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.

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

DTIC Science & Technology

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.

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...

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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...

Agricultural Production Monitoring in the Sahel Using Remote Sensing: Present Possibilities and Research Needs

DTIC Science & Technology

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

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…

PROCEEDINGS OF THE FOURTH SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT; 12, 13, 14 APRIL 1966.

DTIC Science & Technology

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)

Application research on land use remote sensing dynamic monitoring: A case study of Anning district, Lanzhou

NASA Astrophysics Data System (ADS)

Zhu, Yunqiang; Zhu, Huazhong; Lu, Heli; Ni, Jianguang; Zhu, Shaoxia

2005-10-01

Remote sensing dynamic monitoring of land use can detect the change information of land use and update the current land use map, which is important for rational utilization and scientific management of land resources. This paper discusses the technological procedure of remote sensing dynamic monitoring of land use including the process of remote sensing images, the extraction of annual change information of land use, field survey, indoor post processing and accuracy assessment. Especially, we emphasize on comparative research on the choice of remote sensing rectifying models, image fusion algorithms and accuracy assessment methods. Taking Anning district in Lanzhou as an example, we extract the land use change information of the district during 2002-2003, access monitoring accuracy and analyze the reason of land use change.

Applying remote sensing and GIS techniques in solving rural county information needs

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.; Fernandez, R. Norberto; Lozano-Garcia, D. Fabian

1992-01-01

The project designed was to acquaint county government officials and their clientele with remote sensing and GIS products that contain information about land conditions and land use. Other users determined through the course of this project were federal agencies working at the county level, agricultural businesses and others in need of spatial information. The specific project objectives were: (1) to investigate the feasibility of using remotely sensed data to identify and quantify specific land cover categories and conditions for purposes of tax assessment, cropland area measurements and land use evaluation; (2) to investigate the use of satellite remote sensing data as an aid in assessing soil management practices; and (3) to evaluate the use of remotely sensed data to assess soil resources and conditions which affect productivity.

Needs Assessment for the Use of NASA Remote Sensing Data in the Development and Implementation of Estuarine and Coastal Water Quality Standards

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.

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.

Natural Resource Information System. Remote Sensing Studies.

ERIC Educational Resources Information Center

Leachtenauer, J.; And Others

A major design objective of the Natural Resource Information System entailed the use of remote sensing data as an input to the system. Potential applications of remote sensing data were therefore reviewed and available imagery interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and…

Imagery atlas: a structure of expert software designed to improve the accessibility of remote-sensed satellite imagery

NASA Astrophysics Data System (ADS)

Genet, Richard P.

1995-11-01

Policy changes in the United States and Europe will bring a number of firms into the remote sensing market. More importantly, there will be a vast increase in the amount of data and potentially, the amount of information, that is available for academic, commercial and a variety of public uses. Presently many of the users of remote sensing data have some understanding of photogrammetric and remote sensing technologies. This is especially true of environmentalist users and academics. As the amount of remote sensing data increases, in order to broaden the user base, it will become increasingly important that the information user not be required to have a background in photogrammetry, remote sensing, or even in the basics of geographic information systems. The user must be able to articulate his requirements in view of existence of new sources of information. This paper provides the framework for expert systems to accomplish this interface. Specific examples of the capabilities which must be developed in order to maximize the utility of specific images and image archives are presented and discussed.

Practical applications of remote sensing technology

NASA Technical Reports Server (NTRS)

Whitmore, Roy A., Jr.

1990-01-01

Land managers increasingly are becoming dependent upon remote sensing and automated analysis techniques for information gathering and synthesis. Remote sensing and geographic information system (GIS) techniques provide quick and economical information gathering for large areas. The outputs of remote sensing classification and analysis are most effective when combined with a total natural resources data base within the capabilities of a computerized GIS. Some examples are presented of the successes, as well as the problems, in integrating remote sensing and geographic information systems. The need to exploit remotely sensed data and the potential that geographic information systems offer for managing and analyzing such data continues to grow. New microcomputers with vastly enlarged memory, multi-fold increases in operating speed and storage capacity that was previously available only on mainframe computers are a reality. Improved raster GIS software systems have been developed for these high performance microcomputers. Vector GIS systems previously reserved for mini and mainframe systems are available to operate on these enhanced microcomputers. One of the more exciting areas that is beginning to emerge is the integration of both raster and vector formats on a single computer screen. This technology will allow satellite imagery or digital aerial photography to be presented as a background to a vector display.

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

Treesearch

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...

75 FR 32360 - Proposed Information Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems

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...

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

PubMed Central

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

2015-01-01

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

Remote Sensing Information Sciences Research Group, year four

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1987-01-01

The needs of the remote sensing research and application community which will be served by the Earth Observing System (EOS) and space station, including associated polar and co-orbiting platforms are examined. Research conducted was used to extend and expand existing remote sensing research activities in the areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence, and vegetation analysis and modeling. Projects are discussed in detail.

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…

The U.S. Geological Survey land remote sensing program

USGS Publications Warehouse

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.

Multistage remote sensing: toward an annual national inventory

Treesearch

Raymond L. Czaplewski

1999-01-01

Remote sensing can improve efficiency of statistical information. Landsat data can identify and map a few broad categories of forest cover and land use. However, more-detailed information requires a sample of higher-resolution imagery, which costs less than field data but considerably more than Landsat data. A national remote sensing program would be a major...

Incorporating remotely sensed tree canopy cover data into broad scale assessments of wildlife habitat distribution and conservation

Treesearch

Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Kerri T. Vierling; Andrew T. Hudak

2009-01-01

Remote sensing provides critical information for broad scale assessments of wildlife habitat distribution and conservation. However, such efforts have been typically unable to incorporate information about vegetation structure, a variable important for explaining the distribution of many wildlife species. We evaluated the consequences of incorporating remotely sensed...

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

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.

Remote Sensing Data Fusion to Detect Illicit Crops and Unauthorized Airstrips

NASA Astrophysics Data System (ADS)

Pena, J. A.; Yumin, T.; Liu, H.; Zhao, B.; Garcia, J. A.; Pinto, J.

2018-04-01

Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. Multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote sensing data fusion in detecting illicit crop through LSMM, GOBIA, and MCE analyzing of strategic information. This methodology emerges as a complementary and effective strategy to control and eradicate illicit crops.

Remote Sensing Information Sciences Research Group: Santa Barbara Information Sciences Research Group, year 4

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1987-01-01

Information Sciences Research Group (ISRG) research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. Particular focus in on the needs of the remote sensing research and application science community which will be served by the Earth Observing System (EOS) and Space Station, including associated polar and co-orbiting platforms. The areas of georeferenced information systems, machine assisted information extraction from image data, artificial intelligence and both natural and cultural vegetation analysis and modeling research will be expanded.

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.

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)

Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR: Chapter 1

USGS Publications Warehouse

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.

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...

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

USGS Publications Warehouse

Pearson, D.K.; Gary, R.H.; Wilson, Z.D.

2007-01-01

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

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.

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.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

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.

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.

Remote sensing of wetlands

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.

7 CFR 2.29 - Chief Economist.

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...

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

NASA Technical Reports Server (NTRS)

Freeman, Anthony; Dubois, Pascale; Leberl, Franz; Norikane, L.; Way, Jobea

1991-01-01

Viewgraphs on Geographic Information System for fusion and analysis of high-resolution remote sensing and ground truth data are presented. Topics covered include: scientific objectives; schedule; and Geographic Information System.

Sensors research and technology

NASA Technical Reports Server (NTRS)

Cutts, James A.

1988-01-01

Information on sensors research and technology is given in viewgraph form. Information is given on sensing techniques for space science, passive remote sensing techniques and applications, submillimeter coherent sensing, submillimeter mixers and local oscillator sources, non-coherent sensors, active remote sensing, solid state laser development, a low vibration cooler, separation of liquid helium and vapor phase in zero gravity, and future plans.

An information system design for watershed-wide modeling of water loss to the atmosphere using remote sensing techniques

NASA Technical Reports Server (NTRS)

Khorram, S.

1977-01-01

Results are presented of a study intended to develop a general location-specific remote-sensing procedure for watershed-wide estimation of water loss to the atmosphere by evaporation and transpiration. The general approach involves a stepwise sequence of required information definition (input data), appropriate sample design, mathematical modeling, and evaluation of results. More specifically, the remote sensing-aided system developed to evaluate evapotranspiration employs a basic two-stage two-phase sample of three information resolution levels. Based on the discussed design, documentation, and feasibility analysis to yield timely, relatively accurate, and cost-effective evapotranspiration estimates on a watershed or subwatershed basis, work is now proceeding to implement this remote sensing-aided system.

Development and Testing of Physically-Based Methods for Filling Gaps in Remotely Sensed River Data

DTIC Science & Technology

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

Thematic Conference on Geologic Remote Sensing, 8th, Denver, CO, Apr. 29-May 2, 1991, Proceedings. Vols. 1 & 2

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings contain papers discussing the state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing, along with the research and development activities aimed at increasing the future capabilities of this technology. The following topics are addressed: spectral geology, U.S. and international hydrocarbon exporation, radar and thermal infrared remote sensing, engineering geology and hydrogeology, mineral exploration, remote sensing for marine and environmental applications, image processing and analysis, geobotanical remote sensing, and data integration and geographic information systems. Particular attention is given to spectral alteration mapping with imaging spectrometers, mapping the coastal plain of the Congo with airborne digital radar, applications of remote sensing techniques to the assessment of dam safety, remote sensing of ferric iron minerals as guides for gold exploration, principal component analysis for alteration mappping, and the application of remote sensing techniques for gold prospecting in the north Fujian province.

Experimental Sea Slicks in the Marsen (Maritime Remote Sensing) Exercise.

DTIC Science & Technology

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

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.

Remote Sensing Information Gateway

EPA Pesticide Factsheets

Remote Sensing Information Gateway, a tool that allows scientists, researchers and decision makers to access a variety of multi-terabyte, environmental datasets and to subset the data and obtain only needed variables, greatly improving the download time.

Polarization Remote Sensing Physical Mechanism, Key Methods and Application

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

Energy Remote Sensing Applications Projects at the NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Norman, S. D.; Likens, W. C.; Mouat, D. A.

1982-01-01

The NASA Ames Research Center is active in energy projects primarily in the role of providing assistance to users in the solution of a number of problems related to energy. Data bases were produced which can be used, in combination with other sources of information, to solve spatially related energy problems. Six project activities at Ames are described which relate to energy and remote sensing. Two projects involve power demand forecasting and estimations using remote sensing and geographic information systems; two others involve transmission line routing and corridor analysis; one involves a synfuel user needs assessment through remote sensing; and the sixth involves the siting of energy facilities.

Remote sensing and the Mississippi high accuracy reference network

NASA Technical Reports Server (NTRS)

Mick, Mark; Alexander, Timothy M.; Woolley, Stan

1994-01-01

Since 1986, NASA's Commercial Remote Sensing Program (CRSP) at Stennis Space Center has supported commercial remote sensing partnerships with industry. CRSP's mission is to maximize U.S. market exploitation of remote sensing and related space-based technologies and to develop advanced technical solutions for spatial information requirements. Observation, geolocation, and communications technologies are converging and their integration is critical to realize the economic potential for spatial informational needs. Global positioning system (GPS) technology enables a virtual revolution in geopositionally accurate remote sensing of the earth. A majority of states are creating GPS-based reference networks, or high accuracy reference networks (HARN). A HARN can be defined for a variety of local applications and tied to aerial or satellite observations to provide an important contribution to geographic information systems (GIS). This paper details CRSP's experience in the design and implementation of a HARN in Mississippi and the design and support of future applications of integrated earth observations, geolocation, and communications technology.

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.

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Possible role of remote sensing for increasing public awareness of the Chesapeake Bay environment

NASA Technical Reports Server (NTRS)

Wilkerson, T. D.; Maher, P. A.; Billings, G.; Cressy, P. J.; Jarman, J. W.; Macleod, N. H.; Trombka, J. I.; Wisner, T.

1978-01-01

Application of remote sensing techniques to the study of the Chesapeake Bay and the availability of the resulting information are discussed in terms of public awareness of the Chesapeake Bay, its total environment, and the need to protect that environment and to preserve the Bay. Recommendations given include: (1) continue the study of remote sensing technology and its use in the Chesapeake Bay region; (2) emphasize the importance of LANDSAT imagery to the evolution of remote sensing technological developments and the awareness of the environment and its changes; (3) increase dissemination of information of the environmental applications of remote sensing technology to the public; (4) design surveys of the Chesapeake Bay environment and its manmade changes; and (5) establish a coordinating regional institution to develop a management plan for the Chesapeake Bay.

Acoustic Remote Sensing

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.

What is a picture worth? A history of remote sensing

USGS Publications Warehouse

Moore, Gerald K.

1979-01-01

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

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.

Study on identifying deciduous forest by the method of feature space transformation

NASA Astrophysics Data System (ADS)

Zhang, Xuexia; Wu, Pengfei

2009-10-01

The thematic remotely sensed information extraction is always one of puzzling nuts which the remote sensing science faces, so many remote sensing scientists devotes diligently to this domain research. The methods of thematic information extraction include two kinds of the visual interpretation and the computer interpretation, the developing direction of which is intellectualization and comprehensive modularization. The paper tries to develop the intelligent extraction method of feature space transformation for the deciduous forest thematic information extraction in Changping district of Beijing city. The whole Chinese-Brazil resources satellite images received in 2005 are used to extract the deciduous forest coverage area by feature space transformation method and linear spectral decomposing method, and the result from remote sensing is similar to woodland resource census data by Chinese forestry bureau in 2004.

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...

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…

Real Estate Assistance

NASA Technical Reports Server (NTRS)

1997-01-01

The Commercial Remote Sensing Program at Stennis Space Center assists numerous companies across the United States, in learning to use remote sensing capabilities to enhance their competitiveness. Through the Visiting Investigator Program, SSC helped Coast Delta Realty in Diamondhead, Miss., incorporate remote sensing and Geogrpahic Information System technology for real estate marketing and management.

Groundwater inventory and monitoring technical guide: Remote sensing of groundwater

USDA-ARS?s Scientific Manuscript database

The application of remotely sensed data in conjunction with in situ data greatly enhances the ability of the USDA Forest Service to meet the demands of field staff, customers, and others for groundwater information. Generally, the use of remotely sensed data to inventory and monitor groundwater reso...

Theme issue ;State-of-the-art in photogrammetry, remote sensing and spatial information science;

NASA Astrophysics Data System (ADS)

Heipke, Christian; Madden, Marguerite; Li, Zhilin; Dowman, Ian

2016-05-01

Over the past few years, photogrammetry, remote sensing and spatial information science have witnessed great changes in virtually every stage of information from imagery. Indeed, we have seen, for example, a sharply increased interest in unmanned aerial vehicles,

Research on Remote Sensing Geological Information Extraction Based on Object Oriented Classification

NASA Astrophysics Data System (ADS)

Gao, Hui

2018-04-01

The northern Tibet belongs to the Sub cold arid climate zone in the plateau. It is rarely visited by people. The geological working conditions are very poor. However, the stratum exposures are good and human interference is very small. Therefore, the research on the automatic classification and extraction of remote sensing geological information has typical significance and good application prospect. Based on the object-oriented classification in Northern Tibet, using the Worldview2 high-resolution remote sensing data, combined with the tectonic information and image enhancement, the lithological spectral features, shape features, spatial locations and topological relations of various geological information are excavated. By setting the threshold, based on the hierarchical classification, eight kinds of geological information were classified and extracted. Compared with the existing geological maps, the accuracy analysis shows that the overall accuracy reached 87.8561 %, indicating that the classification-oriented method is effective and feasible for this study area and provides a new idea for the automatic extraction of remote sensing geological information.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 4 : web-based bridge information database--visualization analytics and distributed sensing.

DOT National Transportation Integrated Search

2012-03-01

This report introduces the design and implementation of a Web-based bridge information visual analytics system. This : project integrates Internet, multiple databases, remote sensing, and other visualization technologies. The result : combines a GIS ...

The Importance of Information Requirements in Designing Acquisition to Information Systems

NASA Technical Reports Server (NTRS)

Davis, Bruce A.; Hill, Chuck; Maughan, Paul M.

1998-01-01

The partnership model used by NASA's Commercial Remote Sensing Program has been successful in better defining remote sensing functional requirements and translation to technical specifications to address environmental needs of the 21st century.

Commercial remote sensing & spatial information technologies program : program highlights.

DOT National Transportation Integrated Search

2017-01-01

The Commercial Remote Sensing and Spatial Information Technologies (CRS&SI) program was a congressionally mandated program authorized in the Safe, Accountable, Flexible and Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU). Under t...

7 CFR 3800.3 - Functions.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., climate, and related crop monitoring activities. (d) Remote sensing. (1) Provide technical assistance, coordination, and guidance to Department agencies in planning, developing, and carrying out satellite remote... administrative, management, and budget information relating to Department's remote sensing activities. ...

Criteria for successful government-industry-academic partnerships

NASA Astrophysics Data System (ADS)

Brannon, David P.

1996-03-01

The mission of the Commercial Remote Sensing Program (CRSP) Office at NASA's John C. Stennis Space Center is to maximize U.S. industry's commercial use of remote sensing and related space-based technologies and to develop advanced technical responses to spatial information requirements. The CRSP Office carries out this mission by offering several commercial partnership programs that help companies to apply remote sensing technologies in business applications and to buy down the risk of bringing new or improved products and services to market. Through its commercial partnerships, the CRSP seeks to increase the market demand for remote sensing products and related advanced technologies, thus increasing the use and reducing the cost of spatial information.

Institutional issues affecting the integration and use of remotely sensed data and geographic information systems

USGS Publications Warehouse

Lauer, D.T.; Estes, J.E.; Jensen, J.R.; Greenlee, D.D.

1991-01-01

The developers as well as the users of remotely sensed data and geographic information system (GIS) techniques are associated with nearly all types of institutions in government, industry, and academia. Individuals in these various institutions often find the barriers to accepting remote sensing and GIS are not necessarily technical in nature, but can be attributed to the institutions themselves. Several major institutional issues that affect the technologies of remote sensing and GIS are data availability, data marketing and costs, equipment availability and costs, standards and practices, education and training, and organizational infrastructures. Not only are problems associated with these issues identified, but needs and opportunities also are discussed. -from Authors

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

NASA applications project in Miami County, Indiana

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.; Fernandez, R. Norberto; Lozano-Garcia, D. Fabian

1990-01-01

This project was designed to acquaint county government officials and their clientele with remote sensing and geographic information systems (GIS) products that contain information about land conditions and land use. The specific project objectives are: (1) to investigate the feasibility of using remotely sensed data to identify and quantify specific land cover categories and conditions for purposes of tax assessment, cropland area measurements, and land use evaluation; (2) to evaluate the use of remotely sensed data to assess soil resources and conditions which affect productivity; (3) to investigate the use of satellite remote sensing data as an aid in assessing soil management practices; and (4) to evaluate the market potential of products derived from the above projects.

Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

NASA Astrophysics Data System (ADS)

Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

2015-05-01

Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

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.

Needs Assessment for the Use of NASA Remote Sensing Data for Regulatory Water Quality

NASA Technical Reports Server (NTRS)

Spiering, Bruce; Underwood, Lauren

2010-01-01

This slide presentation reviews the assessment of the needs that NASA can use for the remote sensing of water quality. The goal of this project is to provide information for decision-making activities (water quality standards) using remotely sensed/satellite based water quality data from MODIS and Landsat data.

Remote sensing procurement package: A technical guide for state and local governments

NASA Technical Reports Server (NTRS)

1981-01-01

The guide provides the tools and techniques for procuring remote sensing products and services. It is written for administrators, procurement officials and line agency staff who are directly involved in identifying information needs; defining remote sensing project requirements; soliciting and evaluating contract responses and negotiating, awarding, and administering contracts.

Landsat's role in ecological applications of remote sensing.

Treesearch

Warren B. Cohen; Samuel N. Goward

2004-01-01

Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

75 FR 39246 - Agency Information Collection Activities; Submission to OMB for Review and Approval; Comment...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... estimates. An innovative feature of this project will be the use of roadside remote-sensing measurements to...). The acquisition of remote-sensing measurements for hydrocarbons, carbon-monoxide, and oxides of... fleet. Research questions for the project include: (1) Can remote-sensing be used as a reliable index of...

Secure distribution for high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Liu, Jin; Sun, Jing; Xu, Zheng Q.

2010-09-01

The use of remote sensing images collected by space platforms is becoming more and more widespread. The increasing value of space data and its use in critical scenarios call for adoption of proper security measures to protect these data against unauthorized access and fraudulent use. In this paper, based on the characteristics of remote sensing image data and application requirements on secure distribution, a secure distribution method is proposed, including users and regions classification, hierarchical control and keys generation, and multi-level encryption based on regions. The combination of the three parts can make that the same remote sensing images after multi-level encryption processing are distributed to different permission users through multicast, but different permission users can obtain different degree information after decryption through their own decryption keys. It well meets user access control and security needs in the process of high resolution remote sensing image distribution. The experimental results prove the effectiveness of the proposed method which is suitable for practical use in the secure transmission of remote sensing images including confidential information over internet.

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

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

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

1988-01-01

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

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?

Research on enhancing the utilization of digital multispectral data and geographic information systems in global habitability studies

NASA Technical Reports Server (NTRS)

Martinko, E. A.; Merchant, J. W.

1986-01-01

The University of Kansas Applied Remote Sensing (KARS) program is engaged in a continuing long term research and development effort designed to reveal and facilitate new applications of remote sensing technology for decision makers in governmental agencies and private firms. Some objectives of the program follows. The development of new modes of analyzing multispectral scanner, aerial camera, thermal scanner, and radar data, singly or in concert in order to more effectively use these systems. Merge data derived from remote sensing with data derived from conventional sources in geographic information systems to facilitate better environmental planning. Stimulation of the application of the products of remote sensing systems to problems of resource management and environmental quality now being addressed in NASA's Global Habitability directive. The application of remote sensing techniques and analysis and geographic information systems technology to the solution of significant concerns of state and local officials and private industry. The guidance, assistance and stimulation of faculty, staff and students in the utilization of information from the Earth Resources Satellite (LANDSAT) and Aircraft Programs of NASA in research, education, and public service activities carried at the University of Kansas.

Advanced Remote Sensing Research

USGS Publications Warehouse

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).

Remote sensing in the coastal and marine environment. Proceedings of the US North Atlantic Regional Workshop

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.

Activities of the Remote Sensing Information Sciences Research Group

NASA Technical Reports Server (NTRS)

Estes, J. E.; Botkin, D.; Peuquet, D.; Smith, T.; Star, J. L. (Principal Investigator)

1984-01-01

Topics on the analysis and processing of remotely sensed data in the areas of vegetation analysis and modelling, georeferenced information systems, machine assisted information extraction from image data, and artificial intelligence are investigated. Discussions on support field data and specific applications of the proposed technologies are also included.

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Kempler, Steven

2007-01-01

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Interfacing geographic information systems and remote sensing for rural land-use analysis

NASA Technical Reports Server (NTRS)

Nellis, M. Duane; Lulla, Kamlesh; Jensen, John

1990-01-01

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

Radio frequency security system, method for a building facility or the like, and apparatus and methods for remotely monitoring the status of fire extinguishers

DOEpatents

Runyon, Larry [Richland, WA; Gunter, Wayne M [Richland, WA; Gilbert, Ronald W [Gilroy, CA

2006-07-25

A system for remotely monitoring the status of one or more fire extinguishers includes means for sensing at least one parameter of each of the fire extinguishers; means for selectively transmitting the sensed parameters along with information identifying the fire extinguishers from which the parameters were sensed; and means for receiving the sensed parameters and identifying information for the fire extinguisher or extinguishers at a common location. Other systems and methods for remotely monitoring the status of multiple fire extinguishers are also provided.

Information Extraction of Tourist Geological Resources Based on 3d Visualization Remote Sensing Image

NASA Astrophysics Data System (ADS)

Wang, X.

2018-04-01

Tourism geological resources are of high value in admiration, scientific research and universal education, which need to be protected and rationally utilized. In the past, most of the remote sensing investigations of tourism geological resources used two-dimensional remote sensing interpretation method, which made it difficult for some geological heritages to be interpreted and led to the omission of some information. This aim of this paper is to assess the value of a method using the three-dimensional visual remote sensing image to extract information of geological heritages. skyline software system is applied to fuse the 0.36 m aerial images and 5m interval DEM to establish the digital earth model. Based on the three-dimensional shape, color tone, shadow, texture and other image features, the distribution of tourism geological resources in Shandong Province and the location of geological heritage sites were obtained, such as geological structure, DaiGu landform, granite landform, Volcanic landform, sandy landform, Waterscapes, etc. The results show that using this method for remote sensing interpretation is highly recognizable, making the interpretation more accurate and comprehensive.

Remote Sensing Information Gateway (RSIG3D) Fact Sheet

EPA Pesticide Factsheets

The Remote Sensing Information Gateway-3D (RSIG3D) is a free and downloadable application that provides easy and secure access to petabytes (millions of gigabytes) of atmospheric data that can be used to study complex air quality issues.

EPIC'S NEW REMOTE SENSING DATA AND INFORMATION TOOLS AVAILABLE FOR EPA CUSTOMERS

EPA Science Inventory

EPIC's New Remote Sensing Data and Information Tools Available for EPA Customers Donald Garofalo Environmental Photographic Interpretation Center (EPIC) Landscape Ecology Branch Environmental Sciences Division National Exposure Research Laboratory

Several new too...

Remote sensing - A new view for public health

NASA Technical Reports Server (NTRS)

Morrison, D. R.; Barnes, C. M.; Fuller, C. E.

