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.

Opportunities and problems in introducing or expanding the teaching of remote sensing in universities

NASA Technical Reports Server (NTRS)

Maxwell, E. L.

1980-01-01

The need for degree programs in remote sensing is considered. Any education program which claims to train remote sensing specialists must include expertise in the physical principles upon which remote sensing is based. These principles dictate the limits of engineering and design, computer analysis, photogrammetry, and photointerpretation. Faculty members must be hired to provide emphasis in those five areas.

Basic Investigations for Remote Sensing of Coastal Areas.

DTIC Science & Technology

for the delineation and analysis of bottom features in coastal areas. The focus is on the development of remote sensing techniques for delineating and classifying bottom features in the nearshore zone.

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.

SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

DTIC Science & Technology

The Arctic Institute of North America long has been interested in encouraging full and specific attention to applications of remote sensing to polar...research problems. The major purpose of the symposium was to acquaint scientists and technicians concerned with remote sensing with some of the...special problems of the polar areas and, in turn, to acquaint polar scientists with the potential of the use of remote sensing . The Symposium therefore was

REMOTE SENSING IN OCEANOGRAPHY.

DTIC Science & Technology

remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

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 of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

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

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Cybernetic Basis and System Practice of Remote Sensing and Spatial Information Science

NASA Astrophysics Data System (ADS)

Tan, X.; Jing, X.; Chen, R.; Ming, Z.; He, L.; Sun, Y.; Sun, X.; Yan, L.

2017-09-01

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level.

Field Data Collection: an Essential Element in Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Pettinger, L. R.

1971-01-01

Field data collected in support of remote sensing projects are generally used for the following purposes: (1) calibration of remote sensing systems, (2) evaluation of experimental applications of remote sensing imagery on small test sites, and (3) designing and evaluating operational regional resource studies and inventories which are conducted using the remote sensing imagery obtained. Field data may be used to help develop a technique for a particular application, or to aid in the application of that technique to a resource evaluation or inventory problem for a large area. Scientists at the Forestry Remote Sensing Laboratory have utilized field data for both purposes. How meaningful field data has been collected in each case is discussed.

Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

NASA Astrophysics Data System (ADS)

Ding, Hua; Li, Ru Ren; Shuang Sun, Li; Wang, Xin; Liu, Yu Mei

2018-05-01

Taking Landsat remote sensing image as the main data source, the research on land use changes in Panjin City in 2005 to 2015 is made with the support of remote sensing platform and GIS platform in this paper; the range of land use changes and change rate are analyzed through the classification of remote sensing image; the dynamic analysis on land changes is made with the help of transfer matrix of land use type; the quantitative calculation on all kinds of dynamic change features of land changes is made by utilizing mathematical model; and the analysis on driving factors of land changes of image is made at last. The research results show that, in recent ten years, the area of cultivated land in Panjin City decreased, the area of vegetation increased, and meanwhile the area of road increased drastically, the settlement place decreased than ever, and water area changed slightly.

Frontiers of Remote Sensing of the Oceans and Troposphere from Air and Space Platforms

NASA Technical Reports Server (NTRS)

1984-01-01

Several areas of remote sensing are addressed including: future satellite systems; air-sea interaction/wind; ocean waves and spectra/S.A.R.; atmospheric measurements (particulates and water vapor); synoptic and weather forecasting; topography; bathymetry; sea ice; and impact of remote sensing on synoptic analysis/forecasting.

Remote Sensing in Latin America: Technology and Markets for the 1980s

DTIC Science & Technology

1981-08-01

A review is made on the impact of satellite derived remote sensing data in Latin America. Data availability has generated a phenomenal growth in the...The international institutionalization of remote sensing interests in the area is an indicator submitted as a viable force in the continued, future

Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Rosen, Paul A.

2012-01-01

This lecture was just a taste of radar remote sensing techniques and applications. Other important areas include Stereo radar grammetry. PolInSAR for volumetric structure mapping. Agricultural monitoring, soil moisture, ice-mapping, etc. The broad range of sensor types, frequencies of observation and availability of sensors have enabled radar sensors to make significant contributions in a wide area of earth and planetary remote sensing sciences. The range of applications, both qualitative and quantitative, continue to expand with each new generation of sensors.

Applications of remote sensing to watershed management

NASA Technical Reports Server (NTRS)

Rango, A.

1975-01-01

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

Remote Sensing and Reflectance Profiling in Entomology.

PubMed

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

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.

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.

Remote sensing of geobotanical relations in Georgia

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

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.

Remote sensing of Northern mines: supporting operation and environmental monitoring in cold conditions

NASA Astrophysics Data System (ADS)

Tuomela, Anne; Davids, Corine; Knutsson, Sven; Knutsson, Roger; Rauhala, Anssi; Rossi, Pekka M.; Rouyet, Line

2017-04-01

Northern areas of Finland, Sweden and Norway have mineral-rich deposits. There are several active mines in the area but also closed ones and deposits with plans for future mining. With increasing demand for environmental protection in the sensitive Northern conditions, there is a need for more comprehensive monitoring of the mining environment. In our study, we aim to develop new opportunities to use remote sensing data from satellites and unmanned aerial vehicles (UAVs) in improving mining safety and monitoring, for example in the case of mine waste storage facilities. Remote sensing methods have evolved fast, and could in many cases enable precise, reliable, and cost-efficient data collection over large areas. The study has focused on four mining areas in Northern Fennoscandia. Freely available medium-resolution (e.g. Sentinel-1), commercial high-resolution (e.g. TerraSAR-X) and Synthetic Aperture Radar (SAR) data has been collected during 2015-2016 to study how satellite remote sensing could be used e.g. for displacement monitoring using SAR Interferometry (InSAR). Furthermore, UAVs have been utilized in similar data collection in a local scale, and also in collection of thermal infrared data for hydrological monitoring of the areas. The development and efficient use of the methods in mining areas requires experts from several fields. In addition, the Northern conditions with four distinct seasons bring their own challenges for the efficient use of remote sensing, and further complicate their integration as standardised monitoring methods for mine environments. Based on the initial results, remote sensing could especially enhance the monitoring of large-scale structures in mine areas such as tailings impoundments.

Comparison of geostatistical interpolation and remote sensing techniques for estimating long-term exposure to ambient PM2.5 concentrations across the continental United States.

PubMed

Lee, Seung-Jae; Serre, Marc L; van Donkelaar, Aaron; Martin, Randall V; Burnett, Richard T; Jerrett, Michael

2012-12-01

A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data. We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation. We developed a space-time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals. The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates. We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.

Application of remote sensing to state and regional problems. [Mississippi

NASA Technical Reports Server (NTRS)

Miller, W. F.; Carter, B. D.; Solomon, J. L.; Williams, S. G.; Powers, J. S.; Clark, J. R. (Principal Investigator)

1980-01-01

Progress is reported in the following areas: remote sensing applications to land use planning Lowndes County, applications of LANDSAT data to strip mine inventory and reclamation, white tailed deer habitat evaluation using LANDSAT data, remote sensing data analysis support system, and discrimination of unique forest habitats in potential lignite areas of Mississippi. Other projects discussed include LANDSAT change discrimination in gravel operations, environmental impact modeling for highway corridors, and discrimination of fresh water wetlands for inventory and monitoring.

Project THEMIS: A Center for Remote Sensing.

DTIC Science & Technology

This report summarizes the technical work accomplished under Project THEMIS, A Center for Remote Sensing at the University of Kansas during the...period 16 September 1967 through 15 September 1973. The highlights of the four major areas forming the remote sensing system are presented. A detailed description of the latest radar spectrometer results is presented.

Calibration of remotely sensed proportion or area estimates for misclassification error

Treesearch

Raymond L. Czaplewski; Glenn P. Catts

1992-01-01

Classifications of remotely sensed data contain misclassification errors that bias areal estimates. Monte Carlo techniques were used to compare two statistical methods that correct or calibrate remotely sensed areal estimates for misclassification bias using reference data from an error matrix. The inverse calibration estimator was consistently superior to the...

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors

PubMed Central

Zheng, Guang; Moskal, L. Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels. PMID:22574042

Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.

PubMed

Zheng, Guang; Moskal, L Monika

2009-01-01

The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.

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.

Cooling effect of rivers on metropolitan Taipei using remote sensing.

PubMed

Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen

2014-01-23

This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature.

Cooling Effect of Rivers on Metropolitan Taipei Using Remote Sensing

PubMed Central

Chen, Yen-Chang; Tan, Chih-Hung; Wei, Chiang; Su, Zi-Wen

2014-01-01

This study applied remote sensing technology to analyze how rivers in the urban environment affect the surface temperature of their ambient areas. While surface meteorological stations can supply accurate data points in the city, remote sensing can provide such data in a two-dimensional (2-D) manner. The goal of this paper is to apply the remote sensing technique to further our understanding of the relationship between the surface temperature and rivers in urban areas. The 2-D surface temperature data was retrieved from Landsat-7 thermal infrared images, while data collected by Formosat-2 was used to categorize the land uses in the urban area. The land surface temperature distribution is simulated by a sigmoid function with nonlinear regression analysis. Combining the aforementioned data, the range of effect on the surface temperature from rivers can be derived. With the remote sensing data collected for the Taipei Metropolitan area, factors affecting the surface temperature were explored. It indicated that the effect on the developed area was less significant than on the ambient nature zone; moreover, the size of the buffer zone between the river and city, such as the wetlands or flood plain, was found to correlate with the affected distance of the river surface temperature. PMID:24464232

Remote Sensing For Water Resources And Hydrology. Recommended research emphasis for the 1980's

NASA Technical Reports Server (NTRS)

1980-01-01

The problems and the areas of activity that the Panel believes should be emphasized in work on remote sensing for water resources and hydrology in the 1980's are set forth. The Panel deals only with those activities and problems in water resources and hydrology that the Panel considers important, and where, in the Panel's opinion, application of current remote sensing capability or advancements in remote sensing capability can help meet urgent problems and provide large returns in practical benefits.

Research on Method of Interactive Segmentation Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yang, Y.; Li, H.; Han, Y.; Yu, F.

2017-09-01

In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.

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.

Physics teaching by infrared remote sensing of vegetation

NASA Astrophysics Data System (ADS)

Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

2018-05-01

Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

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

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

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

Remote sensing for the sustainable management and conservation of forest environments biodiversity: the conservation managers perspective.

NASA Astrophysics Data System (ADS)

Aguilar-Amuchas, N.; Henebry, G. M.; Blanchard, J.; Sutter, R.

2008-12-01

The potential use of remote sensing for the design and implementation of sustainable management, conservation, and monitoring of forest biodiversity has been well documented in the scientific literature. However, when we look into how often remote sensing is actually being used in the decision making processes affecting biodiversity conservation and sustainable management, we find that, apart from specific study cases, its use is not as widespread as we know it should. There is an enormous gap between our scientific achievements and their use in the real world towards the preservation of a rapidly vanishing biodiversity. Conservation managers understand the potential remote sensing has. However, logistical constraints and high technical skills requirements render the use of remote sensing data difficult. Sound and easy approaches need to be developed and implemented. We present two study cases that illustrate 1st. How the interaction between tropical forest managers and remote sensing specialist allowed developing a simple method for the identification of priority areas for field surveys of tropical forests management ecological sustainability indicators and, 2nd. How remote sensing is being used by The Nature Conservancy as a first level approach towards the assessment of forest conservation strategies effectiveness in for areas located in 11 states, covering different forest types and a variety of conservation objectives.

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.

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.

Research for applications of remote sensing to state and local governments (ARSIG)

NASA Technical Reports Server (NTRS)

Foster, K. E.; Johnson, J. D.

1973-01-01

Remote sensing and its application to problems confronted by local and state planners are reported. The added dimension of remote sensing as a data gathering tool has been explored identifying pertinent land use factors associated with urban growth such as soil associations, soil capability, vegetation distribution, and flood prone areas. Remote sensing within rural agricultural setting has also been utilized to determine irrigation runoff volumes, cropping patterns, and land use. A variety of data sources including U-2 70 mm multispectral black and white photography, RB-57 9-inch color IR, HyAC panoramic color IR and ERTS-1 imagery have been used over selected areas of Arizona including Tucson, Arizona (NASA Test Site #30) and the Sulphur Springs Valley.

Advances in the development of remote sensing technology for agricultural applications

NASA Technical Reports Server (NTRS)

Powers, J. E.; Erb, R. B.; Hall, F. G.; Macdonald, R. B.

1979-01-01

The application of remote sensing technology to crop forecasting is discussed. The importance of crop forecasts to the world economy and agricultural management is explained, and the development of aerial and spaceborne remote sensing for global crop forecasting by the United States is outlined. The structure, goals and technical aspects of the Large Area Crop Inventory Experiment (LACIE) are presented, and main findings on the accuracy, efficiency, applicability and areas for further study of the LACIE procedure are reviewed. The current status of NASA crop forecasting activities in the United States and worldwide is discussed, and the objectives and organization of the newly created Agriculture and Resources Inventory Surveys through Aerospace Remote Sensing (AgRISTARS) program are presented.

Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation

Treesearch

Ronald E. McRoberts; Greg C. Liknes; Grant M. Domke

2014-01-01

For most national forest inventories, the variables of primary interest to users are forest area and growing stock volume. The precision of estimates of parameters related to these variables can be increased using remotely sensed auxiliary variables, often in combination with stratified estimators. However, acquisition and processing of large amounts of remotely sensed...

[Effect of different snow depth and area on the snow cover retrieval using remote sensing data].

PubMed

Jiang, Hong-bo; Qin, Qi-ming; Zhang, Ning; Dong, Heng; Chen, Chao

2011-12-01

For the needs of snow cover monitoring using multi-source remote sensing data, in the present article, based on the spectrum analysis of different depth and area of snow, the effect of snow depth on the results of snow cover retrieval using normalized difference snow index (NDSI) is discussed. Meanwhile, taking the HJ-1B and MODIS remote sensing data as an example, the snow area effect on the snow cover monitoring is also studied. The results show that: the difference of snow depth does not contribute to the retrieval results, while the snow area affects the results of retrieval to some extents because of the constraints of spatial resolution.

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.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

Remote sensing of wet lands in irrigated areas

NASA Technical Reports Server (NTRS)

Ham, H. H.

1972-01-01

The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

Skylab experiments. Volume 2: Remote sensing of earth resources

NASA Technical Reports Server (NTRS)

1973-01-01

This volume covers the broad area of earth resources in which Skylab experiments will be performed. A brief description of the Skylab program, its objectives, and vehicles is included. Section 1 introduces the concept and historical significance of remote sensing, and discusses the major scientific considerations involved in remotely sensing the earth's resources. Sections 2 through 6 provide a description of the individual earth resource sensors and experiments to be performed. Each description includes a discussion of the experiment background and scientific objectives, the equipment involved, and a discussion of significant experiment performance areas.

Natural resource inventory for urban planning utilizing remote sensing techniques

NASA Technical Reports Server (NTRS)

Foster, K. E.; Mackey, P. F.; Bonham, C. D.

1972-01-01

Remote sensing techniques were applied to the lower Pantano Wash area to acquire data for planning an ecological balance between the expanding Tucson metropolitan area and its environment. The types and distribution of vegetation are discussed along with the hydrologic aspects of the Wash.

Applications of Sentinel-2 data for agriculture and forest monitoring using the absolute difference (ZABUD) index derived from the AgroEye software (ESA)

NASA Astrophysics Data System (ADS)

de Kok, R.; WeŻyk, P.; PapieŻ, M.; Migo, L.

2017-10-01

To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and remote sensing programmers. An index value, known in the remote sensing user domain as "Zabud" was selected to represent, in color, the essentials of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control. This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected anomalies allows developers of open source software to design solutions for further agricultural control with remote sensing.

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.

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.

Post-classification approaches to estimating change in forest area using remotely sense auxiliary data.

Treesearch

Ronald E. McRoberts

2014-01-01

Multiple remote sensing-based approaches to estimating gross afforestation, gross deforestation, and net deforestation are possible. However, many of these approaches have severe data requirements in the form of long time series of remotely sensed data and/or large numbers of observations of land cover change to train classifiers and assess the accuracy of...

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.

Measurement of Hydrologic Resource Parameters Through Remote Sensing in the Feather River Headwaters Area

NASA Technical Reports Server (NTRS)

Thorley, G. A.; Draeger, W. C.; Lauer, D. T.; Lent, J.; Roberts, E.

1971-01-01

The four problem are as being investigated are: (1) determination of the feasibility of providing the resource manager with operationally useful information through the use of remote sensing techniques; (2) definition of the spectral characteristics of earth resources and the optimum procedures for calibrating tone and color characteristics of multispectral imagery (3) determination of the extent to which humans can extract useful earth resource information through remote sensing imagery; (4) determination of the extent to which automatic classification and data processing can extract useful information from remote sensing data.

Remote sensing utility in a disaster struck urban environment

NASA Technical Reports Server (NTRS)

Rush, M.; Holguin, A.

1976-01-01

Six major public health areas which might be affected by a natural disaster were identified. The functions and tasks associated with each area following a disaster, potential ways remote sensing could aid these functions, and the baseline data which would expedite problem solving associated with these functions are discussed.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Increasing Access and Usability of Remote Sensing Data: The NASA Protected Area Archive

NASA Technical Reports Server (NTRS)

Geller, Gary N.

2004-01-01

Although remote sensing data are now widely available, much of it at low or no-cost, many managers of protected conservation areas do not have the expertise or tools to view or analyze it. Thus access to it by the protected area management community is effectively blocked. The Protected Area Archive will increase access to remote sensing data by creating collections of satellite images of protected areas and packaging them with simple-to-use visualization and analytical tools. The user can easily locate the area and image of interest on a map, then display, roam, and zoom the image. A set of simple tools will be provided so the user can explore the data and employ it to assist in management and monitoring of their area. The 'Phase 1 ' version requires only a Windows-based computer and basic computer skills, and may be of particular help to protected area managers in developing countries.

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

NASA Technical Reports Server (NTRS)

2002-01-01

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

Proceedings of the Eleventh International Symposium on Remote Sensing of Environment, volume 2. [application and processing of remotely sensed data

NASA Technical Reports Server (NTRS)

1977-01-01

Application and processing of remotely sensed data are discussed. Areas of application include: pollution monitoring, water quality, land use, marine resources, ocean surface properties, and agriculture. Image processing and scene analysis are described along with automated photointerpretation and classification techniques. Data from infrared and multispectral band scanners onboard LANDSAT satellites are emphasized.

Quarterly literature review of the remote sensing of natural resources, third quarter 1976. [bibliography

NASA Technical Reports Server (NTRS)

1976-01-01

Abstracts related to remote sensing instrumentation and techniques, and to the remote sensing of natural resources are presented by the Technology Application Center at the University of New Mexico. Areas of interest included theory, general surveys, and miscellaneous studies; geology and hydrology; agriculture and forestry; marine sciences; and urban and land use. An alphabetically arranged Author/Key Word index is provided.

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…

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.

Remote sensing: An inventory of earth's resources

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1974-01-01

The remote sensing capabilities of Landsat are reviewed along with the broad areas of application of the Landsat imagery. The importance of Landsat imagery in urban planning and resources management is stressed.

Design and Performance of a Multiwavelength Airborne Polarimetric Lidar for Vegetation Remote Sensing

NASA Astrophysics Data System (ADS)

Tan, Songxin; Narayanan, Ram M.

2004-04-01

The University of Nebraska has developed a multiwavelength airborne polarimetric lidar (MAPL) system to support its Airborne Remote Sensing Program for vegetation remote sensing. The MAPL design and instrumentation are described in detail. Characteristics of the MAPL system include lidar waveform capture and polarimetric measurement capabilities, which provide enhanced opportunities for vegetation remote sensing compared with current sensors. Field tests were conducted to calibrate the range measurement. Polarimetric calibration of the system is also discussed. Backscattered polarimetric returns, as well as the cross-polarization ratios, were obtained from a small forested area to validate the system's ability for vegetation canopy detection. The system has been packaged to fly abroad a Piper Saratoga aircraft for airborne vegetation remote sensing applications.

[Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.

PubMed

Sun, Zhong Yu; Chen, Yan Qiao; Yang, Long; Tang, Guang Liang; Yuan, Shao Xiong; Lin, Zhi Wen

2017-02-01

Low-altitude unmanned aerial vehicles (UAV) remote sensing system overcomes the deficiencies of space and aerial remote sensing system in resolution, revisit period, cloud cover and cost, which provides a novel method for ecological research on mesoscale. This study introduced the composition of UAV remote sensing system, reviewed its applications in species, population, community and ecosystem ecology research. Challenges and opportunities of UAV ecology were identified to direct future research. The promising research area of UAV ecology includes the establishment of species morphology and spectral characteristic data base, species automatic identification, the revelation of relationship between spectral index and plant physiological processes, three-dimension monitoring of ecosystem, and the integration of remote sensing data from multi resources and multi scales. With the development of UAV platform, data transformation and sensors, UAV remote sensing technology will have wide application in ecology research.

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.

ANALYZING THE CONSEQUENCES OF ENVIRONMENTAL SPATIAL PATTERNS ON ENVIRONMENTAL RESOURCES: THE USE OF LANDSCAPE METRICS GENERATED FROM REMOTE SENSING DATA

EPA Science Inventory

A number of existing and new remote sensing data provide images of areas ranging from small communities to continents. These images provide views on a wide range of physical features in the landscape, including vegetation, road infrastructure, urban areas, geology, soils, and wa...

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

NASA Astrophysics Data System (ADS)

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

2007-04-01

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

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.

1976-01-01

Activities of the Kansas Applied Remote Sensing Program (KARS) designed to establish interactions on cooperative projects with decision makers in Kansas agencies in the development and application of remote sensing procedures are reported. Cooperative demonstration projects undertaken with several different agencies involved three principal areas of effort: Wildlife Habitat and Environmental Analysis; Urban and Regional Analysis; Agricultural and Rural Analysis. These projects were designed to concentrate remote sensing concepts and methodologies on existing agency problems to insure the continued relevancy of the program and maximize the possibility for immediate operational use. Completed projects are briefly discussed.

Remote sensing and urban public health

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

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.

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost

PubMed Central

Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

2015-01-01

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited. PMID:26528811

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

PubMed

Zhou, Zhen; Huang, Jingfeng; Wang, Jing; Zhang, Kangyu; Kuang, Zhaomin; Zhong, Shiquan; Song, Xiaodong

2015-01-01

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

Geomorphic Processes and Remote Sensing Signatures of Alluvial Fans in the Kun Lun Mountains, China

NASA Technical Reports Server (NTRS)

Farr, Tom G.; Chadwick, Oliver A.

1996-01-01

The timing of alluvial deposition in arid and semiarid areas is tied to land-surface instability caused by regional climate changes. The distribution pattern of dated deposits provides maps of regional land-surface response to past climate change. Sensitivity to differences in surface roughness and composition makes remote sensing techniques useful for regional mapping of alluvial deposits. Radar images from the Spaceborne Radar Laboratory and visible wavelength images from the French SPOT satellite were used to determine remote sensing signatures of alluvial fan units for an area in the Kun Lun Mountains of northwestern China. These data were combined with field observations to compare surface processes and their effects on remote sensing signatures in northwestern China and the southwestern United States. Geomorphic processes affecting alluvial fans in the two areas include aeolian deposition, desert varnish, and fluvial dissection. However, salt weathering is a much more important process in the Kun Lun than in the southwestern United States. This slows the formation of desert varnish and prevents desert pavement from forming. Thus the Kun Lun signatures are characteristic of the dominance of salt weathering, while signatures from the southwestern United States are characteristic of the dominance of desert varnish and pavement processes. Remote sensing signatures are consistent enough in these two regions to be used for mapping fan units over large areas.

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.

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 change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects

Treesearch

Robert E. Kennedy; Philip A. Townsend; John E. Gross; Warren B. Cohen; Paul Bolstad; Wang Y. Q.; Phyllis Adams

2009-01-01

Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis...

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.

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

USGS Publications Warehouse

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Xie, Yaowen

2008-10-01

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

Urban Methane Point Sources Detected by Tiered System of Remote-sensing Observations

NASA Image and Video Library

2015-07-10

This image captured by a prototype NASA satellite instrument at NASA California Laboratory for Atmospheric Remote Sensing CLARS shows a persistent methane hotspot central red area over Los Angeles basin.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

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

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.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

Key Issues in the Analysis of Remote Sensing Data: A report on the workshop

NASA Technical Reports Server (NTRS)

Swain, P. H. (Principal Investigator)

1981-01-01

The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented.

Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment

USDA-ARS?s Scientific Manuscript database

We develop a robust understanding of the effects of assimilating remote sensing observations of leaf area index and soil moisture (in the top 5 cm) on DSSAT-CSM CropSim-Ceres wheat yield estimates. Synthetic observing system simulation experiments compare the abilities of the Ensemble Kalman Filter...

ON-ROAD REMOTE SENSING OF AUTOMOBILE EMISSIONS IN THE RESEARCH TRIANGLE PARK, NORTH CAROLINA AREA: 1997-2001

EPA Science Inventory

The report describes automobile exhaust remote sensing data collected by EPA at a number of sites in the Research Triangle Park, NC area during 1997. Data were also collected at one site in Raleigh, NC from 1998 through 2001 for the Coordinating Research Council (CRC) study of re...

Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and OBIA techniques

Treesearch

S. Panda; D.M. Amatya; G. Hoogenboom

2014-01-01

Remotely sensed images including LANDSAT, SPOT, NAIP orthoimagery, and LiDAR and relevant processing tools can be used to predict plant stomatal conductance (gs), leaf area index (LAI), and canopy temperature, vegetation density, albedo, and soil moisture using vegetation indices like normalized difference vegetation index (NDVI) or soil adjusted...

Remote Sensing of Water Pollution

NASA Technical Reports Server (NTRS)

White, P. G.

1971-01-01

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

EPA REMOTE SENSING RESEARCH

EPA Science Inventory

The 2006 transgenic corn imaging research campaign has been greatly assisted through a cooperative effort with several Illinois growers who provided planting area and crop composition. This research effort was designed to evaluate the effectiveness of remote sensed imagery of var...

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

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.

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.

