Integrated Remote Sensing Modalities for Classification at a Legacy Test Site
NASA Astrophysics Data System (ADS)
Lee, D. J.; Anderson, D.; Craven, J.
2016-12-01
Detecting, locating, and characterizing suspected underground nuclear test sites is of interest to the worldwide nonproliferation monitoring community. Remote sensing provides both cultural and surface geological information over a large search area in a non-intrusive manner. We have characterized a legacy nuclear test site at the Nevada National Security Site (NNSS) using an aerial system based on RGB imagery, light detection and ranging, and hyperspectral imaging. We integrate these different remote sensing modalities to perform pattern recognition and classification tasks on the test site. These tasks include detecting cultural artifacts and exotic materials. We evaluate if the integration of different remote sensing modalities improves classification performance.
Remote sensing in operational range management programs in Western Canada
NASA Technical Reports Server (NTRS)
Thompson, M. D.
1977-01-01
A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.
NASA Technical Reports Server (NTRS)
Reeves, R. G. (Compiler)
1972-01-01
Recent studies conducted in the Bonanza Test Site, Colorado, area indicated that: (1) more geologic structural information is available from remote sensing data than from conventional techniques; (2) greater accuracy results from using remote sensing data; (3) all major structural features were detected; (4) of all structural interpretations, about 75% were correct; and (5) interpretation of remote sensing data will not supplant field work, but it enables field work to be done much more efficiently.
REMOTE SENSING IN OCEANOGRAPHY.
remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and
Field Data Collection: an Essential Element in Remote Sensing Applications
NASA Technical Reports Server (NTRS)
Pettinger, L. R.
1971-01-01
Field data collected in support of remote sensing projects are generally used for the following purposes: (1) calibration of remote sensing systems, (2) evaluation of experimental applications of remote sensing imagery on small test sites, and (3) designing and evaluating operational regional resource studies and inventories which are conducted using the remote sensing imagery obtained. Field data may be used to help develop a technique for a particular application, or to aid in the application of that technique to a resource evaluation or inventory problem for a large area. Scientists at the Forestry Remote Sensing Laboratory have utilized field data for both purposes. How meaningful field data has been collected in each case is discussed.
Development and Testing of Physically-Based Methods for Filling Gaps in Remotely Sensed River Data
2011-09-30
Filling Gaps in Remotely Sensed River Data Jonathan M. Nelson US Geological Survey National Research Program Geomorphology and Sediment Transport...the research work carried out under this grant are to develop and test two methods for filling in gaps in remotely sensed river data. The first...information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215
Remote sensing utility in a disaster struck urban environment
NASA Technical Reports Server (NTRS)
Rush, M.; Holguin, A.; Vernon, S.
1974-01-01
A project to determine the ways in which remote sensing can contribute to solutions of urban public health problems in time of natural disaster is discussed. The objectives of the project are to determine and describe remote sensing standard operating procedures for public health assistance during disaster relief operations which will aid the agencies and organizations involved in disaster intervention. Proposed tests to determine the validity of the remote sensing system are reported.
Learning Methods of Remote Sensing In the 2013 Curriculum of Secondary School
NASA Astrophysics Data System (ADS)
Lili Somantri, Nandi
2016-11-01
The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.
LWIR Microgrid Polarimeter for Remote Sensing Studies
2010-02-28
Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, A.I.; Pettersson, C.B.
1988-01-01
Papers and discussions concerning the geotechnical applications of remote sensing and remote data transmission, sources of remotely sensed data, and glossaries of remote sensing and remote data transmission terms, acronyms, and abbreviations are presented. Aspects of remote sensing use covered include the significance of lineaments and their effects on ground-water systems, waste-site use and geotechnical characterization, the estimation of reservoir submerging losses using CIR aerial photographs, and satellite-based investigation of the significance of surficial deposits for surface mining operations. Other topics presented include the location of potential ground subsidence and collapse features in soluble carbonate rock, optical Fourier analysis ofmore » surface features of interest in geotechnical engineering, geotechnical applications of U.S. Government remote sensing programs, updating the data base for a Geographic Information System, the joint NASA/Geosat Test Case Project, the selection of remote data telemetry methods for geotechnical applications, the standardization of remote sensing data collection and transmission, and a comparison of airborne Goodyear electronic mapping system/SAR with satelliteborne Seasat/SAR radar imagery.« less
Investigation of the application of remote sensing technology to environmental monitoring
NASA Technical Reports Server (NTRS)
Rader, M. L. (Principal Investigator)
1980-01-01
Activities and results are reported of a project to investigate the application of remote sensing technology developed for the LACIE, AgRISTARS, Forestry and other NASA remote sensing projects for the environmental monitoring of strip mining, industrial pollution, and acid rain. Following a remote sensing workshop for EPA personnel, the EOD clustering algorithm CLASSY was selected for evaluation by EPA as a possible candidate technology. LANDSAT data acquired for a North Dakota test sight was clustered in order to compare CLASSY with other algorithms.
Remote Sensing Wind and Wind Shear System.
Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.
Remote sensing as a source of data for outdoor recreation planning
NASA Technical Reports Server (NTRS)
Reed, W. E.; Goodell, H. G.; Emmitt, G. D.
1972-01-01
Specific data needs for outdoor recreation planning and the ability of tested remote sensors to provide sources for these data are examined. Data needs, remote sensor capabilities, availability of imagery, and advantages and problems of incorporating remote sensing data sources into ongoing planning data collection programs are discussed in detail. Examples of the use of imagery to derive data for a range of common planning analyses are provided. A selected bibliography indicates specific uses of data in planning, basic background materials on remote sensing technology, and sources of information on environmental information systems expected to use remote sensing to provide new environmental data of use in outdoor recreation planning.
Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.
2007-01-01
1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.
ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A
2007-01-01
Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470
NASA Astrophysics Data System (ADS)
Tan, Songxin; Narayanan, Ram M.
2004-04-01
The University of Nebraska has developed a multiwavelength airborne polarimetric lidar (MAPL) system to support its Airborne Remote Sensing Program for vegetation remote sensing. The MAPL design and instrumentation are described in detail. Characteristics of the MAPL system include lidar waveform capture and polarimetric measurement capabilities, which provide enhanced opportunities for vegetation remote sensing compared with current sensors. Field tests were conducted to calibrate the range measurement. Polarimetric calibration of the system is also discussed. Backscattered polarimetric returns, as well as the cross-polarization ratios, were obtained from a small forested area to validate the system's ability for vegetation canopy detection. The system has been packaged to fly abroad a Piper Saratoga aircraft for airborne vegetation remote sensing applications.
NASA Technical Reports Server (NTRS)
Miller, L. D.; Tom, C.; Nualchawee, K.
1977-01-01
A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.
An object-based storage model for distributed remote sensing images
NASA Astrophysics Data System (ADS)
Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng
2006-10-01
It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.
40 CFR 51.371 - On-road testing.
Code of Federal Regulations, 2014 CFR
2014-07-01
... inspection; notification may be by mailing in the case of remote sensing on-road testing or through immediate... information about the performance of in-use vehicles, by measuring on-road emissions through the use of remote sensing devices or by assessing vehicle emission performance through roadside pullovers including tailpipe...
40 CFR 51.371 - On-road testing.
Code of Federal Regulations, 2013 CFR
2013-07-01
... inspection; notification may be by mailing in the case of remote sensing on-road testing or through immediate... information about the performance of in-use vehicles, by measuring on-road emissions through the use of remote sensing devices or by assessing vehicle emission performance through roadside pullovers including tailpipe...
40 CFR 51.371 - On-road testing.
Code of Federal Regulations, 2012 CFR
2012-07-01
... inspection; notification may be by mailing in the case of remote sensing on-road testing or through immediate... information about the performance of in-use vehicles, by measuring on-road emissions through the use of remote sensing devices or by assessing vehicle emission performance through roadside pullovers including tailpipe...
40 CFR 51.371 - On-road testing.
Code of Federal Regulations, 2011 CFR
2011-07-01
... inspection; notification may be by mailing in the case of remote sensing on-road testing or through immediate... information about the performance of in-use vehicles, by measuring on-road emissions through the use of remote sensing devices or by assessing vehicle emission performance through roadside pullovers including tailpipe...
Current NASA Earth Remote Sensing Observations
NASA Technical Reports Server (NTRS)
Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;
2011-01-01
This slide presentation reviews current NASA Earth Remote Sensing observations in specific reference to improving public health information in view of pollen sensing. While pollen sampling has instrumentation, there are limitations, such as lack of stations, and reporting lag time. Therefore it is desirable use remote sensing to act as early warning system for public health reasons. The use of Juniper Pollen was chosen to test the possibility of using MODIS data and a dust transport model, Dust REgional Atmospheric Model (DREAM) to act as an early warning system.
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.
Commercial use of remote sensing in agriculture: a case study
NASA Astrophysics Data System (ADS)
Gnauck, Gary E.
1999-12-01
Over 25 years of research have clearly shown that an analysis of remote sensing imagery can provide information on agricultural crops. Most of this research has been funded by and directed toward the needs of government agencies. Commercial use of agricultural remote sensing has been limited to very small-scale operations supplying remote sensing services to a few selected customers. Datron/Transco Inc. undertook an internally funded remote sensing program directed toward the California cash crop industry (strawberries, lettuce, tomatoes, other fresh vegetables and cotton). The objectives of this program were twofold: (1) to assess the need and readiness of agricultural land managers to adopt remote sensing as a management tool, and (2) determine what technical barriers exist to large-scale implementation of this technology on a commercial basis. The program was divided into three phases: Planning, Engineering Test and Evaluation, and Commercial Operations. Findings: Remote sensing technology can deliver high resolution multispectral imagery with rapid turnaround, that can provide information on crop stress insects, disease and various soil parameters. The limiting factors to the use of remote sensing in agriculture are a lack of familiarization by the land managers, difficulty in translating 'information' into increased revenue or reduced cost for the land manager, and the large economies of scale needed to make the venture commercially viable.
NASA Astrophysics Data System (ADS)
Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan
2018-07-01
Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.
Ontology-based classification of remote sensing images using spectral rules
NASA Astrophysics Data System (ADS)
Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent
2017-05-01
Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.
Development of sea ice monitoring with aerial remote sensing technology
NASA Astrophysics Data System (ADS)
Jiang, Xuhui; Han, Lei; Dong, Liang; Cui, Lulu; Bie, Jun; Fan, Xuewei
2014-11-01
In the north China Sea district, sea ice disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the sea ice situation becomes too critical. The monitoring of sea ice is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor sea ice mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the sea ice in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of sea ice, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get sea ice charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor sea ice. Aerial remote sensing is an important means in sea ice monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the sea ice monitoring using aerial remote sensing technology are discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Foley, Paul; Skeehan, Kirsten; Smith, Jerome
Report on the confirmation of Commercial Geothermal Resources in Colorado describing the on site testing and analysis to confirm remote sensing identified potential resources. A series of thermal gradient wells were drilled in the Pagosa Springs region and the data collected is analyzed within.
2013-09-30
coordinates locally oriented in the streamwise and cross-stream directions, respectively. To test the expressions and investigate potential errors, we...Survey Geomorphology and Sediment Transport Laboratory (GSTL). The IR camera was mounted on a rack ~1m above the surface of the flow and oriented so that...MD_SWMS, American Society for Photogrammetry and Remote Sensing, Proceedings of the 2008 Annual Conference –PNAMP Special Session: Remote Sensing
Mesoscale Modeling, Forecasting and Remote Sensing Research.
remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed
NASA Astrophysics Data System (ADS)
Zhao, Shaoshuai; Ni, Chen; Cao, Jing; Li, Zhengqiang; Chen, Xingfeng; Ma, Yan; Yang, Leiku; Hou, Weizhen; Qie, Lili; Ge, Bangyu; Liu, Li; Xing, Jin
2018-03-01
The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.
Using GPS Reflections for Satellite Remote Sensing
NASA Technical Reports Server (NTRS)
Mickler, David
2000-01-01
GPS signals that have reflected off of the ocean's surface have shown potential for use in oceanographic and atmospheric studies. The research described here investigates the possible deployment of a GPS reflection receiver onboard a remote sensing satellite in low Earth orbit (LEO). The coverage and resolution characteristics of this receiver are calculated and estimated. This mission analysis examines using reflected GPS signals for several remote sensing missions. These include measurement of the total electron content in the ionosphere, sea surface height, and ocean wind speed and direction. Also discussed is the potential test deployment of such a GPS receiver on the space shuttle. Constellations of satellites are proposed to provide adequate spatial and temporal resolution for the aforementioned remote sensing missions. These results provide a starting point for research into the feasibility of augmenting or replacing existing remote sensing satellites with spaceborne GPS reflection-detecting receivers.
NASA Technical Reports Server (NTRS)
Miller, W. Frank; Sever, Thomas L.; Lee, C. Daniel
1991-01-01
The concept of integrating ecological perspectives on early man's settlement patterns with advanced remote sensing technologies shows promise for predictive site modeling. Early work with aerial imagery and ecosystem analysis is discussed with respect to the development of a major project in Maya archaeology supported by NASA and the National Geographic Society with technical support from the Mississippi State Remote Sensing Center. A preliminary site reconnaissance model will be developed for testing during the 1991 field season.
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.
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.
Multi-crop area estimation and mapping on a microprocessor/mainframe network
NASA Technical Reports Server (NTRS)
Sheffner, E.
1985-01-01
The data processing system is outlined for a 1985 test aimed at determining the performance characteristics of area estimation and mapping procedures connected with the California Cooperative Remote Sensing Project. The project is a joint effort of the USDA Statistical Reporting Service-Remote Sensing Branch, the California Department of Water Resources, NASA-Ames Research Center, and the University of California Remote Sensing Research Program. One objective of the program was to study performance when data processing is done on a microprocessor/mainframe network under operational conditions. The 1985 test covered the hardware, software, and network specifications and the integration of these three components. Plans for the year - including planned completion of PEDITOR software, testing of software on MIDAS, and accomplishment of data processing on the MIDAS-VAX-CRAY network - are discussed briefly.
Verification technology of remote sensing camera satellite imaging simulation based on ray tracing
NASA Astrophysics Data System (ADS)
Gu, Qiongqiong; Chen, Xiaomei; Yang, Deyun
2017-08-01
Remote sensing satellite camera imaging simulation technology is broadly used to evaluate the satellite imaging quality and to test the data application system. But the simulation precision is hard to examine. In this paper, we propose an experimental simulation verification method, which is based on the test parameter variation comparison. According to the simulation model based on ray-tracing, the experiment is to verify the model precision by changing the types of devices, which are corresponding the parameters of the model. The experimental results show that the similarity between the imaging model based on ray tracing and the experimental image is 91.4%, which can simulate the remote sensing satellite imaging system very well.
Research for applications of remote sensing to state and local governments (ARSIG)
NASA Technical Reports Server (NTRS)
Foster, K. E.; Johnson, J. D.
1973-01-01
Remote sensing and its application to problems confronted by local and state planners are reported. The added dimension of remote sensing as a data gathering tool has been explored identifying pertinent land use factors associated with urban growth such as soil associations, soil capability, vegetation distribution, and flood prone areas. Remote sensing within rural agricultural setting has also been utilized to determine irrigation runoff volumes, cropping patterns, and land use. A variety of data sources including U-2 70 mm multispectral black and white photography, RB-57 9-inch color IR, HyAC panoramic color IR and ERTS-1 imagery have been used over selected areas of Arizona including Tucson, Arizona (NASA Test Site #30) and the Sulphur Springs Valley.
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.
NASA Astrophysics Data System (ADS)
McNamara, Laura A.; Berg, Leif; Butler, Karin; Klein, Laura
2017-05-01
Even as remote sensing technology has advanced in leaps and bounds over the past decade, the remote sensing community lacks interfaces and interaction models that facilitate effective human operation of our sensor platforms. Interfaces that make great sense to electrical engineers and flight test crews can be anxiety-inducing to operational users who lack professional experience in the design and testing of sophisticated remote sensing platforms. In this paper, we reflect on an 18-month collaboration which our Sandia National Laboratory research team partnered with an industry software team to identify and fix critical issues in a widely-used sensor interface. Drawing on basic principles from cognitive and perceptual psychology and interaction design, we provide simple, easily learned guidance for minimizing common barriers to system learnability, memorability, and user engagement.
Application of remote sensor data to geologic analysis of the Bonanza test site, Colorado
NASA Technical Reports Server (NTRS)
Lee, K. (Compiler)
1972-01-01
A variety of remote sensor data has aided geologic mapping in central Colorado. This report summarizes the application of sensor data to both regional and local geologic mapping and presents some conclusions on the practical use of remote sensing for solving geologic mapping problems. It is emphasized that this study was not conducted primarily to test or evaluate remote sensing systems or data, but, rather, to apply sensor data as an accessory tool for geologic mapping. The remote sensor data used were acquired by the NASA Earth Observations Aircraft Program. Conclusions reached on the utility of the various sensor data and interpretation techniques for geologic mapping were by-products of attempts to use them.
A solar energy estimation procedure using remote sensing techniques. [watershed hydrologic models
NASA Technical Reports Server (NTRS)
Khorram, S.
1977-01-01
The objective of this investigation is to design a remote sensing-aided procedure for daily location-specific estimation of solar radiation components over the watershed(s) of interest. This technique has been tested on the Spanish Creek Watershed, Northern California, with successful results.
AN INVESTIGATION OF REMOTE SENSING DEVICES FOR CHEMICAL CHARACTERIZATION OF MOTOR VEHICLE EXHAUST
The report summarizes results of tests to (1) evaluate the accuracy and precision of two different remote sensing devices (RSDs) for measuring carbon monoxide (CO), hydrocarbons (HCs), and nitric oxide (NO) and (2) evaluate the capabilities of three RSDs for characterizing fleet ...
Use of Satellite Remote Sensing to Improve Coastal Hypoxia Prediction
We describe the use of Giovanni satellite remote sensing products in the development and testing of a new modeling system that represents the processes leading to hypoxia (defined as water O2 concentration < 63 mmol m-3) on the Louisiana continental shelf (LCS). The modeling ...
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.
NASA Technical Reports Server (NTRS)
Huang, N. E.; Flood, W. A.; Brown, G. S.
1975-01-01
The feasibility of remote sensing of current flows in the ocean and the remote sensing of ocean currents by backscattering cross section techniques was studied. It was established that for capillary waves, small scale currents could be accurately measured through observation of wave kinematics. Drastic modifications of waves by changing currents were noted. The development of new methods for the measurement of capillary waves are discussed. Improvement methods to resolve data processing problems are suggested.
2011-03-01
to remotely sensed SCA and SWE. The first analysis, a comparison to SCA imagery, tests the models ability to correctly estimate the snow extent...remotely sensed data (Con- galton and Green 2009). The producer’s accuracies consistently show the model underestimating the snow extent at the end...and K. Green. 2009. Assessing the accuracy of remotely sensed data: principals and practices, Second edition. CRC Press, Taylor & Francis Group
Real-Time and Post-Processed Georeferencing for Hyperpspectral Drone Remote Sensing
NASA Astrophysics Data System (ADS)
Oliveira, R. A.; Khoramshahi, E.; Suomalainen, J.; Hakala, T.; Viljanen, N.; Honkavaara, E.
2018-05-01
The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites.
NASA Astrophysics Data System (ADS)
de Kok, R.; WeŻyk, P.; PapieŻ, M.; Migo, L.
2017-10-01
To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and remote sensing programmers. An index value, known in the remote sensing user domain as "Zabud" was selected to represent, in color, the essentials of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control. This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected anomalies allows developers of open source software to design solutions for further agricultural control with remote sensing.
Automated railroad reconstruction from remote sensing image based on texture filter
NASA Astrophysics Data System (ADS)
Xiao, Jie; Lu, Kaixia
2018-03-01
Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.
Remote sensing strategic exploration of large or superlarge gold ore deposits
NASA Astrophysics Data System (ADS)
Yan, Shouxun; Liu, Qingsheng; Wang, Hongmei; Wang, Zhigang; Liu, Suhong
1998-08-01
To prospect large or superlarge gold ore deposits, blending of remote sensing techniques and modern metallogenitic theories is one of the effective measures. The theory of metallogeny plays a director role before and during remote sensing technique applications. The remote sensing data with different platforms and different resolutions can be respectively applied to detect direct or indirect metallogenic information, and to identify the ore-controlling structure, especially, the ore-controlling structural assemblage, which, conversely, usually are the new conditions to study and to modify the metallogenic model, and to further develop the exploration model of large or superlarge ore deposits. Guidance by an academic idea of 'adjustment structure' which is the conceptual model of transverse structure, an obscured ore- controlling transverse structure has been identified on the refined TM imagery in the Hadamengou gold ore deposit, Setai Hyperspectral Geological Remote Sensing Testing Site (SHGRSTS), Wulashan mountains, Inner Mongolia, China. Meanwhile, The MAIS data has been applied to quickly identify the auriferous alteration rocks with Correspondence Analysis method and Spectral Angle Mapping (SAM) technique. The theoretical system and technical method of remote sensing strategic exploration of large or superlarge gold ore deposits have been demonstrated by the practices in the SHGRSTS.
Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes
NASA Astrophysics Data System (ADS)
Luo, Q. W.; Shi, Y. B.; Wang, Z. G.; Zhang, W.; Zhang, Y.
2016-10-01
In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.
Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes.
Luo, Q W; Shi, Y B; Wang, Z G; Zhang, W; Zhang, Y
2016-10-01
In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.
NASA Astrophysics Data System (ADS)
Dowling, David R.; Sabra, Karim G.
2015-01-01
Acoustic waves carry information about their source and collect information about their environment as they propagate. This article reviews how these information-carrying and -collecting features of acoustic waves that travel through fluids can be exploited for remote sensing. In nearly all cases, modern acoustic remote sensing involves array-recorded sounds and array signal processing to recover multidimensional results. The application realm for acoustic remote sensing spans an impressive range of signal frequencies (10-2 to 107 Hz) and distances (10-2 to 107 m) and involves biomedical ultrasound imaging, nondestructive evaluation, oil and gas exploration, military systems, and Nuclear Test Ban Treaty monitoring. In the past two decades, approaches have been developed to robustly localize remote sources; remove noise and multipath distortion from recorded signals; and determine the acoustic characteristics of the environment through which the sound waves have traveled, even when the recorded sounds originate from uncooperative sources or are merely ambient noise.
Cloud-top height retrieval from polarizing remote sensor POLDER
NASA Astrophysics Data System (ADS)
He, Xianqiang; Pan, Delu; Yan, Bai; Mao, Zhihua
2006-10-01
A new cloud-top height retrieval method is proposed by using polarizing remote sensing. In cloudy conditions, it shows that, in purple and blue bands, linear polarizing radiance at the top-of-atmosphere (TOA) is mainly contributed by Rayleigh scattering of the atmosphere's molecules above cloud, and the contribution by cloud reflection and aerosol scattering can be neglected. With such characteristics, the basis principle and method of cloud-top height retrieval using polarizing remote sensing are presented in detail, and tested by the polarizing remote sensing data of POLDER. The satellite-derived cloud-top height product can not only show the distribution of global cloud-top height, but also obtain the cloud-top height distribution of moderate-scale meteorological phenomena like hurricanes and typhoons. This new method is promising to become the operational algorithm for cloud-top height retrieval for POLDER and the future polarizing remote sensing satellites.
NASA Astrophysics Data System (ADS)
Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.
2017-09-01
With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.
Remote sensing of environmental disturbance
NASA Technical Reports Server (NTRS)
Latham, J. P.
1972-01-01
Color, color infrared, and minus-blue films obtained by RB-57 remote sensing aircraft at an altitude of 60,000 feet over Boca Raton and Southeast Florida Earth Resources Test Site were analyzed for nine different types of photographic images of the geographic patterns of the surface. Results of these analyses are briefly described.
Identification of expansive soils using remote sensing and in-situ field measurements : phase I.
DOT National Transportation Integrated Search
2012-10-01
Researchers at the University of Arkansas have conducted research on the suitability of using remote sensing techniques (radar and LIDAR) to monitor the shrink-swell behavior of an expansive clay material in a field test site as part of the Mack Blac...
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.
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
NASA Technical Reports Server (NTRS)
Morris, W. D.; Witte, W. G.; Whitlock, C. H.
1980-01-01
Remote sensing of water quality is dicussed. Remote sensing penetration depth is a function both of water type and wavelength. Results of three tests to help demonstrate the magnitude of this dependence are presented. The water depth to which the remote-sensor data was valid was always less than that of the Secchi disk depth, although not always the same fraction of that depth. The penetration depths were wavelength dependent and showed the greatest variation for the water type with largest Secchi depth. The presence of a reflective plate, simulating a reflective subsurface, increased the apparent depth of light penetration from that calculated for water of infinite depth.
Propagation Limitations in Remote Sensing.
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 .
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.
Resource analysis applications in Michigan. [NASA remote sensing
NASA Technical Reports Server (NTRS)
Schar, S. W.; Enslin, W. R.; Sattinger, I. J.; Robinson, J. G.; Hosford, K. R.; Fellows, R. S.; Raad, J. H.
1974-01-01
During the past two years, available NASA imagery has been applied to a broad spectrum of problems of concern to Michigan-based agencies. These demonstrations include the testing of remote sensing for the purposes of (1) highway corridor planning and impact assessments, (2) game management-area information bases, (3) multi-agency river basin planning, (4) timber resource management information systems, (5) agricultural land reservation policies, and (6) shoreline flooding damage assessment. In addition, cost accounting procedures have been developed for evaluating the relative costs of utilizing remote sensing in land cover and land use analysis data collection procedures.
Development of satellite remote sensing techniques as an economic tool for forestry industry
NASA Technical Reports Server (NTRS)
Sader, Steven A.; Jadkowski, Mark A.
1989-01-01
A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?
Vortex sensing tests at NAFEC.
DOT National Transportation Integrated Search
1972-01-01
The report describes the results of a series of tests to determine and evaluate three experimental techniques for remote sensing of the wing-tip vortices generated by heavy commercial and military aircraft. These techniques involved a pulsed, bistati...
Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang
2009-10-01
Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.
Research on Horizontal Accuracy Method of High Spatial Resolution Remotely Sensed Orthophoto Image
NASA Astrophysics Data System (ADS)
Xu, Y. M.; Zhang, J. X.; Yu, F.; Dong, S.
2018-04-01
At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostly based on a set of testing points with the same accuracy and reliability. However, it is difficult to get a set of testing points with the same accuracy and reliability in the areas where the field measurement is difficult and the reference data with high accuracy is not enough. So it is difficult to test and evaluate the horizontal accuracy of the orthophoto image. The uncertainty of the horizontal accuracy has become a bottleneck for the application of satellite borne high-resolution remote sensing image and the scope of service expansion. Therefore, this paper proposes a new method to test the horizontal accuracy of orthophoto image. This method using the testing points with different accuracy and reliability. These points' source is high accuracy reference data and field measurement. The new method solves the horizontal accuracy detection of the orthophoto image in the difficult areas and provides the basis for providing reliable orthophoto images to the users.
Earth view: A business guide to orbital remote sensing
NASA Technical Reports Server (NTRS)
Bishop, Peter C.
1990-01-01
The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.
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.
