and remote sensing. The communications services considered for this region are focused on the existing and future frequency allocations that are required for terrestrial radio services, space to ground radio services, space to space radio services, and space to deep space radio services. The remote sensing services considered for this region are divided into two groups of activities: earth viewing and space viewing.

Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

2010-12-01

There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

Remote sensing program

NASA Technical Reports Server (NTRS)

Whitmore, R. A., Jr. (Principal Investigator)

1980-01-01

A syllabus and training materials prepared and used in a series of one-day workshops to introduce modern remote sensing technology to selected groups of professional personnel in Vermont are described. Success in using computer compatible tapes, LANDSAT imagery and aerial photographs is reported for the following applications: (1) mapping defoliation of hardwood forests by tent caterpillar and gypsy moth; (2) differentiating conifer species; (3) mapping ground cover of major lake and pond watersheds; (4) inventorying and locating artificially regenerated conifer forest stands; (5) mapping water quality; (6) ascertaining the boat population to quantify recreational activity on lakes and waterways; and (7) identifying potential aquaculture sites.

A View from Above Without Leaving the Ground

NASA Technical Reports Server (NTRS)

2004-01-01

In order to deliver accurate geospatial data and imagery to the remote sensing community, NASA is constantly developing new image-processing algorithms while refining existing ones for technical improvement. For 8 years, the NASA Regional Applications Center at Florida International University has served as a test bed for implementing and validating many of these algorithms, helping the Space Program to fulfill its strategic and educational goals in the area of remote sensing. The algorithms in return have helped the NASA Regional Applications Center develop comprehensive semantic database systems for data management, as well as new tools for disseminating geospatial information via the Internet.

Remote Sensing for Farmers and Flood Watching

NASA Technical Reports Server (NTRS)

2005-01-01

The Applied Sciences Directorate, part of NASA s Science Mission Directorate, makes use of the Agency s remote-sensing capabilities to acquire detailed information about our home planet. It uses this information for a variety of purposes, ranging from increasing agricultural efficiency to protecting homeland security. Sensors fly over areas of interest to detect and record information that sometimes is not even visible from the ground with the human eye. Scientists analyze these data for a variety of purposes and make maps of the areas. These maps are often used to answer questions about the environment, weather, natural resources, community growth, and natural disasters.

IGARSS 89: Canadian Symposium on Remote Sensing (12th) (Symposium Canadien sur la Teledetection): Quantitative Remote Sensing: An Economic Tool for the Nineties Held in Vancouver, Canada on 10-14 July 1989. Volume 2. Tuesday, July 11

DTIC Science & Technology

1989-07-14

blunder-free DEMs, the manual verification group of Ground Control Points (GCPs); (ii) and editing stage is still needed. the orbit and attitude of... control the influence (weight) of the sources and model the that each information class only had one subclass! To set non -Gaussian data. When the...clear line of infinitesimally close laminae sliding parallel to a shear line of shear; a quasi -brittle inner regime and a non -linear viscous outer

Effect of metal stress on the thermal infrared emission of soybeans: A greenhouse experiment - Possible utility in remote sensing

NASA Technical Reports Server (NTRS)

Suresh, R.; Schwaller, M. R.; Foy, C. D.; Weidner, J. R.; Schnetzler, C. S.

1989-01-01

Manganese-sensitive forest and manganese-tolerant lee soybean cultivars were subjected to differential manganese stress in loring soil in a greenhouse experiment. Leaf temperature measurements were made using thermistors for forest and lee. Manganese-stressed plants had higher leaf temperatures than control plants in both forest and lee. Results of this experiment have potential applications in metal stress detection using remote sensing thermal infrared data over large areas of vegetation. This technique can be useful in reconnaissance mineral exploration in densely-vegetated regions where conventional ground-based methods are of little help.

Infrared Detector Activities at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Abedin, M. N.; Refaat, T. F.; Sulima, O. V.; Amzajerdian, F.

2008-01-01

Infrared detector development and characterization at NASA Langley Research Center will be reviewed. These detectors were intended for ground, airborne, and space borne remote sensing applications. Discussion will be focused on recently developed single-element infrared detector and future development of near-infrared focal plane arrays (FPA). The FPA will be applied to next generation space-based instruments. These activities are based on phototransistor and avalanche photodiode technologies, which offer high internal gain and relatively low noise-equivalent-power. These novel devices will improve the sensitivity of active remote sensing instruments while eliminating the need for a high power laser transmitter.

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

PubMed Central

Handcock, Rebecca N.; Swain, Dave L.; Bishop-Hurley, Greg J.; Patison, Kym P.; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J.

2009-01-01

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle. PMID:22412327

Hydrology with unmanned aerial vehicles (UAVs)

USDA-ARS?s Scientific Manuscript database

Hydrologic remote sensing currently depends on expensive and infrequent aircraft observations for validation of operational satellite products, typically conducted during field campaigns that also include ground-based measurements. With the advent of new, hydrologically-relevant satellite missions, ...

Ground-based grasslands data to support remote sensing and ecosystem modeling of terrestrial primary production

NASA Technical Reports Server (NTRS)

Olson, R. J.; Scurlock, J. M. O.; Turner, R. S.; Jennings, S. V.

1995-01-01

Estimating terrestrial net primary production (NPP) using remote-sensing tools and ecosystem models requires adequate ground-based measurements for calibration, parameterization, and validation. These data needs were strongly endorsed at a recent meeting of ecosystem modelers organized by the International Geosphere-Biosphere Program's (IGBP's) Data and Information System (DIS) and its Global Analysis, Interpretation, and Modelling (GAIM) Task Force. To meet these needs, a multinational, multiagency project is being coordinated by the IGBP DIS to compile existing NPP data from field sites and to regionalize NPP point estimates to various-sized grid cells. Progress at Oak Ridge National Laboratory (ORNL) on compiling NPP data for grasslands as part of the IGBP DIS data initiative is described. Site data and associated documentation from diverse field studies are being acquired for selected grasslands and are being reviewed for completeness, consistency, and adequacy of documentation, including a description of sampling methods. Data are being compiled in a database with spatial, temporal, and thematic characteristics relevant to remote sensing and global modeling. NPP data are available from the ORNL Distributed Active Archive Center (DAAC) for biogeochemical dynamics. The ORNL DAAC is part of the Earth Observing System Data and Information System, of the US National Aeronautics and Space Administration.

Vegetation shifts observed in arctic tundra 17 years after fire

USGS Publications Warehouse

Barrett, Kirsten; Rocha, Adrian V.; van de Weg, Martine Janet; Shaver, Gaius

2012-01-01

With anticipated climate change, tundra fires are expected to occur more frequently in the future, but data on the long-term effects of fire on tundra vegetation composition are scarce. This study addresses changes in vegetation structure that have persisted for 17 years after a tundra fire on the North Slope of Alaska. Fire-related shifts in vegetation composition were assessed from remote-sensing imagery and ground observations of the burn scar and an adjacent control site. Early-season remotely sensed imagery from the burn scar exhibits a low vegetation index compared with the control site, whereas the late-season signal is slightly higher. The range and maximum vegetation index are greater in the burn scar, although the mean annual values do not differ among the sites. Ground observations revealed a greater abundance of moss in the unburned site, which may account for the high early growing season normalized difference vegetation index (NDVI) anomaly relative to the burn. The abundance of graminoid species and an absence of Betula nana in the post-fire tundra sites may also be responsible for the spectral differences observed in the remotely sensed imagery. The partial replacement of tundra by graminoid-dominated ecosystems has been predicted by the ALFRESCO model of disturbance, climate and vegetation succession.

Mapping of risk prone areas of kala-azar (Visceral leishmaniasis) in parts of Bihar State, India: an RS and GIS approach.

PubMed

Sudhakar, S; Srinivas, T; Palit, A; Kar, S K; Battacharya, S K

2006-09-01

The kala-azar fever (Visceral leishmaniasis) is continuing unabated in India for over a century, now being largely confined to the eastern part of India mainly in Bihar state and to some extent in its bordering states like West Bengal and Uttar Pradesh. Two study sites namely Patepur block in Vaishali district with high endemicity in northern part and Lohardagga block in Lohardagga district with absolute non-endemicity in southern part of Bihar were selected for the study with the following objectives : (i) to study the macro-ecosystem in relation to distribution of vector -Phlebotomus argentipes; (ii) to identify/map the risk prone areas or villages in a block for quick remedial measures; and (iii) to make use of satellite remote sensing and GIS to demonstrate the utility for rapid assessment of landuse/landcover and their relation with the incidence of kalaazar leading to the mapping of risk prone areas. Indian Remote Sensing (IRS)-1D LISS III satellite data for the periods of March and November 2000 were analysed in Silicon graphic image processing system using ERDAS software. False color composites (FCC) were generated and landuse/landcover was assessed using Maximum likelihood supervised classification techniques based on ground truth training sets. During the study the GIS functions are used to quantify the remotely sensed landscape proportions of 5 km2 buffer surrounding each known group of villages of high occurrence of sandflies in endemic and nonendemic study sites. Instead of traditional ground based survey methods to vector surveillance, the present study used a combination of remote sensing (RS) and geographical information system (GIS) approach to develop landscape predictors of sandfly abundance-an indicator of human vector contact and as a measure of risk prone areas. Statistical analysis using the remotely sensed landscape variables showed that rural villages surrounded by higher proportion of transitional swamps with soft stemmed edible plants and banana, sugarcane plantations had higher sandfly abundance and would, therefore, be at higher risk prone areas for man-vector contact. The present study clearly brought out the usefulness of satellite remote sensing technology in generating the crucial information on spatial distribution of landuse/landcover classes with special emphasis on indicator landcover classes thereby helping in prioritising the area to identify risk prone areas of kala-azar through GIS application tools.

Remote Sensing of Landscapes with Spectral Images

NASA Astrophysics Data System (ADS)

Adams, John B.; Gillespie, Alan R.

2006-05-01

Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

NASA Astrophysics Data System (ADS)

Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

2018-01-01

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Analysis of multispectral signatures and investigation of multi-aspect remote sensing techniques

NASA Technical Reports Server (NTRS)

Malila, W. A.; Hieber, R. H.; Sarno, J. E.

1974-01-01

Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, multispectral signature analysis, includes the effects on classification performance of systematic variations found in the average signals received from various ground covers as well as the prediction of these variations with theoretical models of physical processes. The foremost effects studied are those associated with the time of day airborne MSS data are collected. Six data collection runs made over the same flight line in a period of five hours are analyzed, it is found that the time span significantly affects classification performance. Variations associated with scan angle also are studied. The second major topic of discussion is multi-aspect remote sensing, a new concept in remote sensing with scanners. Here, data are collected on multiple passes by a scanner that can be tilted to scan forward of the aircraft at different angles on different passes. The use of such spatially registered data to achieve improved classification of agricultural scenes is investigated and found promising. Also considered are the possibilities of extracting from multi-aspect data, information on the condition of corn canopies and the stand characteristics of forests.

An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

NASA Astrophysics Data System (ADS)

Lebed, L.; Qi, J.; Heilman, P.

2012-06-01

The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation.

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

Ransom, K. J.; Sun, G.; Kharuk, V. I.; Howl, J.

2011-01-01

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

The AmericaView Project - Putting the Earth into Your Hands

USGS Publications Warehouse

,

2005-01-01

The U.S. Geological Survey (USGS) is a leader in collecting, archiving, and distributing geospatial data and information about the Earth. Providing quick, reliable access to remotely sensed images and geospatial data is the driving principle behind the AmericaView Project. A national not-for-profit organization, AmericaView, Inc. was established and is supported by the USGS to coordinate the activities of a national network of university-led consortia with the primary objective of the advancement of the science of remote sensing. Individual consortia members include academic institutions, as well as state, local, and tribal government agencies. AmericaView's focus is to expand the understanding and use of remote sensing through education and outreach efforts and to provide affordable, integrated remote sensing information access and delivery to the American public. USGS's Landsat and NASA's Earth Observing System (EOS) satellite data are downlinked from satellites or transferred from other facilities to the USGS Center for Earth Resources Observation and Science (EROS) ground receiving station in Sioux Falls, South Dakota. The data can then be transferred over high-speed networks to consortium members, where it is archived and made available for public use.

A stereo remote sensing feature selection method based on artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

An airborne remote sensing system for urban air quality

NASA Technical Reports Server (NTRS)

Duncan, L. J.; Friedman, E. J.; Keitz, E. L.; Ward, E. A.

1974-01-01

Several NASA sponsored remote sensors and possible airborne platforms were evaluated. Outputs of dispersion models for SO2 and CO pollution in the Washington, D.C. area were used with ground station data to establish the expected performance and limitations of the remote sensors. Aircraft/sensor support requirements are discussed. A method of optimum flight plan determination was made. Cost trade offs were performed. Conclusions about the implementation of various instrument packages as parts of a comprehensive air quality monitoring system in Washington are presented.

Remote Sensing of Arizona Monsoons: Application of GOES Infrared Imagery

NASA Astrophysics Data System (ADS)

Carter, S.; Christensen, P. R.; Cerveny, R. S.

2013-12-01

Large, violent thunder and dust storms occur in the Phoenix area during monsoon season. Currently, the best ways to predict these dangerous and potentially damaging storms are not very accurate. The primary goal of this investigation is to attempt to develop a new technique to identify and predict these storms before they reach Phoenix. In order to address this question, two data sets (remote sensing satellite imagery and ground-based weather information) will be analyzed and compared against one another using time as a corresponding variable. The goal is to discern any correlations between data sets which be used as an indicator of imminent large monsoons. The moisture needed for the storms is carried to Arizona by events known as gulf surges (from the California Gulf); these will be the target of investigation. These chutes of moisture surge through Arizona, primarily up through Yuma in a northeasterly direction towards central/south central Arizona. The main goal is to identify if satellite imagery can be used as an accurate identifier of moisture movements preceding a storm in areas where ground measurements are not available. Presently, ground measurements of dew points are the primary technique by which these moisture surges are identified. However, while these measurements do have a fairly high temporal resolution (once an hour) they cover an awfully poor spacial range. Furthermore, it is suspected that because of interference to the instruments, the ground point data may not be as accurate as is preferred. On the other hand, satellite imagery such as GOES - the instrument used in this investigation - has both a remarkably high temporal resolution and spacial coverage. If a correlation can be demonstrated, then the high temporal resolution of the remote sensing data could be used as an identifier of oncoming monsoon storms. In order to proceed in this research, a software package known as Java Mission-planning and Analysis for Remote Sensing (JMARS) for Earth was used. While this program is great for visualizing and comparing multiple data sets (and data from the same set), the ability to compare along a temporal scale in a given spacial region was not previously available. During this research additional functionality was developed for an existing tool known as the 'Investigate Tool'. This tool was was enhanced to include a functionality called the 'Data Spike' which displays all the desired numerical data found at one point. This added functionality can be used in a variety of data analysis, and this investigation is a prime example of how to use it. Throughout this investigation data processing, software development, and research analysis and preliminary conclusions show some potential candidate trends in linking the ground acquired data and remote sensing imagery. Further study is needed to confirm the hypothesis, but it is possible that a new method of monsoon detection could be more accurate and have a broader spatial scope of prediction.

NEON Airborne Remote Sensing of Terrestrial Ecosystems

NASA Astrophysics Data System (ADS)

Kampe, T. U.; Leisso, N.; Krause, K.; Karpowicz, B. M.