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.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia

NASA Astrophysics Data System (ADS)

Tweed, Sarah O.; Leblanc, Marc; Webb, John A.; Lubczynski, Maciek W.

2007-02-01

Identifying groundwater recharge and discharge areas across catchments is critical for implementing effective strategies for salinity mitigation, surface-water and groundwater resource management, and ecosystem protection. In this study, a synergistic approach has been developed, which applies a combination of remote sensing and geographic information system (GIS) techniques to map groundwater recharge and discharge areas. This approach is applied to an unconfined basalt aquifer, in a salinity and drought prone region of southeastern Australia. The basalt aquifer covers ~11,500 km2 in an agriculturally intensive region. A review of local hydrogeological processes allowed a series of surface and subsurface indicators of groundwater recharge and discharge areas to be established. Various remote sensing and GIS techniques were then used to map these surface indicators including: terrain analysis, monitoring of vegetation activity, and mapping of infiltration capacity. All regions where groundwater is not discharging to the surface were considered potential recharge areas. This approach, applied systematically across a catchment, provides a framework for mapping recharge and discharge areas. A key component in assigning surface and subsurface indicators is the relevance to the dominant recharge and discharge processes occurring and the use of appropriate remote sensing and GIS techniques with the capacity to identify these processes.

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.

Remote Sensing: The View from Above. Know Your Environment.

ERIC Educational Resources Information Center

Academy of Natural Sciences, Philadelphia, PA.

This publication identifies some of the general concepts of remote sensing and explains the image collection process and computer-generated reconstruction of the data. Monitoring the ecological collapse in coral reefs, weather phenomena like El Nino/La Nina, and U.S. Space Shuttle-based sensing projects are some of the areas for which remote…

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.

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)

Analysis of Human Activities in Nature Reserves Based on Nighttime Light Remote Sensing and Microblogging Data - by the Case of National Nature Reserves in Jiangxi Province

NASA Astrophysics Data System (ADS)

Shi, F.; Li, X.; Xu, H.

2017-09-01

The study used the mainstream social media in china - Sina microblogging data combined with nighttime light remote sensing and various geographical data to reveal the pattern of human activities and light pollution of the Jiangxi Provincial National Nature Reserves. Firstly, we performed statistical analysis based on both functional areas and km-grid from the perspective of space and time, and selected the key areas for in-depth study. Secondly, the relationship between microblogging data and nighttime light remote sensing, population, GDP, road coverage, road distance and road type in nature reserves was analyzed by Spearman correlation coefficient method, so the distribution pattern and influencing factors of the microblogging data were explored. Thirdly, a region where the luminance value was greater than 0.2 was defined as a light region. We evaluated the management status by analyzing the distribution of microblogging data in both light area and non-light area. Final results showed that in all nature reserves, the top three were the Lushan Nature Reserve, the Jinggangshan Nature Reserve, the Taohongling National Nature Reserve of Sikas both on the total number and density of microblogging ; microblogging had a significant correlation with nighttime light remote sensing , the GDP, population, road and other factors; the distribution of microblogging near roads in protected area followed power laws; luminous radiance of Lushan Nature Reserve was the highest, with 43 percent of region was light at night; analysis combining nighttime light remote sensing with microblogging data reflected the status of management of nature reserves.

Spectral estimates of net radiation and soil heat flux

USGS Publications Warehouse

Daughtry, C.S.T.; Kustas, William P.; Moran, M.S.; Pinter, P. J.; Jackson, R. D.; Brown, P.W.; Nichols, W.D.; Gay, L.W.

1990-01-01

Conventional methods of measuring surface energy balance are point measurements and represent only a small area. Remote sensing offers a potential means of measuring outgoing fluxes over large areas at the spatial resolution of the sensor. The objective of this study was to estimate net radiation (Rn) and soil heat flux (G) using remotely sensed multispectral data acquired from an aircraft over large agricultural fields. Ground-based instruments measured Rn and G at nine locations along the flight lines. Incoming fluxes were also measured by ground-based instruments. Outgoing fluxes were estimated using remotely sensed data. Remote Rn, estimated as the algebraic sum of incoming and outgoing fluxes, slightly underestimated Rn measured by the ground-based net radiometers. The mean absolute errors for remote Rn minus measured Rn were less than 7%. Remote G, estimated as a function of a spectral vegetation index and remote Rn, slightly overestimated measured G; however, the mean absolute error for remote G was 13%. Some of the differences between measured and remote values of Rn and G are associated with differences in instrument designs and measurement techniques. The root mean square error for available energy (Rn - G) was 12%. Thus, methods using both ground-based and remotely sensed data can provide reliable estimates of the available energy which can be partitioned into sensible and latent heat under nonadvective conditions. ?? 1990.

Estimating urban forest carbon sequestration potential in the southern United States using current remote sensing imagery sources

Treesearch

Krista Merry; Pete Bettinger; Jacek Siry; J. Michael Bowker

2015-01-01

With an increased interest in reducing carbon dioxide in the atmosphere, tree planting and maintenance in urban areas has become a viable option for increasing carbon sequestration. Methods for assessing the potential for planting trees within an urban area should allow for quick, inexpensive, and accurate estimations of available land using current remote sensing...

Colorado SIP: 5 CCR 1001-13, Reg 11, Motor Vehicle Emissions Inspection Program—Part A, General Provisions, Area of Applicability, Schedules for Obtaining Certification of Emissions Control, Definitions, Exemptions, and Clean Screening/Remote Sensing

EPA Pesticide Factsheets

Colorado SIP: 5 CCR 1001-13, Reg 11, Motor Vehicle Emissions Inspection Program—Part A, General Provisions, Area of Applicability, Schedules for Obtaining Certification of Emissions Control, Definitions, Exemptions, and Clean Screening/Remote Sensing

A study to identify research issues in the area of electromagnetic measurements and signal handling of remotely sensed data

NASA Technical Reports Server (NTRS)

1982-01-01

Research issues in the area of electromagnetic measurements and signal handling of remotely sensed data are identified. The following seven issues are discussed; platform/sensor system position and velocity, platform/sensor attitudes and attitude rates, optics and antennas, detectors and associated electronics, sensor calibration, signal handling, and system design.

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

Land remote sensing in the 1980's

NASA Technical Reports Server (NTRS)

Thome, P. G.

1982-01-01

A discussion is presented concerning U.S. governmental funding policy for the Land Remote Sensing programs, in which the Landsat spacecraft and the research and development activities associated with them are essential elements. Even if present program management practices were to be changed in the next 1-2 years, the investment of significant amounts of private capital in land remote sensing may be 3-5 years away, due to the immaturity of the prospective markets for the services rendered and the present state of technological development. It is judged that even if NASA is successful in bringing significant private investment into remote sensing activities by the mid-1980s, government must continue to support basic research and expensive technology development in long term and high risk, but potentially high payoff, areas which the still-developing remote sensing industry cannot afford.

Applied Remote Sensing Program (ARSP)

NASA Technical Reports Server (NTRS)

Mouat, D. A.; Johnson, J. D.; Foster, K. E.

1977-01-01

Descriptions of projects engaged by the Applied Remote Sensors Program in the state of Arizona are contained in an annual report for the fiscal year 1976-1977. Remote sensing techniques included thermal infrared imagery in analog and digital form and conversion of data into thermograms. Delineation of geologic areas, surveys of vegetation and inventory of resources were also presented.

Remote sensing, imaging, and signal engineering

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

Brase, J.M.

1993-03-01

This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.

Applications of airborne remote sensing in atmospheric sciences research

NASA Technical Reports Server (NTRS)

Serafin, R. J.; Szejwach, G.; Phillips, B. B.

1984-01-01

This paper explores the potential for airborne remote sensing for atmospheric sciences research. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. Promising candidates include Doppler radar and lidar, infrared short range radiometry, and microwave radiometry.

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

NASA Technical Reports Server (NTRS)

Lang, H. R. (Editor)

1985-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Aerospace remote sensing of the coastal zone for water quality and biotic productivity applications

NASA Technical Reports Server (NTRS)

Pritchard, E. B.; Harriss, R. C.

1981-01-01

Remote sensing can provide the wide area synoptic coverage of surface waters which is required for studies of such phenomena as river plume mixing, phytoplankton dynamics, and pollutant transport and fate, but which is not obtainable by conventional oceanographic techniques. The application of several remote sensors (aircraftborne and spacecraftborne multispectral scanners, passive microwave radiometers, and active laser systems) to coastal zone research is discussed. Current measurement capabilities (particulates, chlorophyll a, temperature, salinity, ocean dumped materials, other pollutants, and surface winds and roughness) are defined and the results of recent remote sensing experiments conducted in the North Atlantic coastal zone are presented. The future development of remote sensing must rely on an integrated laboratory research program in optical physics. Recent results indicate the potential for separation of particulates into subsets by remote sensors.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

The application of remote sensing techniques to selected inter and intra urban data acquisition problems

NASA Technical Reports Server (NTRS)

Horton, F. E.

1970-01-01

The utility of remote sensing techniques to urban data acquisition problems in several distinct areas was identified. This endeavor included a comparison of remote sensing systems for urban data collection, the extraction of housing quality data from aerial photography, utilization of photographic sensors in urban transportation studies, urban change detection, space photography utilization, and an application of remote sensing techniques to the acquisition of data concerning intra-urban commercial centers. The systematic evaluation of variable extraction for urban modeling and planning at several different scales, and the model derivation for identifying and predicting economic growth and change within a regional system of cities are also studied.

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.

User requirements for project-oriented remote sensing

NASA Technical Reports Server (NTRS)

Hitchcock, H. C.; Baxter, F. P.; Cox, T. L.

1975-01-01

Registration of remotely sensed data to geodetic coordinates provides for overlay analysis of land use data. For aerial photographs of a large area, differences in scales, dates, and film types are reconciled, and multispectral scanner data are machine registered at the time of acquisition.

Upper Kalamazoo watershed land cover inventory. [based on remote sensing

NASA Technical Reports Server (NTRS)

Richason, B., III; Enslin, W.

1973-01-01

Approximately 1000 square miles of the eastern portion of the watershed were inventoried based on remote sensing imagery. The classification scheme, imagery and interpretation procedures, and a cost analysis are discussed. The distributions of land cover within the area are tabulated.

Workshop on The Rio Grande Rift: Crustal Modeling and Applications of Remote Sensing

NASA Technical Reports Server (NTRS)

Blanchard, D. P. (Editor)

1980-01-01

The elements of a program that could address significant earth science problems by combining remote sensing and traditional geological, geophysical, and geochemical approaches were addressed. Specific areas and tasks related to the Rio Grande Rift are discussed.

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

EPA Science Inventory

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

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…

Millimeter-Wave Propagation and Remote Sensing of the Atmosphere,

DTIC Science & Technology

1983-12-01

tool to probe lower atmospheric structure. The principal applications of millimeter waves have been in the areas of communications, radar, and remote ... sensing . The availability of large bandwidths makes this region of the spectrum particularly attractive for high data rate communications. Because

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

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Research on the application of satellite remote sensing to local, state, regional, and national programs involved with resource management and environmental quality

NASA Technical Reports Server (NTRS)

Walters, R. L.; Eastmond, R. J.; Barr, B. G.

1973-01-01

Project summaries and project reports are presented in the area of satellite remote sensing as applied to local, regional, and national environmental programs. Projects reports include: (1) Douglas County applications program; (2) vegetation damage and heavy metal concentration in new lead belt; (3) evaluating reclamation of strip-mined land; (4) remote sensing applied to land use planning at Clinton Reservoir; and (5) detailed land use mapping in Kansas City, Kansas.

Enhancement of Capabilities in Hyperspectral and Radar Remote Sensing for Environmental Assessment and Monitoring

NASA Technical Reports Server (NTRS)

Hepner, George F.

1999-01-01

The University of Utah, Department of Geography has developed a research and instructional program in satellite remote sensing and image processing. The University requested funds for the purchase of software licenses, mass storage for massive hyperspectral imager data sets, upgrades for the central data server to handle the additional storage capacity, a spectroradiometer for field data collection. These purchases have been made. This equipment will support research in one of the newest and most rapidly expanding areas of remote sensing.

1994 ASPRS/ACSM annual convention exposition. Volume 2

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

Not Available

1994-01-01

This report is Volume II of presented papers at the joint 1994 convention of the American Society for Photgrammetry and Remote Sensing and American Congress on Surveying and Mapping. Topic areas covered include the following: Data Base/GPS Issues; Survey Management Issues; Surveying computations; Surveying education; Digital mapping; global change, EOS and NALC issues; GPS issues; Battelle Research in Remote Sensing and in GIS; Advanced Image Processing;GIS Issues; Surveying and Geodesy Issues; water resource issues; Advanced applications of remote sensing; Landsat Pathfinder I.

Aircraft remote sensing of soil moisture and hydrologic parameters, Taylor Creek, Florida, and Little River, Georgia, 1979 data report

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Schmugge, T. J.; Allen, L. H., Jr.; Oneill, P.; Slack, R.; Wang, J.; Engman, E. T.

1981-01-01

Experiments were conducted to evaluate aircraft remote sensing techniques for hydrology in a wide range of physiographic and climatic regions using several sensor platforms. The data were collected in late 1978 and during 1979 in two humid areas--Taylor Creek, Fla., and Little River, Ga. Soil moisture measurements and climatic observations are presented as well as the remote sensing data collected using thermal infrared, passive microwave, and active microwave systems.

Accuracy of Remotely Sensed Classifications For Stratification of Forest and Nonforest Lands

Treesearch

Raymond L. Czaplewski; Paul L. Patterson

2001-01-01

We specify accuracy standards for remotely sensed classifications used by FIA to stratify landscapes into two categories: forest and nonforest. Accuracy must be highest when forest area approaches 100 percent of the landscape. If forest area is rare in a landscape, then accuracy in the nonforest stratum must be very high, even at the expense of accuracy in the forest...

The use of high altitude aerial photography to inventory wildlife habitat in Kansas: An initial evaluation

NASA Technical Reports Server (NTRS)

Merchant, J. W.; Waddell, B. H.

1974-01-01

The use of aerial photography as a method for determining the wildlife conditions of an area is discussed. Color infrared photography is investigated as the most effective type of remote sensor. The characteristics of the remote sensing systems are described. Examples of the remote sensing operation and the method for reducing the data are presented.

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

PIXELS: Using field-based learning to investigate students' concepts of pixels and sense of scale

NASA Astrophysics Data System (ADS)

Pope, A.; Tinigin, L.; Petcovic, H. L.; Ormand, C. J.; LaDue, N.

2015-12-01

Empirical work over the past decade supports the notion that a high level of spatial thinking skill is critical to success in the geosciences. Spatial thinking incorporates a host of sub-skills such as mentally rotating an object, imagining the inside of a 3D object based on outside patterns, unfolding a landscape, and disembedding critical patterns from background noise. In this study, we focus on sense of scale, which refers to how an individual quantified space, and is thought to develop through kinesthetic experiences. Remote sensing data are increasingly being used for wide-reaching and high impact research. A sense of scale is critical to many areas of the geosciences, including understanding and interpreting remotely sensed imagery. In this exploratory study, students (N=17) attending the Juneau Icefield Research Program participated in a 3-hour exercise designed to study how a field-based activity might impact their sense of scale and their conceptions of pixels in remotely sensed imagery. Prior to the activity, students had an introductory remote sensing lecture and completed the Sense of Scale inventory. Students walked and/or skied the perimeter of several pixel types, including a 1 m square (representing a WorldView sensor's pixel), a 30 m square (a Landsat pixel) and a 500 m square (a MODIS pixel). The group took reflectance measurements using a field radiometer as they physically traced out the pixel. The exercise was repeated in two different areas, one with homogenous reflectance, and another with heterogeneous reflectance. After the exercise, students again completed the Sense of Scale instrument and a demographic survey. This presentation will share the effects and efficacy of the field-based intervention to teach remote sensing concepts and to investigate potential relationships between students' concepts of pixels and sense of scale.

A Merging Approach for Urban Boundary Correction Acquired By Remote Sensing Images

NASA Astrophysics Data System (ADS)

Zhang, P. L.; Shi, W. Z.; Wu, X. Y.

2014-11-01

Since reform and opening up to outside world, ever-growing economy and development of urbanization of China have caused expansion of the urban land scale. It's necessary to grasp the information about urban spatial form change, expansion situation and expanding regularity, in order to provide the scientific basis for urban management and planning. The traditional methods, like land supply cumulative method and remote sensing, to get the urban area, existed some defects. Their results always doesn't accord with the reality, and can't reflects the actual size of the urban area. Therefore, we propose a new method, making the best use of remote sensing, the population data, road data and other social economic statistic data. Because urban boundary not only expresses a geographical concept, also a social economic systems.It's inaccurate to describe urban area with only geographic areas. We firstly use remote sensing images, demographic data, road data and other data to produce urban boundary respectively. Then we choose the weight value for each boundary, and in terms of a certain model the ultimate boundary can be obtained by a series of calculations of previous boundaries. To verify the validity of this method, we design a set of experiments and obtained the preliminary results. The results have shown that this method can extract the urban area well and conforms with both the broad and narrow sense. Compared with the traditional methods, it's more real-time, objective and ornamental.

Remote sensing measurements of real world high exhaust emitters

DOT National Transportation Integrated Search

1999-03-12

Remote Sensing measurements were taken at five primary sites in the Denver Area between April 1997 and March 1998 using an RS2000 unit capable of measuring HC, CO, and NO. The RD unit also measures vehicle speed and acceleration to permit determinati...

[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.

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.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

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.

Modeling residential lawn fertilization practices: integrating high resolution remote sensing with socioeconomic data.

PubMed

Zhou, Weiqi; Troy, Austin; Grove, Morgan

2008-05-01

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman's Run, in Baltimore County, Maryland, USA. Parcel lawn area and lawn greenness were derived from high-resolution aerial imagery using an object-oriented classification approach. Four indicators of household characteristics, including lot size, square footage of the house, housing value, and housing age were obtained from a property database. Residential lawn care survey data combined with remotely sensed parcel lawn area and greenness data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application amount (N_yr) and household annual fertilizer nitrogen application rate (N_ha_yr). Using multiple regression with multi-model inferential procedures, we found that a combination of parcel lawn area and parcel lawn greenness best predicts N_yr, whereas a combination of parcel lawn greenness and lot size best predicts variation in N_ha_yr. Our analyses show that household fertilization practices can be effectively predicted by remotely sensed lawn indices and household characteristics. This has significant implications for urban watershed managers and modelers.

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

USGS Publications Warehouse

Lauer, Donald T.; Chu, Liangcai

1992-01-01

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

Biogeochemical cycling in terrestrial ecosystems - Modeling, measurement, and remote sensing

NASA Technical Reports Server (NTRS)

Peterson, D. L.; Matson, P. A.; Lawless, J. G.; Aber, J. D.; Vitousek, P. M.

1985-01-01

The use of modeling, remote sensing, and measurements to characterize the pathways and to measure the rate of biogeochemical cycling in forest ecosystems is described. The application of the process-level model to predict processes in intact forests and ecosystems response to disturbance is examined. The selection of research areas from contrasting climate regimes and sites having a fertility gradient in that regime is discussed, and the sites studied are listed. The use of remote sensing in determining leaf area index and canopy biochemistry is analyzed. Nitrous oxide emission is investigated by using a gas measurement instrument. Future research projects, which include studying the influence of changes on nutrient cycling in ecosystems and the effect of pollutants on the ecosystems, are discussed.

State resource management and role of remote sensing. [California

NASA Technical Reports Server (NTRS)

Johnson, H. D.

1981-01-01

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

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

NASA Technical Reports Server (NTRS)

Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

2003-01-01

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS).

PubMed

Zhang, Yuanzhi; Chen, Zhengyi; Zhu, Boqin; Luo, Xiuyue; Guan, Yanning; Guo, Shan; Nie, Yueping

2008-12-01

The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.

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.

Monitoring the lake area changes of the Qinghai-Tibet Plateau using coarse-resolution time series remote sensing data

NASA Astrophysics Data System (ADS)

Ma, M.

2015-12-01

The Qinghai-Tibet Plateau (QTP) is the world's highest and largest plateau and is occasionally referred to as "the roof of the world". As the important "water tower", there are 1,091 lakes of more than 1.0 km2 in the QTP areas, which account for 49.4% of the total area of lakes in China. Some studies focus on the lake area changes of the QTP areas, which mainly use the middle-resolution remote sensing data (e.g. Landsat TM). In this study, the coarse-resolution time series remote sensing data, MODIS data at a spatial resolution of 250m, was used to monitor the lake area changes of the QTP areas during the last 15 years. The dataset is the MOD13Q1 and the Normal Difference Vegetation Index (NDVI) is used to identify the lake area when the NDVI is less than 0. The results show the obvious inner-annual changes of most of the lakes. Therefore the annually average and maximum lake areas are calculated based on the time series remote data, which can better quantify the change characteristics than the single scene of image data from the middle-resolution data. The results indicate that there are big spatial variances of the lake area changes in the QTB. The natural driving factors are analyzed for revealing the causes of changes.

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

PubMed

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

2006-09-01

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

Earthquake Hazard Analysis Methods: A Review

NASA Astrophysics Data System (ADS)

Sari, A. M.; Fakhrurrozi, A.

2018-02-01

One of natural disasters that have significantly impacted on risks and damage is an earthquake. World countries such as China, Japan, and Indonesia are countries located on the active movement of continental plates with more frequent earthquake occurrence compared to other countries. Several methods of earthquake hazard analysis have been done, for example by analyzing seismic zone and earthquake hazard micro-zonation, by using Neo-Deterministic Seismic Hazard Analysis (N-DSHA) method, and by using Remote Sensing. In its application, it is necessary to review the effectiveness of each technique in advance. Considering the efficiency of time and the accuracy of data, remote sensing is used as a reference to the assess earthquake hazard accurately and quickly as it only takes a limited time required in the right decision-making shortly after the disaster. Exposed areas and possibly vulnerable areas due to earthquake hazards can be easily analyzed using remote sensing. Technological developments in remote sensing such as GeoEye-1 provide added value and excellence in the use of remote sensing as one of the methods in the assessment of earthquake risk and damage. Furthermore, the use of this technique is expected to be considered in designing policies for disaster management in particular and can reduce the risk of natural disasters such as earthquakes in Indonesia.

Use of remote sensing for land use policy formulation. [Allegan, Bay, Branch, Ionia, Livingston, and St. Clair Counties in Michigan and Lake Michigan shorelines

NASA Technical Reports Server (NTRS)

Boylan, M. (Principal Investigator)

1978-01-01

The author has identified the following significant results. By utilizing remote sensing techniques, it was possible to accurately inventory a relatively large area for sand mining impact on protection and management of shoreland dunes within a limited time period and at a relatively low cost. Analysis of two sample areas selected from the Grand Mere area after prohibition of off-road-vehicle use indicated an increase in vegetation regrowth of 8.52% for sample area 1 and of 4.44% for sample area 2.

Investigations on classification categories for wetlands of Chesapeake Bay using remotely sensed data

NASA Technical Reports Server (NTRS)

Williamson, F. S. L.

1974-01-01

The use of remote sensors to determine the characteristics of the wetlands of the Chesapeake Bay and surrounding areas is discussed. The objectives of the program are stated as follows: (1) to use data and remote sensing techniques developed from studies of Rhode River, West River, and South River salt marshes to develop a wetland classification scheme useful in other regions of the Chesapeake Bay and to evaluate the classification system with respect to vegetation types, marsh physiography, man-induced perturbation, and salinity; and (2) to develop a program using remote sensing techniques, for the extension of the classification to Chesapeake Bay salt marshes and to coordinate this program with the goals of the Chesapeake Research Consortium and the states of Maryland and Virginia. Maps of the Chesapeake Bay areas are developed from aerial photographs to display the wetland structure and vegetation.

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.

SIMULATION STUDY FOR GASEOUS FLUXES FROM AN AREA SOURCE USING COMPUTED TOMOGRAPHY AND OPTICAL REMOTE SENSING

EPA Science Inventory

The paper presents a new approach to quantifying emissions from fugitive gaseous air pollution sources. Computed tomography (CT) and path-integrated optical remote sensing (PI-ORS) concentration data are combined in a new field beam geometry. Path-integrated concentrations are ...

A Rapidly Prototyped Vegetation Dryness Index Developed for Wildfire Risk Assessment at Stennis Space Center

NASA Technical Reports Server (NTRS)

Ross, Kenton; Graham, William D.; Prados, Donald; Spruce, Joseph

2006-01-01

A remote sensing index was developed to allow improved monitoring of vegetation dryness conditions on a regional basis. This remote sensing index was rapidly prototyped at Stennis Space Center in response to drought conditions in the local area in spring 2006.

Remote Sensing of Earth--A New Perspective

ERIC Educational Resources Information Center

Boyer, Robert E.

1973-01-01

Photographs of the earth taken from space are used to illustrate the advantages and application of remote sensing. This technique may be used in such areas as the immediate appraisal of disasters, surveillance of the oceans, monitoring of land, food and water resources, detection of natural resources, and identification of pollution. (JR)

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

DTIC Science & Technology

2015-11-04

is more likely to be encountered in high latitudes. The technique recognizes areas of urban or rural built environments, such as mowed fields...optical remote sensing of river channel morphology and in-stream habitat : physical basis and feasability. Remote Sensing of the Environment 93: 493

Research in remote sensing of agriculture, earth resources, and man's environment

NASA Technical Reports Server (NTRS)

Landgrebe, D. A.

1975-01-01

Progress is reported for several projects involving the utilization of LANDSAT remote sensing capabilities. Areas under study include crop inventory, crop identification, crop yield prediction, forest resources evaluation, land resources evaluation and soil classification. Numerical methods for image processing are discussed, particularly those for image enhancement and analysis.

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 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.

ESTAR: The Electronically Scanned Thinned Array Radiometer for remote sensing measurement of soil moisture and ocean salinity

NASA Technical Reports Server (NTRS)

Swift, C. T.

1993-01-01

The product of a working group assembled to help define the science objectives and measurement requirements of a spaceborne L-band microwave radiometer devoted to remote sensing of surface soil moisture and sea surface salinity is presented. Remote sensing in this long-wavelength portion of the microwave spectrum requires large antennas in low-Earth orbit to achieve acceptable spatial resolution. The proposed radiometer, ESTAR, is unique in that it employs aperture synthesis to reduce the antenna area requirements for a space system.