Technology study of quantum remote sensing imaging
NASA Astrophysics Data System (ADS)
Bi, Siwen; Lin, Xuling; Yang, Song; Wu, Zhiqiang
2016-02-01
According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.
Wageningen UR Unmanned Aerial Remote Sensing Facility - Overview of activities
NASA Astrophysics Data System (ADS)
Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe
2016-04-01
To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all around the world, while new camera systems are being planned such as LiDAR and a full frame hyperspectral camera. In the presentation we will give an overview of our activities, ranging from erosion studies, decision support for precision agriculture, determining leaf biochemistry and canopy structure in tropical forests to the mapping of coastal zones.
NASA Technical Reports Server (NTRS)
Jenkins, D. W.
1972-01-01
NASA chose the watershed of Rhode River, a small sub-estuary of the Bay, as a representative test area for intensive studies of remote sensing, the results of which could be extrapolated to other estuarine watersheds around the Bay. A broad program of ecological research was already underway within the watershed, conducted by the Smithsonian Institution's Chesapeake Bay Center for Environmental Studies (CBCES) and cooperating universities. This research program offered a unique opportunity to explore potential applications for remote sensing techniques. This led to a joint NASA-CBCES project with two basic objectives: to evaluate remote sensing data for the interpretation of ecological parameters, and to provide essential data for ongoing research at the CBCES. A third objective, dependent upon realization of the first two, was to extrapolate photointerpretive expertise gained at the Rhode River watershed to other portions of the Chesapeake Bay.
Cooperative remote sensing and actuation using networked unmanned vehicles
NASA Astrophysics Data System (ADS)
Chao, Haiyang
This dissertation focuses on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes in the current information-rich world. The target scenarios are environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks, etc. AggieAir, a small and low-cost unmanned aircraft system, is designed based on the remote sensing requirements from environmental monitoring missions. The state estimation problem and the advanced lateral flight controller design problem are further attacked focusing on the small unmanned aerial vehicle (UAV) platform. Then the UAV-based remote sensing problem is focused with further flight test results. Given the measurements from unmanned vehicles, the actuation algorithms are needed for missions like the diffusion control. A consensus-based central Voronoi tessellation (CVT) algorithm is proposed for better control of the diffusion process. Finally, the dissertation conclusion and some new research suggestions are presented.
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
Disaster Emergency Rapid Assessment Based on Remote Sensing and Background Data
NASA Astrophysics Data System (ADS)
Han, X.; Wu, J.
2018-04-01
The period from starting to the stable conditions is an important stage of disaster development. In addition to collecting and reporting information on disaster situations, remote sensing images by satellites and drones and monitoring results from disaster-stricken areas should be obtained. Fusion of multi-source background data such as population, geography and topography, and remote sensing monitoring information can be used in geographic information system analysis to quickly and objectively assess the disaster information. According to the characteristics of different hazards, the models and methods driven by the rapid assessment of mission requirements are tested and screened. Based on remote sensing images, the features of exposures quickly determine disaster-affected areas and intensity levels, and extract key disaster information about affected hospitals and schools as well as cultivated land and crops, and make decisions after emergency response with visual assessment results.
Separating vegetation and soil temperature using airborne multiangular remote sensing image data
NASA Astrophysics Data System (ADS)
Liu, Qiang; Yan, Chunyan; Xiao, Qing; Yan, Guangjian; Fang, Li
2012-07-01
Land surface temperature (LST) is a key parameter in land process research. Many research efforts have been devoted to increase the accuracy of LST retrieval from remote sensing. However, because natural land surface is non-isothermal, component temperature is also required in applications such as evapo-transpiration (ET) modeling. This paper proposes a new algorithm to separately retrieve vegetation temperature and soil background temperature from multiangular thermal infrared (TIR) remote sensing data. The algorithm is based on the localized correlation between the visible/near-infrared (VNIR) bands and the TIR band. This method was tested on the airborne image data acquired during the Watershed Allied Telemetry Experimental Research (WATER) campaign. Preliminary validation indicates that the remote sensing-retrieved results can reflect the spatial and temporal trend of component temperatures. The accuracy is within three degrees while the difference between vegetation and soil temperature can be as large as twenty degrees.
Development of flight experiments for remote measurement of pollution
NASA Technical Reports Server (NTRS)
Keafer, L. S., Jr.; Kopia, L. P.
1973-01-01
The status as of February 1973 of several NASA-sponsored development projects is reported concerning flight experiments for remote measurement of pollution. Eight passive multispectral instruments for remotely sensing air and water pollutants are described, as well as two active (laser radar) measuring techniques. These techniques are expected to add some new dimensions to the remote sensing of water quality, oceanographic parameters, and earth resources. Multiple applications in these fields are generally possible. Successful completion of the flight demonstration tests and comparisons with simultaneously obtained surface truth measurements may establish these techniques as valid water quality monitoring tools.
A high throughput geocomputing system for remote sensing quantitative retrieval and a case study
NASA Astrophysics Data System (ADS)
Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting
2011-12-01
The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.
Alistair M.S. Smith; Martin J. Wooster; Nick A. Drake; Frederick M. Dipotso; Michael J. Falkowski; Andrew T. Hudak
2005-01-01
The remote sensing of fire severity is a noted goal in studies of forest and grassland wildfires. Experiments were conducted to discover and evaluate potential relationships between the characteristics of African savannah fires and post-fire surface spectral reflectance in the visible to shortwave infrared spectral region. Nine instrumented experimental fires were...
Applications of Remote Sensing to Emergency Management.
1980-02-15
Contents: Foundations of Remote Sensing : Data Acquisition and Interpretation; Availability of Remote Sensing Technology for Disaster Response...Imaging Systems, Current and Near Future Satellite and Aircraft Remote Sensing Systems; Utilization of Remote Sensing in Disaster Response: Categories of...Disasters, Phases of Monitoring Activities; Recommendations for Utilization of Remote Sensing Technology in Disaster Response; Selected Reading List.
Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas
NASA Astrophysics Data System (ADS)
Sun, X. F.; Lin, X. G.
2017-09-01
As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.
NASA Astrophysics Data System (ADS)
Cherukuru, Nagur; Ford, Phillip W.; Matear, Richard J.; Oubelkheir, Kadija; Clementson, Lesley A.; Suber, Ken; Steven, Andrew D. L.
2016-10-01
Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20-520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.
NASA Astrophysics Data System (ADS)
Changyong, Dou; Huadong, Guo; Chunming, Han; Ming, Liu
2014-03-01
With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.
NASA Technical Reports Server (NTRS)
Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.
2013-01-01
In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.
NASA Technical Reports Server (NTRS)
Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.
2013-01-01
In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.
The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce
NASA Astrophysics Data System (ADS)
Chen, Xi; Zhou, Liqing
2015-12-01
With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.
NASA Technical Reports Server (NTRS)
Beck, L. R.; Rodriguez, M. H.; Dister, S. W.; Rodriguez, A. D.; Washino, R. K.; Roberts, D. R.; Spanner, M. A.
1997-01-01
A blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.
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 TECHNOLOGIES APPLICATIONS RESEARCH
Remote sensing technologies applications research supports the ORD Landscape Sciences Program (LSP) in two separate areas: operational remote sensing, and remote sensing research and development. Operational remote sensing is provided to the LSP through the use of current and t...
NDSI products system based on Hadoop platform
NASA Astrophysics Data System (ADS)
Zhou, Yan; Jiang, He; Yang, Xiaoxia; Geng, Erhui
2015-12-01
Snow is solid state of water resources on earth, and plays an important role in human life. Satellite remote sensing is significant in snow extraction with the advantages of cyclical, macro, comprehensiveness, objectivity, timeliness. With the continuous development of remote sensing technology, remote sensing data access to the trend of multiple platforms, multiple sensors and multiple perspectives. At the same time, in view of the remote sensing data of compute-intensive applications demand increase gradually. However, current the producing system of remote sensing products is in a serial mode, and this kind of production system is used for professional remote sensing researchers mostly, and production systems achieving automatic or semi-automatic production are relatively less. Facing massive remote sensing data, the traditional serial mode producing system with its low efficiency has been difficult to meet the requirements of mass data timely and efficient processing. In order to effectively improve the production efficiency of NDSI products, meet the demand of large-scale remote sensing data processed timely and efficiently, this paper build NDSI products production system based on Hadoop platform, and the system mainly includes the remote sensing image management module, NDSI production module, and system service module. Main research contents and results including: (1)The remote sensing image management module: includes image import and image metadata management two parts. Import mass basis IRS images and NDSI product images (the system performing the production task output) into HDFS file system; At the same time, read the corresponding orbit ranks number, maximum/minimum longitude and latitude, product date, HDFS storage path, Hadoop task ID (NDSI products), and other metadata information, and then create thumbnails, and unique ID number for each record distribution, import it into base/product image metadata database. (2)NDSI production module: includes the index calculation, production tasks submission and monitoring two parts. Read HDF images related to production task in the form of a byte stream, and use Beam library to parse image byte stream to the form of Product; Use MapReduce distributed framework to perform production tasks, at the same time monitoring task status; When the production task complete, calls remote sensing image management module to store NDSI products. (3)System service module: includes both image search and DNSI products download. To image metadata attributes described in JSON format, return to the image sequence ID existing in the HDFS file system; For the given MapReduce task ID, package several task output NDSI products into ZIP format file, and return to the download link (4)System evaluation: download massive remote sensing data and use the system to process it to get the NDSI products testing the performance, and the result shows that the system has high extendibility, strong fault tolerance, fast production speed, and the image processing results with high accuracy.
NASA Technical Reports Server (NTRS)
Coyle, D. Barry; Stysley, Paul R.; Poulios, Demetrios; Fredrickson, Robert M.; Kay, Richard B.; Cory, Kenneth C.
2014-01-01
We report on a newly solid state laser transmitter, designed and packaged for Earth and planetary space-based remote sensing applications for high efficiency, low part count, high pulse energy scalability/stability, and long life. Finally, we have completed a long term operational test which surpassed 2 Billion pulses with no measured decay in pulse energy.
Application of remote sensor data to geologic analysis of the Bonanza test site Colorado
NASA Technical Reports Server (NTRS)
Lee, K. (Compiler); Butler, R. W.; Fisher, J. C.; Huntley, D.; Hulstrom, R. L.; Knepper, D. H., Jr.; Muhm, J. R.; Sawatzky, D. L.; Worman, K. E.; Wychgram, D.
1973-01-01
Research activities on geologic remote sensing applications for Colorado are summarized. Projects include: regional and detailed geologic mapping, surficial and engineering geology, fracture studies, uranium exploration, hydrology, and data reduction and enhancement. The acquisition of remote sensor data is also discussed.
Reliability analysis of airship remote sensing system
NASA Astrophysics Data System (ADS)
Qin, Jun
1998-08-01
Airship Remote Sensing System (ARSS) for obtain the dynamic or real time images in the remote sensing of the catastrophe and the environment, is a mixed complex system. Its sensor platform is a remote control airship. The achievement of a remote sensing mission depends on a series of factors. For this reason, it is very important for us to analyze reliability of ARSS. In first place, the system model was simplified form multi-stage system to two-state system on the basis of the result of the failure mode and effect analysis and the failure tree failure mode effect and criticality analysis. The failure tree was created after analyzing all factors and their interrelations. This failure tree includes four branches, e.g. engine subsystem, remote control subsystem, airship construction subsystem, flying metrology and climate subsystem. By way of failure tree analysis and basic-events classing, the weak links were discovered. The result of test running shown no difference in comparison with theory analysis. In accordance with the above conclusions, a plan of the reliability growth and reliability maintenance were posed. System's reliability are raised from 89 percent to 92 percent with the reformation of the man-machine interactive interface, the augmentation of the secondary better-groupie and the secondary remote control equipment.
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
Tunnel-Site Selection by Remote Sensing Techniques
A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave
1998 IEEE Aerospace Conference. Proceedings.
NASA Astrophysics Data System (ADS)
The following topics were covered: science frontiers and aerospace; flight systems technologies; spacecraft attitude determination and control; space power systems; smart structures and dynamics; military avionics; electronic packaging; MEMS; hyperspectral remote sensing for GVP; space laser technology; pointing, control, tracking and stabilization technologies; payload support technologies; protection technologies; 21st century space mission management and design; aircraft flight testing; aerospace test and evaluation; small satellites and enabling technologies; systems design optimisation; advanced launch vehicles; GPS applications and technologies; antennas and radar; software and systems engineering; scalable systems; communications; target tracking applications; remote sensing; advanced sensors; and optoelectronics.
System and method for evaluating wind flow fields using remote sensing devices
Schroeder, John; Hirth, Brian; Guynes, Jerry
2016-12-13
The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.
Exploring Models and Data for Remote Sensing Image Caption Generation
NASA Astrophysics Data System (ADS)
Lu, Xiaoqiang; Wang, Binqiang; Zheng, Xiangtao; Li, Xuelong
2018-04-01
Inspired by recent development of artificial satellite, remote sensing images have attracted extensive attention. Recently, noticeable progress has been made in scene classification and target detection.However, it is still not clear how to describe the remote sensing image content with accurate and concise sentences. In this paper, we investigate to describe the remote sensing images with accurate and flexible sentences. First, some annotated instructions are presented to better describe the remote sensing images considering the special characteristics of remote sensing images. Second, in order to exhaustively exploit the contents of remote sensing images, a large-scale aerial image data set is constructed for remote sensing image caption. Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption. Extensive experiments on the proposed data set demonstrate that the content of the remote sensing image can be completely described by generating language descriptions. The data set is available at https://github.com/201528014227051/RSICD_optimal
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.
NASA Technical Reports Server (NTRS)
Labovitz, M. L.; Masuoka, E. J.; Bell, R.; Nelson, R. F.; Larsen, C. A.; Hooker, L. K.; Troensegaard, K. W.
1985-01-01
It is pointed out that in many regions of the world, vegetation is the predominant factor influencing variation in reflected energy in the 0.4-2.5 micron region of the spectrum. Studies have, therefore, been conducted regarding the utility of remote sensing for detecting changes in vegetation which could be related to the presence of mineralization. The present paper provides primarily a report on the results of the second year of a multiyear study of geobotanical-remote-sensing relationships as developed over areas of sulfide mineralization. The field study has a strong experimental design basis. It is proceeded by first delineating the boundaries of a large geographic region which satisfied a set of previously enumerated field-site criteria. Within this region, carefully selected pairs of mineralized and nonmineralized test sites were examined over the growing season. The experiment is to provide information about the spectral and temporal resolutions required for remote-sensing-geobotanical exploration. The obtained results are evaluated.
Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop
NASA Astrophysics Data System (ADS)
Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.
2018-04-01
The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.
Hyperspectral remote sensing of plant pigments.
Blackburn, George Alan
2007-01-01
The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.
The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish
NASA Technical Reports Server (NTRS)
Savastano, K. J.; Leming, T. D.
1975-01-01
An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.
NASA Astrophysics Data System (ADS)
Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang
2017-08-01
According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.
Introduction to the physics and techniques of remote sensing
NASA Technical Reports Server (NTRS)
Elachi, Charles
1987-01-01
This book presents a comprehensive overview of the basics behind remote-sensing physics, techniques, and technology. The physics of wave/matter interactions, techniques of remote sensing across the electromagnetic spectrum, and the concepts behind remote sensing techniques now established and future ones under development are discussed. Applications of remote sensing are described for a wide variety of earth and planetary atmosphere and surface sciences. Solid surface sensing across the electromagnetic spectrum, ocean surface sensing, basic principles of atmospheric sensing and radiative transfer, and atmospheric remote sensing in the microwave, millimeter, submillimeter, and infrared regions are examined.
[Thematic Issue: Remote Sensing.
ERIC Educational Resources Information Center
Howkins, John, Ed.
1978-01-01
Four of the articles in this publication discuss the remote sensing of the Earth and its resources by satellites. Among the topics dealt with are the development and management of remote sensing systems, types of satellites used for remote sensing, the uses of remote sensing, and issues involved in using information obtained through remote…
75 FR 65304 - Advisory Committee on Commercial Remote Sensing (ACCRES); Request for Nominations
Federal Register 2010, 2011, 2012, 2013, 2014
2010-10-22
... Commercial Remote Sensing (ACCRES); Request for Nominations AGENCY: National Oceanic and Atmospheric... Commercial Remote Sensing (ACCRES). SUMMARY: The Advisory Committee on Commercial Remote Sensing (ACCRES) was... Atmosphere, on matters relating to the U.S. commercial remote sensing industry and NOAA's activities to carry...
NASA Astrophysics Data System (ADS)
Freeman, Lauren A.; Ackleson, Steven G.; Rhea, William Joseph
2017-10-01
Suspended particulate matter (SPM) is a key environmental indicator for rivers, estuaries, and coastal waters, which can be calculated from remote sensing reflectance obtained by an airborne or satellite imager. Here, algorithms from prior studies are applied to a dataset of in-situ at surface hyperspectral remote sensing reflectance, collected in three geographic regions representing different water types. These data show the optically inherent exponential nature of the relationship between reflectance and sediment concentration. However, linear models are also shown to provide a reasonable estimate of sediment concentration when utilized with care in similar conditions to those under which the algorithms were developed, particularly at lower SPM values (0 to 20 mg/L). Fifteen published SPM algorithms are tested, returning strong correlations of R2>0.7, and in most cases, R2>0.8. Very low SPM values show weaker correlation with algorithm calculated SPM that is not wavelength dependent. None of the tested algorithms performs well for high SPM values (>30 mg/L), with most algorithms underestimating SPM. A shift toward a smaller number of simple exponential or linear models relating satellite remote sensing reflectance to suspended sediment concentration with regional consideration will greatly aid larger spatiotemporal studies of suspended sediment trends.
Literature relevant to remote sensing of water quality
NASA Technical Reports Server (NTRS)
Middleton, E. M.; Marcell, R. F.
1983-01-01
References relevant to remote sensing of water quality were compiled, organized, and cross-referenced. The following general categories were included: (1) optical properties and measurement of water characteristics; (2) interpretation of water characteristics by remote sensing, including color, transparency, suspended or dissolved inorganic matter, biological materials, and temperature; (3) application of remote sensing for water quality monitoring; (4) application of remote sensing according to water body type; and (5) manipulation, processing and interpretation of remote sensing digital water data.
NASA Astrophysics Data System (ADS)
Zheng, Maoteng; Zhang, Yongjun; Zhou, Shunping; Zhu, Junfeng; Xiong, Xiaodong
2016-07-01
In recent years, new platforms and sensors in photogrammetry, remote sensing and computer vision areas have become available, such as Unmanned Aircraft Vehicles (UAV), oblique camera systems, common digital cameras and even mobile phone cameras. Images collected by all these kinds of sensors could be used as remote sensing data sources. These sensors can obtain large-scale remote sensing data which consist of a great number of images. Bundle block adjustment of large-scale data with conventional algorithm is very time and space (memory) consuming due to the super large normal matrix arising from large-scale data. In this paper, an efficient Block-based Sparse Matrix Compression (BSMC) method combined with the Preconditioned Conjugate Gradient (PCG) algorithm is chosen to develop a stable and efficient bundle block adjustment system in order to deal with the large-scale remote sensing data. The main contribution of this work is the BSMC-based PCG algorithm which is more efficient in time and memory than the traditional algorithm without compromising the accuracy. Totally 8 datasets of real data are used to test our proposed method. Preliminary results have shown that the BSMC method can efficiently decrease the time and memory requirement of large-scale data.
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.
Simulating optoelectronic systems for remote sensing with SENSOR
NASA Astrophysics Data System (ADS)
Boerner, Anko
2003-04-01
The consistent end-to-end simulation of airborne and spaceborne remote sensing systems is an important task and sometimes the only way for the adaptation and optimization of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software ENvironment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. It allows the simulation of a wide range of optoelectronic systems for remote sensing. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. Part three consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimization requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and examples of its use are given. The verification of SENSOR is demonstrated.
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.
Using Remotely Sensed Data to Map Urban Vulnerability to Heat
NASA Technical Reports Server (NTRS)
Stefanov, William L.
2010-01-01
This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.
JPRS Report, Science & Technology, China, Remote Sensing Systems, Applications.
1991-01-17
Partial Contents: Short Introduction to Nation’s Remote Sensing Units, Domestic Airborne Remote - Sensing System, Applications in Monitoring Natural...Disasters, Applications of Imagery From Experimental Satellites Launched in 1985, 1986, Current Status, Future Prospects for Domestic Remote - Sensing -Satellite...Ground Station, and Radar Remote - Sensing Technology Used to Monitor Yellow River Delta,
Radar-based dynamic testing of the cable-suspended bridge crossing the Ebro River at Amposta, Spain
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gentile, Carmelo; Luzi, Guido
2014-05-27
Microwave remote sensing is the most recent experimental methodology suitable to the non-contact measurement of deflections on large structures, in static or dynamic conditions. After a brief description of the radar measurement system, the paper addresses the application of microwave remote sensing to ambient vibration testing of a cable-suspended bridge. The investigated bridge crosses the Ebro River at Amposta, Spain and consists of two steel stiffening trusses and a series of equally spaced steel floor beams; the main span is supported by inclined stay cables and two series of 8 suspension cables. The dynamic tests were performed in operational conditions,more » with the sensor being placed in two different positions so that the response of both the steel deck and the arrays of suspension elements was measured. The experimental investigation confirms the simplicity of use of the radar and the accuracy of the results provided by the microwave remote sensing as well as the issues often met in the clear localization of measurement points.« less
[A review on polarization information in the remote sensing detection].
Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao
2010-04-01
Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.
NASA Technical Reports Server (NTRS)
Jolliff, B.; Moersch, J.; Knoll, A.; Morris, R.; Arvidson, R.; Gilmore, M.; Greeley, R.; Herkenhoff, K.; McSween, H.; Squyres, S.
2000-01-01
Tests of the FIDO (Field Integration Design and Operations) rover and Athena-like operational scenarios were conducted May 7-16, 2000. A group located at the Jet Propulsion Lab, Pasadena, CA, formed the Core Operations Team (COT) that designed experiments and command sequences while another team tracked, maintained, and secured the rover in the field. The COT had no knowledge of the specific field location, thus the tests were done "blind." In addition to FIDO rover instrumentation, the COT had access to LANDSAT 7, TIMS, and AVIRIS regional coverage and color descent images. Using data from the FIDO instruments, primarily a color microscopic imager (CMI), infrared point spectrometer (IPS; 1.5-2.4 microns), and a three-color stereo panoramic camera (Pancam), the COT correlated lithologic features (mineralogy, rock types) from the simulated landing site to a regional scale. The May test results provide an example of how to relate site geology from landed rover investigations to the regional geology using remote sensing. The capability to relate mineralogic signatures using the point IR spectrometer to remotely sensed, multispectral or hyperspectral data proved to be key to integration of the in-situ and remote data. This exercise demonstrated the potential synergy between lander-based and orbital data, and highlighted the need to investigate a landing site in detail and at multiple scales.
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.
Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science
NASA Astrophysics Data System (ADS)
Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.
2017-09-01
Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.
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.
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.
Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic
NASA Astrophysics Data System (ADS)
Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav
2015-04-01
Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in order to improve planning, business strategies but also to target the drought relief in case of major drought event. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".
Automobile gross emitter screening with remote sensing data using objective-oriented neural network.
Chen, Ho-Wen; Yang, Hsi-Hsien; Wang, Yu-Sheng
2009-11-01
One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.
Remote Sensing Applications to Water Quality Management in Florida
NASA Astrophysics Data System (ADS)
Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.
2013-12-01
Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria
NASA Technical Reports Server (NTRS)
Ross, Kenton W.; McKellip, Rodney D.
2005-01-01
Topics covered include: Implementation and Validation of Sensor-Based Site-Specific Crop Management; Enhanced Management of Agricultural Perennial Systems (EMAPS) Using GIS and Remote Sensing; Validation and Application of Geospatial Information for Early Identification of Stress in Wheat; Adapting and Validating Precision Technologies for Cotton Production in the Mid-Southern United States - 2004 Progress Report; Development of a System to Automatically Geo-Rectify Images; Economics of Precision Agriculture Technologies in Cotton Production-AG 2020 Prescription Farming Automation Algorithms; Field Testing a Sensor-Based Applicator for Nitrogen and Phosphorus Application; Early Detection of Citrus Diseases Using Machine Vision and DGPS; Remote Sensing of Citrus Tree Stress Levels and Factors; Spectral-based Nitrogen Sensing for Citrus; Characterization of Tree Canopies; In-field Sensing of Shallow Water Tables and Hydromorphic Soils with an Electromagnetic Induction Profiler; Maintaining the Competitiveness of Tree Fruit Production Through Precision Agriculture; Modeling and Visualizing Terrain and Remote Sensing Data for Research and Education in Precision Agriculture; Thematic Soil Mapping and Crop-Based Strategies for Site-Specific Management; and Crop-Based Strategies for Site-Specific Management.
Hakkenberg, C R; Zhu, K; Peet, R K; Song, C
2018-02-01
The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms. © 2017 by the Ecological Society of America.
Supervised classification of aerial imagery and multi-source data fusion for flood assessment
NASA Astrophysics Data System (ADS)
Sava, E.; Harding, L.; Cervone, G.
2015-12-01
Floods are among the most devastating natural hazards and the ability to produce an accurate and timely flood assessment before, during, and after an event is critical for their mitigation and response. Remote sensing technologies have become the de-facto approach for observing the Earth and its environment. However, satellite remote sensing data are not always available. For these reasons, it is crucial to develop new techniques in order to produce flood assessments during and after an event. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. This research presents a fusion technique using satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and tweets. A new computational methodology is proposed based on machine learning algorithms to automatically identify water pixels in CAP imagery. Specifically, wavelet transformations are paired with multiple classifiers, run in parallel, to build models discriminating water and non-water regions. The learned classification models are first tested against a set of control cases, and then used to automatically classify each image separately. A measure of uncertainty is computed for each pixel in an image proportional to the number of models classifying the pixel as water. Geo-tagged tweets are continuously harvested and stored on a MongoDB and queried in real time. They are fused with CAP classified data, and with satellite remote sensing derived flood extent results to produce comprehensive flood assessment maps. The final maps are then compared with FEMA generated flood extents to assess their accuracy. The proposed methodology is applied on two test cases, relative to the 2013 floods in Boulder CO, and the 2015 floods in Texas.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Newman, Jennifer; Clifton, Andrew; Bonin, Timothy
As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing considermore » uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict errors in lidar-measured wind speed. The results show how uncertainty varies over time and can be used to help select data with different levels of uncertainty for different applications, for example, low uncertainty data for power performance testing versus all data for plant performance monitoring.« less
Spectrometric test of a linear array sensor
NASA Technical Reports Server (NTRS)
Brown, Kenneth S.; Kim, Moon S.
1987-01-01
A spectroradiometer which measures spectral reflectivities and irradiance in discrete spectral channels was tested to determine the accuracy of its wavelength calibration. This sensor is a primary tool in the remote sensing investigations conducted on biomass at NASA's Goddard Space Flight Center. Measurements have been collected on crop and forest plants both in the laboratory and field with this radiometer to develop crop identification and plant stress remote sensing techniques. Wavelength calibration is essential for use in referencing the study measurements with those of other investigations and satellite remote sensor data sets. This calibration determines a wavelength vs channel address conversion which was found to have an RMS deviation of approximately half a channel, or 1.5 nm in the range from 360 to 1050 nm. A comparison of these results with those of another test showed an average difference of approximately 4 nm, sufficiently accurate for most investigative work.