2012-12-01

The National Ecological Observatory Network (NEON) is the continental-scale research platform that will collect information on ecosystems across the United States to advance our understanding and ability to forecast environmental change at the continental scale. One of NEON's observing systems, the Airborne Observation Platform (AOP), will fly an instrument suite consisting of a high-fidelity visible-to-shortwave infrared imaging spectrometer, a full waveform small footprint LiDAR, and a high-resolution digital camera on a low-altitude aircraft platform. NEON AOP is focused on acquiring data on several terrestrial Essential Climate Variables including bioclimate, biodiversity, biogeochemistry, and land use products. These variables are collected throughout a network of 60 sites across the Continental United States, Alaska, Hawaii and Puerto Rico via ground-based and airborne measurements. Airborne remote sensing plays a critical role by providing measurements at the scale of individual shrubs and larger plants over hundreds of square kilometers. The NEON AOP plays the role of bridging the spatial scales from that of individual organisms and stands to the scale of satellite-based remote sensing. NEON is building 3 airborne systems to facilitate the routine coverage of NEON sites and provide the capacity to respond to investigator requests for specific projects. The first NEON imaging spectrometer, a next-generation VSWIR instrument, was recently delivered to NEON by JPL. This instrument has been integrated with a small-footprint waveform LiDAR on the first NEON airborne platform (AOP-1). A series of AOP-1 test flights were conducted during the first year of NEON's construction phase. The goal of these flights was to test out instrument functionality and performance, exercise remote sensing collection protocols, and provide provisional data for algorithm and data product validation. These test flights focused the following questions: What is the optimal remote sensing data collection protocol to meet NEON science requirements? How do aircraft altitude, spatial sampling, spatial resolution, and LiDAR instrument configuration affect data retrievals? What are appropriate algorithms to derive ECVs from AOP data? What methodology should be followed to validate AOP remote sensing products and how should ground truth data be collected? Early test flights were focused on radiometric and geometric calibration as well as processing from raw data to Level-1 products. Subsequent flights were conducted focusing on collecting vegetation chemistry and structure measurements. These test flights that were conducted during 2012 have proved to be extremely valuable for verifying instrument functionality and performance, exercising remote sensing collection protocols, and providing data for algorithm and science product validation. Results from these early flights are presented, including the radiometric and geometric calibration of the AOP instruments. These 2012 flight campaigns are just the first of a series of test flights that will take place over the next several years as part of the NEON observatory construction. Lessons learned from these early campaigns will inform both airborne and ground data collection methodologies for future campaigns as well as guide the AOP sampling strategy before NEON enters full science operations.

An automated system for rail transit infrastructure inspection.

DOT National Transportation Integrated Search

2015-03-01

This project applied commercial remote sensing and spatial information (CRS&SI) : technologies such as Ground Penetrating Radar (GPR), laser, GIS, and GPS to passenger rail : inspections. An integrated rail inspection system that can be mounted on hi...

Spectral data analysis of rock and mineral in Hatu Western Junggar Region, Xinjiang

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Zhou, Kefa; Zhang, Nannan; Wang, Jinlin

2014-11-01

Mineral resources are important material basis for the survival and development of human society. The development of hyperspectral remote sensing technology, which has made direct identification of minerals or mineral aggregates become possible, paves a new way for the application of remote sensing geology. The West Junggar region is located Xinjiang west verge of Junggar, with ore-forming geological conditions be richly endowed by nature and huge prospecting potentiality. The area has very good outcrop exposure with almost no vegetation cover, which is a natural test new method of remote sensing geological exploration. The characteristic of rock and mineral spectrum is not only the physical base of geological remote sensing technical application but also the base of the quantificational analysis of geological remote sensing, and the study of reflectance spectrum is the main content in the basic research of remote sensing. In this study, we collected the outdoor and indoor reflectance spectrum of rocks and minerals by using a spectroradiometer (ASD FieldSpec FR, ASD, USA), which band extent varied from 350 to 2,500 nm. Basin on a great deal of spectral data for different kinds of rocks and minerals, we have analyzed the spectrum characteristics and change of seven typical mineral rocks. According to the actual conditions, we analyzed the data noise characteristic of the spectrum and got rid of the noise. Meanwhile, continuum removed technology was used to remove the environmental background influence. Finally, in order to take full advantage of multi-spectrum data, ground information is absolutely necessary, and it is important to build a representative spectral library. We build the spectral library of rocks and minerals in Hatu, which can be used for features investigation, mineral classification, mineral mapping and geological prospecting in Hatu Western Junggar region by remote sensing. The result of this research will be significant to the research of accelerating Western Junggar mineral exploration.

Ground-based remote sensing observation of the complex behaviour of the Marseille boundary layer during ESCOMPTE

NASA Astrophysics Data System (ADS)

Delbarre, H.; Augustin, P.; Saïd, F.; Campistron, B.; Bénech, B.; Lohou, F.; Puygrenier, V.; Moppert, C.; Cousin, F.; Fréville, P.; Fréjafon, E.

2005-03-01

Ground-based remote sensing systems have been used during the ESCOMPTE campaign, to continuously characterize the boundary-layer behaviour through many atmospheric parameters (wind, extinction and ozone concentration distribution, reflectivity, turbulence). This analysis is focused on the comparison of the atmospheric stratification retrieved from a UV angular ozone lidar, an Ultra High Frequency wind profiler and a sodar, above the area of Marseille, on June 26th 2001 (Intensive Observation Period 2b). The atmospheric stratification is shown to be very complex including two superimposed sea breezes, with an important contribution of advection. The temporal and spatial evolution of the stratification observed by the UV lidar and by the UHF radar are in good agreement although the origin of the echoes of these systems is quite different. The complexity of the dynamic situation has only partially been retrieved by a non-hydrostatic mesoscale model used with a 3 km resolution.

Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Williams, Earle

2016-01-01

During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.

Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Williams, Earle

2017-01-01

During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions.

Retrieving cloudy atmosphere parameters from RPG-HATPRO radiometer data

NASA Astrophysics Data System (ADS)

Kostsov, V. S.

2015-03-01

An algorithm for simultaneously determining both tropospheric temperature and humidity profiles and cloud liquid water content from ground-based measurements of microwave radiation is presented. A special feature of this algorithm is that it combines different types of measurements and different a priori information on the sought parameters. The features of its use in processing RPG-HATPRO radiometer data obtained in the course of atmospheric remote sensing experiments carried out by specialists from the Faculty of Physics of St. Petersburg State University are discussed. The results of a comparison of both temperature and humidity profiles obtained using a ground-based microwave remote sensing method with those obtained from radiosonde data are analyzed. It is shown that this combined algorithm is comparable (in accuracy) to the classical method of statistical regularization in determining temperature profiles; however, this algorithm demonstrates better accuracy (when compared to the method of statistical regularization) in determining humidity profiles.

Russian Earth Science Research Program on ISS

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

Armand, N. A.; Tishchenko, Yu. G.

1999-01-22

Version of the Russian Earth Science Research Program on the Russian segment of ISS is proposed. The favorite tasks are selected, which may be solved with the use of space remote sensing methods and tools and which are worthwhile for realization. For solving these tasks the specialized device sets (submodules), corresponding to the specific of solved tasks, are working out. They would be specialized modules, transported to the ISS. Earth remote sensing research and ecological monitoring (high rates and large bodies transmitted from spaceborne information, comparatively stringent requirements to the period of its processing, etc.) cause rather high requirements tomore » the ground segment of receiving, processing, storing, and distribution of space information in the interests of the Earth natural resources investigation. Creation of the ground segment has required the development of the interdepartmental data receiving and processing center. Main directions of works within the framework of the ISS program are determined.« less

Change detection using vegetation indices and multiplatform satellite imagery at multiple temporal and spatial scales

USGS Publications Warehouse

Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.; Weng, Qihao

2014-01-01

This chapter describes emerging methods for using satellite imagery across temporal and spatial scales using a case study approach to illustrate some of the opportunities now available for combining observations across scales. It explores the use of multiplatform sensor systems to characterize ecological change, as exemplified by efforts to scale the effects of a biocontrol insect (the leaf beetle Diorhabda carinulata) on the phenology and water use of Tamarix shrubs (Tamarix ramosissima and related species and hybrids) targeted for removal on western U.S. rivers, from the level of individual leaves to the regional level of measurement. Finally, the chapter summarizes the lessons learned and emphasize the need for ground data to calibrate and validate remote sensing data and the types of errors inherent in scaling point data over wide areas, illustrated with research on evapotranspiration (ET) of Tamarix using a wide range of ground measurement and remote sensing methods.

Effects of vegetation canopy structure on remotely sensed canopy temperatures. [inferring plant water stress and yield

NASA Technical Reports Server (NTRS)

Kimes, D. S.

1979-01-01

The effects of vegetation canopy structure on thermal infrared sensor response must be understood before vegetation surface temperatures of canopies with low percent ground cover can be accurately inferred. The response of a sensor is a function of vegetation geometric structure, the vertical surface temperature distribution of the canopy components, and sensor view angle. Large deviations between the nadir sensor effective radiant temperature (ERT) and vegetation ERT for a soybean canopy were observed throughout the growing season. The nadir sensor ERT of a soybean canopy with 35 percent ground cover deviated from the vegetation ERT by as much as 11 C during the mid-day. These deviations were quantitatively explained as a function of canopy structure and soil temperature. Remote sensing techniques which determine the vegetation canopy temperature(s) from the sensor response need to be studied.

Retrieval Analysis of the CO2 1.6 μm Band in Solar Absorption Spectra Measured by a Ground-Based High-Resolution Fourier Transform Spectrometer at Tsukuba

NASA Astrophysics Data System (ADS)

Ohyama, H.; Morino, I.; Nagahama, T.; Suto, H.; Oguma, H.; Machida, T.; Sugimoto, N.; Nakane, H.; Nakagawa, K.

2006-12-01

The global measurements of greenhouse gases from space are being planned, such as GOSAT (Greenhouse gases Observing SATellite) and OCO (Orbiting Carbon Observatory). Satellite remote sensing needs validations with other measurement techniques, for example, in-situ or sampling measurement by aircraft or ground station, or remote sensing measurement by ground-based Fourier Transform Spectrometer (FTS). The ground-based FTS measurement can provide the column amounts of atmospheric composition by a retrieval analysis with relatively high precision. In 2001, we started a project to observe the atmospheric compositions in solar absorption spectra by a ground- based high-resolution FTS (Bruker IFS 120 HR) located at Tsukuba, Japan. Three years ago, optical components of the FTS were replaced for measuring greenhouse gases such as carbon dioxide (CO2) and methane (CH4) in the near-infrared region: a CaF2 beam splitter, an InSb detector, and a 1.4-2.4 μm optical filter. The measurements were carried out once a day for ~100 days per year. We also made simultaneous FTS and aircraft in-situ measurements on August 10, 2004 and March 30, 2005. The retrieval analysis was performed for the measured spectra in the CO2 1.6 μm band. We used SEASCRAPE PLUS (Sequential Evaluation Algorithm for Simultaneous and Concurrent Retrieval of Atmospheric Parameter Estimates PLUS, Remote Sensing Analysis Systems, Inc.) as a retrieval analysis program. The column amounts were compared with those derived from in-situ measurements complemented by model data; differences are less than 1%. We have derived the diurnal variations of CO2 on the same days as in-situ measurements, and they showed tendencies similar to the tower measurements at the Meteorological Research Institute in Tsukuba.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Jackson, Thomas J.; Manu, Andrew; Tsegaye, Teferi D.; Soman, V.; Arnold, James E. (Technical Monitor)

2001-01-01

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

UniScan technology for innovative laboratory at a university for acquisition data from space in real-time

NASA Astrophysics Data System (ADS)

Gershenzon, V.; Gershenzon, O.; Sergeeva, M.; Ippolitov, V.; Targulyan, O.

2012-04-01

Keywords: Remote Sensing, UniScan ground station, Education, Monitoring. Remote Sensing Centers allowing real-time imagery acquisition from Earth observing satellites within the structure of Universities provides proper environment for innovative education. It delivers the efficient training for scientific and academic and teaching personnel, secure the role of the young professionals in science, education and hi-tech, and maintain the continuity of generations in science and education. Article is based on experience for creation such centers in more than 20 higher education institutions in Russia, Kazakhstan, and Spain on the base of UniScan ground station by R&D Center ScanEx. These stations serve as the basis for Earth monitoring from space providing the training and advanced training to produce the specialists having the state-of-the-art knowledge in Earth Remote Sensing and GIS, as well as the land-use monitoring and geo-data service for the economic operators in such diverse areas as the nature resource management, agriculture, land property management, disasters monitoring, etc. Currently our proposal of UniScan for universities all over the world allows to receive low resolution free of charge MODIS data from Terra and Aqua satellites, VIIRS from the NPP mission, and also high resolution optical images from EROS A and radar images from Radarsat-1 satellites, including the telemetry for the first year of operation, within the footprint of up to 2,500 kilometers in radius. Creation remote sensing centers at universities will lead to a new quality level for education and scientific studies and will enable to make education system in such innovation institutions open to modern research work and economy.

Evaluation of 3-D Air Quality System Remotely-Sensed Aerosol Optical Depth for the Baltimore/Washington Metropolitan Air Shed

NASA Astrophysics Data System (ADS)

Weber, S. A.; Engel-Cox, J. A.; Hoff, R. M.; Prados, A.; Zhang, H.

2008-12-01

Integrating satellite- and ground-based aerosol optical depth (AOD) observations with surface total fine particulate (PM2.5) and sulfate concentrations allows for a more comprehensive understanding of local- and urban-scale air quality. This study evaluates the utility of integrated databases being developed for NOAA and EPA through the 3D-AQS project by examining the relationship between remotely-sensed AOD and PM2.5 concentrations for each platform for the summer of 2004 and the entire year of 2005. We compare results for the Baltimore, MD/Washington, DC metropolitan air shed, incorporating AOD products from the Terra and GOES-12 satellites, AERONET sunphotometer, and ground-based lidar, and PM2.5 concentrations from five surface monitoring sites. The satellite-derived products include AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR), as well as the GOES Aerosol/Smoke Product (GASP). The vertical profile of lidar backscatter is used to retrieve the planetary boundary layer (PBL) height in an attempt to capture only that fraction of the AOD arising from near surface aerosols. Adjusting the AOD data using platform- and season-specific ratios, calculated using the parameters of the regression equations, for two case studies resulted in a more accurate representation of surface PM2.5 concentrations when compared to a constant ratio that is currently being used in the NOAA IDEA product. This work demonstrates that quantitative relationships between remotely-sensed and in-situ aerosol observations in an integrated database can be computed and applied to improve the use of remotely-sensed observations for estimating surface concentrations.

Taking advantage of inclination variation in resonant remote-sensing satellite orbits

NASA Astrophysics Data System (ADS)

Gopinath, N. S.; Ravindrababu, T.; Rao, S. V.; Daniel, D. A.; Goel, P. S.

2004-08-01

The inclination of remote-sensing satellites, which are generally placed in sun-synchronous orbits, varies as a function of the nominal equatorial crossing local mean solar time selected for a given mission. The Indian Remote-Sensing satellites will have an inclination reduction of about 0.034° per year and for most of the satellites, the local time chosen was around 10:30 hours at descending node. In practice, the initial inclination is biased appropriately so that the expensive out-of-plane maneuvers could be taken up after few years of mission operations, depending on the deviations permitted in the local time for a given mission. However, the scenario differs when the mission objectives require an almost exact repeat orbit of 14 or 15 per day. In such a situation, the satellite orbit, which passes through a 14th or 15th order resonance, undergoes a nearly secular increase in orbit inclination. This paper presents a detailed analysis carried out for such an orbit, based on Cowell's approach. Long-term predictions have been carried out by considering all major forces that perturbs the satellite orbit. Observed behavior of orbit, based on the daily definitive orbit determination is also presented. The variation in inclination and the cause is clearly brought out. Further, it is demonstrated that the selection of longitude for nominal ground track pattern has an impact on the inclination variation. A proposal is made to take advantage of such expected inclination variation so that initial inclination bias can be chosen appropriately. Ground track longitude can be chosen to take advantage, subject to the mission coverage requirements. The paper contains the results of an exhaustive analysis of the actually observed orbit resonance. It is felt that the work has both theoretical and operational importance for remote-sensing missions.

Spatial assessment of Geo-environmental data by the integration of Remote Sensing and GIS techniques for Sitakund Region, Eastern foldbelt, Bangladesh.

NASA Astrophysics Data System (ADS)

Gazi, M. Y.; Rahman, M.; Islam, M. A.; Kabir, S. M. M.