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

USGS Publications Warehouse

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

2012-01-01

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

Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis—A case study in Tengchong, China

NASA Astrophysics Data System (ADS)

Qin, Qiming; Zhang, Ning; Nan, Peng; Chai, Leilei

2011-08-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. Based on radiometric calibration, atmospheric correction and emissivity calculation, a simple but efficient single channel algorithm with acceptable precision is applied to retrieve the land surface temperature (LST) of study area. The LST anomalous areas with temperature about 4-10 K higher than background area are discovered. Four geothermal areas are identified with the discussion of geothermal mechanism and the further analysis of regional geologic structure. The research reveals that the distribution of geothermal areas is consistent with the fault development in study area. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect LST anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Multiscale and Multitemporal Urban Remote Sensing

NASA Astrophysics Data System (ADS)

Mesev, V.

2012-07-01

The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.

Remote sensing in biological oceanography

NASA Technical Reports Server (NTRS)

Esaias, W. E.

1981-01-01

The main attribute of remote sensing is seen as its ability to measure distributions over large areas on a synoptic basis and to repeat this coverage at required time periods. The way in which the Coastal Zone Color Scanner, by showing the distribution of chlorophyll a, can locate areas productive in both phytoplankton and fishes is described. Lidar techniques are discussed, and it is pointed out that lidar will increase the depth range for observations.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Rapid Change Detection Algorithm for Disaster Management

NASA Astrophysics Data System (ADS)

Michel, U.; Thunig, H.; Ehlers, M.; Reinartz, P.

2012-07-01

This paper focuses on change detection applications in areas where catastrophic events took place which resulted in rapid destruction especially of manmade objects. Standard methods for automated change detection prove not to be sufficient; therefore a new method was developed and tested. The presented method allows a fast detection and visualization of change in areas of crisis or catastrophes. While often new methods of remote sensing are developed without user oriented aspects, organizations and authorities are not able to use these methods because of absence of remote sensing know how. Therefore a semi-automated procedure was developed. Within a transferable framework, the developed algorithm can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated Temporal Change Index (TCI) only panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas where rebuilding has already started.

On multidisciplinary research on the application of remote sensing to water resources problems. [Wisconsin

NASA Technical Reports Server (NTRS)

Clapp, J. L.

1973-01-01

Research objectives during 1972-73 were to: (1) Ascertain the extent to which special aerial photography can be operationally used in monitoring water pollution parameters. (2) Ascertain the effectiveness of remote sensing in the investigation of nearshore mixing and coastal entrapment in large water bodies. (3) Develop an explicit relationship of the extent of the mixing zone in terms of the outfall, effluent and water body characteristics. (4) Develop and demonstrate the use of the remote sensing method as an effective legal implement through which administrative agencies and courts can not only investigate possible pollution sources but also legally prove the source of water pollution. (5) Evaluate the field potential of remote sensing techniques in monitoring algal blooms and aquatic macrophytes, and the use of these as indicators of lake eutrophication level. (6) Develop a remote sensing technique for the determination of the location and extent of hydrologically active source areas in a watershed.

The role of satellite remote sensing in structured ecosystem risk assessments.

PubMed

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Remote Sensing Application to Land Use Classification in a Rapidly Changing Agricultural/Urban Area: City of Virginia Beach, Virginia. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Odenyo, V. A. O.

1975-01-01

Remote sensing data on computer-compatible tapes of LANDSAT 1 multispectral scanner imager were analyzed to generate a land use map of the City of Virginia Beach. All four bands were used in both the supervised and unsupervised approaches with the LAYSYS software system. Color IR imagery of a U-2 flight of the same area was also digitized and two sample areas were analyzed via the unsupervised approach. The relationships between the mapped land use and the soils of the area were investigated. A land use land cover map at a scale of 1:24,000 was obtained from the supervised analysis of LANDSAT 1 data. It was concluded that machine analysis of remote sensing data to produce land use maps was feasible; that the LAYSYS software system was usable for this purpose; and that the machine analysis was capable of extracting detailed information from the relatively small scale LANDSAT data in a much shorter time without compromising accuracy.

Appraisement of environment remote sensing method in mining area

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Zhen, Han; Jiang, Tao; Lei, Liqing; Gong, Cailan

1998-08-01

Coal mining is attached great importance by society as a key profession of environmental pollution. The monitor and protection of coal-mine environment is a developing profession in China. The sulfur dioxide, carbon dioxide, carbon monoxide and other waste gases, which are put out by the spontaneous combustion or weathering of gangue are an important pollution resource of atmosphere. The stack of gangue held down many farmlands. Smoke, coal dust and powder coal ash pollute the environment of mining area and surroundings though the affection of monsoon. The pH value of water which coal mine drained off is low, and the drinking, farming and animal husbandry water where it flowed are affected. The surface subsidence which mining caused is a typical destruction of ground environment. The people pay attention to remote sensing as a method of rapidly, cheaply regional environment investigation. The paper tires making an appraisement of mining area environment monitor by many kind methods of remote sensing from the characteristic of mining area environment.

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.

A feasibility study of using remotely sensed data for water resource models

NASA Technical Reports Server (NTRS)

Ruff, J. F.

1973-01-01

Remotely sensed data were collected to demonstrate the feasibility of applying the results to water resource problems. Photographs of the Wolf Creek watershed in southwestern Colorado were collected over a one year period. Cloud top temperatures were measured using a radiometer. Thermal imagery of the Wolf Creek Pass area was obtained during one pre-dawn flight. Remote sensing studies of water resource problems for user agencies were also conducted. The results indicated that: (1) remote sensing techniques could be used to assist in the solution of water resource problems; (2) photogrammetric determination of snow depths is feasible; (3) changes in turbidity or suspended material concentration can be observed; and (4) surface turbulence can be related to bed scour; and (5) thermal effluents into rivers can be monitored.

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.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Automobile gross emitter screening with remote sensing data using objective-oriented neural network.

PubMed

Chen, Ho-Wen; Yang, Hsi-Hsien; Wang, Yu-Sheng

2009-11-01

One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.

[Application of remote sensing and GIS in study of suitability distribution of Swertia mussotii, a Tibetan medicine in Sichuan province].

PubMed

Dong, Yong-Bo; Luo, Yao; Zhu, Cong; Peng, Wen-Fu; Xu, Xin-Liang; Fang, Qing-Mao

2017-11-01

Swertia mussotii is a kind of rare medicinal materials, the relevant researches are mainly concentrated on its medicinal efficacy and medicinal value till now, researches of adaptive distribution by applying remote sensing and GIS are relatively less. This study is to analyze the adaptive distribution of S.mussotii in Sichuan province by applying remote sensing and GIS technology, and provide scientific basis for the protection and development of wild resources, artificial cultivation and adjustment of Chinese medicine industrial distribution in Sichuan province. Based on literature review and ecological factors such as altitude, annual precipitation and annual average temperature, this study extracted ecological factors, overlay analysis in GIS, as well as combining GPS field validation data by means of remote sensing and GIS, discusses the adaptive distribution of SMF sin Sichuan province. ①The area of adaptive distribution of S. mussotii in Sichuan province is 1 543.749 km², mainly in Dege county, Ganzi county, Daofu county, Kangding county, Barkam, Jinchuan county, Xiaojin county, Danba county, Daocheng county, Xiangcheng county, Xinlong county, Aba county, Muli county and other counties and cities, accounts for about 7.25% in total area. ② Combining statistical information and field validation, this study found that S. mussotii adaptive distribution gained by remote sensing and GIS is in conformity with its actual distribution. The study shows that remote sensing and GIS technology are feasible to obtain the S. mussotii adaptive distribution, they can further be applied to studies on adaptive distributions of other rare Chinese medicinal herb. Copyright© by the Chinese Pharmaceutical Association.

Inroads of remote sensing into hydrologic science during the WRR era

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.; Alsdorf, Doug; Dozier, Jeff; Huffman, George J.; Pan, Ming; Wood, Eric F.

2015-09-01

The first issue of WRR appeared eight years after the launch of Sputnik, but by WRR's 25th anniversary, only seven papers that used remote sensing had appeared. Over the journal's second 25 years, that changed remarkably, and remote sensing is now widely used in hydrology and other geophysical sciences. We attribute this evolution to production of data sets that scientists not well versed in remote sensing can use, and to educational initiatives like NASA's Earth System Science Fellowship program that has supported over a thousand scientists, many in hydrology. We review progress in remote sensing in hydrology from a water balance perspective. We argue that progress is primarily attributable to a creative use of existing and past satellite sensors to estimate such variables as evapotranspiration rates or water storage in lakes and reservoirs and to new and planned missions. Recent transforming technologies include the Gravity Recovery and Climate Experiment (GRACE), the European Soil Moisture and Ocean Salinity (SMOS) and U.S. Soil Moisture Active Passive (SMAP) missions, and the Global Precipitation Measurement (GPM) mission. Future missions include Surface Water and Ocean Topography (SWOT) to measure river discharge and lake, reservoir, and wetland storage. Measurement of some important hydrologic variables remains problematic: retrieval of snow water equivalent (SWE) from space remains elusive especially in mountain areas, even though snow cover extent is well observed, and was the topic of 4 of the first 5 remote sensing papers published in WRR. We argue that this area deserves more strategic thinking from the hydrology community.

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

NASA Technical Reports Server (NTRS)

Weinstein, R. H.

1980-01-01

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

Multi-crop area estimation and mapping on a microprocessor/mainframe network

NASA Technical Reports Server (NTRS)

Sheffner, E.

1985-01-01

The data processing system is outlined for a 1985 test aimed at determining the performance characteristics of area estimation and mapping procedures connected with the California Cooperative Remote Sensing Project. The project is a joint effort of the USDA Statistical Reporting Service-Remote Sensing Branch, the California Department of Water Resources, NASA-Ames Research Center, and the University of California Remote Sensing Research Program. One objective of the program was to study performance when data processing is done on a microprocessor/mainframe network under operational conditions. The 1985 test covered the hardware, software, and network specifications and the integration of these three components. Plans for the year - including planned completion of PEDITOR software, testing of software on MIDAS, and accomplishment of data processing on the MIDAS-VAX-CRAY network - are discussed briefly.

Natural Resource Information System, remote sensing studies

NASA Technical Reports Server (NTRS)

Leachtenauer, J.; Hirsch, R.; Williams, V.; Tucker, R.

1972-01-01

Potential applications of remote sensing data were reviewed, and available imagery was interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and qualities of imagery required to satisfy identified data needs. Ektachrome imagery available over the demonstration areas was reviewed to establish the feasibility of interpreting cultural features, range condition, and timber type. Using the same imagery, a land use map was prepared for the demonstration area. The feasibility of identifying commercial timber areas using a density slicing technique was tested on multispectral imagery available for a portion of the demonstration area.

The rationale for attempting to define salt marsh mosquito-breeding areas in Galveston County by remote sensing the associated vegetation

NASA Technical Reports Server (NTRS)

Arp, G. K.

1975-01-01

The rationale for attempting to define salt marsh mosquito breeding areas in Galveston County was discussed, including a botanical survey of the marsh plant communities, their relationship to flooding, and their exposure to salt water. Particular emphasis is given to Distichlis spicata, a widespread marsh grass. Evidence suggests that breeding areas of Aedes sollicitans are associated with Distichlis and that both species respond to similar ecological conditions in the salt marsh. Aspects of the remote sensing of the Distichlis are considered.

Application of remote sensing

NASA Technical Reports Server (NTRS)

Graff, W. J. (Compiler)

1973-01-01

Remote sensing and aerial photographic interpretation are discussed along with the specific imagery techniques used for this research. The method used to select sites, the results of data analyses for the Houston metropolitan area, and the location of dredging sites along the Houston Ship Channel are presented. The work proposed for the second year of the project is described.

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...

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

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...

Modeling residential lawn fertilization practices: integrating high resolution remote sensing with socioeconomic data

Treesearch

Weiqi Zhou; Austin Troy; Morgan Grove

2008-01-01

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman's Run, in Baltimore County, Maryland, USA. Parcel lawn...

Selective logging in the Brazilian Amazon.

Treesearch

G. P. Asner; D. E. Knapp; E. N. Broadbent; P. J. C. Oliveira; M Keller; J. N. Silva

2005-01-01

Amazon deforestation has been measured by remote sensing for three decades. In comparison, selective logging has been mostly invisible to satellites. We developed a large-scale, high-resolution, automated remote-sensing analysis of selective logging in the top five timber-producing states of the Brazilian Amazon. Logged areas ranged from 12,075 to 19,823 square...

Remote Sensing of Suspended Sediments and Shallow Coastal Waters

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.; Gao, Bo-Cai; Davis, Curtiss O.

2002-01-01

Ocean color sensors were designed mainly for remote sensing of chlorophyll concentrations over the clear open oceanic areas (case 1 water) using channels between 0.4 and 0.86 micrometers. The Moderate Resolution Imaging Spectroradiometer (MODIS) launched on the NASA Terra and Aqua Spacecrafts is equipped with narrow channels located within a wider wavelength range between 0.4 and 2.5 micrometers for a variety of remote sensing applications. The wide spectral range can provide improved capabilities for remote sensing of the more complex and turbid coastal waters (case 2 water) and for improved atmospheric corrections for Ocean scenes. In this article, we describe an empirical algorithm that uses this wide spectral range to identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. The algorithm takes advantage of the strong water absorption at wavelengths longer than 1 micrometer that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

Bakó, Gábor; Tolnai, Márton; Takács, Ádám

2014-01-01

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

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.

Assessing Wetland Hydroperiod and Soil Moisture with Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

NASA Technical Reports Server (NTRS)

Brooks, Colin; Bourgeau-Chavez, Laura; Endres, Sarah; Battaglia, Michael; Shuchman, Robert

2015-01-01

Assist with the evaluation and measuring of wetlands hydroperiod at the Plum Brook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: (1) Show the relative length of hydroperiod using available remote sensing datasets, (2) Date linked table of wetlands extent over time for all feasible non-forested wetlands, (3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables (4), A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment; and (5) A MTRI style report summarizing year 2 results.

A visiting scientist program in atmospheric sciences for the Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Davis, M. H.

1989-01-01

A visiting scientist program was conducted in the atmospheric sciences and related areas at the Goddard Laboratory for Atmospheres. Research was performed in mathematical analysis as applied to computer modeling of the atmospheres; development of atmospheric modeling programs; analysis of remotely sensed atmospheric, surface, and oceanic data and its incorporation into atmospheric models; development of advanced remote sensing instrumentation; and related research areas. The specific research efforts are detailed by tasks.

Application of remote sensing to the geological study of the alkaline complex region of Itatiaia. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Rodrigues, J. E.

1980-01-01

The methodology of remote sensing applied to geological study in a complex area was evaluated. Itatiaia was selected as a test area, which covers the alkaline massives and its precambrian basement. LANDSAT-MSS and radar mosaic of the RADAMBRASIL Project were used for photointerpretation. Previous geological works were consulted and many discrepancies in the distribution of stratigraphic units were found. Moreover, structural lineaments and talus deposits were clearly delineated.

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.

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.

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Monitoring water quality by remote sensing

NASA Technical Reports Server (NTRS)

Brown, R. L. (Principal Investigator)

1977-01-01

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

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.

Applications of remote sensing in public health.

NASA Technical Reports Server (NTRS)

Barnes, C. M.; Fuller, C. E.; Schneider, H. J.; Kennedy, E. E.; Jones, H. G.; Morrison, D. R.

1973-01-01

Current research concerning the determination of the habitat of mosquito vectors of disease is discussed. It is shown how advanced interpretative processes have enabled recognition of the breeding areas of salt marsh mosquitoes and the breeding sites of the mosquito responsible for the transmission of St. Louis strain of encephalitis and of human filariasis. In addition, remote sensing data have also been useful in the study of the habitat of endemic strains of Venezuelan encephalitis virus in Florida. The beginning of the application of remote sensing to such public health aspects as air, water, and urban degradation is noted.

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.

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.

Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China.

PubMed

Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

2008-11-07

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index) values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1) the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2) the installation/innovation of the drainage system did help to control salinity; and (3) a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

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.

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

NASA Astrophysics Data System (ADS)

Rokhmana, Catur Aries; Andaru, Ruli

2017-07-01

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

Development of monitoring method of coffee leaf rust fungus (Hemileia vastatrix) infected area using satellite remote sensing

NASA Astrophysics Data System (ADS)

Katsuhama, N.; Ikeda, K.; Imai, M.; Watanabe, K.; Marpaung, F.; Yoshii, T.; Naruse, N.; Takahashi, Y.

2016-12-01

Since 2008, coffee leaf rust fungus (Hemileia vastatrix) has expanded its infection in Latin America, and early trimming and burning infected trees have been only effective countermeasures to prevent spreading infection. Although some researchers reported a case about the monitoring of coffee leaf rust using satellite remote sensing in 1970s, the spatial resolution was unsatisfied, and therefore, further technological development has been required. The purpose of this research is to develop effective method of discovering coffee leaf rust infected areas using satellite remote sensing. Annual changes of vegetation indices, i.e. Normalized Difference Vegetation Index (NDVI) and Modified Structure Insensitive Pigment Index (MSIPI), around Cuchumatanes Mountains, Republic of Guatemala, were analyzed by Landsat 7 images. Study fields in the research were limited by the coffee farm areas based on a previous paper about on site surveys in different damage areas. As the result of the analysis, the annual change of NDVI at the coffee farm areas with damages tended to be lower than those without damages. Moreover, the decline of NDVI appear from 2008 before the damage was reported. On the other hand, the change of MSIPI had no significant difference. NDVI and MSIPI are mainly related to the amount of chlorophyll and carotenoid in the leaves respectively. This means that the infected coffee leaves turned yellow without defoliation. This situation well matches the symptom of coffee leaf rust. The research concluded that the property of infected leaves turning yellow is effective to monitoring of infection areas by satellite remote sensing.

Capacity Building in Using NASA Remote Sensing for Water Resources and Disasters Management

NASA Astrophysics Data System (ADS)

Mehta, A. V.; Podest, E.; Prados, A. I.

2017-12-01

The NASA Applied Remote Sensing Training Program (ARSET), a part of NASA's Applied Sciences Capacity Building program, empowers the global community through online and in-person training. The program focuses on helping policy makers, environmental managers, and other professionals, both domestic and international, use remote sensing in decision making. Since 2011, ARSET has provided more than 20 trainings in water resource and disaster management, including floods and droughts. This presentation will include an overview of the ARSET program, best practices for approaching trainings, feedback from participants, and examples of case studies from the trainings showing the application of GPM, SMAP, Landsat, Terra and Aqua (MODIS), and Sentinel (SAR) data. This presentation will also outline how ARSET can serve as a liaison between remote sensing applications developers and users in the areas of water resource and disaster management.

Photogrammetry and remote sensing education subjects

NASA Astrophysics Data System (ADS)

Lazaridou, Maria A.; Karagianni, Aikaterini Ch.

2017-09-01

The rapid technologic advances in the scientific areas of photogrammetry and remote sensing require continuous readjustments at the educational programs and their implementation. The teaching teamwork should deal with the challenge to offer the volume of the knowledge without preventing the understanding of principles and methods and also to introduce "new" knowledge (advances, trends) followed by evaluation and presentation of relevant applications. This is of particular importance for a Civil Engineering Faculty as this in Aristotle University of Thessaloniki, as the framework of Photogrammetry and Remote Sensing is closely connected with applications in the four educational Divisions of the Faculty. This paper refers to the above and includes subjects of organizing the courses in photogrammetry and remote sensing in the Civil Engineering Faculty of Aristotle University of Thessaloniki. A scheme of the general curriculum as well the teaching aims and methods are also presented.

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

Aerial remote sensing survey of Fusarium wilt of cotton in New Mexico and Texas

USDA-ARS?s Scientific Manuscript database

Fusarium wilt of cotton, caused by the fungus Fusarium oxysporum f. sp. vasinfectum (FOV), is a widespread cotton disease, but the more virulent FOV race 4 (FOV4) has recently been identified in the New Mexico-Texas border area near El Paso, Texas. A preliminary aerial remote sensing survey was cond...

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...

Application of Remote Sensing for the Analysis of Environmental Changes in Albania

NASA Astrophysics Data System (ADS)

Frasheri, N.; Beqiraj, G.; Bushati, S.; Frasheri, A.

2016-08-01

In the paper there is presented a review of remote sensing studies carried out for investigation of environmental changes in Albania. Using, often simple methodologies and general purpose image processing software, and exploiting free Internet archives of satellite imagery, significant results were obtained for hot areas of environmental changes. Such areas include sea coasts experiencing sea transgression, temporal variations of vegetation and aerosols, lakes, landslides and regional tectonics. Internet archives of European Space Agency ESA and USA Geological Service USGS are used.

Geologic evaluation of remote sensing data, site 157, Awza-Borrego Desert, California

NASA Technical Reports Server (NTRS)

Wolfe, E. W.

1969-01-01

Remote sensing data were obtained at site 157 in May 1968 under mission 73 of the NASA aircraft program. The site is located in an area of high temperatures and extreme aridity immediately west of the Imperial Valley, Southern California. Site 157 is partially surrounded by pre-Cenozoic crystalline rocks exposed in the Fish Creek, Vallecito, and Tierra Blanca Mountains. The study area itself is underlain by more than 20,000 feet of sedimentary strata of late Cenozoic age.

Introduction. [usefulness of modern remote sensing techniques for studying components of California water resources

NASA Technical Reports Server (NTRS)

Colwell, R. N.

1973-01-01

Since May 1970, personnel on several campuses of the University of California have been conducting investigations which seek to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Emphasis has been given to California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan. This study is designed to consider in detail the supply, demand, and impact relationships. The specific geographic areas studied are the Feather River drainage in northern California, the Chino-Riverside Basin and Imperial Valley areas in southern California, and selected portions of the west side of San Joaquin Valley in central California. An analysis is also given on how an effective benefit-cost study of remote sensing in relation to California's water resources might best be made.

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.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

Application of Lidar remote sensing to the estimation of forest canopy and stand structure

NASA Astrophysics Data System (ADS)

Lefsky, Michael Andrew

A new remote sensing instrument, SLICER (Scanning Lidar Imager of Canopies by Echo Recovery), has been applied to the problem of remote sensing the canopy and stand structure of two groups of deciduous forests, Tulip Poplar-Oak stands in the vicinity of Annapolis, MD. and bottomland hardwood stands near Williamston, NC. The ability of the SLICER instrument to remotely sense the vertical distribution of canopy structure (Canopy Height Profile), bulk canopy transmittance, and several indices of canopy height has been successfully validated using twelve stands with coincident field and SLICER estimates of canopy structure. Principal components analysis has been applied to canopy height profiles from both field sites, and three significant factors were identified, each closely related to the amount of foliage in a recognizable layer of the forest, either understory, midstory, or overstory. The distribution of canopy structure to these layers is significantly correlated with the size and number of stems supporting them. The same layered structure was shown to apply to both field and SLICER remotely sensed canopy height profiles, and to apply to SLICER remotely sensed canopy profiles from both the bottomland hardwood stands in the coastal plain of North Carolina, and to mesic Tulip-Poplars stands in the upland coastal plain of Maryland. Linear regressions have demonstrated that canopy and stand structure are correlated to both a statistically significant and useful degree. Stand age and stem density is more highly correlated to stand height, while stand basal area and aboveground biomass are more closely related to a new measure of canopy structure, the quadratic mean canopy height. A geometric model of canopy structure has been shown to explain the differing relationships between canopy structure and stand basal area for stands of Eastern Deciduous Forest and Douglas Fir Forest.

Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing

NASA Astrophysics Data System (ADS)

Ya'acob, Norsuzila; Mohd Azize, Aziean Binti; Anis Mahmon, Nur; Laily Yusof, Azita; Farhana Azmi, Nor; Mustafa, Norfazira

2014-03-01

This paper presents the detection of Angsi and Berembun Reserve Forest change for years 1996 and 2013. Forest is an important part of our ecosystem. The main function is to absorb carbon oxide and produce oxygen in their cycle of photosynthesis to maintain a balance and healthy atmosphere. However, forest changes as time changes. Some changes are necessary as to give way for economic growth. Nevertheless, it is important to monitor forest change so that deforestation and development can be planned and the balance of ecosystem is still preserved. It is important because there are number of unfavorable effects of deforestation that include environmental and economic such as erosion of soil, loss of biodiversity and climate change. The forest change detection can be studied with reference of several satellite images using remote sensing application. Forest change detection is best done with remote sensing due to large and remote study area. The objective of this project is to detect forest change over time and to compare forest health indicated by Normalized Difference Vegetation Index (NDVI) using remote sensing and image processing. The forest under study shows depletion of forest area by 12% and 100% increment of deforestation activities. The NDVI value which is associated with the forest health also shows 13% of reduction.

[Remote sensing of atmospheric trace gas by airborne passive FTIR].

PubMed

Gao, Min-quang; Liu, Wen-qing; Zhang, Tian-shu; Liu, Jian-guo; Lu, Yi-huai; Wang, Ya-ping; Xu, Liang; Zhu, Jun; Chen, Jun

2006-12-01

The present article describes the details of aviatic measurement for remote sensing trace gases in atmosphere under various surface backgrounds with airborne passive FTIR. The passive down viewing and remote sensing technique used in the experiment is discussed. The method of acquiring atmospheric trace gases infrared characteristic spectra in complicated background and the algorithm of concentration retrieval are discussed. The concentrations of CO and N2O of boundary-layer atmosphere in experimental region below 1000 m are analyzed quantitatively. This measurement technique and the data analysis method, which does not require a previously measured background spectrum, allow fast and mobile remote detection and identification of atmosphere trace gas in large area, and also can be used for urgent monitoring of pollution accidental breakout.

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications

NASA Astrophysics Data System (ADS)

McCarthy, Matthew J.; Colna, Kaitlyn E.; El-Mezayen, Mahmoud M.; Laureano-Rosario, Abdiel E.; Méndez-Lázaro, Pablo; Otis, Daniel B.; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E.

2017-08-01

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.