Near-earth orbital guidance and remote sensing
NASA Technical Reports Server (NTRS)
Powers, W. F.
1972-01-01
The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.
Operational programs in forest management and priority in the utilization of remote sensing
NASA Technical Reports Server (NTRS)
Douglass, R. W.
1978-01-01
A speech is given on operational remote sensing programs in forest management and the importance of remote sensing in forestry is emphasized. Forest service priorities in using remote sensing are outlined.
Remote sensing, land use, and demography - A look at people through their effects on the land
NASA Technical Reports Server (NTRS)
Paul, C. K.; Landini, A. J.
1976-01-01
Relevant causes of failure by the remote sensing community in the urban scene are analyzed. The reasons for the insignificant role of remote sensing in urban land use data collection are called the law of realism, the incompatibility of remote sensing and urban management system data formats is termed the law of nominal/ordinal systems compatibility, and the land use/population correlation dilemma is referred to as the law of missing persons. The study summarizes the three laws of urban land use information for which violations, avoidance, or ignorance have caused the decline of present remote sensing research. Particular attention is given to the rationale for urban land use information and for remote sensing. It is shown that remote sensing of urban land uses compatible with the three laws can be effectively developed by realizing the 10 percent contribution of remote sensing to urban land use planning data collection.
NASA Technical Reports Server (NTRS)
1991-01-01
The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.
Methods of training the graduate level and professional geologist in remote sensing technology
NASA Technical Reports Server (NTRS)
Kolm, K. E.
1981-01-01
Requirements for a basic course in remote sensing to accommodate the needs of the graduate level and professional geologist are described. The course should stress the general topics of basic remote sensing theory, the theory and data types relating to different remote sensing systems, an introduction to the basic concepts of computer image processing and analysis, the characteristics of different data types, the development of methods for geological interpretations, the integration of all scales and data types of remote sensing in a given study, the integration of other data bases (geophysical and geochemical) into a remote sensing study, and geological remote sensing applications. The laboratories should stress hands on experience to reinforce the concepts and procedures presented in the lecture. The geologist should then be encouraged to pursue a second course in computer image processing and analysis of remotely sensed data.
Remote sensing of Earth terrain
NASA Technical Reports Server (NTRS)
Kong, J. A.
1993-01-01
Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.
Remote sensing by satellite - Technical and operational implications for international cooperation
NASA Technical Reports Server (NTRS)
Doyle, S. E.
1976-01-01
International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.
NASA Astrophysics Data System (ADS)
Suchocki, Czesław; Katzer, Jacek; Panuś, Arkadiusz
2017-06-01
Terrestrial Laser Scanner (TLS) method which is commonly used for geodetic applications has a great potential to be successfully harnessed for multiple civil engineering applications. One of the most promising uses of TLS in construction industry is remote sensing of saturation of building materials. A research programme was prepared in order to prove that harnessing TLS for such an application is viable. Results presented in the current paper are a part of a much larger research programme focused on harnessing TLS for remote sensing of saturation of building materials. The paper describes results of the tests conducted with an impulse scanner Leica C-10. Tests took place both indoors (in a stable lab conditions) and outdoors (in a real environment). There were scanned specimens of the most popular building materials in Europe. Tested specimens were dried and saturated (including capillary rising moisture). One of the tests was performed over a period of 95 hours. Basically, a concrete specimen was scanned during its setting and hardening. It was proven that absorption of a laser signal is influenced by setting and hardening of concrete. Outdoor tests were based on scanning real buildings with partially saturated facades. The saturation assessment was based on differences of values of intensity. The concept proved to be feasible and technically realistic.
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.
Multitask SVM learning for remote sensing data classification
NASA Astrophysics Data System (ADS)
Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo
2010-10-01
Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.
Remote sensing of a coupled carbon-water-energy-radiation balances from the Globe to plot scales
NASA Astrophysics Data System (ADS)
Ryu, Y.; Jiang, C.; Huang, Y.; Kim, J.; Hwang, Y.; Kimm, H.; Kim, S.
2016-12-01
Advancements in near-surface and satellite remote sensing technologies have enabled us to monitor the global terrestrial ecosystems at multiple spatial and temporal scales. An emergent challenge is how to formulate a coupled water, carbon, energy, radiation, and nitrogen cycles from remote sensing. Here, we report Breathing Earth System Simulator (BESS), which coupled radiation (shortwave, longwave, PAR, diffuse PAR), carbon (gross primary productivity, ecosystem respiration, net ecosystem exchange), water (evaporation), and energy (latent and sensible heat) balances across the global land at 1 km resolution, 8 daily between 2000 and 2015 using multiple satellite remote sensing. The performance of BESS was tested against field observations (FLUXNET, BSRN) and other independent products (MPI-BGC, MODIS, GLASS). We found that the coupled model, BESS showed on par with, or better performance than the other products which computed land surface fluxes individually. Lastly, we show one plot-level study conducted in a paddy rice to demonstrate how to couple radiation, carbon, water, nitrogen balances with a series of near-surface spectral sensors.
Bakó, Gábor; Tolnai, Márton; Takács, Ádám
2014-01-01
Remote sensing is a method that collects data of the Earth's surface without causing disturbances. Thus, it is worthwhile to use remote sensing methods to survey endangered ecosystems, as the studied species will behave naturally while undisturbed. The latest passive optical remote sensing solutions permit surveys from long distances. State-of-the-art highly sensitive sensor systems allow high spatial resolution image acquisition at high altitudes and at high flying speeds, even in low-visibility conditions. As the aerial imagery captured by an airplane covers the entire study area, all the animals present in that area can be recorded. A population assessment is conducted by visual interpretations of an ortho image map. The basic objective of this study is to determine whether small- and medium-sized bird species are recognizable in the ortho images by using high spatial resolution aerial cameras. The spatial resolution needed for identifying the bird species in the ortho image map was studied. The survey was adjusted to determine the number of birds in a colony at a given time. PMID:25046012
Ocean experiments and remotely sensed images of chemically dispersed oil spills
NASA Technical Reports Server (NTRS)
Croswell, W. F.; Fedors, J. C.; Hoge, F. E.; Swift, R. N.; Johnson, J. C.
1983-01-01
A series of experiments was performed at sea where the effectiveness of dispersants applied from a helicopter was tested on fresh and weathered crude oils released from a surface research vessel. In conjunction with these experiments, remote sensing measurements using an array of airborne optical and microwave sensors were performed in order to aid in the interpretation of the dispersant effectiveness and to obtain quantitative images of oil on the sea under controlled conditions. Surface oil thickness and volume are inferred from airborne measurements using a dual-channel microwave imaging radiometer, aerial color photography, and an airborne oceanographic lidar. The remotely sensed measurements are compared with point sampled data obtained using a research vessel. The mass balance computations of surface versus subsurface oil volume using remotely sensed and point sampled data are consistent with each other and with the volumes of oil released. Data collected by the several techniques concur in indicating that, for the oils used and under the sea conditions encountered, the dispersant and application method are primarily useful when applied to fresh oil.
Layered classification techniques for remote sensing applications
NASA Technical Reports Server (NTRS)
Swain, P. H.; Wu, C. L.; Landgrebe, D. A.; Hauska, H.
1975-01-01
The single-stage method of pattern classification utilizes all available features in a single test which assigns the unknown to a category according to a specific decision strategy (such as the maximum likelihood strategy). The layered classifier classifies the unknown through a sequence of tests, each of which may be dependent on the outcome of previous tests. Although the layered classifier was originally investigated as a means of improving classification accuracy and efficiency, it was found that in the context of remote sensing data analysis, other advantages also accrue due to many of the special characteristics of both the data and the applications pursued. The layered classifier method and several of the diverse applications of this approach are discussed.
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.
Application of remote sensing for prediction and detection of thermal pollution
NASA Technical Reports Server (NTRS)
Veziroglu, T. N.; Lee, S. S.
1974-01-01
The first phase is described of a three year project for the development of a mathematical model for predicting thermal pollution by use of remote sensing measurements. A rigid-lid model was developed, and results were obtained for different wind conditions at Biscayne Bay in South Florida. The design of the measurement system was completed, and instruments needed for the first stage of experiment were acquired, tested, and calibrated. A preliminary research flight was conducted.
NASA Technical Reports Server (NTRS)
Dejesusparada, N. (Principal Investigator); Rodrigues, J. E.
1980-01-01
The methodology of remote sensing applied to geological study in a complex area was evaluated. Itatiaia was selected as a test area, which covers the alkaline massives and its precambrian basement. LANDSAT-MSS and radar mosaic of the RADAMBRASIL Project were used for photointerpretation. Previous geological works were consulted and many discrepancies in the distribution of stratigraphic units were found. Moreover, structural lineaments and talus deposits were clearly delineated.
Airborne Remote Sensing of the Plata Plume Using STARRS
2006-09-01
marine constructions . www.sea-technoJlav.com .byT. RT O ’A" n. -, Airborne Remote Sensing of the Plata Plume Using STARRS A New Generation Microwave...using possibilities of adapting a Seville, MATLAB®-from The Spain-based Construcciones Aero- Mathworks Inc. (Natick, Mas- nduticas SA (CASA) Aviocar C...34 Simula-STARRS was constructed and flight of smaller coastal areas with a preci- tion, vol. 78, pp. 36-55, 2002.tested in July 2003. Since aircraft
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
PROCEEDINGS OF THE FOURTH SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT; 12, 13, 14 APRIL 1966.
The symposium was conducted as part of a continuing program investigating the field of remote sensing , its potential in scientific research and...information on all aspects of remote sensing , with special emphasis on such topics as needs for remotely sensed data, data management, and the special... remote sensing programs, data acquisition, data analysis and application, and equipment design, were presented. (Author)
Remote sensing and image interpretation
NASA Technical Reports Server (NTRS)
Lillesand, T. M.; Kiefer, R. W. (Principal Investigator)
1979-01-01
A textbook prepared primarily for use in introductory courses in remote sensing is presented. Topics covered include concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; airphoto interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.
Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN)
Kaya, Shannon; Brisco, Brian; Cull, Andrew; Gallant, Alisa L.; Sadinski, Walter J.; Thompson, Dean
2010-01-01
The Canada Centre for Remote Sensing (CCRS) has more than 30 years of experience investigating the use of SAR remote sensing for many applications related to terrestrial water resources. Recently, CCRS scientists began contributing to the Terrestrial Wetland Global Change Research Network (TWGCRN), a bi-national research network dedicated to assessing impacts of global change on interconnected wetland-upland landscapes across a vital portion of North America. CCRS scientists are applying SAR remote sensing to characterize wetland components of these landscapes in three ways. First, they are using a comprehensive set of RADARSAT-2 SAR data collected during April to September 2009 to extract multi-temporal surface water information for key TWGCRN study landscapes in North America. Second, they are analyzing polarimetric RADARSAT-2 data to determine areas where double-bounce represents the primary scattering mechanism and is indicative of flooded vegetation in these landscapes. Third, they are testing advanced interferometric SAR techniques to estimate water levels with RADARSAT-2 Fine Quad polarimetric image pairs. The combined information from these three SAR analysis activities will provide TWGCRN scientists with an integrated view and monitoring capability for these dynamic wetland-upland landscapes. These data are being used in conjunction with other remote sensing and field data to study interactions between landscape and animal (birds and amphibians) responses to climate/global change.
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.
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.
Zou, Zhengxia; Shi, Zhenwei
2018-03-01
We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.
Education in Environmental Remote Sensing: Potentials and Problems.
ERIC Educational Resources Information Center
Kiefer, Ralph W.; Lillesand, Thomas M.
1983-01-01
Discusses remote sensing principles and applications and the status and needs of remote sensing education in the United States. A summary of the fundamental policy issues that will determine remote sensing's future role in environmental and resource managements is included. (Author/BC)
THE EPA REMOTE SENSING ARCHIVE
What would you do if you were faced with organizing 30 years of remote sensing projects that had been haphazardly stored at two separate locations for years then combined? The EPA Remote Sensing Archive, currently located in Las Vegas, Nevada. contains the remote sensing data and...
Research on remote sensing image pixel attribute data acquisition method in AutoCAD
NASA Astrophysics Data System (ADS)
Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui
2013-07-01
The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.
Bibliography of Remote Sensing Techniques Used in Wetland Research.
1993-01-01
remote sensing technology for detecting changes in wetland environments. This report documents a bibliographic search conducted as part of that work unit on applications of remote sensing techniques in wetland research. Results were used to guide research efforts on the use of remote sensing technology for wetland change detection and assessment. The citations are presented in three appendixes, organized by wetland type, sensor type, and author.... Change detection, Wetland assessment, Remote sensing ,
Kite Aerial Photography as a Tool for Remote Sensing
ERIC Educational Resources Information Center
Sallee, Jeff; Meier, Lesley R.
2010-01-01
As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…
NASA Astrophysics Data System (ADS)
Hunger, Sebastian; Karrasch, Pierre; Wessollek, Christine
2016-10-01
The European Water Framework Directive (Directive 2000/60/EC) is a mandatory agreement that guides the member states of the European Union in the field of water policy to fulfill the requirements for reaching the aim of the good ecological status of water bodies. In the last years several workflows and methods were developed to determine and evaluate the characteristics and the status of the water bodies. Due to their area measurements remote sensing methods are a promising approach to constitute a substantial additional value. With increasing availability of optical and radar remote sensing data the development of new methods to extract information from both types of remote sensing data is still in progress. Since most limitations of these data sets do not agree the fusion of both data sets to gain data with higher spectral resolution features the potential to obtain additional information in contrast to the separate processing of the data. Based thereupon this study shall research the potential of multispectral and radar remote sensing data and the potential of their fusion for the assessment of the parameters of water body structure. Due to the medium spatial resolution of the freely available multispectral Sentinel-2 data sets especially the surroundings of the water bodies and their land use are part of this study. SAR data is provided by the Sentinel-1 satellite. Different image fusion methods are tested and the combined products of both data sets are evaluated afterwards. The evaluation of the single data sets and the fused data sets is performed by means of a maximum-likelihood classification and several statistical measurements. The results indicate that the combined use of different remote sensing data sets can have an added value.
NASA Astrophysics Data System (ADS)
Painter, T. H.; Famiglietti, J. S.; Stephens, G. L.
2016-12-01
We live in a time of increasing strains on our global fresh water availability due to increasing population, warming climate, changes in precipitation, and extensive depletion of groundwater supplies. At the same time, we have seen enormous growth in capabilities to remotely sense the regional to global water cycle and model complex systems with physically based frameworks. The GEWEX Water Availability Grand Challenge for North America is poised to leverage this convergence of remote sensing and modeling capabilities to answer fundamental questions on the water cycle. In particular, we envision an experiment that targets the complex and resource-critical Western US from California to just into the Great Plains, constraining physically-based hydrologic modeling with the US and international remote sensing capabilities. In particular, the last decade has seen the implementation or soon-to-be launch of water cycle missions such as GRACE and GRACE-FO for groundwater, SMAP for soil moisture, GPM for precipitation, SWOT for terrestrial surface water, and the Airborne Snow Observatory for snowpack. With the advent of convection-resolving mesoscale climate and water cycle modeling (e.g. WRF, WRF-Hydro) and mesoscale models capable of quantitative assimilation of remotely sensed data (e.g. the JPL Western States Water Mission), we can now begin to test hypotheses on the nature and changes in the water cycle of the Western US from a physical standpoint. In turn, by fusing water cycle science, water management, and ecosystem management while addressing these hypotheses, this golden age of remote sensing and modeling can bring all fields into a markedly less uncertain state of present knowledge and decadal scale forecasts.
NASA Astrophysics Data System (ADS)
Kuhn, C.; Richey, J. E.; Striegl, R. G.; Ward, N.; Sawakuchi, H. O.; Crawford, J.; Loken, L. C.; Stadler, P.; Dornblaser, M.; Butman, D. E.
2017-12-01
More than 93% of the world's river-water volume occurs in basins impacted by large dams and about 43% of river water discharge is impacted by flow regulation. Human land use also alters nutrient and carbon cycling and the emission of carbon dioxide from inland reservoirs. Increased water residence times and warmer temperatures in reservoirs fundamentally alter the physical settings for biogeochemical processing in large rivers, yet river biogeochemistry for many large systems remains undersampled. Satellite remote sensing holds promise as a methodology for responsive regional and global water resources management. Decades of ocean optics research has laid the foundation for the use of remote sensing reflectance in optical wavelengths (400 - 700 nm) to produce satellite-derived, near-surface estimates of phytoplankton chlorophyll concentration. Significant improvements between successive generations of ocean color sensors have enabled the scientific community to document changes in global ocean productivity (NPP) and estimate ocean biomass with increasing accuracy. Despite large advances in ocean optics, application of optical methods to inland waters has been limited to date due to their optical complexity and small spatial scale. To test this frontier, we present a study evaluating the accuracy and suitability of empirical inversion approaches for estimating chlorophyll-a, turbidity and temperature for the Amazon, Columbia and Mississippi rivers using satellite remote sensing. We demonstrate how riverine biogeochemical measurements collected at high frequencies from underway vessels can be used as in situ matchups to evaluate remotely-sensed, near-surface temperature, turbidity, chlorophyll-a derived from the Landsat 8 (NASA) and Sentinel 2 (ESA) satellites. We investigate the use of remote sensing water reflectance to infer trophic status as well as tributary influences on the optical characteristics of the Amazon, Mississippi and Columbia rivers.
Remote sensing for detecting and mapping whitefly (Bemisia tabaci) infestations
USDA-ARS?s Scientific Manuscript database
Remote sensing technology has long been used for detecting insect infestations on agricultural crops. With recent advances in remote sensing sensors and other spatial information technologies such as Global Position Systems (GPS) and Geographic Information Systems (GIS), remote sensing is finding mo...
Reflections on Earth--Remote-Sensing Research from Your Classroom.
ERIC Educational Resources Information Center
Campbell, Bruce A.
2001-01-01
Points out the uses of remote sensing in different areas, and introduces the program "Reflections on Earth" which provides access to basic and instructional information on remote sensing to students and teachers. Introduces students to concepts related to remote sensing and measuring distances. (YDS)
Remote-Sensing Practice and Potential
1974-05-01
Six essential processes that must be accomplished if use of a remote - sensing system is to result in useful information are defined as problem...to be useful in remote - sensing projects are described. An overview of the current state-of-the-art of remote sensing is presented.
History and future of remote sensing technology and education
NASA Technical Reports Server (NTRS)
Colwell, R. N.
1980-01-01
A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.
Testing a small UAS for mapping artisanal diamond mining sites in Africa
Malpeli, Katherine C.; Chirico, Peter G.
2015-01-01
Remote sensing technology is advancing at an unprecedented rate. At the forefront of the new technological developments are unmanned aircraft systems (UAS). The advent of small, lightweight, low-cost, and user-friendly UAS is greatly expanding the potential applications of remote sensing technology and improving the set of tools available to researchers seeking to map and monitor terrain from above. In this article, we explore the applications of a small UAS for mapping informal diamond mining sites in Africa. We found that this technology provides aerial imagery of unparalleled resolution in a data-sparse, difficult to access, and remote terrain.
Ten ways remote sensing can contribute to conservation
Rose, Robert A.; Byler, Dirck; Eastman, J. Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A.; Laporte, Nadine; Leidner, Allison K.; Leimgruber, Peter; Morisette, Jeffrey T.; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C.; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara
2014-01-01
In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?
Ten ways remote sensing can contribute to conservation.
Rose, Robert A; Byler, Dirck; Eastman, J Ron; Fleishman, Erica; Geller, Gary; Goetz, Scott; Guild, Liane; Hamilton, Healy; Hansen, Matt; Headley, Rachel; Hewson, Jennifer; Horning, Ned; Kaplin, Beth A; Laporte, Nadine; Leidner, Allison; Leimgruber, Peter; Morisette, Jeffrey; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara
2015-04-01
In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions? © 2014 Society for Conservation Biology.
Role of remote sensing in documenting living resources
NASA Technical Reports Server (NTRS)
Wagner, P. E.; Anderson, R. R.; Brun, B.; Eisenberg, M.; Genys, J. B.; Lear, D. W., Jr.; Miller, M. H.
1978-01-01
Specific cases of known or potentially useful applications of remote sensing in assessing biological resources are discussed. It is concluded that the more usable remote sensing techniques relate to the measurement of population fluctuations in aquatic systems. Sensing of the flora and the fauna of the Bay is considered with emphasis on direct sensing of aquatic plant populations and of water quality. Recommendations for remote sensing projects are given.
Commercial future: making remote sensing a media event
NASA Astrophysics Data System (ADS)
Lurie, Ian
1999-12-01
The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.
1. Photocopy of photograph (original photograph/negative located at the Remote ...
1. Photocopy of photograph (original photograph/negative located at the Remote Sensing Laboratory, Nellis Air Force Base, Las Vegas, Nevada). R.B., Photograph for Civil Effects Test Organization, May 9, 1962. Historic view of Japanese village, facing west - Nevada Test Site, Japanese Village, Area 4, Yucca Flat, 4-04 Road near Rainier Mesa Road, Mercury, Nye County, NV
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.
NASA Astrophysics Data System (ADS)
Moskalenko, Irina V.; Shecheglov, Djolinard A.; Rogachev, Aleksei P.; Avdonin, Aleksandr A.; Molodtsov, Nikolai A.
1999-01-01
The lidar remote sensing techniques are powerful for monitoring of gaseous toxic species in atmosphere over wide areas. The paper presented describes design, development and field testing of Mobile Lidar System (MLS) based on utilization of Differential Absorption Lidar (DIAL) technique. The activity is performed by Russian Research Center 'Kurchatov Institute' and Research Institute of Pulse Technique within the project 'Mobile Remote SEnsing System Based on Tunable Laser Transmitter for Environmental Monitoring' under funding of International Scientific and Technology Center Moscow. A brief description of MLS is presented including narrowband transmitter, receiver, system steering, data acquisition subsystem and software. MLS is housed in a mobile truck and is able to provide 3D mapping of gaseous species. Sulfur dioxide and elemental mercury were chosen as basic atmospheric pollutants for field test of MLS. The problem of anthropogenic ozone detection attracts attention due to increase traffic in Moscow. The experimental sites for field testing are located in Moscow Region. Examples of field DIAL measurements will be presented. Application of remote sensing to toxic species near-real time measurements is now under consideration. The objective is comparison of pollution level in working zone with maximum permissible concentration of hazardous pollutant.
77 FR 39220 - Advisory Committee on Commercial Remote Sensing (ACCRES); Charter Renewal
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-02
... Commercial Remote Sensing (ACCRES); Charter Renewal AGENCY: National Oceanic and Atmospheric Administration... Committee on Commercial Remote Sensing (ACCRES) was renewed on March 14, 2012. SUPPLEMENTARY INFORMATION: In... Commercial Remote Sensing (ACCRES) is in the public interest in connection with the performance of duties...
76 FR 66042 - Advisory Committee on Commercial Remote Sensing (ACCRES); Request for Nominations
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-25
... Commercial Remote Sensing (ACCRES); Request for Nominations ACTION: Notice requesting nominations for the Advisory Committee on Commercial Remote Sensing (ACCRES). SUMMARY: The Advisory Committee on Commercial Remote Sensing (ACCRES) was established to advise the Secretary of Commerce, through the Under Secretary...
An introduction to quantitative remote sensing. [data processing
NASA Technical Reports Server (NTRS)
Lindenlaub, J. C.; Russell, J.
1974-01-01
The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.
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.
A Multiscale Random Field Model for Bayesian Image Segmentation
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
Application of remote sensing techniques for identification of irrigated crop lands in Arizona
NASA Technical Reports Server (NTRS)
Billings, H. A.
1981-01-01
Satellite imagery was used in a project developed to demonstrate remote sensing methods of determining irrigated acreage in Arizona. The Maricopa water district, west of Phoenix, was chosen as the test area. Band rationing and unsupervised categorization were used to perform the inventory. For both techniques the irrigation district boundaries and section lines were digitized and calculated and displayed by section. Both estimation techniques were quite accurate in estimating irrigated acreage in the 1979 growing season.
NASA Astrophysics Data System (ADS)
Gao, J.; Lythe, M. B.
1996-06-01
This paper presents the principle of the Maximum Cross-Correlation (MCC) approach in detecting translational motions within dynamic fields from time-sequential remotely sensed images. A C program implementing the approach is presented and illustrated in a flowchart. The program is tested with a pair of sea-surface temperature images derived from Advanced Very High Resolution Radiometer (AVHRR) images near East Cape, New Zealand. Results show that the mean currents in the region have been detected satisfactorily with the approach.
NASA Technical Reports Server (NTRS)
Douglass, R. W.; Meyer, M. P.; French, D. W.
1972-01-01
Criteria was established for practical remote sensing of vegetation stress and mortality caused by dwarf mistletoe infections in black spruce subboreal forest stands. The project was accomplished in two stages: (1) A fixed tower-tramway site in an infected black spruce stand was used for periodic multispectral photo coverage to establish basic film/filter/scale/season/weather parameters; (2) The photographic combinations suggested by the tower-tramway tests were used in low, medium, and high altitude aerial photography.
Geologic Reconnaissance and Lithologic Identification by Remote Sensing
remote sensing in geologic reconnaissance for purposes of tunnel site selection was studied further and a test case was undertaken to evaluate this geological application. Airborne multispectral scanning (MSS) data were obtained in May, 1972, over a region between Spearfish and Rapid City, South Dakota. With major effort directed toward the analysis of these data, the following geologic features were discriminated: (1) exposed rock areas, (2) five separate rock groups, (3) large-scale structures. This discrimination was accomplished by ratioing multispectral channels.
Wang, Kai; Franklin, Steven E.; Guo, Xulin; Cattet, Marc
2010-01-01
Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS). PMID:22163432
Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc
2010-01-01
Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).
Remote Sensing and Reflectance Profiling in Entomology.
Nansen, Christian; Elliott, Norman
2016-01-01
Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.
Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.; Jensen, John R.; Morain, Stanley A.; Walsh, Stephen J.; Ridd, Merrill K.
1999-01-01
Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.
Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment
NASA Technical Reports Server (NTRS)
Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa
2013-01-01
The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.
NASA Astrophysics Data System (ADS)
Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.
2018-04-01
Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.
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.
NASA Technical Reports Server (NTRS)
Musick, H. Brad
1993-01-01
The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.
Studies in remote sensing of Southern California and related environments
NASA Technical Reports Server (NTRS)
Bowden, L. W.
1971-01-01
A summary is presented of the research activities in southern California to determine whether meaningful geographic information was obtainable by use of remote sensing in an area already well documented or if the techniques and methodology could be transferred to related environments. Several broad characteristics of the regional geography were investigated with regards to their feasibility to be studied by aircraft and spacecraft sensors to improve the inventory and understanding of resources and environmental circumstances and to serve as models for future geographic analysis of other regions when using remote sensing devices. Sample activities are described in detail and three experiments producing worthwhile results are highlighted: mapping montane vegetation with color IR imagery, analysis of urban residual environment using color IR aerial photography, and regional agricultural land use mapping tested against color IR photography.
1993-01-01
during the agricultural season. Satellite remote sensing can contribute significantly to such a system by collecting information on crops and on...well as techniques to derive biophysical variables from remotely-sensed data. Finally, the integration of these remote - sensing techniques with crop
Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.