1973-01-01

It is shown that the technology of remote sensing can be of great importance to the field of public health. This possibility is based on the deepened understanding of the biologies and ecologies of the vector/organism/host interelationships of arthropod-, soil-, and water-borne diseases to result from the information that remote sensing can provide.

Monitoring landscape level processes using remote sensing of large plots

Treesearch

Raymond L. Czaplewski

1991-01-01

Global and regional assessaents require timely information on landscape level status (e.g., areal extent of different ecosystems) and processes (e.g., changes in land use and land cover). To measure and understand these processes at the regional level, and model their impacts, remote sensing is often necessary. However, processing massive volumes of remotely sensing...

76 FR 69760 - Agency Information Collection Activities: The William T. Pecora Award Application and Nomination...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-09

... toward understanding the earth by means of remote sensing. The award is sponsored jointly by the... program for civil remote sensing of the earth from space. The purpose of the award is to recognize individuals or groups working in the field of remote sensing of the earth. National and international...

76 FR 50753 - Agency Information Collections Activities; The Pecora Award; Application and Nomination Process

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-16

... groups that make outstanding contributions toward understanding the earth by means of remote sensing. The... motivating force behind the establishment of a program for civil remote sensing of the earth from space. The purpose of the award is to recognize individuals or groups working in the field of remote sensing of the...

The impact of remote sensing on United States' geography: The past in perspective, present realities, future potentials

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Simonett, D. S.

1977-01-01

The use of remotely sensed data by cartographers and other physical geographers is reviewed. The current status of remote sensing in the academic, governmental, and private sector is assessed, as well as its capability for providing information within the context of the explanatory forms used by geographers.

CRESTA : consortium on remote sensing of freight flows in congested border crossings and work zones.

DOT National Transportation Integrated Search

2011-03-01

"The objectives of this project were to develop and demonstrate the use of remote sensing and : geospatial information technologies to provide useful information for applications related to : the times trucks incur in various activities (activity...

The Increasing Use of Remote Sensing Data in Studying the Climatological Impacts on Public Health

NASA Astrophysics Data System (ADS)

Kempler, S.; Benedict, K. K.; Ceccato, P.; Golden, M.; Maxwell, S.; Morain, S.; Soebiyanto, R.; Tong, D.

2011-12-01

One of the most fortunate outcomes of the capture and transformation of remote sensing data into applied information is their usefulness and impacts to better understanding climatological impacts on public health. Today, with petabytes of remote sensing data providing global coverage of climatological parameters, public health research and policy decision makers have an unprecedented (and growing) data record that relates the effects of climatic parameters, such as rainfall, heat, soil moisture, etc. to incidences and spread of disease, as well as predictive modeling. In addition, tools and services that specifically serve public health researchers and respondents have grown in response to the needs of the these information users. This presentation provides: A perspective of the use of remote sensing data in public health research; NASA funded systems developed to facilitate specific public health decision and public support services, and: Insights on remote sensing data and information services that are available for public health studies and decision making. After providing a review of the use of remote sensing data, the following specific services will be discussed: - Rainfall, Vegetation and Water Bodies Monitoring for Malaria Surveillance - Heat Evaluation and Assessment - Multi-resolution Nested Dust Forecast - Socioeconomic Data and Application Center (SEDAC) Health Related Data and Services - Goddard Earth Sciences Data and Information Services Center (GES DISC) Health Related Data and Services The purpose of this presentation is to provide a (strong) flavor of the data and information services available to public health research and decision making, to invoke new ways of thinking about how public health work can be accomplished, and stimulate new ideas on how information services can be further utilized.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

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

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 .

Remote sensing and aerial application

USDA-ARS?s Scientific Manuscript database

With the increasing need for global food production in the presence of dwindling productive acres, the business of modern agriculture needs to use all possible information available to maximize production. One tool that is being used to obtain this information is remote sensing. Any crop disease o...

High resolution remote sensing information identification for characterizing uranium mineralization setting in Namibia

NASA Astrophysics Data System (ADS)

Zhang, Jie-Lin; Wang, Jun-hu; Zhou, Mi; Huang, Yan-ju; Xuan, Yan-xiu; Wu, Ding

2011-11-01

The modern Earth Observation System (EOS) technology takes important role in the uranium geological exploration, and high resolution remote sensing as one of key parts of EOS is vital to characterize spectral and spatial information of uranium mineralization factors. Utilizing satellite high spatial resolution and hyperspectral remote sensing data (QuickBird, Radarsat2, ASTER), field spectral measurement (ASD data) and geological survey, this paper established the spectral identification characteristics of uranium mineralization factors including six different types of alaskite, lower and upper marble of Rössing formation, dolerite, alkali metasomatism, hematization and chloritization in the central zone of Damara Orogen, Namibia. Moreover, adopted the texture information identification technology, the geographical distribution zones of ore-controlling faults and boundaries between the different strata were delineated. Based on above approaches, the remote sensing geological anomaly information and image interpretation signs of uranium mineralization factors were extracted, the metallogenic conditions were evaluated, and the prospective areas have been predicted.

High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

PubMed

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

Remote sensing and GIS-based prediction and assessment of copper-gold resources in Thailand

NASA Astrophysics Data System (ADS)

Yang, Shasha; Wang, Gongwen; Du, Wenhui; Huang, Luxiong

2014-03-01

Quantitative integration of geological information is a frontier and hotspot of prospecting decision research in the world. The forming process of large scale Cu-Au deposits is influenced by complicated geological events and restricted by various geological factors (stratum, structure and alteration). In this paper, using Thailand's copper-gold deposit district as a case study, geological anomaly theory is used along with the typical copper and gold metallogenic model, ETM+ remote sensing images, geological maps and mineral geology database in study area are combined with GIS technique. These techniques create ore-forming information such as geological information (strata, line-ring faults, intrusion), remote sensing information (hydroxyl alteration, iron alteration, linear-ring structure) and the Cu-Au prospect targets. These targets were identified using weights of evidence model. The research results show that the remote sensing and geological data can be combined to quickly predict and assess for exploration of mineral resources in a regional metallogenic belt.

Remote sensing impact on corridor selection and placement

NASA Technical Reports Server (NTRS)

Thomson, F. J.; Sellman, A. N.

1975-01-01

Computer-aided corridor selection techniques, utilizing digitized data bases of socio-economic, census, and cadastral data, and developed for highway corridor routing are considered. Land resource data generated from various remote sensing data sources were successfully merged with the ancillary data files of a corridor selection model and prototype highway corridors were designed using the combined data set. Remote sensing derived information considered useful for highway corridor location, special considerations in geometric correction of remote sensing data to facilitate merging it with ancillary data files, and special interface requirements are briefly discussed.

Airborne and satellite remote sensors for precision agriculture

USDA-ARS?s Scientific Manuscript database

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

Remote Sensing by Satellite for Environmental Education: A Survey and a Proposal for Teaching at Upper Secondary and University Level.

ERIC Educational Resources Information Center

Bosler, Ulrich

Knowledge of the environment has grown to such an extent that information technology (IT) is essential to make sense of the available data. An example of this is remote sensing by satellite. In recent years this field has grown in importance and remote sensing is used for a range of uses including the automatic survey of wheat yields in North…

The ASPRS Remote Sensing Industry Forecast: Phase II & III - Digital Sensor Compilation

NASA Technical Reports Server (NTRS)

Mondello, Charles

2007-01-01

In August 1999, ASPRS and NASA's (then) Commercial Remote Sensing Program (CRSP) entered into a 5-year Space Act Agreement (SAA), combining resources and expertise to: (a) Baseline the Remote Sensing Industry (RSI) based on GEIA Model; (b) Develop a 10-Year RSI market forecast and attendant processes; and (c) Provide improved information for decision makers.

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.

A thermal-based remote sensing modeling system for estimating daily evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared (TIR) remote sensing of land surface temperature (LST) provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition as well as providing useful information for constraining prognostic land surface models. This presentation d...

Application of remote sensing and Geographic Information Systems to ecosystem-based urban natural resource management

Treesearch

Xiaohui Zhang; George Ball; Eve Halper

2000-01-01

This paper presents an integrated system to support urban natural resource management. With the application of remote sensing (RS) and geographic information systems (GIS), the paper emphasizes the methodology of integrating information technology and a scientific basis to support ecosystem-based management. First, a systematic integration framework is developed and...

Remote Sensing in Agriculture: An Introductory Review.

ERIC Educational Resources Information Center

Curran, Paul J.

1987-01-01

Discusses the use of remote sensing techniques to obtain locational, estimated, and mapped information at the scales varying from individual fields and farms, to entire continents and the world. (AEM)

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.

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

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.

Hyperspectral sensing of forests

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash

2007-11-01

Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.

Health assessment and risk mitigation of railroad networks exposed to natural hazards using commercial remote sensing and spatial information technologies.

DOT National Transportation Integrated Search

2017-05-31

The overarching goal of this project was to integrate data from commercial remote sensing and spatial information (CRS&SI) technologies to create a novel data-driven decision making framework that empowers the railroad industry to monitor, assess, an...

Background and principle applications of remote sensing in Mexico

NASA Technical Reports Server (NTRS)

Perez, J. A. D.

1978-01-01

Remote sensing, or the collection of information from objectives at a distance, crystallizes the interest in implementing techniques which assist in the search for solutions to the problems raised by the detection, exploitation, and conservation of the natural resources of the earth. An attempt is made to present an overview of the studies and achievements which have been obtained with remote sensing in Mexico.

Up Close from Afar: Using Remote Sensing To Teach the American Landscape. Pathways in Geography Series, Title No. 8.

ERIC Educational Resources Information Center

Baumann, Paul R., Ed.

This teaching guide offers educators glimpses into the value of remote sensing, the process of observing and analyzing the earth from a distance. Remote sensing provides information in forms to see spatial patterns over large areas in a more realistic way than thematic maps and allows a macro-scale look at global problems. The six instructional…

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

Treesearch

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

2010-01-01

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

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

NASA Technical Reports Server (NTRS)

Menenti, M.

1992-01-01

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

Remote sensing education for the Earth sciences: The University of Georgia experience

NASA Technical Reports Server (NTRS)

Welch, R.

1981-01-01

A prospectus is presented of the following courses offered by the Department of Geography: (1) use and interpretation of aerial photographs; (2) advanced photogrammetry; (3) remote sensing of environment; (4) geographic information systems; and (5) directed problems in the remote sensing of the environment. In addition to the course content and objectives, the various equipments available for student training and use are listed.

Agricultural Research Service research highlights in remote sensing for calendar year 1980

NASA Technical Reports Server (NTRS)

Ritchie, J. C. (Principal Investigator)

1981-01-01

The AR research mission in remote sensing is to develop the basic understanding of the soil plant animal atmosphere continuum in agricultural ecosystems and to determine when remotely sensed data can be used to provide information about these agricultural ecosystems. A brief statement of the significant results of each project is given. A list of 1980 publication and location contacts is also given.

76 FR 8784 - Notice of Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-15

... utilization of NASA remote sensing products. Outreach activities will be in the form of workshops. Data...: NASA Applied Sciences Remote Sensing Outreach. OMB Number: 2700-XXXX. Type of review: New Collection...

Applications of remote sensor data to geologic and economic analysis on the Bonanza Test Site, Colorado

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 inputs to landscape models which predict future spatial land use patterns for hydrologic models

NASA Technical Reports Server (NTRS)

Miller, L. D.; Tom, C.; Nualchawee, K.

1977-01-01

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Remote sensing information sciences research group

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1988-01-01

Research conducted under this grant was used to extend and expand existing remote sensing activities at the University of California, Santa Barbara in the areas of georeferenced information systems, matching assisted information extraction from image data and large spatial data bases, artificial intelligence, and vegetation analysis and modeling. The research thrusts during the past year are summarized. The projects are discussed in some detail.

Analyzing long-term changes in vegetation with geographic information system and remotely sensed data

Treesearch

Louis. R. Iverson; Paul. G. Risser; Paul. G. Risser

1987-01-01

Geographic information systems and remote sensing techniques are powerful tools in the analysis of long-term changes in vegetation and land use, especially because spatial information from two or more time intervals can be compared more readily than by manual methods. A primary restriction is the paucity of data that has been digitized from earlier periods. The...

Construction of Green Tide Monitoring System and Research on its Key Techniques

NASA Astrophysics Data System (ADS)

Xing, B.; Li, J.; Zhu, H.; Wei, P.; Zhao, Y.

2018-04-01

As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this study, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of mathematical morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Users report for the Northern Great Plains.

NASA Technical Reports Server (NTRS)

Waltz, F. A.; Myers, V. I.; Heinemann, L. R.

1973-01-01

The applications of remote-sensing techniques offer new approaches to many of the present-day problems encountered by various state agencies in South Dakota. The study was completed in three phases. The first report presented the information needs of the state agencies and educational efforts; the second defined the data handling procedures for fulfilling the applications; and the third phase was a development of a dynamic information dissemination plan on a state-wide basis. Aircraft data, satellite imagery, and other remotely sensed information are valuable for decision-making processes. A design for an organization to acquire for the state the advantages of remote-sensing systems for resources research and management has been developed.

Remote Sensing Information Classification

NASA Technical Reports Server (NTRS)

Rickman, Douglas L.

2008-01-01

This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

15 CFR 960.5 - Confidentiality of information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.5 Confidentiality of... thirty (30) days of the issuance of a license to operate a remote sensing space system, the licensee...

15 CFR 960.5 - Confidentiality of information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.5 Confidentiality of... thirty (30) days of the issuance of a license to operate a remote sensing space system, the licensee...

15 CFR 960.5 - Confidentiality of information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.5 Confidentiality of... thirty (30) days of the issuance of a license to operate a remote sensing space system, the licensee...

15 CFR 960.5 - Confidentiality of information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.5 Confidentiality of... thirty (30) days of the issuance of a license to operate a remote sensing space system, the licensee...

15 CFR 960.5 - Confidentiality of information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.5 Confidentiality of... thirty (30) days of the issuance of a license to operate a remote sensing space system, the licensee...

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;

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.

A proposal for continuation of support for the application of remotely sensed data to state and regional problems. Part 1: Technical proposal

NASA Technical Reports Server (NTRS)

1981-01-01

The objectives, procedures, accomplishments, plans, and ultimate uses of information from current projects at the Mississippi Remote Sensing Center are discussed for the following applications: (1) land use planning; (2) strip mine inventory and reclamation; (3) biological management for white tailed deer; (4) forest habitats in potential lignite areas; (5) change discrimination in gravel operations; (6) discrimination of freshwater wetlands for inventory and monitoring; and (7) remote sensing data analysis support systems. The initiation of a conceptual design for a LANDSAT based, state wide information system is proposed.

The application of remote sensing to resource management and environmental quality programs in Kansas

NASA Technical Reports Server (NTRS)

Barr, B. G.; Martinko, E. A. (Principal Investigator)

1983-01-01

The activities of the Kansas Applied Remote Sensing (KARS) Program during the period April 1, 1982 through Marsh 31, 1983 are described. The most important work revolved around the Kansas Interagency Task Force on Applied Remote Sensing and its efforts to establish an operational service oriented remote sensing program in Kansas state government. Concomitant with this work was the upgrading of KARS capabilities to process data for state agencies through the vehicle of a low cost digital data processing system. The KARS Program continued to take an active role in irrigation mapping. KARS is now integrating data acquired through analysis of LANDSAT into geographic information systems designed for evaluating groundwater resources. KARS also continues to work at the national level on the national inventory of state natural resources information systems.

Remote sensing for urban planning

NASA Technical Reports Server (NTRS)

Davis, Bruce A.; Schmidt, Nicholas; Jensen, John R.; Cowen, Dave J.; Halls, Joanne; Narumalani, Sunil; Burgess, Bryan

1994-01-01

Utility companies are challenged to provide services to a highly dynamic customer base. With factory closures and shifts in employment becoming a routine occurrence, the utility industry must develop new techniques to maintain records and plan for expected growth. BellSouth Telecommunications, the largest of the Bell telephone companies, currently serves over 13 million residences and 2 million commercial customers. Tracking the movement of customers and scheduling the delivery of service are major tasks for BellSouth that require intensive manpower and sophisticated information management techniques. Through NASA's Commercial Remote Sensing Program Office, BellSouth is investigating the utility of remote sensing and geographic information system techniques to forecast residential development. This paper highlights the initial results of this project, which indicate a high correlation between the U.S. Bureau of Census block group statistics and statistics derived from remote sensing data.

Disseminating technological information on remote sensing to potential users

NASA Technical Reports Server (NTRS)

Russell, J. D.; Lindenlaub, J. C.

1977-01-01

The Laboratory for Applications of Remote Sensing developed materials and programs which range from short tutorial brochures to post-doctoral research programs which may span several years. To organize both the content and the instructional techniques, a matrix of instructional materials was conceptualized. Each row in the matrix represents a subject area in remote sensing and each column in the matrix represents a different type media or instructional strategy.

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

NASA Astrophysics Data System (ADS)

Dong, Chunyu

2018-06-01

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

Remote sensing education and Internet/World Wide Web technology

USGS Publications Warehouse

Griffith, J.A.; Egbert, S.L.

2001-01-01

Remote sensing education is increasingly in demand across academic and professional disciplines. Meanwhile, Internet technology and the World Wide Web (WWW) are being more frequently employed as teaching tools in remote sensing and other disciplines. The current wealth of information on the Internet and World Wide Web must be distilled, nonetheless, to be useful in remote sensing education. An extensive literature base is developing on the WWW as a tool in education and in teaching remote sensing. This literature reveals benefits and limitations of the WWW, and can guide its implementation. Among the most beneficial aspects of the Web are increased access to remote sensing expertise regardless of geographic location, increased access to current material, and access to extensive archives of satellite imagery and aerial photography. As with other teaching innovations, using the WWW/Internet may well mean more work, not less, for teachers, at least at the stage of early adoption. Also, information posted on Web sites is not always accurate. Development stages of this technology range from on-line posting of syllabi and lecture notes to on-line laboratory exercises and animated landscape flyovers and on-line image processing. The advantages of WWW/Internet technology may likely outweigh the costs of implementing it as a teaching tool.

Potential for a remote-sensing-aided forest resource survey for the whole globe

Treesearch

E. Tomppo; R. L. Czaplewski

2002-01-01

The Global Forest Resources Assessment 2000 (FRA 2000) relied primarily on information provided by countries, but FAO also conducted a remote-sensing study of tropical forests to complement country information and to bolster understanding of land-cover change processes in the tropics, especially deforestation, forest degradation, fragmentation and shifting cultivation...

Integration of remote sensing based surface information into a three-dimensional microclimate model

NASA Astrophysics Data System (ADS)

Heldens, Wieke; Heiden, Uta; Esch, Thomas; Mueller, Andreas; Dech, Stefan

2017-03-01

Climate change urges cities to consider the urban climate as part of sustainable planning. Urban microclimate models can provide knowledge on the climate at building block level. However, very detailed information on the area of interest is required. Most microclimate studies therefore make use of assumptions and generalizations to describe the model area. Remote sensing data with area wide coverage provides a means to derive many parameters at the detailed spatial and thematic scale required by urban climate models. This study shows how microclimate simulations for a series of real world urban areas can be supported by using remote sensing data. In an automated process, surface materials, albedo, LAI/LAD and object height have been derived and integrated into the urban microclimate model ENVI-met. Multiple microclimate simulations have been carried out both with the dynamic remote sensing based input data as well as with manual and static input data to analyze the impact of the RS-based surface information and the suitability of the applied data and techniques. A valuable support of the integration of the remote sensing based input data for ENVI-met is the use of an automated processing chain. This saves tedious manual editing and allows for fast and area wide generation of simulation areas. The analysis of the different modes shows the importance of high quality height data, detailed surface material information and albedo.

Future use of digital remote sensing data

NASA Technical Reports Server (NTRS)

Spann, G. W.; Jones, N. L.

1978-01-01

Users of remote sensing data are increasingly turning to digital processing techniques for the extraction of land resource, environmental, and natural resource information. This paper presents the results of recent and ongoing research efforts sponsored, in part, by NASA/Marshall Space Flight Center on the current uses of and future needs for digital remote sensing data. An ongoing investigation involves a comprehensive survey of capabilities for digital Landsat data use in the Southeastern U.S. Another effort consists of an evaluation of future needs for digital remote sensing data by federal, state, and local governments and the private sector. These needs are projected into the 1980-1985 time frame. Furthermore, the accelerating use of digital remote sensing data is not limited to the U.S. or even to the developed countries of the world.

National Satellite Land Remote Sensing Data Archive

USGS Publications Warehouse

Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

2013-01-01

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

A Prototype Hydrologic Observatory for the Neuse River Basin Using Remote Sensing Data as a Part of the CUAHSI-HIS Effort

NASA Astrophysics Data System (ADS)

Kanwar, R.; Narayan, U.; Lakshmi, V.

2005-12-01

Remote sensing has the potential to immensely advance the science and application of hydrology as it provides multi-scale and multi-temporal measurements of several hydrologic parameters. There is a wide variety of remote sensing data sources available to a hydrologist with a myriad of data formats, access techniques, data quality issues and temporal and spatial extents. It is very important to make data availability and its usage as convenient as possible for potential users. The CUAHSI Hydrologic Information System (HIS) initiative addresses this issue of better data access and management for hydrologists with a focus on in-situ data, that is point measurements of water and energy fluxes which make up the 'more conventional' sources of hydrologic data. This paper explores various sources of remotely sensed hydrologic data available, their data formats and volumes, current modes of data acquisition by end users, metadata associated with data itself, and requirements from potential data models that would allow a seamless integration of remotely sensed hydrologic observations into the Hydrologic Information System. Further, a prototype hydrologic observatory (HO) for the Neuse River Basin is developed using surface temperature, vegetation indices and soil moisture estimates available from remote sensing. The prototype (HO) uses the CUAHSI digital library system (DLS) on the back (server) end. On the front (client) end, a rich visual environment has been developed in order to provide better decision making tools in order to make an optimal choice in the selection of remote sensing data for a particular application. An easy point and click interface to the remote sensing data is also implemented for common users who are just interested in location based query of hydrologic variable values.

Advancements in Open Geospatial Standards for Photogrammetry and Remote Sensing from Ogc

NASA Astrophysics Data System (ADS)

Percivall, George; Simonis, Ingo

2016-06-01

The necessity of open standards for effective sharing and use of remote sensing continues to receive increasing emphasis in policies of agencies and projects around the world. Coordination on the development of open standards for geospatial information is a vital step to insure that the technical standards are ready to support the policy objectives. The mission of the Open Geospatial Consortium (OGC) is to advance development and use of international standards and supporting services that promote geospatial interoperability. To accomplish this mission, OGC serves as the global forum for the collaboration of geospatial data / solution providers and users. Photogrammetry and remote sensing are sources of the largest and most complex geospatial information. Some of the most mature OGC standards for remote sensing include the Sensor Web Enablement (SWE) standards, the Web Coverage Service (WCS) suite of standards, encodings such as NetCDF, GMLJP2 and GeoPackage, and the soon to be approved Discrete Global Grid Systems (DGGS) standard. In collaboration with ISPRS, OGC working with government, research and industrial organizations continue to advance the state of geospatial standards for full use of photogrammetry and remote sensing.

Remote Sensing: A valuable tool in the Forest Service decision making process. [in Utah

NASA Technical Reports Server (NTRS)

Stanton, F. L.

1975-01-01

Forest Service studies for integrating remotely sensed data into existing information systems highlight a need to: (1) re-examine present methods of collecting and organizing data, (2) develop an integrated information system for rapidly processing and interpreting data, (3) apply existing technological tools in new ways, and (4) provide accurate and timely information for making right management decisions. The Forest Service developed an integrated information system using remote sensors, microdensitometers, computer hardware and software, and interactive accessories. Their efforts substantially reduce the time it takes for collecting and processing data.

Remote Sensing and the Kyoto Protocol: A Workshop Summary

NASA Technical Reports Server (NTRS)

Rosenqvist, Ake; Imhoff, Marc; Milne, Anthony; Dobson, Craig

2000-01-01

The Kyoto Protocol to the United Nations Framework Convention on Climate Change contains quantified, legally binding commitments to limit or reduce greenhouse gas emissions to 1990 levels and allows carbon emissions to be balanced by carbon sinks represented by vegetation. The issue of using vegetation cover as an emission offset raises a debate about the adequacy of current remote sensing systems and data archives to both assess carbon stocks/sinks at 1990 levels, and monitor the current and future global status of those stocks. These concerns and the potential ratification of the Protocol among participating countries is stimulating policy debates and underscoring a need for the exchange of information between the international legal community and the remote sensing community. On October 20-22 1999, two working groups of the International Society for Photogrammetry and Remote Sensing (ISPRS) joined with the University of Michigan (Michigan, USA) to convene discussions on how remote sensing technology could contribute to the information requirements raised by implementation of, and compliance with, the Kyoto Protocol. The meeting originated as a joint effort between the Global Monitoring Working Group and the Radar Applications Working Group in Commission VII of the ISPRS, co-sponsored by the University of Michigan. Tile meeting was attended by representatives from national government agencies and international organizations and academic institutions. Some of the key themes addressed were: (1) legal aspects of transnational remote sensing in the context of the Kyoto Protocol; (2) a review of the current and future and remote sensing technologies that could be applied to the Kyoto Protocol; (3) identification of areas where additional research is needed in order to advance and align remote sensing technology with the requirements and expectations of the Protocol; and 94) the bureaucratic and research management approaches needed to align the remote sensing community with both the science and policy communities.