Remote sensing: a tool for park planning and management

USGS Publications Warehouse

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

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

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications.

PubMed

McCarthy, Matthew J; Colna, Kaitlyn E; El-Mezayen, Mahmoud M; Laureano-Rosario, Abdiel E; Méndez-Lázaro, Pablo; Otis, Daniel B; Toro-Farmer, Gerardo; Vega-Rodriguez, Maria; Muller-Karger, Frank E

2017-08-01

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.

Remote sensing in agriculture. [using Earth Resources Technology Satellite photography

NASA Technical Reports Server (NTRS)

Downs, S. W., Jr.

1974-01-01

Some examples are presented of the use of remote sensing in cultivated crops, forestry, and range management. Areas of concern include: the determination of crop areas and types, prediction of yield, and detection of disease; the determination of forest areas and types, timber volume estimation, detection of insect and disease attack, and forest fires; and the determination of range conditions and inventory, and livestock inventory. Articles in the literature are summarized and specific examples of work being performed at the Marshall Space Flight Center are given. Primarily, aerial photographs and photo-like ERTS images are considered.

The use of remote sensing imagery for environmental land use and flood hazard mapping

NASA Technical Reports Server (NTRS)

Mouat, D. A.; Miller, D. A.; Foster, K. E.

1976-01-01

Flood hazard maps have been constructed for Graham, Yuma, and Yavapai Counties in Arizona using remote sensing techniques. Watershed maps of priority areas were selected on the basis of their interest to the county planning staff and represented areas of imminent or ongoing development and those known to be subject to inundation by storm runoff. Landsat color infrared imagery at scales of 1:1,000,000, 1:500,000, and 1:250,000 was used together with high-altitude aerial photography at scales of 1:120,000 and 1:60,000 to determine drainage patterns and erosional features, soil type, and the extent and type of ground cover. The satellite imagery was used in the form of 70 mm chips for enhancement in a color additive viewer and in all available enlargement modes. Field checking served as the main backup to the interpretations. Areas with high susceptibility to flooding were determined with a high level of confidence from the remotely sensed imagery.

A Terminal Area Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Serke, David J.

2014-01-01

NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

NASA Astrophysics Data System (ADS)

You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

2017-12-01

Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key water environmental parameters and further improved the inversion model. The results indicate that our proposed water environment inversion model can be a good inversion for alpine water environmental parameters, and can improve the monitoring and warning ability for the alpine river water environment in the future.

Remote sensing application to regional activities

NASA Technical Reports Server (NTRS)

Shahrokhi, F.; Jones, N. L.; Sharber, L. A.

1976-01-01

Two agencies within the State of Tennessee were identified whereby the transfer of aerospace technology, namely remote sensing, could be applied to their stated problem areas. Their stated problem areas are wetland and land classification and strip mining studies. In both studies, LANDSAT data was analyzed with the UTSI video-input analog/digital automatic analysis and classification facility. In the West Tennessee area three land-use classifications could be distinguished; cropland, wetland, and forest. In the East Tennessee study area, measurements were submitted to statistical tests which verified the significant differences due to natural terrain, stripped areas, various stages of reclamation, water, etc. Classifications for both studies were output in the form of maps of symbols and varying shades of gray.

Estimation of small reservoir storage capacities in the São Francisco, Limpopo, Bandama and Volta river basins using remotely sensed surface areas

NASA Astrophysics Data System (ADS)

Rodrigues, Lineu; Senzanje, Aidan; Cecchi, Philippe; Liebe, Jens

2010-05-01

People living in areas with highly variable rainfall, experience droughts and floods and often have insecure livelihoods. Small multi-purpose reservoirs (SR) are a widely used form of infrastructures to provide people in such areas with water during the dry season, e.g. in the basins of São Francisco, Brazil, Limpopo, Zimbabwe, Bandama, Ivory Coast and Volta, Ghana. In these areas, the available natural flow in the streams is sometimes less than the flow required for water supply or irrigation, however water can be stored in times of surplus, for example, from a wet season to a dry season. Efficient water management and sound reservoir planning are hindered by the lack of information about the functioning of these reservoirs. Reservoirs in these regions were constructed in a series of projects funded by different agencies, at different times, with little or no coordination among the implementing partners. Poor record keeping and the lack of appropriate institutional support result in deficiencies of information on the capacity, operation, and maintenance of these structures. Estimating the storage capacity of dams is essential to the responsible management of water diversion. Most of SR in these basins have never been evaluated, possibly because the tools currently used for such measurement are labor-intensive, costly and time-consuming. The objective of this research was to develop methodology to estimate small reservoir capacities as a function of their remotely sensed surface areas in the São Francisco, Limpopo, Bandama and Volta basins, as a way to contribute to improve the water resource management in those catchments. Remote sensing was used to identify, localize and characterize small reservoirs. The surface area of each was calculated from satellite images. A sub-set of reservoirs was selected. For each reservoir in the sub-set, the surface area was estimated from field surveys, and storage capacity was estimated using information on reservoir surface area, depth and shape. Depth was measured using a stadia rod or a manual echosounder. For reservoirs in the sub-set, estimated surface area was used as an input into the triangulated irregular network model. With the surface area and depth, measured volume was calculated. Comparisons were made between estimates of surface area from field surveys and estimates of surface area from remote sensing. A linear regression analysis was carried out to establish the relationship between surface area and storage capacities. Within geomorphologically homogenous regions, one may expect a good correlation between the surface area, which may be determined through satellite observations, and the stored volume. Such a relation depends on the general shape of the slopes (convex, through straight, to concave). The power relationships between remotely sensed surface areas (m^2) and storage capacities of reservoirs (m^3) obtained were - Limpopo basin (Lower Mzingwane sub-catchment): Volume = 0.023083 x Area^1.3272 (R2 = 95%); Bandama basin (North of the basin in Ivory Coast): Volume = 0.00405 x Area^1.4953 (R2 = 88.9%); Volta basin (Upper East region of the Volta Basin in Ghana): Volume = 0.00857 × Area^1.43 (R2 = 97.5%); São Francisco basin (Preto river sub-catchment): Volume = 0.2643 x Area^1.1632 (R2 = 92.1%). Remote sensing was found to be a suitable means to detect small reservoirs and accurately measure their surface areas. The general relationship between measured reservoir volumes and their remotely sensed surface areas showed good accuracy for all four basins. Combining such relationships with periodical satellite-based reservoir area measurements may allow hydrologists and planners to have clear picture of water resource system in the Basins, especially in ungauged sub-basins.

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

DOE PAGES

Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly; ...

2017-01-07

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less

Study on paddy rice yield estimation based on multisource data and the Grey system theory

NASA Astrophysics Data System (ADS)

Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua

2009-10-01

The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.

Reconstruction of time-varying tidal flat topography using optical remote sensing imageries

NASA Astrophysics Data System (ADS)

Tseng, Kuo-Hsin; Kuo, Chung-Yen; Lin, Tang-Huang; Huang, Zhi-Cheng; Lin, Yu-Ching; Liao, Wen-Hung; Chen, Chi-Farn

2017-09-01

Tidal flats (TFs) occupy approximately 7% of the total coastal shelf areas worldwide. However, TFs are unavailable in most global digital elevation models (DEMs) due to water-impermeable nature of existing remote sensing approaches (e.g., radar used for WorldDEM™ and Shuttle Radar Topography Mission DEM and optical stereo-pairs used for ASTER Global Digital Elevation Map Version 2). However, this problem can be circumvented using remote sensing imageries to observe land exposure at different tidal heights during each revisit. This work exploits Landsat-4/-5/-7/-8 Thematic Mapper (TM)/Enhanced TM Plus/Operational Land Imager imageries to reconstruct topography of a TF, namely, Hsiang-Shan Wetland in Taiwan, to unveil its formation and temporal changes since the 1980s. We first classify water areas by applying modified normalized difference water index to each Landsat image and normalize chances of water exposure to create an inundation probability map. This map is then scaled by tidal amplitudes extracted from DTU10 tide model to convert the probabilities into actual elevations. After building DEM at intertidal zone, a water level-area curve is established, and accuracy of DEM is validated by sea level (SL) at the timing of each Landsat snapshot. A 22-year (1992-2013) dataset composed of 227 Landsat scenes are analyzed and compared with tide gauge data. Root-mean-square differences of SL reaches 48 cm with a correlation coefficient of 0.93, indicating that the present technique is useful for constructing accurate coastal DEMs, and that products can be utilized for estimating instant SL. This study shows the possibility of exploring evolution of intertidal zones using an archive of optical remote sensing imageries. The technique developed in the present study potentially helps in quantifying SL from the start of optical remote sensing era.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

a Hyperspectral Based Method to Detect Cannabis Plantation in Inaccessible Areas

NASA Astrophysics Data System (ADS)

Houmi, M.; Mohamadi, B.; Balz, T.

2018-04-01

The increase in drug use worldwide has led to sophisticated illegal planting methods. Most countries depend on helicopters, and local knowledge to identify such illegal plantations. However, remote sensing techniques can provide special advantages for monitoring the extent of illegal drug production. This paper sought to assess the ability of the Satellite remote sensing to detect Cannabis plantations. This was achieved in two stages: 1- Preprocessing of Hyperspectral data EO-1, and testing the capability to collect the spectral signature of Cannabis in different sites of the study area (Morocco) from well-known Cannabis plantation fields. 2- Applying the method of Spectral Angle Mapper (SAM) based on a specific angle threshold on Hyperion data EO-1 in well-known Cannabis plantation sites, and other sites with negative Cannabis plantation in another study area (Algeria), to avoid any false Cannabis detection using these spectra. This study emphasizes the benefits of using hyperspectral remote sensing data as an effective detection tool for illegal Cannabis plantation in inaccessible areas based on SAM classification method with a maximum angle (radians) less than 0.03.

NIST activities in support of space-based radiometric remote sensing

NASA Astrophysics Data System (ADS)

Rice, Joseph P.; Johnson, B. Carol

2001-06-01

We provide an historical overview of NIST research and development in radiometry for space-based remote sensing. The applications in this field can be generally divided into two areas: environmental and defense. In the environmental remote sensing area, NIST has had programs with agencies such as the National Aeronautical and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) to verify and improve traceability of the radiometric calibration of sensors that fly on board Earth-observing satellites. These produce data used in climate models and weather prediction. Over the years, the scope of activities has expanded from existing routine calibration services for artifacts such as lamps, diffusers, and filters, to development and off-site deployment of portable radiometers for radiance- and irradiance-scale intercomparisons. In the defense remote sensing area, NIST has had programs with agencies such as the Department of Defense (DOD) for support of calibration of small, low-level infrared sources in a low infrared background. These are used by the aerospace industry to simulate ballistic missiles in a cold space background. Activities have evolved from calibration of point-source cryogenic blackbodies at NIST to measurement of irradiance in off-site calibration chambers by a portable vacuum/cryogenic radiometer. Both areas of application required measurements on the cutting edge of what was technically feasible, thus compelling NIST to develop a state-of-the-art radiometric measurement infrastructure to meet the needs. This infrastructure has led to improved dissemination of the NIST spectroradiometric quantities.

Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico

NASA Technical Reports Server (NTRS)

Beck, L. R.; Rodriguez, M. H.; Dister, S. W.; Rodriguez, A. D.; Washino, R. K.; Roberts, D. R.; Spanner, M. A.

1997-01-01

A blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.

A survey for the use of remote sensing in the Chesapeake Bay region

NASA Technical Reports Server (NTRS)

Ulanowicz, R. E.

1974-01-01

Environmental problem areas concerning the Chesapeake Bay region are reviewed along with ongoing remote sensing programs pertaining to these problems, and recommendations are presented to help fill lacunae in present research and to utilize the remote sensing capabilities of NASA to their fullest. A list of interested organizations and individuals is presented for each category. The development of technologies to monitor dissolved nutrients in bay waters, the initiation of a census of the disappearing rooted acquatic plants in the littoral zones, and the mapping of natural building constraints in the growth regions of the states of Maryland and Virginia are among the recommendations presented.

Irrigated lands: Monitoring by remote sensing

NASA Technical Reports Server (NTRS)

Epiphanio, J. C. N.; Vitorelli, I.

1983-01-01

The use of remote sensing for irrigated areas, especially in the region of Guaira, Brazil (state of Sao Paulo), is examined. Major principles of utilizing LANDSAT data for the detection and mapping of irrigated lands are discussed. In addition, initial results obtained by computer processing of digital data, use of MSS (Multispectral Scanner System)/LANDSAT products, and the availability of new remote sensing products are highlighted. Future activities include the launching of the TM (Thematic Mapper)/LANDSAT 4 with 30 meters of resolution and SPOT (Systeme Probatorie d'Observation de la Terre) with 10 to 20 meters of resolution, to be operational in 1984 and 1986 respectively.

Use of remote sensing for land use policy formulation. [in Michigan

NASA Technical Reports Server (NTRS)

Boylan, M.

1977-01-01

The use of remotely sensed data for eliminating abuses and mismanagement of land and water resources in Michigan is discussed. Applications discussed include inventory of mosquito breeding sites; analysis of biomass in old field ecosystems used for wastewater recycling; areas for agricultural use; and preservation of the Grand Mere Dune environment. Services to users are described and contact activities reported.

VARIABILITY IN NET PRIMARY PRODUCTION AND CARBON STORAGE IN BIOMASS ACROSS OREGON FORESTS - AN ASSESSMENT INTEGRATING DATA FROM FOREST INVENTORIES, INTENSIVE SITES, AND REMOTE SENSING. (R828309)

EPA Science Inventory

We used a combination of data from USDA Forest Service inventories, intensive
chronosequences, extensive sites, and satellite remote sensing, to estimate biomass
and net primary production (NPP) for the forested region of western Oregon. The
study area was divided int...

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.

End-to-end remote sensing at the Science and Technology Laboratory of John C. Stennis Space Center

NASA Technical Reports Server (NTRS)

Kelly, Patrick; Rickman, Douglas; Smith, Eric

1991-01-01

The Science and Technology Laboratory (STL) of Stennis Space Center (SSC) was developing an expertise in remote sensing for more than a decade. Capabilities at SSC/STL include all major areas of the field. STL includes the Sensor Development Laboratory (SDL), Image Processing Center, a Learjet 23 flight platform, and on-staff scientific investigators.

Tree health mapping with multispectral remote sensing data at UC Davis, California

Treesearch

Q. Xiao; E.G. McPherson

2005-01-01

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Tradi­tionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health...

Data compression in remote sensing applications

NASA Technical Reports Server (NTRS)

Sayood, Khalid

1992-01-01

A survey of current data compression techniques which are being used to reduce the amount of data in remote sensing applications is provided. The survey aspect is far from complete, reflecting the substantial activity in this area. The purpose of the survey is more to exemplify the different approaches being taken rather than to provide an exhaustive list of the various proposed approaches.

Pixel by pixel: the evolving landscapes of remote sensing.

Treesearch

Sally Duncan

1999-01-01

This issue of "Science Findings" focuses on remote sensing research and how it can be used to assess a landscape. The work of PNW Research Station scientists Tom Spies and Warren Cohen and their use of satellite technology in developing the coastal landscape analysis and modeling study (CLAMS) is featured. The CLAMS study area includes more than 5 million...

Toward a national early warning system for forest disturbances using remotely sensed canopy phenology

Treesearch

William W. Hargrove; Joseph P. Spruce; Gerald E. Gasser; Forrest M. Hoffman

2009-01-01

Imagine a national system with the ability to quickly identify forested areas under attack from insects or disease. Such an early warning system might minimize surprises such as the explosion of caterpillars referred to in the quotation above. Moderate resolution (ca. 500m) remote sensing repeated at frequent (ca. weekly) intervals could power such a monitoring system...

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.

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

NASA Astrophysics Data System (ADS)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

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

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Collection and analysis of remotely sensed data from the Rhode River Estuary Watershed. [ecological parameters of Chesapeake Bay

NASA Technical Reports Server (NTRS)

Jenkins, D. W.

1972-01-01

NASA chose the watershed of Rhode River, a small sub-estuary of the Bay, as a representative test area for intensive studies of remote sensing, the results of which could be extrapolated to other estuarine watersheds around the Bay. A broad program of ecological research was already underway within the watershed, conducted by the Smithsonian Institution's Chesapeake Bay Center for Environmental Studies (CBCES) and cooperating universities. This research program offered a unique opportunity to explore potential applications for remote sensing techniques. This led to a joint NASA-CBCES project with two basic objectives: to evaluate remote sensing data for the interpretation of ecological parameters, and to provide essential data for ongoing research at the CBCES. A third objective, dependent upon realization of the first two, was to extrapolate photointerpretive expertise gained at the Rhode River watershed to other portions of the Chesapeake Bay.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Early Warning of Food Security Crises in Urban Areas: The Case of Harare, Zimbabwe, 2007

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Funk, Christopher C.

2008-01-01

In 2007, the citizens of Harare, Zimbabwe began experiencing an intense food security crisis. The crisis, due to a complex mix of poor government policies, high inflation rates and production decline due to drought, resulted in a massive increase in the number of food insecure people in Harare. The international humanitarian aid response to this crisis was largely successful due to the early agreement among donors and humanitarian aid officials as to the size and nature of the problem. Remote sensing enabled an early and decisive movement of resources greatly assisting the delivery of food aid in a timely manner. Remote sensing data gave a clear and compelling assessment of significant crop production shortfalls, and provided donors of humanitarian assistance a single number around which they could come to agreement. This use of remote sensing data typifies how remote sensing may be used in early warning systems in Africa.

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 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.

The detection and mapping of oil on a marshy area by a remote luminescent sensor

USGS Publications Warehouse

McFarlane, C.; Watson, R.D.

2005-01-01

Airborne remote sensing can be a cost-effective method for monitoring pollutants in large areas such as occur in oil spills. An opportunity to test a particular method arose when a well ruptured and for 23 days spewed a 90-meter fountain of oil into the air, dispersing the oil over a wide area. The method tested was an airborne luminescence detector with a Fraunhofer Line Discriminator (FLD) which was flown over the affected area 41 days after the well was capped to obtain a map or the deposition pattern. To calibrate the system, samples of Spartina (wire grass) and Phragmites (common reed) were collected from the contaminated area and the oil residues were eluted in cyclohexane and quantitatively analyzed in a fluorescence photometer. Good correlation was observed between the remote sensor (FLD) and the laboratory analysis. Isopleths defining the deposition pattern of oil were drawn from the remote sensing information. A discussion will be presented on the feasibility of using this instrument for similar contamination incidents for cleanup and damage assessment.

The application of unmanned aerial vehicle remote sensing for monitoring secondary geological disasters after earthquakes

NASA Astrophysics Data System (ADS)

Lei, Tianjie; Zhang, Yazhen; Wang, Xingyong; Fu, Jun'e.; Li, Lin; Pang, Zhiguo; Zhang, Xiaolei; Kan, Guangyuan

2017-07-01

Remote sensing system fitted on Unmanned Aerial Vehicle (UAV) can obtain clear images and high-resolution aerial photographs. It has advantages of strong real-time, flexibility and convenience, free from influence of external environment, low cost, low-flying under clouds and ability to work full-time. When an earthquake happened, it could go deep into the places safely and reliably which human staff can hardly approach, such as secondary geological disasters hit areas. The system can be timely precise in response to secondary geological disasters monitoring by a way of obtaining first-hand information as quickly as possible, producing a unique emergency response capacity to provide a scientific basis for overall decision-making processes. It can greatly enhance the capability of on-site disaster emergency working team in data collection and transmission. The great advantages of UAV remote sensing system played an irreplaceable role in monitoring secondary geological disaster dynamics and influences. Taking the landslides and barrier lakes for example, the paper explored the basic application and process of UAV remote sensing in the disaster emergency relief. UAV high-resolution remote sensing images had been exploited to estimate the situation of disaster-hit areas and monitor secondary geological disasters rapidly, systematically and continuously. Furthermore, a rapid quantitative assessment on the distribution and size of landslides and barrier lakes was carried out. Monitoring results could support relevant government departments and rescue teams, providing detailed and reliable scientific evidence for disaster relief and decision-making.

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 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

Environmental Remote Sensing for Natural Resources Management: A Workshop in Collaboration with Faculdade de Agronomia e Engenharia Florestal, Universidade Eduardo Mondlane

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Fatoyinbo, T. E.; Ribeiro, N. S.; Shugart, H. H.; Therrell, M. D.; Vaz, K. T.; von Schill, L.

2006-12-01

A workshop titled: Environmental Remote Sensing for Natural Resources Management was held from June 12 23, 2006 at Eduardo Mondlane University in Maputo Mozambique. The workshop was initiated through an invitation and pre-course evaluation form to interested NGOs, universities, and government organizations. The purpose of the workshop was to provide training to interested professionals, graduate students, faculty and researchers at Mozambican institutions on the research and practical uses of remote sensing for natural resource management. The course had 24 participants who were predominantly professionals in remote sensing and GIS from various NGOs, governmental and academic institutions in Mozambique. The course taught remote sensing from an ecological perspective, specifically the course focused on the application of new remote sensing technology [the Shuttle Radar Topography Mission (SRTM) C-band radar data] to carbon accounting research in Miombo woodlands and Mangrove forests. The 2-week course was free to participants and consisted of lectures, laboratories, and a field trip to the mangrove forests of Inhaca Island, Maputo. The field trip consisted of training in the use of forest inventory techniques in support of remote sensing studies. Specifically, the field workshop centered on use of Global Positioning Systems (GPS) and collection of forest inventory data on tree height, structure [leaf area index (LAI)], and productivity. Productivity studies were enhanced with the teaching of introductory dendrochronology including sample collection of tree rings from four different mangrove species. Students were provided with all course materials including a DVD that contained satellite data (e.g., Landsat and SRTM imagery), ancillary data, lectures, exercises, and remote sensing publications used in the course including a CD from the Environmental Protection Agency's Environmental Photographic Interpretation Center's (EPA-EPIC) program to teach remote sensing and data CDs from NASA's SAFARI 2000 field campaign. Nineteen participants evaluated the effectiveness of the course in regards to the course lectures, instructors, and the field trip. Future workshops should focus more on the individual projects that students are engaged with in their jobs, replace the laboratories computers with workstations geared towards computer intensive image processing software, and the purchase of field remote sensing instrumentation for practical exercises.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A patch-based convolutional neural network for remote sensing image classification.

PubMed

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

2014-12-01

Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown.

Use of remote sensing in agriculture

NASA Technical Reports Server (NTRS)

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

1975-01-01

The remote sensing studies of (a) cultivated peanut areas in Southeastern Virginia; (b) studies at the Virginia Truck and Ornamentals Research Station near Painter, Virginia, the Eastern Virginia Research Station near Warsaw, Virginia, the Tidewater Research and Continuing Education Center near Suffolk, Virginia, and the Southern Piedmont Research and Continuing Education Center Blackstone, Virginia; and (c) land use classification studies at Virginia Beach, Virginia are presented. The practical feasibility of using false color infrared imagery to detect and determine the areal extent of peanut disease infestation of Cylindrocladium black rot and Sclerotinia blight is demonstrated. These diseases pose a severe hazard to this major agricultural food commodity. The value of remote sensing technology in terrain analyses and land use classification of diverse land areas is also investigated. Continued refinement of spectral signatures of major agronomic crops and documentation of pertinent environmental variables have provided a data base for the generation of an agricultural-environmental prediction model.

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.

Earth Survey Applications Division. [a bibliography

NASA Technical Reports Server (NTRS)

Carpenter, L. (Editor)

1981-01-01

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

Airborne Remote Sensing (ARS) for Agricultural Research and Commercialization Applications

NASA Technical Reports Server (NTRS)

Narayanan, Ram; Bowen, Brent D.; Nickerson, Jocelyn S.

2002-01-01

Tremendous advances in remote sensing technology and computing power over the last few decades are now providing scientists with the opportunity to investigate, measure, and model environmental patterns and processes with increasing confidence. Such advances are being pursued by the Nebraska Remote Sensing Facility, which consists of approximately 30 faculty members and is very competitive with other institutions in the depth of the work that is accomplished. The development of this facility targeted at applications, commercialization, and education programs in the area of precision agriculture provides a unique opportunity. This critical area is within the scope of NASA goals and objectives of NASA s Applications, Technology Transfer, Commercialization, and Education Division and the Earth Science Enterprise. This innovative integration of Aerospace (Aeronautics) Technology Enterprise applications with other NASA enterprises serves as a model of cross-enterprise transfer of science with specific commercial applications.

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

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

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

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.

[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.

Irrigated rice area estimation using remote sensing techniques: Project's proposal and preliminary results. [Rio Grande do Sul, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Deassuncao, G. V.; Moreira, M. A.; Novaes, R. A.

1984-01-01

The development of a methodology for annual estimates of irrigated rice crop in the State of Rio Grande do Sul, Brazil, using remote sensing techniques is proposed. The project involves interpretation, digital analysis, and sampling techniques of LANDSAT imagery. Results are discussed from a preliminary phase for identifying and evaluating irrigated rice crop areas in four counties of the State, for the crop year 1982/1983. This first phase involved just visual interpretation techniques of MSS/LANDSAT images.

Applications of TIMS data in agricultural areas and related atmospheric considerations

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Ochoa, M. C.

1986-01-01

While much of traditional remote sensing in agricultural research was limited to the visible and reflective infrared, advances in thermal infrared remote sensing technology are adding a dimension to digital image analysis of agricultural areas. The Thermal Infrared Multispectral Scanner (TIMS) an airborne sensor having six bands over the nominal 8.2 to 12.2 m range, offers the ability to calculate land surface emissivities unlike most previous singular broadband sensors. Preliminary findings on the utility of the TIMS for several agricultural applications and related atmospheric considerations are discussed.

Remotely-Sensed Mapping of Irrigation Area in the Chu-Talas River Basin in Central Asia and Application to Compliance Monitoring of Transboundary Water Sharing

NASA Astrophysics Data System (ADS)

Ragettli, S.; Siegfried, T.; Herberz, T.