Wang, Jiao; Deng, Zhiqiang
2017-06-01
A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.
Method of determining forest production from remotely sensed forest parameters
Corey, J.C.; Mackey, H.E. Jr.
1987-08-31
A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.
2010-12-01
remote - sensing reflectance) can be highly inaccurate if a spectrally constant value is applied (although errors can be reduced by carefully filtering measured raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with results compared with those from remote sensing models and from direct measurements. The agreement from different determinations suggests that reasonable results for remote sensing reflectance of clear
2010-12-06
remote - sensing reflectance) can be highly inaccurate if a spectrally constant value is applied (although errors can be reduced by carefully filtering measured raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with results compared with those from remote sensing models and from direct measurements. The agreement from different determinations suggests that reasonable results for remote sensing reflectance of clear
Rocket engine exhaust plume diagnostics and health monitoring/management during ground testing
NASA Technical Reports Server (NTRS)
Chenevert, D. J.; Meeks, G. R.; Woods, E. G.; Huseonica, H. F.
1992-01-01
The current status of a rocket exhaust plume diagnostics program sponsored by NASA is reviewed. The near-term objective of the program is to enhance test operation efficiency and to provide for safe cutoff of rocket engines prior to incipient failure, thereby avoiding the destruction of the engine and the test complex and preventing delays in the national space program. NASA programs that will benefit from the nonintrusive remote sensed rocket plume diagnostics and related vehicle health management and nonintrusive measurement program are Space Shuttle Main Engine, National Launch System, National Aero-Space Plane, Space Exploration Initiative, Advanced Solid Rocket Motor, and Space Station Freedom. The role of emission spectrometry and other types of remote sensing in rocket plume diagnostics is discussed.
Remote sensing and eLearning 2.0 for school education
NASA Astrophysics Data System (ADS)
Voss, Kerstin; Goetzke, Roland; Hodam, Henryk
2010-10-01
The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.
Integration of Remote Sensing Data In Operational Flood Forecast In Southwest Germany
NASA Astrophysics Data System (ADS)
Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.
Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the project ESA's ENVISAT satellite, which will be launched in 2002, will serve as remote sensing data source. Until EN- VISAT data is available, algorithm retrieval, software development and product gener- ation is performed using existing sensors with ENVISAT-like specifications. Based on these data sets test cases and demonstration runs are conducted and will be presented to prove the advantages of the approach.
Remote sensing programs and courses in engineering and water resources
NASA Technical Reports Server (NTRS)
Kiefer, R. W.
1981-01-01
The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.
Remote sensing research in geographic education: An alternative view
NASA Technical Reports Server (NTRS)
Wilson, H.; Cary, T. K.; Goward, S. N.
1981-01-01
It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.
Research on assessment and improvement method of remote sensing image reconstruction
NASA Astrophysics Data System (ADS)
Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping
2018-01-01
Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.
Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management
USDA-ARS?s Scientific Manuscript database
Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...
Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan
2016-01-01
Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-08
... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and.... Abstract NOAA has established requirements for the licensing of private operators of remote-sensing space... Land Remote- Sensing Policy Act of 1992 and with the national security and international obligations of...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-24
... Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems AGENCY: National Oceanic and... for the licensing of private operators of remote-sensing space systems. The information in applications and subsequent reports is needed to ensure compliance with the Land Remote- Sensing Policy Act of...
Advancement of China’s Visible Light Remote Sensing Technology In Aerospace,
1996-03-19
Aerospace visible light film systems were among the earliest space remote sensing systems to be developed in China. They have been applied very well...makes China the third nation in the world to master space remote sensing technology, it also puts recoverable remote sensing satellites among the first
Polarimetric passive remote sensing of periodic surfaces
NASA Technical Reports Server (NTRS)
Veysoglu, Murat E.; Yueh, H. A.; Shin, R. T.; Kong, J. A.
1991-01-01
The concept of polarimetry in active remote sensing is extended to passive remote sensing. The potential use of the third and fourth Stokes parameters U and V, which play an important role in polarimetric active remote sensing, is demonstrated for passive remote sensing. It is shown that, by the use of the reciprocity principle, the polarimetric parameters of passive remote sensing can be obtained through the solution of the associated direct scattering problem. These ideas are applied to study polarimetric passive remote sensing of periodic surfaces. The solution of the direct scattering problem is obtained by an integral equation formulation which involves evaluation of periodic Green's functions and normal derivative of those on the surface. Rapid evaluation of the slowly convergent series associated with these functions is observed to be critical for the feasibility of the method. New formulas, which are rapidly convergent, are derived for the calculation of these series. The study has shown that the brightness temperature of the Stokes parameter U can be significant in passive remote sensing. Values as high as 50 K are observed for certain configurations.
From planets to crops and back: Remote sensing makes sense
NASA Astrophysics Data System (ADS)
Mustard, John F.
2017-04-01
Remotely sensed data and the instruments that acquire them are core parts of Earth and planetary observation systems. They are used to quantify the Earth's interconnected systems, and remote sensing is the only way to get a daily, or more frequent, snapshot of the status of the Earth. It really is the Earth's stethoscope. In a similar manner remote sensing is the rock hammer of the planetary scientist and the only way comprehensive data sets can be acquired. To risk offending many remotely sensed data acquired across the electromagnetic spectrum, it is the tricorder to explore known and unknown planets. Arriving where we are today in the use of remotely sensed data in the solar system has been a continually evolving synergy between Earth observation, planetary exploration, and fundamental laboratory work.
Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong
NASA Astrophysics Data System (ADS)
Huang, Yuhan; Organ, Bruce; Zhou, John L.; Surawski, Nic C.; Hong, Guang; Chan, Edward F. C.; Yam, Yat Shing
2018-06-01
Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.
Remote sensing of natural resources: Quarterly literature review
NASA Technical Reports Server (NTRS)
1976-01-01
A quarterly review of technical literature concerning remote sensing techniques is presented. The format contains indexed and abstracted materials with emphasis on data gathering techniques performed or obtained remotely from space, aircraft, or ground-based stations. Remote sensor applications including the remote sensing of natural resources are presented.
Long-range strategy for remote sensing: an integrated supersystem
NASA Astrophysics Data System (ADS)
Glackin, David L.; Dodd, Joseph K.
1995-12-01
Present large space-based remote sensing systems, and those planned for the next two decades, remain dichotomous and custom-built. An integrated architecture might reduce total cost without limiting system performance. An example of such an architecture, developed at The Aerospace Corporation, explores the feasibility of reducing overall space systems costs by forming a 'super-system' which will provide environmental, earth resources and theater surveillance information to a variety of users. The concept involves integration of programs, sharing of common spacecraft bus designs and launch vehicles, use of modular components and subsystems, integration of command and control and data capture functions, and establishment of an integrated program office. Smart functional modules that are easily tested and replaced are used wherever possible in the space segment. Data is disseminated to systems such as NASA's EOSDIS, and data processing is performed at established centers of expertise. This concept is advanced for potential application as a follow-on to currently budgeted and planned space-based remote sensing systems. We hope that this work will serve to engender discussion that may be of assistance in leading to multinational remote sensing systems with greater cost effectiveness at no loss of utility to the end user.
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
NASA Astrophysics Data System (ADS)
Diao, Chunyuan
In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.
Forest mensuration with remote sensing: A retrospective and a vision for the future
Randolph H. Wynne
2004-01-01
Remote sensing, while occasionally oversold, has clear potential to reduce the overall cost of traditional forest inventories. Perhaps most important, some of the information needed for more intensive, rather than extensive, forest management is available from remote sensing. These new information needs may justify increased use and the increased cost of remote sensing...
15 CFR 960.12 - Data policy for remote sensing space systems.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
Remote Sensing: Analyzing Satellite Images to Create Higher Order Thinking Skills.
ERIC Educational Resources Information Center
Marks, Steven K.; And Others
1996-01-01
Presents a unit that uses remote-sensing images from satellites and other spacecraft to provide new perspectives of the earth and generate greater global awareness. Relates the levels of Bloom's hierarchy to different aspects of the remote sensing unit to confirm that the concepts and principles of remote sensing and related images belong in…
15 CFR 960.12 - Data policy for remote sensing space systems.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
15 CFR 960.12 - Data policy for remote sensing space systems.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 15 Commerce and Foreign Trade 3 2012-01-01 2012-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
15 CFR 960.12 - Data policy for remote sensing space systems.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 15 Commerce and Foreign Trade 3 2014-01-01 2014-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
15 CFR 960.12 - Data policy for remote sensing space systems.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 15 Commerce and Foreign Trade 3 2013-01-01 2013-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...
Annotated bibliography of remote sensing methods for monitoring desertification
Walker, A.S.; Robinove, Charles J.
1981-01-01
Remote sensing techniques are valuable for locating, assessing, and monitoring desertification. Remotely sensed data provide a permanent record of the condition of the land in a format that allows changes in land features and condition to be measured. The annotated bibliography of 118 items discusses remote sensing methods that may be applied to desertification studies.
Applied Remote Sensing Program (ARSP)
NASA Technical Reports Server (NTRS)
Johnson, J. D.; Foster, K. E.; Mouat, D. A.; Miller, D. A.; Conn, J. S.
1976-01-01
The activities and accomplishments of the Applied Remote Sensing Program during FY 1975-1976 are reported. The principal objective of the Applied Remote Sensing Program continues to be designed projects having specific decision-making impacts as a principal goal. These projects are carried out in cooperation and collaboration with local, state and federal agencies whose responsibilities lie with planning, zoning and environmental monitoring and/or assessment in the application of remote sensing techniques. The end result of the projects is the use by the involved agencies of remote sensing techniques in problem solving.
Communicating remote sensing concepts in an interdisciplinary environment
NASA Technical Reports Server (NTRS)
Chung, R.
1981-01-01
Although remote sensing is currently multidisciplinary in its applications, many of its terms come from the engineering sciences, particularly from the field of pattern recognition. Scholars from fields such as the social sciences, botany, and biology, may experience initial difficulty with remote sensing terminology, even though parallel concepts exist in their own fields. Some parallel concepts and terminologies from nonengineering fields, which might enhance the understanding of remote sensing concepts in an interdisciplinary situation are identified. Feedbacks which this analogue strategy might have on remote sensing itself are explored.
People, Places and Pixels: Remote Sensing in the Service of Society
NASA Technical Reports Server (NTRS)
Lulla, Kamlesh
2003-01-01
What is the role of Earth remote sensing and other geospatial technologies in our society? Recent global events have brought into focus the role of geospatial science and technology such as remote sensing, GIS, GPS in assisting the professionals who are responsible for operations such as rescue and recovery of sites after a disaster or a terrorist act. This paper reviews the use of recent remote sensing products from satellites such as IKONOS in these efforts. Aerial and satellite imagery used in land mine detection has been evaluated and the results of this evaluation will be discussed. Synopsis of current and future ISS Earth Remote Sensing capabilities will be provided. The role of future missions in humanitarian use of remote sensing will be explored.
Development of a Near Ground Remote Sensing System
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
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.
30 CFR 57.22227 - Approved testing devices (I-A, I-B, I-C, II-A, II-B, III, IV, V-A, and V-B mines).
Code of Federal Regulations, 2010 CFR
2010-07-01
... be used in Subcategory I-C mines. (c)(1) If electrically powered, remote sensing devices are used.... (2) If air samples are delivered to remote analytical devices through sampling tubes, such tubes...
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.
The use of the Space Shuttle for land remote sensing
NASA Technical Reports Server (NTRS)
Thome, P. G.
1982-01-01
The use of the Space Shuttle for land remote sensing will grow significantly during the 1980's. The main use will be for general land cover and geological mapping purposes by worldwide users employing specialized sensors such as: high resolution film systems, synthetic aperture radars, and multispectral visible/IR electronic linear array scanners. Because these type sensors have low Space Shuttle load factors, the user's preference will be for shared flights. With this strong preference and given the present prognosis for Space Shuttle flight frequency as a function of orbit inclination, the strongest demand will be for 57 deg orbits. However, significant use will be made of lower inclination orbits. Compared with freeflying satellites, Space Shuttle mission investment requirements will be significantly lower. The use of the Space Shuttle for testing R and D land remote sensors will replace the free-flying satellites for most test programs.
Application of remote sensing to estimating soil erosion potential
NASA Technical Reports Server (NTRS)
Morris-Jones, D. R.; Kiefer, R. W.
1980-01-01
A variety of remote sensing data sources and interpretation techniques has been tested in a 6136 hectare watershed with agricultural, forest and urban land cover to determine the relative utility of alternative aerial photographic data sources for gathering the desired land use/land cover data. The principal photographic data sources are high altitude 9 x 9 inch color infrared photos at 1:120,000 and 1:60,000 and multi-date medium altitude color and color infrared photos at 1:60,000. Principal data for estimating soil erosion potential include precipitation, soil, slope, crop, crop practice, and land use/land cover data derived from topographic maps, soil maps, and remote sensing. A computer-based geographic information system organized on a one-hectare grid cell basis is used to store and quantify the information collected using different data sources and interpretation techniques. Research results are compared with traditional Universal Soil Loss Equation field survey methods.
NASA Technical Reports Server (NTRS)
Caldas, M.; Walker, R. T.; Shirota, R.; Perz, S.; Skole, D.
2003-01-01
This paper examines the relationships between the socio-demographic characteristics of small settlers in the Brazilian Amazon and the life cycle hypothesis in the process of deforestation. The analysis was conducted combining remote sensing and geographic data with primary data of 153 small settlers along the TransAmazon Highway. Regression analyses and spatial autocorrelation tests were conducted. The results from the empirical model indicate that socio-demographic characteristics of households as well as institutional and market factors, affect the land use decision. Although remotely sensed information is not very popular among Brazilian social scientists, these results confirm that they can be very useful for this kind of study. Furthermore, the research presented by this paper strongly indicates that family and socio-demographic data, as well as market data, may result in misspecification problems. The same applies to models that do not incorporate spatial analysis.
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.
Water supply studies. [management and planning of water supplies in California
NASA Technical Reports Server (NTRS)
Burgy, R. H.; Algazi, V. R.; Draeger, W. C.; Churchman, C. W.; Thomas, R. W.; Lauer, D. T.; Hoos, I.; Krumpe, P. F.; Nichols, J. D.; Gialdini, M. J.
1973-01-01
The primary test site for water supply investigations continues to be the Feather River watershed in northeastern California. This test site includes all of the area draining into and including the Oroville Reservoir. The principal effort is to determine the extent to which remote sensing techniques, when properly employed, can provide information useful to those persons concerned with the management and planning of lands and facilities for the production of water, using the Oroville Reservoir and the California Water Project as the focus for the study. In particular, emphasis is being placed on determining the cost effectiveness of information derived through remote sensing as compared with that currently being derived through more conventional means.
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.
1996-04-08
Development tasks and products of remote sensing ground stations in Europe are represented by the In-Sec Corporation and the Schlumberger Industries Corporation. The article presents the main products of these two corporations.
[Estimation of desert vegetation coverage based on multi-source remote sensing data].
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.
NASA Astrophysics Data System (ADS)
Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi
2017-01-01
Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.
An Approach of Registration between Remote Sensing Image and Electronic Chart Based on Coastal Line
NASA Astrophysics Data System (ADS)
Li, Ying; Yu, Shuiming; Li, Chuanlong
Remote sensing plays an important role marine oil spill emergency. In order to implement a timely and effective countermeasure, it is important to provide exact position of oil spills. Therefore it is necessary to match remote sensing image and electronic chart properly. Variance ordinarily exists between oil spill image and electronic chart, although geometric correction is applied to remote sensing image. It is difficult to find the steady control points on sea to make exact rectification of remote sensing image. An improved relaxation algorithm was developed for finding the control points along the coastline since oil spills occurs generally near the coast. A conversion function is created with the least square, and remote sensing image can be registered with the vector map based on this function. SAR image was used as the remote sensing data and shape format map as the electronic chart data. The results show that this approach can guarantee the precision of the registration, which is essential for oil spill monitoring.
The U.S. Geological Survey land remote sensing program
Saunders, T.; Feuquay, J.; Kelmelis, J.A.
2003-01-01
The U.S. Geological Survey has been a provider of remotely sensed information for decades. As the availability and use of satellite data has grown, USGS has placed increasing emphasis on expanding the knowledge about the science of remote sensing and on making remotely sensed data more accessible. USGS encourages widespread availability and distribution of these data and through its programs, encourages and enables a variety of research activities and the development of useful applications of the data. The science of remote sensing has great potential for assisting in the monitoring and assessment of the impacts of natural disasters, management and analysis of environmental, biological, energy, and mineral investigations, and supporting informed public policy decisions. By establishing the Land Remote Sensing Program (LRS) as a major unit of the USGS Geography Program, USGS has taken the next step to further increase support for the accessibility, understanding, and use of remotely sensed data. This article describes the LRS Program, its mission and objectives, and how the program has been structured to accomplish its goals.
NASA Astrophysics Data System (ADS)
Floyd, A.; Liljedahl, A. K.; Gens, R.; Prakash, A.; Mann, D. H.
2011-12-01
A combined use of remote sensing techniques, modeling and in-situ measurements is a pragmatic approach to study arctic hydrology, given the vastness, complexity, and logistical challenges posed by most arctic watersheds. Remote sensing techniques can provide tools to assess the geospatial variations that form the integrated response of a river system and therefore provide important details to study climate change effects on the remote arctic environment. The proposed study tests the applicability of remote sensing and modeling techniques to map, monitor and compare river temperatures and river break-up in the coastal and foothill sections of the Kuparak River, which is an intensely studied watershed. We co-registered about hundred synthetic aperture radar (SAR) images from RADARSAT-1, ERS-1 and ERS-2 satellites, acquired during the months of May through July for a period between 1999 and 2010. Co-registration involved a Fast Fourier Transform (FFT) match of amplitude images. The offsets were then applied to the radiometrically corrected SAR images, converted to dB values, to generate an image stack. We applied a mask to extract pixels representing only the river, and used an adaptive threshold to delineate open water from frozen areas. The variation in river break-up can be bracketed by defining open vs. frozen river conditions. Summer river surface water temperatures will be simulated through the well-established HEC-RAS hydrologic software package and validated with field measurements. The three-pronged approach of using remote sensing, modeling and field measurements demonstrated in this study can be adapted to work for other watersheds across the Arctic.
Remote sensing and field test capabilities at U.S. Army Dugway Proving Ground
NASA Astrophysics Data System (ADS)
Pearson, James T.; Herron, Joshua P.; Marshall, Martin S.
2011-11-01
U.S. Army Dugway Proving Ground (DPG) is a Major Range and Test Facility Base (MRTFB) with the mission of testing chemical and biological defense systems and materials. DPG facilities include state-of-the-art laboratories, extensive test grids, controlled environment calibration facilities, and a variety of referee instruments for required test measurements. Among these referee instruments, DPG has built up a significant remote sensing capability for both chemical and biological detection. Technologies employed for remote sensing include FTIR spectroscopy, UV spectroscopy, Raman-shifted eye-safe lidar, and other elastic backscatter lidar systems. These systems provide referee data for bio-simulants, chemical simulants, toxic industrial chemicals (TICs), and toxic industrial materials (TIMs). In order to realize a successful large scale open-air test, each type of system requires calibration and characterization. DPG has developed specific calibration facilities to meet this need. These facilities are the Joint Ambient Breeze Tunnel (JABT), and the Active Standoff Chamber (ASC). The JABT and ASC are open ended controlled environment tunnels. Each includes validation instrumentation to characterize simulants that are disseminated. Standoff systems are positioned at typical field test distances to measure characterized simulants within the tunnel. Data from different types of systems can be easily correlated using this method, making later open air test results more meaningful. DPG has a variety of large scale test grids available for field tests. After and during testing, data from the various referee instruments is provided in a visual format to more easily draw conclusions on the results. This presentation provides an overview of DPG's standoff testing facilities and capabilities, as well as example data from different test scenarios.
Remote sensing and field test capabilities at U.S. Army Dugway Proving Ground
NASA Astrophysics Data System (ADS)
Pearson, James T.; Herron, Joshua P.; Marshall, Martin S.
2012-05-01
U.S. Army Dugway Proving Ground (DPG) is a Major Range and Test Facility Base (MRTFB) with the mission of testing chemical and biological defense systems and materials. DPG facilities include state-of-the-art laboratories, extensive test grids, controlled environment calibration facilities, and a variety of referee instruments for required test measurements. Among these referee instruments, DPG has built up a significant remote sensing capability for both chemical and biological detection. Technologies employed for remote sensing include FTIR spectroscopy, UV spectroscopy, Raman-shifted eye-safe lidar, and other elastic backscatter lidar systems. These systems provide referee data for bio-simulants, chemical simulants, toxic industrial chemicals (TICs), and toxic industrial materials (TIMs). In order to realize a successful large scale open-air test, each type of system requires calibration and characterization. DPG has developed specific calibration facilities to meet this need. These facilities are the Joint Ambient Breeze Tunnel (JABT), and the Active Standoff Chamber (ASC). The JABT and ASC are open ended controlled environment tunnels. Each includes validation instrumentation to characterize simulants that are disseminated. Standoff systems are positioned at typical field test distances to measure characterized simulants within the tunnel. Data from different types of systems can be easily correlated using this method, making later open air test results more meaningful. DPG has a variety of large scale test grids available for field tests. After and during testing, data from the various referee instruments is provided in a visual format to more easily draw conclusions on the results. This presentation provides an overview of DPG's standoff testing facilities and capabilities, as well as example data from different test scenarios.
NASA Astrophysics Data System (ADS)
Schuerger, Andrew C.; Richards, Jeffrey T.
2006-09-01
Plant-based life support systems that utilize bioregenerative technologies have been proposed for long-term human missions to both the Moon and Mars. Bioregenerative life support systems will utilize higher plants to regenerate oxygen, water, and edible biomass for crews, and are likely to significantly lower the ‘equivalent system mass’ of crewed vehicles. As part of an ongoing effort to begin the development of an automatic remote sensing system to monitor plant health in bioregenerative life support modules, we tested the efficacy of seven artificial illumination sources on the remote detection of plant stresses. A cohort of pepper plants (Capsicum annuum L.) were grown 42 days at 25 °C, 70% relative humidity, and 300 μmol m-2 s-1 of photosynthetically active radiation (PAR; from 400 to 700 nm). Plants were grown under nutritional stresses induced by irrigating subsets of the plants with 100, 50, 25, or 10% of a standard nutrient solution. Reflectance spectra of the healthy and stressed plants were collected under seven artificial lamps including two tungsten halogen lamps, plus high pressure sodium, metal halide, fluorescent, microwave, and red/blue light emitting diode (LED) sources. Results indicated that several common algorithms used to estimate biomass and leaf chlorophyll content were effective in predicting plant stress under all seven illumination sources. However, the two types of tungsten halogen lamps and the microwave illumination source yielded linear models with the highest residuals and thus the highest predictive capabilities of all lamps tested. The illumination sources with the least predictive capabilities were the red/blue LEDs and fluorescent lamps. Although the red/blue LEDs yielded the lowest residuals for linear models derived from the remote sensing data, the LED arrays used in these experiments were optimized for plant productivity and not the collection of remote sensing data. Thus, we propose that if adjusted to optimize the collectio n of remote sensing information from plants, LEDs remain the best candidates for illumination sources for monitoring plant stresses in bioregenerative life support systems.
NASA Technical Reports Server (NTRS)
Yueh, Simon H.
2004-01-01
Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.
Online catalog access and distribution of remotely sensed information
NASA Astrophysics Data System (ADS)
Lutton, Stephen M.
1997-09-01
Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.
Remote Sensing and the Environment.
ERIC Educational Resources Information Center
Osmers, Karl
1991-01-01
Suggests using remote sensing technology to help students make sense of the natural world. Explains that satellite information allows observation of environmental changes over time. Identifies possible student projects based on remotely sensed data. Recommends obtaining the assistance of experts and seeking funding through effective project…
Wang, Teng; Shi, Qibin; Nikkhoo, Mehdi; Wei, Shengji; Barbot, Sylvain; Dreger, Douglas; Bürgmann, Roland; Motagh, Mahdi; Chen, Qi-Fu
2018-05-10
Surveillance of clandestine nuclear tests relies on a global seismic network, but the potential of spaceborne monitoring has been underexploited. Here, we determined the complete surface displacement field of up to 3.5 m of divergent horizontal motion with 0.5 m of subsidence associated with North Korea's largest underground nuclear test using satellite radar imagery. Combining insight from geodetic and seismological remote sensing, we found that the aftermath of the initial explosive deformation involved subsidence associated with sub-surface collapse and aseismic compaction of the damaged rocks of the test site. The explosive yield from the nuclear detonation with seismic modeling for 450m depth was between 120-304 kt of TNT equivalent. Our results demonstrate the capability of spaceborne remote sensing to help characterize large underground nuclear tests. Copyright © 2018, American Association for the Advancement of Science.
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.
Applications of remote sensing to watershed management
NASA Technical Reports Server (NTRS)
Rango, A.
1975-01-01
Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.
NASA Glenn OHIOVIEW FY01/02 Project
NASA Technical Reports Server (NTRS)
2003-01-01
The results of the research performed by the university principal investigators are herein compiled. OhioView's general goals were: 1) To increase remote sensing education for Ohio s undergraduate and graduate students, and also enhancing curriculum in the mathematics and science for K-12 students using the capabilities of remote sensing; 2) To conduct advanced research to develop novel remote sensing applications, i.e. to turn data into information for more applications; 3) To maximize the use of remote sensing technology by the general public through outreach and the development of tools for more user-friendly access to remote sensing data.
The availability of conventional forms of remotely sensed data
Sturdevant, James A.; Holm, Thomas M.
1982-01-01
For decades Federal and State agencies have been collecting aerial photographs of various film types and scales over parts of the United States. More recently, worldwide Earth resources data acquired by orbiting satellites have inundated the remote sensing community. Determining the types of remotely sensed data that are publicly available can be confusing to the land-resource manager, planner, and scientist. This paper is a summary of the more commonly used types of remotely sensed data (aircraft and satellite) and their public availability. Special emphasis is placed on the National High-Altitude Photography (NHAP) program and future remote-sensing satellites.
NASA Astrophysics Data System (ADS)
Subiyanto, Sawitri; Ramadhanis, Zainab; Baktiar, Aditya Hafidh
2018-02-01
One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.
NASA's Applied Remote Sensing Training (ARSET) Webinar Series
Atmospheric Science Data Center
2016-07-12
NASA's Applied Remote Sensing Training (ARSET) Webinar Series Tuesday, July 12, 2016 ... you of a free training opportunity: Introduction to Remote Sensing for Air Quality Applications Webinar Series Beginning in ...
Tropospheric Passive Remote Sensing
NASA Technical Reports Server (NTRS)
Keafer, L. S., Jr. (Editor)
1982-01-01
The long term role of airborne/spaceborne passive remote sensing systems for tropospheric air quality research and the identification of technology advances required to improve the performance of passive remote sensing systems were discussed.
Remote Sensing as a Demonstration of Applied Physics.
ERIC Educational Resources Information Center
Colwell, Robert N.