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

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

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

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

2010-01-01

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

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

PubMed Central

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

2016-01-01

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

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Change detection from remotely sensed images: From pixel-based to object-based approaches

NASA Astrophysics Data System (ADS)

Hussain, Masroor; Chen, Dongmei; Cheng, Angela; Wei, Hui; Stanley, David

2013-06-01

The appetite for up-to-date information about earth's surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.

Accounting for ecosystem assets using remote sensing in the Colombian Orinoco River Basin lowlands

NASA Astrophysics Data System (ADS)

Vargas, Leonardo; Hein, Lars; Remme, Roy P.

2017-04-01

Worldwide, ecosystem change compromises the supply of ecosystem services (ES). Better managing ecosystems requires detailed information on these changes and their implications for ES supply. Ecosystem accounting has been developed as an environmental-economic accounting system using concepts aligned with the System of National Accounts. Ecosystem accounting requires spatial information from a local to national scale. The objective of this paper is to explore how remote sensing can be used to analyze ecosystems using an accounting approach in the Orinoco River Basin. We assessed ecosystem assets in terms of extent, condition, and capacity to supply ES. We focus on four specific ES: grasslands grazed by cattle, timber harvesting, oil palm fresh fruit bunches harvesting, and carbon sequestration. We link ES with six ecosystem assets: savannahs, woody grasslands, mixed agroecosystems, very dense forests, dense forest, and oil palm plantations. We used remote sensing vegetation and productivity indexes to measure ecosystem assets. We found that remote sensing is a powerful tool to estimate ecosystem extent. The enhanced vegetation index can be used to assess ecosystems condition, and net primary productivity can be used for the assessment of ecosystem assets capacity to supply ES. Integrating remote sensing and ecological information facilitates efficient monitoring of ecosystem assets.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

A new simple concept for ocean colour remote sensing using parallel polarisation radiance

PubMed Central

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.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

Lowe, D. S.; Istvan, L. B.; Roller, N. E.; Sattinger, I. J.; Sellman, A. N.; Wagner, T. W.

1974-01-01

The application of NASA earth resource survey technology to resource management and environmental protection in Michigan was investigated. Remote sensing techniques to aid Michigan government agencies were applied in the following activities: (1) land use inventory and management, (2) great lakes shorelands protection and management, (3) wetlands protection and management, and (4) soil survey. In addition, information was disseminated on remote sensing technology, and advice and assistance was provided to a number of users.

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 sensors and applications in environmental resources mapping and modeling

USGS Publications Warehouse

Melesse, Assefa M.; Weng, Qihao; Thenkabail, Prasad S.; Senay, Gabriel B.

2007-01-01

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling.

14 CFR Appendix A to Part 440 - Information Requirements for Obtaining a Maximum Probable Loss Determination for Licensed or...

Code of Federal Regulations, 2010 CFR

2010-01-01

... payload, including type (e.g., telecommunications, remote sensing), propellants, and hazardous components... description of any payload, including type (e.g., telecommunications, remote sensing), propellants, and...

Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; Xu, Fuxiang; Song, Debin; Zheng, Xiangyu; Chen, Maosi

2017-09-01

This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera) occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1 WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation based on remote sensing and geographic information system technologies. The result shows that unmanned aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva prolifera. The result of this research can provide effective information support for the prevention and control of Ulva prolifera.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

USGS Publications Warehouse

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 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.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

Sattinger, I. J.; Istvan, L. B.; Roller, N. E. G.; Lowe, D. S.

1977-01-01

An extensive program was conducted to establish practical uses of NASA earth resource survey technology in meeting resource management problems throughout Michigan. As a result, a broad interest in and understanding of the usefulness of remote sensing methods was developed and a wide variety of applications was undertaken to provide information needed for informed decision making and effective action.

A 'user friendly' geographic information system in a color interactive digital image processing system environment

NASA Technical Reports Server (NTRS)

Campbell, W. J.; Goldberg, M.

1982-01-01

NASA's Eastern Regional Remote Sensing Applications Center (ERRSAC) has recognized the need to accommodate spatial analysis techniques in its remote sensing technology transfer program. A computerized Geographic Information System to incorporate remotely sensed data, specifically Landsat, with other relevant data was considered a realistic approach to address a given resource problem. Questions arose concerning the selection of a suitable available software system to demonstrate, train, and undertake demonstration projects with ERRSAC's user community. The very specific requirements for such a system are discussed. The solution found involved the addition of geographic information processing functions to the Interactive Digital Image Manipulation System (IDIMS). Details regarding the functions of the new integrated system are examined along with the characteristics of the software.

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

NASA Technical Reports Server (NTRS)

Davis, Frank W.; Quattrochi, Dale A.; Ridd, Merrill K.; Lam, Nina S.-N.; Walsh, Stephen J.

1991-01-01

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Ten ways remote sensing can contribute to conservation

USGS Publications Warehouse

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.

PubMed

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.

Hyperspectral remote sensing of coral reefs: Deriving bathymetry, aquatic optical properties and a benthic spectral unmixing classification using AVIRIS data in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Goodman, James Ansell

My research focuses on the development and application of hyperspectral remote sensing as a valuable component in the assessment and management of coral ecosystems. Remote sensing provides an important quantitative ability to investigate the spatial dynamics of coral health and evaluate the impacts of local, regional and global change on this important natural resource. Furthermore, advances in detector capabilities and analysis methods, particularly with respect to hyperspectral remote sensing, are also increasing the accuracy and level of effectiveness of the resulting data products. Using imagery of Kaneohe Bay and French Frigate Shoals in the Hawaiian Islands, acquired in 2000 by NASA's Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), I developed, applied and evaluated algorithms for analyzing coral reefs using hyperspectral remote sensing data. Research included developing methods for acquiring in situ underwater reflectance, collecting spectral measurements of the dominant bottom components in Kaneohe Bay, applying atmospheric correction and sunglint removal algorithms, employing a semianalytical optimization model to derive bathymetry and aquatic optical properties, and developing a linear unmixing approach for deriving bottom composition. Additionally, algorithm development focused on using fundamental scientific principles to facilitate the portability of methods to diverse geographic locations and across variable environmental conditions. Assessments of this methodology compared favorably with available field measurements and habitat information, and the overall analysis demonstrated the capacity to derive information on water properties, bathymetry and habitat composition. Thus, results illustrated a successful approach for extracting environmental information and habitat composition from a coral reef environment using hyperspectral remote sensing.

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

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

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

Technology Trends and Remote Sensing

NASA Technical Reports Server (NTRS)

Wegener, Steve; Hipskind, R. Stephen (Technical Monitor)

2001-01-01

The science and application of remote sensing is flourishing in the digital age. Geographical information systems can provide a broad range of information tailored to the specific needs of disaster managers. Recent advances in airborne platforms, sensors and information technologies have come together provide the ability to put geo-registered, multispectral imagery on the web in near real-time. Highlights of a demonstration of NASA's First Response Experiment (FiRE) will be presented.

77 FR 4056 - Agency Information Collection Activities: Submitted for Office of Management and Budget (OMB...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-26

... university and State organizations in a ready to use form; and to expand the science of remote sensing... requirements for the National Land Remote Sensing Education, Outreach and Research Activity (NLRSEORA) and...

Proceedings of the National Conference on Energy Resource Management. Volume 1: Techniques, Procedures and Data Bases

NASA Technical Reports Server (NTRS)

Brumfield, J. O. (Editor); Schiffman, Y. M. (Editor)

1982-01-01

Topics dealing with the integration of remotely sensed data with geographic information system for application in energy resources management are discussed. Associated remote sensing and image analysis techniques are also addressed.

Information Processing of Remote-Sensing Data.

ERIC Educational Resources Information Center

Berry, P. A. M.; Meadows, A. J.

1987-01-01

Reviews the current status of satellite remote sensing data, including problems with efficient storage and rapid retrieval of the data, and appropriate computer graphics to process images. Areas of research concerned with overcoming these problems are described. (16 references) (CLB)

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

PubMed

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

2016-01-01

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

GIS Integration for Quantitatively Determining the Capabilities of Five Remote Sensors for Resource Exploration

NASA Technical Reports Server (NTRS)

Pascucci, R. F.; Smith, A.

1982-01-01

To assist the U.S. Geological Survey in carrying out a Congressional mandate to investigate the use of side-looking airborne radar (SLAR) for resources exploration, a research program was conducted to define the contribution of SLAR imagery to structural geologic mapping and to compare this with contributions from other remote sensing systems. Imagery from two SLAR systems and from three other remote sensing systems was interpreted, and the resulting information was digitized, quantified and intercompared using a computer-assisted geographic information system (GIS). The study area covers approximately 10,000 square miles within the Naval Petroleum Reserve, Alaska, and is situated between the foothills of the Brooks Range and the North Slope. The principal objectives were: (1) to establish quantitatively, the total information contribution of each of the five remote sensing systems to the mapping of structural geology; (2) to determine the amount of information detected in common when the sensors are used in combination; and (3) to determine the amount of unique, incremental information detected by each sensor when used in combination with others. The remote sensor imagery that was investigated included real-aperture and synthetic-aperture radar imagery, standard and digitally enhanced LANDSAT MSS imagery, and aerial photos.

[Use of Remote Sensing for Crop and Soil Analysis

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.

1997-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

ADVANCED REMOTE SENSING MONITORING OF MINE WASTE

EPA Science Inventory

The OEI-EAD and NERL-ESD have been cooperating on development of monitoring technologies and research to better use remote sensor-derived information and to ultimately disseminate that information to users. This work has focused on NASA'S airborne advanced remote sensor systems ...

Accounting for ecosystem assets using remote sensing in the Colombian Orinoco River basin lowlands

NASA Astrophysics Data System (ADS)

Vargas, Leonardo; Hein, Lars; Remme, Roy P.

2016-10-01

In many parts of the world, ecosystems change compromises the supply of ecosystem services (ES). Better ecosystem management requires detailed and structured information. Ecosystem accounting has been developed as an information system for ecosystems, using concepts and valuation approaches that are aligned with the System of National Accounts (SNA). The SNA is used to store and analyse economic data, and the alignment of ecosystem accounts with the SNA facilitates the integrated analysis of economic and ecological aspects of ecosystem use. Ecosystem accounting requires detailed spatial information at aggregated scales. The objective of this paper is to explore how remote sensing images can be used to analyse ecosystems using an accounting approach in the Orinoco river basin. We assessed ecosystem assets in terms of extent, condition and capacity to supply ES. We focus on four specific ES: grasslands grazed by cattle, timber and oil palm harvest, and carbon sequestration. We link ES with six ecosystem assets; savannahs, woody grasslands, mixed agro-ecosystems, very dense forests, dense forest and oil palm plantations. We used remote sensing vegetation, surface temperature and productivity indexes to measure ecosystem assets. We found that remote sensing is a powerful tool to estimate ecosystem extent. The enhanced vegetation index can be used to assess ecosystems condition, and net primary productivity can be used for the assessment of ecosystem assets capacity to supply ES. Integrating remote sensing and ecological information facilitates efficient monitoring of ecosystem assets, in particular in data poor contexts.

Meta Data Mining in Earth Remote Sensing Data Archives

NASA Astrophysics Data System (ADS)

Davis, B.; Steinwand, D.

2014-12-01

Modern search and discovery tools for satellite based remote sensing data are often catalog based and rely on query systems which use scene- (or granule-) based meta data for those queries. While these traditional catalog systems are often robust, very little has been done in the way of meta data mining to aid in the search and discovery process. The recently coined term "Big Data" can be applied in the remote sensing world's efforts to derive information from the vast data holdings of satellite based land remote sensing data. Large catalog-based search and discovery systems such as the United States Geological Survey's Earth Explorer system and the NASA Earth Observing System Data and Information System's Reverb-ECHO system provide comprehensive access to these data holdings, but do little to expose the underlying scene-based meta data. These catalog-based systems are extremely flexible, but are manually intensive and often require a high level of user expertise. Exposing scene-based meta data to external, web-based services can enable machine-driven queries to aid in the search and discovery process. Furthermore, services which expose additional scene-based content data (such as product quality information) are now available and can provide a "deeper look" into remote sensing data archives too large for efficient manual search methods. This presentation shows examples of the mining of Landsat and Aster scene-based meta data, and an experimental service using OPeNDAP to extract information from quality band from multiple granules in the MODIS archive.

Dynamic stratification of the landscape of Mexico: analysis of vegetation patterns observed with multitemporal remotely sensed images

Treesearch

Franz Mora; Louis R. Iverson; Louis R. Iverson

1997-01-01

Rapid deforestation in Mexico, when coupled with poor access to current and consistent ecological information across the country underscores the need for an ecological classification system that can be readily updated as new data become available. In this study, regional vegetation resources in Mexico were evaluated using remotely sensed information. Multitemporal...

A Multi-Temporal Remote Sensing Approach to Freshwater Turtle Conservation

NASA Astrophysics Data System (ADS)

Mui, Amy B.

Freshwater turtles are a globally declining taxa, and estimates of population status are not available for many species. Primary causes of decline stem from widespread habitat loss and degradation, and obtaining spatially-explicit information on remaining habitat across a relevant spatial scale has proven challenging. The discipline of remote sensing science has been employed widely in studies of biodiversity conservation, but it has not been utilized as frequently for cryptic, and less vagile species such as turtles, despite their vulnerable status. The work presented in this thesis investigates how multi-temporal remote sensing imagery can contribute key information for building spatially-explicit and temporally dynamic models of habitat and connectivity for the threatened, Blanding's turtle (Emydoidea blandingii) in southern Ontario, Canada. I began with outlining a methodological approach for delineating freshwater wetlands from high spatial resolution remote sensing imagery, using a geographic object-based image analysis (GEOBIA) approach. This method was applied to three different landscapes in southern Ontario, and across two biologically relevant seasons during the active (non-hibernating) period of Blanding's turtles. Next, relevant environmental variables associated with turtle presence were extracted from remote sensing imagery, and a boosted regression tree model was developed to predict the probability of occurrence of this species. Finally, I analysed the movement potential for Blanding's turtles in a disturbed landscape using a combination of approaches. Results indicate that (1) a parsimonious GEOBIA approach to land cover mapping, incorporating texture, spectral indices, and topographic information can map heterogeneous land cover with high accuracy, (2) remote-sensing derived environmental variables can be used to build habitat models with strong predictive power, and (3) connectivity potential is best estimated using a variety of approaches, though accurate estimates across human-altered landscapes is challenging. Overall, this body of work supports the use of remote sensing imagery in species distribution models to strengthen the precision, and power of predictive models, and also draws attention to the need to consider a multi-temporal examination of species habitat requirements.

The Federal Oil Spill Team for Emergency Response Remote Sensing (FOSTERRS)

NASA Astrophysics Data System (ADS)

Stough, T.; Jones, C. E.; Leifer, I.; Lindsay, F. E.; Murray, J. J.; Ramirez, E. M.; Salemi, A.; Streett, D.

2014-12-01

Oil spills can cause enormous ecological and economic devastation, necessitating application of the best science and technology available, for which remote sensing plays a critical role in detection and monitoring of oil spills. The FOSTERRS interagency working group seeks to ensure that during an oil spill, remote sensing assets (satellite/aircraft) and analysis techniques are quickly, effectively and seamlessly available to oil spills responders. FOSTERRS enables cooperation between agencies with core environmental remote sensing assets and capabilities and academic and industry experts to act as an oil spill remote sensing information clearinghouse. The US government and its collaborators have a broad variety of aircraft and satellite sensors, imagery interrogation techniques and other technology that can provide indispensable remote sensing information to agencies, emergency responders and the public during an oil spill. Specifically, FOSTERRS will work to ensure that (1) suitable aircraft and satellite imagery and radar observations are quickly made available in a manner that can be integrated into oil spill detection and mitigation efforts, (2) existing imagery interrogation techniques are in the hands of those who will provide the 24 x 7 operational support and (3) efforts are made to develop new technology where the existing techniques do not provide oil spills responders with important information they need. The FOSTERRS mission goal places it in an ideal place for identification of critical technological needs, and identifying bottlenecks in technology acceptance. The core FOSTERRS team incorporates representation for operations and science for agencies with relevant instrumental and platform assets (NASA, NOAA, USGS, NRL). FOSTERRS membership will open to a wide range of end-user agencies and planned observer status from industry and academic experts, and eventually international partners. Through these collaborations, FOSTERRS facilitates interagency and cooperation and communication to the larger end-user community on remote sensing and its best use.

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

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

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

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

NASA Technical Reports Server (NTRS)

Tsang, Leung; Hwang, Jenq-Neng

1996-01-01

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Quantitative interpretation of Great Lakes remote sensing data

NASA Technical Reports Server (NTRS)

Shook, D. F.; Salzman, J.; Svehla, R. A.; Gedney, R. T.

1980-01-01

The paper discusses the quantitative interpretation of Great Lakes remote sensing water quality data. Remote sensing using color information must take into account (1) the existence of many different organic and inorganic species throughout the Great Lakes, (2) the occurrence of a mixture of species in most locations, and (3) spatial variations in types and concentration of species. The radiative transfer model provides a potential method for an orderly analysis of remote sensing data and a physical basis for developing quantitative algorithms. Predictions and field measurements of volume reflectances are presented which show the advantage of using a radiative transfer model. Spectral absorptance and backscattering coefficients for two inorganic sediments are reported.

Remote Sensing Sensors and Applications in Environmental Resources Mapping and Modelling

PubMed Central

Melesse, Assefa M.; Weng, Qihao; S.Thenkabail, Prasad; Senay, Gabriel B.

2007-01-01

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling. PMID:28903290

Development of multi-mission satellite data systems at the German Remote Sensing Data Centre

NASA Astrophysics Data System (ADS)

Lotz-Iwen, H. J.; Markwitz, W.; Schreier, G.

1998-11-01

This paper focuses on conceptual aspects of the access to multi-mission remote sensing data by online catalogue and information systems. The system ISIS of the German Remote Sensing Data Centre is described as an example of a user interface to earth observation data. ISIS has been designed to support international scientific research as well as operational applications by offering online access to the database via public networks. It provides catalogue retrieval, visualisation and transfer of image data, and is integrated in international activities dedicated to catalogue and archive interoperability. Finally, an outlook is given on international projects dealing with access to remote sensing data in distributed archives.

Remote sensing monitoring and driving force analysis to forest and greenbelt in Zhuhai

NASA Astrophysics Data System (ADS)

Yuliang Qiao, Pro.

As an important city in the southern part of Chu Chiang Delta, Zhuhai is one of the four special economic zones which are opening up to the outside at the earliest in China. With pure and fresh air and trees shading the street, Zhuhai is a famous beach port city which is near the mountain and by the sea. On the basis of Garden City, the government of Zhuhai decides to build National Forest City in 2011, which firstly should understand the situation of greenbelt in Zhuhai in short term. Traditional methods of greenbelt investigation adopt the combination of field surveying and statistics, whose efficiency is low and results are not much objective because of artificial influence. With the adventure of the information technology such as remote sensing to earth observation, especially the launch of many remote sensing satellites with high resolution for the past few years, kinds of urban greenbelt information extraction can be carried out by using remote sensing technology; and dynamic monitoring to spatial pattern evolvement of forest and greenbelt in Zhuhai can be achieved by the combination of remote sensing and GIS technology. Taking Landsat5 TM data in 1995, Landsat7 ETM+ data in 2002, CCD and HR data of CBERS-02B in 2009 as main information source, this research firstly makes remote sensing monitoring to dynamic change of forest and greenbelt in Zhuhai by using the combination of vegetation coverage index and three different information extraction methods, then does a driving force analysis to the dynamic change results in 3 months. The results show: the forest area in Zhuhai shows decreasing tendency from 1995 to 2002, increasing tendency from 2002 to 2009; overall, the forest area show a small diminution tendency from 1995 to 2009. Through the comparison to natural and artificial driving force, the artificial driving force is the leading factor to the change of forest and greenbelt in Zhuhai. The research results provide a timely and reliable scientific basis for the Zhuhai Government in building National Forest City. Keywords: forest and greenbelt; remote sensing; dynamic monitoring; driving force; vegetation coverage

Information mining in remote sensing imagery

NASA Astrophysics Data System (ADS)

Li, Jiang

The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and fuzzy normalized difference vegetation index (NDVI) pattern mining. The study results show the effectiveness of the proposed system prototype and the potentials for other applications in remote sensing.

Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

NASA Astrophysics Data System (ADS)

Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

2017-07-01

Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

NASA Astrophysics Data System (ADS)

Liu, Likun

2018-01-01

In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

The U.S. Geological Survey Land Remote Sensing Program

USGS Publications Warehouse

,

2007-01-01

The fundamental goals of the U.S. Geological Survey's Land Remote Sens-ing (LRS) Program are to provide the Federal Government and the public with a primary source of remotely sensed data and applications and to be a leader in defining the future of land remote sensing, nationally and internationally. Remotely sensed data provide information that enhance the understand-ing of ecosystems and the capabilities for predicting ecosystem change. The data promote an understanding of the role of the environment and wildlife in human health issues, the requirements for disaster response, the effects of climate variability, and the availability of energy and mineral resources. Also, as land satellite systems acquire global coverage, the program coordinates a network of international receiving stations and users of the data. It is the responsibility of the program to assure that data from land imaging satellites, airborne photography, radar, and other technologies are available to the national and global science communities.

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

PubMed

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

2006-08-01

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

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.

An evaluation of the utilization of remote sensing in resource and environmental management of the Chesapeake Bay region

NASA Technical Reports Server (NTRS)

Fuller, D. B.; Harmon, D. M.; Fuller, K. B.

1976-01-01

A nine-month study was conducted to assess the effectiveness of the NASA Wallops Chesapeake Bay Ecological Program in remote sensing. The study consisted of a follow-up investigation and information analysis of actual cases in which remote sensing was utilized by management and research personnel in the Chesapeake Bay region. The study concludes that the NASA Wallops Chesapeake Bay Ecological Program is effective, both in terms of costs and performance.

Aerosol Remote Sensing

NASA Technical Reports Server (NTRS)

Lenoble, Jacqueline (Editor); Remer, Lorraine (Editor); Tanre, Didier (Editor)

2012-01-01

This book gives a much needed explanation of the basic physical principles of radia5tive transfer and remote sensing, and presents all the instruments and retrieval algorithms in a homogenous manner. For the first time, an easy path from theory to practical algorithms is available in one easily accessible volume, making the connection between theoretical radiative transfer and individual practical solutions to retrieve aerosol information from remote sensing. In addition, the specifics and intercomparison of all current and historical methods are explained and clarified.

Science Data Preservation: Implementation and Why It Is Important

NASA Technical Reports Server (NTRS)

Kempler, Steven J.; Moses, John F.; Gerasimov, Irina V.; Johnson, James E.; Vollmer, Bruce E.; Theobald, Michael L.; Ostrenga, Dana M.; Ahmad, Suraiya; Ramapriyan, Hampapuram K.; Khayat, Mohammad G.

2013-01-01

Remote Sensing data generation by NASA to study Earth s geophysical processes was initiated in 1960 with the launch of the first Television Infrared Observation Satellite Program (TIROS), to develop a meteorological satellite information system. What would be deemed as a primitive data set by today s standards, early Earth science missions were the foundation upon which today s remote sensing instruments have built their scientific success, and tomorrow s instruments will yield science not yet imagined. NASA Scientific Data Stewardship requirements have been documented to ensure the long term preservation and usability of remote sensing science data. In recent years, the Federation of Earth Science Information Partners and NASA s Earth Science Data System Working Groups have organized committees that specifically examine standards, processes, and ontologies that can best be employed for the preservation of remote sensing data, supporting documentation, and data provenance information. This presentation describes the activities, issues, and implementations, guided by the NASA Earth Science Data Preservation Content Specification (423-SPEC-001), for preserving instrument characteristics, and data processing and science information generated for 20 Earth science instruments, spanning 40 years of geophysical measurements, at the NASA s Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition, unanticipated preservation/implementation questions and issues in the implementation process are presented.

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

USGS Publications Warehouse

,

2009-01-01

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is useful for analyzing a wide variety of spatial data. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This fact sheet presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup during 2008 and 2009. After a summary of GIS Workgroup capabilities, brief descriptions of activities by project at the local and national levels are presented. Projects are grouped by the fiscal year (October-September 2008 or 2009) the project ends and include overviews, project images, and Internet links to additional project information and related publications or articles.

A REMOTE SENSING AND GIS-ENABLED HIGHWAY ASSET MANAGEMENT SYSTEM PHASE 2

DOT National Transportation Integrated Search

2018-02-02

The objective of this project is to validate the use of commercial remote sensing and spatial information (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile light detection and ranging (LiDAR), image processing algorit...

A remote sensing and GIS-enabled highway asset management system : final report.

DOT National Transportation Integrated Search

2016-04-01

The objective of this project is to validate the use of commercial remote sensing and spatial information : (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile LiDAR, image : processing algorithms, and GPS/GIS technolog...

Remote sensing applications for environmental analysis in transportation planning : application to the Washington State I-405 corridor

DOT National Transportation Integrated Search

2004-08-30

The project's major objective is to demonstrate and assess the applicability of commercial remote sensing products and spatial information technologies to environmental analysis in transportation planning, using the I-405 corridor in Washington State...

Remote Sensing of Earth and Environment

ERIC Educational Resources Information Center

Schertler, Ronald J.