2017-12-01

In the Central Asian Chu-Talas River Basin, farmers depend on freshwater from international rivers to irrigate their fields during the summer growing season. While the allocation percentages of water sharing between up- and downstream are defined for both rivers, marked interannual supply variability plus inadequate monitoring renders the compliance with these quotas difficult. In such circumstances, data on irrigated area obtained by remote sensing can be used to map the extent of irrigation in terms of its area on at national and subnational scales. Due to its transparency on how the data was obtained (freely available satellite data) and processed, this objective measure could potentially be used as a data product for confidence building and for compliance monitoring. This study assesses the extent and location of irrigated areas over the period 2000 - 2016 in the basins by using state-of-the-art remote sensing technology. Using a random forest classifier, an automated irrigated cropland mapping algorithm was implemented in Google Earth Engine using Landsat 7 data. First, a training set was established through visual interpretation (irrigated and non-irrigated classes for the year 2015) and the classifier then trained. The classier was then applied on a series of seasonal greenest pixels image mosaics from 2000 to 2016. A four-stepped accuracy assessment confirmed that the classifier yielded robust, reliable and reproducible results. Outcomes indicate that irrigated areas in the Kyrgyz side of the Talas Basin approximately doubled by 2016 since 2000 while the irrigated area in the Kazakh part of the basin did not significantly change over the 17 year time period. In the Chu River Basin, total irrigated area tripled since 2000. Comparison with officially reported statistics shows differences and points to reporting issues in both countries. We conclude that remote sensing of irrigated areas in arid and semi-arid regions in combination with cloud computing offers excellent opportunities for monitoring activities. Remotely-sensed cropland products as derived for this study provide the required data for assessing the compliance of the interstate water use agreements for the Chu and Talas Rivers and can thus help to conciliate future conflicts that might be based on the absence of reliable data.

The use of satellite data for monitoring temporal and spatial patterns of fire: a comprehensive review

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2009-04-01

Remotely sensed (RS) data can fruitfully support both research activities and operative monitoring of fire at different temporal and spatial scales with a synoptic view and cost effective technologies. "The contribution of remote sensing (RS) to forest fires may be grouped in three categories, according to the three phases of fire management: (i) risk estimation (before fire), (ii) detection (during fire) and (iii) assessment (after fire)" Chuvieco (2006). Relating each phase, wide research activities have been conducted over the years. (i) Risk estimation (before fire) has been mainly based on the use of RS data for (i) monitoring vegetation stress and assessing variations in vegetation moisture content, (ii) fuel type mapping, at different temporal and spatial scales from global, regional down to a local scale (using AVHRR, MODIS, TM, ASTER, Quickbird images and airborne hyperspectral and LIDAR data). Danger estimation has been mainly based on the use of AVHRR (onborad NOAA), MODIS (onboard TERRA and AQUA), VEGETATION (onboard SPOT) due to the technical characteristics (i.e. spectral, spatial and temporal resolution). Nevertheless microwave data have been also used for vegetation monitoring. (ii) Detection: identification of active fires, estimation of fire radiative energy and fire emission. AVHRR was one of the first satellite sensors used for setting up fire detection algorithms. The availbility of MODIS allowed us to obtain global fire products free downloaded from NASA web site. Sensors onboard geostationary satellite platforms, such as GOES, SEVIRI, have been used for fire detection, to obtain a high temporal resolution (at around 15 minutes) monitoring of active fires. (iii) Post fire damage assessment includes: burnt area mapping, fire emission, fire severity, vegetation recovery, fire resilience estimation, and, more recently, fire regime characterization. Chuvieco E. L. Giglio, C. Justice, 2008 Global charactrerization of fire activity: toward defining fire regimes from Earth observation data Global Change Biology vo. 14. doi: 10.1111/j.1365-2486.2008.01585.x 1-15, Chuvieco E., P. Englefield, Alexander P. Trishchenko, Yi Luo Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2381-2396 Chuvieco Emilio 2006, Remote Sensing of Forest Fires: Current limitations and future prospects in Observing Land from Space: Science, Customers and Technology, Advances in Global Change Research Vol. 4 pp 47-51 De Santis A., E. Chuvieco Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models, Remote Sensing of Environment, Volume 108, Issue 4, 29 June 2007, Pages 422-435. De Santis A., E. Chuvieco, Patrick J. Vaughan, Short-term assessment of burn severity using the inversion of PROSPECT and GeoSail models, Remote Sensing of Environment, Volume 113, Issue 1, 15 January 2009, Pages 126-136 García M., E. Chuvieco, H. Nieto, I. Aguado Combining AVHRR and meteorological data for estimating live fuel moisture content Remote Sensing of Environment, Volume 112, Issue 9, 15 September 2008, Pages 3618-3627 Ichoku C., L. Giglio, M. J. Wooster, L. A. Remer Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2950-2962. Lasaponara R. and Lanorte, On the capability of satellite VHR QuickBird data for fuel type characterization in fragmented landscape Ecological Modelling Volume 204, Issues 1-2, 24 May 2007, Pages 79-84 Lasaponara R., A. Lanorte, S. Pignatti,2006 Multiscale fuel type mapping in fragmented ecosystems: preliminary results from Hyperspectral MIVIS and Multispectral Landsat TM data, Int. J. Remote Sens., vol. 27 (3) pp. 587-593. Lasaponara R., V. Cuomo, M. F. Macchiato, and T. Simoniello, 2003 .A self-adaptive algorithm based on AVHRR multitemporal data analysis for small active fire detection.n International Journal of Remote Sensing, vol. 24, No 8, 1723-1749. Minchella A., F. Del Frate, F. Capogna, S. Anselmi, F. Manes Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas Remote Sensing of Environment, In Press Næsset E., T. Gobakken Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 3079-3090 Peterson S. H, Dar A. Roberts, Philip E. Dennison Mapping live fuel moisture with MODIS data: A multiple regression approach, Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4272-4284. Schroeder Wilfrid, Elaine Prins, Louis Giglio, Ivan Csiszar, Christopher Schmidt, Jeffrey Morisette, Douglas Morton Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2711-2726 Shi J., T. Jackson, J. Tao, J. Du, R. Bindlish, L. Lu, K.S. Chen Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4285-4300 Tansey, K., Grégoire, J-M., Defourny, P., Leigh, R., Pekel, J-F., van Bogaert, E. and Bartholomé, E., 2008 A New, Global, Multi-Annual (2000-2007) Burnt Area Product at 1 km Resolution and Daily Intervals Geophysical Research Letters, VOL. 35, L01401, doi:10.1029/2007GL031567, 2008. Telesca L. and Lasaponara R., 2006; "Pre-and Post- fire Behaviural trends revealed in satellite NDVI time series" Geophysical Research Letters,., 33, L14401, doi:10.1029/2006GL026630 Telesca L. and Lasaponara R 2005 Discriminating Dynamical Patterns in Burned and Unburned Vegetational Covers by Using SPOT-VGT NDVI Data. Geophysical Research Letters,, 32, L21401, doi:10.1029/2005GL024391. Telesca L. and Lasaponara R. Investigating fire-induced behavioural trends in vegetation covers , Communications in Nonlinear Science and Numerical Simulation, 13, 2018-2023, 2008 Telesca L., A. Lanorte and R. Lasaponara, 2007. Investigating dynamical trends in burned and unburned vegetation covers by using SPOT-VGT NDVI data. Journal of Geophysics and Engineering, Vol. 4, pp. 128-138, 2007 Telesca L., R. Lasaponara, and A. Lanorte, Intra-annual dynamical persistent mechanisms in Mediterranean ecosystems revealed SPOT-VEGETATION Time Series, Ecological Complexity, 5, 151-156, 2008 Verbesselt, J., Somers, B., Lhermitte, S., Jonckheere, I., van Aardt, J., and Coppin, P. (2007) Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Remote Sensing of Environment 108: 357-368. Zhang X., S. Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897 Zhang X., Shobha Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897

Multi-Source Image Analysis.

DTIC Science & Technology

1979-12-01

vegetation shows on the imagery but emphasis has been placed on the detection of wooded and scrub areas and the differentiation between deciduous and...S. A., 1974b, Phenology and remote sensing, phenology and seasonality modeling: in Helmut Lieth, H. (ed.), Ecological Studies-Analysis and Synthesis...Remote Sensing of Ecology , University of d-eorgia Press, Athens, Georgia, p. 63-94. Phillipson, W. R. and T. Liang, 1975, Airphoto analysis in the

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

Treesearch

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

2015-01-01

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

Re-sampling remotely sensed data to improve national and regional mapping of forest conditions with confidential field data

Treesearch

Raymond L. Czaplewski

2005-01-01

Forest Service Research and Development (R&D) and State and Private Forestry Deputy Areas, in partnership with the National Forest System Remote Sensing Applications Center (RSAC), built a 250-m resolution (6.25-ha pixel) dataset for the entire USA. It assembles multi-seasonal hyperspectral MODIS data and derivatives, Landsat derivatives (i.e., summary statistics...

A survey of automated remote sensing for agriculture

NASA Technical Reports Server (NTRS)

Hall, F. G.; Macdonald, R. B.

1983-01-01

The state-of-the-art of the technology available to make remote sensing crop production estimates is reviewed with reference to several past and present research projects. In particular, attention is given to Landsat data acquisition, registration and preprocessing, data transformation, data modeling, proportion estimation, and labeling. Development stage models and crop condition models are briefly characterized, and areas where further research is needed are identified.

Remote sensing of the seasonal variation of coniferous forest structure and function

NASA Technical Reports Server (NTRS)

Spanner, Michael; Waring, Richard

1991-01-01

One of the objectives of the Oregon Transect Ecosystem Research (OTTER) project is the remotely sensed determination of the seasonal variation of leaf area index (LAI) and absorbed photosynthetically active radiation (APAR). These measurements are required for input into a forest ecosystem model which predicts net primary production evapotranspiration, and photosynthesis of coniferous forests. Details of the study are given.

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.

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

PubMed

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

2018-02-15

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

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

In situ ozone data for evaluation of the laser absorption spectrometer ozone remote sensor: 1979 southeastern Virginia urban plume study summer field program

NASA Technical Reports Server (NTRS)

Gregory, G. L.; Mcdougal, D. S.; Mathis, J. J., Jr.

1980-01-01

Ozone data from the 1979 Southeastern Virginia Urban Study (SEV-UPS) field program are presented. The SEV-UPS was conducted for evaluation of an ozone remote sensor, the Laser Absorption Spectrometer. During the measurement program, remote-sensor evaluation was in two areas; (1) determination of the remote sensor's accuracy, repeatability, and operational characteristics, and (2) demonstration of the application of remotely sensed ozone data in air-quality studies. Data from six experiments designed to provide in situ ozone data for evaluation of the sensor in area 1, above, are presented. Experiments consisted of overflights of a test area with the remote sensor aircraft while in situ measurements with a second aircraft and selected surface stations provided correlative ozone data within the viewing area of the remote sensor.

Active microwave users working group program planning

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Bare, J.; Brown, W. E., Jr.; Childs, L. F.; Dellwig, L. F.; Heighway, J. E.; Joosten, R.; Lewis, A. J.; Linlor, W.; Lundien, J. R.

1978-01-01

A detailed programmatic and technical development plan for active microwave technology was examined in each of four user activities: (1) vegetation; (2) water resources and geologic applications, and (4) oceanographic applications. Major application areas were identified, and the impact of each application area in terms of social and economic gains were evaluated. The present state of knowledge of the applicability of active microwave remote sensing to each application area was summarized and its role relative to other remote sensing devices was examined. The analysis and data acquisition techniques needed to resolve the effects of interference factors were reviewed to establish an operational capability in each application area. Flow charts of accomplished and required activities in each application area that lead to operational capability were structured.

Progress in the Development of Practical Remote Detection of Icing Conditions

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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 image sea ice monitoring method in Bohai Bay based on C4.5 decision tree algorithm

NASA Astrophysics Data System (ADS)

Ye, Wei; Song, Wei

2018-02-01

In The Paper, the remote sensing monitoring of sea ice problem was turned into a classification problem in data mining. Based on the statistic of the related band data of HJ1B remote sensing images, the main bands of HJ1B images related with the reflectance of seawater and sea ice were found. On the basis, the decision tree rules for sea ice monitoring were constructed by the related bands found above, and then the rules were applied to Liaodong Bay area seriously covered by sea ice for sea ice monitoring. The result proved that the method is effective.

National Satellite Land Remote Sensing Data Archive

USGS Publications Warehouse

Faundeen, John L.; Longhenry, Ryan

2018-06-13

The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

Matrix of educational and training materials in remote sensing

NASA Technical Reports Server (NTRS)

Lindenlaub, J. C.; Lube, B. M.

1976-01-01

Remote sensing educational and training materials developed by LARS have been organized in a matrix format. Each row in the matrix represents a subject area in remote sensing and the columns represent different types of instructional materials. This format has proved to be useful for displaying in a concise manner the subject matter content, prerequisite requirements and technical depth of each instructional module in the matrix. A general description of the matrix is followed by three examples designed to illustrate how the matrix can be used to synthesize training programs tailored to meet the needs of individual students. A detailed description of each of the modules in the matrix is contained in a catalog section.

[Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

PubMed

Li, Na; Lü, Jian-sheng; Altemann, W

2010-09-01

Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.

Human and remote sensing data to investigate the frontiers of urbanization in the south of Mexico City.

PubMed

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

2017-04-01

The data presented here were originally collected for the article "Frontiers of Urbanization: Identifying and Explaining Urbanization Hot Spots in the South of Mexico City Using Human and Remote Sensing" (Rodriguez et al. 2017) [4]. They were divided into three databases (remote sensing, human sensing, and census information), using a multi-method approach with the goal of analyzing the impact of urbanization on protected areas in southern Mexico City. The remote sensing database was prepared as a result of a semi-automatic classification, dividing the land cover data into urban and non-urban classes. The second data set details an alternative view of the phenomena of urbanization by concentrating on illegal settlements in the conservation zone. It was based on voluntary complaints about environmental and land use offences filed at the Procuraduria Ambiental y del Ordenamiento Territorial del Distrito Federal (PAOT), which is a governmental entity responsible for reviewing and processing grievances on five basic topics: illegal land use, deterioration of green areas, waste, noise/vibrations, and animals. Anyone can file a PAOT complaint by phone, electronically, or in person. The complaint ends with a resolution, act of conciliation, or recommendation for action by other actors, such as the police or health office. The third data about unemployment was extracted from Mexico׳s National Census 2010 database available via public access.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Factors affecting the remotely sensed response of coniferous forest plantations

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

Danson, F.M.; Curran, P.J.

1993-01-01

Remote sensing of forest biophysical properties has concentrated upon forest sites with a wide range of green vegetation amount and thereby leaf area index and canopy cover. However, coniferous forest plantations, an important forest type in Europe, are managed to maintain a large amount of green vegetation with little spatial variation. Therefore, the strength of the remotely sensed signal will, it is hypothesized, be determined more by the structure of this forest than by its cover. Airborne Thematic Mapper (ATM) and SPOT-1 HRV data were used to determine the effects of this structural variation on the remotely sensed response ofmore » a coniferous forest plantation in the United Kingdom. Red and near infrared radiance were strongly and negatively correlated with a range of structural properties and with the age of the stands but weakly correlated with canopy cover. A composite variable, related to the volume of the canopy, accounted for over 75% of the variation in near infrared radiance. A simple model that related forest structural variables to the remotely sensed response was used to understand and explain this response from a coniferous forest plantation.« less

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 .

UAVs Being Used for Environmental Surveying

ScienceCinema

Chung, Sandra

2017-12-09

UAVs, are much more sophisticated than your typical remote-controlled plane. INL robotics and remote sensing experts have added state-of-the-art imaging and wireless technology to the UAVs to create intelligent remote surveillance craft that can rapidly survey a wide area for damage and track down security threats.

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 Plastic Debris

NASA Astrophysics Data System (ADS)

Garaba, S. P.; Dierssen, H. M.

2016-02-01

Plastic debris is becoming a nuisance in the environment and as a result there has been a dire need to synoptically detect and quantify them in the ocean and on land. We investigate the possible utility of spectral information determined from hand held, airborne and satellite remote sensing tools in the detection and identification polymer source of plastic debris. Sampled debris will be compared to our derived spectral library of typical raw polymer sources found at sea and in household waste. Additional work will be to determine ways to estimate the abundance of plastic debris in target areas. Implications of successful remote detection, tracking and quantification of plastic debris will be towards validating field observations over large areas and at repeated time intervals both on land and at sea.

Hyperspectral remote sensing of wild oyster reefs

NASA Astrophysics Data System (ADS)

Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent

2016-04-01

The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal areas.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

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

NASA Astrophysics Data System (ADS)

Ambinakudige, Shrinidhi; Joshi, Kabindra

2012-07-01

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

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.

Remote Sensing Information Science Research

NASA Technical Reports Server (NTRS)

Clarke, Keith C.; Scepan, Joseph; Hemphill, Jeffrey; Herold, Martin; Husak, Gregory; Kline, Karen; Knight, Kevin

2002-01-01

This document is the final report summarizing research conducted by the Remote Sensing Research Unit, Department of Geography, University of California, Santa Barbara under National Aeronautics and Space Administration Research Grant NAG5-10457. This document describes work performed during the period of 1 March 2001 thorough 30 September 2002. This report includes a survey of research proposed and performed within RSRU and the UCSB Geography Department during the past 25 years. A broad suite of RSRU research conducted under NAG5-10457 is also described under themes of Applied Research Activities and Information Science Research. This research includes: 1. NASA ESA Research Grant Performance Metrics Reporting. 2. Global Data Set Thematic Accuracy Analysis. 3. ISCGM/Global Map Project Support. 4. Cooperative International Activities. 5. User Model Study of Global Environmental Data Sets. 6. Global Spatial Data Infrastructure. 7. CIESIN Collaboration. 8. On the Value of Coordinating Landsat Operations. 10. The California Marine Protected Areas Database: Compilation and Accuracy Issues. 11. Assessing Landslide Hazard Over a 130-Year Period for La Conchita, California Remote Sensing and Spatial Metrics for Applied Urban Area Analysis, including: (1) IKONOS Data Processing for Urban Analysis. (2) Image Segmentation and Object Oriented Classification. (3) Spectral Properties of Urban Materials. (4) Spatial Scale in Urban Mapping. (5) Variable Scale Spatial and Temporal Urban Growth Signatures. (6) Interpretation and Verification of SLEUTH Modeling Results. (7) Spatial Land Cover Pattern Analysis for Representing Urban Land Use and Socioeconomic Structures. 12. Colorado River Flood Plain Remote Sensing Study Support. 13. African Rainfall Modeling and Assessment. 14. Remote Sensing and GIS Integration.

Rapid Assessment of Wave Height Transformation through a Tidal Inlet via Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Díaz Méndez, G.; Haller, M. C.; Raubenheimer, B.; Elgar, S.; Honegger, D.

2014-12-01

Radar has the potential to enable temporally and spatially dense, continuous monitoring of waves and currents in nearshore environments. If quantitative relationships between the remote sensing signals and the hydrodynamic parameters of interest can be found, remote sensing techniques can mitigate the challenges of continuous in situ sampling and possibly enable a better understanding of wave transformation in areas with strongly inhomogeneous along and across-shore bathymetry, currents, and dissipation. As part of the DARLA experiment (New River Inlet, NC), the accuracy of a rapid assessment of wave height transformation via radar remote sensing is tested. Wave breaking events are identified in the radar image time series (Catalán et al. 2011). Once the total number of breaking waves (per radar collection) is mapped throughout the imaging domain, radar-derived bathymetry and wave frequency are used to compute wave breaking dissipation (Janssen and Battjes 2007). Given the wave breaking dissipation, the wave height transformation is calculated by finding an inverse solution to the 1D cross-shore energy flux equation (including the effect of refraction). The predicted wave height transformation is consistent (correlation R > 0.9 and rmse as low as 0.1 m) with the transformation observed with in situ sensors in an area of complex morphology and strong (> 1 m/s) tidal currents over a nine-day period. The wave forcing (i.e., radiation stress gradients) determined from the remote sensing methodology will be compared with values estimated with in situ sensors. Funded by ONR and ASD(R&E)

Lidar system for air-pollution monitoring over urban areas

NASA Astrophysics Data System (ADS)

Moskalenko, Irina V.; Shcheglov, Djolinard A.; Molodtsov, Nikolai A.

1997-05-01

The atmospheric environmental situation over the urban area of a large city is determined by a complex combination of anthropogenic pollution and meteorological factors. The efficient way to provide three-dimensional mapping of gaseous pollutants over wide areas is utilization of lidar systems employing tunable narrowband transmitters. The paper presented describes activity of RRC 'Kurchatov Institute' in the field of lidar atmospheric monitoring. The project 'mobile remote sensing system based on tunable laser transmitter for environmental monitoring' is developed under financial support of International Scientific and Technology Center (Moscow). The objective of the project is design, construction and field testing of a DIAL-technique system. The lidar transmitter consists of an excimer laser pumping dye laser, BBO crystal frequency doubler, and scanning flat mirror. Sulfur dioxide and atomic mercury have been selected as pollutants for field tests of the lidar system under development. A recent large increase in Moscow traffic stimulated taking into consideration also the remote sensing of lower troposphere ozone because of the photochemical smog problem. The status of the project is briefly discussed. The current activity includes also collecting of environmental data relevant to lidar remote sensing. Main attention is paid to pollutant concentration levels over Moscow city and Moscow district areas.

A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

NASA Astrophysics Data System (ADS)

Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

2016-09-01

Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

Thermal anomaly before earthquake and damage assessment using remote sensing data for 2014 Yutian earthquake

NASA Astrophysics Data System (ADS)

Zhang, Yanmei; Huang, Haiying; Jiang, Zaisen; Fang, Ying; Cheng, Xiao

2014-12-01

Thermal anomaly appears to be a significant precursor of some strong earthquakes. In this study, time series of MODIS Land Surface Temperature (LST) products from 2001 to 2014 are processed and analyzed to locate possible anomalies prior to the Yutian earthquake (12 February 2014, Xinjiang, CHINA). In order to reduce the seasonal or annual effects from the LST variations, also to avoid the rainy and cloudy weather in this area, a background mean of ten-day nighttime LST are derived using averaged MOD11A2 products from 2001 to 2012. Then the ten-day LST data from Jan 2014 to FebJanuary 2014 were differenced using the above background. Abnormal LST increase before the earthquake is quite obvious from the differential images, indicating that this method is useful in such area with high mountains and wide-area deserts. Also, in order to assess the damage to infrastructure, China's latest civilian high-resolution remote sensing satellite - GF-1 remote sensed data are applied to the affected counties in this area. The damaged infrastructures and ground surface could be easily interpreted in the fused pan-chromatic and multi-spectral images integrating both texture and spectral information.

Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis

USGS Publications Warehouse

Xian, George; Homer, Collin G.; Granneman, Brian; Meyer, Debra K.

2012-01-01

Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

NASA Technical Reports Server (NTRS)

1973-01-01

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

OhioView: Distribution of Remote Sensing Data Across Geographically Distributed Environments

NASA Technical Reports Server (NTRS)

Ramos, Calvin T.

1998-01-01

Various issues associated with the distribution of remote sensing data across geographically distributed environments are presented in viewgraph form. Specific topics include: 1) NASA education program background; 2) High level architectures, technologies and applications; 3) LeRC internal architecture and role; 4) Potential GIBN interconnect; 5) Potential areas of network investigation and research; 6) Draft of OhioView data model; and 7) the LeRC strategy and roadmap.

[Algorithms of multiband remote sensing for coastal red tide waters].

PubMed

Mao, Xianmou; Huang, Weigen

2003-07-01

The spectral characteristics of the coastal waters in East China Sea was studied using in situ measurements, and the multiband algorithms of remote sensing for bloom waters was discussed and developed. Examples of red tide detection using the algorithms in the East China Sea were presented. The results showed that the algorithms could provide information about the location and the area coverage of the red tide events.

Reassessing the conservation status of the giant panda using remote sensing.

PubMed

Xu, Weihua; Viña, Andrés; Kong, Lingqiao; Pimm, Stuart L; Zhang, Jingjing; Yang, Wu; Xiao, Yi; Zhang, Lu; Chen, Xiaodong; Liu, Jianguo; Ouyang, Zhiyun

2017-11-01

The conservation status of the iconic giant panda is a barometer of global conservation efforts. The IUCN Red List has downgraded the panda's extinction risk from "endangered" to "vulnerable". Newly obtained, detailed GIS and remotely sensed data applied consistently over the last four decades show that panda habitat covered less area and was more fragmented in 2013 than in 1988 when the species was listed as endangered.

Land use planning

NASA Technical Reports Server (NTRS)

1975-01-01

The organization, objectives, and accomplishments of the panel on Land Use Planning are reported. Technology developments, and projected developments are discussed along with anticipated information requirements. The issues for users, recommended remote sensing programs, and space systems are presented. It was found that remote sensing systems are useful in future land use planning. It is recommended that a change detection system for monitoring land use and critical environmental areas be developed by 1979.

Sea Surface Signature of Tropical Cyclones Using Microwave Remote Sensing

DTIC Science & Technology

2013-01-01

due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those...and corrections for sun glint, galactic and cosmic background radiation, and Stokes effects of the ionosphere. The accuracy of a given retrieval...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) Sea surface signature of tropical cyclones using microwave remote sensing Bumjun Kil

Remote sensing detection of atmospheric pollutants using lidar, sodar and correlation with air quality data in an industrial area

NASA Astrophysics Data System (ADS)

Steffens, Juliana; da Costa, Renata F.; Landulfo, Eduardo; Guardani, Roberto; Moreira, Paulo F., Jr.; Held, Gerhard

2011-11-01

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of Sao Paulo, in the city of Cubatao, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar.

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel

2011-01-01

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

NASA Astrophysics Data System (ADS)

Ma, Yi; Zhang, Jie; Zhang, Jingyu

2016-01-01

The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale hyperspectral images based on time sequence. The research results of this paper will help to break the traditional concept of remote sensing monitoring coastal wetlands by satellite and manned aerial vehicle, lead the trend of this monitoring technology, and put forward a new technical proposal for grasping the distribution of the coastal wetland and the changing trend and carrying out the protection and management of the coastal wetland.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks

PubMed Central

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-01-01

Simple Summary The understanding of the spatio-temporal distribution of the species habitats would facilitate wildlife resource management and conservation efforts. Existing methods have poor performance due to the limited availability of training samples. More recently, location-aware sensors have been widely used to track animal movements. The aim of the study was to generate suitability maps of bar-head geese using movement data coupled with environmental parameters, such as remote sensing images and temperature data. Therefore, we modified a deep convolutional neural network for the multi-scale inputs. The results indicate that the proposed method can identify the areas with the dense goose species around Qinghai Lake. In addition, this approach might also be interesting for implementation in other species with different niche factors or in areas where biological survey data are scarce. Abstract With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction. PMID:29701686

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.