1980-01-01
Provides information about the field of remote sensing, including discussions of geo-synchronous and sun-synchronous remote-sensing platforms, the actual physical processes and equipment involved in sensing, the analysis of images by humans and machines, and inexpensive, small scale methods, including aerial photography. (CS)
NASA Technical Reports Server (NTRS)
Maxwell, E. L.
1980-01-01
The need for degree programs in remote sensing is considered. Any education program which claims to train remote sensing specialists must include expertise in the physical principles upon which remote sensing is based. These principles dictate the limits of engineering and design, computer analysis, photogrammetry, and photointerpretation. Faculty members must be hired to provide emphasis in those five areas.
Remote sensing of vegetation fires and its contribution to a fire management information system
Stephane P. Flasse; Simon N. Trigg; Pietro N. Ceccato; Anita H. Perryman; Andrew T. Hudak; Mark W. Thompson; Bruce H. Brockett; Moussa Drame; Tim Ntabeni; Philip E. Frost; Tobias Landmann; Johan L. le Roux
2004-01-01
In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then...
2016-07-15
AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a. CONTRACT NUMBER 5b. GRANT NUMBER... electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study
2016-07-15
AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a. CONTRACT NUMBER 5b. GRANT NUMBER...electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study
Basic Remote Sensing Investigations for Beach Reconnaissance.
Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in
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.
Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges
NASA Astrophysics Data System (ADS)
Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.
2014-12-01
Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.
Remote Sensing: A Film Review.
ERIC Educational Resources Information Center
Carter, David J.
1986-01-01
Reviews the content of 19 films on remote sensing published between 1973 and 1980. Concludes that they are overly simplistic, notably outdated, and generally too optimistic about the potential of remote sensing from space for resource exploration and environmental problem-solving. Provides names and addresses of more current remote sensing…
NASA Astrophysics Data System (ADS)
Labak, Peter; Sussman, Aviva; Rowlands, Aled; Chiappini, Massimo; Malich, Gregor; MacLeod, Gordon; Sankey, Peter; Sweeney, Jerry; Tuckwell, George
2016-04-01
The Integrated Field Exercise of 2014 (IFE14) was a field event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of a Comprehensive Test Ban Treaty's (CTBT) on-site inspection (OSI). During an OSI, up to 40 inspectors search a 1000km2 inspection area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of an OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams to execute the scenario in which the exercise was played, to those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, a number of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force Group (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, as well as other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection by other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.
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.
NASA Technical Reports Server (NTRS)
Savastano, K. J. (Principal Investigator); Pastula, E. J., Jr.; Woods, G.; Faller, K.
1974-01-01
The author has identified the following significant results. This investigation is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area in the northeastern Gulf of Mexico has made possible the identification of fisheries significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature, and turbidity have been inferred from aircraft sensor data. Cloud cover and delayed receipt have inhibited the use of Skylab data. The first step toward establishing the feasibility of utilizing remotely sensed data to assess amd monitor the distribution of ocean gamefish has been taken with the successful identification of fisheries significant oceanographic parameters and the demonstration of the capability of measuring most of these parameters remotely.
ERIC Educational Resources Information Center
Brosius, Craig A.; And Others
This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…
Microwave remote sensing of snowpack properties
NASA Technical Reports Server (NTRS)
Rango, A. (Editor)
1980-01-01
Topic concerning remote sensing capabilities for providing reliable snow cover data and measurement of snow water equivalents are discussed. Specific remote sensing technqiues discussed include those in the microwave region of the electromagnetic spectrum.
Commerical Remote Sensing Data Contract
,
2005-01-01
The U. S. Geological Survey's (USGS) Commercial Remote Sensing Data Contracts (CRSDCs) provide government agencies with access to a broad range of commercially available remotely sensed airborne and satellite data. These contracts were established to support The National Map partners, other Federal Civilian agency programs, and Department of Defense programs that require data for the United States and its territories. Experience shows that centralized procurement of remotely sensed data leads to considerable cost savings to the Federal government through volume discounts, reduction of redundant contract administrative costs, and avoidance of duplicate purchases. These contracts directly support the President's Commercial Remote Sensing Space Policy, signed in 2003, by providing a centralized mechanism for civil agencies to acquire commercial remote sensing products to support their mission needs in an efficient and coordinated way. CRSDC administration is provided by the USGS Mid-Continent Mapping Center in Rolla, Missouri.
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 .
2012-01-01
Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. PMID:22443452
Dambach, Peter; Machault, Vanessa; Lacaux, Jean-Pierre; Vignolles, Cécile; Sié, Ali; Sauerborn, Rainer
2012-03-23
The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. © 2012 Dambach et al; licensee BioMed Central Ltd.
The Use of Remote Sensing Satellites for Verification in International Law
NASA Astrophysics Data System (ADS)
Hettling, J. K.
The contribution is a very sensitive topic which is currently about to gain significance and importance in the international community. It implies questions of international law as well as the contemplation of new developments and decisions in international politics. The paper will begin with the meaning and current status of verification in international law as well as the legal basis of satellite remote sensing in international treaties and resolutions. For the verification part, this implies giving a definition of verification and naming its fields of application and the different means of verification. For the remote sensing part, it involves the identification of relevant provisions in the Outer Space Treaty and the United Nations General Assembly Principles on Remote Sensing. Furthermore it shall be looked at practical examples: in how far have remote sensing satellites been used to verify international obligations? Are there treaties which would considerably profit from the use of remote sensing satellites? In this respect, there are various examples which can be contemplated, such as the ABM Treaty (even though out of force now), the SALT and START Agreements, the Chemical Weapons Convention and the Conventional Test Ban Treaty. It will be mentioned also that NGOs have started to verify international conventions, e.g. Landmine Monitor is verifying the Mine-Ban Convention. Apart from verifying arms control and disarmament treaties, satellites can also strengthen the negotiation of peace agreements (such as the Dayton Peace Talks) and the prevention of international conflicts from arising. Verification has played an increasingly prominent role in high-profile UN operations. Verification and monitoring can be applied to the whole range of elements that constitute a peace implementation process, ranging from the military aspects through electoral monitoring and human rights monitoring, from negotiating an accord to finally monitoring it. Last but not least the problem of enforcing international obligations needs to be addressed, especially the dependence of international law on the will of political leaders and their respective national interests.
The detection and mapping of oil on a marshy area by a remote luminescent sensor
McFarlane, C.; Watson, R.D.
2005-01-01
Airborne remote sensing can be a cost-effective method for monitoring pollutants in large areas such as occur in oil spills. An opportunity to test a particular method arose when a well ruptured and for 23 days spewed a 90-meter fountain of oil into the air, dispersing the oil over a wide area. The method tested was an airborne luminescence detector with a Fraunhofer Line Discriminator (FLD) which was flown over the affected area 41 days after the well was capped to obtain a map or the deposition pattern. To calibrate the system, samples of Spartina (wire grass) and Phragmites (common reed) were collected from the contaminated area and the oil residues were eluted in cyclohexane and quantitatively analyzed in a fluorescence photometer. Good correlation was observed between the remote sensor (FLD) and the laboratory analysis. Isopleths defining the deposition pattern of oil were drawn from the remote sensing information. A discussion will be presented on the feasibility of using this instrument for similar contamination incidents for cleanup and damage assessment.
NASA Astrophysics Data System (ADS)
Song, Z. N.; Sui, H. G.
2018-04-01
High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.
Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion
Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G.; Sun, Mindy; Simard, Marc; Holmes, Richard
2012-01-01
Background Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level. PMID:22235254
Can we infer plant facilitation from remote sensing? A test across global drylands
Xu, Chi; Holmgren, Milena; Van Nes, Egbert H.; Maestre, Fernando T.; Soliveres, Santiago; Berdugo, Miguel; Kéfi, Sonia; Marquet, Pablo A.; Abades, Sebastian; Scheffer, Marten
2016-01-01
Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely-sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely-sensed images freely available through Google Earth™ with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely-sensed images were more right-skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth™ images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely-sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. PMID:26552256
Reliable clarity automatic-evaluation method for optical remote sensing images
NASA Astrophysics Data System (ADS)
Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen
2015-10-01
Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.
Rapid Assessment of Wave Height Transformation through a Tidal Inlet via Radar Remote Sensing
NASA Astrophysics Data System (ADS)
Díaz Méndez, G.; Haller, M. C.; Raubenheimer, B.; Elgar, S.; Honegger, D.
2014-12-01
Radar has the potential to enable temporally and spatially dense, continuous monitoring of waves and currents in nearshore environments. If quantitative relationships between the remote sensing signals and the hydrodynamic parameters of interest can be found, remote sensing techniques can mitigate the challenges of continuous in situ sampling and possibly enable a better understanding of wave transformation in areas with strongly inhomogeneous along and across-shore bathymetry, currents, and dissipation. As part of the DARLA experiment (New River Inlet, NC), the accuracy of a rapid assessment of wave height transformation via radar remote sensing is tested. Wave breaking events are identified in the radar image time series (Catalán et al. 2011). Once the total number of breaking waves (per radar collection) is mapped throughout the imaging domain, radar-derived bathymetry and wave frequency are used to compute wave breaking dissipation (Janssen and Battjes 2007). Given the wave breaking dissipation, the wave height transformation is calculated by finding an inverse solution to the 1D cross-shore energy flux equation (including the effect of refraction). The predicted wave height transformation is consistent (correlation R > 0.9 and rmse as low as 0.1 m) with the transformation observed with in situ sensors in an area of complex morphology and strong (> 1 m/s) tidal currents over a nine-day period. The wave forcing (i.e., radiation stress gradients) determined from the remote sensing methodology will be compared with values estimated with in situ sensors. Funded by ONR and ASD(R&E)
Mapping migratory bird prevalence using remote sensing data fusion.
Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard
2012-01-01
Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.
Experimental Sea Slicks in the Marsen (Maritime Remote Sensing) Exercise.
1980-10-30
Experimental slicks with various surface properties were generated in the North Sea as part of the MARSEN (Maritime Remote Sensing ) exercise. The one...with remote sensing instrumentation. Because of the numerous effects of surface films on air-sea interfacial processes, these experiments were designed...information was obtained on the influence of sea surface films on the interpretation of signals received by remote sensing systems. Criteria for the
SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS
The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was
Methods of Determining Playa Surface Conditions Using Remote Sensing
1987-10-08
NO. 11. TITLE (include Security Classification) METHODS OF DETERMINING PLAYA SURFACE CONDITIONS USING REMOTE SENSING 12. PERSONAL AUTHOR(S) J. PONDER...PLAYA SURFACE CONDITIONS USING REMOTE SENSING J. Ponder Henley U. S. Army Engineer Topographic Laboratories Fort Belvoir, Virginia 22060-5546 "ABSTRACT...geochemistry, hydrology and remote sensing but all of these are important to the understanding of these unique geomorphic features. There is a large body
NASA Technical Reports Server (NTRS)
Spiering, Bruce; Underwood, Lauren; Ellis, Chris; Lehrter, John; Hagy, Jim; Schaeffer, Blake
2010-01-01
The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.
An integrated use of topography with RSI in gully mapping, Shandong Peninsula, China.
He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo
2014-01-01
Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed.
An Integrated Use of Topography with RSI in Gully Mapping, Shandong Peninsula, China
He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo
2014-01-01
Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed. PMID:25302333
Unmanned Aerial Mass Spectrometer Systems for In-Situ Volcanic Plume Analysis
NASA Astrophysics Data System (ADS)
Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C. Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin
2015-02-01
Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models.
Unmanned aerial mass spectrometer systems for in-situ volcanic plume analysis.
Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin
2015-02-01
Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models.
Code of Federal Regulations, 2013 CFR
2013-01-01
... remote sensing satellite industry. (Available from NOAA, National Environmental Satellite Data and... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.1 Purpose. (a) The regulations in this part set... sensing space system under Title II of the Land Remote Sensing Policy Act of 1992 (15 U.S.C. 5601 et seq...
Code of Federal Regulations, 2011 CFR
2011-01-01
... remote sensing satellite industry. (Available from NOAA, National Environmental Satellite Data and... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.1 Purpose. (a) The regulations in this part set... sensing space system under Title II of the Land Remote Sensing Policy Act of 1992 (15 U.S.C. 5601 et seq...
Code of Federal Regulations, 2014 CFR
2014-01-01
... remote sensing satellite industry. (Available from NOAA, National Environmental Satellite Data and... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.1 Purpose. (a) The regulations in this part set... sensing space system under Title II of the Land Remote Sensing Policy Act of 1992 (15 U.S.C. 5601 et seq...
Code of Federal Regulations, 2012 CFR
2012-01-01
... remote sensing satellite industry. (Available from NOAA, National Environmental Satellite Data and... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.1 Purpose. (a) The regulations in this part set... sensing space system under Title II of the Land Remote Sensing Policy Act of 1992 (15 U.S.C. 5601 et seq...
Code of Federal Regulations, 2010 CFR
2010-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.1 Purpose. (a) The regulations in this part set... sensing space system under Title II of the Land Remote Sensing Policy Act of 1992 (15 U.S.C. 5601 et seq... remote sensing satellite industry. (Available from NOAA, National Environmental Satellite Data and...
Advanced Remote Sensing Research
Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna
2008-01-01
'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).
NASA Technical Reports Server (NTRS)
Zaitzeff, J. B. (Editor); Cornillon, P. (Editor); Aubrey, D. A. (Editor)
1980-01-01
Presentations were grouped in the following categories: (1) a technical orientation of Earth resources remote sensing including data sources and processing; (2) a review of the present status of remote sensing technology applicable to the coastal and marine environment; (3) a description of data and information needs of selected coastal and marine activities; and (4) an outline of plans for marine monitoring systems for the east coast and a concept for an east coast remote sensing facility. Also discussed were user needs and remote sensing potentials in the areas of coastal processes and management, commercial and recreational fisheries, and marine physical processes.
Remote sensing of Earth terrain
NASA Technical Reports Server (NTRS)
Kong, J. A.
1992-01-01
Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.
Brazil's remote sensing activities in the Eighties
NASA Technical Reports Server (NTRS)
Raupp, M. A.; Pereiradacunha, R.; Novaes, R. A.
1985-01-01
Most of the remote sensing activities in Brazil have been conducted by the Institute for Space Research (INPE). This report describes briefly INPE's activities in remote sensing in the last years. INPE has been engaged in research (e.g., radiance studies), development (e.g., CCD-scanners, image processing devices) and applications (e.g., crop survey, land use, mineral resources, etc.) of remote sensing. INPE is also responsible for the operation (data reception and processing) of the LANDSATs and meteorological satellites. Data acquisition activities include the development of CCD-Camera to be deployed on board the space shuttle and the construction of a remote sensing satellite.
Application of remote sensing to state and regional problems. [for Mississippi
NASA Technical Reports Server (NTRS)
Miller, W. F.; Bouchillon, C. W.; Harris, J. C.; Carter, B.; Whisler, F. D.; Robinette, R.
1974-01-01
The primary purpose of the remote sensing applications program is for various members of the university community to participate in activities that improve the effective communication between the scientific community engaged in remote sensing research and development and the potential users of modern remote sensing technology. Activities of this program are assisting the State of Mississippi in recognizing and solving its environmental, resource and socio-economic problems through inventory, analysis, and monitoring by appropriate remote sensing systems. Objectives, accomplishments, and current status of the following individual projects are reported: (1) bark beetle project; (2) state park location planning; and (3) waste source location and stream channel geometry monitoring.
Physics teaching by infrared remote sensing of vegetation
NASA Astrophysics Data System (ADS)
Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund
2018-05-01
Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.
Application of remote sensing to water resources problems
NASA Technical Reports Server (NTRS)
Clapp, J. L.
1972-01-01
The following conclusions were reached concerning the applications of remote sensing to water resources problems: (1) Remote sensing methods provide the most practical method of obtaining data for many water resources problems; (2) the multi-disciplinary approach is essential to the effective application of remote sensing to water resource problems; (3) there is a correlation between the amount of suspended solids in an effluent discharged into a water body and reflected energy; (4) remote sensing provides for more effective and accurate monitoring, discovery and characterization of the mixing zone of effluent discharged into a receiving water body; and (5) it is possible to differentiate between blue and blue-green algae.
Towards automatic lithological classification from remote sensing data using support vector machines
NASA Astrophysics Data System (ADS)
Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael
2010-05-01
Remote sensing data can be effectively used as a mean to build geological knowledge for poorly mapped terrains. Spectral remote sensing data from space- and air-borne sensors have been widely used to geological mapping, especially in areas of high outcrop density in arid regions. However, spectral remote sensing information by itself cannot be efficiently used for a comprehensive lithological classification of an area due to (1) diagnostic spectral response of a rock within an image pixel is conditioned by several factors including the atmospheric effects, spectral and spatial resolution of the image, sub-pixel level heterogeneity in chemical and mineralogical composition of the rock, presence of soil and vegetation cover; (2) only surface information and is therefore highly sensitive to the noise due to weathering, soil cover, and vegetation. Consequently, for efficient lithological classification, spectral remote sensing data needs to be supplemented with other remote sensing datasets that provide geomorphological and subsurface geological information, such as digital topographic model (DEM) and aeromagnetic data. Each of the datasets contain significant information about geology that, in conjunction, can potentially be used for automated lithological classification using supervised machine learning algorithms. In this study, support vector machine (SVM), which is a kernel-based supervised learning method, was applied to automated lithological classification of a study area in northwestern India using remote sensing data, namely, ASTER, DEM and aeromagnetic data. Several digital image processing techniques were used to produce derivative datasets that contained enhanced information relevant to lithological discrimination. A series of SVMs (trained using k-folder cross-validation with grid search) were tested using various combinations of input datasets selected from among 50 datasets including the original 14 ASTER bands and 36 derivative datasets (including 14 principal component bands, 14 independent component bands, 3 band ratios, 3 DEM derivatives: slope/curvatureroughness and 2 aeromagnetic derivatives: mean and variance of susceptibility) extracted from the ASTER, DEM and aeromagnetic data, in order to determine the optimal inputs that provide the highest classification accuracy. It was found that a combination of ASTER-derived independent components, principal components and band ratios, DEM-derived slope, curvature and roughness, and aeromagnetic-derived mean and variance of magnetic susceptibility provide the highest classification accuracy of 93.4% on independent test samples. A comparison of the classification results of the SVM with those of maximum likelihood (84.9%) and minimum distance (38.4%) classifiers clearly show that the SVM algorithm returns much higher classification accuracy. Therefore, the SVM method can be used to produce quick and reliable geological maps from scarce geological information, which is still the case with many under-developed frontier regions of the world.
SUPERFUND REMOTE SENSING SUPPORT
This task provides remote sensing technical support to the Superfund program. Support includes the collection, processing, and analysis of remote sensing data to characterize hazardous waste disposal sites and their history. Image analysis reports, aerial photographs, and assoc...
NASA Technical Reports Server (NTRS)
Brosius, C. A.; Gervin, J. C.; Ragusa, J. M.
1977-01-01
A text book on remote sensing, as part of the earth resources Skylab programs, is presented. The fundamentals of remote sensing and its application to agriculture, land use, geology, water and marine resources, and environmental monitoring are summarized.
Operational Use of Remote Sensing within USDA
NASA Technical Reports Server (NTRS)
Bethel, Glenn R.
2007-01-01
A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.
Investigation related to multispectral imaging systems
NASA Technical Reports Server (NTRS)
Nalepka, R. F.; Erickson, J. D.
1974-01-01
A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community.
Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.
Li, Linyi; Xu, Tingbao; Chen, Yun
2017-01-01
In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.
Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features
Xu, Tingbao; Chen, Yun
2017-01-01
In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440
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.
Method for Identifying Probable Archaeological Sites from Remotely Sensed Data
NASA Technical Reports Server (NTRS)
Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel
2011-01-01
Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.
NASA Astrophysics Data System (ADS)
Jaafar, H. H.; Ahmad, F. A.
2015-04-01
In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.
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.
Lidar system for air-pollution monitoring over urban areas
NASA Astrophysics Data System (ADS)
Moskalenko, Irina V.; Shcheglov, Djolinard A.; Molodtsov, Nikolai A.
1997-05-01
The atmospheric environmental situation over the urban area of a large city is determined by a complex combination of anthropogenic pollution and meteorological factors. The efficient way to provide three-dimensional mapping of gaseous pollutants over wide areas is utilization of lidar systems employing tunable narrowband transmitters. The paper presented describes activity of RRC 'Kurchatov Institute' in the field of lidar atmospheric monitoring. The project 'mobile remote sensing system based on tunable laser transmitter for environmental monitoring' is developed under financial support of International Scientific and Technology Center (Moscow). The objective of the project is design, construction and field testing of a DIAL-technique system. The lidar transmitter consists of an excimer laser pumping dye laser, BBO crystal frequency doubler, and scanning flat mirror. Sulfur dioxide and atomic mercury have been selected as pollutants for field tests of the lidar system under development. A recent large increase in Moscow traffic stimulated taking into consideration also the remote sensing of lower troposphere ozone because of the photochemical smog problem. The status of the project is briefly discussed. The current activity includes also collecting of environmental data relevant to lidar remote sensing. Main attention is paid to pollutant concentration levels over Moscow city and Moscow district areas.
Automated training site selection for large-area remote-sensing image analysis
NASA Astrophysics Data System (ADS)
McCaffrey, Thomas M.; Franklin, Steven E.
1993-11-01
A computer program is presented to select training sites automatically from remotely sensed digital imagery. The basic ideas are to guide the image analyst through the process of selecting typical and representative areas for large-area image classifications by minimizing bias, and to provide an initial list of potential classes for which training sites are required to develop a classification scheme or to verify classification accuracy. Reducing subjectivity in training site selection is achieved by using a purely statistical selection of homogeneous sites which then can be compared to field knowledge, aerial photography, or other remote-sensing imagery and ancillary data to arrive at a final selection of sites to be used to train the classification decision rules. The selection of the homogeneous sites uses simple tests based on the coefficient of variance, the F-statistic, and the Student's i-statistic. Comparisons of site means are conducted with a linear growing list of previously located homogeneous pixels. The program supports a common pixel-interleaved digital image format and has been tested on aerial and satellite optical imagery. The program is coded efficiently in the C programming language and was developed under AIX-Unix on an IBM RISC 6000 24-bit color workstation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pickles, W. L.; Ebrom, D. A.
This collaborative effort was in support of the CO 2 Capture Project (CCP), to develop techniques that integrate overhead images of plant species, plant health, geological formations, soil types, aquatic, and human use spatial patterns for detection and discrimination of any CO 2 releases from underground storage formations. The goal of this work was to demonstrate advanced hyperspectral geobotanical remote sensing methods to assess potential leakage of CO 2 from underground storage. The timeframes and scales relevant to the long-term storage of CO 2 in the subsurface make remote sensing methods attractive. Moreover, it has been shown that individual fieldmore » measurements of gas composition are subject to variability on extremely small temporal and spatial scales. The ability to verify ultimate reservoir integrity and to place individual surface measurements into context will be crucial to successful long-term monitoring and verification activities. The desired results were to produce a defined and tested procedure that could be easily used for long-term monitoring of possible CO 2 leakage from underground CO 2 sequestration sites. This testing standard will be utilized on behalf of the oil industry.« less
NASA Astrophysics Data System (ADS)
Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong
2015-03-01
A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.
NASA Astrophysics Data System (ADS)
Shuxin, Li; Zhilong, Zhang; Biao, Li
2018-01-01
Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.
NASA Astrophysics Data System (ADS)
Dell'Acqua, Fabio; Iannelli, Gianni Cristian; Kerekes, John; Lisini, Gianni; Moser, Gabriele; Ricardi, Niccolo; Pierce, Leland
2016-08-01
The issue of homogeneity in performance assessment of proposed algorithms for information extraction is generally perceived also in the Earth Observation (EO) domain. Different authors propose different datasets to test their developed algorithms and to the reader it is frequently difficult to assess which is better for his/her specific application, given the wide variability in test sets that makes pure comparison of e.g. accuracy values less meaningful than one would desire. With our work, we gave a modest contribution to ease the problem by making it possible to automatically distribute a limited set of possible "standard" open datasets, together with some ground truth info, and automatically assess processing results provided by the users.
Pre-Flight Radiometric Model of Linear Imager on LAPAN-IPB Satellite
NASA Astrophysics Data System (ADS)
Hadi Syafrudin, A.; Salaswati, Sartika; Hasbi, Wahyudi
2018-05-01
LAPAN-IPB Satellite is Microsatellite class with mission of remote sensing experiment. This satellite carrying Multispectral Line Imager for captured of radiometric reflectance value from earth to space. Radiometric quality of image is important factor to classification object on remote sensing process. Before satellite launch in orbit or pre-flight, Line Imager have been tested by Monochromator and integrating sphere to get spectral and every pixel radiometric response characteristic. Pre-flight test data with variety setting of line imager instrument used to see correlation radiance input and digital number of images output. Output input correlation is described by the radiance conversion model with imager setting and radiometric characteristics. Modelling process from hardware level until normalize radiance formula are presented and discussed in this paper.
A study of application of remote sensing to river forecasting. Volume 1: Executive summary
NASA Technical Reports Server (NTRS)
1975-01-01
A project is described whose goal was to define, implement and evaluate a pilot demonstration test to show the practicability of applying remotely sensed data to operational river forecasting in gaged or previously ungaged watersheds. A secondary objective was to provide NASA with documentation describing the computer programs that comprise the streamflow forecasting simulation model used. A computer-based simulation model was adapted to a streamflow forecasting application and implemented in an IBM System/360 Model 44 computer, operating in a dedicated mode, with operator interactive control through a Model 2250 keyboard/graphic CRT terminal. The test site whose hydrologic behavior was simulated is a small basin (365 square kilometers) designated Town Creek near Geraldine, Alabama.
Airborne multicamera system for geo-spatial applications
NASA Astrophysics Data System (ADS)
Bachnak, Rafic; Kulkarni, Rahul R.; Lyle, Stacey; Steidley, Carl W.
2003-08-01
Airborne remote sensing has many applications that include vegetation detection, oceanography, marine biology, geographical information systems, and environmental coastal science analysis. Remotely sensed images, for example, can be used to study the aftermath of episodic events such as the hurricanes and floods that occur year round in the coastal bend area of Corpus Christi. This paper describes an Airborne Multi-Spectral Imaging System that uses digital cameras to provide high resolution at very high rates. The software is based on Delphi 5.0 and IC Imaging Control's ActiveX controls. Both time and the GPS coordinates are recorded. Three successful test flights have been conducted so far. The paper present flight test results and discusses the issues being addressed to fully develop the system.
MEDSAT - A remote sensing satellite for malaria early warning and control
NASA Technical Reports Server (NTRS)
Vesecky, John; Slawski, James; Stottlemeyer, Bret; De La Sierra, Ruben; Daida, Jason; Wood, Byron; Lawless, James
1992-01-01
A remote sensing, medical satellite (MEDSAT) aids in the control of carrier (vector) borne disease. The prototype design is a light satellite to test for control of malaria. The design features a 340-kg satellite with visual/IR and SAR sensors in a low inclination orbit observing a number of worldwide test sites. The approach is to use four-band visual/IR and dual-polarized L-band SAR images obtained from MEDSAT in concert with in-situ data to estimate the temporal and spatial variations of malaria risk. This allows public health resources to focus on the most vulnerable areas at the appropriate time. It is concluded that a light-satellite design for a MEDSAT satellite with a Pegasus launch is feasible.