1974-01-01

Discusses basic principles of remote sensing applications and five areas of the earth resources survey program: agriculture and forestry production; geography, cartography, cultural resources; geology and mineral resources; hydrology and water resources; and oceanography and marine resources. Indicates that information acquisition is the first…

The Increasing Use of Remote Sensing Data in Studying the Climatological Impacts on Public Health

NASA Technical Reports Server (NTRS)

Kempler, Steven; Benedict, Karl; Ceccato, Pietro; Golden, Meredith; Maxwell, Susan; Morian, Stan; Soebiyanto, Radina; Tong, Daniel

2011-01-01

One of the more fortunate outcomes of the capture and transformation of remote sensing data into applied information is their usefulness and impacts to better understanding climatological impacts on public health. Today, with petabytes of remote sensing data providing global coverage of climatological parameters, public health research and policy decision makers have an unprecedented (and growing) data record that relates the effects of climatic parameters, such as rainfall, heat, soil moisture, etc. to incidences and spread of disease, as well as predictive modeling. In addition, tools and services that specifically serve public health researchers and respondents have grown in response to needs of the these information users.

Long-Term Monitoring of Desert Land and Natural Resources and Application of Remote Sensing Technologies

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

Hamada, Yuki; Rollins, Katherine E.

2016-11-01

Monitoring environmental impacts over large, remote desert regions for long periods of time can be very costly. Remote sensing technologies present a promising monitoring tool because they entail the collection of spatially contiguous data, automated processing, and streamlined data analysis. This report provides a summary of remote sensing products and refinement of remote sensing data interpretation methodologies that were generated as part of the U.S. Department of the Interior Bureau of Land Management Solar Energy Program. In March 2015, a team of researchers from Argonne National Laboratory (Argonne) collected field data of vegetation and surface types from more than 5,000more » survey points within the eastern part of the Riverside East Solar Energy Zone (SEZ). Using the field data, remote sensing products that were generated in 2014 using very high spatial resolution (VHSR; 15 cm) multispectral aerial images were validated in order to evaluate potential refinements to the previous methodologies to improve the information extraction accuracy.« less

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

NASA Technical Reports Server (NTRS)

Brown, Molly Elizabeth; Brickley, Elizabeth B

2012-01-01

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

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

The application analysis of the multi-angle polarization technique for ocean color remote sensing

NASA Astrophysics Data System (ADS)

Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Keli

2017-02-01

The multi-angle polarization technique, which uses the intensity of polarized radiation as the observed quantity, is a new remote sensing means for earth observation. With this method, not only can the multi-angle light intensity data be provided, but also the multi-angle information of polarized radiation can be obtained. So, the technique may solve the problems, those could not be solved with the traditional remote sensing methods. Nowadays, the multi-angle polarization technique has become one of the hot topics in the field of the international quantitative research on remote sensing. In this paper, we firstly introduce the principles of the multi-angle polarization technique, then the situations of basic research and engineering applications are particularly summarized and analysed in 1) the peeled-off method of sun glitter based on polarization, 2) the ocean color remote sensing based on polarization, 3) oil spill detection using polarization technique, 4) the ocean aerosol monitoring based on polarization. Finally, based on the previous work, we briefly present the problems and prospects of the multi-angle polarization technique used in China's ocean color remote sensing.

On the feasibility of benefit-cost analysis applied to remote sensing projects. [California water resources

NASA Technical Reports Server (NTRS)

Merewitz, L.

1973-01-01

The following step-wise procedure for making a benefit-cost analysis of using remote sensing techniques could be used either in the limited context of California water resources, or a context as broad as the making of integrated resource surveys of the entire earth resource complex on a statewide, regional, national, or global basis. (1) Survey all data collection efforts which can be accomplished by remote sensing techniques. (2) Carefully inspect the State of California budget and the Budget of the United States Government to find annual cost of data collection efforts. (3) Decide the extent to which remote sensing can obviate each of the collection efforts. (4) Sum the annual costs of all data collection which can be equivalently accomplished through remote sensing. (5) Decide what additional data could and would be collected through remote sensing. (6) Estimate the value of this information. It is not harmful to do a benefit-cost analysis so long as its severe limitations are recalled and it is supplemented with socio-economic impact studies.

Bushland Evapotranspiration and Agricultural Remote Sensing System (BEARS) software

NASA Astrophysics Data System (ADS)

Gowda, P. H.; Moorhead, J.; Brauer, D. K.

2017-12-01

Evapotranspiration (ET) is a major component of the hydrologic cycle. ET data are used for a variety of water management and research purposes such as irrigation scheduling, water and crop modeling, streamflow, water availability, and many more. Remote sensing products have been widely used to create spatially representative ET data sets which provide important information from field to regional scales. As UAV capabilities increase, remote sensing use is likely to also increase. For that purpose, scientists at the USDA-ARS research laboratory in Bushland, TX developed the Bushland Evapotranspiration and Agricultural Remote Sensing System (BEARS) software. The BEARS software is a Java based software that allows users to process remote sensing data to generate ET outputs using predefined models, or enter custom equations and models. The capability to define new equations and build new models expands the applicability of the BEARS software beyond ET mapping to any remote sensing application. The software also includes an image viewing tool that allows users to visualize outputs, as well as draw an area of interest using various shapes. This software is freely available from the USDA-ARS Conservation and Production Research Laboratory website.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review

PubMed Central

Zhang, Dianjun; Zhou, Guoqing

2016-01-01

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research. PMID:27548168

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review.

PubMed

Zhang, Dianjun; Zhou, Guoqing

2016-08-17

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research.

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

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.; Ambrosia, Vincent G.

1996-01-01

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

An evaluation of the use of remotely sensed parameters for prediction of incidence and risk associated with Vibrio parahaemolyticus in Gulf Coast oysters (Crassostrea virginica).

PubMed

Phillips, A M B; Depaola, A; Bowers, J; Ladner, S; Grimes, D J

2007-04-01

The U.S. Food and Drug Administration recently published a Vibrio parahaemolyticus risk assessment for consumption of raw oysters that predicts V. parahaemolyticus densities at harvest based on water temperature. We retrospectively compared archived remotely sensed measurements (sea surface temperature, chlorophyll, and turbidity) with previously published data from an environmental study of V. parahaemolyticus in Alabama oysters to assess the utility of the former data for predicting V. parahaemolyticus densities in oysters. Remotely sensed sea surface temperature correlated well with previous in situ measurements (R(2) = 0.86) of bottom water temperature, supporting the notion that remotely sensed sea surface temperature data are a sufficiently accurate substitute for direct measurement. Turbidity and chlorophyll levels were not determined in the previous study, but in comparison with the V. parahaemolyticus data, remotely sensed values for these parameters may explain some of the variation in V. parahaemolyticus levels. More accurate determination of these effects and the temporal and spatial variability of these parameters may further improve the accuracy of prediction models. To illustrate the utility of remotely sensed data as a basis for risk management, predictions based on the U.S. Food and Drug Administration V. parahaemolyticus risk assessment model were integrated with remotely sensed sea surface temperature data to display graphically variations in V. parahaemolyticus density in oysters associated with spatial variations in water temperature. We believe images such as these could be posted in near real time, and that the availability of such information in a user-friendly format could be the basis for timely and informed risk management decisions.

Remote sensing of wildland resources: A state-of-the-art review

Treesearch

Robert C. Aldrich

1979-01-01

A review, with literature citations, of current remote sensing technology, applications, and costs for wildland resource management, including collection, interpretation, and processing of data gathered through photographic and nonphotographic techniques for classification and mapping, interpretive information for specific applications, measurement of resource...

A Physically-Based Drought Product Using Thermal Remote Sensing of Evapotranspiration

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonst...

Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Essam, Timothy; Leonard, Kenneth

2011-01-01

Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

[Contribution of remote sensing to malaria control].

PubMed

Machault, V; Pages, F; Rogier, C

2009-04-01

Despite national and international efforts, malaria remains a major public health problem and the fight to control the disease is confronted by numerous hurdles. Study of space and time dynamics of malaria is necessary as a basis for making appropriate decision and prioritizing intervention including in areas where field data are rare and sanitary information systems are inadequate. Evaluation of malarial risk should also help anticipate the risk of epidemics as a basis for early warning systems. Since 1960-70 civilian satellites launched for earth observation have been providing information for the measuring or evaluating geo-climatic and anthropogenic factors related to malaria transmission and burden. Remotely sensed data gathered for several civilian or military studies have allowed setup of entomological, parasitological, and epidemiological risk models and maps for rural and urban areas. Mapping of human populations at risk has also benefited from remotely sensing. The results of the published studies show that remote sensing is a suitable tool for optimizing planning, efficacy and efficiency of malaria control.

Future Applications of Remote Sensing to Archeological Research

NASA Technical Reports Server (NTRS)

Sever, Thomas L.

2003-01-01

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

Sensible Success

NASA Technical Reports Server (NTRS)

2001-01-01

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

Analysis on the application of background parameters on remote sensing classification

NASA Astrophysics Data System (ADS)

Qiao, Y.

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

Hyperspectral Remote Sensing of Foliar Nitrogen Content

NASA Technical Reports Server (NTRS)

Knyazikhin, Yuri; Schull, Mitchell A.; Stenberg, Pauline; Moettus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Carmona, Pedro Latorre; Kaufmann, Robert K.; Lewis, Philip;

Methods and potentials for using satellite image classification in school lessons

NASA Astrophysics Data System (ADS)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2011-11-01

The FIS project - FIS stands for Fernerkundung in Schulen (Remote Sensing in Schools) - aims at a better integration of the topic "satellite remote sensing" in school lessons. According to this, the overarching objective is to teach pupils basic knowledge and fields of application of remote sensing. Despite the growing significance of digital geomedia, the topic "remote sensing" is not broadly supported in schools. Often, the topic is reduced to a short reflection on satellite images and used only for additional illustration of issues relevant for the curriculum. Without addressing the issue of image data, this can hardly contribute to the improvement of the pupils' methodical competences. Because remote sensing covers more than simple, visual interpretation of satellite images, it is necessary to integrate remote sensing methods like preprocessing, classification and change detection. Dealing with these topics often fails because of confusing background information and the lack of easy-to-use software. Based on these insights, the FIS project created different simple analysis tools for remote sensing in school lessons, which enable teachers as well as pupils to be introduced to the topic in a structured way. This functionality as well as the fields of application of these analysis tools will be presented in detail with the help of three different classification tools for satellite image classification.

Water Dynamics in Fogera and the Upper Blue Nile - Farmers perspectives and remote sensing

NASA Astrophysics Data System (ADS)

Chemin, Yann; Desalegn, Mengistu; Curnow, Jayne; Johnston, Robyn

2015-04-01

This research work is about finding the connection between farmers perspectives on changes of water conditions in their socio-agricultural environment and satellite remote sensing analysis. Key informant surveys were conducted to investigate localised views on water scarcity as a counterpoint to the physical measurement of water availability. Does a numerical or mapped image identifying water scarcity always equate to a dearth of water for agriculture? To push the limits of the relationship between human and physical data we sought to ground-truth GIS results with the practical experience and knowledge of people living in the area. We data-mined public domain satellite data with FOSS (GDAL, GRASS GIS) and produced water-related spatio-temporal domains for our study area and the larger Upper Nile Basin. Accumulated remote sensing information was then cross-referenced with informant's accounts of water availability for the same space and time. During the survey fieldwork the team also took photographs electronically stamped with GPS coordinates to compare and contrast the views of informants and the remote sensing information with high resolution images of the landscape. We found that farmers perspective on the Spring maize crop sensibility to variability of rainfall can be quantified in space and time by remote sensing cumulative transpiration. A crop transpiration gap of 1-2.5 mm/day for about 20 days is to be overcome, a full amount of 20 to 50 mm, depending on the type of year deficit. Such gap can be overcome, even by temporary supplemental irrigation practices, however, the economical and cultural set up is already developed in another way, as per sesonal renting of higher soil profile water retention capacity fields.

Integration of Remotely Sensed Data Into Geospatial Reference Information Databases. Un-Ggim National Approach

NASA Astrophysics Data System (ADS)

Arozarena, A.; Villa, G.; Valcárcel, N.; Pérez, B.

2016-06-01

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the "skeleton" of any Spatial Data Infrastructure (SDI). Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

Remote sensing for rural development planning in Africa

NASA Technical Reports Server (NTRS)

Dunford, C.; Mouat, D. A.; Norton-Griffiths, M.; Slaymaker, D. M.

1983-01-01

Multilevel remote-sensing techniques were combined to provide land resource and land-use information for rural development planning in Arusha Region, Tanzania. Enhanced Landsat imagery, supplemented by low-level aerial survey data, slope angle data from topographic sheets, and existing reports on vegetation and soil conditions, was used jointly by image analysts and district-level land-management officials to divide the region's six districts into land-planning units. District-planning officials selected a number of these land-planning units for priority planning and development activities. For the priority areas, natural color aerial photographs provided detailed information for land-use planning discussions between district officials and villagers. Consideration of the efficiency of this remote sensing approach leads to general recommendations for similar applications. The technology and timing of data collection and interpretation activities should allow maximum participation by intended users of the information.

How Can Remote Sensing Be Used for Water Quality Monitoring?

EPA Science Inventory

“How can remote sensing address information needs and gaps in water quality and quantity management?” was a workshop convened during the biennial National Water Quality Monitoring Conference 2014, held in Cincinnati, OH. The focus of this workshop was to provide an o...

Book Review: Book review

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.

[Advances in the research on hyperspectral remote sensing in biodiversity and conservation].

PubMed

He, Cheng; Feng, Zhong-Ke; Yuan, Jin-Jun; Wang, Jia; Gong, Yin-Xi; Dong, Zhi-Hai

2012-06-01

With the species reduction and the habitat destruction becoming serious increasingly, the biodiversity conservation has become one of the hottest topics. Remote sensing, the science of non-contact collection information, has the function of corresponding estimates of biodiversity, building model between species diversity relationship and mapping the index of biodiversity, which has been used widely in the field of biodiversity conservation. The present paper discussed the application of hyperspectral technology to the biodiversity conservation from two aspects, remote sensors and remote sensing techniques, and after, enumerated successful applications for emphasis. All these had a certain reference value in the development of biodiversity conservation.

Investigation of forestry resources and other remote sensing data. 1: LANDSAT. 2: Remote sensing of volcanic emissions

NASA Technical Reports Server (NTRS)

Birnie, R. W.; Stoiber, R. E. (Principal Investigator)

1983-01-01

Computer classification of LANDSAT data was used for forest type mapping in New England. The ability to classify areas of hardwood, softwood, and mixed tree types was assessed along with determining clearcut regions and gypsy moth defoliation. Applications of the information to forest management and locating potential deer yards were investigated. The principal activities concerned with remote sensing of volcanic emissions centered around the development of remote sensors for SO2 and HCl gas, and their use at appropriate volcanic sites. Two major areas were investigated (Masaya, Nicaragua, and St. Helens, Washington) along with several minor ones.

Remote sensing and geographically based information systems

NASA Technical Reports Server (NTRS)

Cicone, R. C.

1977-01-01

A structure is proposed for a geographically-oriented computer-based information system applicable to the analysis of remote sensing digital data. The structure, intended to answer a wide variety of user needs, would permit multiple views of the data, provide independent management of data security, quality and integrity, and rely on automatic data filing. Problems in geographically-oriented data systems, including those related to line encoding and cell encoding, are considered.

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

NASA Astrophysics Data System (ADS)

Gail, William B.

2006-08-01

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

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.

The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills

NASA Astrophysics Data System (ADS)

Garron, J.; Trainor, S.

2017-12-01

Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill responses. Using automated synthetic aperture radar analyses of oil spills in a common operational picture as a scientific case study, this presentation is a demonstration of how landscape-level scientific data can be integrated into Arctic planning and operational decision-making.

Application of remote sensing to land and water resource planning: The Pocomoke River Basin, Maryland

NASA Technical Reports Server (NTRS)

Wildesen, S. E.; Phillips, E. P.

1981-01-01

Because of the size of the Pocomoke River Basin, the inaccessibility of certain areas, and study time constraints, several remote sensing techniques were used to collect base information on the river corridor, (a 23.2 km channel) and on a 1.2 km wooded floodplain. This information provided an adequate understanding of the environment and its resources, thus enabling effective management options to be designed. The remote sensing techniques used for assessment included manual analysis of high altitude color-infrared photography, computer-assisted analysis of LANDSAT-2 imagery, and the application of airborne oceanographic Lidar for topographic mapping. Results show that each techniques was valuable in providing the needed base data necessary for resource planning.

Evapotranspiration and remote sensing

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Gurney, R.

1982-01-01

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

Urban Spatial Pattern and Interaction based on Analysis of Nighttime Remote Sensing Data and Geo-social Media Information

NASA Astrophysics Data System (ADS)

Ratnasari, Nila; Dwi Candra, Erika; Herdianta Saputra, Defa; Putra Perdana, Aji

2016-11-01

Urban development in Indonesia significantly incerasing in line with rapid development of infrastructure, utility, and transportation network. Recently, people live depend on lights at night and social media and these two aspects can depicted urban spatial pattern and interaction. This research used nighttime remote sensing data with the VIIRS (Visible Infrared Imaging Radiometer Suite) day-night band detects lights, gas flares, auroras, and wildfires. Geo-social media information derived from twitter data gave big picture on spatial interaction from the geospatial footprint. Combined both data produced comprehensive urban spatial pattern and interaction in general for Indonesian territory. The result is shown as a preliminary study of integrating nighttime remote sensing data and geospatial footprint from twitter data.

Hi-Tech for Archeology

NASA Technical Reports Server (NTRS)

1987-01-01

Remote sensing is the process of acquiring physical information from a distance, obtaining data on Earth features from a satellite or an airplane. Advanced remote sensing instruments detect radiations not visible to the ordinary camera or the human eye in several bands of the spectrum. These data are computer processed to produce multispectral images that can provide enormous amounts of information about Earth objects or phenomena. Since every object on Earth emits or reflects radiation in its own unique signature, remote sensing data can be interpreted to tell the difference between one type of vegetation and another, between densely populated urban areas and lightly populated farmland, between clear and polluted water or in the archeological application between rain forest and hidden man made structures.

Earth Remote Sensing: What is it Really? What to do with it?

NASA Technical Reports Server (NTRS)

Meeson, Blanche W.

1998-01-01

NASA!s Earth Sciences Program supports a wide range of endeavors in basic Earth system scientific research, technology development to support that research, development of materials and training for educators and students based on that research and information, and increasingly practical applications. A brief overview of the scope of this scientific research and the key features of the necessary remote sensing instrumentation will be given. I will also describe available educational materials and training courses for a wide range of grade levels. Information will be provided on how to obtain educational materials or to participate in a training course. Finally, a few examples will be given to illustrate how Earth remote sensing effects our daily life.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.

PubMed

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-06-06

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

Remote sensing of land surface phenology

USGS Publications Warehouse

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 7: Nonreplenishable natural resources: Minerals, fossil fuels and geothermal energy sources

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1974-01-01

The application of remotely-sensed information to the mineral, fossil fuel, and geothermal energy extraction industry is investigated. Public and private cost savings are documented in geologic mapping activities. Benefits and capabilities accruing to the ERS system are assessed. It is shown that remote sensing aids in resource extraction, as well as the monitoring of several dynamic phenomena, including disturbed lands, reclamation, erosion, glaciation, and volcanic and seismic activity.

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

NASA Astrophysics Data System (ADS)

Popov, M.; Fedorovsky, O.; Stankevich, S.; Filipovich, V.; Khyzhniak, A.; Piestova, I.; Lubskyi, M.; Svideniuk, M.

2017-12-01

The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester - Graham system dynamics model is provided over Kiev urban area.

U. S. GEOLOGICAL SURVEY LAND REMOTE SENSING ACTIVITIES.

USGS Publications Warehouse

Frederick, Doyle G.

1983-01-01

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

Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

NASA Astrophysics Data System (ADS)

Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

2016-09-01

Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

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

NASA Technical Reports Server (NTRS)

Ryerson, Charles C.

2000-01-01

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

Two Optical Atmospheric Remote Sensing Techniques and AN Associated Analytic Solution to a Class of Integral Equations

NASA Astrophysics Data System (ADS)

Manning, Robert Michael

This work concerns itself with the analysis of two optical remote sensing methods to be used to obtain parameters of the turbulent atmosphere pertinent to stochastic electromagnetic wave propagation studies, and the well -posed solution to a class of integral equations that are central to the development of these remote sensing methods. A remote sensing technique is theoretically developed whereby the temporal frequency spectrum of the scintillations of a stellar source or a point source within the atmosphere, observed through a variable radius aperture, is related to the space-time spectrum of atmospheric scintillation. The key to this spectral remote sensing method is the spatial filtering performed by a finite aperture. The entire method is developed without resorting to a priori information such as results from stochastic wave propagation theory. Once the space-time spectrum of the scintillations is obtained, an application of known results of atmospheric wave propagation theory and simple geometric considerations are shown to yield such important information such as the spectrum of atmospheric turbulence, the cross-wind velocity, and the path profile of the atmospheric refractive index structure parameter. A method is also developed to independently verify the Taylor frozen flow hypothesis. The success of the spectral remote sensing method relies on the solution to a Fredholm integral equation of the first kind. An entire class of such equations, that are peculiar to inverse diffraction problems, is studied and a well-posed solution (in the sense of Hadamard) is obtained and probed. Conditions of applicability are derived and shown not to limit the useful operating range of the spectral remote sensing method. The general integral equation solution obtained is then applied to another remote sensing problem having to do with the characterization of the particle size distribution to atmospheric aerosols and hydrometeors. By measuring the diffraction pattern in the focal plane of a lens created by the passage of a laser beam through a distribution of particles, it is shown that the particle-size distribution of the particles can be obtained. An intermediate result of the analysis also gives the total volume concentration of the particles.

Trophic Status, Ecological Condition and Cyanobacteria Risk of New England Lakes and Ponds Based on Aircraft Remote Sensing.

EPA Science Inventory

Aircraft remote sensing of freshwater ecosystems offers federal and state monitoring agencies an ability to meet their assessment requirements by rapidly acquiring information on ecosystem responses to environmental change for water bodies that are below the resolution of space...

Construction of a remotely sensed area sampling frame for Southern Brazil

NASA Technical Reports Server (NTRS)

Fecso, R.; Gardner, W.; Hale, B.; Johnson, V.; Pavlasek, S. (Principal Investigator)

1982-01-01

A remotely sensed area sampling frame was constructed for selected areas in Southern Brazil. The sampling unit information was stored in digital form in a latitudinal/longitudinal characterized population. Computerized sampling procedures were developed which allow for flexibility in sample unit specifications and sampling designs.

A selected bibliography: Remote sensing applications in agriculture

USGS Publications Warehouse

Draeger, William C.; McClelland, David T.

1977-01-01

The bibliography contains nearly 300 citations of selected publications and technical reports dealing with the application of remote-sensing techniques to the collection and analysis of agricultural information. Most of the items included were published between January 1968 and December 1975, although some earlier works of continuing interest are included.

Remote sensing. [land use mapping

NASA Technical Reports Server (NTRS)

Jinich, A.

1979-01-01

Various imaging techniques are outlined for use in mapping, land use, and land management in Mexico. Among the techniques discussed are pattern recognition and photographic processing. The utilization of information from remote sensing devices on satellites are studied. Multispectral band scanners are examined and software, hardware, and other program requirements are surveyed.

A thermal-based remote sensing modeling system for estimating evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This paper describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/s...

Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation ...

Section summary: Remote sensing

Treesearch

Belinda Arunarwati Margono

2013-01-01

Remote sensing is an important data source for monitoring the change of forest cover, in terms of both total removal of forest cover (deforestation), and change of canopy cover, structure and forest ecosystem services that result in forest degradation. In the context of Intergovernmental Panel on Climate Change (IPCC), forest degradation monitoring requires information...

Applications of satellite remote sensing to forested ecosystems

Treesearch

Louis R. Iverson; Robin Lambert Graham; Elizabeth A. Cook; Elizabeth A. Cook

1989-01-01

Since the launch of the first civilian earth-observing satellite in 1972, satellite remote sensing has provided increasingly sophisticated information on the structure and function of forested ecosystems. Forest classification and mapping, common uses of satellite data, have improved over the years as a result of more discriminating sensors, better classification...

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing..

EPA Science Inventory

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

Breaking the barriers to adopting satellite remote sensing for water quality management: ?monitoring cyanobacteria blooms

EPA Science Inventory

Remote sensing technology has the potential to inform and accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long...

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...

Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models

USDA-ARS?s Scientific Manuscript database

Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a variety of crop biophysical properties. However, the outcome of the model inversion procedure will be ...

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

USGS Publications Warehouse

,

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

International Symposium on Remote Sensing of Environment, Third Thematic Conference: Remote Sensing for Exploration Geology, Colorado Springs, CO, April 16-19, 1984, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

1985-01-01

A photogeologic and remote sensing model of porphyry type mineral sytems is considered along with a Landsat application to development of a tectonic model for hydrocarbon exploration of Devonian shales in west-central Virginia, remote sensing and the funnel philosophy, Landsat-based tectonic and metallogenic synthesis of the southwest United States, and an evolving paradigm for computer vision. Attention is given to the neotectonics of the Tibetan plateau deduced from Landsat MSS image interpretation, remote sensing in northern Arizona, the use of an airborne laser system for vegetation inventories and geobotanical prospecting, an evaluation of Thematic Mapper data for hydrocarbon exploration in low-relief basins, and an evaluation of the information content of high spectral resolution imagery. Other topics explored are related to a major source of new radar data for exploration research, the accuracy of geologic maps produced from Landsat data, and an approach for the geometric rectification of radar imagery.

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

PubMed

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

2000-01-01

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

Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

NASA Astrophysics Data System (ADS)

Hochschild, V.