2016-12-01

Techniques of remote sensing and geographic information systems (GIS) have been applied for the analysis and interpretation of the Geo-environmental assessment to Sitakund area, located within the administrative boundaries of the Chittagong district, Bangladesh. Landsat ETM+ image with a ground resolution of 30-meter and Digital Elevation Model (DEM) has been adopted in this study in order to produce a set of thematic maps. The diversity of the terrain characteristics had a major role in the diversity of recipes and types of soils that are based on the geological structure, also helped to diversity in land cover and use in the region. The geological situation has affected on the general landscape of the study area. The problem of research lies in the possibility of the estimating the techniques of remote sensing and geographic information systems in the evaluation of the natural data for the study area spatially as well as determine the appropriate in grades for the appearance of the ground and in line with the reality of the region. Software for remote sensing and geographic information systems were adopted in the analysis, classification and interpretation of the prepared thematic maps in order to get to the building of the Geo-environmental assessment map of the study area. Low risk geo-environmental land mostly covered area of Quaternary deposits especially with area of slope wash deposits carried by streams. Medium and high risk geo-environmental land distributed with area of other formation with the study area, mostly the high risk shows area of folds and faults. The study has assessed the suitability of lands for agricultural purpose and settlements in less vulnerable areas within this region.

FLUXNET to MODIS: Connecting the dots to capture heterogenious biosphere metabolism

NASA Astrophysics Data System (ADS)

Woods, K. D.; Schwalm, C.; Huntzinger, D. N.; Massey, R.; Poulter, B.; Kolb, T.

2015-12-01

Eddy co-variance flux towers provide our most widely distributed network of direct observations for land-atmosphere carbon exchange. Carbon flux sensitivity analysis is a method that uses in situ networks to understand how ecosystems respond to changes in climatic variables. Flux towers concurrently observe key ecosystem metabolic processes (e..g. gross primary productivity) and micrometeorological variation, but only over small footprints. Remotely sensed vegetation indices from MODIS offer continuous observations of the vegetated land surface, but are less direct, as they are based on light use efficiency algorithms, and not on the ground observations. The marriage of these two data products offers an opportunity to validate remotely sensed indices with in situ observations and translate information derived from tower sites to globally gridded products. Here we provide correlations between Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and MODIS gross primary production with FLUXNET derived estimates of gross primary production, respiration and net ecosystem exchange. We demonstrate remotely sensed vegetation products which have been transformed to gridded estimates of terrestrial biosphere metabolism on a regional-to-global scale. We demonstrate anomalies in gross primary production, respiration, and net ecosystem exchange as predicted by both MODIS-carbon flux sensitivities and meteorological driver-carbon flux sensitivities. We apply these sensitivities to recent extreme climatic events and demonstrate both our ability to capture changes in biosphere metabolism, and differences in the calculation of carbon flux anomalies based on method. The quantification of co-variation in these two methods of observation is important as it informs both how remotely sensed vegetation indices are correlated with on the ground tower observations, and with what certainty we can expand these observations and relationships.

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

NASA Technical Reports Server (NTRS)

Cetin, Haluk

1999-01-01

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly Elizabeth; Brickley, Elizabeth B

2012-01-01

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Textural-Contextual Labeling and Metadata Generation for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1999-01-01

Despite the extensive research and the advent of several new information technologies in the last three decades, machine labeling of ground categories using remotely sensed data has not become a routine process. Considerable amount of human intervention is needed to achieve a level of acceptable labeling accuracy. A number of fundamental reasons may explain why machine labeling has not become automatic. In addition, there may be shortcomings in the methodology for labeling ground categories. The spatial information of a pixel, whether textural or contextual, relates a pixel to its surroundings. This information should be utilized to improve the performance of machine labeling of ground categories. Landsat-4 Thematic Mapper (TM) data taken in July 1982 over an area in the vicinity of Washington, D.C. are used in this study. On-line texture extraction by neural networks may not be the most efficient way to incorporate textural information into the labeling process. Texture features are pre-computed from cooccurrence matrices and then combined with a pixel's spectral and contextual information as the input to a neural network. The improvement in labeling accuracy with spatial information included is significant. The prospect of automatic generation of metadata consisting of ground categories, textural and contextual information is discussed.

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Ground-based hyperspectral imaging and terrestrial laser scanning for fracture characterization in the Mississippian Boone Formation

NASA Astrophysics Data System (ADS)

Sun, Lei; Khan, Shuhab D.; Sarmiento, Sergio; Lakshmikantha, M. R.; Zhou, Huawei

2017-12-01

Petroleum geoscientists have been using cores and well logs to study source rocks and reservoirs, however, the inherent discontinuous nature of these data cannot account for horizontal heterogeneities. Modern exploitation requires better understanding of important source rocks and reservoirs at outcrop scale. Remote sensing of outcrops is becoming a first order tool for reservoir analog studies including horizontal heterogeneities. This work used ground-based hyperspectral imaging, terrestrial laser scanning (TLS), and high-resolution photography to study a roadcut of the Boone Formation at Bella Vista, northwest Arkansas, and developed an outcrop model for reservoir analog analyses. The petroliferous Boone Formation consists of fossiliferous limestones interbedded with chert of early Mississippian age. We used remote sensing techniques to identify rock types and to collect 3D geometrical data. Mixture tuned matched filtering classification of hyperspectral data show that the outcrop is mostly limestones with interbedded chert nodules. 1315 fractures were classified according to their strata-bounding relationships, among these, larger fractures are dominantly striking in ENE - WSW directions. Fracture extraction data show that chert holds more fractures than limestones, and both vertical and horizontal heterogeneities exist in chert nodule distribution. Utilizing ground-based remote sensing, we have assembled a virtual outcrop model to extract mineral composition as well as fracture data from the model. We inferred anisotropy in vertical fracture permeability based on the dominancy of fracture orientations, the preferential distribution of fractures and distribution of chert nodules. These data are beneficial in reservoir analogs to study rock mechanics and fluid flow, and to improve well performances.

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

NASA Astrophysics Data System (ADS)

Hadley, Brian Christopher

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

Challenges of Communications and Tracking for Solar System Small Body Exploration

NASA Technical Reports Server (NTRS)

Rush, John J.; Lichten, Stephen M.; Srinivasan, Jeffrey M.

2011-01-01

This presentation will address: (1) Communications capabilities that will be needed for space missions for Small Planetary Body exploration (2) Utilization of large ground-based radar capabilities for Small Body remote sensing and mission planning

NONDESTRUCTIVE TESTING (NDT) TECHNIQUES TO DETECT CONTAINED SUBSURFACE HAZARDOUS WASTE

EPA Science Inventory

The project involves the detection of buried containers with NDT (remote-sensing) techniques. Seventeen techniques were considered and four were ultimately decided upon. They were: electromagnetic induction (EMI); metal detection (MD); magnetometer (MAG); and ground penetrating r...

Tracking and Monitoring Oil Slicks Using remote Sensing

NASA Astrophysics Data System (ADS)

Klemas, V. V.

2011-12-01

Tracking and Monitoring Oil Slicks Using Remote Sensing Victor Klemas, Ph.D. , College of Earth, Ocean and Environment, University of Delaware, Newark, DE 19716 Abstract Oil spills can harm marine life in the ocean, estuaries and wetlands. To limit the damage by a spill and facilitate cleanup efforts, emergency managers need information on spill location, size and extent, direction and speed of oil movement, wind, current, and wave information for predicting oil drift and dispersion. The main operational data requirements are fast turn-around time and frequent imaging to monitor the dynamics of the spill. Radar and multispectral remote sensors on satellites and aircraft meet most of these requirements by tracking the spilled oil at various resolutions, over wide areas and at frequent intervals. They also provide key inputs to drift prediction models and facilitate targeting of skimming and booming efforts. Satellite data are frequently supplemented by information provided by aircraft, ships and remotely controlled underwater robots. The Sea Princess tanker grounding off the coast of Wales and the explosion on the Deepwater Horizon rig in the Gulf of Mexico provide two representative, yet different, scenarios for evaluating the effectiveness of remote sensors during oil spill emergencies. Session NH17: Remote Sensing of Natural Hazards Session Chair: Ramesh P. Singh Sponsor: Natural Hazards (NH)

Aerosol optical properties over the Svalbard region of Arctic: ground-based measurements and satellite remote sensing

NASA Astrophysics Data System (ADS)

Gogoi, Mukunda M.; Babu, S. Suresh

2016-05-01

In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronald; Russell, Jeffrey A.; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the basis for many inter-sensor interoperability or change detection techniques. Satellite inter-comparisons and accurate vegetation indices such as the Normalized Difference Vegetation Index, which is used to describe or to imply a wide variety of biophysical parameters and is defined in terms of near-infrared and redband reflectance, require the generation of accurate reflectance maps. This generation relies upon the removal of solar illumination, satellite geometry, and atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance, however, has been widely applied to only a few systems. In this study, we atmospherically corrected commercially available, high spatial resolution IKONOS and QuickBird imagery using several methods to determine the accuracy of the resulting reflectance maps. We used extensive ground measurement datasets for nine IKONOS and QuickBird scenes acquired over a two-year period to establish reflectance map accuracies. A correction approach using atmospheric products derived from Moderate Resolution Imaging Spectrometer data created excellent reflectance maps and demonstrated a reliable, effective method for reflectance map generation.

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

USGS Publications Warehouse

Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

Challenges in Complementing Data from Ground-Based Sensors with Satellite-Derived Products to Measure Ecological Changes in Relation to Climate—Lessons from Temperate Wetland-Upland Landscapes

PubMed Central

Sadinski, Walt; Senay, Gabriel B.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines. PMID:29547531

Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model

NASA Astrophysics Data System (ADS)

Wu, Z.; Chen, X.; Gao, Y.; Li, Y.

2018-04-01

Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.

Spacecraft Jitter Attenuation Using Embedded Piezoelectric Actuators

NASA Technical Reports Server (NTRS)

Belvin, W. Keith

1995-01-01

Remote sensing from spacecraft requires precise pointing of measurement devices in order to achieve adequate spatial resolution. Unfortunately, various spacecraft disturbances induce vibrational jitter in the remote sensing instruments. The NASA Langley Research Center has performed analysis, simulations, and ground tests to identify the more promising technologies for minimizing spacecraft pointing jitter. These studies have shown that the use of smart materials to reduce spacecraft jitter is an excellent match between a maturing technology and an operational need. This paper describes the use of embedding piezoelectric actuators for vibration control and payload isolation. In addition, recent advances in modeling, simulation, and testing of spacecraft pointing jitter are discussed.

Satellite hydrology; Proceedings of the Fifth Annual William T. Pecora Memorial Symposium on Remote Sensing, Sioux Falls, SD, June 10-15, 1979

NASA Technical Reports Server (NTRS)

Deutsch, M. (Editor); Wiesnet, D. R.; Rango, A.

1981-01-01

Philosophical and technical backgrounds for the application of remote sensing by earth scientists are presented. Interests and activities of participating agencies of the United States and Canadian governments, universities, and the private sector in implementing satellite technology in a diverse array of water-related programs are described. Consideration is then given to applications of satellite data to the various aspects of the hydrologic cycle and man's impact on it: meteorology, snow and ice, surface water, soil moisture, ground water, wetlands, coastal zone, water quality and environment, and water use and management.

The Science and Application of Satellite Based Fire Radiative Energy

NASA Technical Reports Server (NTRS)

Ellicott, Evan; Vermote, Eric (Editor)

2012-01-01

The accurate measurement of ecosystem biomass is of great importance in scientific, resource management and energy sectors. In particular, biomass is a direct measurement of carbon storage within an ecosystem and of great importance for carbon cycle science and carbon emission mitigation. Remote Sensing is the most accurate tool for global biomass measurements because of the ability to measure large areas. Current biomass estimates are derived primarily from ground-based samples, as compiled and reported in inventories and ecosystem samples. By using remote sensing technologies, we are able to scale up the sample values and supply wall to wall mapping of biomass.

Forestry applications project/timber resource. Sam Houston National forest inventory and development of a survey planning model

NASA Technical Reports Server (NTRS)

Colwell, R. N.

1976-01-01

The Forestry Applications Project has been directed towards solving the problem of meeting informational needs of the resource managers utilizing remote sensing data sources including satellite data, conventional aerial photography, and direct measurement on the ground in such combinations as needed to best achieve these goals. It is recognized that sampling plays an important role in generating relevant information for managing large geographic populations. The central problem, therefore, is to define the kind and amount of sampling and the place of remote sensing data sources in that sampling system to do the best possible job of meeting the manager's informational needs.

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 3: Mission and System Requirements for the Total Earth Resources System

NASA Technical Reports Server (NTRS)

1974-01-01

Resource management missions to be performed by TERSSE are described. Mission and user requirements are defined along with information flows developed for each major resource management mission. Other topics discussed include: remote sensing platforms, remote sensor requirements, ground system architecture, and such related issues as cloud cover, resolution, orbit mechanics, and aircraft versus satellite.

A practical CO2 flux remote sensing technique

NASA Astrophysics Data System (ADS)

Queisser, Manuel; Burton, Mike

2017-04-01

An accurate quantification of CO2 flux from both natural and anthropogenic sources is of great interest in various areas of the Earth, environmental and atmospheric sciences. As emitted excess CO2 quickly dilutes into the 400 ppm ambient CO2 concentration and degassing often occurs diffusively, measuring CO2 fluxes is challenging. Therefore, fluxes are usually derived from grids of in-situ measurements, which are labour intensive measurements. Other than a safe measurement distance, remote sensing offers quick, spatially integrated and thus a more thorough measurement of gas fluxes. Active remote sensing combines these merits with operation independent of sunlight or clear sky conditions. Due to their weight and size, active remote sensing platforms for CO2, such as LIDAR, cannot easily be applied in the field or transported overseas. Moreover, their complexity requires a rather lengthy setup procedure to be undertaken by skilled personal. To meet the need for a rugged, practical CO2 remote sensing technique to scan volcanic plumes, we have developed the CO2 LIDAR. It measures 1-D column densities of CO2 with sufficient sensitivity to reveal the contribution of magmatic CO2. The CO2 LIDAR has been mounted inside a small aircraft and used to measure atmospheric column CO2 concentrations between the aircraft and the ground. It was further employed on the ground, measuring CO2 emissions from mud volcanism. During the measurement campaign the CO2 LIDAR demonstrated reliability, portability, quick set-up time (10 to 15 min) and platform independence. This new technique opens the possibility of rapid, comprehensive surveys of point source, open-vent CO2 emissions, as well as emissions from more diffuse sources such as lakes and fumarole fields. Currently, within the proof-of-concept ERC project CarbSens, a further reduction in size, weight and operational complexity is underway with the goal to commercialize the platform. Areas of potential applications include fugitive CO2 detection at carbon capture and storage sites, volcano monitoring and bottom-up quantification of CO2 fluxes, such as from urban areas or natural sources.

Monitoring Ecosystem Dynamics Ecosystem Using Hyperspectral Reflectance and a Robotic Tram System in Barrow Alaska

NASA Astrophysics Data System (ADS)

Goswami, S.; Gamon, J. A.; Tweedie, C. E.

2012-12-01

Understanding the future state of the earth system requires improved knowledge of ecosystem dynamics and long term observations of how ecosystem structures and functions are being impacted by global change. Improving remote sensing methods is essential for such advancement because satellite remote sensing is the only means by which landscape to continental-scale change can be observed. The Arctic appears to be impacted by climate change more than any other region on Earth. Arctic terrestrial ecosystems comprise only 6% of the land surface area on Earth yet contain an estimated 25% of global soil organic carbon, most of which is stored in permafrost. If projected increases in plant productivity do not offset forecast losses of soil carbon to the atmosphere as greenhouse gases, regional to global greenhouse warming could be enhanced. Soil moisture is an important control of land-atmosphere carbon exchange in arctic terrestrial ecosystems. However, few studies to date have examined using remote sensing, or developed remote sensing methods for observing the complex interplay between soil moisture and plant phenology and productivity in arctic landscapes. This study was motivated by this knowledge gap and addressed the following questions as a contribution to a large scale, multi investigator flooding and draining experiment funded by the National Science Foundation near Barrow, Alaska from 2005 - 2009. 1. How can optical remote sensing be used to monitor the surface hydrology of arctic landscapes? 2. What are the spatio-temporal dynamics of land-surface phenology (NDVI) in the study area and do hydrological treatment has any effect on inter-annual patterns? A new spectral index, the normalized difference surface water index (NDSWI) was developed and tested at multiple spatial and temporal scales. NDSWI uses the 460nm (blue) and 1000nm (IR) bands and was developed to capture surface hydrological dynamics in the study area using the robotic tram system. When applied to high spatial resolution satellite imagery, NDSWI was also able to capture changes in surface hydrology at the landscape scale. Interannual patterns of landsurface phenology (measured with the normalized difference vegetation index - NDVI) unexpectedly lacked marked differences under experimental conditions. Measurement of NDVI was, however, compromised when WTD was above ground level. NDVI and NDSWI were negatively correlated when WTD was above ground level, which held when scaled to MODIS imagery collected from satellite, suggesting that published findings showing a 'greening of the Arctic' may be related to a 'drying of the Arctic' in landscapes dominated by vegetated landscapes where WTD is close to ground level.

Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

NASA Astrophysics Data System (ADS)

Schneider, M.; González, Y.; Dyroff, C.; Christner, E.; Wiegele, A.; Barthlott, S.; García, O. E.; Sepúlveda, E.; Hase, F.; Andrey, J.; Blumenstock, T.; Guirado, C.; Ramos, R.; Rodríguez, S.

2014-07-01

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isototopologue remote sensing and in-situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products (generated from ground-based FTIR, Fourier Transform InfraRed, spectrometer and space-based IASI, Infrared Atmospheric Sounding Interferometer, observation). As reference we use well calibrated in-situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues and the scatter with respect to the in-situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In addition, we find indications for a positive δD bias in the remote sensing products. The δD data are scientifically interesting only if they add information to the H2O observations. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data by comparing δD-vs.-H2O curves. First, we show that the added value of δD as seen in the Picarro data is similarly seen in FTIR data measured in coincidence. Second, we document that the δD-vs.-H2O curves obtained from the different in-situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

Evaluation criteria for software classification inventories, accuracies, and maps

NASA Technical Reports Server (NTRS)

Jayroe, R. R., Jr.

1976-01-01

Statistical criteria are presented for modifying the contingency table used to evaluate tabular classification results obtained from remote sensing and ground truth maps. This classification technique contains information on the spatial complexity of the test site, on the relative location of classification errors, on agreement of the classification maps with ground truth maps, and reduces back to the original information normally found in a contingency table.

Exploring multi-scale forest above ground biomass estimation with optical remote sensing imageries

NASA Astrophysics Data System (ADS)

Koju, U.; Zhang, J.; Gilani, H.

2017-02-01

Forest shares 80% of total exchange of carbon between the atmosphere and the terrestrial ecosystem. Due to this monitoring of forest above ground biomass (as carbon can be calculated as 0.47 part of total biomass) has become very important. Forest above ground biomass as being the major portion of total forest biomass should be given a very careful consideration in its estimation. It is hoped to be useful in addressing the ongoing problems of deforestation and degradation and to gain carbon mitigation benefits through mechanisms like Reducing Emissions from Deforestation and Forest Degradation (REDD+). Many methods of above ground biomass estimation are in used ranging from use of optical remote sensing imageries of very high to very low resolution to SAR data and LIDAR. This paper describes a multi-scale approach for assessing forest above ground biomass, and ultimately carbon stocks, using very high imageries, open source medium resolution and medium resolution satellite datasets with a very limited number of field plots. We found this method is one of the most promising method for forest above ground biomass estimation with higher accuracy and low cost budget. Pilot study was conducted in Chitwan district of Nepal on the estimation of biomass using this technique. The GeoEye-1 (0.5m), Landsat (30m) and Google Earth (GE) images were used remote sensing imageries. Object-based image analysis (OBIA) classification technique was done on Geo-eye imagery for the tree crown delineation at the watershed level. After then, crown projection area (CPA) vs. biomass model was developed and validated at the watershed level. Open source GE imageries were used to calculate the CPA and biomass from virtual plots at district level. Using data mining technique, different parameters from Landsat imageries along with the virtual sample biomass were used for upscaling biomass estimation at district level. We found, this approach can considerably reduce field data requirements for estimation of biomass and carbon in comparison with inventory methods based on enumeration of all trees in a plot. The proposed methodology is very cost effective and can be replicated with limited resources and time.

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Finn, M.

2009-01-01

At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service-Southeast Watershed Research Lab (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To develop an accurate interpolation of the in situ readings that can be used to produce distributed representations of soil moisture (SM) and energy balances at the landscape scale for remote sensing studies, we studied (1) the temporal and spatial variations of ground temperature (GT) and infra red temperature (IRT) within 30 by 30 m plots around selected network stations; (2) the relationship between the readings from the eight 30 by 30 m plots and the point reading of the network stations for the variables SM, GT and IRT; and (3) the spatial and temporal variation of GT and IRT within agriculture landuses: grass, orchard, peanuts, cotton and bare soil in the surrounding landscape. The results showed high correlations between the station readings and the adjacent 30 by 30 m plot average value for SM; high seasonal independent variation in the GT and IRT behavior among the eight 30 by 30 m plots; and site specific, in-field homogeneity in each 30 by 30 m plot. We found statistical differences in the GT and IRT between the different landuses as well as high correlations between GT and IRT regardless of the landuse. Greater standard deviations for IRT than for GT (in the range of 2-4) were found within the 30 by 30 m, suggesting that when a single point reading for this variable is selected for the validation of either remote sensing data or water-energy models, errors may occur. The results confirmed that in this landscape homogeneous 30 by 30 m plots can be used as landscape spatial units for soil moisture and ground temperature studies. Under this landscape conditions small plots can account for local expressions of environmental processes, decreasing the errors and uncertainties in remote sensing estimates caused by landscape heterogeneity.

A remotely piloted aircraft system in major incident management: concept and pilot, feasibility study.

PubMed

Abrahamsen, Håkon B

2015-06-10

Major incidents are complex, dynamic and bewildering task environments characterised by simultaneous, rapidly changing events, uncertainty and ill-structured problems. Efficient management, communication, decision-making and allocation of scarce medical resources at the chaotic scene of a major incident is challenging and often relies on sparse information and data. Communication and information sharing is primarily voice-to-voice through phone or radio on specified radio frequencies. Visual cues are abundant and difficult to communicate between teams and team members that are not co-located. The aim was to assess the concept and feasibility of using a remotely piloted aircraft (RPA) system to support remote sensing in simulated major incident exercises. We carried out an experimental, pilot feasibility study. A custom-made, remotely controlled, multirotor unmanned aerial vehicle with vertical take-off and landing was equipped with digital colour- and thermal imaging cameras, a laser beam, a mechanical gripper arm and an avalanche transceiver. We collected data in five simulated exercises: 1) mass casualty traffic accident, 2) mountain rescue, 3) avalanche with buried victims, 4) fisherman through thin ice and 5) search for casualties in the dark. The unmanned aerial vehicle was remotely controlled, with high precision, in close proximity to air space obstacles at very low levels without compromising work on the ground. Payload capacity and tolerance to wind and turbulence were limited. Aerial video, shot from different altitudes, and remote aerial avalanche beacon search were streamed wirelessly in real time to a monitor at a ground base. Electromagnetic interference disturbed signal reception in the ground monitor. A small remotely piloted aircraft can be used as an effective tool carrier, although limited by its payload capacity, wind speed and flight endurance. Remote sensing using already existing remotely piloted aircraft technology in pre-hospital environments is feasible and can be used to support situation assessment and information exchange at a major incident scene. Regulations are needed to ensure the safe use of unmanned aerial vehicles in major incidents. Ethical issues are abundant.

Drought monitoring using remote sensing of evapotranspiration

USDA-ARS?s Scientific Manuscript database

Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moist...

Understanding the yield gap in wheat production

USDA-ARS?s Scientific Manuscript database

Remote sensing has been used to assess various components of agricultural systems for several decades. Utilization of different wavebands in various combinations to form vegetative indices have been used to estimate ground cover, biomass, leaf chlorophyll content, light interception, leaf area index...

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.

The use of remote sensing imagery for environmental land use and flood hazard mapping

NASA Technical Reports Server (NTRS)

Mouat, D. A.; Miller, D. A.; Foster, K. E.

1976-01-01

Flood hazard maps have been constructed for Graham, Yuma, and Yavapai Counties in Arizona using remote sensing techniques. Watershed maps of priority areas were selected on the basis of their interest to the county planning staff and represented areas of imminent or ongoing development and those known to be subject to inundation by storm runoff. Landsat color infrared imagery at scales of 1:1,000,000, 1:500,000, and 1:250,000 was used together with high-altitude aerial photography at scales of 1:120,000 and 1:60,000 to determine drainage patterns and erosional features, soil type, and the extent and type of ground cover. The satellite imagery was used in the form of 70 mm chips for enhancement in a color additive viewer and in all available enlargement modes. Field checking served as the main backup to the interpretations. Areas with high susceptibility to flooding were determined with a high level of confidence from the remotely sensed imagery.

Proceedings of the twelfth international symposium on remote sensing of environment

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

Not Available

This is the third of three volumes of the proceedings of the Twelfth International Symposium on Remote Sensing of Environment, held 20 to 26 April 1978 in Manila, Philippines. This symposium is part of a continuing program investigating current activities in the field of remote sensing. The meeting is intended to promote increased international cooperation in research, development and application of this technology, and to stimulate an exchange of information on all aspects of this multidisciplinary field through the presentation of reports on work planned, in progress or completed. Presentations include those concerned with the utilization of this technology inmore » various national and international programs as well as in numerous applications for monitoring and managing the earth's resources and man's global environment. Ground-based, airborne, and spaceborne sensor systems and both manual and machine-assisted data analysis and interpretation are included. All papers included in their entirety were abstracted and indexed for EDB/ERA.« less

A Terminal Area Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Serke, David J.

2014-01-01

NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

a Novel Framework for Remote Sensing Image Scene Classification

NASA Astrophysics Data System (ADS)

Jiang, S.; Zhao, H.; Wu, W.; Tan, Q.

2018-04-01

High resolution remote sensing (HRRS) images scene classification aims to label an image with a specific semantic category. HRRS images contain more details of the ground objects and their spatial distribution patterns than low spatial resolution images. Scene classification can bridge the gap between low-level features and high-level semantics. It can be applied in urban planning, target detection and other fields. This paper proposes a novel framework for HRRS images scene classification. This framework combines the convolutional neural network (CNN) and XGBoost, which utilizes CNN as feature extractor and XGBoost as a classifier. Then, this framework is evaluated on two different HRRS images datasets: UC-Merced dataset and NWPU-RESISC45 dataset. Our framework achieved satisfying accuracies on two datasets, which is 95.57 % and 83.35 % respectively. From the experiments result, our framework has been proven to be effective for remote sensing images classification. Furthermore, we believe this framework will be more practical for further HRRS scene classification, since it costs less time on training stage.

Remote sensing of Qatar nearshore habitats with perspectives for coastal management.

PubMed

Warren, Christopher; Dupont, Jennifer; Abdel-Moati, Mohamed; Hobeichi, Sanaa; Palandro, David; Purkis, Sam

2016-04-30

A framework is proposed for utilizing remote sensing and ground-truthing field data to map benthic habitats in the State of Qatar, with potential application across the Arabian Gulf. Ideally the methodology can be applied to optimize the efficiency and effectiveness of mapping the nearshore environment to identify sensitive habitats, monitor for change, and assist in management decisions. The framework is applied to a case study for northeastern Qatar with a key focus on identifying high sensitivity coral habitat. The study helps confirm the presence of known coral and provides detail on a region in the area of interest where corals have not been previously mapped. Challenges for the remote sensing methodology associated with natural heterogeneity of the physical and biological environment are addressed. Recommendations on the application of this approach to coastal environmental risk assessment and management planning are discussed as well as future opportunities for improvement of the framework. Copyright © 2015 Elsevier Ltd. All rights reserved.

Appraisement of environment remote sensing method in mining area

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Zhen, Han; Jiang, Tao; Lei, Liqing; Gong, Cailan

1998-08-01

Coal mining is attached great importance by society as a key profession of environmental pollution. The monitor and protection of coal-mine environment is a developing profession in China. The sulfur dioxide, carbon dioxide, carbon monoxide and other waste gases, which are put out by the spontaneous combustion or weathering of gangue are an important pollution resource of atmosphere. The stack of gangue held down many farmlands. Smoke, coal dust and powder coal ash pollute the environment of mining area and surroundings though the affection of monsoon. The pH value of water which coal mine drained off is low, and the drinking, farming and animal husbandry water where it flowed are affected. The surface subsidence which mining caused is a typical destruction of ground environment. The people pay attention to remote sensing as a method of rapidly, cheaply regional environment investigation. The paper tires making an appraisement of mining area environment monitor by many kind methods of remote sensing from the characteristic of mining area environment.

International Symposium on Remote Sensing of Environment, 17th, University of Michigan, Ann Arbor, MI, May 9-13, 1983, Proceedings. Volumes 1, 2 & 3

NASA Technical Reports Server (NTRS)

1984-01-01

The collection, processing, and analysis of remote-sensing data from ground-based, airborne, and spaceborne instruments for application to the monitoring and management of the earth and environment and resources are examined in reviews and reports, some in summary form. Subject areas covered include US policy and directions on remote sensing (RS); the future of terrestrial RS from space; RS of land, oceans, and atmosphere from a global perspective; RS in hydrological modeling; microprocessing technology; array processors; geobased information systems; artificial intelligence; the Shuttle imaging radar; and current results from Landsat-4. Among the specific topics discussed are RS application to hydrocarbon exploration, airborne gamma-radiation assessment of snow water equivalent, surface-vegetation-biomass modeling from AVHRR and Landsat data, Landsat imagery of Mediterranean pollution, fast two-dimensional filtering of thermal-scanner data, RS of severe convective storms, registration of rotated images by invariant moments, and the geometric accuracy of Landsat-4 Thematic-Mapper P-tapes.

Spatialized Application of Remotely Sensed Data Assimilation Methods for Farmland Drought Monitoring Using Two Different Crop Models

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Casa, Raffaele; Pignatti, Stefano; Castaldi, Fabio; Yang, Hao; Guijun, Yang

2016-08-01

The aim of this work was to develop a tool to evaluate the effect of water stress on yield losses at the farmland and regional scale, by assimilating remotely sensed biophysical variables into crop growth models. Biophysical variables were retrieved from HJ1A, HJ1B and Landsat 8 images, using an algorithm based on the training of artificial neural networks on PROSAIL.For the assimilation, two crop models of differing degree of complexity were used: Aquacrop and SAFY. For Aquacrop, an optimization procedure to reduce the difference between the remotely sensed and simulated CC was developed. For the modified version of SAFY, the assimilation procedure was based on the Ensemble Kalman Filter.These procedures were tested in a spatialized application, by using data collected in the rural area of Yangling (Shaanxi Province) between 2013 and 2015Results were validated by utilizing yield data both from ground measurements and statistical survey.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J. E.; Richardson, T.; Yang, Z.

2012-12-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to present this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data.We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J.; Richardson, T. S.

2012-04-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to display this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data. We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

Application of remote thermal scanning to the NASA energy conservation program

NASA Technical Reports Server (NTRS)

Bowman, R. L.; Jack, J. R.

1977-01-01

Airborne thermal scans of all NASA centers were made during 1975 and 1976. The remotely sensed data were used to identify a variety of heat losses, including those from building roofs and central heating system distribution lines. Thermal imagery from several NASA centers is presented to demonstrate the capability of detecting these heat losses remotely. Many heat loss areas located by the scan data were verified by ground surveys. At this point, at least for such energy-intensive areas, thermal scanning is an excellent means of detecting many possible energy losses.

Application of airborne hyperspectral remote sensing for the retrieval of forest inventory parameters

NASA Astrophysics Data System (ADS)

Dmitriev, Yegor V.; Kozoderov, Vladimir V.; Sokolov, Anton A.