Multi Source Remote Sensing for Monitoring Light-Absorbing Impurities on Snow and Ice in the European Alps

NASA Astrophysics Data System (ADS)

Colombo, R.; Baccolo, G.; Garzonio, R.; Massabò, D.; Julitta, T.; Rossini, M.; Ferrero, L.; Delmonte, B.; Maggi, V.; Mattavelli, M.; Panigada, C.; Cogliati, S.; Cremonese, E.; Di Mauro, B.

2016-12-01

The European Alps are located close to one of the most industrialized areas of the planet and they are 3.000 km from the largest desert of the Earth. Light-absorbing impurities (LAI) emitted from these sources can reach the Alpine chain and deposit on snow covered areas and mountain glaciers. Although several studies show that LAI have important impacts on the optical properties of snow and ice, reducing the albedo and promoting the melt, this impact has been poorly characterized in the Alps. In this contribution, we present the results of a multisource remote sensing approach aimed to study the LAI impact on snow and ice properties in the Alpine area. This process has been observed by means of remote and proximal sensing methods, using satellite (Landsat 8, Hyperion and MODIS data), field spectroscopy (ASD measurements), Automatic Weather Stations, aerial surveys (Unmanned Aerial Vehicle), radiative transfer modeling (SNICAR and TARTES) and laboratory analysis (hyperspectral imaging system). Furthermore, particle size (Coulter Counter), geochemical (Instrumental Neutron Activation Analysis, INAA) and optical (Multi-Wavelength Absorbance Analyzer, MWAA) analyses have been applied to determine the nature and radiative properties of particulate material deposited on snow and ice or aggregated into cryoconite holes. Our results demonstrate that LAI can be monitored from remote sensing at different scale. LAI showed to have a strong impact on the Alpine cryosphere, paving the way for the assessment of their role in melting processes.

The pan-sharpening of satellite and UAV imagery for agricultural applications

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

2016-10-01

Remote sensing techniques are widely used in many different areas of interest, i.e. urban studies, environmental studies, agriculture, etc., due to fact that they provide rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. Agricultural management is one of the most common application of remote sensing methods nowadays. Monitoring of agricultural sites and creating information regarding spatial distribution and characteristics of crops are important tasks to provide data for precision agriculture, crop management and registries of agricultural lands. For monitoring of cultivated areas many different types of remote sensing data can be used- most popular are multispectral satellites imagery. Such data allow for generating land use and land cover maps, based on various methods of image processing and remote sensing methods. This paper presents fusion of satellite and unnamed aerial vehicle (UAV) imagery for agricultural applications, especially for distinguishing crop types. Authors in their article presented chosen data fusion methods for satellite images and data obtained from low altitudes. Moreover the authors described pan- sharpening approaches and applied chosen pan- sharpening methods for multiresolution image fusion of satellite and UAV imagery. For such purpose, satellite images from Landsat- 8 OLI sensor and data collected within various UAV flights (with mounted RGB camera) were used. In this article, the authors not only had shown the potential of fusion of satellite and UAV images, but also presented the application of pan- sharpening in crop identification and management.

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

PubMed Central

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

2018-01-01

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

Ship detection using STFT sea background statistical modeling for large-scale oceansat remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Lixia; Pei, Jihong; Xie, Weixin; Liu, Jinyuan

2018-03-01

Large-scale oceansat remote sensing images cover a big area sea surface, which fluctuation can be considered as a non-stationary process. Short-Time Fourier Transform (STFT) is a suitable analysis tool for the time varying nonstationary signal. In this paper, a novel ship detection method using 2-D STFT sea background statistical modeling for large-scale oceansat remote sensing images is proposed. First, the paper divides the large-scale oceansat remote sensing image into small sub-blocks, and 2-D STFT is applied to each sub-block individually. Second, the 2-D STFT spectrum of sub-blocks is studied and the obvious different characteristic between sea background and non-sea background is found. Finally, the statistical model for all valid frequency points in the STFT spectrum of sea background is given, and the ship detection method based on the 2-D STFT spectrum modeling is proposed. The experimental result shows that the proposed algorithm can detect ship targets with high recall rate and low missing rate.

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.

Experimental evidence for spring and autumn windows for the detection of geobotanical anomalies through the remote sensing of overlying vegetation

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.; Bell, R.; Nelson, R. F.; Larsen, C. A.; Hooker, L. K.; Troensegaard, K. W.

1985-01-01

It is pointed out that in many regions of the world, vegetation is the predominant factor influencing variation in reflected energy in the 0.4-2.5 micron region of the spectrum. Studies have, therefore, been conducted regarding the utility of remote sensing for detecting changes in vegetation which could be related to the presence of mineralization. The present paper provides primarily a report on the results of the second year of a multiyear study of geobotanical-remote-sensing relationships as developed over areas of sulfide mineralization. The field study has a strong experimental design basis. It is proceeded by first delineating the boundaries of a large geographic region which satisfied a set of previously enumerated field-site criteria. Within this region, carefully selected pairs of mineralized and nonmineralized test sites were examined over the growing season. The experiment is to provide information about the spectral and temporal resolutions required for remote-sensing-geobotanical exploration. The obtained results are evaluated.

Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing

NASA Technical Reports Server (NTRS)

Treuhaft, Robert N.; Law, Beverly E.; Asner, Gregory P.

2004-01-01

The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.

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.

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.

A summary of the history of the development of automated remote sensing for agricultural applications

NASA Technical Reports Server (NTRS)

Macdonald, R. B.

1983-01-01

The research conducted in the United States for the past 20 years with the objective of developing automated satellite remote sensing for monitoring the earth's major food crops is reviewed. The highlights of this research include a National Academy of Science study on the applicability of remote sensing monitoring given impetus by the introduction in the mid-1960's of the first airborne multispectral scanner (MSS); design simulations for the first earth resource satellite in 1969; and the use of the airborne MSS in the Corn Blight Watch, the first large application of remote sensing in agriculture, in 1970. Other programs discussed include the CITAR research project in 1972 which established the feasibility of automating digital classification to process high volumes of Landsat MSS data; the Large Area Crop Inventory Experiment (LACIE) in 1974-78, which demonstrated automated processing of Landsat MSS data in estimating wheat crop production on a global basis; and AgRISTARS, a program designed to address the technical issues defined by LACIE.

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

PubMed

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

2017-04-01

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

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

The application of geologic remote sensing to vertebrate biostratigraphy - General results from the Wind River Basin, Wyoming

NASA Technical Reports Server (NTRS)

Stucky, Richard K.; Krishtalka, Leonard

1991-01-01

Since 1986, remote sensing images derived from satellite and aircraft-borne sensor data have been used to study the stratigraphy and sedimentology of the vertebrate-bearing Wind River and Wagon Bed formations in the Wind River Basin (Wyoming). Landsat 5 TM and aircraft Thermal Infrared Multispectral Scanner data were combined with conventional geologic analyses. The remote sensing data have contributed significantly to: (1) geologic mapping at the formation, member, and bed levels; (2) stratigraphic correlation; (3) reconstruction of ancient depositional environments; and (4) identification of structural complexity. This information is critical to vertebrate paleontology in providing the stratigraphic, sedimentologic, and structural framework required for evolutionary and paleoecologic studies. Of primary importance is the ability to map at minimal cost the geology of large areas (20,000 sq km or greater) at a high level of precision. Remote sensing data can be especially useful in geologically and paleontologically unexplored or poorly understood regions.

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.

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 rainfall using remote sensing for Riyadh climate, KSA

NASA Astrophysics Data System (ADS)

AlHassoun, Saleh A.

2013-05-01

Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

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

Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less

A new multi-angle remote sensing framework for scaling vegetation properties from tower-based spectro-radiometers to next generation "CubeSat"-satellites.

NASA Astrophysics Data System (ADS)

Hilker, T.; Hall, F. G.; Dyrud, L. P.; Slagowski, S.

2014-12-01

Frequent earth observations are essential for assessing the risks involved with global climate change, its feedbacks on carbon, energy and water cycling and consequences for live on earth. Often, satellite-remote sensing is the only practical way to provide such observations at comprehensive spatial scales, but relationships between land surface parameters and remotely sensed observations are mostly empirical and cannot easily be scaled across larger areas or over longer time intervals. For instance, optically based methods frequently depend on extraneous effects that are unrelated to the surface property of interest, including the sun-server geometry or background reflectance. As an alternative to traditional, mono-angle techniques, multi-angle remote sensing can help overcome some of these limitations by allowing vegetation properties to be derived from comprehensive reflectance models that describe changes in surface parameters based on physical principles and radiative transfer theory. Recent results have shown in theoretical and experimental research that multi-angle techniques can be used to infer and scale the photosynthetic rate of vegetation, its biochemical and structural composition robustly from remote sensing. Multi-angle remote sensing could therefore revolutionize estimates of the terrestrial carbon uptake as scaling of primary productivity may provide a quantum leap in understanding the spatial and temporal complexity of terrestrial earth science. Here, we introduce a framework of next generation tower-based instruments to a novel and unique constellation of nano-satellites (Figure 1) that will allow us to systematically scale vegetation parameters from stand to global levels. We provide technical insights, scientific rationale and present results. We conclude that future earth observation from multi-angle satellite constellations, supported by tower based remote sensing will open new opportunities for earth system science and earth system modeling.

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.

NASA EPSCoR Preparation Grant

NASA Technical Reports Server (NTRS)

Sukanek, Peter C.

2002-01-01

The NASA EPSCoR project in Mississippi involved investigations into three areas of interest to NASA by researchers at the four comprehensive universities in the state. These areas involved: (1) Noninvasive Flow Measurement Techniques, (2) Spectroscopic Exhaust Plume Measurements of Hydrocarbon Fueled Rocket Engines and (3) Integration of Remote Sensing and GIS data for Flood Forecasting on the Mississippi Gulf Coast. Each study supported a need at the Stennis Space Center in Mississippi. The first two addressed needs in rocket testing, and the third, in commercial remote sensing. Students from three of the institutions worked with researchers at Stennis Space Center on the projects.

Remote sensing for control of tsetse flies

NASA Technical Reports Server (NTRS)

Giddings, L. E.

1976-01-01

Remotely sensed information is discussed which has potential for aiding in the control or eradication of tsetse flies. Data are available from earth resources meteorological, and manned satellites, from airborne sensors, and possibly from data collection platforms. A new zone discrimination technique, based on data from meteorological satellites may also allow the identification of zones hospitable to one or another species of tsetse. For background, a review is presented of the vegetation of Tanzania and Zanzibar, and illustrations presented of automatic processing of data from these areas. In addition, a review is presented of the applicability of temperature data to tsetse areas.

The Remote Sensing of Surface Radiative Temperature over Barbados.

DTIC Science & Technology

remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

Levee Health Monitoring With Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.

2012-12-01

Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers the entire network of more than 1100 miles of levees in the area, has used several sets of in situ data to validate the results. This type of levee health status information acquired with radar remote sensing could provide a cost-effective method to significantly improve the spatial and temporal coverage of levee systems and identify areas of concern for targeted levee maintenance, repair, and emergency response in the future. Our results show, for example, that during an emergency, when time is of the essence, SAR remote sensing offers the potential of rapidly providing levee status information that is effectively impossible to obtain over large areas using conventional monitoring, e.g., through high precision measurements of subcentimeter-scale levee movement prior to failure. The research described here was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

NASA Astrophysics Data System (ADS)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Monitoring the ecology and environment using remote sensing in the Jinta area/Middle Reaches of Heihe River Basin

NASA Astrophysics Data System (ADS)

Lu, Anxin; Wang, Lihong; Chen, Xianzhang

2003-07-01

A major monitoring area, a part of the middle reaches of Heihe basin, was selected. The Landsat TM data in summer of 1990 and 2000 were used with interpretation on the computer screen, classification and setting up environmental investigation database (1:100000) combined with DEM, land cover/land use, land type data and etc., according to the environmental classification system. Then towards to the main problems of environment, the spatial statistical analysis and dynamic comparisons were carried out using the database. The dynamic monitoring results of 1999 and 2000 show that the changing percentage with the area of 6 ground objects are as follows: land use and agriculture land use increased by 34.17% and 19.47% respectively, wet land and water-body also increased by 6.29% and 8.03% respectively; unused land increased by 1.73% and the biggest change is natural/semi-natural vegetation area, decreased by 42.78%, the main results above meat with the requirements of precise and practical conditions by the precise exam and spot check. With the combinations of using TM remote sensing data and rich un-remote sensing data, the investigations of ecology and environment and the dynamic monitoring would be carried out efficiently in the arid area. It is a dangerous signal of large area desertification if the area of natural/semi-natural vegetation is reduced continuously and obviously.

[Changes of wetland landscape pattern in Dayang River Estuary based on high-resolution remote sensing image].

PubMed

Wu, Tao; Zhao, Dong-zhi; Zhang, Feng-shou; Wei, Bao-quan

2011-07-01

Based on the comprehensive consideration of the high resolution characteristics of remote sensing data and the current situation of land cover and land use in Dayang River Estuary wetland, a classification system with different resolutions of wetland landscape in the Estuary was established. The landscape pattern indices and landscape transition matrix were calculated by using the high resolution remote sensing data, and the dynamic changes of the landscape pattern from 1984 to 2008 were analyzed. In the study period, the wetland landscape components changed drastically. Wetland landscape transferred from natural wetland into artificial wetland, and wetland core regional area decreased. Natural wetland's largest patch area index descended, and the fragmentation degree ascended; while artificial wetland area expanded, its patch number decreased, polymerization degree increased, and the maximum patch area index had an obvious increasing trend. Increasing human activities, embankment construction, and reclamation for aquaculture were the main causes for the decrease of wetland area and the degradation of the ecological functions of Dayang River Estuary. To constitute long-term scientific and reasonable development plan, establish wetland nature reserves, protect riverway, draft strict inspective regimes for aquaculture reclamation, and energetically develop resource-based tourism industry would be the main strategies for the protection of the estuarine wetland.

Study of the wide area of a lake with remote sensing

NASA Astrophysics Data System (ADS)

Lazaridou, Maria A.; Karagianni, Aikaterini C.

2016-08-01

Water bodies are particularly important for environment and development issues. Their study requires multiple information. Remote sensing has been proven useful in the above study. This paper concerns the wide area of Lake Orestiada in the region of Western Macedonia in Greece. The area is of particular interest because Lake Orestiada is included in the Natura 2000 network and is surrounded by diverse landcovers as built up areas and agricultural land. Multispectral and thermal Landsat 5 satellite images of two time periods are being used. Their processing is being done by Erdas Imagine software. The general physiognomy of the area and the lake shore are examined after image enhancement techniques and image interpretation. Directions of the study concern geomorphological aspects, land covers, estimation of surface temperature as well as changes through time.

Extraction of Greenhouse Areas with Image Processing Methods in Karabuk Province

NASA Astrophysics Data System (ADS)

Yildirima, M. Z.; Ozcan, C.

2017-11-01

Greenhouses provide the environmental conditions to be controlled and regulated as desired while allowing agricultural products to be produced without being affected by external environmental conditions. High quality and a wide variety of agricultural products can be produced throughout the year. In addition, mapping and detection of these areas has great importance in terms of factors such as yield analysis, natural resource management and environmental impact. Various remote sensing techniques are currently available for extraction of greenhouse areas. These techniques are based on the automatic detection and interpretation of objects on remotely sensed images. In this study, greenhouse areas were determined from optical images obtained from Landsat. The study was carried out in the greenhouse areas in Karabuk province. The obtained results are presented with figures and tables.

Flood hazards studies in the Mississippi River basin using remote sensing

NASA Technical Reports Server (NTRS)

Rango, A.; Anderson, A. T.

1974-01-01

The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicated that ERTS-1 is extremely useful as a regional tool for flood mamagement. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.

A summary of the history of the development of automated remote sensing for agricultural applications

NASA Technical Reports Server (NTRS)

Macdonald, R. B.

1984-01-01

An historical account is given of the development of technology for the processing of satellite-acquired multispectral data aimed at the identification of the type, condition, and ontogenic stages of agricultural areas. During 1972 and 1973, research established the feasibility of automating digital classification for the processing of large volumes of Landsat MSS data. This capability was successfully demonstrated during the Large Area Crop Inventory Experiment, which estimated wheat crop production on a global basis. This achievement in turn led to the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing, which investigated other portions of the electromagnetic spectrum and expanded the study of key commercial crops in important agricultural areas.

Application of remote sensing to the photogeologic mapping of the region of the Itatiaia alkaline complex. M.S. Thesis; [Minas Gerais, Rio De Janeiro, Sao Paulo, and Itatiaia, Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Rodrigues, J. E.

1981-01-01

Remote sensing methods applied to geologically complex areas, through interaction of ground truth and information obtained from multispectral LANDSAT images and radar mosaics were evaluated. The test area covers parts of Minos Gerais, Rio De Janeiro and Sao Paulo states and contains the alkaline complex of Itatiaia and surrounding Precambrian terrains. Geological and structural mapping was satisfactory; however, lithological varieties which form the massif's could not be identified. Photogeological lineaments were mapped, some of which represent the boundaries of stratigraphic units. Automatic processing was used to classify sedimentary areas, which includes the talus deposits of the alkaline massifs.

Chemical-biological defense remote sensing: what's happening

NASA Astrophysics Data System (ADS)

Carrico, John P.

1998-08-01

The proliferation of weapons of mass destruction (WMD) continues to be a serious threat to the security of the US. Proliferation of chemical and biological (CB) weapons is particularly disturbing, and the threats posed can be devastating. Critical elements of the US efforts to reduce and counter WMD proliferation include: (1) the location and characterization of WMD facilities and capabilities worldwide; (2) the ability to rapidly detect and identify the use of CB weapons for expeditious warning and reporting on the battlefield; and (3) the capability to mitigate deleterious consequences of a CB incident through effective protective and medical treatment measures. Remote sensing has been touted as a key technology in these efforts. Historically, the role of remote sensing in CB defense has been to provide early warning of an attack from an extended distance. However, additional roles for remote sensing in CB defense, as well as applications in related missions, are possible and should be pursued. This paper examines what has been happening in remote sensing over the past decade to address needs in this area. Accomplishments, emerging technologies, programmatic issues, and opportunities for the future are covered. The Department of Defence chemical- biological, the Department of Energy's Chemical Analysis by Laser Interrogation of Proliferation Effluents, and other agency related programs are examined. Also, the status of remote sensing in the commercial market arena for environmental monitoring, its relevance to the WMD counterproliferation program, and opportunities for technology transfer are discussed. A course of action for the future is recommended.

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

USGS Publications Warehouse

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

2017-01-01

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

Polarization Remote Sensing Physical Mechanism, Key Methods and Application

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Utilizing multisource remotely sensed data to dynamically monitor drought in China

NASA Astrophysics Data System (ADS)

Liu, Sanchao; Li, Wenbo

2011-12-01

Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

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.

Eighth year projects and activities of the Environmental Remote Sensing Applications Laboratory (ERSAL). [Oregon

NASA Technical Reports Server (NTRS)

Lewis, A. J.; Isaacson, D. L.; Schrumpf, B. J. (Principal Investigator)

1980-01-01

Projects completed for the NASA Office of University Affairs include the application of remote sensing data in support of rehabilitation of wild fire damaged areas and the use of LANDSAT 3 return beam vidicon in forestry mapping applications. Continuing projects for that office include monitoring western Oregon timber clearcut; detecting and monitoring wheat disease; land use monitoring for tax assessment in Umatilla, Lake, and Morrow Counties; and the use of Oregon Air National Guard thermal infrared scanning data. Projects funded through other agencies include the remote sensing inventory of elk in the Blue Mountains; the estimation of burned agricultural acreage in the Willamette Valley; a resource inventory of Deschutes County; and hosting a LANDSAT digital workshop.

Remote sensing in Michigan for land resource management

NASA Technical Reports Server (NTRS)

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

1975-01-01

The utilization of NASA earth resource survey technology as an important aid in the solution of current problems in resource management and environmental protection in Michigan is discussed. Remote sensing techniques to aid Michigan government agencies were used to achieve the following results: (1) provide data on Great Lakes beach recession rates to establish shoreline zoning ordinances; (2) supply technical justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (3) establish economical and effective methods for performing a statewide wetlands survey; (4) accomplish a variety of regional resource management actions in the Upper Peninsula; and (5) demonstrate improved soil survey methods. The project disseminated information on remote sensing technology and provided advice and assistance to a number of users in Michigan.

An airborne remote sensing platform of the Helsinki University of Technology

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

Nikulainen, M.; Hallikainen, M.; Kemppinen, M.

1996-10-01

In 1994 Helsinki University of Technology acquired a Short SC7 Skyvan turboprop aircraft to be modified to carry remote sensing instruments. As the aircraft is originally designed to carry heavy and space consuming cargo, a modification program was implemented to make the aircraft feasible for remote sensing operations. The twelve-month long modification program had three design objectives: flexibility, accessibility and cost efficiency. The aircraft interior and electrical system were modified. Furthermore, the aircraft is equipped with DGPS-navigation system, multi-channel radiometer system and side looking airborne radar. Future projects include installation of local area network, attitude GPS system, imaging spectrometer andmore » 1.4 GHz radiometer. 6 refs., 5 figs., 1 tab.« less

Using Remotely Sensed Data to Map Urban Vulnerability to Heat

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2010-01-01

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

Application of airborne remote sensing to the ancient Pompeii site

NASA Astrophysics Data System (ADS)

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

1996-12-01

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

Development of data processing, interpretation and analysis system for the remote sensing of trace atmospheric gas species

NASA Technical Reports Server (NTRS)

Casas, Joseph C.; Saylor, Mary S.; Kindle, Earl C.

1987-01-01

The major emphasis is on the advancement of remote sensing technology. In particular, the gas filter correlation radiometer (GFCR) technique was applied to the measurement of trace gas species, such as carbon monoxide (CO), from airborne and Earth orbiting platforms. Through a series of low altitude aircraft flights, high altitude aircraft flights, and orbiting space platform flights, data were collected and analyzed, culminating in the first global map of carbon monoxide concentration in the middle troposphere and stratosphere. The four major areas of this remote sensing program, known as the Measurement of Air Pollution from Satellites (MAPS) experiment, are: (1) data acquisition, (2) data processing, analysis, and interpretation algorithms, (3) data display techniques, and (4) information processing.

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.

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)

1982-01-01

Capabilities to process data for state agencies in Kansas were upgraded through the vehicle of a low cost data processing system. Short term projects in which agencies identified areas of immediate needs, and longer terms projects, continued from previous years, are described including studies of Arkansas River irrigation; evaluation of rangeland in the Cimarron National Grassland; a model of the Walnut Creek watershed groundwater; selection of a pronghorn antelope release site; the establishment of a geographical data base for tax reassessment in Finney County; a land use/land cover inventory and hazards assessment; and applied R & D in agricultural remote sensing. The topics discussed at a short course in remote sensing and publications are listed.

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.

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.

Using Remote Sensing Mapping and Growth Response to Environmental Variability to Aide Aquatic Invasive Plant Management

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Schlick, Greg; Genovese, Vanessa; Wilson, Kenneth D.

2018-01-01

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta.

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

NASA Astrophysics Data System (ADS)

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

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

Project MEDSAT: The design of a remote sensing platform for malaria research and control

NASA Astrophysics Data System (ADS)

1991-04-01

Project MEDSAT was proposed with the specific goal of designing a satellite to remotely sense pertinent information useful in establishing strategies to control malaria. The 340 kg MEDSAT satellite is to be inserted into circular earth orbit aboard the Pegasus Air-Launched Space Booster at an inclination of 21 degrees and an altitude of 473 km. It is equipped with a synthetic aperture radar and a visible thermal/infrared sensor to remotely sense conditions at the target area of Chiapas, Mexico. The orbit is designed so that MEDSAT will pass over the target site twice each day. The data from each scan will be downlinked to Hawaii for processing, resulting in maps indicating areas of high malaria risk. These will be distributed to health officials at the target site. A relatively inexpensive launch by Pegasus and a design using mainly proven, off-the-shelf technology permit a low mission cost, while innovations in the satellite controls and the scientific instruments allow a fairly complex mission.

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

NASA Astrophysics Data System (ADS)

Cong, Chao; Liu, Dingsheng; Zhao, Lingjun

2008-12-01

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

AVIRIS data and neural networks applied to an urban ecosystem

NASA Technical Reports Server (NTRS)

Ridd, Merrill K.; Ritter, Niles D.; Bryant, Nevin A.; Green, Robert O.

1992-01-01

Urbanization is expanding on every continent. Although urban/industrial areas occupy a small percentage of the total landscape of the earth, their influence extends far beyond their borders, affecting terrestrial, aquatic, and atmospheric systems globally. Yet little has been done to characterize urban ecosystems of their linkages to other systems horizontally or vertically. With remote sensing we now have the tools to characterize, monitor, and model urban landscapes world-wide. However, the remote sensing performed on cities so far has concentrated on land-use patterns as distinct from land-cover or composition. The popular Anderson system is entirely land-use oriented in urban areas. This paper begins with the premise that characterizing the biophysical composition of urban environments is fundamental to understanding urban/industrial ecosystems, and, in turn, supports the modeling of other systems interfacing with urban systems. Further, it is contended that remote sensing is a tool poised to provide the biophysical composition data to characterize urban landscapes.