2012-12-01

This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

The integrated design and archive of space-borne signal processing and compression coding

NASA Astrophysics Data System (ADS)

He, Qiang-min; Su, Hao-hang; Wu, Wen-bo

2017-10-01

With the increasing demand of users for the extraction of remote sensing image information, it is very urgent to significantly enhance the whole system's imaging quality and imaging ability by using the integrated design to achieve its compact structure, light quality and higher attitude maneuver ability. At this present stage, the remote sensing camera's video signal processing unit and image compression and coding unit are distributed in different devices. The volume, weight and consumption of these two units is relatively large, which unable to meet the requirements of the high mobility remote sensing camera. This paper according to the high mobility remote sensing camera's technical requirements, designs a kind of space-borne integrated signal processing and compression circuit by researching a variety of technologies, such as the high speed and high density analog-digital mixed PCB design, the embedded DSP technology and the image compression technology based on the special-purpose chips. This circuit lays a solid foundation for the research of the high mobility remote sensing camera.

Remote sensing and human health: new sensors and new opportunities

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

An investigation of satellite sounding products for the remote sensing of the surface energy balance and soil moisture

NASA Technical Reports Server (NTRS)

Diak, George R.

1989-01-01

Improved techniques for the remote sensing of the land surface energy balance (SEB) and soil moisture would greatly improve prediction of climate and weather as well as be of benefit to agriculture, hydrology and many associated fields. Most of the satellite remote sensing methods which were researched to date rely upon satellite-measured infrared surface temperatures or their time changes as a remote sensing signal. Optimistically, only four or five levels of information (wet to dry) in surface heating/evaporation are discernable by surface temperature methods and a good understanding of atmospheric conditions is necessary to bring them to this accuracy level. Skin temperature methods were researched as well as begun work on several new methods for the remote sensing of the SEB, some elements of which are applicable to current and retrospective data sources and some which will rely on instrumentation from the Earth Observing System (EOS) program in the 1990s.

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

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

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

2014-04-01

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

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

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

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

2014-04-01

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

Surveillance of Arthropod Vector-Borne Infectious Diseases Using Remote Sensing Techniques: A Review

PubMed Central

Kalluri, Satya; Gilruth, Peter; Rogers, David; Szczur, Martha

2007-01-01

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed. PMID:17967056

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.

Water Column Correction for Coral Reef Studies by Remote Sensing

PubMed Central

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-01-01

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application. PMID:25215941

Water column correction for coral reef studies by remote sensing.

PubMed

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-09-11

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

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.

Remote sensing in Michigan for land resource management: Highway impact assessment

NASA Technical Reports Server (NTRS)

1972-01-01

An existing section of M-14 freeway constructed in 1964 and a potential extension from Ann Arbor to Plymouth, Michigan provided an opportunity for investigating the potential uses of remote sensing techniques in providing projective information needed for assessing the impact of highway construction. Remote sensing data included multispectral scanner imagery and aerial photography. Only minor effects on vegetation, soils, and land use were found to have occurred in the existing corridor. Adverse changes expected to take place in the corridor proposed for extension of the freeway can be minimized by proper design of drainage ditches and attention to good construction practices. Remote sensing can be used to collect and present many types of data useful for highway impact assessment on land use, vegetation categories and species, soil properties and hydrologic characteristics.

Tasseled cap transformation for HJ multispectral remote sensing data

NASA Astrophysics Data System (ADS)

Han, Ling; Han, Xiaoyong

2015-12-01

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

The potential and prospects of proximal remote sensing of arthropod pests.

PubMed

Nansen, Christian

2016-04-01

Bench-top or proximal remote sensing applications are widely used as part of quality control and machine vision systems in commercial operations. In addition, these technologies are becoming increasingly important in insect systematics and studies of insect physiology and pest management. This paper provides a review and discussion of how proximal remote sensing may contribute valuable quantitative information regarding identification of species, assessment of insect responses to insecticides, insect host responses to parasitoids and performance of biological control agents. The future role of proximal remote sensing is discussed as an exciting path for novel paths of multidisciplinary research among entomologists and scientists from a wide range of other disciplines, including image processing engineers, medical engineers, research pharmacists and computer scientists. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

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

NASA Technical Reports Server (NTRS)

Cook, J. J.

1972-01-01

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

Remote sensing techniques for conservation and management of natural vegetation ecosystems

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Verdesio, J. J.; Dossantos, J. R.

1981-01-01

The importance of using remote sensing techniques, in the visible and near-infrared ranges, for mapping, inventory, conservation and management of natural ecosystems is discussed. Some examples realized in Brazil or other countries are given to evaluate the products from orbital platform (MSS and RBV imagery of LANDSAT) and aerial level (photography) for ecosystems study. The maximum quantitative and qualitative information which can be obtained from each sensor, at different level, are discussed. Based on the developed experiments it is concluded that the remote sensing technique is a useful tool in mapping vegetation units, estimating biomass, forecasting and evaluation of fire damage, disease detection, deforestation mapping and change detection in land-use. In addition, remote sensing techniques can be used in controling implantation and planning natural/artificial regeneration.

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.

The Earth Resources Observation Systems data center's training technical assistance, and applications research activities

USGS Publications Warehouse

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.

[Application of hyperspectral remote sensing in research on ecological boundary in north farming-pasturing transition in China].

PubMed

Wang, Hong-Mei; Wang, Kun; Xie, Ying-Zhong

2009-06-01

Studies of ecological boundaries are important and have become a rapidly evolving part of contemporary ecology. The ecotones are dynamic and play several functional roles in ecosystem dynamics, and the changes in their locations can be used as an indicator of environment changes, and for these reasons, ecotones have recently become a focus of investigation of landscape ecology and global climate change. As the interest in ecotone increases, there is an increased need for formal techniques to detect it. Hence, to better study and understand the functional roles and dynamics of ecotones in ecosystem, we need quantitative methods to characterize them. In the semi-arid region of northern China, there exists a farming-pasturing transition resulting from grassland reclamation and deforestation. With the fragmentation of grassland landscape, the structure and function of the grassland ecosystem are changing. Given this perspective; new-image processing approaches are needed to focus on transition themselves. Hyperspectral remote sensing data, compared with wide-band remote sensing data, has the advantage of high spectral resolution. Hyperspectral remote sensing can be used to visualize transitional zones and to detect ecotone based on surface properties (e. g. vegetation, soil type, and soil moisture etc). In this paper, the methods of hyperspectral remote sensing information processing, spectral analysis and its application in detecting the vegetation classifications, vegetation growth state, estimating the canopy biochemical characteristics, soil moisture, soil organic matter etc are reviewed in detail. Finally the paper involves further application of hyperspectral remote sensing information in research on local climate in ecological boundary in north farming-pasturing transition in China.

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

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Remote sensing terminology: past experience and recent needs

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana

2013-10-01

Terminology is a key issue for a better understanding among people using various languages. Terminology accuracy is essential during all phases of international cooperation. It is crucial to keep up with the latest quantitative and qualitative 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 wide and ever extending applications in various domains of human activity. The importance of the correct use of remote sensing terms refers not only to people working in this field but also to experts in many disciplines who handle remote sensing data and information products. The paper is devoted to terminology issues that refer to all aspects of remote sensing research and application areas. The attention is drawn on the recent needs and peculiarities of compiling specialized dictionaries in the subject area of remote sensing. Details are presented about the work in progress on the preparation of an English-Bulgarian dictionary of remote sensing terms focusing on Earth observations and geoinformation science. 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. Any interest in cooperation and initiating of suchlike collaborative multilingual projects is welcome and highly appreciated.

Tracking and Monitoring Oil Slicks Using remote Sensing

NASA Astrophysics Data System (ADS)

Klemas, V. V.

2011-12-01

Tracking and Monitoring Oil Slicks Using Remote Sensing Victor Klemas, Ph.D. , College of Earth, Ocean and Environment, University of Delaware, Newark, DE 19716 Abstract Oil spills can harm marine life in the ocean, estuaries and wetlands. To limit the damage by a spill and facilitate cleanup efforts, emergency managers need information on spill location, size and extent, direction and speed of oil movement, wind, current, and wave information for predicting oil drift and dispersion. The main operational data requirements are fast turn-around time and frequent imaging to monitor the dynamics of the spill. Radar and multispectral remote sensors on satellites and aircraft meet most of these requirements by tracking the spilled oil at various resolutions, over wide areas and at frequent intervals. They also provide key inputs to drift prediction models and facilitate targeting of skimming and booming efforts. Satellite data are frequently supplemented by information provided by aircraft, ships and remotely controlled underwater robots. The Sea Princess tanker grounding off the coast of Wales and the explosion on the Deepwater Horizon rig in the Gulf of Mexico provide two representative, yet different, scenarios for evaluating the effectiveness of remote sensors during oil spill emergencies. Session NH17: Remote Sensing of Natural Hazards Session Chair: Ramesh P. Singh Sponsor: Natural Hazards (NH)

Remotely Sensed Information and Field Data are both Essential to Assess Biodiversity CONDITION!

NASA Astrophysics Data System (ADS)

Sparrow, B.; Schaefer, M.; Scarth, P.; Phinn, S. R.; Christensen, R.; Lowe, A. J.; O'Neill, S.; Thurgate, N.; Wundke, D.

2015-12-01

Over the past year the TERN Ausplots facility has hosted a process to determine the definition of Biodiversity Condition in an Australian Continental Context, and conducted a wide collaborative process to determine which environmental attributes are required to be measures to accurately inform on biodiversity condition. A major output from this work was the acknowledgement that good quality data from both remotely sensed sources and good quality field collected data are both essential to provide the best information possible on biodiversity condition. This poster details some background to the project, the assesment of which attributes to measure, and if the are sources primarily from field based or remotely sensed measures. It then proceeds to provide three examples of ways in which the combination of data types provides a superior product as output, with one example being provided for the three cornerstone areas of condition: Structure, Function and Composition.

The role of remote sensing and GIS for spatial prediction of vector-borne diseases transmission: a systematic review.

PubMed

Palaniyandi, M

2012-12-01

There have been several attempts made to the appreciation of remote sensing and GIS for the study of vectors, biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time. This study was made for reviewing and appraising the potential use of remote sensing and GIS applications for spatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectors and vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined with geographical, environmental and climatic factors, and are localized. The presence of vectors and vector-borne diseases is most complex in nature, however, it is confined and fueled by the geographical, climatic and environmental factors including man-made factors. The usefulness of the present day availability of the information derived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture, soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of other geoclimatic and geoenvironmental variables. The present study gives the detailed information on the classical studies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseases control. The ecological modeling directly gives us the relevant information to understand the spatial variation of the vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association with geoclimatic and the environmental variables. The probability map of the geographical distribution and seasonal variations of horizontal and vertical distribution of vector abundance and its association with vector -borne diseases can be obtained with low cost remote sensing and GIS tool with reliable data and speed.

Remote Sensing Image Classification Applied to the First National Geographical Information Census of China

NASA Astrophysics Data System (ADS)

Yu, Xin; Wen, Zongyong; Zhu, Zhaorong; Xia, Qiang; Shun, Lan

2016-06-01

Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN) to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC) and Maximum Likelihood Classification Method (MLC) in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

NASA Astrophysics Data System (ADS)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

Searching data for supporting archaeo-landscapes in Cyprus: an overview of aerial, satellite, and cartographic datasets of the island

NASA Astrophysics Data System (ADS)

Agapiou, Athos; Lysandrou, Vasiliki; Themistocleous, Kyriakos; Nisantzi, Argyro; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter; Hadjimitsis, Diofantos

2016-08-01

The landscape of Cyprus is characterized by transformations that occurred during the 20th century, with many of such changes being still active today. Landscapes' changes are due to a variety of reasons including war conflicts, environmental conditions and modern development that have often caused the alteration or even the total loss of important information that could have assisted the archaeologists to comprehend the archaeo-landscape. The present work aims to provide detailed information regarding the different existing datasets that can be used to support archaeologists in understanding the transformations that the landscape in Cyprus undergone, from a remote sensing perspective. Such datasets may help archaeologists to visualize a lost landscape and try to retrieve valuable information, while they support researchers for future investigations. As such they can further highlight in a predictive manner and consequently assess the impacts of landscape transformation -being of natural or anthropogenic cause- to cultural heritage. Three main datasets are presented here: aerial images, satellite datasets including spy satellite datasets acquired during the Cold War, and cadastral maps. The variety of data is provided in a chronological order (e.g. year of acquisitions), while other important parameters such as the cost and the accuracy are also determined. Individual examples of archaeological sites in Cyprus are also provided for each dataset in order to underline both their importance and performance. Also some pre- and post-processing remote sensing methodologies are briefly described in order to enhance the final results. The paper within the framework of ATHENA project, dedicated to remote sensing archaeology/CH, aims to fill a significant gap in the recent literature of remote sensing archaeology of the island and to assist current and future archaeologists in their quest for remote sensing information to support their research.

Post-Disaster Damage Assessment using Remotely Sensed Data for Post Disaster Needs Assessments: Pakistan and Nigeria case studies

NASA Astrophysics Data System (ADS)

Saito, Keiko; Lemoine, Guido; Dell'Oro, Luca; Pedersen, Wendi; Nunez-Gomez, Ariel; Dalmasso, Simone; Balbo, Simone; Louvrier, Christophe; Caravaggi, Ivano; de Groeve, Tom; Slayback, Dan; Policelli, Frederick; Brakenridge, Bob; Rashid, Kashif; Gad, Sawsan; Arshad, Raja; Wielinga, Doekle; Parvez, Ayaz; Khan, Haris

2013-04-01

Since the launch of high-resolution optical satellites in 1999, remote sensing has increasingly been used in the context of post-disaster damage assessments worldwide. In the immediate aftermath of a natural disaster, particularly when extensive geographical areas are affected, it is often difficult to determine the extent and magnitude of disaster impacts. The Global Facility for Disaster Reduction and Recovery (GFDRR) has been leading efforts to utilise remote sensing techniques during disasters, starting with the 2010 Haiti earthquake. However, remote sensing has mostly been applied to extensive flood events in the context of developing Post-Disaster Needs Assessments (PDNAs). Given that worldwide, floods were the most frequent type of natural disasters between 2000 and 2011, affecting 106 million people in 2011 alone (EM-DAT) , there is clearly significant potential for on-going use of remote sensing techniques. Two case studies will be introduced here, the 2010 Pakistan flood and the 2012 Nigeria flood. The typical approach is to map the maximum cumulative inundation extent, then overlay this hazard information with available exposure datasets. The PDNA methodology itself is applied to a maximum of 15 sectors, of which remote sensing is most useful for housing, agriculture, transportation. Environment and irrigation could be included but these sectors were not covered in these events. The maximum cumulative flood extent is determined using remotely sensed data led by in-country agencies together with international organizations. To enhance this process, GFDRR hosted a SPRINT event in 2012 to tailor daily flood maps derived from MODIS imagery by NASA Goddard's Office of Applied Sciences to this purpose. To estimate the (direct) damage, exposure data for each sector is required. Initially global datasets are used, but these may be supplemented by national level datasets to revise damage estimates, depending on availability. Remote sensed estimates of direct damage are used to confirm field estimates of the magnitude of the damage; thus, the speed of assessment can be balanced not having to achieve high accuracy results. In the future, to increase the speed of remote sensed damage assessments, there is a need for existing exposure information - which can also be used for risk prediction as well as disaster response. However, advances in this area vary significantly by country and sector and therefore efforts to move this agenda forward will significantly improve disaster reduction and recovery.

Airborne remote sensing for geology and the environment; present and future

USGS Publications Warehouse

Watson, Ken; Knepper, Daniel H.

1994-01-01

In 1988, a group of leading experts from government, academia, and industry attended a workshop on airborne remote sensing sponsored by the U.S. Geological Survey (USGS) and hosted by the Branch of Geophysics. The purpose of the workshop was to examine the scientific rationale for airborne remote sensing in support of government earth science in the next decade. This report has arranged the six resulting working-group reports under two main headings: (1) Geologic Remote Sensing, for the reports on geologic mapping, mineral resources, and fossil fuels and geothermal resources; and (2) Environmental Remote Sensing, for the reports on environmental geology, geologic hazards, and water resources. The intent of the workshop was to provide an evaluation of demonstrated capabilities, their direct extensions, and possible future applications, and this was the organizational format used for the geologic remote sensing reports. The working groups in environmental remote sensing chose to present their reports in a somewhat modified version of this format. A final section examines future advances and limitations in the field. There is a large, complex, and often bewildering array of remote sensing data available. Early remote sensing studies were based on data collected from airborne platforms. Much of that technology was later extended to satellites. The original 80-m-resolution Landsat Multispectral Scanner System (MSS) has now been largely superseded by the 30-m-resolution Thematic Mapper (TM) system that has additional spectral channels. The French satellite SPOT provides higher spatial resolution for channels equivalent to MSS. Low-resolution (1 km) data are available from the National Oceanographic and Atmospheric Administration's AVHRR system, which acquires reflectance and day and night thermal data daily. Several experimental satellites have acquired limited data, and there are extensive plans for future satellites including those of Japan (JERS), Europe (ESA), Canada (Radarsat), and the United States (EOS). There are currently two national airborne remote sensing programs (photography, radar) with data archived at the USGS' EROS Data Center. Airborne broadband multispectral data (comparable to Landsat MSS and TM but involving several more channels) for limited geographic areas also are available for digital processing and analysis. Narrow-band imaging spectrometer data are available for some NASA experiment sites and can be acquired for other locations commercially. Remote sensing data and derivative images, because of the uniform spatial coverage, availability at different resolutions, and digital format, are becoming important data sets for geographic information system (GIS) analyses. Examples range from overlaying digitized geologic maps on remote sensing images and draping these over topography, to maps of mineral distribution and inferred abundance. A large variety of remote sensing data sets are available, with costs ranging from a few dollars per square mile for satellite digital data to a few hundred dollars per square mile for airborne imaging spectrometry. Computer processing and analysis costs routinely surpass these expenses because of the equipment and expertise necessary for information extraction and interpretation. Effective use requires both an understanding of the current methodology and an appreciation of the most cost-effective solution.

Remote measurement of pollution

NASA Technical Reports Server (NTRS)

1971-01-01

A summary of the major conclusions and recommendations developed by the panels on gaseous air pollution, water pollution, and particulate air pollution is presented. It becomes evident that many of the trace gases are amenable to remote sensing; that certain water pollutants can be measured by remote techniques, but their number is limited; and that a similar approach to the remote measurement of specific particulate pollutants will follow only after understanding of their physical, chemical, and radiative properties is improved. It is also clear that remote sensing can provide essential information in all three categories that can not be obtained by any other means.

Role of remote sensing in Bay measurements

NASA Technical Reports Server (NTRS)

Mugler, J. P., Jr.; Godfrey, J. P.; Hickman, G. D.; Hovis, W. G.; Pearson, A. O.; Weaver, K. N.

1978-01-01

Remote measurements of a number of surface or near surface parameters for baseline definition and specialized studies, remote measurements of episodic events, and remote measurements of the Bay lithosphere are considered in terms of characterizing and understanding the ecology of the Chesapeake Bay. Geologic processes and features best suited for information enhancement by remote sensing methods are identified. These include: (1) rates of sedimentation in the Bay; (2) rates of erosion of Bay shorelines; (3) spatial distribution and geometry of aquifers; (4) mapping of Karst terrain (sinkholes); and (5) mapping of fracture patterns. Recommendations for studying problem areas identified are given.

Factors affecting the identification of phytoplankton groups by means of remote sensing

NASA Technical Reports Server (NTRS)

Weaver, Ellen C.; Wrigley, Robert

1994-01-01

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS).

Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion

USDA-ARS?s Scientific Manuscript database

A continuous monitoring of daily evapotranspiration (ET) at field scale can be achieved by combining thermal infrared remote sensing data information from multiple satellite platforms. Here, an integrated approach to field scale ET mapping is described, combining multi-scale surface energy balance e...

A hyper-temporal remote sensing protocol for detecting ecosystem disturbance, classifying ecological state, and assessing soil resilience

USDA-ARS?s Scientific Manuscript database

Hyper-temporal remote sensing is capable of detecting detailed information on vegetation dynamics relating to plant functional types (PFT), a useful proxy for estimating soil physical and chemical properties. A central concept of PFT is that plant morphological and physiological adaptations are link...

Spatial and functional characterization, identification and assessment of isolated wetlands in Alachua County, Florida, USA - GIS and remote sensing techniques

EPA Science Inventory

In this study, Geographic Information Systems (GIS) and remote sensing mapping techniques were developed to identify the locations of isolated wetlands in Alachua County, FL, a 2510 sq km area in north-central Florida with diverse geology and numerous isolated wetlands. The resul...

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynami...

How to Study the Earth From Space.

ERIC Educational Resources Information Center

Boyer, Robert E.

This booklet is one in a series of instructional aids designed for use by elementary and secondary school science teachers. It reviews how the various forms of remote sensing can provide invaluable knowledge about the earth as the need for environmental information continues to increase. Remote sensing involves space photography, infrared imagery,…

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

USDA-ARS?s Scientific Manuscript database

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i...

Remote sensing for restoration planning: how the big picture can inform stakeholders

Treesearch

Susan Cordell; Erin J. Questad; Gregory P. Asner; Kealoha M. Kinney; Jarrod M. Thaxton; Amanda Uowolo; Sam Brooks; Mark W. Chynoweth

2016-01-01

The use of remote sensing in ecosystem management has transformed how land managers, practitioners, and policymakers evaluate ecosystem loss, gain, and change at multiple spatial and temporal scales. Less developed is the use of these spatial tools for planning, implementing, and evaluating ecosystem restoration projects and especially so in multifunctional...

A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. A thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temp...

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.

Advances in U.S. Land Imaging Capabilities

NASA Astrophysics Data System (ADS)

Stryker, T. S.

2017-12-01

Advancements in Earth observations, cloud computing, and data science are improving everyday life. Information from land-imaging satellites, such as the U.S. Landsat system, helps us to better understand the changing landscapes where we live, work, and play. This understanding builds capacity for improved decision-making about our lands, waters, and resources, driving economic growth, protecting lives and property, and safeguarding the environment. The USGS is fostering the use of land remote sensing technology to meet local, national, and global challenges. A key dimension to meeting these challenges is the full, free, and open provision of land remote sensing observations for both public and private sector applications. To achieve maximum impact, these data must also be easily discoverable, accessible, and usable. The presenter will describe the USGS Land Remote Sensing Program's current capabilities and future plans to collect and deliver land remote sensing information for societal benefit. He will discuss these capabilities in the context of national plans and policies, domestic partnerships, and international collaboration. The presenter will conclude with examples of how Landsat data is being used on a daily basis to improve lives and livelihoods.

Remote sensing: Snow monitoring tool for today and tomorrow

NASA Technical Reports Server (NTRS)

Rango, A.

1977-01-01

Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

Operational Remote Sensing Services in North Eastern Region of India for Natural Resources Management, Early Warning for Disaster Risk Reduction and Dissemination of Information and Services

NASA Astrophysics Data System (ADS)

Raju, P. L. N.; Sarma, K. K.; Barman, D.; Handique, B. K.; Chutia, D.; Kundu, S. S.; Das, R. Kr.; Chakraborty, K.; Das, R.; Goswami, J.; Das, P.; Devi, H. S.; Nongkynrih, J. M.; Bhusan, K.; Singh, M. S.; Singh, P. S.; Saikhom, V.; Goswami, C.; Pebam, R.; Borgohain, A.; Gogoi, R. B.; Singh, N. R.; Bharali, A.; Sarma, D.; Lyngdoh, R. B.; Mandal, P. P.; Chabukdhara, M.

2016-06-01

North Eastern Region (NER) of India comprising of eight states considered to be most unique and one of the most challenging regions to govern due to its unique physiographic condition, rich biodiversity, disaster prone and diverse socio-economic characteristics. Operational Remote Sensing services increased manifolds in the region with the establishment of North Eastern Space Applications Centre (NESAC) in the year 2000. Since inception, NESAC has been providing remote sensing services in generating inventory, planning and developmental activities, and management of natural resources, disasters and dissemination of information and services through geo-web services for NER. The operational remote sensing services provided by NESAC can be broadly divided into three categories viz. natural resource planning and developmental services, disaster risk reduction and early warning services and information dissemination through geo-portal services. As a apart of natural resources planning and developmental services NESAC supports the state forest departments in preparing the forest working plans by providing geospatial inputs covering entire NER, identifying the suitable culturable wastelands for cultivation of silkworm food plants, mapping of natural resources such as land use/land cover, wastelands, land degradation etc. on temporal basis. In the area of disaster risk reduction, NESAC has initiated operational services for early warning and post disaster assessment inputs for flood early warning system (FLEWS) using satellite remote sensing, numerical weather prediction, hydrological modeling etc.; forest fire alert system with actionable attribute information; Japanese Encephalitis Early Warning System (JEWS) based on mosquito vector abundance, pig population and historical disease intensity and agriculture drought monitoring for the region. The large volumes of geo-spatial databases generated as part of operational services are made available to the administrators and local government bodies for better management, preparing prospective planning, and sustainable use of available resources. The knowledge dissemination is being done through online web portals wherever the internet access is available and as well as offline space based information kiosks, where the internet access is not available or having limited bandwidth availability. This paper presents a systematic and comprehensive study on the remote sensing services operational in NER of India for natural resources management, disaster risk reduction and dissemination of information and services, in addition to outlining future areas and direction of space applications for the region.

REMOTE SENSING AND GIS FOR WETLANDS

EPA Science Inventory

In identifying and characterizing wetland and adjacent features, the use of remote sensor and Geographic Information Systems (GIS) technologies has been valuable. Remote sensors such as photographs and computer-sensor generated images can illustrate conditions of hydrology, exten...

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.

Optical vs. electronic enhancement of remote sensing imagery

NASA Technical Reports Server (NTRS)

Colwell, R. N.; Katibah, E. F.