A remote sensing and GIS-enabled asset management system (RS-GAMS).
DOT National Transportation Integrated Search
2013-04-01
Under U.S. Department of Transportation (DOT) Commercial Remote Sensing and : Spatial Information (CRS&SI) Technology Initiative 2 of the Transportation : Infrastructure Construction and Condition Assessment, an intelligent Remote Sensing and : GIS-b...
ERIC Educational Resources Information Center
Williams, Richard S., Jr.; Southworth, C. Scott
1983-01-01
The Landsat Program became the major event of 1982 in geological remote sensing with the successful launch of Landsat 4. Other 1982 remote sensing accomplishments, research, publications, (including a set of Landsat worldwide reference system index maps), and conferences are highlighted. (JN)
2010-12-06
raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with...results compared with those from remote - sensing models and from direct measurements. The agreement from different determinations suggests that...reasonable results for remote sensing reflectance of clear blue water to turbid brown water are obtainable from above-surface measurements, even under conditions of high waves.
Bibliography of Remote Sensing Techniques Used in Wetland Research
1993-01-01
8217 is investigating the application of remote sensing technology for detecting changes in wetland environments. This report documents a bibliographic...search conducted as part of that work unit on applications of remote sensing techniques in wetland research. Results were used to guide research...efforts on the use of remote sensing technology for wetland change detection and assessment. The citations are presented in three appendixes, organized by wetland type, sensor type, and author.
Use of Openly Available Satellite Images for Remote Sensing Education
NASA Astrophysics Data System (ADS)
Wang, C.-K.
2011-09-01
With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.
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.
NASA Technical Reports Server (NTRS)
Sand, F.; Christie, R.
1975-01-01
Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.
Archimedean Witness: The Application of Remote Sensing as an Aid to Human Rights Prosecutions
NASA Astrophysics Data System (ADS)
Walker, James Robin
The 21st century has seen a significant increase in the use of remote sensing technology in the international human rights arena for the purposes of documenting crimes against humanity. The nexus between remote sensing, human rights activism, and international criminal prosecutions sits at a significant crossroads within geographic thought, calling attention to the epistemological and geopolitical implications that stem from the "view from nowhere" afforded by satellite imagery. Therefore, this thesis is divided into three sections. The first looks at the geographical questions raised by the expansion of remote sensing use in the context of international activism. The second explores the complications inherent in the presentation of remote sensing data as evidence of war crimes. Building upon the first two, the third section is a case study in alternate forms of analysis, aimed at expanding the utility of remote sensing data in international criminal prosecutions.
Sun, Zhong Yu; Chen, Yan Qiao; Yang, Long; Tang, Guang Liang; Yuan, Shao Xiong; Lin, Zhi Wen
2017-02-01
Low-altitude unmanned aerial vehicles (UAV) remote sensing system overcomes the deficiencies of space and aerial remote sensing system in resolution, revisit period, cloud cover and cost, which provides a novel method for ecological research on mesoscale. This study introduced the composition of UAV remote sensing system, reviewed its applications in species, population, community and ecosystem ecology research. Challenges and opportunities of UAV ecology were identified to direct future research. The promising research area of UAV ecology includes the establishment of species morphology and spectral characteristic data base, species automatic identification, the revelation of relationship between spectral index and plant physiological processes, three-dimension monitoring of ecosystem, and the integration of remote sensing data from multi resources and multi scales. With the development of UAV platform, data transformation and sensors, UAV remote sensing technology will have wide application in ecology research.
International Models and Methods of Remote Sensing Education and Training.
ERIC Educational Resources Information Center
Anderson, Paul S.
A classification of remote sensing courses throughout the world, the world-wide need for sensing instruction, and alternative instructional methods for meeting those needs are discussed. Remote sensing involves aerial photointerpretation or the use of satellite and other non-photographic imagery; its focus is to interpret what is in the photograph…
NASA Technical Reports Server (NTRS)
Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.
2007-01-01
This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities
Theme section for 36th International Symposium for Remote Sensing of the Environment in Berlin
NASA Astrophysics Data System (ADS)
Trinder, John; Waske, Björn
2016-09-01
The International Symposium for Remote Sensing of the Environment (ISRSE) is the longest series of international conferences held on the topic of Remote Sensing, commencing in Ann Arbor, Michigan USA in 1962. While the name of the conference has changed over the years, it is regularly held approximately every 2 years and continues to be one of the leading international conferences on remote sensing. The latest of these conferences, the 36th ISRSE, was held in Berlin, Germany from 11 to 15 May 2015. All complete papers from the conference are available in the ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences at http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/index.html.
THE REMOTE SENSING DATA GATEWAY
The EPA Remote Sensing Data Gateway (RSDG) is a pilot project in the National Exposure Research Laboratory (NERL) to develop a comprehensive data search, acquisition, delivery and archive mechanism for internal, national and international sources of remote sensing data for the co...
A remote sensing and GIS-enabled asset management system (RS-GAMS) : phase 2.
DOT National Transportation Integrated Search
2014-04-01
Under the U.S. Department of Transportation (DOT) Commercial Remote Sensing and Spatial : Information (CRS&SI) Technology Initiative 2 of the Transportation Infrastructure Construction : and Condition Assessment, an intelligent Remote Sensing and GIS...
Remote sensing applications program
NASA Technical Reports Server (NTRS)
1984-01-01
The activities of the Mississippi Remote Sensing Center are described in addition to technology transfer and information dissemination, remote sensing topics such as timber identification, water quality, flood prevention, land use, erosion control, animal habitats, and environmental impact studies are also discussed.
Remote Sensing Terminology in a Global and Knowledge-Based World
NASA Astrophysics Data System (ADS)
Kancheva, Rumiana
The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy, GIS, etc. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. The work on an English-Bulgarian Dictionary of Remote Sensing Terms is described including considerations on its scope, structure, information content, sellection of terms, and etc. The vision builds upon previous national and international experience and makes use of ongoing activities on the subject. Any interest in cooperation and initiating suchlike collaborative projects is welcome and highly appreciated.
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.
Natural Resource Information System, remote sensing studies
NASA Technical Reports Server (NTRS)
Leachtenauer, J.; Hirsch, R.; Williams, V.; Tucker, R.
1972-01-01
Potential applications of remote sensing data were reviewed, and available imagery was interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and qualities of imagery required to satisfy identified data needs. Ektachrome imagery available over the demonstration areas was reviewed to establish the feasibility of interpreting cultural features, range condition, and timber type. Using the same imagery, a land use map was prepared for the demonstration area. The feasibility of identifying commercial timber areas using a density slicing technique was tested on multispectral imagery available for a portion of the demonstration area.
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.
NASA Astrophysics Data System (ADS)
Su, Tengfei
2018-04-01
In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.
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.
NASA Technical Reports Server (NTRS)
Sukanek, Peter C.
2002-01-01
The NASA EPSCoR project in Mississippi involved investigations into three areas of interest to NASA by researchers at the four comprehensive universities in the state. These areas involved: (1) Noninvasive Flow Measurement Techniques, (2) Spectroscopic Exhaust Plume Measurements of Hydrocarbon Fueled Rocket Engines and (3) Integration of Remote Sensing and GIS data for Flood Forecasting on the Mississippi Gulf Coast. Each study supported a need at the Stennis Space Center in Mississippi. The first two addressed needs in rocket testing, and the third, in commercial remote sensing. Students from three of the institutions worked with researchers at Stennis Space Center on the projects.
Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis
NASA Technical Reports Server (NTRS)
Schoenwald, Adam; Kim, Seung-Jun; Mohammed-Tano, Priscilla
2017-01-01
Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interferece-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.
Radio Frequency Interference Detection for Passive Remote Sensing Using Eigenvalue Analysis
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Kim, Seung-Jun; Mohammed, Priscilla N.
2017-01-01
Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels. Simulated tests show that the proposed detector outperforms conventional kurtosis-based RFI detectors in the low-to-medium interference-to-noise-power-ratio (INR) regime under continuous wave (CW) and quadrature phase shift keying (QPSK) RFIs.
Some fundamental concepts in remote sensing
NASA Technical Reports Server (NTRS)
1982-01-01
The term remote sensing is defined as well as ideas such as class, pattern, feature, pattern recognition, feature extraction, and theme. The electromagnetic spectrum is examined especially those wavelength regions available to remote sensing. Relevant energy and wave propagation laws are discussed and the characteristics of emitted and reflected radiation and their detection are investigated. The identification of classes by their spectral signatures, the multispectral approach, and the principal types of sensors and platforms used in remote sensing are also considered.
NASA Astrophysics Data System (ADS)
Han, Xiuzhen; Ma, Jianwen; Bao, Yuhai
2006-12-01
Currently the function of operational locust monitor system mainly focused on after-hazards monitoring and assessment, and to found the way effectively to perform early warning and prediction has more practical meaning. Through 2001, 2002 two years continuously field sample and statistics for locusts eggs hatching, nymph growth, adults 3 phases observation, sample statistics and calculation, spectral measurements as well as synchronically remote sensing data processing we raise the view point of Remote Sensing three stage monitor the locust hazards. Based on the point of view we designed remote sensing monitor in three stages: (1) during the egg hitching phase remote sensing can retrieve parameters of land surface temperature (LST) and soil moisture; (2) during nymph growth phase locust increases appetite greatly and remote sensing can calculate vegetation index, leaf area index, vegetation cover and analysis changes; (3) during adult phase the locust move and assembly towards ponds and water ditches as well as less than 75% vegetation cover areas and remote sensing combination with field data can monitor and predicts potential areas for adult locusts to assembly. In this way the priority of remote sensing technology is elaborated effectively and it also provides technique support for the locust monitor system. The idea and techniques used in the study can also be used as reference for other plant diseases and insect pests.
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.
Characterization of Vegetation using the UC Davis Remote Sensing Testbed
NASA Astrophysics Data System (ADS)
Falk, M.; Hart, Q. J.; Bowen, K. S.; Ustin, S. L.
2006-12-01
Remote sensing provides information about the dynamics of the terrestrial biosphere with continuous spatial and temporal coverage on many different scales. We present the design and construction of a suite of instrument modules and network infrastructure with size, weight and power constraints suitable for small scale vehicles, anticipating vigorous growth in unmanned aerial vehicles (UAV) and other mobile platforms. Our approach provides the rapid deployment and low cost acquisition of high aerial imagery for applications requiring high spatial resolution and revisits. The testbed supports a wide range of applications, encourages remote sensing solutions in new disciplines and demonstrates the complete range of engineering knowledge required for the successful deployment of remote sensing instruments. The initial testbed is deployed on a Sig Kadet Senior remote controlled plane. It includes an onboard computer with wireless radio, GPS, inertia measurement unit, 3-axis electronic compass and digital cameras. The onboard camera is either a RGB digital camera or a modified digital camera with red and NIR channels. Cameras were calibrated using selective light sources, an integrating spheres and a spectrometer, allowing for the computation of vegetation indices such as the NDVI. Field tests to date have investigated technical challenges in wireless communication bandwidth limits, automated image geolocation, and user interfaces; as well as image applications such as environmental landscape mapping focusing on Sudden Oak Death and invasive species detection, studies on the impact of bird colonies on tree canopies, and precision agriculture.
Testing and Evaluation of the EOSDIS Core System: An ECS Science Advisor Proposal
NASA Technical Reports Server (NTRS)
Welch, Ronald M.; Christopher, Sundar A.
1997-01-01
The major goal of this project was to: 1) perform hands on testing of the evaluation packages, 2) provide feedback in the design of the EOSDIS Core System, and 3) test the effectiveness of the DAAC's by acquiring and testing remote sensing data sets.
Code of Federal Regulations, 2010 CFR
2010-01-01
... Committees prior to any release outside the Department. (6) Related to remote sensing. (i) Provide technical... satellite remote sensing activities to assure full consideration and evaluation of advanced technology. (ii) Coordinate administrative, management, and budget information relating to the Department's remote sensing...
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.
Estimating time available for sensor fusion exception handling
NASA Astrophysics Data System (ADS)
Murphy, Robin R.; Rogers, Erika
1995-09-01
In previous work, we have developed a generate, test, and debug methodology for detecting, classifying, and responding to sensing failures in autonomous and semi-autonomous mobile robots. An important issue has arisen from these efforts: how much time is there available to classify the cause of the failure and determine an alternative sensing strategy before the robot mission must be terminated? In this paper, we consider the impact of time for teleoperation applications where a remote robot attempts to autonomously maintain sensing in the presence of failures yet has the option to contact the local for further assistance. Time limits are determined by using evidential reasoning with a novel generalization of Dempster-Shafer theory. Generalized Dempster-Shafer theory is used to estimate the time remaining until the robot behavior must be suspended because of uncertainty; this becomes the time limit on autonomous exception handling at the remote. If the remote cannot complete exception handling in this time or needs assistance, responsibility is passed to the local, while the remote assumes a `safe' state. An intelligent assistant then facilitates human intervention, either directing the remote without human assistance or coordinating data collection and presentation to the operator within time limits imposed by the mission. The impact of time on exception handling activities is demonstrated using video camera sensor data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ye, Tianyu; Mani, R. G.; Wegscheider, W.
2013-11-04
A concurrent remote sensing and magneto-transport study of the microwave excited two dimensional electron system (2DES) at liquid helium temperatures has been carried out using a carbon detector to remotely sense the microwave activity of the 2D electron system in the GaAs/AlGaAs heterostructure during conventional magneto-transport measurements. Various correlations are observed and reported between the oscillatory magnetotransport and the remotely sensed reflection. In addition, the oscillatory remotely sensed signal is shown to exhibit a power law type variation in its amplitude, similar to the radiation-induced magnetoresistance oscillations.
NASA Astrophysics Data System (ADS)
Hobson, V. R.; Shervais, J. W.
2004-12-01
Developing a method to characterize the physical, chemical and temporal aspects of terrestrial volcanics is a necessary step toward studying volcanics on other planetary bodies. Volcanoes and flows close to populated centers have been studied to varying degree, but remote volcanics remain largely unstudied. Remotely sensed data and derived information can be used to select field sites on Earth and on other planets. Scientists studying volcanics in dangerous areas would benefit from as much advance knowledge of the area as possible before beginning fieldwork. By using satellites and other remote sensing methods, information about the eruptive history can be derived and potentially, the hazard these remote volcanic areas may pose to current and future generations can be estimated. Using Landsat TM, ASTER and other remotely sensed data, the extent and characteristics of lava flows can be examined, but verification and refinement of these methods requires collection of data on the ground. Young lava flows at Craters of the Moon National Park were selected to test methods for remote mapping of recent volcanics. These late Pleistocene to Holocene basalt flows have been mapped to 1:100,000 scale (Kuntz et al, 1988) and have only minor vegetative cover. A range of remotely sensed spectral images were combined to optimize recovery of the mapped flows. Major flow units can be distinguished from each other using unsupervised classification of Landsat TM Bands 1-7, but differentiation of flows within these units presents greater difficulty. Principal component analyses revealed that during the daytime, thermal infrared variations outweigh variations in all other bands. Larger-scale features were observed like edge effects attributable to changes in surface roughness or texture that might occur at flow fronts or at boundaries between flows. Using a digitized version of the geologic map, TM and ASTER data for individual flows were isolated and examined for changes with distance from the source vent or fissure. Several flows were selected for further examination in the field, based on accessibility and scientific interest.
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.
Sturdevant, J.A.
1981-01-01
The Earth Resources Observation Systems (EROS) Data Center (EDO, administered by the U.S. Geological Survey, U.S. Department of the Interior, provides remotely sensed data to the user community and offers a variety of professional services to further the understanding and use of remote sensing technology. EDC reproduces and sells photographic and electronic copies of satellite images of areas throughout the world. Other products include aerial photographs collected by 16 organizations, including the U.S. Geological Survey and the National Aeronautics and Space Administration. Primary users of the remotely sensed data are Federal, State, and municipal government agencies, universities, foreign nations, and private industries. The professional services available at EDC are primarily directed at integrating satellite and aircraft remote sensing technology into the programs of the Department of the Interior and its cooperators. This is accomplished through formal training workshops, user assistance, cooperative demonstration projects, and access to equipment and capabilities in an advanced data analysis laboratory. In addition, other Federal agencies, State and local governments, universities, and the general public can get assistance from the EDC Staff. Since 1973, EDC has contributed to the accelerating growth in development and operational use of remotely sensed data for land resource problems through its role as educator and by conducting basic and applied remote sensing applications research. As remote sensing technology continues to evolve, EDC will continue to respond to the increasing demand for timely information on remote sensing applications. Questions most often asked about EDC's research and training programs include: Who may attend an EDC remote sensing training course? Specifically, what is taught? Who may cooperate with EDC on remote sensing projects? Are interpretation services provided on a service basis? This report attempts to define the goals and objectives of and policies on the following EDC services: Training Program.User Assistance.Data Analysis Laboratory.Cooperative Demonstration Projects.Research Projects.
Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook.
Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Raso, Giovanna; Utzinger, Jürg
2015-03-17
Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions. We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised. We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from. Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.
NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing
NASA Technical Reports Server (NTRS)
Chirayath, Ved
2018-01-01
We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.
Online Remote Sensing Interface
NASA Technical Reports Server (NTRS)
Lawhead, Joel
2007-01-01
BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.
What is a picture worth? A history of remote sensing
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.
NASA Astrophysics Data System (ADS)
Palumbo, Gaetano; Powlesland, Dominic
1996-12-01
The Getty Conservation Institute is exploring the feasibility of using remote sensing associated with a geographic database management system (GDBMS) in order to provide archaeological and historic site managers with sound evaluations of the tools available for site and information management. The World Heritage Site of Chaco Canyon, New Mexico, a complex of archeological sites dating to the 10th to the 13th centuries AD, was selected as a test site. Information from excavations conducted there since the 1930s, and a range of documentation generated by the National Park Service was gathered. NASA's John C. Stennis Space Center contributed multispectral data of the area, and the Jet Propulsion Laboratory contributed data from ATLAS (airborne terrestrial applications sensor) and CAMS (calibrated airborne multispectral scanner) scanners. Initial findings show that while 'automatic monitoring systems' will probably never be a reality, with careful comparisons of historic and modern photographs, and performing digital analysis of remotely sensed data, excellent results are possible.
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.
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.
NASA Astrophysics Data System (ADS)
Bruggemann, Lena; Bach, Heike; Ruf, Tobias; Appel, Florian; Migdall, Silke; Hank, Tobias; Mauser, Wolfram; Eiblmeier, Peter
2016-08-01
The central topic of this study is the monitoring of winter wheat phenology and the detection of anthesis (flowering) using remotely sensed data as well as crop growth modeling. It is not possible to directly observe the flowering of wheat with optical satellite sensors. Thus, an approach that combines crop growth modeling with remote sensing data covering optical and microwave spectral ranges was developed. This was done in three steps: The hydro-agroecological land surface model PROMET was first run in a stand-alone version for selected sites distributed throughout Bavaria using only static input parameters (e.g. soil map) and current meteorological data as driving factors. Thus, multitemporal information from optical remote sensing data was assimilated into the model runs in a second step to improve the accuracy of the results. Finally, the use of radar data for anthesis detection in winter wheat was tested using Sentinel-1 data of 2015 in dual polarization mode (VV+VH).
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.
Exploring Remote Rensing Through The Use Of Readily-Available Classroom Technologies
NASA Astrophysics Data System (ADS)
Rogers, M. A.
2013-12-01
Frontier geoscience research using remotely-sensed satellite observation routinely requires sophisticated and novel remote sensing techniques to succeed. Describing these techniques in an educational format presents significant challenges to the science educator, especially with regards to the professional development setting where a small, but competent audience has limited instructor contact time to develop the necessary understanding. In this presentation, we describe the use of simple and cheaply available technologies, including ultrasonic transducers, FLIR detectors, and even simple web cameras to provide a tangible analogue to sophisticated remote sensing platforms. We also describe methods of curriculum development that leverages the use of these simple devices to teach the fundamentals of remote sensing, resulting in a deeper and more intuitive understanding of the techniques used in modern remote sensing research. Sample workshop itineraries using these techniques are provided as well.
NASA Technical Reports Server (NTRS)
Roller, N. E. G.
1977-01-01
The concept of using remote sensing to inventory wetlands and the related topics of proper inventory design and data collection are discussed. The material presented shows that aerial photography is the form of remote sensing from which the greatest amount of wetlands information can be derived. For extensive, general-purpose wetlands inventories, however, the use of LANDSAT data may be more cost-effective. Airborne multispectral scanners and radar are, in the main, too expensive to use - unless the information that these sensors alone can gather remotely is absolutely required. Multistage sampling employing space and high altitude remote sensing data in the initial stages appears to be an efficient survey strategy for gathering non-point specific wetlands inventory data over large areas. The operational role of remote sensing insupplying inventory data for application to several typical wetlands management problems is illustrated by summary descriptions of past ERIM projects.
NASA Technical Reports Server (NTRS)
Byrnes, Ray
2007-01-01
A general overview of the USGS land remote sensing program is presented. The contents include: 1) Brief overview of USGS land remote sensing program; 2) Highlights of JACIE work at USGS; 3) Update on NASA/USGS Landsat Data Continuity Mission; and 4) Notes on alternative data sources.
Hydrological Application of Remote Sensing: Surface States -- Snow
NASA Technical Reports Server (NTRS)
Hall, Dorothy K.; Kelly, Richard E. J.; Foster, James L.; Chang, Alfred T. C.
2004-01-01
Remote sensing research of snow cover has been accomplished for nearly 40 years. The use of visible, near-infrared, active and passive-microwave remote sensing for the analysis of snow cover is reviewed with an emphasis on the work on the last decade.
Remote sensing education in NASA's technology transfer program
NASA Technical Reports Server (NTRS)
Weinstein, R. H.
1981-01-01
Remote sensing is a principal focus of NASA's technology transfer program activity with major attention to remote sensing education the Regional Program and the University Applications Program. Relevant activities over the past five years are reviewed and perspective on future directions is presented.
Analysis of Coastal Dunes: A Remote Sensing and Statistical Approach.
ERIC Educational Resources Information Center
Jones, J. Richard
1985-01-01
Remote sensing analysis and statistical methods were used to analyze the coastal dunes of Plum Island, Massachusetts. The research methodology used provides an example of a student project for remote sensing, geomorphology, or spatial analysis courses at the university level. (RM)
7 CFR 2.72 - Chairman, World Agricultural Outlook Board.
Code of Federal Regulations, 2010 CFR
2010-01-01
... Commodity Estimates Committees prior to any release outside the Department. (4) Related to remote sensing..., developing, and carrying out satellite remote sensing activities to assure full consideration and evaluation... to the Department's remote sensing activities including: (A) Inter- and intra-agency meetings...
Remote sensing and reflectance profiling in entomology
USDA-ARS?s Scientific Manuscript database
Remote sensing is about characterizing the status of objects and/or classifies their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be ground-based, and therefore acquired at a high spatial resolutio...
Planning and Implementation of Remote Sensing Experiments.
Contents: TEKTITE II experiment-upwelling detection (NASA Mx 138); Design of oceanographic experiments (Gulf of Mexico, Mx 159); Design of oceanographic experiments (Gulf of Mexico, Mx 165); Experiments on thermal pollution; Remote sensing newsletter; Symposium on remote sensing in marine biology and fishery resources.
Ionospheric Profiles from Ultraviolet Remote Sensing
1997-09-30
The long-term goal of this project is to obtain ionospheric profiles from ultraviolet remote sensing of the ionosphere from orbiting space platforms... Remote sensing of the nighttime ionosphere is a more straightforward process because of the absence of the complications brought about by daytime
The hydrology of prehistoric farming systems in a central Arizona ecotone
NASA Technical Reports Server (NTRS)
Gumerman, G. J.; Hanson, J. A.; Brew, D.; Tomoff, K.; Weed, C. S.
1975-01-01
The prehistoric land use and water management in the semi-arid Southwest was examined. Remote sensing data, geology, hydrology and biology are discussed along with an evaluation of remote sensing contributions, recommendations for applications, and proposed future remote sensing studies.
NASA Technical Reports Server (NTRS)
Hidalgo, J. U.
1975-01-01
The applicability of remote sensing to transportation and traffic analysis, urban quality, and land use problems is discussed. Other topics discussed include preliminary user analysis, potential uses, traffic study by remote sensing, and urban condition analysis using ERTS.
Multi-scale remote sensing of coral reefs
Andréfouët, Serge; Hochberg, E.J.; Chevillon, Christophe; Muller-Karger, Frank E.; Brock, John C.; Hu, Chuanmin
2005-01-01
In this chapter we present how both direct and indirect remote sensing can be integrated to address two major coral reef applications - coral bleaching and assessment of biodiversity. This approach reflects the current non-linear integration of remote sensing for environmental assessment of coral reefs, resulting from a rapid increase in available sensors, processing methods and interdisciplinary collaborations (Andréfouët and Riegl, 2004). Moreover, this approach has greatly benefited from recent collaborations of once independent investigations (e.g., benthic ecology, remote sensing, and numerical modeling).
NASA Technical Reports Server (NTRS)
Philipson, W. R. (Principal Investigator)
1983-01-01
Built on Cornell's thirty years of experience in aerial photographic studies, the NASA-sponsored remote sensing program strengthened instruction and research in remote sensing, established communication links within and beyond the university community, and conducted research projects for or with town, county, state, federal, and private organizations in New York State. The 43 completed applied research projects are listed as well as 13 spinoff grants/contracts. The curriculum offered, consultations provided, and data processing facilities available are described. Publications engendered are listed including the thesis of graduates in the remote sensing program.
NASA Technical Reports Server (NTRS)
Seinfeld, J. H. (Principal Investigator)
1982-01-01
The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed.
NASA Technical Reports Server (NTRS)
Seinfeld, J. H. (Principal Investigator)
1982-01-01
The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.
NASA Technical Reports Server (NTRS)
Polhemus, J. T.
1980-01-01
Five troublesome insect pest groups were chosen for study. These represent a broad spectrum of life cycles, ecological indicators, pest management strategies, and remote sensing requirements. Background data, and field study results for each of these subjects is discussed for each insect group. Specific groups studied include tsetse flies, locusts, western rangeland grasshoppers, range caterpillars, and mosquitoes. It is concluded that remote sensing methods are aplicable to the pest management of the insect groups studied.
Searches over graphs representing geospatial-temporal remote sensing data
Brost, Randolph; Perkins, David Nikolaus
2018-03-06
Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.
Antarctic Tabular Iceberg A-24 Movement and Decay Via Satellite Remote Sensing
1993-04-02
Austraia. Pulished by ft Amencan Meteormogicat Society. Bost:o, MA. P7.27 ANTARCTIC TABULAR ICEBERG A-24 MOVEMENT AND DECAY VIA SATELLITE REMOTE SENSING AD...2. REMOTE SENSING DATA SOURCES 85 GHz imagery verified that the iceberg began to indicate more than The vis/IR imagery from the one berg existed in...SSM/I Instrument Evaluation, conditions. The corresponding IR data IEEE Trans. Geosci. Remote Sensing , was also of particular interest due Vol. 28, pp
Coastal Remote Sensing Investigations. Volume 2. Beach Environment
1980-12-01
1 ’ "■"’.."■•■.» ■ a .1 "llpll CO Ifi o Q- O CO I y Final Report COASTAL REMOTE SENSING INVESTIGATIONS VOLUME 2: BEACH... Remote Sensing Grain Size Soil Moisture Soil Mineralogy Multispectral Scanner iO AUTNACT fCHtfÜBB on merit nJt ij ntinwin and idmlify In hloti...The work reported herein summarizes the final research activity in the Beach Environment Task of a program at ERIM entitled "Coastal Remote Sensing Investigations
Radar Remote Sensing of Waves and Currents in the Nearshore Zone
2006-01-01
and application of novel microwave, acoustic, and optical remote sensing techniques. The objectives of this effort are to determine the extent to which...Doppler radar techniques are useful for nearshore remote sensing applications. Of particular interest are estimates of surf zone location and extent...surface currents, waves, and bathymetry. To date, optical (video) techniques have been the primary remote sensing technology used for these applications. A key advantage of the radar is its all weather day-night operability.