2016-04-01

Collecting and updating forest inventory data play an important part in the forest management. The data can be obtained directly by using exact enough but low efficient ground based methods as well as from the remote sensing measurements. We present applications of airborne hyperspectral remote sensing for the retrieval of such important inventory parameters as the forest species and age composition. The hyperspectral images of the test region were obtained from the airplane equipped by the produced in Russia light-weight airborne video-spectrometer of visible and near infrared spectral range and high resolution photo-camera on the same gyro-stabilized platform. The quality of the thematic processing depends on many factors such as the atmospheric conditions, characteristics of measuring instruments, corrections and preprocessing methods, etc. An important role plays the construction of the classifier together with methods of the reduction of the feature space. The performance of different spectral classification methods is analyzed for the problem of hyperspectral remote sensing of soil and vegetation. For the reduction of the feature space we used the earlier proposed stable feature selection method. The results of the classification of hyperspectral airborne images by using the Multiclass Support Vector Machine method with Gaussian kernel and the parametric Bayesian classifier based on the Gaussian mixture model and their comparative analysis are demonstrated.

Remote sensing and implications for variable-rate application using agricultural aircraft

NASA Astrophysics Data System (ADS)

Thomson, Steven J.; Smith, Lowrey A.; Ray, Jeffrey D.; Zimba, Paul V.

2004-01-01

Aircraft routinely used for agricultural spray application are finding utility for remote sensing. Data obtained from remote sensing can be used for prescription application of pesticides, fertilizers, cotton growth regulators, and water (the latter with the assistance of hyperspectral indices and thermal imaging). Digital video was used to detect weeds in early cotton, and preliminary data were obtained to see if nitrogen status could be detected in early soybeans. Weeds were differentiable from early cotton at very low altitudes (65-m), with the aid of supervised classification algorithms in the ENVI image analysis software. The camera was flown at very low altitude for acceptable pixel resolution. Nitrogen status was not detectable by statistical analysis of digital numbers (DNs) obtained from images, but soybean cultivar differences were statistically discernable (F=26, p=0.01). Spectroradiometer data are being analyzed to identify narrow spectral bands that might aid in selecting camera filters for determination of plant nitrogen status. Multiple camera configurations are proposed to allow vegetative indices to be developed more readily. Both remotely sensed field images and ground data are to be used for decision-making in a proposed variable-rate application system for agricultural aircraft. For this system, prescriptions generated from digital imagery and data will be coupled with GPS-based swath guidance and programmable flow control.

Remote sensing detection of atmospheric pollutants using lidar, sodar and correlation with air quality data in an industrial area

NASA Astrophysics Data System (ADS)

Steffens, Juliana; da Costa, Renata F.; Landulfo, Eduardo; Guardani, Roberto; Moreira, Paulo F., Jr.; Held, Gerhard

2011-11-01

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of Sao Paulo, in the city of Cubatao, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar.

Long-term monitoring on environmental disasters using multi-source remote sensing technique

NASA Astrophysics Data System (ADS)

Kuo, Y. C.; Chen, C. F.

2017-12-01

Environmental disasters are extreme events within the earth's system that cause deaths and injuries to humans, as well as causing damages and losses of valuable assets, such as buildings, communication systems, farmlands, forest and etc. In disaster management, a large amount of multi-temporal spatial data is required. Multi-source remote sensing data with different spatial, spectral and temporal resolutions is widely applied on environmental disaster monitoring. With multi-source and multi-temporal high resolution images, we conduct rapid, systematic and seriate observations regarding to economic damages and environmental disasters on earth. It is based on three monitoring platforms: remote sensing, UAS (Unmanned Aircraft Systems) and ground investigation. The advantages of using UAS technology include great mobility and availability in real-time rapid and more flexible weather conditions. The system can produce long-term spatial distribution information from environmental disasters, obtaining high-resolution remote sensing data and field verification data in key monitoring areas. It also supports the prevention and control on ocean pollutions, illegally disposed wastes and pine pests in different scales. Meanwhile, digital photogrammetry can be applied on the camera inside and outside the position parameters to produce Digital Surface Model (DSM) data. The latest terrain environment information is simulated by using DSM data, and can be used as references in disaster recovery in the future.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Runoff simulation sensitivity to remotely sensed initial soil water content

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Schmugge, T. J.; Jackson, T. J.; Unkrich, C. L.; Keefer, T. O.; Parry, R.; Bach, L. B.; Amer, S. A.

1994-05-01

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies

DTIC Science & Technology

2011-01-01

sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI ), tend to saturate at...little or no improvement over NDVI . Furthermore, indirect ground-sampling techniques often used to evaluate the potential of vegetation indices also...landscapes makes remote sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index ( NDVI

LOCAL AIR: Local Aerosol monitoring combining in-situ and Remote Sensing observations

NASA Astrophysics Data System (ADS)

Mona, Lucia; Caggiano, Rosa; Donvito, Angelo; Giannini, Vincenzo; Papagiannopoulos, Nikolaos; Sarli, Valentina; Trippetta, Serena

2015-04-01

The atmospheric aerosols have effects on climate, environment and health. Although the importance of the study of aerosols is well recognized, the current knowledge of the characteristics and their distribution is still insufficient, and there are large uncertainties in the current understanding of the role of aerosols on climate and the environment, both on a regional and local level. Overcoming these uncertainties requires a search strategy that integrates data from multiple platforms (eg, terrestrial, satellite, ships and planes) and the different acquisition techniques (for example, in situ measurements, remote sensing, modeling numerical and data assimilation) (Yu et al., 2006). To this end, in recent years, there have been many efforts such as the creation of networks dedicated to systematic observation of aerosols (eg, European Monitoring and Evaluation Programme-EMEP, European Aerosol Research Lidar NETwork-EARLINET, MicroPulse Lidar Network- MPLNET, and Aerosol Robotic NETwork-AERONET), the development and implementation of new satellite sensors and improvement of numerical models. The recent availability of numerous data to the ground, columnar and profiles of aerosols allows to investigate these aspects. An integrated approach between these different techniques could be able to provide additional information, providing greater insight into the properties of aerosols and their distribution and overcoming the limits of each single technique. In fact, the ground measurements allow direct determination of the physico-chemical properties of aerosols, but cannot be considered representative for large spatial and temporal scales and do not provide any information about the vertical profile of aerosols. On the other hand, the remote sensing techniques from the ground and satellite provide information on the vertical distribution of atmospheric aerosols both in the Planetary Boundary Layer (PBL), mainly characterized by the presence of aerosols originating from local sources, which in the troposphere, where there are aerosols transported over long distances by the phenomena of atmospheric circulation. The purpose of the LOCAL AIR project is the development of a methodology for using synergistic data at different resolutions (ground measurements, remote sensing from ground and satellite) as an effective tool for the characterization of tropospheric aerosols on a local scale. The backbone of the project is the long-term ground-based measurements collected at CIAO (CNR-IMAA Atmospheric Observatory) plus the CALIPSO observations.. The location of the plethora of instruments and measurements of atmospheric interest available at CNR-IMAA makes it a sample site not only for the realization of the methodology, but also allows a feasibility study of this method in the absence of some by analysis of the measures considered in the scaling down of the algorithm developed. It will be evaluated the applicability and reliability of the algorithm implemented for the characterization of the aerosol content to the ground in other places of special interest. Acknowledgments: LOCAL AIR is supported by PO FSE Basilicata 2007-2013 Azione n. 45/AP/05/2013/REG - CUP: G53G13000300009.

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

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

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

Quantitative comparison of airborne remote-sensed and in situ Rhodamine WT dye and temperature during RIVET & IB09

NASA Astrophysics Data System (ADS)

Lenain, L.; Clark, D. B.; Guza, R. T.; Hally-Rosendahl, K.; Statom, N.; Feddersen, F.

2012-12-01

The transport and evolution of temperature, sediment, chlorophyll, fluorescent dye, and other tracers is of significant oceanographic interest, particularly in complex coastal environments such as the nearshore, river mouths, and tidal inlets. Remote sensing improves spatial coverage over in situ observations, and ground truthing remote sensed observations is critical for its use. Here, we present remotely sensed observations of Rhodamine WT dye and Sea Surface Temperature (SST) using the SIO Modular Aerial Sensing System (MASS) and compare them with in situ observations from the IB09 (0-300 m seaward of the surfzone, Imperial Beach, CA, October 2009) and RIVET (New River Inlet, NC, May 2012) field experiments. Dye concentrations are estimated from a unique multispectral camera system that measures the emission and absorption wavelengths of Rhodamine WT dye. During RIVET, dye is also characterized using a pushbroom hyperspectral imaging system (SPECIM AISAEagle VNIR 400-990 nm) while SST is estimated using a long-wave infrared camera (FLIR SC6000HS) coupled with an infrared pyrometer (Heitronics KT19.85II). Repeated flight passes over the dye plume were conducted approximately every 5 min for up to 4.5 hr in duration with a swath width ranging from 400 to 2000 m (altitude dependent), and provided a unique spatio-temporal depiction of the plume. A dye proxy is developed using the measured radiance at the emission and absorption wavelengths of the Rhodamine WT dye. During IB09 and RIVET, in situ dye and temperature were measured with two GPS-tracked jet skis, a small boat, and moored observations. The in situ observations are compared with the remotely sensed data in these two complex coastal environments. Funding was provided by the Office of Naval Research.

Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

NASA Astrophysics Data System (ADS)

Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

2017-12-01

SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

Report to the National Park Service for Permit LAKE-2014-SCI-002

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

Burnley, Pamela C.

The overall purpose of the study is to determine how to use existing geologic data to predict gamma-ray background levels as measured during aerial radiological surveys. Aerial radiological surveys have typically been for resource exploration purposes but are now also used for homeland security purposes and nuclear disaster assessment as well as determining the depth of snowpack. Foreknowledge of the background measured during aerial radiological survey will be valuable for all the above applications. The gamma-ray background comes from the rocks and soil within the first 30 cm of the earth’s surface in the area where the survey is beingmore » made. The background should therefore be predictable based on an understanding of the distribution and geochemistry of the rocks on the surface. We are using a combination of geologic maps, remote sensing imagery and geochemical data from existing databases and the scientific literature to develop a method for predicting gamma-ray backgrounds. As part of this project we have an opportunity to ground truth our technique along a survey calibration line near Lake Mojave that is used by the Remote Sensing Lab (RSL) of National Security Technologies, LLC (NSTec). RSL makes aerial measurements along this line on a regular basis, so the aerial background in the area is well known. By making ground-based measurements of the gamma-ray background and detailed observations of the geology of the ground surface as well as local topography we will have the data we need to make corrections to the models we build based on the remote sensing and geologic data. Our project involves collaborators from the Airborne Geophysics Section of the Geological Survey of Canada as well as from NSTec’s RSL. Findings« less

EMC problems on board the remote sensing and communications satellites equipped with electric propulsions

NASA Astrophysics Data System (ADS)

Plokhikh, A.; Vazhenin, N.; Soganova, G.

Wide application of electric propulsions (EP) as attitude control and orbit correction thrusters for a numerous class of satellites (remote sensing and communications satellites including) imposes new problems before the developers in meeting the electromagnetic compatibility requirements on board these satellites. This is connected with the fact that any EP is a source of interference broad-band emission reaching, as a rule, frequency ranges used by on-board radio systems designed for remote sensing and communications. In this case, reliable joint operation should be secured for the highly sensitive on -board radio receiving systems and sensors of remote sensing systems on one hand and EP on the other. In view of this, analysis is rather actual for the influence of EP interference emission upon the parameters and characteristics of modern remote sensing and communications systems. Procedures and results of typical operating characteristics calculation for the radio systems with the presence of operating EP on board are discussed in the paper on the basis of systematic approach with the following characteristics being among them: signal-to-noise ratio, range, data transmission rate, error probability, etc. EP effect is taken into account by the statistical analysis for the results of joint influence of valid signal and interference produced by EP upon the quality indices of communication systems and paths of the sensors being the parts of remote sensing systems. Test data for the measured EP interference characteristics were used for qualitative assessments. All necessary measurements were made by authors on the basis of the test procedure developed by them for assessing self- em ission of EP under ground conditions that may be used as a base for the certification of such measurements. Analysis was made on the basis of test data obtained and calculation procedures developed by authors for the EP influence upon the qualitative characteristics of remote sensing and communications radio systems that revealed the presence of destructive effect resulting in substantial decrease in maximum range and data transmission rate, as well as reduction of sensitivity for the sensors of remote sensing systems. Recommendations are given on the basis of analysis made for the optimization of radio systems and calibration of their sensors at a presence of electric propulsions on board the satellites.

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.

Combining optical remote sensing, agricultural statistics and field observations for culture recognition over a peri-urban region

NASA Astrophysics Data System (ADS)

Delbart, Nicolas; Emmanuelle, Vaudour; Fabienne, Maignan; Catherine, Ottlé; Jean-Marc, Gilliot

2017-04-01

This study explores the potential of multi-temporal optical remote sensing, with high revisit frequency, to derive missing information on agricultural calendar and crop types over the agricultural lands in the Versailles plain in the western Paris suburbs. This study comes besides past and ongoing studies on the use of radar and high spatial resolution optical remote sensing to monitor agricultural practices in this study area (e.g. Vaudour et al. 2014). Agricultural statistics, such as the Land Parcel Identification System (LPIS) for France, permit to know the nature of annual crops for each digitized declared field of this land parcel registry. However, within each declared field several cropped plots and a diversity of practices may exist, being marked by agricultural rotations which vary both spatially and temporally within it and differ from one year to the other. Even though the new LPIS to be released in 2016 is expected to describe individual plots within declared fields, its attributes may not enable to discriminate between winter and spring crops. Here we evaluate the potential of high observation frequency remote sensing to differentiate seasonal crops based essentially on the seasonality of the spectral properties. In particular, we use the Landsat data to spatially disaggregate the LPIS statistical data, on the basis of the analysis of the remote sensing spectral seasonality measured on a number of selected ground-observed fields. This work is carried out in the framework of the CNES TOSCA-PLEIADES-CO of the French Space Agency.

A Design of a Novel Airborne Aerosol Spectrometer for Remote Sensing Validation

NASA Astrophysics Data System (ADS)

Adler, G. A.; Brock, C. A.; Dube, W. P.; Erdesz, F.; Gordon, T.; Law, D. C.; Manfred, K.; Mason, B. J.; McLaughlin, R. J.; Richardson, M.; Wagner, N. L.; Washenfelder, R. A.; Murphy, D. M.

2016-12-01

Aerosols and their effect on the radiative properties of clouds contribute one of the largest sources of uncertainty to the Earth's energy budget. Many current global assessments, of atmospheric aerosol radiative forcing rely heavily on remote sensing observation; therefore, in situ aircraft and ground-based measurements are essential for validation of remote sensing measurements. Cavity ringdown spectrometers (CRD) measure aerosol extinction and are commonly used to validate remote sensing observations. These instruments have been deployed on aircraft based platforms over the years thus providing the opportunity to measure these properties over large areas in various conditions. However, deployment of the CRD on an aircraft platform has drawbacks. Typically, aircraft based CRDs draw sampled aerosol into a cabin based instrument through long lengths of tubing. This limits the ability of the instrument to measure: 1) Course mode aerosols (e.g. dust) 2) Aerosols at high relative humidity (above 90%) Here we describe the design of a novel aircraft based open path CRD. The open path CRD is intended to be mounted external to the cabin and has no sample tubing for aerosol delivery, thus measuring optical properties of all aerosol at the ambient conditions. However, the design of an open path CRD for operation on a wing-mounted aircraft platform has certain design complexities. The instrument's special design features include 2 CRD channels, 2 airfoils around the open Path CRD and a configuration which could be easily aligned and rigid at the same time. This novel implementation of cavity ringdown spectroscopy will provide a better assessment of the accuracy of remote sensing satellite measurements

Strip mine reclamation: criteria and methods for measurement of revegetation success. Progress report, April 1, 1980-March 31, 1981

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

Carrel, J.E.; Kucera, C.L.; Johannsen, C.J.