1976-01-01

Basic aspects of remote sensing are considered and a description is provided of the methods which are employed in connection with the optical or electronic enhancement of remote sensing imagery. The advantages and limitations of various image enhancement methods and techniques are evaluated. It is pointed out that optical enhancement methods and techniques are currently superior to electronic ones with respect to spatial resolution and equipment cost considerations. Advantages of electronic procedures, on the other hand, are related to a greater flexibility regarding the presentation of the information as an aid for the interpretation by the image analyst.

Research and Practice of Uav Remote Sensing in the Monitoring and Management of Construction Projects in Riparian Areas

NASA Astrophysics Data System (ADS)

Yu, J.; Gan, Z.; Zhong, L.; Deng, L.

2018-04-01

The objective of this paper is to investigate the use of UAV remote sensing in the monitoring and management of construction projects in riparian areas through the case study of embankment construction projects' monitoring in the Three Gorges Reservoir area. A three-step approach is proposed to address the problem: data acquisition with UAV, data processing, and monitoring information extraction. The results of the case study demonstrate that UAV remote sensing is capable of providing fast and accurate measurements and calculations for the needs of monitoring of riparian constructions.

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

USGS Publications Warehouse

Jones, John W.

2011-01-01

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

Multispectral analysis of ocean dumped materials

NASA Technical Reports Server (NTRS)

Johnson, R. W.

1977-01-01

Experiments conducted in the Atlantic coastal zone indicated that plumes resulting from ocean dumping of acid wastes and sewage sludge have unique spectral characteristics. Remotely sensed wide area synoptic coverage provided information on these pollution features that was not readily available from other sources. Aircraft remotely sensed photographic and multispectral scanner data were interpreted by two methods. First, qualitative analyses in which pollution features were located, mapped, and identified without concurrent sea truth and, second, quantitative analyses in which concurrently collected sea truth was used to calibrate the remotely sensed data and to determine quantitative distributions of one or more parameters in a plume.

Cases in the relation of research on remote sensing to decisionmakers in a state agency

NASA Technical Reports Server (NTRS)

Jondrow, J. W.

1975-01-01

The use is considered of various management tools in order to assess their effects on the anticipated relevance of the remote sensing research to the needs of government agencies. Among these tools are different organizational structures and ways of functioning, which are applied to the design and management of projects and to the communication of research results. The characteristics of data and information flow, and technology transfer are discussed along with the management of three projects and a remote sensing data center in terms of the use of some tools for influencing these processes.

Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

NASA Astrophysics Data System (ADS)

Sofina, N.; Ehlers, M.

2012-08-01

High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

Bit of History and Some Lessons Learned in Using NASA Remote Sensing Data in Public Health Applications

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Sue

2011-01-01

The NASA Applied Sciences Program's public health initiative began in 2004 to illustratethe potential benefits for using remote sensing in public health applications. Objectives/Purpose: The CDC initiated a st udy with NASA through the National Center for Environmental Health (NCEH) to establish a pilot effort to use remote sensing data as part of its Environmental Public Health Tracking Network (EPHTN). As a consequence, the NCEH and NASA developed a project called HELIX-Atlanta (Health and Environment Linkage for Information Exchange) to demonstrate a process for developing a local environmental public health tracking and surveillance network that integrates non-infectious health and environment systems for the Atlanta metropolitan area. Methods: As an ongo ing, systematic integration, analysis and interpretation of data, an EPHTN focuses on: 1 -- environmental hazards; 2 -- human exposure to environmental hazards; and 3 -- health effects potentially related to exposure to environmental hazards. To satisfy the definition of a surveillance system the data must be disseminated to plan, implement, and evaluate environmental public health action. Results: A close working r elationship developed with NCEH where information was exchanged to assist in the development of an EPHTN that incorporated NASA remote sensing data into a surveillance network for disseminating public health tracking information to users. This project?s success provided NASA with the opportunity to work with other public health entities such as the University of Mississippi Medical Center, the University of New Mexico and the University of Arizona. Conclusions: HELIX-Atlanta became a functioning part of the national EPHTN for tracking environmental hazards and exposure, particularly as related to air quality over Atlanta. Learning Objectives: 1 -- remote sensing data can be integral to an EPHTN; 2 -- public tracking objectives can be enhanced through remote sensing data; 3 -- NASA's involvement in public health applications can have wider benefits in the future.

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

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

Software Suite to Support In-Flight Characterization of Remote Sensing Systems

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Holekamp, Kara; Gasser, Gerald; Tabor, Wes; Vaughan, Ronald; Ryan, Robert; Pagnutti, Mary; Blonski, Slawomir; Kenton, Ross

2014-01-01

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Geospatial Education and Research Development: A Laboratory for Remote Sensing and Environmental Analysis (LaRSEA)

NASA Technical Reports Server (NTRS)

Allen, Thomas R., Jr.

1999-01-01

Old Dominion University has claimed the title "University of the 21st Century," with a bold emphasis on technology innovation and application. In keeping with this claim, the proposed work has implemented a new laboratory equipped for remote sensing as well as curriculum and research innovations afforded for present and future faculty and students. The developments summarized within this report would not have been possible without the support of the NASA grant and significant cost-sharing of several units within the University. The grant effectively spring-boarded the university into major improvements in its approach to remote sensing and geospatial information technologies. The university has now committed to licensing Erdas Imagine software for the laboratory, a campus-wide ESRI geographic information system (GIS) products license, and several smaller software and hardware utilities available to faculty and students through the laboratory. Campus beneficiaries of this grant have included faculty from departments including Ocean, Earth. and Atmospheric Sciences, Political Science and Geography, Ecological Sciences, Environmental Health, and Civil and Environmental Engineering. High student interest is evidenced in students in geology, geography, ecology, urban studies, and planning. Three new courses have been added to the catalog and offered this year. Cross-cutting curriculum changes are in place with growing enrollments in remote sensing, GIS, and a new co-taught seminar in applied coastal remote sensing. The enabling grant has also allowed project participants to attract external funding for research grants, thereby providing additional funds beyond the planned matching, maintenance and growth of software and hardware, and stipends for student assistants. Two undergraduate assistants and two graduate assistants have been employed by full-time assistantships as a result. A new certificate is offered to students completing an interdisciplinary course sequence in remote sensing and coastal environments. Subsequent phases of the project are under planning. including seminars for regional coastal managers and public dissemination of remote sensing science through the local media and university publications.

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

NASA Technical Reports Server (NTRS)

Kiang, Richard; Adimi, Farida; Kempler, Steven

2008-01-01

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

The application of remote sensing techniques: Technical and methodological issues

NASA Technical Reports Server (NTRS)

Polcyn, F. C.; Wagner, T. W.

1974-01-01

Capabilities and limitations of modern imaging electromagnetic sensor systems are outlined, and the products of such systems are compared with those of the traditional aerial photographic system. Focus is given to the interface between the rapidly developing remote sensing technology and the information needs of operational agencies, and communication gaps are shown to retard early adoption of the technology by these agencies. An assessment is made of the current status of imaging remote sensors and their potential for the future. Public sources of remote sensor data and several cost comparisons are included.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN)

USGS Publications Warehouse

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.

The role of remote sensing in global forest assessment: A remote sensing background paper for Kotka IV expert consultation; 01.07-05.07.2002, Kotka, Finland

Treesearch

Erkki Tomppo; Raymond L. Czaplewski; Kai Makisara

2002-01-01

The approach of FRA 2000 by FAO was the reliance on the participation of individual countries for both supply and analysis of information. It is hoped that this approach will lead for further capacity building in countries (FRA 2000 -main report). While countries firmly support this approach, it has sometimes been criticised on the basis that country information may be...

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Perspectives of methods of laser monitoring of the atmosphere and sea surface

NASA Astrophysics Data System (ADS)

Pashayev, Arif; Tunaboylu, Bahadir; Usta, Metin; Sadixov, Ilham; Allahverdiyev, Kerim

2016-01-01

Laser monitoring (remote sensing) may be considered as the science of collecting and interpreting information about the atmosphere, earth and sea using sensors on earth, on platforms in our atmosphere (airplanes, balloons) or in space (satellites) without being in direct physical contact with them. Remote sensing by LIDARs (Light Identification Detection and Ranging) has wide applications as technique to probe the Earth's atmosphere, ocean and land surfaces. LIDARs are widely used to get knowledge of spatial and temporal variations in meteorological quantities (e.g. temperature, humidity, clouds and aerosol properties) and to monitor the changes in these quantities on different timescales. Subject of the present work is quite wide. It is rather difficult to perform analysis and to provide full knowledge about existing information. In the present work, in addition to the literature data, the information will be provided also about KA-09 aerosol LIDAR developed at the Marmara Research Centre of TÜBITAK (Turkish Scientific and technological Research Council) and also about KA-14 LIDAR developed at the National Aviation Academy of Azerbaijan for remote sensing of contaminations on water surfaces taking place during oil-gas production. The main goal of this paper is to give students insight in different remote sensing instruments and techniques (including their perspectives) that are used for the derivation of meteorological quantities and obtaining the information about water surface.

PREFACE: 35th International Symposium on Remote Sensing of Environment (ISRSE35)

NASA Astrophysics Data System (ADS)

2014-03-01

35th International Symposium on Remote Sensing of Environment (ISRSE35) 22-26 April, 2013, Beijing, China The 35th International Symposium on Remote Sensing of Environment (ISRSE35) was successfully convened in Beijing, China, from April 22nd to 26th, 2013. This was the first event in the ISRSE series being held in China. The symposium was hosted by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, and co-organized by the International Center for Remote Sensing of Environment (ICRSE), the International Society for Photogrammetry and Remote Sensing (ISPRS), the Group on Earth Observations (GEO), the International Society for Digital Earth (ISDE) and the Chinese Academy of Sciences (CAS). The theme of the symposium was ''Earth Observation and Global Environmental Change''. Back in 1962, the first ISRSE was convened at the University of Michigan, USA. Over the past 50 years, Earth observation has advanced significantly, and remote sensing has become a mature technology for observing the Earth and monitoring global environmental change. At present, remote sensing has already entered an era of integrated, coordinated and sustainable global Earth observation and rapid development of spatial information services. It is very exciting to see that remote sensing technologies have become indispensable tools in numerous fields of Earth systems science, and are playing more and more important roles in areas such as land resources surveying and mapping, crop and forest monitoring, mineral exploration, urban development, ocean and coastlines resources surveillance, and in the monitoring and assessment of floods, droughts, forest fires, landslides and earthquakes. Thus, remote sensing has made great contributions to the socio-economic development of the world and it is anticipated that it will provide more powerful support in advancing the fields of Earth systems science and global change research. The 35th ISRSE was a platform for scientists and young scholars to exchange their research results from the cutting-edge frontiers of spatial information sciences, to review the history of remote sensing development and to consider the prospects for the future development of geospatial information. Therefore, this symposium was dedicated to marking the 50th anniversary of remote sensing especially focused on earth observation and global environmental change. The 35th ISRSE attracted over a thousand scientists and researchers from 56 countries and regions. The Technical Program Committee selected 346 oral presentations and 376 poster presentations, out of 1249 submitted abstracts. In order that the papers from this symposium could be published on a well-recognized platform, the organizers decided to produce refereed papers in IOP EES and invited all presenters to contribute to these proceedings. Each submitted paper was refereed by two anonymous reviewers, following the guidelines of the IOP's Peer Review Policy. The final collection of 279 papers covers a broad range of topics under 14 headings, which not only reflects the diversity of the presentations prompted by the current research hotspots related to remote sensing of the environment, but also witnesses to the increasingly mature development of the discipline. We would like to take this opportunity of the publication of the ISRSE35 Proceedings to express our gratitude to all the participants, especially those who contributed with presentations and manuscripts, for making ISRSE35 such a successful conference. Our thanks also go to our colleagues for their support and encouragement, particularly to the reviewers who worked very hard in reviewing the papers and provided thoughtful comments on the manuscripts. Finally, we sincerely hope that 35th ISRSE will prove to be a significant step forward in Earth observation technologies as applied to addressing the persistent challenges related to global sustainable development. Thank you for your interest and please enjoy the Proceedings. Editor-in-Chief: GUO Huadong Executive Editors: WANG Changlin, JING Linhai, WANG Lizhe, and CHEN Fang Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences The organizing structure of the 35th International Symposium on Remote Sensing of Environment can be found in the PDF.

Machine processing of remotely sensed data - quantifying global process: Models, sensor systems, and analytical methods; Proceedings of the Eleventh International Symposium, Purdue University, West Lafayette, IN, June 25-27, 1985

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

Mengel, S.K.; Morrison, D.B.

1985-01-01

Consideration is given to global biogeochemical issues, image processing, remote sensing of tropical environments, global processes, geology, landcover hydrology, and ecosystems modeling. Topics discussed include multisensor remote sensing strategies, geographic information systems, radars, and agricultural remote sensing. Papers are presented on fast feature extraction; a computational approach for adjusting TM imagery terrain distortions; the segmentation of a textured image by a maximum likelihood classifier; analysis of MSS Landsat data; sun angle and background effects on spectral response of simulated forest canopies; an integrated approach for vegetation/landcover mapping with digital Landsat images; geological and geomorphological studies using an image processing technique;more » and wavelength intensity indices in relation to tree conditions and leaf-nutrient content.« less

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.

Decision Support Systems To Manage Water Resources At Irrigation District Level In Southern Italy Using Remote Sensing Information. An Integrated Project (AQUATER)

NASA Astrophysics Data System (ADS)

Rinaldi, M.; Castrignanò, A.; Mastrorilli, M.; Rana, G.; Ventrella, D.; Acutis, M.; D'Urso, G.; Mattia, F.

2006-08-01

An efficient management of water resources is crucial point for Italy and in particular for southern areas characterized by Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. A three-year Project (2005-2008) has been funded by the Italian Ministry of Agriculture and Forestry Policies; it involves four Italian research institutions: the Agricultural Research Council (ISA, Bari), the National Research Council (ISSIA, Bari) and two Universities (Federico II-Naples and Milan). It is focused on the remote sensing, the plant and the climate and, for interdisciplinary relationships, the project working group consists of agronomists, engineers and physicists. The aims of the Project are: a) to produce a Decision Support System (DSS) combining remote sensing information, spatial data and simulation models to manage water resources in irrigation districts; b) to simulate irrigation scenarios to evaluate the effects of water stress on crop yield using agro-ecological indicators; c) to identify the most sensitive areas to drought risk in Southern Italy. The tools used in this Project will be: 1. Remote sensing images, topographic maps, soil and land use maps; 2. Geographic Information Systems; 3. Geostatistic methodologies; 4. Ground truth measurements (land use, canopy and soil temperatures, soil and plant water status, Normalized Difference Vegetation Index, Crop Water Stress Index, Leaf Area Index, actual evapotranspiration, crop coefficients, crop yield, agro-ecological indicators); 5. Crop simulation models. The Project is structured in four work packages with specific objectives, high degree of interaction and information exchange: 1) Remote Sensing and Image Analysis; 2) Cropping Systems; 3) Modelling and Softwares Development; 4) Stakeholders. The final product will be a DSS with the purpose of integrating remote sensing images, to estimate crop and soil variables related to drought, to assimilate these variables into a simulation model at district scale and, finally, to estimate evapotranspiration, plant water status and drought indicators. A project Web home page, a technical course about DSS for the employers of irrigation authorities and dissemination of results (meetings, publications, reports), are also planned.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

Photogrammetry - Remote Sensing and Geoinformation

NASA Astrophysics Data System (ADS)

Lazaridou, M. A.; Patmio, E. N.

2012-07-01

Earth and its environment are studied by different scientific disciplines as geosciences, science of engineering, social sciences, geography, etc. The study of the above, beyond pure scientific interest, is useful for the practical needs of man. Photogrammetry and Remote Sensing (defined by Statute II of ISPRS) is the art, science, and technology of obtaining reliable information from non-contact imaging and other sensor systems about the Earth and its environment, and other physical objects and of processes through recording, measuring, analyzing and representation. Therefore, according to this definition, photogrammetry and remote sensing can support studies of the above disciplines for acquisition of geoinformation. This paper concerns basic concepts of geosciences (geomorphology, geology, hydrology etc), and the fundamentals of photogrammetry-remote sensing, in order to aid the understanding of the relationship between photogrammetry-remote sensing and geoinformation and also structure curriculum in a brief, concise and coherent way. This curriculum can represent an appropriate research and educational outline and help to disseminate knowledge in various directions and levels. It resulted from our research and educational experience in graduate and post-graduate level (post-graduate studies relative to the protection of environment and protection of monuments and historical centers) in the Lab. of Photogrammetry - Remote Sensing in Civil Engineering Faculty of Aristotle University of Thessaloniki.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

PubMed

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

2014-11-01

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

Resource Management

NASA Technical Reports Server (NTRS)

1993-01-01

Summit Envirosolutions of Minneapolis, Minnesota, used remote sensing images as a source for groundwater resource management. Summit is a full-service environmental consulting service specializing in hydrogeologic, environmental management, engineering and remediation services. CRSP collected, processed and analyzed multispectral/thermal imagery and aerial photography to compare remote sensing and Geographic Information System approaches to more traditional methods of environmental impact assessments and monitoring.

Remote sensing techniques to assess active fire characteristics and post-fire effects

Treesearch

Leigh B. Lentile; Zachary A. Holden; Alistair M. S. Smith; Michael J. Falkowski; Andrew T. Hudak; Penelope Morgan; Sarah A. Lewis; Paul E. Gessler; Nate C. Benson

2006-01-01

Space and airborne sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Confusion about fire intensity, fire severity, burn severity, and related terms can result in the potential misuse of the inferred information by land managers and remote sensing practitioners who require unambiguous...

Techniques of remote sensing and GIS as tools for visualizing impact of climate change-induced flood in the southern African region.

USDA-ARS?s Scientific Manuscript database

This study employs remote sensing and Geographical Information Systems (GIS) data to visualize the impact of climate change caused by flooding in the Southern African region in order to assist decision makers’ plans for future occurrences. In pursuit of this objective, this study uses Digital Elevat...

Remote sensing techniques aid in preattack planning for fire management

Treesearch

Lucy Anne Salazar

1982-01-01

Remote sensing techniques were investigated as an alternative for documenting selected prettack fire planning information. Locations of fuel models, road systems, and water sources were recorded by Landsat satellite imagery and aerial photography for a portion of the Six Rivers National Forest in northwestern California. The two fuel model groups used were from the...

Remote sensing and the pelagic fisheries environment off Oregon

NASA Technical Reports Server (NTRS)

Pearcy, W. G.

1970-01-01

Remote sensing oceanography at Oregon State University is part of a multidisciplinary research program: (1) to learn more about nearshore oceanographic processes and how they affect the production of marine life and the availability of albacore tuna; and (2) to provide fishermen with information in near real time that will be useful in scouting for albacore concentrations.

Second Eastern Regional Remote Sensing Applications Conference

NASA Technical Reports Server (NTRS)

Imhoff, M. L. (Editor); Witt, R. G. (Editor); Kugelmann, D. (Editor)

1981-01-01

Participants from state and local governments share experiences in remote sensing applications with one another and with users in the Federal government, universities, and the private sector during technical sessions and forums covering agriculture and forestry; land cover analysis and planning; surface mining and energy; data processing; water quality and the coastal zone; geographic information systems; and user development programs.

The focus series: A collection of single-concept remote sensing educational materials

NASA Technical Reports Server (NTRS)

Davis, S. M.

1977-01-01

The FOCUS series is a collection of two-page foldout documents each consisting of a diagram or photograph and an extended option of three to four hundred words. The series was developed to present basic remote sensing concepts in a simple, concise way. Issues currently available are collected in this information note.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.

1976-01-01

A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

Evaluating the potential of image fusion of multispectral and radar remote sensing data for the assessment of water body structure

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.

Predicting Near-Term Water Quality from Satellite Observations of Watershed Conditions

NASA Astrophysics Data System (ADS)

Weiss, W. J.; Wang, L.; Hoffman, K.; West, D.; Mehta, A. V.; Lee, C.

2017-12-01

Despite the strong influence of watershed conditions on source water quality, most water utilities and water resource agencies do not currently have the capability to monitor watershed sources of contamination with great temporal or spatial detail. Typically, knowledge of source water quality is limited to periodic grab sampling; automated monitoring of a limited number of parameters at a few select locations; and/or monitoring relevant constituents at a treatment plant intake. While important, such observations are not sufficient to inform proactive watershed or source water management at a monthly or seasonal scale. Satellite remote sensing data on the other hand can provide a snapshot of an entire watershed at regular, sub-monthly intervals, helping analysts characterize watershed conditions and identify trends that could signal changes in source water quality. Accordingly, the authors are investigating correlations between satellite remote sensing observations of watersheds and source water quality, at a variety of spatial and temporal scales and lags. While correlations between remote sensing observations and direct in situ measurements of water quality have been well described in the literature, there are few studies that link remote sensing observations across a watershed with near-term predictions of water quality. In this presentation, the authors will describe results of statistical analyses and discuss how these results are being used to inform development of a desktop decision support tool to support predictive application of remote sensing data. Predictor variables under evaluation include parameters that describe vegetative conditions; parameters that describe climate/weather conditions; and non-remote sensing, in situ measurements. Water quality parameters under investigation include nitrogen, phosphorus, organic carbon, chlorophyll-a, and turbidity.

Recommendations concerning satellite-acquired earth resource data: 1982 report of the Data Management Subcommittee of the GEOSAT Committee, Incorporated

NASA Technical Reports Server (NTRS)

1982-01-01

End user concerns about the content and accessibility of libraries of remote sensing data in general are addressed. Recommendations pertaining to the United States' satellite remote sensing programs urge: (1) the continuation of the NASA/EROS Data Center program to convert pre-1979 scenes to computer readable tapes and create a historical archive of this valuable data; (2) improving the EROS archive by adding geologically interesting scenes, data from other agencies (including previously classified data), and by adopting a policy to retire data from the archive; (3) establishing a computer data base inquiry system that includes remote sensing data from all publically available sources; (4) capability for prepurchase review and evaluation; (5) a flexible price structure; and (6) adoption of standard digital data products format. Information about LANDSAT 4, the status of worldwide LANDSAT receiving stations, future non-U.S. remote sensing satellites, a list of sources for LANDSAT data, and the results of a survey of GEOSAT members' remote sensing data processing systems are also considered.

Narragansett Bay From Space: A Perspective for the 21st Century

NASA Technical Reports Server (NTRS)

Mustard, John F.; Swanson, Craig; Deacutis, Chris

2001-01-01

In 1996, the NASA Administrator Dan Goldin and Rhode Island Congressman Patrick Kennedy challenged researchers in the Department of Geological Sciences at Brown University to developed a series of projects to apply remotely sensed data to problems of immediate concern to the State of Rhode Island. The result of that challenge was the project Narragansett Bay from Space: A Perspective for the 21st Century. The goals of the effort were to a) identify problems in coordination with state and local agencies, b) apply NASA technology to the problems and c) to involve small business that would benefit from incorporating remotely sensed data into their business operations. The overall effort was to serve two functions: help provide high quality science results based on remotely sensed data and increase the capacity of environmental managers and companies to use remotely sensed data. The effort has succeeded on both these fronts by providing new, quantitative information on the extent of environmental problems and developing a greater awareness and acceptance of remotely sensed data as a tool for monitoring and research.

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

NASA Technical Reports Server (NTRS)

Czaja, Wojciech; Le Moigne-Stewart, Jacqueline

2014-01-01

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

PubMed Central

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-01-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment. PMID:27922592

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

NASA Astrophysics Data System (ADS)

Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

2016-12-01

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

Distributed solar photovoltaic array location and extent dataset for remote sensing object identification.

PubMed

Bradbury, Kyle; Saboo, Raghav; L Johnson, Timothy; Malof, Jordan M; Devarajan, Arjun; Zhang, Wuming; M Collins, Leslie; G Newell, Richard

2016-12-06

Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Estimates of Leaf Relative Water Content from Optical Polarization Measurements

NASA Astrophysics Data System (ADS)

Dahlgren, R. P.; Vanderbilt, V. C.; Daughtry, C. S. T.

2017-12-01

Remotely sensing the water status of plant canopies remains a long term goal of remote sensing research. Existing approaches to remotely sensing canopy water status, such as the Crop Water Stress Index (CWSI) and the Equivalent Water Thickness (EWT), have limitations. The CWSI, based upon remotely sensing canopy radiant temperature in the thermal infrared spectral region, does not work well in humid regions, requires estimates of the vapor pressure deficit near the canopy during the remote sensing over-flight and, once stomata close, provides little information regarding the canopy water status. The EWT is based upon the physics of water-light interaction in the 900-2000nm spectral region, not plant physiology. Our goal, development of a remote sensing technique for estimating plant water status based upon measurements in the VIS/NIR spectral region, would potentially provide remote sensing access to plant dehydration physiology - to the cellular photochemistry and structural changes associated with water deficits in leaves. In this research, we used optical, crossed polarization filters to measure the VIS/NIR light reflected from the leaf interior, R, as well as the leaf transmittance, T, for 78 corn (Zea mays) and soybean (Glycine max) leaves having relative water contents (RWC) between 0.60 and 0.98. Our results show that as RWC decreases R increases while T decreases. Our results tie R and T changes in the VIS/NIR to leaf physiological changes - linking the light scattered out of the drying leaf interior to its relative water content and to changes in leaf cellular structure and pigments. Our results suggest remotely sensing the physiological water status of a single leaf - and perhaps of a plant canopy - might be possible in the future.