Emergence of the Green’s Functions from Noise and Passive Acoustic Remote Sensing of Ocean Dynamics
2009-09-30
Acoustic Remote Sensing of Ocean Dynamics Oleg A. Godin CIRES/Univ. of Colorado and NOAA/OAR/Earth System Research Lab., R/PSD99, 325 Broadway...characterization of a time-varying ocean where ambient acoustic noise is utilized as a probing signal. • To develop a passive remote sensing technique for...inapplicable. 3. To quantify degradation of performance of passive remote sensing techniques due to ocean surface motion and other variations of underwater
Active and Passive Remote Sensing of Ice
1993-01-26
92 4. TITLE AND SUBTITLE S. FUNDING NUMBERS Active and Passive Remote Sensing of Ice NO0014-89-J-l 107 6. AUTHOR(S) 425f023-08 Prof. J.A. Kong 7... REMOTE SENSING OF ICE Sponsored by: Department of the Navy Office of Naval Research Contract number: N00014-89-J-1107 Research Organization: Center for...J. A. Kong Period covered: October 1, 1988 - November 30, 1992 St ACTIVE AND PASSIVE REMOTE SENSING OF ICE FINAL REPORT This annual report covers
Remote Sensing For Water Resources And Hydrology. Recommended research emphasis for the 1980's
NASA Technical Reports Server (NTRS)
1980-01-01
The problems and the areas of activity that the Panel believes should be emphasized in work on remote sensing for water resources and hydrology in the 1980's are set forth. The Panel deals only with those activities and problems in water resources and hydrology that the Panel considers important, and where, in the Panel's opinion, application of current remote sensing capability or advancements in remote sensing capability can help meet urgent problems and provide large returns in practical benefits.
Research on Method of Interactive Segmentation Based on Remote Sensing Images
NASA Astrophysics Data System (ADS)
Yang, Y.; Li, H.; Han, Y.; Yu, F.
2017-09-01
In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.
Yang, Ke; Peretz-Soroka, Hagit; Liu, Yong; Lin, Francis
2016-03-21
Portable electronic devices and wireless communication systems enable a broad range of applications such as environmental and food safety monitoring, personalized medicine and healthcare management. Particularly, hybrid smartphone and microfluidic devices provide an integrated solution for the new generation of mobile sensing applications. Such mobile sensing based on microfluidic devices (broadly defined) and smartphones (MS(2)) offers a mobile laboratory for performing a wide range of bio-chemical detection and analysis functions such as water and food quality analysis, routine health tests and disease diagnosis. MS(2) offers significant advantages over traditional platforms in terms of test speed and control, low cost, mobility, ease-of-operation and data management. These improvements put MS(2) in a promising position in the fields of interdisciplinary basic and applied research. In particular, MS(2) enables applications to remote in-field testing, homecare, and healthcare in low-resource areas. The marriage of smartphones and microfluidic devices offers a powerful on-chip operating platform to enable various bio-chemical tests, remote sensing, data analysis and management in a mobile fashion. The implications of such integration are beyond telecommunication and microfluidic-related research and technology development. In this review, we will first provide the general background of microfluidic-based sensing, smartphone-based sensing, and their integration. Then, we will focus on several key application areas of MS(2) by systematically reviewing the important literature in each area. We will conclude by discussing our perspectives on the opportunities, issues and future directions of this emerging novel field.
Novel Developments of Mobile Sensing Based on the Integration of Microfluidic Devices and Smartphone
Yang, Ke; Peretz-Soroka, Hagit; Liu, Yong; Lin, Francis
2016-01-01
Portable electronic devices and wireless communication systems enable a broad range of applications such as environmental and food safety monitoring, personalized medicine and healthcare management. Particularly, hybrid smartphone and microfluidic devices provide an integrated solution for the new generation of mobile sensing applications. Such mobile sensing based on microfluidic devices (broadly defined) and smartphones (MS2) offers a mobile laboratory for performing a wide range of bio-chemical detection and analysis functions such as water and food quality analysis, routine health tests and disease diagnosis. MS2 offers significant advantages over traditional platforms in terms of test speed and control, low cost, mobility, ease-of-operation and data management. These improvements put MS2 in a promising position in the fields of interdisciplinary basic and applied research. In particular, MS2 enables applications to remote infield testing, homecare, and healthcare in low-resource areas. The marriage of smartphones and microfluidic devices offers a powerful on-chip operating platform to enable various bio-chemical tests, remote sensing, data analysis and management in a mobile fashion. The implications of such integration are beyond telecommunication and microfluidic-related research and technology development. In this review, we will first provide the general background of microfluidic-based sensing, smartphone-based sensing, and their integration. Then, we will focus on several key application areas of MS2 by systematically reviewing the important literature in each area. We will conclude by discussing our perspectives on the opportunities, issues and future directions of this emerging novel field. PMID:26899264
Nonlinear Photonic Systems for V- and W-Band Antenna Remoting Applications
2016-10-22
for commercial, academic, and military purposes delivering microwaves through fibers to remote areas for wireless sensing , imaging, and detection...academic, and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and...and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and detection
First results of ground-based LWIR hyperspectral imaging remote gas detection
NASA Astrophysics Data System (ADS)
Zheng, Wei-jian; Lei, Zheng-gang; Yu, Chun-chao; Wang, Hai-yang; Fu, Yan-peng; Liao, Ning-fang; Su, Jun-hong
2014-11-01
The new progress of ground-based long-wave infrared remote sensing is presented. The LWIR hyperspectral imaging by using the windowing spatial and temporal modulation Fourier spectroscopy, and the results of outdoor ether gas detection, verify the features of LWIR hyperspectral imaging remote sensing and technical approach. It provides a new technical means for ground-based gas remote sensing.
Study on paddy rice yield estimation based on multisource data and the Grey system theory
NASA Astrophysics Data System (ADS)
Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua
2009-10-01
The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.
Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea.
Simis, Stefan G H; Ylöstalo, Pasi; Kallio, Kari Y; Spilling, Kristian; Kutser, Tiit
2017-01-01
Optical-biogeochemical relationships of particulate and dissolved organic matter are presented in support of remote sensing of the Baltic Sea pelagic. This system exhibits strong seasonality in phytoplankton community composition and wide gradients of chromophoric dissolved organic matter (CDOM), properties which are poorly handled by existing remote sensing algorithms. Absorption and scattering properties of particulate matter reflected the seasonality in biological (phytoplankton succession) and physical (thermal stratification) processes. Inherent optical properties showed much wider variability when normalized to the chlorophyll-a concentration compared to normalization to either total suspended matter dry weight or particulate organic carbon. The particle population had the largest optical variability in summer and was dominated by organic matter in both seasons. The geographic variability of CDOM and relationships with dissolved organic carbon (DOC) are also presented. CDOM dominated light absorption at blue wavelengths, contributing 81% (median) of the absorption by all water constituents at 400 nm and 63% at 442 nm. Consequentially, 90% of water-leaving radiance at 412 nm originated from a layer (z90) no deeper than approximately 1.0 m. With water increasingly attenuating light at longer wavelengths, a green peak in light penetration and reflectance is always present in these waters, with z90 up to 3.0-3.5 m depth, whereas z90 only exceeds 5 m at biomass < 5 mg Chla m-3. High absorption combined with a weakly scattering particle population (despite median phytoplankton biomass of 14.1 and 4.3 mg Chla m-3 in spring and summer samples, respectively), characterize this sea as a dark water body for which dedicated or exceptionally robust remote sensing techniques are required. Seasonal and regional optical-biogeochemical models, data distributions, and an extensive set of simulated remote-sensing reflectance spectra for testing of remote sensing algorithms are provided as supplementary data.
Modeling Atmospheric CO2 Processes to Constrain the Missing Sink
NASA Technical Reports Server (NTRS)
Kawa, S. R.; Denning, A. S.; Erickson, D. J.; Collatz, J. C.; Pawson, S.
2005-01-01
We report on a NASA supported modeling effort to reduce uncertainty in carbon cycle processes that create the so-called missing sink of atmospheric CO2. Our overall objective is to improve characterization of CO2 source/sink processes globally with improved formulations for atmospheric transport, terrestrial uptake and release, biomass and fossil fuel burning, and observational data analysis. The motivation for this study follows from the perspective that progress in determining CO2 sources and sinks beyond the current state of the art will rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. The major components of this effort are: 1) Continued development of the chemistry and transport model using analyzed meteorological fields from the Goddard Global Modeling and Assimilation Office, with comparison to real time data in both forward and inverse modes; 2) An advanced biosphere model, constrained by remote sensing data, coupled to the global transport model to produce distributions of CO2 fluxes and concentrations that are consistent with actual meteorological variability; 3) Improved remote sensing estimates for biomass burning emission fluxes to better characterize interannual variability in the atmospheric CO2 budget and to better constrain the land use change source; 4) Evaluating the impact of temporally resolved fossil fuel emission distributions on atmospheric CO2 gradients and variability. 5) Testing the impact of existing and planned remote sensing data sources (e.g., AIRS, MODIS, OCO) on inference of CO2 sources and sinks, and use the model to help establish measurement requirements for future remote sensing instruments. The results will help to prepare for the use of OCO and other satellite data in a multi-disciplinary carbon data assimilation system for analysis and prediction of carbon cycle changes and carbodclimate interactions.
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.
Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.
2015-01-01
The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.
NASA Astrophysics Data System (ADS)
Chen, Xuelong; Su, Bob
2017-04-01
Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.
Research Status and Development Trend of Remote Sensing in China Using Bibliometric Analysis
NASA Astrophysics Data System (ADS)
Zeng, Y.; Zhang, J.; Niu, R.
2015-06-01
Remote sensing was introduced into China in 1970s and then began to flourish. At present, China has developed into a big remote sensing country, and remote sensing is increasingly playing an important role in various fields of national economic construction and social development. Based on China Academic Journals Full-text Database and China Citation Database published by China National Knowledge Infrastructure, this paper analyzed academic characteristics of 963 highly cited papers published by 16 professional and academic journals in the field of surveying and mapping from January 2010 to December 2014 in China, which include hot topics, literature authors, research institutions, and fundations. At the same time, it studied a total of 51,149 keywords published by these 16 journals during the same period. Firstly by keyword selection, keyword normalization, keyword consistency and keyword incorporation, and then by analysis of high frequency keywords, the progress and prospect of China's remote sensing technology in data acquisition, data processing and applications during the past five years were further explored and revealed. It can be seen that: highly cited paper analysis and word frequency analysis is complementary on subject progress analysis; in data acquisition phase, research focus is new civilian remote sensing satellite systems and UAV remote sensing system; research focus of data processing and analysis is multi-source information extraction and classification, laser point cloud data processing, objectoriented high resolution image analysis, SAR data and hyper-spectral image processing, etc.; development trend of remote sensing data processing is quantitative, intelligent, automated, and real-time, and the breadth and depth of remote sensing application is gradually increased; parallel computing, cloud computing and geographic conditions monitoring and census are the new research focuses to be paid attention to.
The U.S. Geological Survey Land Remote Sensing Program
,
2003-01-01
In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.; Luvall, Jeffrey C.
1998-01-01
Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.
Use of Remote Sensing for Decision Support in Africa
NASA Technical Reports Server (NTRS)
Policelli, Frederick S.
2007-01-01
Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.
Remote sensing with unmanned aircraft systems for precision agriculture applications
USDA-ARS?s Scientific Manuscript database
The Federal Aviation Administration is revising regulations for using unmanned aircraft systems (UAS) in the national airspace. An important potential application of UAS may be as a remote-sensing platform for precision agriculture, but simply down-scaling remote sensing methodologies developed usi...
Remote sensing for cotton farming
USDA-ARS?s Scientific Manuscript database
Application of remote sensing technologies in agriculture began with the use of aerial photography to identify cotton root rot in the late 1920s. From then on, agricultural remote sensing has developed gradually until the introduction of precision farming technologies in the late 1980s and biotechno...
Remote sensing for mined area reclamation: Application inventory
NASA Technical Reports Server (NTRS)
1971-01-01
Applications of aerial remote sensing to coal mined area reclamation are documented, and information concerning available data banks for coal producing areas in the east and midwest is given. A summary of mined area information requirements to which remote sensing methods might contribute is included.
NASA Technical Reports Server (NTRS)
Epps, J. W.
1973-01-01
Current references were surveyed for the application of remote sensing to traffic and transportation studies. The major problems are presented that concern traffic engineers and transportation managers, and the literature references that discuss remote sensing applications are summarized.
What does remote sensing do for ecology?
NASA Technical Reports Server (NTRS)
Roughgarden, J.; Running, S. W.; Matson, P. A.
1991-01-01
The application of remote sensing to ecological investigations is briefly discussed. Emphasis is given to the recruitment problem in marine population dynamics, the regional analysis of terrestrial ecosystems, and the monitoring of ecological changes. Impediments to the use of remote sensing data in ecology are addressed.
REVIEW OF METHODS FOR REMOTE SENSING OF ATMOSPHERIC EMISSIONS FROM STATIONARY SOURCES
The report reviews the commercially available and developing technologies for the application of remote sensing to the measurement of source emissions. The term 'remote sensing technology', as applied in the report, means the detection or concentration measurement of trace atmosp...
75 FR 26919 - Charter Renewals
Federal Register 2010, 2011, 2012, 2013, 2014
2010-05-13
...: Notice of Renewal of the Advisory Committee on Commercial Remote Sensing Charter. SUMMARY: In accordance... Commercial Remote Sensing (ACCRES) is in the public interest in connection with the performance of duties... Oceans and Atmosphere on matters relating to the U.S. commercial remote-sensing industry and NOAA's...
75 FR 52307 - Submission for OMB Review; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-25
...: National Oceanic and Atmospheric Administration (NOAA). Title: Licensing of Private Remote-Sensing Space... National Satellite Land Remote Sensing Data Archive; 3 hours for the submission of an operational quarterly... and Uses: NOAA has established requirements for the licensing of private operators of remote-sensing...
Atmospheric Correction Algorithm for Hyperspectral Remote Sensing of Ocean Color from Space
2000-02-20
Existing atmospheric correction algorithms for multichannel remote sensing of ocean color from space were designed for retrieving water-leaving...atmospheric correction algorithm for hyperspectral remote sensing of ocean color with the near-future Coastal Ocean Imaging Spectrometer. The algorithm uses
Target detection method by airborne and spaceborne images fusion based on past images
NASA Astrophysics Data System (ADS)
Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng
2017-11-01
To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.
Scaling field data to calibrate and validate moderate spatial resolution remote sensing models
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.
Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.
2010-01-01
In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.
a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images
NASA Astrophysics Data System (ADS)
Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.
2015-07-01
Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.
A NDVI assisted remote sensing image adaptive scale segmentation method
NASA Astrophysics Data System (ADS)
Zhang, Hong; Shen, Jinxiang; Ma, Yanmei
2018-03-01
Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.
Qader, Sarchil Hama; Dash, Jadunandan; Atkinson, Peter M
2018-02-01
Crop production and yield estimation using remotely sensed data have been studied widely, but such information is generally scarce in arid and semi-arid regions. In these regions, inter-annual variation in climatic factors (such as rainfall) combined with anthropogenic factors (such as civil war) pose major risks to food security. Thus, an operational crop production estimation and forecasting system is required to help decision-makers to make early estimates of potential food availability. Data from NASA's MODIS with official crop statistics were combined to develop an empirical regression-based model to forecast winter wheat and barley production in Iraq. The study explores remotely sensed indices representing crop productivity over the crop growing season to find the optimal correlation with crop production. The potential of three different remotely sensed indices, and information related to the phenology of crops, for forecasting crop production at the governorate level was tested and their results were validated using the leave-one-year-out approach. Despite testing several methodological approaches, and extensive spatio-temporal analysis, this paper depicts the difficulty in estimating crop yield on an annual base using current satellite low-resolution data. However, more precise estimates of crop production were possible. The result of the current research implies that the date of the maximum vegetation index (VI) offered the most accurate forecast of crop production with an average R 2 =0.70 compared to the date of MODIS EVI (Avg R 2 =0.68) and a NPP (Avg R 2 =0.66). When winter wheat and barley production were forecasted using NDVI, EVI and NPP and compared to official statistics, the relative error ranged from -20 to 20%, -45 to 28% and -48 to 22%, respectively. The research indicated that remotely sensed indices could characterize and forecast crop production more accurately than simple cropping area, which was treated as a null model against which to evaluate the proposed approach. Copyright © 2017 Elsevier B.V. All rights reserved.
West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
2016-01-01
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
de Klerk, Helen M; Gilbertson, Jason; Lück-Vogel, Melanie; Kemp, Jaco; Munch, Zahn
2016-11-01
Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single 'best performer' from which the final map is made. We use a combination of an omission/commission plot to evaluate various results and compile a probability map based on consistently strong performing models across a range of standard accuracy measures. We suggest that this easy-to-use approach can be applied in any study using remote sensing to map natural features for management action. We demonstrate this approach using optical remote sensing products of different spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral resolution). Of the variety of classification algorithms available, we tested maximum likelihood and support vector machine, and applied these to raw spectral data, the first three PCA summaries of the data, and the standard normalised difference vegetation index. We found that there is no 'one size fits all' solution to the choice of a 'best fit' model (i.e. combination of classification algorithm or data sets), which is in agreement with the literature that classifier performance will vary with data properties. We feel this lends support to our suggestion that rather than the identification of a 'single best' model and a map based on this result alone, a probability map based on the range of consistently top performing models provides a rigorous solution to environmental mapping. Copyright © 2016 Elsevier Ltd. All rights reserved.
Utility of remotely sensed data for identification of soil conservation practices
NASA Technical Reports Server (NTRS)
Pelletier, R. E.; Griffin, R. H.
1986-01-01
Discussed are a variety of remotely sensed data sources that may have utility in the identification of conservation practices and related linear features. Test sites were evaluated in Alabama, Kansas, Mississippi, and Oklahoma using one or more of a variety of remotely sensed data sources, including color infrared photography (CIR), LANDSAT Thematic Mapper (TM) data, and aircraft-acquired Thermal Infrared Multispectral Scanner (TIMS) data. Both visual examination and computer-implemented enhancement procedures were used to identify conservation practices and other linear features. For the Kansas, Mississippi, and Oklahoma test sites, photo interpretations of CIR identified up to 24 of the 109 conservation practices from a matrix derived from the SCS National Handbook of Conservation Practices. The conservation practice matrix was modified to predict the possibility of identifying the 109 practices at various photographic scales based on the observed results as well as photo interpreter experience. Some practices were successfully identified in TM data through visual identification, but a number of existing practices were of such size and shape that the resolution of the TM could not detect them accurately. A series of computer-automated decorrelation and filtering procedures served to enhance the conservation practices in TM data with only fair success. However, features such as field boundaries, roads, water bodies, and the Urban/Ag interface were easily differentiated. Similar enhancement techniques applied to 5 and 10 meter TIMS data proved much more useful in delineating terraces, grass waterways, and drainage ditches as well as the features mentioned above, due partly to improved resolution and partly to thermally influenced moisture conditions. Spatially oriented data such as those derived from remotely sensed data offer some promise in the inventory and monitoring of conservation practices as well as in supplying parameter data for a variety of computer-implemented agricultural models.
West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan
2016-10-11
Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.
Passive optical remote sensing of Congo River bathymetry using Landsat
NASA Astrophysics Data System (ADS)
Ache Rocha Lopes, V.; Trigg, M. A.; O'Loughlin, F.; Laraque, A.
2014-12-01
While there have been notable advances in deriving river characteristics such as width, using satellite remote sensing datasets, deriving river bathymetry remains a significant challenge. Bathymetry is fundamental to hydrodynamic modelling of river systems and being able to estimate this parameter remotely would be of great benefit, especially when attempting to model hard to access areas where the collection of field data is difficult. One such region is the Congo Basin, where due to past political instability and large scale there are few studies that characterise river bathymetry. In this study we test whether it is possible to use passive optical remote sensing to estimate the depth of the Congo River using Landsat 8 imagery in the region around Malebo Pool, located just upstream of the Kinshasa gauging station. Methods of estimating bathymetry using remotely sensed datasets have been used extensively for coastal regions and now more recently have been demonstrated as feasible for optically shallow rivers. Previous river bathymetry studies have focused on shallow rivers and have generally used aerial imagery with a finer spatial resolution than Landsat. While the Congo River has relatively low suspended sediment concentration values the application of passive bathymetry estimation to a river of this scale has not been attempted before. Three different analysis methods are tested in this study: 1) a single band algorithm; 2) a log ratio method; and 3) a linear transform method. All three methods require depth data for calibration and in this study area bathymetry measurements are available for three cross-sections resulting in approximately 300 in-situ measurements of depth, which are used in the calibration and validation. The performance of each method is assessed, allowing the feasibility of passive depth measurement in the Congo River to be determined. Considering the scarcity of in-situ bathymetry measurements on the Congo River, even an approximate estimate of depths from these methods will be of considerable value in its hydraulic characterisation.
NASA Astrophysics Data System (ADS)
Sussman, A. J.; Macleod, G.; Labak, P.; Malich, G.; Rowlands, A. P.; Craven, J.; Sweeney, J. J.; Chiappini, M.; Tuckwell, G.; Sankey, P.
2015-12-01
The Integrated Field Exercise of 2014 (IFE14) was an event held in the Hashemite Kingdom of Jordan (with concurrent activities in Austria) that tested the operational and technical capabilities of an on-site inspection (OSI) within the CTBT verification regime. During an OSI, up to 40 international inspectors will search an area for evidence of a nuclear explosion. Over 250 experts from ~50 countries were involved in IFE14 (the largest simulation of a real OSI to date) and worked from a number of different directions, such as the Exercise Management and Control Teams (which executed the scenario in which the exercise was played) and those participants performing as members of the Inspection Team (IT). One of the main objectives of IFE14 was to test and integrate Treaty allowed inspection techniques, including a number of geophysical and remote sensing methods. In order to develop a scenario in which the simulated exercise could be carried out, suites of physical features in the IFE14 inspection area were designed and engineered by the Scenario Task Force (STF) that the IT could detect by applying the geophysical and remote sensing inspection technologies, in addition to other techniques allowed by the CTBT. For example, in preparation for IFE14, the STF modeled a seismic triggering event that was provided to the IT to prompt them to detect and localize aftershocks in the vicinity of a possible explosion. Similarly, the STF planted shallow targets such as borehole casings and pipes for detection using other geophysical methods. In addition, airborne technologies, which included multi-spectral imaging, were deployed such that the IT could identify freshly exposed surfaces, imported materials, and other areas that had been subject to modification. This presentation will introduce the CTBT and OSI, explain the IFE14 in terms of the goals specific to geophysical and remote sensing methods, and show how both the preparation for and execution of IFE14 meet those goals.
Portable Imagery Quality Assessment Test Field for Uav Sensors
NASA Astrophysics Data System (ADS)
Dąbrowski, R.; Jenerowicz, A.
2015-08-01
Nowadays the imagery data acquired from UAV sensors are the main source of all data used in various remote sensing applications, photogrammetry projects and in imagery intelligence (IMINT) as well as in other tasks as decision support. Therefore quality assessment of such imagery is an important task. The research team from Military University of Technology, Faculty of Civil Engineering and Geodesy, Geodesy Institute, Department of Remote Sensing and Photogrammetry has designed and prepared special test field- The Portable Imagery Quality Assessment Test Field (PIQuAT) that provides quality assessment in field conditions of images obtained with sensors mounted on UAVs. The PIQuAT consists of 6 individual segments, when combined allow for determine radiometric, spectral and spatial resolution of images acquired from UAVs. All segments of the PIQuAT can be used together in various configurations or independently. All elements of The Portable Imagery Quality Assessment Test Field were tested in laboratory conditions in terms of their radiometry and spectral reflectance characteristics.
eFarm: A Tool for Better Observing Agricultural Land Systems
Yu, Qiangyi; Shi, Yun; Tang, Huajun; Yang, Peng; Xie, Ankun; Liu, Bin; Wu, Wenbin
2017-01-01
Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human–land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies. PMID:28245554
NASA Astrophysics Data System (ADS)
Hong, Liang
2013-10-01
The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.
NASA Astrophysics Data System (ADS)
van der Linden, Sebastian
2016-05-01
Compiling a good book on urban remote sensing is probably as hard as the research in this disciplinary field itself. Urban areas comprise various environments and show high heterogeneity in many respects, they are highly dynamic in time and space and at the same time of greatest influence on connected and even tele-connected regions due to their great economic importance. Urban remote sensing is therefore of great importance, yet as manifold as its study area: mapping urban areas (or sub-categories thereof) plays an important (and challenging) role in land use and land cover (change) monitoring; the analysis of urban green and forests is by itself a specialization of ecological remote sensing; urban climatology asks for spatially and temporally highly resolved remote sensing products; the detection of artificial objects is not only a common and important remote sensing application but also a typical benchmark for image analysis techniques, etc. Urban analyses are performed with all available spaceborne sensor types and at the same time they are one of the most relevant fields for airborne remote sensing. Several books on urban remote sensing have been published during the past 10 years, each taking a different perspective. The book Global Urban Monitoring and Assessment through Earth Observation is motivated by the objectives of the Global Urban Observation and Information Task (SB-04) in the GEOSS (Global Earth Observation System of Systems) 2012-2015 workplan (compare Chapter 2) and wants to highlight the global aspects of state-of-the-art urban remote sensing.
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
Multiscale and Multitemporal Urban Remote Sensing
NASA Astrophysics Data System (ADS)
Mesev, V.
2012-07-01
The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.
Research and technology: Report, FY 1982
NASA Technical Reports Server (NTRS)
1983-01-01
Sensor systems, data analysis programs, agriculture and resources inventory survey through aerospace remote sensing (AgRISTARS), applied research and data analysis, joint research project, and testing and evaluation are reported.
Application of cokriging techniques for the estimation of hail size
NASA Astrophysics Data System (ADS)
Farnell, Carme; Rigo, Tomeu; Martin-Vide, Javier
2018-01-01
There are primarily two ways of estimating hail size: the first is the direct interpolation of point observations, and the second is the transformation of remote sensing fields into measurements of hail properties. Both techniques have advantages and limitations as regards generating the resultant map of hail damage. This paper presents a new methodology that combines the above mentioned techniques in an attempt to minimise the limitations and take advantage of the benefits of interpolation and the use of remote sensing data. The methodology was tested for several episodes with good results being obtained for the estimation of hail size at practically all the points analysed. The study area presents a large database of hail episodes, and for this reason, it constitutes an optimal test bench.