1980-12-01

During this contract period research was continued at finding suitable methods and criteria for determining the success of revegetation in Midwestern prime ag lands strip mined for coal. Particularly important to the experimental design was the concept of reference areas, which were nearby fields from which the performance standards for reclaimed areas were derived. Direct and remote sensing techniques for measuring plant ground cover, production, and species composition were tested. 15 mine sites were worked in which were permitted under interim permanent surface mine regulations and in 4 adjoining reference sites. Studies at 9 prelaw sites were continued. All sitesmore » were either in Missouri or Illinois. Data gathered in the 1980 growing season showed that 13 unmanaged or young mineland pastures generally had lower average ground cover and production than 2 reference pastures. In contrast, yields at approximately 40% of 11 recently reclaimed mine sites planted with winter wheat, soybeans, or milo were statistically similar to 3 reference values. Digital computer image analysis of color infrared aerial photographs, when compared to ground level measurements, was a fast, accurate, and inexpensive way to determine plant ground cover and areas. But the remote sensing approach was inferior to standard surface methods for detailing plant species abundance and composition.« less

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

PubMed Central

Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.

2014-01-01

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949

LAI inversion algorithm based on directional reflectance kernels.

PubMed

Tang, S; Chen, J M; Zhu, Q; Li, X; Chen, M; Sun, R; Zhou, Y; Deng, F; Xie, D

2007-11-01

Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Near Real Time Applications for Maritime Situational Awareness

NASA Astrophysics Data System (ADS)

Schwarz, E.; Krause, D.; Berg, M.; Daedelow, H.; Maass, H.

2015-04-01

Applications to derive maritime value added products like oil spill and ship detection based on remote sensing SAR image data are being developed and integrated at the Ground Station Neustrelitz, part of the German Remote Sensing Data Center. Products of meteo-marine parameters like wind and wave will complement the product portfolio. Research and development aim at the implementation of highly automated services for operational use. SAR images are being used because of the possibility to provide maritime products with high spatial resolution over wide swaths and under all weather conditions. In combination with other information like Automatic Identification System (AIS) data fusion products are available to support the Maritime Situational Awareness.

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M. P.; Arvidson, R. E.; Bell, J. F., III; Christensen, P. R.; Crisp, J. A.; Ehlmann, B. L.; Fergason, R. L.; Grant, J. A.; Haldemann, A. F. C.; Parker, T. J.;

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Application of remote sensing to the photogeologic mapping of the region of the Itatiaia alkaline complex. M.S. Thesis; [Minas Gerais, Rio De Janeiro, Sao Paulo, and Itatiaia, Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Rodrigues, J. E.

1981-01-01

Remote sensing methods applied to geologically complex areas, through interaction of ground truth and information obtained from multispectral LANDSAT images and radar mosaics were evaluated. The test area covers parts of Minos Gerais, Rio De Janeiro and Sao Paulo states and contains the alkaline complex of Itatiaia and surrounding Precambrian terrains. Geological and structural mapping was satisfactory; however, lithological varieties which form the massif's could not be identified. Photogeological lineaments were mapped, some of which represent the boundaries of stratigraphic units. Automatic processing was used to classify sedimentary areas, which includes the talus deposits of the alkaline massifs.

Satellite, environmental, and medical information applied to epidemiological monitoring

NASA Technical Reports Server (NTRS)

Roberts, Donald R.; Legters, Llewellyn J.

1991-01-01

Improved communications and space-science technologies, such as remote sensing, offer hope of new, more holistic approaches to combating many arthropod-borne disease problems. The promise offered by these technologies has surfaced at a time when global and national efforts at disease control are in decline. Indeed, these programs seem to be losing ground against the arthropod-borne diseases just as rapidly as we seem to be moving forward in technological development. Given these circumstances, we can only hope that remote sensing and geographic information system (GIS) technologies can be pressed into service to help target the temporal and spatial application of control measures and to help in developing new control strategies.

A computer software system for integration and analysis of grid-based remote sensing data with other natural resource data. Remote Sensing Project

NASA Technical Reports Server (NTRS)

Tilmann, S. E.; Enslin, W. R.; Hill-Rowley, R.

1977-01-01

A computer-based information system is described designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. Soil, land cover/use, topographic and geological maps were used as a data base to develope an eleven map portfolio. The major themes of the portfolio are land cover/use, non-point water pollution, waste disposal, and ground water recharge.

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1980-01-01

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

REMOTE SENSING FOR DETECTING SWINE ANIMAL FEEDING OPERATIONS

EPA Science Inventory

Surface runoff from animal feeding operations (AFO's) and its infiltration into ground water can
pose a number of risks to water quality mainly because of the amount of animal manure and wastewater they produce. Excess nutrients generated by livestock facilities can lead to a...

Development of EPA OTM 10 for Landfill Applications

EPA Science Inventory

In 2006, the U.S. Environmental Protection Agency posted a new test method on its website called OTM 10 which describes direct measurement of pollutant mass emission flux from area sources using ground-based optical remote sensing. The method has validated application to relative...

Multiscale analyses of solar-induced florescence and gross primary production

USDA-ARS?s Scientific Manuscript database

Remotely sensed solar induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground-based GPP have posed challenges toward...

Evaluation of remote sensing aerial systems in existing transportation practices, phase II.

DOT National Transportation Integrated Search

2011-06-01

A low-cost aerial platform represents a flexible tool for acquiring high-resolution images for ground areas of interest. The geo-referencing of objects within these images could benefit civil engineers in a variety of research areas including, but no...

Satellite and Ground-based Radiometers Reveal Much Lower Dust Absorption of Sunlight than Used in Climate Models

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Tanre, D.; Dubovik, O.; Karnieli, A.; Remer, L. A.; Einaudi, Franco (Technical Monitor)

2000-01-01

The ability of dust to absorb solar radiation and heat the atmosphere is one of the main uncertainties in climate modeling and the prediction of climate change. Dust absorption is not well known due to limitations of in situ measurements. New techniques to measure dust absorption are needed in order to assess the impact of dust on climate. Here we report two new independent remote sensing techniques that provide sensitive measurements of dust absorption. Both are based on remote sensing. One uses satellite spectral measurements, the second uses ground based sky measurements from the AERONET network. Both techniques demonstrate that Saharan dust absorption of solar radiation is several times smaller than the current international standards. Dust cooling of the earth system in the solar spectrum is therefore significantly stronger than recent calculations indicate. We shall also address the issue of the effects of dust non-sphericity on the aerosol optical properties.

Sensing underground coal gasification by ground penetrating radar

NASA Astrophysics Data System (ADS)

Kotyrba, Andrzej; Stańczyk, Krzysztof

2017-12-01

The paper describes the results of research on the applicability of the ground penetrating radar (GPR) method for remote sensing and monitoring of the underground coal gasification (UCG) processes. The gasification of coal in a bed entails various technological problems and poses risks to the environment. Therefore, in parallel with research on coal gasification technologies, it is necessary to develop techniques for remote sensing of the process environment. One such technique may be the radar method, which allows imaging of regions of mass loss (voids, fissures) in coal during and after carrying out a gasification process in the bed. The paper describes two research experiments. The first one was carried out on a large-scale model constructed on the surface. It simulated a coal seam in natural geological conditions. A second experiment was performed in a shallow coal deposit maintained in a disused mine and kept accessible for research purposes. Tests performed in the laboratory and in situ conditions showed that the method provides valuable data for assessing and monitoring gasification surfaces in the UCG processes. The advantage of the GPR method is its high resolution and the possibility of determining the spatial shape of various zones and forms created in the coal by the gasification process.

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.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

Soil water content and evaporation determined by thermal parameters obtained from ground-based and remote measurements

NASA Technical Reports Server (NTRS)

Reginato, R. J.; Idso, S. B.; Jackson, R. D.; Vedder, J. F.; Blanchard, M. B.; Goettelman, R.

1976-01-01

Soil water contents from both smooth and rough bare soil were estimated from remotely sensed surface soil and air temperatures. An inverse relationship between two thermal parameters and gravimetric soil water content was found for Avondale loam when its water content was between air-dry and field capacity. These parameters, daily maximum minus minimum surface soil temperature and daily maximum soil minus air temperature, appear to describe the relationship reasonably well. These two parameters also describe relative soil water evaporation (actual/potential). Surface soil temperatures showed good agreement among three measurement techniques: in situ thermocouples, a ground-based infrared radiation thermometer, and the thermal infrared band of an airborne multispectral scanner.

Sensor web enables rapid response to volcanic activity

USGS Publications Warehouse

Davies, Ashley G.; Chien, Steve; Wright, Robert; Miklius, Asta; Kyle, Philip R.; Welsh, Matt; Johnson, Jeffrey B.; Tran, Daniel; Schaffer, Steven R.; Sherwood, Robert

2006-01-01

Rapid response to the onset of volcanic activity allows for the early assessment of hazard and risk [Tilling, 1989]. Data from remote volcanoes and volcanoes in countries with poor communication infrastructure can only be obtained via remote sensing [Harris et al., 2000]. By linking notifications of activity from ground-based and spacebased systems, these volcanoes can be monitored when they erupt.Over the last 18 months, NASA's Jet Propulsion Laboratory (JPL) has implemented a Volcano Sensor Web (VSW) in which data from ground-based and space-based sensors that detect current volcanic activity are used to automatically trigger the NASA Earth Observing 1 (EO-1) spacecraft to make highspatial-resolution observations of these volcanoes.

Multi-scales and multi-satellites estimates of evapotranspiration with a residual energy balance model in the Muzza agricultural district in Northern Italy

NASA Astrophysics Data System (ADS)

Corbari, C.; Bissolati, M.; Mancini, M.

2015-05-01

Evapotranspiration estimates were performed with a residual energy balance model (REB) over an agricultural area using remote sensing data. REB uses land surface temperature (LST) as main input parameter so that energy fluxes were computed instantaneously at the time of data acquisition. Data from MODIS and SEVIRI sensors were used and downscaling techniques were implemented to improve their spatial resolutions. Energy fluxes at the original spatial resolutions (1000 m for MODIS and 5000 m for SEVIRI) as well as at the downscaled resolutions (250 m for MODIS and 1000 m for SEVIRI) were calculated with the REB model. Ground eddy covariance data and remote sensing information from the Muzza agricultural irrigation district in Italy from 2010 to 2012 gave the opportunity to validate and compare spatially distributed energy fluxes. The model outputs matched quite well ground observations when ground LST data were used, while differences increased when MODIS and SEVIRI LST were used. The spatial analysis revealed significant differences between the two sensors both in term of LST (around 2.8 °C) and of latent heat fluxes with values (around 100 W m-2).

Land movement monitoring at the Mavropigi lignite mine using spaceborne D-InSAR

NASA Astrophysics Data System (ADS)

Papadaki, Eirini; Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis; Schilizzi, Pavlos

2013-08-01

This paper examines the capability of remote sensing radar interferometry to monitor land movements, as it varies with time, in areas close to open pit lignite mines. The study area is the "Mavropigi" lignite mine in Ptolemais, Northern Greece; whose continuous operation is of vital importance to the electric power supply of Greece. The mine is presently 100-120m deep while horizontal and vertical movements have been measured in the vicinity of the pit. Within the mine, ground geodetic monitoring has revealed an average rate of movement amounting to 10-20mm/day at the southeast slopes. In this work, differential interferometry (DInSAR), using 19 Synthetic Aperture Radar (SAR) images of ALOS satellite, has been applied to monitor progression of land movement caused my mining within the greater area of "Mavropigi" region. The results of this work show that DInSAR can be used effectively to capture ground movement information, well before signs of movements can be observed visually in the form of imminent fissures and tension cracks. The advantage of remote sensing interferometry is that it can be applied even in inaccessible areas where monitoring with ground equipment is either impossible or of high-cost (large areas).

In-flight edge response measurements for high-spatial-resolution remote sensing systems

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Pagnutti, Mary A.; Ryan, Robert; Zanoni, Vickie

2002-09-01

In-flight measurements of spatial resolution were conducted as part of the NASA Scientific Data Purchase Verification and Validation process. Characterization included remote sensing image products with ground sample distance of 1 meter or less, such as those acquired with the panchromatic imager onboard the IKONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effects of both the image acquisition system and image post-processing. Spatial resolution was characterized by full width at half maximum of an edge-response-derived line spread function. The edge responses were analyzed using the tilted-edge technique that overcomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as tarps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. The effects of such factors as acquisition geometry, temporal variability, Modulation Transfer Function compensation, and ground sample distance on spatial resolution were investigated.

Integration of Remote Sensing Products with Ground-Based Measurements to Understand the Dynamics of Nepal's Forests and Plantation Sites

NASA Astrophysics Data System (ADS)

Gilani, H.; Jain, A. K.

2016-12-01

This study assembles information from three sources - remote sensing, terrestrial photography and ground-based inventory data, to understand the dynamics of Nepal's tropical and sub-tropical forests and plantation sites for the period 1990-2015. Our study focuses on following three specific district areas, which have conserved forests through social and agroforestry management practices: 1. Dolakha district: This site has been selected to study the impact of community-based forest management on land cover change using repeat photography and satellite imagery, in combination with interviews with community members. The study time period is during the period 1990-2010. We determined that satellite data with ground photographs can provide transparency for long term monitoring. The initial results also suggests that community-based forest management program in the mid-hills of Nepal was successful. 2. Chitwan district: Here we use high resolution remote sensing data and optimized community field inventories to evaluate potential application and operational feasibility of community level REDD+ measuring, reporting and verification (MRV) systems. The study uses temporal dynamics of land cover transitions, tree canopy size classes and biomass over a Kayar khola watershed REDD+ study area with community forest to evaluate satellite Image segmentation for land cover, linear regression model for above ground biomass (AGB), and estimation and monitoring field data for tree crowns and AGB. We study three specific years 2002, 2009, 2012. Using integration of WorldView-2 and airborne LiDAR data for tree species level. 3. Nuwakot district: This district was selected to study the impact of establishment of tree plantation on total barren/fallow. Over the last 40 year, this area has went through a drastic changes, from barren land to forest area with tree species consisting of Dalbergia sissoo, Leucaena leucocephala, Michelia champaca, etc. In 1994, this district area was registered and established to grow and process high quality trees shaded of Arabica coffee beans. Here we use temporal satellite images and repeat terrestrial and aerial photographs, along with plot level biomass to show impact of this positive transformation of the landscape on above and below ground carbon masses. The study time period is 1990-2015.

Ground-based SMART-COMMIT Measurements for Studying Aerosol and Cloud Properties

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2008-01-01

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

Comprehensive UAV agricultural remote-sensing research at Texas A M University

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Olsenholler, Jeffrey; Valasek, John; Murray, Seth C.; Bishop, Michael P.

2016-05-01

Unmanned aerial vehicles (UAVs) have advantages over manned vehicles for agricultural remote sensing. Flying UAVs is less expensive, is more flexible in scheduling, enables lower altitudes, uses lower speeds, and provides better spatial resolution for imaging. The main disadvantage is that, at lower altitudes and speeds, only small areas can be imaged. However, on large farms with contiguous fields, high-quality images can be collected regularly by using UAVs with appropriate sensing technologies that enable high-quality image mosaics to be created with sufficient metadata and ground-control points. In the United States, rules governing the use of aircraft are promulgated and enforced by the Federal Aviation Administration (FAA), and rules governing UAVs are currently in flux. Operators must apply for appropriate permissions to fly UAVs. In the summer of 2015 Texas A&M University's agricultural research agency, Texas A&M AgriLife Research, embarked on a comprehensive program of remote sensing with UAVs at its 568-ha Brazos Bottom Research Farm. This farm is made up of numerous fields where various crops are grown in plots or complete fields. The crops include cotton, corn, sorghum, and wheat. After gaining FAA permission to fly at the farm, the research team used multiple fixed-wing and rotary-wing UAVs along with various sensors to collect images over all parts of the farm at least once per week. This article reports on details of flight operations and sensing and analysis protocols, and it includes some lessons learned in the process of developing a UAV remote-sensing effort of this sort.

Remotely piloted aircraft in the civil environment

NASA Technical Reports Server (NTRS)

Gregory, T. J.; Nelms, W. P.; Karmarkar, J. S.

1977-01-01

Improved remotely piloted aircraft (RPAs), i.e., incorporating reductions in size, weight, and cost, are becoming available for civilian applications. Existing RPA programs are described and predicted into the future. Attention is given to the NASA Mini-Sniffer, which will fly to altitudes of more than 20,000 m, sample the atmosphere behind supersonic cruise aircraft, and telemeter the data to ground stations. Design and operating parameters of the aircraft are given, especially the optical sensing systems, and civilian RPA uses are outlined, including airborne research, remote mapping, rescue, message relay, and transportation of need materials. Civil regulatory factors are also dealt with.