The Solar Spectrum: An Atmospheric Remote Sensing Perspective

NASA Technical Reports Server (NTRS)

Toon, Geoff

2013-01-01

The solar spectrum not only contains information about the composition and structure of the sun, it also provides a bright and stable continuum source for earth remote sensing (atmosphere and surface). Many types of remote sensors use solar radiation. While high-resolution spaceborne sensors (e.g. ACE) can largely remove the effects of the solar spectrum by exo-atmospheric calibration, this isn't an option for sub-orbital sensors, such as the FTIR spectrometers used in the NDACC and TCCON networks. In this case the solar contribution must be explicitly included in the spectral analysis. In this talk the methods used to derive the solar spectrum are presented, and the underlying solar physics are discussed. Implication for remote sensing are described.

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

USGS Publications Warehouse

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

1996-01-01

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

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.

A Remote Sensing Image Fusion Method based on adaptive dictionary learning

NASA Astrophysics Data System (ADS)

He, Tongdi; Che, Zongxi

2018-01-01

This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

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.

Remote Sensing of Terrestrial Snow and Ice for Global Change Studies

NASA Technical Reports Server (NTRS)

Kelly, Richard; Hall, Dorothy K.

2007-01-01

Snow and ice play a significant role in the Earth's water cycle and are sensitive and informative indicators climate change. Significant changes in terrestrial snow and ice water storage are forecast, and while evidence of large-scale changes is emerging, in situ measurements alone are insufficient to help us understand and explain these changes. Imaging remote sensing systems are capable of successfully observing snow and ice in the cryosphere. This chapter examines how those remote sensing sensors, that now have more than 35 years of observation records, are capable of providing information about snow cover, snow water equivalent, snow melt, ice sheet temperature and ice sheet albedo. While significant progress has been made, especially in the last five years, a better understanding is required of the records of satellite observations of these cryospheric variables.

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

PubMed Central

Brolly, Matthew; Woodhouse, Iain H.; Niklas, Karl J.; Hammond, Sean T.

2012-01-01

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100. PMID:22457800

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

NASA Astrophysics Data System (ADS)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product validation.

A macroecological analysis of SERA derived forest heights and implications for forest volume remote sensing.

PubMed

Brolly, Matthew; Woodhouse, Iain H; Niklas, Karl J; Hammond, Sean T

2012-01-01

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H₁₀₀.

Hyperspectral forest monitoring and imaging implications

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Bannon, David

2014-05-01

The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

Selecting reconnaissance strategies for floodplain surveys

NASA Technical Reports Server (NTRS)

Sollers, S. C.; Rango, A.; Henninger, D. L.

1977-01-01

Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to flood-plain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The digital approach permitted LANDSAT results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas as opposed to areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.

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.

Urbanization in Pearl River Delta area in past 20 years: remote sensing of impact on water quality

NASA Astrophysics Data System (ADS)

Wang, Yunpeng; Fan, Fenglei; Zhang, Jinqu; Xia, Hao; Ye, Chun

2004-11-01

The Pearl River Delta of Guangdong province in China is one of the world"s largest growths in urbanization for the past 20 years. The objective of this research is to explore the relationship between urbanization and water quality in this area. Present and past remote sensing data including MSS< TM/ETM and ASTER are used to research the urbanization and its impact on water quality. Land use and water quality information are extracted from remote sensing data. Data of population, industrial and agricultural productivity indices are integrated with the thematic maps derived from remote sensing data by GIS method. Spatial analysis methods are applied on these data and the results indicate that population, waste water both from household and industrial and chemical fertilizer consumptions are main controls of the regional water quality and environment.

American Society for Photogrammetry and Remote Sensing and ACSM, Fall Convention, Reno, NV, Oct. 4-9, 1987, ASPRS Technical Papers

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

Not Available

1987-01-01

Recent advances in remote-sensing technology and applications are examined in reviews and reports. Topics addressed include the use of Landsat TM data to assess suspended-sediment dispersion in a coastal lagoon, the use of sun incidence angle and IR reflectance levels in mapping old-growth coniferous forests, information-management systems, Large-Format-Camera soil mapping, and the economic potential of Landsat TM winter-wheat crop-condition assessment. Consideration is given to measurement of ephemeral gully erosion by airborne laser ranging, the creation of a multipurpose cadaster, high-resolution remote sensing and the news media, the role of vegetation in the global carbon cycle, PC applications in analytical photogrammetry,more » multispectral geological remote sensing of a suspected impact crater, fractional calculus in digital terrain modeling, and automated mapping using GP-based survey data.« less

Application of remote sensing to monitoring and studying dispersion in ocean dumping

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Ohlhorst, C. W.

1981-01-01

Remotely sensed wide area synoptic data provides information on ocean dumping that is not readily available by other means. A qualitative approach has been used to map features, such as river plumes. Results of quantitative analyses have been used to develop maps showing quantitative distributions of one or more water quality parameters, such as suspended solids or chlorophyll a. Joint NASA/NOAA experiments have been conducted at designated dump areas in the U.S. coastal zones to determine the applicability of aircraft remote sensing systems to map plumes resulting from ocean dumping of sewage sludge and industrial wastes. A second objective is related to the evaluation of previously developed quantitative analysis techniques for studying dispersion of materials in these plumes. It was found that plumes resulting from dumping of four waste materials have distinctive spectral characteristics. The development of a technology for use in a routine monitoring system, based on remote sensing techniques, is discussed.

Use of remote sensing techniques for inventorying and planning utilization of land resources in South Dakota

NASA Technical Reports Server (NTRS)

Myers, V. I.; Frazee, C. J.; Rusche, A. E.; Moore, D. G.; Nelson, G. D.; Westin, F. C.

1974-01-01

The basic procedures for interpreting remote sensing imagery to rapidly develop general soils and land use inventories were developed and utilized in Pennington County, South Dakota. These procedures and remote sensing data products were illustrated and explained to many user groups, some of whom are interested in obtaining similar data. The general soils data were integrated with land soils data supplied by the county director of equalization to prepare a land value map. A computer print-out of this map indicating a land value for each quarter section is being used in tax reappraisal of Pennington County. The land use data provided the land use planners with the present use of land in Pennington County. Additional uses of remote sensing applications are also discussed including tornado damage assessment, hail damage evaluation, and presentation of soil and land value information on base maps assembled from ERTS-1 imagery.

Satellite remote sensing for hydrology and water management

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

Barrett, E.C.; Power, C.H.; Micallef, A.

Interest in satellite remote sensing is fast moving away from pure science and individual case studies towards truly operational applications. At the same time the micro-computer revolution is ensuring that data reception and processing facilities need no longer be the preserve of a small number of global centers, but can be common-place installations in smaller countries and even local regional agency offices or laboratories. As remote sensing matures, and its applications proliferate, a new type of treatment is required to ensure both that decision makers, managers and engineers with problems to solve are informed of today's opportunities and that scientistsmore » are provided with integrated overviews of the ever-growing need for their services. This book addresses these needs uniquely focusing on the area bounded by satellite remote sensing, pure and applied hydrological sciences, and a specific world region, namely the Mediterranean basin.« less

China national space remote sensing infrastructure and its application

NASA Astrophysics Data System (ADS)

Li, Ming

2016-07-01

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

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Earth remote sensing - 1970-1995

NASA Technical Reports Server (NTRS)

Thome, P. G.

1984-01-01

The past-achievements, current status, and future prospects of the Landsat terrestrial-remote-sensing satellite program are surveyed. Topics examined include the early history of space flight; the development of analysis techniques to interpret the multispectral images obtained by Landsats 1, 2, and 3; the characteristics of the advanced Landsat-4 Thematic Mapper; microwave scanning by Seasat and the Shuttle Imaging Radar; the usefulness of low-resolution AVHRR data from the NOAA satellites; improvements in Landsats 4 and 5 to permit tailoring of information to user needs; expansion and internationalization of the remote-sensing market in the late 1980s; and technological advances in both instrumentation and data-processing predicted by the 1990s.

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

USGS Publications Warehouse

Jones, J.W.

2011-01-01

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

Remote sensing of suspended sediment water research: principles, methods, and progress

NASA Astrophysics Data System (ADS)

Shen, Ping; Zhang, Jing

2011-12-01

In this paper, we reviewed the principle, data, methods and steps in suspended sediment research by using remote sensing, summed up some representative models and methods, and analyzes the deficiencies of existing methods. Combined with the recent progress of remote sensing theory and application in water suspended sediment research, we introduced in some data processing methods such as atmospheric correction method, adjacent effect correction, and some intelligence algorithms such as neural networks, genetic algorithms, support vector machines into the suspended sediment inversion research, combined with other geographic information, based on Bayesian theory, we improved the suspended sediment inversion precision, and aim to give references to the related researchers.

RFI and Remote Sensing of the Earth from Space

NASA Technical Reports Server (NTRS)

Le Vine, D. M.; Johnson, J. T.; Piepmeier, J.

2016-01-01

Passive microwave remote sensing of the Earth from space provides information essential for understanding the Earth's environment and its evolution. Parameters such as soil moisture, sea surface temperature and salinity, and profiles of atmospheric temperature and humidity are measured at frequencies determined by the physics (e.g. sensitivity to changes in desired parameters) and by the availability of suitable spectrum free from interference. Interference from manmade sources (radio frequency interference) is an impediment that in many cases limits the potential for accurate measurements from space. A review is presented here of the frequencies employed in passive microwave remote sensing of the Earth from space and the associated experience with RFI.

Propagation Limitations in Remote Sensing.

DTIC Science & Technology

Contents: Multi-sensors and systems in remote sensing ; Radar sensing systems over land; Remote sensing techniques in oceanography; Influence of...propagation media and background; Infrared techniques in remote sensing ; Photography in remote sensing ; Analytical studies in remote sensing .

Guide to remote-sensor data systems

NASA Technical Reports Server (NTRS)

Dewitt, R. R.; Ellison, J. L.

1980-01-01

Remote sensing data-handbook presents theoretical and practical information on spaceborne sensors and associated systems for Earth-resources applications. Handbook provides discussion on historical information, principles of operations, factors affecting performances, nature of data output, and system required to process data and trends in research and development.

Use of remote sensing and a geographical information system in a national helminth control programme in Chad.

PubMed Central

Brooker, Simon; Beasley, Michael; Ndinaromtan, Montanan; Madjiouroum, Ester Mobele; Baboguel, Marie; Djenguinabe, Elie; Hay, Simon I.; Bundy, Don A. P.

2002-01-01

OBJECTIVE: To design and implement a rapid and valid epidemiological assessment of helminths among schoolchildren in Chad using ecological zones defined by remote sensing satellite sensor data and to investigate the environmental limits of helminth distribution. METHODS: Remote sensing proxy environmental data were used to define seven ecological zones in Chad. These were combined with population data in a geographical information system (GIS) in order to define a sampling protocol. On this basis, 20 schools were surveyed. Multilevel analysis, by means of generalized estimating equations to account for clustering at the school level, was used to investigate the relationship between infection patterns and key environmental variables. FINDINGS: In a sample of 1023 schoolchildren, 22.5% were infected with Schistosoma haematobium and 32.7% with hookworm. None were infected with Ascaris lumbricoides or Trichuris trichiura. The prevalence of S. haematobium and hookworm showed marked geographical heterogeneity and the observed patterns showed a close association with the defined ecological zones and significant relationships with environmental variables. These results contribute towards defining the thermal limits of geohelminth species. Predictions of infection prevalence were made for each school surveyed with the aid of models previously developed for Cameroon. These models correctly predicted that A. lumbricoides and T. trichiura would not occur in Chad but the predictions for S. haematobium were less reliable at the school level. CONCLUSION: GIS and remote sensing can play an important part in the rapid planning of helminth control programmes where little information on disease burden is available. Remote sensing prediction models can indicate patterns of geohelminth infection but can only identify potential areas of high risk for S. haematobium. PMID:12471398

Developing particle emission inventories using remote sensing (PEIRS).

PubMed

Tang, Chia-Hsi; Coull, Brent A; Schwartz, Joel; Lyapustin, Alexei I; Di, Qian; Koutrakis, Petros

2017-01-01

Information regarding the magnitude and distribution of PM 2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM 2.5 . This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R 2 = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM 2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

The Use of a Geographic Information System and Remote Sensing Technology for Monitoring Land Use and Soil Carbon Change in the Subtropical Dry Forest Life Zone of Puerto Rico

NASA Technical Reports Server (NTRS)

Velez-Rodriguez, Linda L. (Principal Investigator)

1996-01-01

Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.

Program on Earth Observation Data Management Systems (EODMS)

NASA Technical Reports Server (NTRS)

Eastwood, L. F., Jr.; Gohagan, J. K.; Hill, C. T.; Morgan, R. P.; Hays, T. R.; Ballard, R. J.; Crnkovick, G. R.; Schaeffer, M. A.

1976-01-01

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-05

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

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 5 : automated management bridge information system.

DOT National Transportation Integrated Search

2009-12-01

This volume focuses on one of the key components of the IRSV system, i.e., the AMBIS module. This module serves as one of : the tools used in this study to translate raw remote sensing data in the form of either high-resolution aerial photos or v...

Linking Climate Change Education through the Integration of a Kite-Borne Remote Sensing System: Linking Climate Change Education and Remote Sensing

ERIC Educational Resources Information Center

Xie, Yichun; Henry, Andy; Bydlowski, David; Musial, Joseph

2014-01-01

A majority of secondary science teachers are found to include the topic of climate change in their courses. However, teachers informally and sporadically discuss climate change and students rarely understand the underlying scientific concepts. The project team developed an innovative pedagogical approach, in which teachers and students learn…

Book Review

NASA Astrophysics Data System (ADS)

Clevers, Jan G. P. W.

2018-05-01

This book provides a comprehensive and timely overview on all aspects of hyperspectral remote sensing combined with various applications. As such, it is an excellent book of reference for both students and professionals active in the field of optical remote sensing. It deals with all aspects of retrieving quantitative information on biophysical properties of the Earth's surface, the data corrections needed and the range of analysis approaches available.

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

NASA Technical Reports Server (NTRS)

Khorram, S.; Smith, H. G.

1979-01-01

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

Tools and Services for Working with Multiple Land Remote Sensing Data Products

NASA Astrophysics Data System (ADS)

Krehbiel, C.; Friesz, A.; Harriman, L.; Quenzer, R.; Impecoven, K.; Maiersperger, T.

2016-12-01

The availability of increasingly large and diverse satellite remote sensing datasets provides both an opportunity and a challenge across broad Earth science research communities. On one hand, the extensive assortment of available data offer unprecedented opportunities to improve our understanding of Earth science and enable data use across a multitude of science disciplines. On the other hand, increasingly complex formats, data structures, and metadata can be an obstacle to data use for the broad user community that is interested in incorporating remote sensing Earth science data into their research. NASA's Land Processes Distributed Active Archive Center (LP DAAC) provides easy to use Python notebook tutorials for services such as accessing land remote sensing data from the LP DAAC Data Pool and interpreting data quality information from MODIS. We use examples to demonstrate the capabilities of the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), such as spatially and spectrally subsetting data, decoding valuable quality information, and exploring initial analysis results within the user interface. We also show data recipes for R and Python scripts that help users process ASTER L1T and ASTER Global Emissivity Datasets.

The AmericaView Project - Putting the Earth into Your Hands

USGS Publications Warehouse

,

2005-01-01

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

Review of FEWS NET Biophysical Monitoring Requirements

NASA Technical Reports Server (NTRS)

Ross, K. W.; Brown, Molly E.; Verdin, J.; Underwood, L. W.

2009-01-01

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information.

Applying high resolution remote sensing image and DEM to falling boulder hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Changqing; Shi, Wenzhong; Ng, K. C.

2005-10-01

Boulder fall hazard assessing generally requires gaining the boulder information. The extensive mapping and surveying fieldwork is a time-consuming, laborious and dangerous conventional method. So this paper proposes an applying image processing technology to extract boulder and assess boulder fall hazard from high resolution remote sensing image. The method can replace the conventional method and extract the boulder information in high accuracy, include boulder size, shape, height and the slope and aspect of its position. With above boulder information, it can be satisfied for assessing, prevention and cure boulder fall hazard.

Remote Sensing for Farmers and Flood Watching

NASA Technical Reports Server (NTRS)

2005-01-01

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

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

NASA Astrophysics Data System (ADS)

Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar

2012-10-01

Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

PubMed Central

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-01-01

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection. PMID:28587299

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

A Decision Support Information System for Urban Landscape Management Using Thermal Infrared Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Rickman, Douglas L.; Estes, Maurice G., Jr.; Laymon, Charles A.; Howell, Burgess F.

2000-01-01

In this paper, we describe efforts to use remote sensing data within the purview of an information support system, to assess urban thermal landscape characteristics as a means for developing more robust models of the Urban Heat Island (UHI) effect. We also present a rationale on how we have successfully translated the results from the study of urban thermal heating and cooling regimes as identified from remote sensing data, to decision-makers, planners, government officials, and the public at large in several US cities to facilitate better understanding of how the UHI affects air quality. Additionally, through the assessment of the spatial distribution of urban thermal landscape characteristics using remote sensing data, it is possible to develop strategies to mitigate the UHI that hopefully will in turn, drive down ozone levels and improve overall urban air quality. Four US cities have been the foci for intensive analysis as part of our studies: Atlanta, GA, Baton Rouge, LA, Salt Lake City, UT, and Sacramento, CA. The remote sensing data for each of these cities has been used to generate a number of products for use by "stakeholder" working groups to convey information on what the effects are of the UHI and what measures can be taken to mitigate it. In turn, these data products are used to both educate and inform policy-makers, planners, and the general public about what kinds of UHI mitigation strategies are available.

The potential of volunteered geographic information to investigate peri-urbanization in the conservation zone of Mexico City.

PubMed

Heider, Katharina; Lopez, Juan Miguel Rodriguez; Scheffran, Jürgen

2018-03-14

Due to the availability of Web 2.0 technologies, volunteered geographic information (VGI) is on the rise. This new type of data is available on many topics and on different scales. Thus, it has become interesting for research. This article deals with the collective potential of VGI and remote sensing to detect peri-urbanization in the conservation zone of Mexico City. On the one hand, remote sensing identifies horizontal urban expansion, and on the other hand, VGI of ecological complaints provides data about informal settlements. This enables the combination of top-down approaches (remote sensing) and bottom-up approaches (ecological complaints). Within the analysis, we identify areas of high urbanization as well as complaint densities and bring them together in a multi-scale analysis using Geographic Information Systems (GIS). Furthermore, we investigate the influence of settlement patterns and main roads on the peri-urbanization process in Mexico City using OpenStreetMap. Peri-urbanization is detected especially in the transition zone between the urban and rural (conservation) area and near main roads as well as settlements.

Application of remotely sensed land-use information to improve estimates of streamflow characteristics, volume 8. [Maryland, Virginia, and Delaware

NASA Technical Reports Server (NTRS)

Pluhowski, E. J. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Land use data derived from high altitude photography and satellite imagery were studied for 49 basins in Delaware, and eastern Maryland and Virginia. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, demonstrated that land use data from high altitude photography provided an effective means of significantly improving estimates of stream flow. Forty stream flow characteristic equations for incorporating remotely sensed land use information, were compared with a control set of equations using map derived land cover. Significant improvement was detected in six equations where level 1 data was added and in five equations where level 2 information was utilized. Only four equations were improved significantly using land use data derived from LANDSAT imagery. Significant losses in accuracy due to the use of remotely sensed land use information were detected only in estimates of flood peaks. Losses in accuracy for flood peaks were probably due to land cover changes associated with temporal differences among the primary land use data sources.

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

NASA Astrophysics Data System (ADS)

KIM, J.; Bastidas, L. A.

2011-12-01

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

RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Kang, L.

2014-12-01

Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.

eFarm: A Tool for Better Observing Agricultural Land Systems

PubMed Central

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

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

NASA Technical Reports Server (NTRS)

Wychgram, D. C.

1972-01-01

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

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

NASA Technical Reports Server (NTRS)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

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

Initial Scientific Assessment of the EOS Data and Information System (EOSDIS)

NASA Technical Reports Server (NTRS)

1989-01-01

Crucial to the success of the Earth Observing System (Eos) is the Eos Data and Information System (EosDIS). The goals of Eos depend not only on its instruments and science investigations, but also on how well EosDlS helps scientists integrate reliable, large-scale data sets of geophysical and biological measurements made from Eos data, and on how successfully Eos scientists interact with other investigations in Earth System Science. Current progress in the use of remote sensing for science is hampered by requirements that the scientist understand in detail the instrument, the electromagnetic properties of the surface, and a suite of arcane tape formats, and by the immaturity of some of the techniques for estimating geophysical and biological variables from remote sensing data. These shortcomings must be transcended if remote sensing data are to be used by a much wider population of scientists who study environmental change at regional and global scales.

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.

Japan's efforts to promote global health using satellite remote sensing data from the Japan Aerospace Exploration Agency for prediction of infectious diseases and air quality.

PubMed

Igarashi, Tamotsu; Kuze, Akihiko; Sobue, Shinichi; Yamamoto, Aya; Yamamoto, Kazuhide; Oyoshi, Kei; Imaoka, Keiji; Fukuda, Toru

2014-12-01

In this paper we review the status of new applications research of the Japanese Aerospace Exploration Agency (JAXA) for global health promotion using information derived from Earth observation data by satellites in cooperation with inter-disciplinary collaborators. Current research effort at JAXA to promote global public health is focused primarily on the use of remote sensing to address two themes: (i) prediction models for malaria and cholera in Kenya, Africa; and (ii) air quality assessment of small, particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Respiratory and cardivascular diseases constitute cross-boundary public health risk issues on a global scale. The authors report here on results of current of a collaborative research to call attention to the need to take preventive measures against threats to public health using newly arising remote sensing information from space.

Improving tsunami warning systems with remote sensing and geographical information system input.

PubMed

Wang, Jin-Feng; Li, Lian-Fa

2008-12-01

An optimal and integrative tsunami warning system is introduced that takes full advantage of remote sensing and geographical information systems (GIS) in monitoring, forecasting, detection, loss evaluation, and relief management for tsunamis. Using the primary impact zone in Banda Aceh, Indonesia as the pilot area, we conducted three simulations that showed that while the December 26, 2004 Indian Ocean tsunami claimed about 300,000 lives because there was no tsunami warning system at all, it is possible that only about 15,000 lives could have been lost if the area had used a tsunami warning system like that currently in use in the Pacific Ocean. The simulations further calculated that the death toll could have been about 3,000 deaths if there had been a disaster system further optimized with full use of remote sensing and GIS, although the number of badly damaged or destroyed houses (29,545) could have likely remained unchanged.

Family Life Cycle and Deforestation in Amazonia: Combining Remotely Sensed Information with Primary Data

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.

Near real time water quality monitoring of Chivero and Manyame lakes of Zimbabwe

NASA Astrophysics Data System (ADS)

Muchini, Ronald; Gumindoga, Webster; Togarepi, Sydney; Pinias Masarira, Tarirai; Dube, Timothy

2018-05-01

Zimbabwe's water resources are under pressure from both point and non-point sources of pollution hence the need for regular and synoptic assessment. In-situ and laboratory based methods of water quality monitoring are point based and do not provide a synoptic coverage of the lakes. This paper presents novel methods for retrieving water quality parameters in Chivero and Manyame lakes, Zimbabwe, from remotely sensed imagery. Remotely sensed derived water quality parameters are further validated using in-situ data. It also presents an application for automated retrieval of those parameters developed in VB6, as well as a web portal for disseminating the water quality information to relevant stakeholders. The web portal is developed, using Geoserver, open layers and HTML. Results show the spatial variation of water quality and an automated remote sensing and GIS system with a web front end to disseminate water quality information.

Remote sensing of the boundary layer over the oceans. [by IRIS measurements

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Dalu, G.; Nath, N. R.; Lo, R.

1978-01-01

The paper explores the possibility of remotely sensing the boundary layer structure over the oceans by means of the Nimbus 4 IR Interferometric Spectrometer (IRIS) measurements in the water vapor bands. It is found from theoretical considerations that the moderately strong spectral lines in the 9-micron water vapor window region contain useful information about the lowest layers in the atmosphere. The difference between the observed line strength and the theoretically predicted line strength provides information about the departure in the atmospheric temperature and water vapor profiles from standard conditions. The observations of METEOR oceanographic expedition over the North and South Atlantic, and the Indian Ocean expedition make it possible to model the inversion conditions. It is concluded that significant characteristics of the temperature and water vapor profiles in the boundary layer of the atmosphere can be remotely sensed using the water vapor spectral measurements over the oceans.

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.

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Hyperspectral remote sensing of the responses of vegetation ecosystems to physical and biological changes of the environment

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.

Needs and emerging trends of remote sensing

NASA Astrophysics Data System (ADS)

McNair, Michael

2014-06-01

From the earliest need to be able to see an enemy over a hill to sending semi-autonomous platforms with advanced sensor packages out into space, humans have wanted to know more about what is around them. Issues of distance are being minimized through advances in technology to the point where remote control of a sensor is useful but sensing by way of a non-collocated sensor is better. We are not content to just sense what is physically nearby. However, it is not always practical or possible to move sensors to an area of interest; we must be able to sense at a distance. This requires not only new technologies but new approaches; our need to sense at a distance is ever changing with newer challenges. As a result, remote sensing is not limited to relocating a sensor but is expanded into possibly deducing or inferring from available information. Sensing at a distance is the heart of remote sensing. Much of the sensing technology today is focused on analysis of electromagnetic radiation and sound. While these are important and the most mature areas of sensing, this paper seeks to identify future sensing possibilities by looking beyond light and sound. By drawing a parallel to the five human senses, we can then identify the existing and some of the future possibilities. A further narrowing of the field of sensing causes us to look specifically at robotic sensing. It is here that this paper will be directed.

Advanced and applied remote sensing of environmental conditions

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.

2013-01-01

"Remote sensing” is a general 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 U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Space-Derived Imagery and a Commercial Remote Sensing Industry: Impossible Dream or Inevitable Reality?