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.
NASA Astrophysics Data System (ADS)
Nielsen, Allan A.; Conradsen, Knut; Skriver, Henning
2016-10-01
Test statistics for comparison of real (as opposed to complex) variance-covariance matrices exist in the statistics literature [1]. In earlier publications we have described a test statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated p-value [2]. We showed their application to bitemporal change detection and to edge detection [3] in multilook, polarimetric synthetic aperture radar (SAR) data in the covariance matrix representation [4]. The test statistic and the associated p-value is described in [5] also. In [6] we focussed on the block-diagonal case, we elaborated on some computer implementation issues, and we gave examples on the application to change detection in both full and dual polarization bitemporal, bifrequency, multilook SAR data. In [7] we described an omnibus test statistic Q for the equality of k variance-covariance matrices following the complex Wishart distribution. We also described a factorization of Q = R2 R3 … Rk where Q and Rj determine if and when a difference occurs. Additionally, we gave p-values for Q and Rj. Finally, we demonstrated the use of Q and Rj and the p-values to change detection in truly multitemporal, full polarization SAR data. Here we illustrate the methods by means of airborne L-band SAR data (EMISAR) [8,9]. The methods may be applied to other polarimetric SAR data also such as data from Sentinel-1, COSMO-SkyMed, TerraSAR-X, ALOS, and RadarSat-2 and also to single-pol data. The account given here closely follows that given our recent IEEE TGRS paper [7]. Selected References [1] Anderson, T. W., An Introduction to Multivariate Statistical Analysis, John Wiley, New York, third ed. (2003). [2] Conradsen, K., Nielsen, A. A., Schou, J., and Skriver, H., "A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 41(1): 4-19, 2003. [3] Schou, J., Skriver, H., Nielsen, A. A., and Conradsen, K., "CFAR edge detector for polarimetric SAR images," IEEE Transactions on Geoscience and Remote Sensing 41(1): 20-32, 2003. [4] van Zyl, J. J. and Ulaby, F. T., "Scattering matrix representation for simple targets," in Radar Polarimetry for Geoscience Applications, Ulaby, F. T. and Elachi, C., eds., Artech, Norwood, MA (1990). [5] Canty, M. J., Image Analysis, Classification and Change Detection in Remote Sensing,with Algorithms for ENVI/IDL and Python, Taylor & Francis, CRC Press, third revised ed. (2014). [6] Nielsen, A. A., Conradsen, K., and Skriver, H., "Change detection in full and dual polarization, single- and multi-frequency SAR data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(8): 4041-4048, 2015. [7] Conradsen, K., Nielsen, A. A., and Skriver, H., "Determining the points of change in time series of polarimetric SAR data," IEEE Transactions on Geoscience and Remote Sensing 54(5), 3007-3024, 2016. [9] Christensen, E. L., Skou, N., Dall, J., Woelders, K., rgensen, J. H. J., Granholm, J., and Madsen, S. N., "EMISAR: An absolutely calibrated polarimetric L- and C-band SAR," IEEE Transactions on Geoscience and Remote Sensing 36: 1852-1865 (1998).
NASA Technical Reports Server (NTRS)
Veziroglu, T. N.; Lee, S. S.
1973-01-01
A feasibility study for the development of a three-dimensional generalized, predictive, analytical model involving remote sensing, in-situ measurements, and an active system to remotely measure turbidity is presented. An implementation plan for the development of the three-dimensional model and for the application of remote sensing of temperature and turbidity measurements is outlined.
Remote sensing procurement package: Remote Sensing Industry Directory
NASA Technical Reports Server (NTRS)
1981-01-01
A directory of over 140 firms and organizations which contains detailed information in the types of products, services and equipment which they offer is presented. Also included for each firm or organization are addresses, phone numbers, contact person(s), and experience in the remote sensing field.
Accommodating Student Diversity in Remote Sensing Instruction.
ERIC Educational Resources Information Center
Hammen, John L., III.
1992-01-01
Discusses the difficulty of teaching computer-based remote sensing to students of varying levels of computer literacy. Suggests an instructional method that accommodates all levels of technical expertise through the use of microcomputers. Presents a curriculum that includes an introduction to remote sensing, digital image processing, and…
76 FR 65529 - Agency Information Collection Activities: Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-21
... National Land Remote Sensing Education, Outreach and Research Activity (NLRSEORA). As required by the... Drive MS 517, Reston, VA, 20192 (mail) . SUPPLEMENTARY INFORMATION: Title: National Land Remote Sensing... Remote Sensing Program, therefore it is more appropriate to refer to this effort as an activity rather...
15 CFR 960.11 - Conditions for operation.
Code of Federal Regulations, 2010 CFR
2010-01-01
... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.11 Conditions for... all facilities which comprise the remote sensing space system for the purpose of conducting license... possession, the licensee shall offer such data to the National Satellite Land Remote Sensing Data Archive at...
Code of Federal Regulations, 2010 CFR
2010-01-01
... SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.3 Definitions. For purposes of the regulations in this part, the following terms have the following meanings: Act means the Land Remote Sensing... application for a NOAA license to operate a remote sensing space system. Assistant Administrator means the...
Code of Federal Regulations, 2010 CFR
2010-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.2 Scope. (a) The Act and the regulations in this... proposes to operate a private remote sensing space system, either directly or through an affiliate or... private remote sensing system. (b) In determining whether substantial connections exist with regard to a...
Western Regional Remote Sensing Conference Proceedings, 1981
NASA Technical Reports Server (NTRS)
1981-01-01
Diverse applications of LANDSAT data, problem solutions, and operational goals are described by remote sensing users from 14 western states. The proposed FY82 federal budget reductions for technology transfer activities and the planned transition of the operational remote sensing system to NOAA's supervision are also considered.
Some Defence Applications of Civilian Remote Sensing Satellite Images
1993-11-01
This report is on a pilot study to demonstrate some of the capabilities of remote sensing in intelligence gathering. A wide variety of issues, both...colour images. The procedure will be presented in a companion report. Remote sensing , Satellite imagery, Image analysis, Military applications, Military intelligence.
Active/Passive Remote Sensing of the Ocean Surface at Microwave Frequencies
1999-09-30
This report summarizes research activities and results obtained under grant N000l4-99-1-0627 "Active/Passive Remote Sensing of the Ocean Surface at...Measurements were completed during April 1999 by the Microwave Remote Sensing Laboratory at the University of Massachusetts.
Code of Federal Regulations, 2012 CFR
2012-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.2 Scope. (a) The Act and the regulations in this... proposes to operate a private remote sensing space system, either directly or through an affiliate or... private remote sensing system. (b) In determining whether substantial connections exist with regard to a...
Code of Federal Regulations, 2014 CFR
2014-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.2 Scope. (a) The Act and the regulations in this... proposes to operate a private remote sensing space system, either directly or through an affiliate or... private remote sensing system. (b) In determining whether substantial connections exist with regard to a...
Code of Federal Regulations, 2013 CFR
2013-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.2 Scope. (a) The Act and the regulations in this... proposes to operate a private remote sensing space system, either directly or through an affiliate or... private remote sensing system. (b) In determining whether substantial connections exist with regard to a...
Code of Federal Regulations, 2011 CFR
2011-01-01
... LICENSING OF PRIVATE REMOTE SENSING SYSTEMS General § 960.2 Scope. (a) The Act and the regulations in this... proposes to operate a private remote sensing space system, either directly or through an affiliate or... private remote sensing system. (b) In determining whether substantial connections exist with regard to a...
Tools and Methods for the Registration and Fusion of Remotely Sensed Data
NASA Technical Reports Server (NTRS)
Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline
2010-01-01
Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.
NASA Technical Reports Server (NTRS)
Batista, G. T. (Principal Investigator); Delima, A. M.; Tardin, A. T.; Rudorff, B. F. T.; Mendonca, F. J.; Dosanjosferreirapinto, S.; Chen, S. C.; Duarte, V.
1984-01-01
Remote sensing techniques for supporting the rural credit supervision system were developed and tested. The test area comprised the counties of Aracatuba and Guararapes, located in the State of Sao Paulo. Aerial photography, LANDSAT images and topographic charts were used. Aerial photographs were extremely useful for the out lining of properties boundaries with financing of sugarcane plantations by the Banco do Brasil S.A.. The percentage of correctly interpreted sugarcane on LANDSAT images, considering the 85 analyzed properties, was of 63.12%. The occurrence of atypical conditions such as excessive raining, sugarcane in bloom, and wind damaged sugarcane and sugarcane not harvested due to planning failures verified during the period the images were obtained, were some of the contributing factors associated with a low interpretation performance. An alternative approach was developed using several LANDSAT overpasses and auxiliary field data, which resulted in 91.77 percent correct.
Application of remote sensing techniques to the geology of the bonanza volcanic center
NASA Technical Reports Server (NTRS)
Marrs, R. W.
1973-01-01
A program is reported for evaluating remote sensing as an aid to geologic mapping for the past four years. Data tested in this evaluation include color and color infrared photography, multiband photography, low sun-angle photography, thermal infrared scanner imagery, and side-looking airborne radar. The relative utility of color and color infrared photography was tested as it was used to refine geologic maps in previously mapped areas, as field photos while mapping in the field, and in making photogeologic maps prior to field mapping. The latter technique served as a test of the maximum utility of the photography. In this application the photography was used successfully to locate 75% of all faults in a portion of the geologically complex Bonanza volcanic center and to map and correctly identify 93% of all Quaternary deposits and 62% of all areas of Tertiary volcanic outcrop in the area.
Estimation of water turbidity in Gorgan Bay, South-east of Caspian Sea by using IRS-LISS-III images.
Aghighi, Hossein; Alimohammadi, Abbas; Saradjian, Mohammad Reza; Ashourloo, Davood
2008-03-01
In this research, usefulness of IRS-LISS-III data of Gorgan Bay, South-east of Caspian Sea located in North of Iran for water turbidity mapping, has been tested. After correction of geometric and radiometric errors, the resulting radiance data were used for examination of correlations between the remotely sensed and in situ water turbidity data simultaneously measured by the Secchi depth approach. Results of this research showed good relations between the Secchi depth and spectral data. The fitted statistical model was very significant (R2 = 0.77) and test of the model performance by independent samples was encouraging. Because of the low costs encountered with acquisition and processing of remotely sensed data, further research in larger scales for the purpose of more precise test of the approach for water turbidity mapping and monitoring is recommended.
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.
Linking remote sensing, land cover and disease.
Curran, P J; Atkinson, P M; Foody, G M; Milton, E J
2000-01-01
Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover; the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.
J. McKean; D. Tonina; C. Bohn; C. W. Wright
2014-01-01
New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional...
2. Photocopy of photograph (original photograph/negative located at the Remote ...
2. Photocopy of photograph (original photograph/negative located at the Remote Sensing Laboratory, Nellis Air Force Base, Las Vegas, Nevada). David Wehner, EG&G Photographic Services Photographer, October 13, 1992. Overall view of Japanese village, facing north - Nevada Test Site, Japanese Village, Area 4, Yucca Flat, 4-04 Road near Rainier Mesa Road, Mercury, Nye County, NV
Potential for remote sensing of agriculture from the international space station
NASA Astrophysics Data System (ADS)
Morgenthaler, George W.; Khatib, Nader
1999-01-01
Today's spatial resolution of orbital sensing systems is too coarse to economically serve the yield-improvement/contamination-reduction needs of the small to mid-size farm enterprise. Remote sensing from aircraft is being pressed into service. However, satellite remote sensing constellations with greater resolution and more spectral bands, i.e., with resolutions of 1 m in the panchromatic, 4 m in the multi-spectral, and 8 m in the hyper-spectral are expected to be in orbit by the year 2000. Such systems coupled with Global Positioning System (GPS) capability will make ``precision agriculture,'' i.e., the identification of specific and timely fertilizer, irrigation, herbicide, and insecticide needs on an acre-by-acre basis and the ability to meet these needs with precision delivery systems at affordable costs, is what is needed and can be achieved. Current plans for remote sensing systems on the International Space Station (ISS) include externally attached payloads and a window observation platform. The planned orbit of the Space Station will result in overflight of a specific latitude and longitude at the same clock time every 3 months. However, a pass over a specific latitude and longitude during ``daylight hours'' could occur much more frequently. The ISS might thus be a space platform for experimental and developmental testing of future commercial space remote sensing precision agriculture systems. There is also a need for agricultural ``truth'' sites so that predictive crop yield and pollution models can be devised and corrective suggestions delivered to farmers at affordable costs. In Summer 1998, the University of Colorado at Boulder and the Center for the Study of Terrestrial and Extraterrestrial Atmospheres (CSTEA) at Howard University, under NASA Goddard Space Flight Center funding, established an agricultural ``truth'' site in eastern Colorado. The ``truth'' site was highly instrumented for measuring trace gas concentrations (NOx, SOx, CO2, O3, organics, and aerosols), ground water contamination via drain-tile catch from the fields, and Leaf Area Index (LAI). Also, a tethered balloon flight sampled the site's vertical air column and both aerial infrared photography and satellite imagery were acquired. This paper summarizes the 1998 activities in establishing and operating the ``truth'' site. The goal of such a ``truth'' site is to develop and validate precision agriculture predictive models to improve farming practices. ISS sensor testing can greatly accelerate development of such systems.
NASA Technical Reports Server (NTRS)
Lindenlaub, J. C.; Davis, S. M.
1974-01-01
Materials are presented for assisting instructors in teaching the LARSYS Educational Package, which is a set of instructional materials to train people to analyze remotely sensed multispectral data. The seven units of the package are described. These units are: quantitative remote sensing, overview of the LARSYS software system, the 2780 remote terminal, demonstration of LARSYS on the 2780 remote terminal, exercises, guide to multispectral data analysis, and a case study using LARSYS for analysis of LANDSAT data.
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.
NASA Astrophysics Data System (ADS)
Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei
2017-07-01
In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.
SENSOR: a tool for the simulation of hyperspectral remote sensing systems
NASA Astrophysics Data System (ADS)
Börner, Anko; Wiest, Lorenz; Keller, Peter; Reulke, Ralf; Richter, Rolf; Schaepman, Michael; Schläpfer, Daniel
The consistent end-to-end simulation of airborne and spaceborne earth remote sensing systems is an important task, and sometimes the only way for the adaptation and optimisation of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software Environment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray-tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. The third part consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimisation requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and first examples of its use are given. The verification of SENSOR is demonstrated. This work is closely related to the Airborne PRISM Experiment (APEX), an airborne imaging spectrometer funded by the European Space Agency.
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.
A patch-based convolutional neural network for remote sensing image classification.
Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di
2017-11-01
Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hybrid region merging method for segmentation of high-resolution remote sensing images
NASA Astrophysics Data System (ADS)
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi; Wang, Jiangeng; Wang, Zuo
2014-12-01
Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images. HRM integrates the advantages of global-oriented and local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect the local context, as compared with the global-oriented method. A set of high-resolution remote sensing images is used to test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single regions better than MRS, and the supervised and unsupervised evaluation results further prove the superiority of HRM.
NASA Technical Reports Server (NTRS)
Njoku, E.; Wilson, W.; Yueh, S.; Freeland, R.; Helms, R.; Edelstein, W.; Sadowy, G.; Farra, D.; West, R.; Oxnevad, K.
2001-01-01
This report describes a two-year study of a large-aperture, lightweight, deployable mesh antenna system for radiometer and radar remote sensing of the Earth from space. The study focused specifically on an instrument to measure ocean salinity and Soil moisture. Measurements of ocean salinity and soil moisture are of critical . importance in improving knowledge and prediction of key ocean and land surface processes, but are not currently obtainable from space. A mission using this instrument would be the first demonstration of deployable mesh antenna technology for remote sensing and could lead to potential applications in other remote sensing disciplines that require high spatial resolution measurements. The study concept features a rotating 6-m-diameter deployable mesh antenna, with radiometer and radar sensors, to measure microwave emission and backscatter from the Earth's surface. The sensors operate at L and S bands, with multiple polarizations and a constant look angle, scanning across a wide swath. The study included detailed analyses of science requirements, reflector and feedhorn design and performance, microwave emissivity measurements of mesh samples, design and test of lightweight radar electronic., launch vehicle accommodations, rotational dynamics simulations, and an analysis of attitude control issues associated with the antenna and spacecraft, The goal of the study was to advance the technology readiness of the overall concept to a level appropriate for an Earth science emission.
Atmospheric Effect on Remote Sensing of the Earth's Surface
NASA Technical Reports Server (NTRS)
Fraser, R. S.; Kaufman, Y. J. (Principal Investigator)
1985-01-01
Radiative transfer theory (RT) for an atmosphere with a nonuniform surface is the basis for understanding and correcting for the atmospheric effect on remote sensing of surface properties. In the present work the theory is generalized and tested successfully against laboratory and field measurements. There is still a need to generalize the RT approximation for off-nadir directions and to take into account anisotropic reflectance at the surface. The reflectance at the surface. The adjacency effect results in a significant modification of spectral signatures of the surface, and therefore results in modification of classifications, of separability of field classes, and of spatial resolution. For example, the 30 m resolution of the Thematic Mapper is reduced to 100 m by a hazy atmosphere. The adjacency effect depends on several optical parameters of aerosols: optical thickness, depth of aerosol layer, scattering phase function, and absorption. Remote sensing in general depends on these parameter, not just adjacency effects, but they are not known well enough for making accurate atmospheric corrections. It is important to establish methods for estimating these parameters in order to develop correction methods for atmospheric effects. Such estimations can be based on climatological data, which are not available yet, correlations between the optical parameters and meteorological data, and the same satellite measurements of radiances that are used for estimating surface properties. Knowledge about the atmospheric parameters important for remote sensing is being enlarged with current measurements of them.
NASA Astrophysics Data System (ADS)
See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz
2016-04-01
The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.
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.
A new simple concept for ocean colour remote sensing using parallel polarisation radiance
He, Xianqiang; Pan, Delu; Bai, Yan; Wang, Difeng; Hao, Zengzhou
2014-01-01
Ocean colour remote sensing has supported research on subjects ranging from marine ecosystems to climate change for almost 35 years. However, as the framework for ocean colour remote sensing is based on the radiation intensity at the top-of-atmosphere (TOA), the polarisation of the radiation, which contains additional information on atmospheric and water optical properties, has largely been neglected. In this study, we propose a new simple concept to ocean colour remote sensing that uses parallel polarisation radiance (PPR) instead of the traditional radiation intensity. We use vector radiative transfer simulation and polarimetric satellite sensing data to demonstrate that using PPR has two significant advantages in that it effectively diminishes the sun glint contamination and enhances the ocean colour signal at the TOA. This concept may open new doors for ocean colour remote sensing. We suggest that the next generation of ocean colour sensors should measure PPR to enhance observational capability. PMID:24434904
The University of Kansas Applied Sensing Program: An operational perspective
NASA Technical Reports Server (NTRS)
Martinko, E. A.
1981-01-01
The Kansas applied remote sensing (KARS) program conducts demonstration projects and applied research on remote sensing techniques which enable local, regional, state and federal agency personnel to better utilize available satellite and airborne remote sensing systems. As liason with Kansas agencies for the Earth Resources Laboratory (ERL), Kansas demonstration project, KARS coordinated interagency communication, field data collection, hands-on training, and follow-on technical assistance and worked with Kansas agency personnel in evaluating land cover maps provided by ERL. Short courses are being conducted to provide training in state-of-the-art remote sensing technology for university faculty, state personnel, and persons from private industry and federal government. Topics are listed which were considered in intensive five-day courses covering the acquisition, interpretation, and application of information derived through remote sensing with specific training and hands-on experience in image interpretation and the analysis of LANDSAT data are listed.
NASA Technical Reports Server (NTRS)
Johnson, Paul E.; Smith, Milton O.; Adams, John B.
1992-01-01
Algorithms were developed, based on Hapke's (1981) equations, for remote determinations of mineral abundances and particle sizes from reflectance spectra. In this method, spectra are modeled as a function of end-member abundances and illumination/viewing geometry. The method was tested on a laboratory data set. It is emphasized that, although there exist more sophisticated models, the present algorithms are particularly suited for remotely sensed data, where little opportunity exists to independently measure reflectance versus article size and phase function.
Laser-Based Remote Sensing of Explosives by a Differential Absorption and Scattering Method
NASA Astrophysics Data System (ADS)
Ayrapetyan, V. S.
2018-01-01
A multifunctional IR parametric laser system is developed and tested for remote detection and identification of atmospheric gases, including explosive and chemically aggressive substances. Calculations and experimental studies of remote determination of the spectroscopic parameters of the best known explosive substances TNT, RDX, and PETN are carried out. The feasibility of high sensitivity detection ( 1 ppm) of these substances with the aid of a multifunctional IR parametric light source by differential absorption and scattering is demonstrated.
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.
NASA Astrophysics Data System (ADS)
Krezhova, Dora; Krezhov, Kiril; Maneva, Svetla; Moskova, Irina; Petrov, Nikolay
2016-07-01
Hyperspectral remote sensing technique, based on reflectance measurements acquired in a high number of contiguous spectral bands in the visible and near infrared spectral ranges, was used to detect the influence of some environmental changes to vegetation ecosystems. Adverse physical and biological conditions give rise to morphological, physiological, and biochemical changes in the plants that affect the manner in which they interact with the light. All green vegetation species have unique spectral features, mainly because of the chlorophyll and carotenoid, and other pigments, and water content. Because spectral reflectance is a function of the illumination conditions, tissue optical properties and biochemical content of the plants it may be used to collect information on several important biophysical parameters such as color and the spectral signature of features, vegetation chlorophyll absorption characteristics, vegetation moisture content, etc. Remotely sensed data collected by means of a portable fiber-optics spectrometer in the spectral range 350-1100 nm were used to extract information on the influence of some environmental changes. Stress factors such as enhanced UV-radiation, salinity, viral infections, were applied to some young plants species (potato, tomato, plums). The test data were subjected to different digital image processing techniques. This included statistical (Student's t-criterion), first derivative and cluster analyses and some vegetation indices. Statistical analyses were carried out in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (680-720 nm) and near infrared (720-780 nm). The strong relationship, which was found between the results from the remote sensing technique and some biochemical and serological analyses (stress markers, DAS-ELISA), indicates the importance of hyperspectral reflectance data for conducting, easily and without damage, rapid assessments of plant biophysical variables. Emphasis is put on current capability and future potential of remote sensing for assessment of the plant health and on the optimum spectral regions and vegetation indices for sensing these biophysical variables.
USDA-ARS?s Scientific Manuscript database
Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Most image acquisitions from UAS have been in the visible bands, while multispectral remote sensing ap...
Reflectance spectroscopy: quantitative analysis techniques for remote sensing applications.
Clark, R.N.; Roush, T.L.
1984-01-01
Several methods for the analysis of remotely sensed reflectance data are compared, including empirical methods and scattering theories, both of which are important for solving remote sensing problems. The concept of the photon mean path length and the implications for use in modeling reflectance spectra are presented.-from Authors
An overview of the development of remote sensing techniques for the screwworm eradication program
NASA Technical Reports Server (NTRS)
Barnes, C. M.; Forsberg, F. C.
1975-01-01
The current status of remote sensing techniques developed for the screwworm eradication program of the Mexican-American Screwworm Eradication Commission was reported. A review of the type of data and equipment used in the program is presented. Future applications of remote sensing techniques are considered.
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...
Conference of Remote Sensing Educators (CORSE-78)
NASA Technical Reports Server (NTRS)
1978-01-01
Ways of improving the teaching of remote sensing students at colleges and universities are discussed. Formal papers and workshops on various Earth resources disciplines, image interpretation, and data processing concepts are presented. An inventory of existing remote sensing and related subject courses being given in western regional universities is included.
Frontiers of Remote Sensing of the Oceans and Troposphere from Air and Space Platforms
NASA Technical Reports Server (NTRS)
1984-01-01
Several areas of remote sensing are addressed including: future satellite systems; air-sea interaction/wind; ocean waves and spectra/S.A.R.; atmospheric measurements (particulates and water vapor); synoptic and weather forecasting; topography; bathymetry; sea ice; and impact of remote sensing on synoptic analysis/forecasting.
Remote sensing of earth terrain
NASA Technical Reports Server (NTRS)
Kong, Jin AU; Yueh, Herng-Aung; Shin, Robert T.
1991-01-01
Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others.
Evapotranspiration estimates derived using multi-platform remote sensing in a semiarid region
USDA-ARS?s Scientific Manuscript database
Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed ob...
Code of Federal Regulations, 2010 CFR
2010-01-01
... SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.9 License term. (a) Each license for... licensee to: (1) Provide data to the National Satellite Land Remote Sensing Data Archive for the basic data set; (2) Make data available to the National Satellite Land Remote Sensing Data Archive that the...
NASA Technical Reports Server (NTRS)
Karakoylu, E.; Franz, B.
2016-01-01
First attempt at quantifying uncertainties in ocean remote sensing reflectance satellite measurements. Based on 1000 iterations of Monte Carlo. Data source is a SeaWiFS 4-day composite, 2003. The uncertainty is for remote sensing reflectance (Rrs) at 443 nm.
Elementary Age Children and Remote Sensing: Research from Project Omega.
ERIC Educational Resources Information Center
Kirman, Joseph M.
1991-01-01
Discusses remote sensing technology use in teaching elementary school students about science and social studies. Reviews findings dealing with the use of remote sensing and considering children's abilities, teacher training, computer applications, gifted children, and sex-related differences. Concludes that children as young as grade three can…
Inquiry-Based Learning in Remote Sensing: A Space Balloon Educational Experiment
ERIC Educational Resources Information Center
Mountrakis, Giorgos; Triantakonstantis, Dimitrios
2012-01-01
Teaching remote sensing in higher education has been traditionally restricted in lecture and computer-aided laboratory activities. This paper presents and evaluates an engaging inquiry-based educational experiment. The experiment was incorporated in an introductory remote sensing undergraduate course to bridge the gap between theory and…
Interactive Online Tools for Enhancing Student Learning Experiences in Remote Sensing
ERIC Educational Resources Information Center
Joyce, Karen E.; Boitshwarelo, Bopelo; Phinn, Stuart R.; Hill, Greg J. E.; Kelly, Gail D.
2014-01-01
The rapid growth in Information and Communications Technologies usage in higher education has provided immense opportunities to foster effective student learning experiences in geography. In particular, remote sensing lends itself to the creative utilization of multimedia technologies. This paper presents a case study of a remote sensing computer…
ERIC Educational Resources Information Center
Hotchkiss, Rose; Dickerson, Daniel
2008-01-01
Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…
Code of Federal Regulations, 2010 CFR
2010-01-01
... SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Prohibitions § 960.13 Prohibitions. It is unlawful for... subsidiary or affiliate to: (a) Operate a private remote sensing space system in such a manner as to...) Operate a private remote sensing space system without possession of a valid license issued under the Act...
Fully Engaging Students in the Remote Sensing Process through Field Experience
ERIC Educational Resources Information Center
Rundquist, Bradley C.; Vandeberg, Gregory S.
2013-01-01
Field data collection is often crucial to the success of investigations based upon remotely sensed data. Students of environmental remote sensing typically learn about the discipline through classroom lectures, a textbook, and computer laboratory sessions focused on the interpretation and processing of aircraft and satellite data. The importance…