Evaluating Remotely-Sensed Soil Moisture Retrievals Using Triple Collocation Techniques

USDA-ARS?s Scientific Manuscript database

The validation is footprint-scale (~40 km) surface soil moisture retrievals from space is complicated by a lack of ground-based soil moisture instrumentation and challenges associated with up-scaling point-scale measurements from such instrumentation. Recent work has demonstrated the potential of e...

Testing of Cerex Open-Path Ultraviolet Differential Optical Absorption Spectroscopy Systems for Fenceline Monitoring Applications

EPA Science Inventory

Development of cost-effective, time-resolved fenceline measurement methods that facilitate improved emissions mitigation strategies is of growing interest to both industry and regulators. Ground-based optical remote sensing (ORS) is a well-known class of technical approaches use...

Testing of Cerex Open-Path Ultraviolet Differential Optical Absorption Spectroscopy System for Fenceline Monitoring Applications

EPA Science Inventory

Development of cost-effective, time-resolved fenceline measurement methods that facilitate improved emissions mitigation strategies is of growing interest to both industry and regulators. Ground-based optical remote sensing (ORS) is a well-known class of technical approaches use...

Possible near-IR channels for remote sensing precipitable water vapor from geostationary satellite platforms

NASA Technical Reports Server (NTRS)

Gao, B.-C.; Goetz, A. F. H.; Westwater, Ed R.; Conel, J. E.; Green, R. O.

1993-01-01

Remote sensing of troposheric water vapor profiles from current geostationary weather satellites is made using a few broadband infrared (IR) channels in the 6-13 micron region. Uncertainties greater than 20% exist in derived water vapor values just above the surface from the IR emission measurements. In this paper, we propose three near-IR channels, one within the 0.94-micron water vapor band absorption region, and the other two in nearby atmospheric windows, for remote sensing of precipitable water vapor over land areas, excluding lakes and rivers, during daytime from future geostationary satellite platforms. The physical principles are as follows. The reflectance of most surface targets varies approximately linearly with wavelength near 1 micron. The solar radiation on the sun-surface-sensor ray path is attenuated by atmospheric water vapor. The ratio of the radiance from the absorption channel with the radiances from the two window channels removes the surface reflectance effects and yields approximately the mean atmospheric water vapor transmittance of the absorption channel. The integrated water vapor amount from ground to space can be obtained with a precision of better than 5% from the mean transmittance. Because surface reflectances vary slowly with time, temporal variation of precipitable water vapor can be determined reliably. High spatial resolution, precipitable water vapor images are derived from spectral data collected by the Airborne Visable-Infrared Imaging Spectrometer, which measures solar radiation reflected by the surface in the 0.4-2.5 micron region in 10-nm channels and has a ground instantaneous field of view of 20 m from its platform on an ER-2 aircraft at 20 km. The proposed near-IR reflectance technique would complement the IR emission techniques for remote sensing of water vapor profiles from geostationary satellite platforms, especially in the boundary layer where most of the water vapor is located.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Remote sensing of smoke, clouds, and radiation using AVIRIS during SCAR experiments

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Remer, Lorraine; Kaufman, Yorman J.

1995-01-01

During the past two years, researchers from several institutes joined together to take part in two SCAR experiments. The SCAR-A (Sulfates, Clouds And Radiation - Atlantic) took place in the mid-Atlantic region of the United States in July, 1993. remote sensing data were acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), the MODIS Airborne Simulator (MAS), and a RC-10 mapping camera from an ER-2 aircraft at 20 km. In situ measurements of aerosol and cloud microphysical properties were made with a variety of instruments equipped on the University of Washington's C-131A research aircraft. Ground based measurements of aerosol optical depths and particle size distributions were made using a network of sunphotometers. The main purpose of SCAR-A experiment was to study the optical, physical and chemical properties of sulfate aerosols and their interaction with clouds and radiation. Sulfate particles are believed to affect the energy balance of the earth by directly reflecting solar radiation back to space and by increasing the cloud albedo. The SCAR-C (Smoke, Clouds And Radiation - California) took place on the west coast areas during September - October of 1994. Sets of aircraft and ground-based instruments, similar to those used during SCAR-A, were used during SCAR-C. Remote sensing of fires and smoke from AVIRIS and MAS imagers on the ER-2 aircraft was combined with a complete in situ characterization of the aerosol and trace gases from the C-131A aircraft of the University of Washington and the Cesna aircraft from the U.S. Forest Service. The comprehensive data base acquired during SCAR-A and SCAR-C will contribute to a better understanding of the role of clouds and aerosols in global change studies. The data will also be used to develop satellite remote sensing algorithms from MODIS on the Earth Observing System.

Validation for Vegetation Green-up Date Extracted from GIMMS NDVI and NDVI3g Using Variety of Methods

NASA Astrophysics Data System (ADS)

Chang, Q.; Jiao, W.

2017-12-01

Phenology is a sensitive and critical feature of vegetation change that has regarded as a good indicator in climate change studies. So far, variety of remote sensing data sources and phenology extraction methods from satellite datasets have been developed to study the spatial-temporal dynamics of vegetation phenology. However, the differences between vegetation phenology results caused by the varies satellite datasets and phenology extraction methods are not clear, and the reliability for different phenology results extracted from remote sensing datasets is not verified and compared using the ground observation data. Based on three most popular remote sensing phenology extraction methods, this research calculated the Start of the growing season (SOS) for each pixels in the Northern Hemisphere for two kinds of long time series satellite datasets: GIMMS NDVIg (SOSg) and GIMMS NDVI3g (SOS3g). The three methods used in this research are: maximum increase method, dynamic threshold method and midpoint method. Then, this study used SOS calculated from NEE datasets (SOS_NEE) monitored by 48 eddy flux tower sites in global flux website to validate the reliability of six phenology results calculated from remote sensing datasets. Results showed that both SOSg and SOS3g extracted by maximum increase method are not correlated with ground observed phenology metrics. SOSg and SOS3g extracted by the dynamic threshold method and midpoint method are both correlated with SOS_NEE significantly. Compared with SOSg extracted by the dynamic threshold method, SOSg extracted by the midpoint method have a stronger correlation with SOS_NEE. And, the same to SOS3g. Additionally, SOSg showed stronger correlation with SOS_NEE than SOS3g extracted by the same method. SOS extracted by the midpoint method from GIMMS NDVIg datasets seemed to be the most reliable results when validated with SOS_NEE. These results can be used as reference for data and method selection in future's phenology study.

Change detection using 75-year aerial photo and satellite data sets, inexpensive means to obtain 6 cm resolution data, and developing opportunities for community-oriented remote sensing through photography

USDA-ARS?s Scientific Manuscript database

Some governmental research sites have been in existence for as many as 100 years with ground photography used for documentation starting in the early 1900s(e.g., at the USDA Jornada Experimental Range(JER)(783 km2) in south central New Mexico) If ground photography is properly documented when acquir...

Detect, map, and preserve Bronze & Iron Age monuments along the pre-historic Silk Road

NASA Astrophysics Data System (ADS)

Balz, Timo; Caspari, Gino; Fu, Bihong

2017-02-01

Central Asia is rich in cultural heritage generated by thousands of years of human occupation. Aiming for a better understanding of Central Asia’s archaeology and how this unique heritage can be protected, the region should be studied as a whole with regard to its cultural ties with China and combined efforts should be undertaken in shielding the archaeological monuments from destruction. So far, international research campaigns have focused predominantly on single-sites or small-scale surveys, mainly due to the bureaucratic and security related issues involved in cross-border research. This is why we created the Dzungaria Landscape Project. Since 2013, we have worked on collecting remote sensing data of Xinjiang including IKONOS, WorldView-2, and TerraSAR-X data. We have developed a method for the automatic detection of larger grave mound structures in optical and SAR data. Gravemounds are typically spatially clustered and the detection of larger mound structures is a sufficient hint towards areas of high archaeological interest in a region. A meticulous remote sensing survey is the best planning tool for subsequent ground surveys and excavation. In summer 2015, we undertook a survey in the Chinese Altai in order to establish ground-truth in the Hailiutan valley. We categorized over 1000 monuments in just three weeks thanks to the previous detection and classification work using remote sensing data. Creating accurate maps of the cemeteries in northern Xinjiang is a crucial step to preserving the cultural heritage of the region since graves in remote areas are especially prone to looting. We will continue our efforts with the ultimate aim to map and monitor all large gravemounds in Dzungaria and potentially neighbouring eastern Kazakhstan.

Airborne Detection of Cosmic-Ray Albedo Neutrons for Regional-Scale Surveys of Root-Zone Soil Water on Earth

NASA Astrophysics Data System (ADS)

Schrön, M.; Bannehr, L.; Köhli, M.; Zreda, M. G.; Weimar, J.; Zacharias, S.; Oswald, S. E.; Bumberger, J.; Samaniego, L. E.; Schmidt, U.; Zieger, P.; Dietrich, P.

2017-12-01

While the detection of albedo neutrons from cosmic rays became a standard method in planetary space science, airborne neutron sensing has never been conceived for hydrological research on Earth. We assessed the applicability of atmospheric neutrons to sense root-zone soil moisture averaged over tens of hectares using neutron detectors on an airborne vehicle. Large-scale quantification of near-surface water content is an urgent challenge in hydrology. Information about soil and plant water is crucial to accurately assess the risks for floods and droughts, to adjust regional weather forecasts, and to calibrate and validate the corresponding models. However, there is a lack of data at scales relevant for these applications. Most conventional ground-based geophysical instruments provide root-zone soil moisture only within a few tens of m2, while electromagnetic signals from conventional remote-sensing instruments can only penetrate the first few centimeters below surface, though at larger spatial areas.In the last couple of years, stationary and roving neutron detectors have been used to sense the albedo component of cosmic-ray neutrons, which represents the average water content within 10—15 hectares and 10—50 cm depth. However, the application of these instruments is limited by inaccessible terrain and interfering local effects from roads. To overcome these limitations, we have pioneered first simulations and experiments of such sensors in the field of airborne geophysics. Theoretical investigations have shown that the footprint increases substantially with height above ground, while local effects smooth out throughout the whole area. Campaigns with neutron detectors mounted on a lightweight gyrocopter have been conducted over areas of various landuse types including agricultural fields, urban areas, forests, flood plains, and lakes. The neutron signal showed influence of soil moisture patterns in heights of up to 180 m above ground. We found correlation with ground-truthing data, using mobile cosmic-ray neutron sensors, local soil samples, TDR, and buried wireless soil moisture monitoring networks. The work opens the path towards further systematic assessment of airborne neutron sensing, which could become a valuable addition - or even an alternative - to conventional remote-sensing methods.

Application of Risk Analysis Based On Remote Sensing and Geographic Information System Technologies To Control of Malaria In Nigeria

NASA Astrophysics Data System (ADS)

Njemanze, Philip; Njemanze, Philip; Peters, Constance; Uwaeziozi, Amarachukwu

More than 1 million Africans die from malaria each year. Remote sensing (RS) and geographic information system (GIS) technologies could be applied to study the risk of malaria epidemic. The patient population included 45,140 of persons aged 0-85 years seen at primary health centers in 18 different local government areas (LGAs) of Imo State. Maps of old Imo State were converted to digital form using ARC/INFO GIS software, and the resulting coverages included hydrology, towns, and villages. Remote sensing images from Advanced Very High Resolution Radiometer (AVHRR) data set were used to obtain color-coded monthly normalized-difference vegetation index or NDVI. Three groups were distinguished as: group A LGAs using water from natural hydrology and bore-holes, group B - using rain water harvesting from roof tops into surface water reservoirs, and group C - using ground surface catchment of rain water with ground ponds. These stagnant ponds were Anopheles mosquito breeding sites. The NDVI values were used to determine water availability, and were least in January/February each year, and highest in April/May. Probabilistic layer analysis (PLA) was used to determine the Odds Ratio (OR), Relative Risk (RR) and Attributable Risk (AR) for malaria in groups A, B, C. Significant risk for malaria was associated with local water conservation methods in group C, compared to A, (OR = 4.55; RR = 4.46, AR = 77.6

Antennas Lower Cost of Satellite Access

NASA Technical Reports Server (NTRS)

2009-01-01

Whether for scientific inquiry, weather forecasting, or public safety, the world relies upon the data gathered by satellite remote sensing. Some of NASA s most valuable work is in its remote sensing capabilities - the ability to retrieve data acquired at great distances - affording a height and scope not available from the ground. NASA satellites in low Earth orbit (LEO) monitor ocean health by taking large-scale pictures of phytoplankton blooms and measuring surface temperatures; snap photographs of full hurricanes from above, teaching researchers about how these giant storms form; and capture images of cloud formation and air pollution, all allowing researchers to further develop understanding of the planet s health. NASA remote sensing satellites also monitor shifts in the Earth s crust, analyze wind patterns around the world to develop efficient wind energy, help people around the world recover from natural disasters, and monitor diminishing sea ice levels. Just as researchers are more heavily relying on this data from space to conduct their work, the instruments carried on satellites are getting more sophisticated and capable of capturing increasingly complex and accurate measurements. The satellites are covering larger areas, from farther away, and generating more and more valuable data. The ground-based receivers for this wealth of satellite data have grown increasingly capable of handling greater bandwidth and higher power levels. They have also become less expensive, through a NASA research partnership, with the creation of a high-rate X-band data receiver system that is now in widespread use around the globe.

Assessing the use of remotely sensed measurements for characterizing rangeland condition

NASA Astrophysics Data System (ADS)

Folker, Geoffrey P.

There are over 233 million hectares (ha) of nonfederal grazing lands in the United States. Conventional field observation and sampling techniques are insufficient methods to monitor such large areas frequently enough to confidently quantify the biophysical state and assess rangeland condition over large geographic areas. In an attempt to enhance rangeland resource managers' abilities to monitor and assess these factors, remote sensing scientists and land resource managers have worked together to determine whether remotely sensed measurements can improve the ability to measure rangeland response to land management practices. The relationship between spectral reflectance patterns and plant species composition was investigated on six south-central Kansas ranches. Airborne multispectral color infrared images for 2002 through 2004 were collected at multiple times in the growing season over the study area. Concurrent with the image acquisition periods, ground cover estimates of plant species composition and biomass by growth form were collected. Correlation analysis was used to examine relationships among spectral and biophysical field measurements. Results indicate that heavily grazed sites exhibited the highest spectral vegetation index values. This was attributed to increases in low forage quality broadleaf forbs such as annual ragweed (Ambrosia artemisiifolia L.). Although higher vegetation index values have a positive correlation with overall above ground primary productivity, species composition may be the best indicator of healthy rangeland condition. A Weediness Index, which was found to be correlated with range condition, was also strongly linked to spectral reflectance patterns recorded in the airborne imagery.

Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

PubMed Central

Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

2010-01-01

Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558

Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

NASA Astrophysics Data System (ADS)

Rouze, G.; Neely, H.; Morgan, C.; Kustas, W. P.; McKee, L.; Prueger, J. H.; Cope, D.; Yang, C.; Thomasson, A.; Jung, J.

2017-12-01

Airborne and satellite remote sensing methods have been developed to provide ET estimates across entire management fields. However, airborne-based ET is not particularly cost-effective and satellite-based ET provides insufficient spatial/temporal information. ET estimations through remote sensing are also problematic where soils are highly variable within a given management field. Unlike airborne/satellite-based ET, Unmanned Aerial Vehicle (UAV)-based ET has the potential to increase the spatial and temporal detail of these measurements, particularly within a heterogeneous soil landscape. However, it is unclear to what extent UAVs can model ET. The overall goal of this project was to assess the capability of UAVs in modeling ET across a heterogeneous landscape. Within a 20-ha irrigated cotton field in Central Texas, low-altitude UAV surveys were conducted throughout the growing season over two soil types. UAVs were equipped with thermal and multispectral cameras to obtain canopy temperature and NDVI, respectively. UAV data were supplemented simultaneously with ground-truth measurements such as Leaf Area Index (LAI) and plant height. Both remote sensing and ground-truth parameters were used to model ET using a Two-Source Energy Balance (TSEB) model. UAV-based estimations of ET and other energy balance components were validated against energy balance measurements obtained from nearby eddy covariance towers that were installed within each soil type. UAV-based ET fluxes were also compared with airborne and satellite (Landsat 8)-based ET fluxes collected near the time of the UAV survey.

Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase

NASA Astrophysics Data System (ADS)

Ciampalini, Andrea; Raspini, Federico; Bianchini, Silvia; Frodella, William; Bardi, Federica; Lagomarsino, Daniela; Di Traglia, Federico; Moretti, Sandro; Proietti, Chiara; Pagliara, Paola; Onori, Roberta; Corazza, Angelo; Duro, Andrea; Basile, Giuseppe; Casagli, Nicola

2015-11-01

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province.

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Evaluating ESA CCI soil moisture in East Africa.

PubMed

McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P

2016-06-01

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R>0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

An evaluation of the role played by remote sensing technology following the World Trade Center attack

NASA Astrophysics Data System (ADS)

Huyck, Charles K.; Adams, Beverley J.; Kehrlein, David I.

2003-06-01

Remote sensing technology has been widely recognized for contributing to emergency response efforts after the World Trade Center attack on September 11th, 2001. The need to coordinate activities in the midst of a dense, yet relatively small area, made the combination of imagery and mapped data strategically useful. This paper reviews the role played by aerial photography, satellite imagery, and LIDAR data at Ground Zero. It examines how emergency managers utilized these datasets, and identifies significant problems that were encountered. It goes on to explore additional ways in which imagery could have been used, while presenting recommendations for more effective use in future disasters and Homeland Security applications. To plan adequately for future events, it was important to capture knowledge from individuals who responded to the World Trade Center attack. In recognition, interviews with key emergency management and geographic information system (GIS) personnel provide the basis of this paper. Successful techniques should not be forgotten, or serious problems dismissed. Although widely used after September 11th, it is important to recognize that with better planning, remote sensing and GIS could have played an even greater role. Together with a data acquisition timeline, an expanded discussion of these issues is available in the MCEER/NSF report “Emergency Response in the Wake of the World Trade Center Attack; The Remote Sensing Perspective” (Huyck and Adams, 2002)

Remote sensing of land use and water quality relationships - Wisconsin shore, Lake Michigan

NASA Technical Reports Server (NTRS)

Haugen, R. K.; Marlar, T. L.

1976-01-01

This investigation assessed the utility of remote sensing techniques in the study of land use-water quality relationships in an east central Wisconsin test area. The following types of aerial imagery were evaluated: high altitude (60,000 ft) color, color infrared, multispectral black and white, and thermal; low altitude (less than 5000 ft) color infrared, multispectral black and white, thermal, and passive microwave. A non-imaging hand-held four-band radiometer was evaluated for utility in providing data on suspended sediment concentrations. Land use analysis includes the development of mapping and quantification methods to obtain baseline data for comparison to water quality variables. Suspended sediment loads in streams, determined from water samples, were related to land use differences and soil types in three major watersheds. A multiple correlation coefficient R of 0.85 was obtained for the relationship between the 0.6-0.7 micrometer incident and reflected radiation data from the hand-held radiometer and concurrent ground measurements of suspended solids in streams. Applications of the methods and baseline data developed in this investigation include: mapping and quantification of land use; input to watershed runoff models; estimation of effects of land use changes on stream sedimentation; and remote sensing of suspended sediment content of streams. High altitude color infrared imagery was found to be the most acceptable remote sensing technique for the mapping and measurement of land use types.

Laser long-range remote-sensing program experimental results

NASA Astrophysics Data System (ADS)

Highland, Ronald G.; Shilko, Michael L.; Fox, Marsha J.; Gonglewski, John D.; Czyzak, Stanley R.; Dowling, James A.; Kelly, Brian; Pierrottet, Diego F.; Ruffatto, Donald; Loando, Sharon; Matsuura, Chris; Senft, Daniel C.; Finkner, Lyle; Rae, Joe; Gallegos, Joe

1995-12-01

A laser long range remote sensing (LRS) program is being conducted by the United States Air Force Phillips Laboratory (AF/PL). As part of this program, AF/PL is testing the feasibility of developing a long path CO(subscript 2) laser-based DIAL system for remote sensing. In support of this program, the AF/PL has recently completed an experimental series using a 21 km slant- range path (3.05 km ASL transceiver height to 0.067 km ASL target height) at its Phillips Laboratory Air Force Maui Optical Station (AMOS) facility located on Maui, Hawaii. The dial system uses a 3-joule, (superscript 13)C isotope laser coupled into a 0.6 m diameter telescope. The atmospheric optical characterization incorporates information from an infrared scintillometer co-aligned to the laser path, atmospheric profiles from weather balloons launched from the target site, and meteorological data from ground stations at AMOS and the target site. In this paper, we report a description of the experiment configuration, a summary of the results, a summary of the atmospheric conditions and their implications to the LRS program. The capability of such a system for long-range, low-angle, slant-path remote sensing is discussed. System performance issues relating to both coherent and incoherent detection methods, atmospheric limitations, as well as, the development of advanced models to predict performance of long range scenarios are presented.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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.

Direct Satellite Data Acquisition and its Application for Large -scale Monitoring Projects in Russia

NASA Astrophysics Data System (ADS)

Gershenzon, O.

2011-12-01

ScanEx RDC created an infrastructure (ground stations network) to acquire and process remote sensing data from different satellites: Terra, Aqua, Landsat, IRS-P5/P6, SPOT 4/5, FORMOSAT-2, EROS A/B, RADARSAT-1/2, ENVISAT-1. It owns image archives from these satellites as well as from SPOT-2 and CARTOSAT-2. ScanEx RDC builds and delivers remote sensing ground stations (working with up to 15 satellites); and owns the ground stations network to acquire data for Russia and surrounding territory. ScanEx stations are the basic component in departmental networks of remote sensing data acquisition for different state authorities (Roshydromet, Ministry of Natural Recourses, Emercom) and University- based remote sensing data acquisition and processing centers in Russia and abroad. ScanEx performs large-scale projects in collaboration with government agencies to monitor forests, floods, fires, sea surface pollution, and ice situation in Northern Russia. During 2010-2011 ScanEx conducted daily monitoring of wild fires in Russia detecting and registering thermal anomalies using data from Terra, Aqua, Landsat and SPOT satellites. Detailed SPOT 4/5 data is used to analyze burnt areas and to assess damage caused by fire. Satellite data along with other information about fire situation in Russia was daily updated and published via free-access Internet geoportal. A few projects ScanEx conducted together with environmental NGO. Project "Satellite monitoring of Especially Protected Natural Areas of Russia and its results visualization on geoportal was conducted in cooperation with NGO "Transparent World". The project's goal was to observe natural phenomena and economical activity, including illegal, by means of Earth remote sensing data. Monitoring is based on multi-temporal optical space imagery of different spatial resolution. Project results include detection of anthropogenic objects that appeared in the vicinity or even within the border of natural territories, that have never been touched by civilization before. "Satellite based technology for monitoring ship ice navigation and its influence on seal population in the White Sea" project was conducted in cooperation with IFAW. Results of the near real-time satellite monitoring were published on specially designed open web source. This allows project team to put image interpretation results in near real-time mode for on-line access to all interesting external stakeholders. During project realization Envisat, Radarsat, SPOT, EROS space images were used. In addition the methodology to locate seal population using EROS space images was developed. This methodology is based on detection of vital functions and displacement traces. Environmental satellite monitoring of Northern Russian territory and Arctic seas projects where the results are published via free-access Internet geoportal has a significant social importance.

Propagation Limitations in Remote Sensing.

DTIC Science & Technology

Contents: Multi-sensors and systems in remote sensing ; Radar sensing systems over land; Remote sensing techniques in oceanography; Influence of...propagation media and background; Infrared techniques in remote sensing ; Photography in remote sensing ; Analytical studies in remote sensing .

Automatic Assessment of Acquisition and Transmission Losses in Indian Remote Sensing Satellite Data

NASA Astrophysics Data System (ADS)

Roy, D.; Purna Kumari, B.; Manju Sarma, M.; Aparna, N.; Gopal Krishna, B.

2016-06-01

The quality of Remote Sensing data is an important parameter that defines the extent of its usability in various applications. The data from Remote Sensing satellites is received as raw data frames at the ground station. This data may be corrupted with data losses due to interferences during data transmission, data acquisition and sensor anomalies. Thus it is important to assess the quality of the raw data before product generation for early anomaly detection, faster corrective actions and product rejection minimization. Manual screening of raw images is a time consuming process and not very accurate. In this paper, an automated process for identification and quantification of losses in raw data like pixel drop out, line loss and data loss due to sensor anomalies is discussed. Quality assessment of raw scenes based on these losses is also explained. This process is introduced in the data pre-processing stage and gives crucial data quality information to users at the time of browsing data for product ordering. It has also improved the product generation workflow by enabling faster and more accurate quality estimation.

Volcano remote sensing with ground-based spectroscopy.

PubMed

McGonigle, Andrew J S

2005-12-15

The chemical compositions and emission rates of volcanic gases carry important information about underground magmatic and hydrothermal conditions, with application in eruption forecasting. Volcanic plumes are also studied because of their impacts upon the atmosphere, climate and human health. Remote sensing techniques are being increasingly used in this field because they provide real-time data and can be applied at safe distances from the target, even throughout violent eruptive episodes. However, notwithstanding the many scientific insights into volcanic behaviour already achieved with these approaches, technological limitations have placed firm restrictions upon the utility of the acquired data. For instance, volcanic SO(2) emission rate measurements are typically inaccurate (errors can be greater than 100%) and have poor time resolution (ca once per week). Volcanic gas geochemistry is currently being revolutionized by the recent implementation of a new generation of remote sensing tools, which are overcoming the above limitations and are providing degassing data of unprecedented quality. In this article, I review this field at this exciting point of transition, covering the techniques used and the insights thereby obtained, and I speculate upon the breakthroughs that are now tantalizingly close.

Analysis of remote sensing data for evaluation of vegetation resources

NASA Technical Reports Server (NTRS)

1970-01-01

Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.

Remote Sensing Product Verification and Validation at the NASA Stennis Space Center

NASA Technical Reports Server (NTRS)

Stanley, Thomas M.

2005-01-01

Remote sensing data product verification and validation (V&V) is critical to successful science research and applications development. People who use remote sensing products to make policy, economic, or scientific decisions require confidence in and an understanding of the products' characteristics to make informed decisions about the products' use. NASA data products of coarse to moderate spatial resolution are validated by NASA science teams. NASA's Stennis Space Center (SSC) serves as the science validation team lead for validating commercial data products of moderate to high spatial resolution. At SSC, the Applications Research Toolbox simulates sensors and targets, and the Instrument Validation Laboratory validates critical sensors. The SSC V&V Site consists of radiometric tarps, a network of ground control points, a water surface temperature sensor, an atmospheric measurement system, painted concrete radial target and edge targets, and other instrumentation. NASA's Applied Sciences Directorate participates in the Joint Agency Commercial Imagery Evaluation (JACIE) team formed by NASA, the U.S. Geological Survey, and the National Geospatial-Intelligence Agency to characterize commercial systems and imagery.

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

Sustainable Biosphere Initiative Project

NASA Technical Reports Server (NTRS)

1997-01-01

The goal of the Advanced Technology in Ecological Sciences project is to gain broad participation within the environmental scientific community in developing a research agenda addressing the development and refinement of technologies instrumental to research that responds to these challenges (e.g. global climate change, unsustainable resource use, and threats to biological diversity). The following activities have been completed: (1) A listserve 'eco-tech was set up to serve as a clearinghouse of information about activities and events relating to advanced technologies; (2) A series of conference calls were organized on specific topics including data visualization and spatial analysis, and remote sensing; and (3) Two meetings were organized at the 19% ESA Annual Meeting in Providence, Rhode Island. Topics covered included concerns about tool and data sharing; interest in expanded development of ground-based remote sensing technologies for monitoring; issues involved in training for using new technologies and increasing data streams, and- associated implications of data processing capabilities; questions about how to develop appropriate standards (i.e. surface morphology classification standards) that facilitate the exchange and comparison of analytical results; and some thoughts about remote sensing platforms and vehicles.

Recent Advances in Remote Sensing of Natural Hazards-Induced Atmospheric and Ionospheric Perturbations

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Komjathy, A.; Meng, X.; Verkhoglyadova, O. P.; Langley, R. B.; Mannucci, A. J.

2015-12-01

Traveling ionospheric disturbances (TIDs) induced by acoustic-gravity waves in the neutral atmosphere have significant impact on trans-ionospheric radio waves such as Global Navigation Satellite System (GNSS, including Global Position System (GPS)) measurements. Natural hazards and solid Earth events, such as earthquakes, tsunamis and volcanic eruptions are actual sources that may trigger acoustic and gravity waves resulting in traveling ionospheric disturbances (TIDs) in the upper atmosphere. Trans-ionospheric radio wave measurements sense the total electron content (TEC) along the signal propagation path. In this research, we introduce a novel GPS-based detection and estimation technique for remote sensing of atmospheric wave-induced TIDs including space weather phenomena induced by major natural hazard events, using TEC time series collected from worldwide ground-based dual-frequency GNSS (including GPS) receiver networks. We demonstrate the ability of using ground- and space-based dual-frequency GPS measurements to detect and monitor tsunami wave propagation from the 2011 Tohoku-Oki earthquake and tsunami. Major wave trains with different propagation speeds and wavelengths were identified through analysis of the GPS remote sensing observations. Dominant physical characteristics of atmospheric wave-induced TIDs are found to be associated with specific tsunami propagations and oceanic Rayleigh waves. In this research, we compared GPS-based observations, corresponding model simulations and tsunami wave propagation. Results are shown to lead to a better understanding of the tsunami-induced ionosphere responses. Based on current distribution of Plate Boundary Observatory GPS stations, the results indicate that tsunami-induced TIDs may be detected about 60 minutes prior to tsunamis arriving at the U.S. west coast. It is expected that this GNSS-based technology will become an integral part of future early-warning systems.

Ground-based remote sensing of volcanic CO2 and correlated SO2, HF, HCl, and BrO, in safe-distance from the crater

NASA Astrophysics Data System (ADS)

Butz, Andre; Solvejg Dinger, Anna; Bobrowski, Nicole; Kostinek, Julian; Fieber, Lukas; Fischerkeller, Constanze; Giuffrida, Giovanni Bruno; Hase, Frank; Klappenbach, Friedrich; Kuhn, Jonas; Lübcke, Peter; Tirpitz, Lukas; Tu, Qiansi

2017-04-01

Remote sensing of CO2 enhancements in volcanic plumes can be a tool to estimate volcanic CO2 emissions and thereby, to gain insight into the geological carbon cycle and into volcano interior processes. However, remote sensing of the volcanic CO2 is challenged by the large atmospheric background concentrations masking the minute volcanic signal. Here, we report on a demonstrator study conducted in September 2015 at Mt. Etna on Sicily, where we deployed an EM27/SUN Fourier Transform Spectrometer together with a UV spectrometer on a mobile remote sensing platform. The spectrometers were operated in direct-sun viewing geometry collecting cross-sectional scans of solar absorption spectra through the volcanic plume by operating the platform in stop-and-go patterns in 5 to 10 kilometers distance from the crater region. We successfully detected correlated intra-plume enhancements of CO2 and volcanic SO2, HF, HCl, and BrO. The path-integrated volcanic CO2 enhancements amounted to about 0.5 ppm (on top of the ˜400 ppm background). Key to successful detection of volcanic CO2 was A) the simultaneous observation of the O2 total column which allowed for correcting changes in the CO2 column caused by changes in observer altitude and B) the simultaneous measurement of volcanic species co-emitted with CO2 which allowed for discriminating intra-plume and extra-plume observations. The latter were used for subtracting the atmospheric CO2 background. The field study suggests that our remote sensing observatory is a candidate technique for volcano monitoring in safe distance from the crater region.

Malaria Modeling using Remote Sensing and GIS Technologies

NASA Technical Reports Server (NTRS)

Kiang, Richard

2004-01-01

Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.