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

NASA Technical Reports Server (NTRS)

1975-01-01

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

A framework for nowcasting and forecasting of rainfall-triggered landslide activity using remotely sensed data

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas

2016-04-01

Remote sensing data offers the unique perspective to provide situational awareness of hydrometeorological hazards over large areas in a way that is impossible to achieve with in situ data. Recent work has shown that rainfall-triggered landslides, while typically local hazards that occupy small spatial areas, can be approximated over regional or global scales in near real-time. This work presents a regional and global approach to approximating potential landslide activity using the landslide hazard assessment for situational awareness (LHASA) model. This system couples remote sensing data, including Global Precipitation Measurement rainfall data, Shuttle Radar Topography Mission and other surface variables to estimate where and when landslide activity may be likely. This system also evaluates the effectiveness of quantitative precipitation estimates from the Goddard Earth Observing System Model, Version 5 to provide a 24 forecast of potential landslide activity. Preliminary results of the LHASA model and implications for are presented for a regional version of this system in Central America as well as a prototype global approach.

Project MEDSAT: The design of a remote sensing platform for malaria research and control

NASA Technical Reports Server (NTRS)

1991-01-01

Project MEDSAT was proposed with the specific goal of designing a satellite to remotely sense pertinent information useful in establishing strategies to control malaria. The 340 kg MEDSAT satellite is to be inserted into circular earth orbit aboard the Pegasus Air-Launched Space Booster at an inclination of 21 degrees and an altitude of 473 km. It is equipped with a synthetic aperture radar and a visible thermal/infrared sensor to remotely sense conditions at the target area of Chiapas, Mexico. The orbit is designed so that MEDSAT will pass over the target site twice each day. The data from each scan will be downlinked to Hawaii for processing, resulting in maps indicating areas of high malaria risk. These will be distributed to health officials at the target site. A relatively inexpensive launch by Pegasus and a design using mainly proven, off-the-shelf technology permit a low mission cost, while innovations in the satellite controls and the scientific instruments allow a fairly complex mission.

Integrated analysis of remote sensing products from basic geological surveys. [Brazil

NASA Technical Reports Server (NTRS)

Dasilvafagundesfilho, E. (Principal Investigator)

1984-01-01

Recent advances in remote sensing led to the development of several techniques to obtain image information. These techniques as effective tools in geological maping are analyzed. A strategy for optimizing the images in basic geological surveying is presented. It embraces as integrated analysis of spatial, spectral, and temporal data through photoptic (color additive viewer) and computer processing at different scales, allowing large areas survey in a fast, precise, and low cost manner.

Wide-area remote-sensing system of pollution and gas dispersal by near-infrared absorption based on low-loss optical fiber network

NASA Technical Reports Server (NTRS)

Inaba, H.

1986-01-01

An all optical remote sensing system utilizing long distance, ultralow loss optical fiber networks is studied and discussed for near infrared absorption measurements of combustible and/or explosive gases such as CH4 and C3H8 in our environment, including experimental results achieved in a diameter more than 20 km. The use of a near infrared wavelength range is emphasized.

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Preliminary study of Songa-Wayaua geothermal prospect area using volcanostratigraphy and remote sensing analysis

NASA Astrophysics Data System (ADS)

Asokawaty, Ribka; Nugroho, Indra; Satriana, Joshua; Hafidz, Muhamad; Suryantini

2017-12-01

Songa-Wayaua geothermal prospect area is located on Bacan Island, Northern Molluca Province. Geothermal systems in this area associated with three Quartenary volcanoes, such as Mt. Pele-pele, Mt. Lansa, and Mt. Bibinoi. Based on literature study, five surface manifestations such as hot springs and alteration occurred within this area. The active manifestations indicate that Songa-Wayaua area has potential geothermal resource. This study objective is to evaluate Songa-Wayaua geothermal system on preliminary study stage by using volcanostratigraphy and remote sensing analysis to delineate the boundary of geothermal system area. The result of this study showed that Songa-Wayaua prospect area has four heat sources potential (e.g. Pele-pele Hummock, Lansa Hummock, Songa Hummock, and Bibinoi Hummock), controlled by geological structure presented by Pele-pele Normal Fault, and had three places as the recharge and discharge area which are very fulfilling as a geothermal system.

[Object-oriented remote sensing image classification in epidemiological studies of visceral leishmaniasis in urban areas].

PubMed

Almeida, Andréa Sobral de; Werneck, Guilherme Loureiro; Resendes, Ana Paula da Costa

2014-08-01

This study explored the use of object-oriented classification of remote sensing imagery in epidemiological studies of visceral leishmaniasis (VL) in urban areas. To obtain temperature and environmental information, an object-oriented classification approach was applied to Landsat 5 TM scenes from the city of Teresina, Piauí State, Brazil. For 1993-1996, VL incidence rates correlated positively with census tracts covered by dense vegetation, grass/pasture, and bare soil and negatively with areas covered by water and densely populated areas. In 2001-2006, positive correlations were found with dense vegetation, grass/pasture, bare soil, and densely populated areas and negative correlations with occupied urban areas with some vegetation. Land surface temperature correlated negatively with VL incidence in both periods. Object-oriented classification can be useful to characterize landscape features associated with VL in urban areas and to help identify risk areas in order to prioritize interventions.

Cropland measurement using Thematic Mapper data and radiometric model

NASA Technical Reports Server (NTRS)

Lyon, John G.; Khuwaiter, I. H. S.

1989-01-01

To halt erosion and desertification, it is necessary to quantify resources that are affected. Necessary information includes inventory of croplands and desert areas as they change over time. Several studies indicate the value of remote sensor data as input to inventories. In this study, the radiometric modeling of spectral characteristics of soil and vegetation provides the theoretical basis for the remote sensing approach. Use of Landsat Thematic Mapper images allows measurement of croplands in Saudi Arabia, demonstrating the capability of the approach. The inventory techniques and remote sensing approach presented are potentially useful in developing countries.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Public health applications of remote sensing of the environment, an evaluation

NASA Technical Reports Server (NTRS)

1972-01-01

The available techniques were examined in the field of remote sensing (including aerial photography, infrared detection, radar, etc.) and applications to a number of problems in the wide field of public health determined. The specific areas of public health examined included: air pollution, water pollution, communicable disease, and the combined problems of urban growth and the effect of disasters on human communities. The assessment of the possible applications of remote sensing to these problems was made primarily by examination of the available literature in each field, and by interviews with health authorities, physicists, biologists, and other interested workers. Three types of programs employing remote sensors were outlined in the air pollution field: (1) proving ability of sensors to monitor pollutants at three levels of interest - point source, ambient levels in cities, and global patterns; (2) detection of effects of pollutants on the environment at local and global levels; and (3) routine monitoring.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Integration of TerraSAR-X, RapidEye and airborne lidar for remote sensing of intertidal bedforms on the upper flats of Norderney (German Wadden Sea)

NASA Astrophysics Data System (ADS)

Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert

2017-04-01

The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.

Bundle block adjustment of large-scale remote sensing data with Block-based Sparse Matrix Compression combined with Preconditioned Conjugate Gradient

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhang, Yongjun; Zhou, Shunping; Zhu, Junfeng; Xiong, Xiaodong

2016-07-01

In recent years, new platforms and sensors in photogrammetry, remote sensing and computer vision areas have become available, such as Unmanned Aircraft Vehicles (UAV), oblique camera systems, common digital cameras and even mobile phone cameras. Images collected by all these kinds of sensors could be used as remote sensing data sources. These sensors can obtain large-scale remote sensing data which consist of a great number of images. Bundle block adjustment of large-scale data with conventional algorithm is very time and space (memory) consuming due to the super large normal matrix arising from large-scale data. In this paper, an efficient Block-based Sparse Matrix Compression (BSMC) method combined with the Preconditioned Conjugate Gradient (PCG) algorithm is chosen to develop a stable and efficient bundle block adjustment system in order to deal with the large-scale remote sensing data. The main contribution of this work is the BSMC-based PCG algorithm which is more efficient in time and memory than the traditional algorithm without compromising the accuracy. Totally 8 datasets of real data are used to test our proposed method. Preliminary results have shown that the BSMC method can efficiently decrease the time and memory requirement of large-scale data.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

NASA Icing Remote Sensing System Comparisons From AIRS II

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Brinker, David J.; Ratvasky, Thomas P.

2005-01-01

NASA has an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Individual remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Comparisons between the remote sensing system s fused icing product and in-situ measurements from the research aircraft are reviewed here. While there are areas where improvement can be made, the cases examined indicate that the fused sensor remote sensing technique appears to be a valid approach.

Evaluation of impact of earthquake on agriculture in Nepal based on remote sensing

NASA Astrophysics Data System (ADS)

Sekiyama, Ayako; Shimada, Sawahiko; Okazawa, Hiromu; Mihara, Machito; Kuo, Kuang Ting

2016-07-01

The big earthquake happening on April, 2015 killed over than 8000 people in Nepal. The effect of earthquake not only affected safety of local people but also agricultural field. Agricultural economy dominates income of local people. Therefore, restoration of agricultural areas are required for improving life of local people. However, lack of information about agricultural areas is main problem for local government to assess and restore damaged agricultural areas. Remote sensing was applied for accessing damaged agricultural field due to its advantages in observing responds of environment without temporal and spatial restriction. Accordingly, the objective of the study is to evaluate impact of earthquake on agriculture in Nepal based on remote sensing. The experimental procedure includes conducting the impact of earthquake on changes of total agricultural area, and analysis of response of greenness affected by earthquake in agricultural land. For conducting agricultural land changes, land use map was first created and classified into four categories: road, city, forest, and agricultural land. Changes before and after earthquake in total area of agricultural land were analyzed by GIS. Moreover, vegetation index was used as indicator for evaluating greenness responds in agricultural land and computed based on high-resolution satellite imagery such as World view-3. Finally, the conclusion of the study and suggestions will be made and provided for helping local government in Nepal restore agricultural areas.

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.

Land Use and Land Cover Change Modeling Using Remote Sensing and Soft Computing Approach to Assess Sugarcane Expansion Impacts in Tropical Agriculture

NASA Astrophysics Data System (ADS)

Vicente, L. E.; Koga-Vicente, A.; Friedel, M. J.; Victoria, D.; Zullo, J., Jr.; Gomes, D.; Bayma-Silva, G.

2014-12-01

Agriculture is related with land-use/cover changes (LUCC) over large areas and, in recent years, increase in demand of ethanol fuel has been influence in expansion of areas occupied with corn and sugar cane, raw material for ethanol production. Nevertheless, there´s a concern regarding the impacts on food security, such as, decrease in areas planted with food crops. Considering that the LUCC is highly dynamic, the use of Remote Sensing is a tool for monitoring changes quickly and precisely in order to provide information for agricultural planning. In this work, Remote Sensing techniques were used to monitor the LUCC occurred in municipalities of São Paulo state- Brazil related with sugarcane crops expansion in order to (i) evaluate and quantify the previous land cover in areas of sugarcane crop expansion, and (ii) provide information to elaborate a future land cover scenario based on Self Organizing Map (SOM) approach. The land cover classification procedure was based on Landsat 5 TM images, obtained from the Global Land Survey. The Landsat images were then segmented into homogeneous objects, with represent areas on the ground with similar spatial and spectral characteristics. These objects are related to the distinct land cover types that occur in each municipality. The segmentation procedure resulted in polygons over the three time periods along twenty years (1990-2010). The land cover for each object was visually identified, based on its shape, texture and spectral characteristics. Land cover types considered were: sugarcane plantations, pasture lands, natural cover, forest plantation, permanent crop, short cycle crop, water bodies and urban areas. SOM technique was used to estimate the values for the future land cover scenarios for the selected municipalities, using the information of land change provided by the remote sensing and data from official sources.

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.

Remote sensing, paleoecology, and the archaeology of human migration during the Pleistocene in central Asia and western China

NASA Astrophysics Data System (ADS)

Glantz, Michelle M.; Todd, Lawrence

2003-07-01

Remote sensing used in the context of global information systems has enormous applications within archaeology. This technology enables the discovery of new archaeological features and promotes an understanding of the relationship between ecosystem and cultural dynamics. Archaeologists are able to add a time dimension to 'creeping environmental changes' that other areas of scientific inquiry concerned with climate change often lack. Remote sensing and other aerial prospecting has been used successfully to model land use and population expansions during relatively recent archaeological eras, such as the Bronze and Iron Ages. Although satellite image databases exist for numerous areas of the New and Old World, very little research has been conducted in Central Asia or western China. This region is historically significant because of its position along the important trading route called the Silk Road. The purpose of the present research is to investigate another poorly understood period of human history that would benefit from the application of remote sensing and associated ground truthing techniques. The migration of hominids out of Africa during the late Pliocene/early Pleistocene and their subsequent colonization of north-central, east, and south-east Asia is relatively well documented in the archaeological record and marks the beginning of the long-term process of human impacts on the region. However, the trajectory of dispersal of Homo erectus, Neandertals, and early modern humans and the ways by which ecosystem vagaries affected this dispersal across Eurasia is unknown. Our purpose is to summarize what is currently known about the geological indicators of ecosystem changes that remote sensing techniques provide and how ecosystem variables may allow us to model human migration as that of an invasive species through this important geographic crossroads of the Old World.

Science, technology, and application of THz air photonics

NASA Astrophysics Data System (ADS)

Lu, X. F.; Clough, B.; Ho, I.-C.; Kaur, G.; Liu, J.; Karpowicz, N.; Dai, J. M.; Zhang, X.-C.

2010-11-01

The significant scientific and technological potential of terahertz (THz) wave sensing and imaging has been attracted considerable attention within many fields of research. However, the development of remote, broadband THz wave sensing technology is lagging behind the compelling needs that exist in the areas of astronomy, global environmental monitoring, and homeland security. This is due to the challenge posed by high absorption of ambient moisture in the THz range. Although various time-domain THz detection techniques have recently been demonstrated, the requirement for an on-site bias or forward collection of the optical signal inevitably prohibits their applications for remote sensing. The objective of this paper is to report updated THz air-plasma technology to meet this great challenge of remote sensing. A focused optical pulse (mJ pulse energy and femtosecond pulse duration) in gas creates a plasma, which can serve to generate intense, broadband, and directional THz waves in the far field.

Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981

NASA Technical Reports Server (NTRS)

Mcintosh, R.

1982-01-01

The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Analyzing Forest Inventory Data from Geo-Located Photographs

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Comparision of Bathymetry and Bottom Characteristics From Hyperspectral Remote Sensing Data and Shipborne Acoustic Measurements

NASA Astrophysics Data System (ADS)

McIntyre, M. L.; Naar, D. F.; Carder, K. L.; Howd, P. A.; Lewis, J. M.; Donahue, B. T.; Chen, F. R.

2002-12-01

There is growing interest in applying optical remote sensing techniques to shallow-water geological applications such as bathymetry and bottom characterization. Model inversions of hyperspectral remote-sensing reflectance imagery can provide estimates of bottom albedo and depth. This research was conducted in support of the HyCODE (Hyperspectral Coupled Ocean Dynamics Experiment) project in order to test optical sensor performance and the use of a hyperspectral remote-sensing reflectance algorithm for shallow waters in estimating bottom depths and reflectance. The objective of this project was to compare optically derived products of bottom depths and reflectance to shipborne acoustic measurements of bathymetry and backscatter. A set of three high-resolution, multibeam surveys within an 18 km by 1.5 km shore-perpendicular transect 5 km offshore of Sarasota, Florida were collected at water depths ranging from 8 m to 16 m. These products are compared to bottom depths derived from aircraft remote-sensing data collected with the AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) instrument data by means of a semi-analytical remote sensing reflectance model. The pixel size of the multibeam bathymetry and AVIRIS data are 0.25 m and 10 m, respectively. When viewed at full resolution, the multibeam bathymetry data show small-scale sedimentary bedforms (wavelength ~10m, amplitude ~1m) that are not observed in the lower resolution hyperspectral bathymetry. However, model-derived bottom depths agree well with a smoothed version of the multibeam bathymetry. Depths derived from shipborne hyperspectral measurements were accurate within 13%. In areas where diver observations confirmed biological growth and bioturbation, derived bottom depths were less accurate. Acoustic backscatter corresponds well with the aircraft hyperspectral imagery and in situ measurements of bottom reflectance. Acoustic backscatter was used to define the distribution of different bottom types. Acoustic backscatter imagery corresponds well with the AVIRIS data in the middle to outer study area, implying a close correspondence between seafloor character and optical reflectance. AVIRIS data in the inner study area show poorer correspondence with the acoustic facies, indicating greater water column effects (turbidity). Acoustic backscatter as a proxy for bottom albedo, in conjunction with multibeam bathymetry data, will allow for more precise modeling of the optical signal in coastal environments.

Accuracy Dimensions in Remote Sensing

NASA Astrophysics Data System (ADS)

Barsi, Á.; Kugler, Zs.; László, I.; Szabó, Gy.; Abdulmutalib, H. M.

2018-04-01

The technological developments in remote sensing (RS) during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS), which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users' needs. The present paper gives the theoretic overview of the issue, besides selected, practice-oriented approaches are evaluated too, finally widely-used dimension metrics like Root Mean Squared Error (RMSE) or confusion matrix are discussed. The authors present data quality features of well-defined and poorly defined object. The central part of the study is the land cover mapping, describing its accuracy management model, presented relevance and uncertainty measures of its influencing quality dimensions. In the paper theory is supported by a case study, where the remote sensing technology is used for supporting the area-based agricultural subsidies of the European Union, in Hungarian administration.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Applications of Remote Sensing to Emergency Management.

DTIC Science & Technology

1980-02-15

Contents: Foundations of Remote Sensing : Data Acquisition and Interpretation; Availability of Remote Sensing Technology for Disaster Response...Imaging Systems, Current and Near Future Satellite and Aircraft Remote Sensing Systems; Utilization of Remote Sensing in Disaster Response: Categories of...Disasters, Phases of Monitoring Activities; Recommendations for Utilization of Remote Sensing Technology in Disaster Response; Selected Reading List.

Navigation and Remote Sensing Payloads and Methods of the Sarvant Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Molina, P.; Fortuny, P.; Colomina, I.; Remy, M.; Macedo, K. A. C.; Zúnigo, Y. R. C.; Vaz, E.; Luebeck, D.; Moreira, J.; Blázquez, M.

2013-08-01

In a large number of scenarios and missions, the technical, operational and economical advantages of UAS-based photogrammetry and remote sensing over traditional airborne and satellite platforms are apparent. Airborne Synthetic Aperture Radar (SAR) or combined optical/SAR operation in remote areas might be a case of a typical "dull, dirty, dangerous" mission suitable for unmanned operation - in harsh environments such as for example rain forest areas in Brazil, topographic mapping of small to medium sparsely inhabited remote areas with UAS-based photogrammetry and remote sensing seems to be a reasonable paradigm. An example of such a system is the SARVANT platform, a fixed-wing aerial vehicle with a six-meter wingspan and a maximumtake- of-weight of 140 kilograms, able to carry a fifty-kilogram payload. SARVANT includes a multi-band (X and P) interferometric SAR payload, as the P-band enables the topographic mapping of densely tree-covered areas, providing terrain profile information. Moreover, the combination of X- and P-band measurements can be used to extract biomass estimations. Finally, long-term plan entails to incorporate surveying capabilities also at optical bands and deliver real-time imagery to a control station. This paper focuses on the remote-sensing concept in SARVANT, composed by the aforementioned SAR sensor and envisioning a double optical camera configuration to cover the visible and the near-infrared spectrum. The flexibility on the optical payload election, ranging from professional, medium-format cameras to mass-market, small-format cameras, is discussed as a driver in the SARVANT development. The paper also focuses on the navigation and orientation payloads, including the sensors (IMU and GNSS), the measurement acquisition system and the proposed navigation and orientation methods. The latter includes the Fast AT procedure, which performs close to traditional Integrated Sensor Orientation (ISO) and better than Direct Sensor Orientation (DiSO), and features the advantage of not requiring the massive image processing load for the generation of tie points, although it does require some Ground Control Points (GCPs). This technique is further supported by the availability of a high quality INS/GNSS trajectory, motivated by single-pass and repeat-pass SAR interferometry requirements.

[Monitoring the thermal plume from coastal nuclear power plant using satellite remote sensing data: modeling, and validation].

PubMed

Zhu, Li; Zhao, Li-Min; Wang, Qiao; Zhang, Ai-Ling; Wu, Chuan-Qing; Li, Jia-Guo; Shi, Ji-Xiang

2014-11-01

Thermal plume from coastal nuclear power plant is a small-scale human activity, mornitoring of which requires high-frequency and high-spatial remote sensing data. The infrared scanner (IRS), on board of HJ-1B, has an infrared channel IRS4 with 300 m and 4-days as its spatial and temporal resolution. Remote sensing data aquired using IRS4 is an available source for mornitoring thermal plume. Retrieval pattern for coastal sea surface temperature (SST) was built to monitor the thermal plume from nuclear power plant. The research area is located near Guangdong Daya Bay Nuclear Power Station (GNPS), where synchronized validations were also implemented. The National Centers for Environmental Prediction (NCEP) data was interpolated spatially and temporally. The interpolated data as well as surface weather conditions were subsequently employed into radiative transfer model for the atmospheric correction of IRS4 thermal image. A look-up-table (LUT) was built for the inversion between IRS4 channel radiance and radiometric temperature, and a fitted function was also built from the LUT data for the same purpose. The SST was finally retrieved based on those preprocessing procedures mentioned above. The bulk temperature (BT) of 84 samples distributed near GNPS was shipboard collected synchronically using salinity-temperature-deepness (CTD) instruments. The discrete sample data was surface interpolated and compared with the satellite retrieved SST. Results show that the average BT over the study area is 0.47 degrees C higher than the retrieved skin temperature (ST). For areas far away from outfall, the ST is higher than BT, with differences less than 1.0 degrees C. The main driving force for temperature variations in these regions is solar radiation. For areas near outfall, on the contrary, the retrieved ST is lower than BT, and greater differences between the two (meaning > 1.0 degrees C) happen when it gets closer to the outfall. Unlike the former case, the convective heat transfer resulting from the thermal plume is the primary reason leading to the temperature variations. Temperature rising (TR) distributions obtained from remote sensing data and in-situ measurements are consistent, except that the interpolated BT shows more level details (> 5 levels) than that of the ST (up to 4 levels). The areas with higher TR levels (> 2) are larger on BT maps, while for lower TR levels (≤ 2), the two methods perform with no obvious differences. Minimal errors for satellite-derived SST occur regularly around local time 10 a. m. This makes the remote sensing results to be substitutes for in-situ measurements. Therefore, for operational applications of HJ-1B IRS4, remote sensing technique can be a practical approach to monitoring the nuclear plant thermal pollution around this time period.

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

Treesearch

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

2011-01-01

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

The Future of Remote Sensing from Space: Civilian Satellite Systems and Applications.

DTIC Science & Technology

1993-07-01

image shows abundant (dark green) vegetation across the Amazon of South America, while lack of vegetation (black areas) is seen across the Sahara Desert...primarily through the space shuttle and space station Freedom programs.25 Hence, if NASA’s overall budget remains flat or includes only modest growth... remain the primary collector of satellite remote sensing data for both meteorolog- ical and climate monitoring efforts through the decade of the 1990s

Highlights: US Commercial Remote Sensing Industry Analysis

NASA Technical Reports Server (NTRS)

Rabin, Ron

2002-01-01

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

Remote Sensing of Chaparral Fire Potential: Case Study in Topanga Canyon, California.

DTIC Science & Technology

Remote sensing techniques, especially the use of color infrared aerial photography, provide a useful tool for fire hazard analysis, including interpetive information about fuel volumes, physiognomic plant groupings, the relationships of buildings to both natural and planted vegetation, and fire vulnerability of roofing materials. In addition, the behavior of the September, 1970 Wright Fire in the Topanga study area suggested the validity of the fire potential analysis which had been made prior to that conflagration.

Airborne Remote Sensing of the Plata Plume Using STARRS

DTIC Science & Technology

2006-09-01

marine constructions . www.sea-technoJlav.com .byT. RT O ’A" n. -, Airborne Remote Sensing of the Plata Plume Using STARRS A New Generation Microwave...using possibilities of adapting a Seville, MATLAB®-from The Spain-based Construcciones Aero- Mathworks Inc. (Natick, Mas- nduticas SA (CASA) Aviocar C...34 Simula-STARRS was constructed and flight of smaller coastal areas with a preci- tion, vol. 78, pp. 36-55, 2002.tested in July 2003. Since aircraft

BOREAS Level-0 AOCI Imagery: Digital Counts in BIL Format

NASA Technical Reports Server (NTRS)

Newcomer, Jeffrey A.; Dominquez, Roseanne; Hall, Forrest G. (Editor)

2000-01-01

The level-0 AOCI imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOREAS study areas. The AOCI was the only remote sensing instrument flown with wavelength bands specific to the investigation of various aquatic parameters such as chlorophyll content and turbidity. Only one flight of the AOCI instrument was made onboard the ER-2 aircraft on 21-Jul-1994 over the SSA.

Measuring the Interdisciplinary Impact of Using Geospatial Data with Remote Sensing Data

NASA Astrophysics Data System (ADS)

Downs, R. R.; Chen, R. S.; Schumacher, J.

2017-12-01

Various disciplines offer benefits to society by contributing to the scientific progress that informs the knowledge and decisions that improve the lives, safety, and conditions of people around the globe. In addition to disciplines within the natural sciences, other disciplines, including those in the social, health, and computer sciences, provide benefits to society by collecting, preparing, and analyzing data in the process of conducting research. Preparing geospatial environmental and socioeconomic data together with remote sensing data from satellite-based instruments for wider use by heterogeneous communities of users increases the potential impact of these data by enabling their use in different application areas and sectors of society. Furthermore, enabling wider use of scientific data can bring to bear resources and expertise that will improve reproducibility, quality, methodological transparency, interoperability, and improved understanding by diverse communities of users. In line with its commitment to open data, the NASA Socioeconomic Data and Applications Center (SEDAC), which focuses on human interactions in the environment, curates and disseminates freely and publicly available geospatial data for use across many disciplines and societal benefit areas. We describe efforts to broaden the use of SEDAC data and to publicly document their impact, assess the interdisciplinary impact of the use of SEDAC data with remote sensing data, and characterize these impacts in terms of their influence across disciplines by analyzing citations of geospatial data with remote sensing data within scientific journals.