NASA Astrophysics Data System (ADS)

Murray, Felsher

Landsat-1 was launched in 1972 as a research satellite. Many of us viewed this satellite as a precursor to remote sensing "commercialization." Indeed since that time, the birth, growth and maturation of a remote sensing "industry" has been an ongoing objective for much of the U.S. private sector engaged in space and ground-segment activities related to the acquisition, analysis, and dissemination of imagery. In September 1999 a U.S. commercial entity, Space Imaging, Inc. launched its 1-meter pan/4-meter multispectral IKONOS sensor. DigitalGlobe, Inc. (nee EarthWatch, Inc.) matched this feat in October 2001. Thus, a full 30 years later, we are finally on the brink of building a true remote sensing information industry based on the global availability of competitively-priced space- derived imagery of the Earth. The upcoming availability of similar imagery from non-U.S. sources as ImageSat and U.S. sources as ORBIMAGE will only strengthen that reality. However, a remote sensing industry can only grow by allowing these entities (in times of peace) unencumbered access to a world market. And that market continues to expand -- up 11% in 2001, with gross revenues of U.S. commercial remote sensing firms alone reaching 2.44 billion, according to a joint NASA/ASPRS industry survey. However, the 30-year gap between the research-labeled Landsat-1 and our current commercial successes was not technology-driven. That lacuna was purely political -- driven by valid concerns related to national security. Although the world's governments have cooperated thoroughly and completely in areas related to satellite telecommunications, cooperation in space-derived image information is still today done cautiously and on a case-by-case basis -- and then only for science- based undertakings. It is still a fact that, except for the United States, all other Earth-imaging satellites/sensors flying today are owned, operated, and their products disseminated, by national governments -- and not private sector entities. Will the template now fashioned by the U.S. -- that of licensing private industry to build, fly, and operate remote sensing satellites as well as to distribute their imagery worldwide -- be replicated by other nations? Eventually, yes. Availability of the World Wide Web is an international communications reality. Availability of world wide imaging will be just as real. And much of that imagery will be marketed, sold, and distributed via that same global Internet. I feel that as an expected outcome of our technological age, we can ensure not only our own national security but international security as well, by assuring worldwide accessibility to worldwide space- derived image information. This requires -- in fact demands -- the presence of a viable international remote sensing industry. It is not impossible; It is inevitable.

Construction of an unmanned aerial vehicle remote sensing system for crop monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seungtaek; Ko, Jonghan; Kim, Mijeong; Kim, Jongkwon

2016-04-01

We constructed a lightweight unmanned aerial vehicle (UAV) remote sensing system and determined the ideal method for equipment setup, image acquisition, and image processing. Fields of rice paddy (Oryza sativa cv. Unkwang) grown under three different nitrogen (N) treatments of 0, 50, or 115 kg/ha were monitored at Chonnam National University, Gwangju, Republic of Korea, in 2013. A multispectral camera was used to acquire UAV images from the study site. Atmospheric correction of these images was completed using the empirical line method, and three-point (black, gray, and white) calibration boards were used as pseudo references. Evaluation of our corrected UAV-based remote sensing data revealed that correction efficiency and root mean square errors ranged from 0.77 to 0.95 and 0.01 to 0.05, respectively. The time series maps of simulated normalized difference vegetation index (NDVI) produced using the UAV images reproduced field variations of NDVI reasonably well, both within and between the different N treatments. We concluded that the UAV-based remote sensing technology utilized in this study is potentially an easy and simple way to quantitatively obtain reliable two-dimensional remote sensing information on crop growth.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

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.

Remote sensing of plant functional types.

PubMed

Ustin, Susan L; Gamon, John A

2010-06-01

Conceptually, plant functional types represent a classification scheme between species and broad vegetation types. Historically, these were based on physiological, structural and/or phenological properties, whereas recently, they have reflected plant responses to resources or environmental conditions. Often, an underlying assumption, based on an economic analogy, is that the functional role of vegetation can be identified by linked sets of morphological and physiological traits constrained by resources, based on the hypothesis of functional convergence. Using these concepts, ecologists have defined a variety of functional traits that are often context dependent, and the diversity of proposed traits demonstrates the lack of agreement on universal categories. Historically, remotely sensed data have been interpreted in ways that parallel these observations, often focused on the categorization of vegetation into discrete types, often dependent on the sampling scale. At the same time, current thinking in both ecology and remote sensing has moved towards viewing vegetation as a continuum rather than as discrete classes. The capabilities of new remote sensing instruments have led us to propose a new concept of optically distinguishable functional types ('optical types') as a unique way to address the scale dependence of this problem. This would ensure more direct relationships between ecological information and remote sensing observations.

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

PubMed

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

2013-10-01

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

Eastern Regional Remote Sensing Applications Conference

NASA Technical Reports Server (NTRS)

Short, N. M. (Editor)

1981-01-01

The roles and activities of NASA and the National Conference of State Legislatures in fostering remote sensing technology utilization by the states and in promoting interstate communication and cooperation are reviewed. The reduction and interpretation of LANDSAT MSS and aerial reconnaissance data for resources management and environment assessment are described as well as resource information systems, and the value of SEASAT synthetic aperture radar and LANDSAT 4 data.

Remote sensing training for Corps of Engineering personnel: The university training module concept

NASA Technical Reports Server (NTRS)

1982-01-01

A concept to permit Corps of Engineers personnel to obtain and maintain an appropriate level of individual proficiency in the application of remote sensing to water resource management is described. Recommendations are made for specific training courses and include structure and staffing requirements, syllabi and methods of operation, supporting materials, and procedures for integrating information systems management into the University Training Modules.

Remote sensing applications to Missouri environmental resources information system

NASA Technical Reports Server (NTRS)

Myers, R. E.

1977-01-01

An efficient system for retrieval of remotely sensed data to be used by natural resources oriented agencies, and a natural resources data system that can meet the needs of state agencies were studied. To accomplish these objectives, natural resources data sources were identified, and study of systems already in operation which address themselves to the more efficient utilization of natural resources oriented data was prepared.

Monitoring spatial variations in soil organic carbon using remote sensing and geographic information systems

NASA Astrophysics Data System (ADS)

Jaber, Salahuddin M.

Soil organic carbon (SOC) sequestration is a component of larger strategies to control the accumulation of greenhouse gases that may be causing global warming. To implement this approach, it is necessary to improve the methods of measuring SOC content. Among these methods are indirect remote sensing and geographic information systems (GIS) techniques that are required to provide non-intrusive, low cost, and spatially continuous information that cover large areas on a repetitive basis. The main goal of this study is to evaluate the effects of using Hyperion hyperspectral data on improving the existing remote sensing and GIS-based methodologies for rapidly, efficiently, and accurately measuring SOC content on farmland. The study area is Big Creek Watershed (BCW) in Southern Illinois. The methodology consists of compiling a GIS database (consisting of remote sensing and soil variables) for 303 composite soil samples collected from representative pixels along the Hyperion coverage area of the watershed. Stepwise procedures were used to calibrate and validate linear multiple regression models where SOC was regarded as the response and the other remote sensing and soil variables as the predictors. Two models were selected. The first was the best all variables model and the second was the best only raster variables model. Map algebra was implemented to extrapolate the best only raster variables model and produce a SOC map for the BGW. This study concluded that Hyperion data marginally improved the predictability of the existing SOC statistical models based on multispectral satellite remote sensing sensors with correlation coefficient of 0.37 and root mean square error of 3.19 metric tons/hectare to a 15-cm depth. The total SOC pool of the study area is about 225,232 metric tons to 15-cm depth. The nonforested wetlands contained the highest SOC density (34.3 metric tons/hectare/15cm) with total SOC content of about 2,003.5 metric tons to 15-cm depth, where croplands had the lowest SOC density (21.6 metric tons/hectare/15cm) with total SOC content of about 44,571.2 metric tons to 15-cm depth.

A perspective of synthetic aperture radar for remote sensing

NASA Technical Reports Server (NTRS)

Skolnik, M. I.

1978-01-01

The characteristics and capabilities of synthetic aperture radar are discussed so as to identify those features particularly unique to SAR. The SAR and Optical images were compared. The SAR is an example of radar that provides more information about a target than simply its location. It is the spatial resolution and imaging capability of SAR that has made its application of interest, especially from spaceborne platforms. However, for maximum utility to remote sensing, it was proposed that other information be extracted from SAR data, such as the cross section with frequency and polarization.

Relationships between remotely sensed fisheries distribution information and selected oceanographic parameters in the Mississippi Sound

NASA Technical Reports Server (NTRS)

Kemmerer, A. J.; Benigno, J. A.

1973-01-01

The author has identified the following significant results. A feasibility study to demonstrate the potential of satellites for providing fisheries significant information was conducted in the Mississippi Sound and adjacent offshore waters. Attempts were made to relate satellite acquired imagery to selected oceanographic parameters and then to relate these parameters to aircraft remotely sensed distribution patterns of resident surface schooling fishes. Initial results suggest that this approach is valid and that the satellite acquired imagery may have important fisheries resource assessment implications.

Preliminary study of Kelso Dunes using AVIRIS, TM, and AIRSAR

NASA Technical Reports Server (NTRS)

Xu, Pung; Blumberg, Dan G.; Greeley, Ronald

1995-01-01

Remote sensing of sand dunes helps in the understanding of aeolian process and provides important information about the regional geologic history, environmental change, and desertification. Remotely sensed data combined with field studies are valuable in studying dune morphology, regional aeolian dynamics, and aeolian depositional history. In particular, active and inactive sands of the Kelso Dunes have been studied using landsat TM and AIRSAR. In this report, we describe the use of AVIRIS data to study the Kelso dunes and to compare the AVIRIS information with that from TM and AIRSAR.

Interfacing remote sensing and geographic information systems for global environmental change research

NASA Technical Reports Server (NTRS)

Lee, Jae K.; Randolph, J. C.; Lulla, Kamlesh P.; Helfert, Michael R.

1993-01-01

Because changes in the Earth's environment have become major global issues, continuous, longterm scientific information is required to assess global problems such as deforestation, desertification, greenhouse effects and climate variations. Global change studies require understanding of interactions of complex processes regulating the Earth system. Space-based Earth observation is an essential element in global change research for documenting changes in Earth environment. It provides synoptic data for conceptual predictive modeling of future environmental change. This paper provides a brief overview of remote sensing technology from the perspective of global change research.

Measuring Environmental Stress

ERIC Educational Resources Information Center

Walker, John E.; Dahm, Douglas B.

1975-01-01

Infrared remote sensors, plus photometric interpretation and digital data analysis are being used to record the stresses on air, water, vegetation and soil. Directly recorded photographic information has been the most effective recording media for remote sensing. (BT)

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 9: Oceans

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1974-01-01

The impact of remote sensing upon marine activities and oceanography is presented. The present capabilities of the current Earth Resources Technology Satellite (ERTS-1), as demonstrated by the principal investigators are discussed. Cost savings benefits are quantified in the area of nautical and hygrographic mapping and charting. Benefits are found in aiding coastal zone management and in the fields of weather (marine) prediction, fishery harvesting and management, and potential uses for ocean vegetation. Difficulties in quantification are explained, the primary factor being that remotely sensed information will be of greater benefit as input to forecasting models which have not yet been constructed.

The application of remote sensing to resource management and environmental quality programs in Kansas

NASA Technical Reports Server (NTRS)

Barr, B. G.

1975-01-01

Specific assistance to state agencies and public bodies on over 15 remote sensing projects concerned with (1) urban and regional analysis, (2) rural development, and (3) habitat management and environmental analysis is discussed. Specific problems of officials are considered and a basis for communication by demonstration is provided. In addition to data products in support of specific agency projects; consultation and training in use of satellite and aircraft imagery is provided to personnel from several state, regional, and county agencies. Effective communication and confidence is established through these efforts and users now routinely seek information and advice about the application of remote sensing technology to solution of their agency problems.

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

DOEpatents

Perkins, David Nikolaus; Brost, Randolph; Ray, Lawrence P.

2017-08-08

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

Preliminary results of fisheries investigation associated with Skylab-3. [remotely sensed distribution and abundance of gamefish in Gulf of Mexico

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.

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.

Integrating Indigenous Traditional, Local and Scientific Knowledge for Improved Management, Policy and Decision-Making in Reindeer Husbandry in the Russian Arctic

NASA Technical Reports Server (NTRS)

Maynard, Nancy G.; Yurchak, Boris; Turi, Johan Mathis; Mathiesen, Svein D.; Aissi-Wespi, Rita L.

2004-01-01

As scientists and policy-makers from both indigenous and non-indigenous communities begin to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This paper describes a new GIs-based system being designed to bring local and indigenous traditional knowledge together with scientific data and information, remote sensing, and information technologies to address health-related environment, weather, climate, pollution and land use change issues for improved decision/policy-making for reindeer husbandry. The system is building an easily-accessible archive of relevant current and historical, traditional, local and remotely-sensed and other data and observations for shared analysis, measuring, and monitoring parameters of interest. Protection of indigenous culturally sensitive information will be respected through appropriate data protocols. A mechanism which enables easy information sharing among all participants, which is real time and geo-referenced and which allows interconnectivity with remote sites is also being designed into the system for maximum communication among partners. A preliminary version of our system will be described for a Russian reindeer test site, which will include a combination of indigenous knowledge about local conditions and issues, remote sensing and ground-based data on such parameters as the vegetation state and distribution, snow cover, temperature, ice condition, and infrastructure.

Remote sensing of vegetation structure using computer vision

NASA Astrophysics Data System (ADS)

Dandois, Jonathan P.

High-spatial resolution measurements of vegetation structure are needed for improving understanding of ecosystem carbon, water and nutrient dynamics, the response of ecosystems to a changing climate, and for biodiversity mapping and conservation, among many research areas. Our ability to make such measurements has been greatly enhanced by continuing developments in remote sensing technology---allowing researchers the ability to measure numerous forest traits at varying spatial and temporal scales and over large spatial extents with minimal to no field work, which is costly for large spatial areas or logistically difficult in some locations. Despite these advances, there remain several research challenges related to the methods by which three-dimensional (3D) and spectral datasets are joined (remote sensing fusion) and the availability and portability of systems for frequent data collections at small scale sampling locations. Recent advances in the areas of computer vision structure from motion (SFM) and consumer unmanned aerial systems (UAS) offer the potential to address these challenges by enabling repeatable measurements of vegetation structural and spectral traits at the scale of individual trees. However, the potential advances offered by computer vision remote sensing also present unique challenges and questions that need to be addressed before this approach can be used to improve understanding of forest ecosystems. For computer vision remote sensing to be a valuable tool for studying forests, bounding information about the characteristics of the data produced by the system will help researchers understand and interpret results in the context of the forest being studied and of other remote sensing techniques. This research advances understanding of how forest canopy and tree 3D structure and color are accurately measured by a relatively low-cost and portable computer vision personal remote sensing system: 'Ecosynth'. Recommendations are made for optimal conditions under which forest structure measurements should be obtained with UAS-SFM remote sensing. Ultimately remote sensing of vegetation by computer vision offers the potential to provide an 'ecologist's eye view', capturing not only canopy 3D and spectral properties, but also seeing the trees in the forest and the leaves on the trees.

Grapevine Remote Sensing Analysis of Phylloxera Early Stress (GRAPES): Remote Sensing Analysis Summary

NASA Technical Reports Server (NTRS)

Lobitz, Brad; Johnson, Lee; Hlavka, Chris; Armstrong, Roy; Bell, Cindy

1997-01-01

High spatial resolution airborne imagery was acquired in California's Napa Valley in 1993 and 1994 as part of the Grapevine Remote sensing Analysis of Phylloxera Early Stress (GRAPES) project. Investigators from NASA, the University of California, the California State University, and Robert Mondavi Winery examined the application of airborne digital imaging technology to vineyard management, with emphasis on detecting the phylloxera infestation in California vineyards. Because the root louse causes vine stress that leads to grapevine death in three to five years, the infested areas must be replanted with resistant rootstock. Early detection of infestation and changing cultural practices can compensate for vine damage. Vineyard managers need improved information to decide where and when to replant fields or sections of fields to minimize crop financial losses. Annual relative changes in leaf area due to phylloxera infestation were determined by using information obtained from computing Normalized Difference Vegetation Index (NDVI) images. Two other methods of monitoring vineyards through imagery were also investigated: optical sensing of the Red Edge Inflection Point (REIP), and thermal sensing. These did not convey the stress patterns as well as the NDVI imagery and require specialized sensor configurations. NDVI-derived products are recommended for monitoring phylloxera infestations.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A data fusion framework for floodplain analysis using GIS and remotely sensed data

NASA Astrophysics Data System (ADS)

Necsoiu, Dorel Marius

Throughout history floods have been part of the human experience. They are recurring phenomena that form a necessary and enduring feature of all river basin and lowland coastal systems. In an average year, they benefit millions of people who depend on them. In the more developed countries, major floods can be the largest cause of economic losses from natural disasters, and are also a major cause of disaster-related deaths in the less developed countries. Flood disaster mitigation research was conducted to determine how remotely sensed data can effectively be used to produce accurate flood plain maps (FPMs), and to identify/quantify the sources of error associated with such data. Differences were analyzed between flood maps produced by an automated remote sensing analysis tailored to the available satellite remote sensing datasets (rFPM), the 100-year flooded areas "predicted" by the Flood Insurance Rate Maps, and FPMs based on DEM and hydrological data (aFPM). Landuse/landcover was also examined to determine its influence on rFPM errors. These errors were identified and the results were integrated in a GIS to minimize landuse/landcover effects. Two substantial flood events were analyzed. These events were selected because of their similar characteristics (i.e., the existence of FIRM or Q3 data; flood data which included flood peaks, rating curves, and flood profiles; and DEM and remote sensing imagery). Automatic feature extraction was determined to be an important component for successful flood analysis. A process network, in conjunction with domain specific information, was used to map raw remotely sensed data onto a representation that is more compatible with a GIS data model. From a practical point of view, rFPM provides a way to automatically match existing data models to the type of remote sensing data available for each event under investigation. Overall, results showed how remote sensing could contribute to the complex problem of flood management by providing an efficient way to revise the National Flood Insurance Program maps.

Remote sensing strategies for global resource exploration and environmental management

NASA Astrophysics Data System (ADS)

Henderson, Frederick B.

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

Multi- and hyperspectral geologic remote sensing: A review

NASA Astrophysics Data System (ADS)

van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie

2012-02-01

Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly workflows should be multidisciplinary and remote sensing data should be integrated with field observations and subsurface geophysical data to monitor and understand geologic processes.

The South Dakota cooperative land use effort: A state level remote sensing demonstration project

NASA Technical Reports Server (NTRS)

Tessar, P. A.; Hood, D. R.; Todd, W. J.

1975-01-01

Remote sensing technology can satisfy or make significant contributions toward satisfying many of the information needs of governmental natural resource planners and policy makers. Recognizing this potential, the South Dakota State Planning Bureau and the EROS Data Center together formulated the framework for an ongoing Land Use and Natural Resource Inventory and Information System Program. Statewide land use/land cover information is generated from LANDSAT digital data and high altitude photography. Many applications of the system are anticipated as it evolves and data are added from more conventional sources. The conceptualization, design, and implementation of the program are discussed.

Forestry applications project/timber resource. Sam Houston National forest inventory and development of a survey planning model

NASA Technical Reports Server (NTRS)

Colwell, R. N.

1976-01-01

The Forestry Applications Project has been directed towards solving the problem of meeting informational needs of the resource managers utilizing remote sensing data sources including satellite data, conventional aerial photography, and direct measurement on the ground in such combinations as needed to best achieve these goals. It is recognized that sampling plays an important role in generating relevant information for managing large geographic populations. The central problem, therefore, is to define the kind and amount of sampling and the place of remote sensing data sources in that sampling system to do the best possible job of meeting the manager's informational needs.

Spectral Resolution and Coverage Impact on Advanced Sounder Information Content

NASA Technical Reports Server (NTRS)

Larar, Allen M.; Liu, Xu; Zhou, Daniel K.; Smith, William L.

2010-01-01

Advanced satellite sensors are tasked with improving global measurements of the Earth s atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Achieving such measurement improvements requires instrument system advancements. This presentation focuses on the impact of spectral resolution and coverage changes on remote sensing system information content, with a specific emphasis on thermodynamic state and trace species variables obtainable from advanced atmospheric sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) systems on the MetOp and NPP/NPOESS series of satellites. Key words: remote sensing, advanced sounders, information content, IASI, CrIS

Results from the National Aeronautics and Space Administration remote sensing experiments in the New York Bight, 7-17 April 1975

NASA Technical Reports Server (NTRS)

Hall, J. B., Jr. (Compiler); Pearson, A. O. (Compiler)

1977-01-01

A cooperative operation was conducted in the New York Bight to evaluate the role of remote sensing technology to monitor ocean dumping. Six NASA remote sensing experiments were flown on the C-54, U-2, and C-130 NASA aircraft, while NOAA obtained concurrent sea truth information using helicopters and surface platforms. The experiments included: (1) a Radiometer/Scatterometer (RADSCAT), (2) an Ocean Color Scanner (OCS), (3) a Multichannel Ocean Color Sensor (MOCS), (4) four Hasselblad cameras, (5) an Ebert spectrometer; and (6) a Reconafax IV infrared scanner and a Precision Radiation Thermometer (PRT-5). The results of these experiments relative to the use of remote sensors to detect, quantify, and determine the dispersion of pollutants dumped into the New York Bight are presented.

Comparison of stimulated and spontaneous laser-radar methods for the remote sensing of ocean physical properties

NASA Astrophysics Data System (ADS)

Leonard, Donald A.; Sweeney, Harold E.

1990-09-01

The physical properties of ocean water, in the top few ten meters, are of great interest in the scientific, engineering, and general oceanographic communities. Subsurface profiles of temperature, salinity, and sound speed measured by laser radar in real time on a synoptic basis over a wide area from an airborne platform would provide valuable information complementary to the data that is now readily available. The laser-radar technique specifically applicable to ocean sensing uses spectroscopic analysis of the inelastic backscattered optical signal. Two methods have received considerable attention for remote sensing and both have been demonstrated in field experiments. These are spontaneous Raman1 and spontaneous Brillouin2 scattering. A discussion of these two processes and a comparison of their properties that are useful for remote sensing was presented3 at SPIE Ocean Optics IX. This paper compares ocean remote sensing using stimulated Brillouin scattering (SBS) and stimulated Raman scattering (SRS) processes with better known spontaneous methods. The results of laboratory measurements of temperature using SBS and some preliminary results of SRS are presented with extensions to performance estimates of potential field systems.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J. E.; Richardson, T.; Yang, Z.

2012-12-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to present this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data.We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

Developing a novel UAV (Unmanned Aerial Vehicle) helicopter platform for very high resolution environmental monitoring of catchment processes

NASA Astrophysics Data System (ADS)

Freer, J.; Richardson, T. S.

2012-04-01

Recent advances in remote sensing and geographic information has led the way for the development of hyperspectral sensors and cloud scanning LIDAR (Light Detection And Ranging). Both these technologies can be used to sense environmental processes and capture detailed spatial information, they are often deployed in ground, aircraft and satellite based systems. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology that is currently being investigated by researchers and scientists with regard to the detection and identification of landscapes, terrestrial vegetation, and manmade materials and backgrounds. There are many applications that could take advantages of hyperspectral remote sensing coupled to detailed surface feature mapping using LIDAR. This embryonic project involves developing the engineering solutions and post processing techniques needed to realise an ultra high resolution helicopter based environmental sensing platform which can fly at lower altitudes than aircraft systems and can be deployed more frequently. We aim to display this new technology platform in this special session (the only one of it's kind in the UK). Initial applications are planned on a range of environmental sensing problems that would benefit from such complex and detailed data. We look forward to being able to display and discuss this initiative with colleagues and any potential interest in future collaborative projects.

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.

Using remote sensing to calculate plant available nitrogen needed by crops on swine factory farm sprayfields in North Carolina

NASA Astrophysics Data System (ADS)

Christenson, Elizabeth; Serre, Marc

2015-10-01

North Carolina (NC) is the second largest producer of hogs in the United States with Duplin county, NC having the densest population of hogs in the world. In NC, liquid swine manure is generally stored in open-air lagoons and sprayed onto sprayfields with sprinkler systems to be used as fertilizer for crops. Swine factory farms, termed concentrated animal feeding operations (CAFOs), are regulated by the Department of Environment and Natural Resources (DENR) based on nutrient management plans (NMPs) having balanced plant available nitrogen (PAN). The estimated PAN in liquid manure being sprayed must be less than the estimated PAN needed crops during irrigation. Estimates for PAN needed by crops are dependent on crop and soil types. Objectives of this research were to develop a new, time-efficient method to identify PAN needed by crops on Duplin county sprayfields for years 2010-2014. Using remote sensing data instead of NMP data to identify PAN needed by crops allowed calendar year identification of which crops were grown on sprayfields instead of a five-year range of values. Although permitted data have more detailed crop information than remotely sensed data, identification of PAN needed by crops using remotely sensed data is more time efficient, internally consistent, easily publically accessible, and has the ability to identify annual changes in PAN on sprayfields. Once PAN needed by crops is known, remote sensing can be used to quantify PAN at other spatial scales, such as sub-watershed levels, and can be used to inform targeted water quality monitoring of swine CAFOs.

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

NASA Astrophysics Data System (ADS)

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

2001-12-01

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

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

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.

PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

NASA Astrophysics Data System (ADS)

Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

2016-11-01

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

NASA Astrophysics Data System (ADS)

Poudyal, R.; Singh, M.; Gautam, R.; Gatebe, C. K.

2016-12-01

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR)- http://car.gsfc.nasa.gov/. Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.