Analysis of the atmospheric upward radiation in low latitude area

NASA Astrophysics Data System (ADS)

Li, Haiying; Wu, Zhensen; Lin, Leke; Lu, Changsheng

2016-10-01

Remote sensing using THz wave has irreplaceable advantage comparing to the microwave and the infrared waves, and study on the THz remote sensing become more and more popular in recent years. The major applications of the remote sensing in THz wavelengths are the retrieval of the atmospheric parameters and the microphysical information of the ice cloud. The remote sensing of the atmosphere is based on the radiation of THz wave along the earth-space path of which the most significant part is the upward radiation of the atmosphere. The upward radiation of the atmosphere in sunny day in the low latitude area is computed and analyzed in this paper. The absorption of THz wave by the atmosphere is calculated using the formulations illustrated in the Recommendation ITU-R P.676 to save machine hour, the frequency range is then restricted below 1THz. The frequencies used for the retrieval of atmospheric parameters such as temperature and water content are usually a few hundred GHz, at the lower end of THz wavelengths, so this frequency range is sufficient. The radiation contribution of every atmospheric layer for typical frequencies such as absorption window frequencies and peak frequencies are analyzed. Results show that at frequencies which absorption is severe, information about lower atmosphere cannot reach the receiver onboard a satellite or other high platforms due to the strong absorption along the path.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed

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

2010-01-01

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

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

NASA Technical Reports Server (NTRS)

Beck, Louisa R.; Rodriquez, Mario H.; Dister, Sheri W.; Rodriquez, Americo D.; Rejmankova, Eliska; Ulloa, Armando; Meza, Rosa A.; Roberts, Donald R.; Paris, Jack F.; Spanner, Michael A.;

Use hyperspectral remote sensing technique to monitoring pine wood nomatode disease preliminary

NASA Astrophysics Data System (ADS)

Qin, Lin; Wang, Xianghong; Jiang, Jing; Yang, Xianchang; Ke, Daiyan; Li, Hongqun; Wang, Dingyi

2016-10-01

The pine wilt disease is a devastating disease of pine trees. In China, the first discoveries of the pine wilt disease on 1982 at Dr. Sun Yat-sen's Mausoleum in Nanjing. It occurred an area of 77000 hm2 in 2005, More than 1540000 pine trees deaths in the year. Many districts of Chongqing in Three Gorges Reservoir have different degrees of pine wilt disease occurrence. It is a serious threat to the ecological environment of the reservoir area. Use unmanned airship to carry high spectrum remote sensing monitoring technology to develop the study on pine wood nematode disease early diagnosis and early warning and forecasting in this study. The hyper spectral data and the digital orthophoto map data of Fuling District Yongsheng Forestry had been achieved In September 2015. Using digital image processing technology to deal with the digital orthophoto map, the number of disease tree and its distribution is automatic identified. Hyper spectral remote sensing data is processed by the spectrum comparison algorithm, and the number and distribution of disease pine trees are also obtained. Two results are compared, the distribution area of disease pine trees are basically the same, indicating that using low air remote sensing technology to monitor the pine wood nematode distribution is successful. From the results we can see that the hyper spectral data analysis results more accurate and less affected by environmental factors than digital orthophoto map analysis results, and more environment variable can be extracted, so the hyper spectral data study is future development direction.

BOREAS Level-3s Landsat TM Imagery Scaled At-sensor Radiance in LGSOWG Format

NASA Technical Reports Server (NTRS)

Nickeson, Jaime; Knapp, David; Newcomer, Jeffrey A.; Cihlar, Josef; Hall, Forrest G. (Editor)

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS),the level-3s Landsat Thematic Mapper (TM) data, along with the other remotely sensed images,were collected in order to provide spatially extensive information over the primary study areas. This information includes radiant energy,detailed land cover, and biophysical parameter maps such as Fraction of Photosynthetically Active Radiation (FPAR) and Leaf area Index (LAI). CCRS collected and supplied the level-3s images to BOREAS for use in the remote sensing research activities. Geographically,the bulk of the level-3s images cover the BOREAS Northern Study Area (NSA) and Southern Study Area (SSA) with a few images covering the area between the NSA and SSA. Temporally,the images cover the period of 22-Jun-1984 to 30-Jul-1996. The images are available in binary,image-format files.

Remote sensing of tropospheric gases and aerosols with airborne DIAL system

NASA Technical Reports Server (NTRS)

Browell, E. V.

1983-01-01

The multipurpose airborne DIAL system developed at NASA Langley Research Center is characterized, and the published results of tropospheric O3, H2O, and aerosol-backscatter remote-sensing experiments performed in 1980 and 1981 are summarized. The system comprises two tunable dye lasers pumped by frequency-doubled Nd:YAG lasers, dielectric-coated steering optics, a 36-cm-diameter Cassegrain receiver telescope, gateable photomultiplier tubes, and a minicomputer data-processing unit for real-time calculation of gas concentrations and backscattering profiles. The transmitted energy of the 100-microsec-separated dye-laser pulses is 40, 80, or 50 mJ/pulse at around 300, 600, or 720-nm wavelength, respectively. Good agreement was found between DIAL-remote-sensed and in-situ H2O and O3 profiles of the lower troposphere and O3 profiles of the tropopause region, and the usefulness of DIAL backscattering measurements in the study of boundary-layer and tropospheric dynamics is demonstrated. The feasibility of DIAL sensing of power-plant or urban plume SO2, of urban-area (or rural-area column-content) NO2, and of temperature and H2O (simultaneously using a third laser) has been suggested by simulation studies.

Study on environment detection and appraisement of mining area with RS

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang

2006-12-01

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

Remote sensing techniques in monitoring areas affected by forest fire

NASA Astrophysics Data System (ADS)

Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

2017-09-01

Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

The Effectiveness of Contrasting Protected Areas in Preventing Deforestation in Madre de Dios, Peru

NASA Astrophysics Data System (ADS)

Vuohelainen, Anni Johanna; Coad, Lauren; Marthews, Toby R.; Malhi, Yadvinder; Killeen, Timothy J.

2012-10-01

Accurate monitoring of the effectiveness of protected areas (PAs) in decreasing deforestation is increasingly important given the vital role of forest protection in climate change mitigation. Recent studies on PA effectiveness have used remote-sensing imagery to compare deforestation rates within PAs to surrounding areas. However, remote-sensing data used in isolation provides limited information on the factors contributing to effectiveness. We used landscape-modelling techniques to estimate the effectiveness of ten PAs in Madre de Dios, Peru. Factors influencing PA effectiveness were investigated using in situ key-informant interviews. Although all of the PAs studied had positive effectiveness scores, those with the highest scores were ecotourism and conservation concessions, where monitoring and surveillance activities and good relations with surrounding communities were reported as possible factors in decreasing deforestation rates. Native community areas had the lowest scores, with deforestation mainly driven by internal resource use and population growth. Weak local governance and immigration were identified as underlying factors decreasing the effectiveness of protection, whereas good relations with surrounding communities and monitoring activity increased effectiveness. The results highlight the need to combine remote sensing with in situ information on PA management because identification of drivers and deterrents of deforestation is vital for improving the effectiveness of protection.

The effectiveness of contrasting protected areas in preventing deforestation in Madre de Dios, Peru.

PubMed

Vuohelainen, Anni Johanna; Coad, Lauren; Marthews, Toby R; Malhi, Yadvinder; Killeen, Timothy J

2012-10-01

Accurate monitoring of the effectiveness of protected areas (PAs) in decreasing deforestation is increasingly important given the vital role of forest protection in climate change mitigation. Recent studies on PA effectiveness have used remote-sensing imagery to compare deforestation rates within PAs to surrounding areas. However, remote-sensing data used in isolation provides limited information on the factors contributing to effectiveness. We used landscape-modelling techniques to estimate the effectiveness of ten PAs in Madre de Dios, Peru. Factors influencing PA effectiveness were investigated using in situ key-informant interviews. Although all of the PAs studied had positive effectiveness scores, those with the highest scores were ecotourism and conservation concessions, where monitoring and surveillance activities and good relations with surrounding communities were reported as possible factors in decreasing deforestation rates. Native community areas had the lowest scores, with deforestation mainly driven by internal resource use and population growth. Weak local governance and immigration were identified as underlying factors decreasing the effectiveness of protection, whereas good relations with surrounding communities and monitoring activity increased effectiveness. The results highlight the need to combine remote sensing with in situ information on PA management because identification of drivers and deterrents of deforestation is vital for improving the effectiveness of protection.

Monitoring Rangeland Health by Remote Sensing

USDA-ARS?s Scientific Manuscript database

Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote s...

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

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

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

Novel Kalman Filter Algorithm for Statistical Monitoring of Extensive Landscapes with Synoptic Sensor Data

PubMed Central

Czaplewski, Raymond L.

2015-01-01

Wall-to-wall remotely sensed data are increasingly available to monitor landscape dynamics over large geographic areas. However, statistical monitoring programs that use post-stratification cannot fully utilize those sensor data. The Kalman filter (KF) is an alternative statistical estimator. I develop a new KF algorithm that is numerically robust with large numbers of study variables and auxiliary sensor variables. A National Forest Inventory (NFI) illustrates application within an official statistics program. Practical recommendations regarding remote sensing and statistical issues are offered. This algorithm has the potential to increase the value of synoptic sensor data for statistical monitoring of large geographic areas. PMID:26393588

Estimating reforestation by means of remote sensing

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.

1981-01-01

LANDSAT imagery at the scale of 1:250.000 and obtained from bands 5 and 7 as well as computer compatible tapes were used to evaluate the effectiveness of remotely sensed orbital data in inventorying forests in a 462,100 area of Brazil emcompassing the cities of Ribeirao, Altinopolis Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Santa Rita do Passa Quatro, and Santa Rosa do Viterbo. Visual interpretation of LANDSAT imagery shows that 37,766 hectares (1977) and 38,003.75 hectares (1979) were reforested areas of pine and eucalyptus species. An increment of 237.5 hectares was found during this two-year time lapse.

Evaluation of reforestation using remote sensing techniques

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.; Dossantos, J. R.

1982-01-01

The utilization of remotely sensed orbital data for forestry inventory. The study area (approximately 491,100 ha) encompasses the municipalities of Ribeirao Preto, Altinopolis, Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Sant Rita do Passa Quatro and Santa Rosa do Viterbo (Sao Paulo State). Materials used were LANDSAT data from channels 5 and 7 (scale 1:250,000) and CCT's. Visual interpretation of the imagery showed that for 1977 a total of 37,766.00 ha and for 1979 38,003.75 ha were reforested with Pinus and Eucalyptus within the area under study. The results obtained show that LANDSAT data can be used efficiently in forestry inventory studies.

Oleoresin, Chemistry and Spectral Reflectance in "Stressed" Lodgepole and White Bark Pine, Mammoth Mountain, California

NASA Technical Reports Server (NTRS)

Hickey, James C.; Birnie, Richard W.; Zhao, Mei-Xun

2001-01-01

Development of methods to identify the physical and chemical character of materials on the earth's surface is one of the foci of hyperspectral remote sensing activities. Enhancing the ability to elucidate changes in foliar chemistry that relate to the health of a plant is a benefit to plant physiologists, foresters, and plant ecologists, as well as geologist and environmental scientists. Vegetation covers the landscape throughout the temperate and tropical regions of the earth. The existence of vegetation in these areas presents special problems to remote sensing systems since geologic bedrock and alteration zones are masked. At times, however, alterations in the soil/sediment geochemical environment result in foliar chemical changes that are detectable via remote sensing. Examples include monitoring of chlorophyll reflectance/fluorescence and equivalent water thickness indices as indicators of drought-induced plant stress. Another processing and interpretation approach used with hyperspectral data has been principal components analysis (PCA). Rowan et al. used PCA to identify absorption feature patterns obtained from vegetated areas with discrete bedrock geology or mineralization as the substrate. Many researchers highlight the need to advance our ability for hyperspectral imaging in vegetated areas as a near-term priority.

Automated training site selection for large-area remote-sensing image analysis

NASA Astrophysics Data System (ADS)

McCaffrey, Thomas M.; Franklin, Steven E.

1993-11-01

A computer program is presented to select training sites automatically from remotely sensed digital imagery. The basic ideas are to guide the image analyst through the process of selecting typical and representative areas for large-area image classifications by minimizing bias, and to provide an initial list of potential classes for which training sites are required to develop a classification scheme or to verify classification accuracy. Reducing subjectivity in training site selection is achieved by using a purely statistical selection of homogeneous sites which then can be compared to field knowledge, aerial photography, or other remote-sensing imagery and ancillary data to arrive at a final selection of sites to be used to train the classification decision rules. The selection of the homogeneous sites uses simple tests based on the coefficient of variance, the F-statistic, and the Student's i-statistic. Comparisons of site means are conducted with a linear growing list of previously located homogeneous pixels. The program supports a common pixel-interleaved digital image format and has been tested on aerial and satellite optical imagery. The program is coded efficiently in the C programming language and was developed under AIX-Unix on an IBM RISC 6000 24-bit color workstation.

Cluster Method Analysis of K. S. C. Image

NASA Technical Reports Server (NTRS)

Rodriguez, Joe, Jr.; Desai, M.

1997-01-01

Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

The Texas Remote Sensing Training Project

NASA Technical Reports Server (NTRS)

Wells, J. B.

1975-01-01

The project was designed to train federal, state and regional agency managers, scientists and engineers. A one-week seminar was designed and implemented to build vocabulary, introduce technical subject areas and give students enough training to allow them to relate remote sensing technology to operational agency projects. The seminar was designed to perform the dual function of conveying enough remote sensing information to be of value as a stand-alone and preparing students for detailed pattern recognition training. The LARSYS III portion of the training project was executed exactly as designed in the LARSYS training materials package; the LARSYS package did not contain a LANDSAT training module. Two LANDSAT training modules were developed using Texas LANDSAT data. One module contained central Texas data and the second module contained coastal zone data.

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.

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.

Airborne multispectral remote sensing data to estimate several oenological parameters in vineyard production. A case study of application of remote sensing data to precision viticulture in central Italy.

NASA Astrophysics Data System (ADS)

Tramontana, Gianluca; Girard, Filippo; Belli, Claudio; Comandini, Maria Cristina; Pietromarchi, Paolo; Tiberi, Domenico; Papale, Dario

2010-05-01

It is widely recognized that environmental differences within the vineyard, with respect to soils, microclimate, and topography, can influence grape characteristics and crop yields. Besides, the central Italy landscape is characterized by a high level of fragmentation and heterogeneity It requires stringent Remote sensing technical features in terms of spectral, geometric and temporal resolution to aimed at supporting applications for precision viticulture. In response to the needs of the Italian grape and wine industry for an evaluation of precision viticulture technologies, the DISAFRI (University of Tuscia) and the Agricultural Research Council - Oenological research unit (ENC-CRA) jointly carried out an experimental study during the year 2008. The study was carried out on 2 areas located in the town of Velletri, near Rome; for each area, two varieties (red and white grape) were studied: Nero d'Avola and Sauvignon blanc in first area , Merlot and Sauvignon blanc in second. Remote sensing data were acquired in different periods using a low cost multisensor Airborne remote sensing platform developed by DISAFRI (ASPIS-2 Advanced Spectroscopic Imager System). ASPIS-2, an evolution of the ASPIS sensor (Papale et al 2008, Sensors), is a multispectral sensor based on 4 CCD and 3 interferential filters per CCD. The filters are user selectable during the flight and in this way Aspis is able to acquire data in 12 bands in the visible and near infrared regions with a bandwidth of 10 or 20 nm. To the purposes of this study 7 spectral band were acquired and 15 vegetation indices calculated. During the ripeness period several vegetative and oenochemical parameters were monitored. Anova test shown that several oenochemical variables, such as sugars, total acidity, polyphenols and anthocyanins differ according to the variety taken into consideration. In order to evaluate the time autocorrelation of several oenological parameters value, a simple linear regression between oenological variables monitored during the season and have been carried out. This statistical analysis shown a significant time autocorrelation of series in particular for sugar content and total acidity. In order to estimate the empirical relationships between the oenochemical parameters acquired during the ripeness period and the remote sensing variables, a simple regression analysis has been carried out. The remotely sensed data were significantly correlated with the following oenochemical parameters: Leaf Surface Exposed (SFE) (correlation coefficient R2 ~ 0.8), wood pruning (R2 ~ 0.8), reducing sugars (R2 ~ 0.6 and Root Mean Square Error ~ 5g/l), acidity holder (R2 ~ 0.6 and RMSE ~ 0.5g/l), polyphenols content (R2 ~ 0.9) and Anthocyanins (R2 ~ 0.89). Vegetation index that showed better relationship with oenological variables was MCARI1 (1.2*[2.5*(R800- R670)-1.3*(R800- R550)]. This study demonstrates that the low cost airborne multispectral remote sensing systems like ASPIS can support the precision viticulture. The empirical relationships between oenological parameters and remote sensing data can be applied to obtain thematic and predictive maps. These maps will be simple and effective tools to guide producers in differentiating harvest and winemaking and to improve the quality of wine production.

Assessment of practicality of remote sensing techniques for a study of the effects of strip mining in Alabama

NASA Technical Reports Server (NTRS)

Hughes, T. H.; Dillion, A. C., III; White, J. R., Jr.; Drummond, S. E., Jr.; Hooks, W. G.

1975-01-01

Because of the volume of coal produced by strip mining, the proximity of mining operations, and the diversity of mining methods (e.g. contour stripping, area stripping, multiple seam stripping, and augering, as well as underground mining), the Warrior Coal Basin seemed best suited for initial studies on the physical impact of strip mining in Alabama. Two test sites, (Cordova and Searles) representative of the various strip mining techniques and environmental problems, were chosen for intensive studies of the correlation between remote sensing and ground truth data. Efforts were eventually concentrated in the Searles Area, since it is more accessible and offers a better opportunity for study of erosional and depositional processes than the Cordova Area.

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.

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.

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.

[Application of small remote sensing satellite constellations for environmental hazards in wetland landscape mapping: taking Liaohe Delta, Liaoning Province of Northeast China as a case].

PubMed

Yang, Yuan-Zheng; Chang, Yu; Hu, Yuan-Man; Liu, Miao; Li, Yue-Hui

2011-06-01

To timely and accurately acquire the spatial distribution pattern of wetlands is of significance for the dynamic monitoring, conservation, and sustainable utilization of wetlands. The small remote sensing satellite constellations A/B stars (HJ-1A/1B stars) for environmental hazards were launched by China for monitoring terrestrial resources, which could provide a new data source of remote sensing image acquisition for retrieving wetland types. Taking Liaohe Delta as a case, this paper compared the accuracy of wetland classification map and the area of each wetland type retrieved from CCD data (HJ CCD data) and TM5 data, and validated and explored the applicability and the applied potential of HJ CCD data in wetland resources dynamic monitoring. The results showed that HJ CCD data could completely replace Landsat TM5 data in feature extraction and remote sensing classification. In real-time monitoring, due to its 2 days of data acquisition cycle, HJ CCD data had the priority to Landsat TM5 data (16 days of data acquisition cycle).

U.S. Geological Survey, remote sensing, and geoscience data: Using standards to serve us all

USGS Publications Warehouse

Benson, Michael G.; Faundeen, John L.

2000-01-01

The U.S. Geological Survey (USGS) advocates the use of standards with geosciences and remotely sensed data and metadata for its own purposes and those of its customers. In activities that range from archiving data to making a product, the incorporation of standards makes these functions repeatable and understandable. More important, when accepted standards are followed, data discovery and sharing can be more efficient and the overall value to society can be expanded. The USGS archives many terabytes of digital geoscience and remotely sensed data. Several million photographs are also available to the research community. To manage these vast holdings and ensure that strict preservation and high usability criteria are observed, the USGS uses standards within the archival, data management, public access and ordering, and data distribution areas. The USGS uses Federal and international standards in performing its role as the U.S. National Satellite Land Remote Sensing Data Archive and in its mission as the long-term archive and production center for aerial photographs and cartographic data covering the United States.

Remote sensing techniques in cultural resource management archaeology

NASA Astrophysics Data System (ADS)

Johnson, Jay K.; Haley, Bryan S.

2003-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Evaporation estimation of rift valley lakes: comparison of models.

PubMed

Melesse, Assefa M; Abtew, Wossenu; Dessalegne, Tibebe

2009-01-01

Evapotranspiration (ET) accounts for a substantial amount of the water flux in the arid and semi-arid regions of the World. Accurate estimation of ET has been a challenge for hydrologists, mainly because of the spatiotemporal variability of the environmental and physical parameters governing the latent heat flux. In addition, most available ET models depend on intensive meteorological information for ET estimation. Such data are not available at the desired spatial and temporal scales in less developed and remote parts of the world. This limitation has necessitated the development of simple models that are less data intensive and provide ET estimates with acceptable level of accuracy. Remote sensing approach can also be applied to large areas where meteorological data are not available and field scale data collection is costly, time consuming and difficult. In areas like the Rift Valley regions of Ethiopia, the applicability of the Simple Method (Abtew Method) of lake evaporation estimation and surface energy balance approach using remote sensing was studied. The Simple Method and a remote sensing-based lake evaporation estimates were compared to the Penman, Energy balance, Pan, Radiation and Complementary Relationship Lake Evaporation (CRLE) methods applied in the region. Results indicate a good correspondence of the models outputs to that of the above methods. Comparison of the 1986 and 2000 monthly lake ET from the Landsat images to the Simple and Penman Methods show that the remote sensing and surface energy balance approach is promising for large scale applications to understand the spatial variation of the latent heat flux.

Multiple Scale Remote Sensing for Monitoring Rangelands

USDA-ARS?s Scientific Manuscript database

Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote se...

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

NASA Technical Reports Server (NTRS)

Hall, F. G.; Bizzell, R. M.

1975-01-01

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

Tunnel-Site Selection by Remote Sensing Techniques

DTIC Science & Technology

A study of the role of remote sensing for geologic reconnaissance for tunnel-site selection was commenced. For this study, remote sensing was defined...conventional remote sensing . Future research directions are suggested, and the extension of remote sensing to include airborne passive microwave

Performance of One-Class Classifiers for Invasive Species Mapping using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Skowronek, S.; Asner, G. P.; Feilhauer, H.

2016-12-01

Reliable distribution maps are crucial for the monitoring and management of invasive plant species. Remote sensing can provide such maps for larger areas. However, most remote sensing approaches focus on species in a prominent phenological stage, and a systematic assessment of the performance of different one-class classifiers for mapping species in a more inconspicuous phenological stage is missing so far. In this study, we used hyperspectral remote sensing data to detect the invasive grass Phalaris aquatica and the invasive herb Centaurea solstitialisin a pre-flowering stage in the Jasper Ridge Biological Preserve in California. We collected presence-only data, 66 plots for C. solstitialis and 30 plots for P. aquatica, to calibrate a distribution model and additional presence-absence data (166 / 173 plots) to validate model performance. All plots have a size of 3 m x 3 m. The hyperspectral remote sensing imagery was acquired using the Carnegie Airborne Observatory (CAO) visible to shortwave infrared (VSWIR) imaging spectrometer (400-2500 nm range) in May 2015 with a ground sampling distance (pixel size) of 1 m x 1 m. To find the best approach for mapping these species, we compared the performance of three different state-of-the-art classifiers working with presence-only data: Maxent, biased support vector machines and boosted regression trees. The resulting overall accuracies were 72 - 74% for C. solstitialis, and 83 - 88% for P. aquatica. For both species the overall performance was slightly better for Maxent and BRT than for biased SVM. The detection rates for low cover plots were considerably higher for C. solstitialis than for P. aquatica. For C. solstitalis, they ranged between 71 and 75% for plots with less than 15% cover, highlighting the potential of remote sensing to contribute to an early detection. The models relied on different areas of the spectrum, but still produced the same general pattern, which implies that more than one property of a species or a mixed plot can be used to create a viable model. We conclude that the different one-class classifiers we tested do allow detecting the target species in a more inconspicuous phenological stage, with similar success rates.

Application of remote sensing techniques for identification of irrigated crop lands in Arizona

NASA Technical Reports Server (NTRS)

Billings, H. A.

1981-01-01

Satellite imagery was used in a project developed to demonstrate remote sensing methods of determining irrigated acreage in Arizona. The Maricopa water district, west of Phoenix, was chosen as the test area. Band rationing and unsupervised categorization were used to perform the inventory. For both techniques the irrigation district boundaries and section lines were digitized and calculated and displayed by section. Both estimation techniques were quite accurate in estimating irrigated acreage in the 1979 growing season.

The Application of Remote Sensing Techniques to Urban Data Acquisition

NASA Technical Reports Server (NTRS)

Horton, F. E.

1971-01-01

The application of remote sensing techniques useful in acquiring data concerning housing quality is discussed. Conclusions reached from the investigation were: (1) Use of individuals with a higher degree of training in photointerpretation should significantly increase the percentage of successful classifications. (2) Small area classification of urban housing quality can definitely be accomplished via high resolution aerial photography. Such surveys, at the levels of accuracy demonstrated, can be of major utility in quick look surveys. (3) Survey costs should be significantly reduced.

Remote Sensing and Characterization of Oil on Water Using Coherent Fringe Projection and Holographic in-Line Interferometry

DTIC Science & Technology

2013-03-01

holo- graphic recording on photo-thermo-plastic structure ,” J. Modern Opt. 57(10), 854–858 (2010). 6. N. Kukhtarev and T. Kukhtareva, “ Dynamic ...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 21-10-2013 Journal Article Remote Sensing and Characterization of Oil on Water Using...green-blue region can also degrade oil. This finding indicates that properly structured laser clean-up can be an alternative method of decontamination

Geologic Reconnaissance and Lithologic Identification by Remote Sensing

DTIC Science & Technology

remote sensing in geologic reconnaissance for purposes of tunnel site selection was studied further and a test case was undertaken to evaluate this geological application. Airborne multispectral scanning (MSS) data were obtained in May, 1972, over a region between Spearfish and Rapid City, South Dakota. With major effort directed toward the analysis of these data, the following geologic features were discriminated: (1) exposed rock areas, (2) five separate rock groups, (3) large-scale structures. This discrimination was accomplished by ratioing multispectral channels.

Some applications of remote sensing in atmospheric monitoring programs

NASA Technical Reports Server (NTRS)

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

1972-01-01

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