WorldWideScience

Sample records for remote sensing approach

  1. Remote Sensing

    CERN Document Server

    Khorram, Siamak; Koch, Frank H; van der Wiele, Cynthia F

    2012-01-01

    Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.

  2. A NEW APPROACH TO PIP CROP MONITORING USING REMOTE SENSING

    Science.gov (United States)

    Current plantings of 25+ million acres of transgenic corn in the United States require a new approach to monitor this important crop for the development of pest resistance. Remote sensing by aerial or satellite images may provide a method of identifying transgenic pesticidal cro...

  3. Remote Sensing.

    Science.gov (United States)

    Williams, Richard S., Jr.; Southworth, C. Scott

    1983-01-01

    The Landsat Program became the major event of 1982 in geological remote sensing with the successful launch of Landsat 4. Other 1982 remote sensing accomplishments, research, publications, (including a set of Landsat worldwide reference system index maps), and conferences are highlighted. (JN)

  4. MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH

    Data.gov (United States)

    National Aeronautics and Space Administration — MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Multispectral remote sensing images have...

  5. An Approach to Extracting Fractal in Remote Sensing Image

    Institute of Scientific and Technical Information of China (English)

    ZHU Ji; LIN Ziyu; WANG Angsheng; CUI Peng

    2006-01-01

    In order to apply the spatial structure information to remote sensing interpretation through fractal theory,an algorithm is introduced to compute the single pixel fractal dimension in remote sensing images. After a computer program was written according to the algorithm, the ETM+ images were calculated to obtain their fractal data through the program. The algorithm has following characteristics: The obtained fractal values indicate the complexity of image, and have positive correlation with the complexity of images and ground objects. Moreover, the algorithm is simple and reliable, and easy to be implemented.

  6. Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook.

    Science.gov (United States)

    Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Raso, Giovanna; Utzinger, Jürg

    2015-03-17

    Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions. We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised. We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from. Our findings imply that the

  7. Introduction to remote sensing

    CERN Document Server

    Cracknell, Arthur P

    2007-01-01

    Addressing the need for updated information in remote sensing, Introduction to Remote Sensing, Second Edition provides a full and authoritative introduction for scientists who need to know the scope, potential, and limitations in the field. The authors discuss the physical principles of common remote sensing systems and examine the processing, interpretation, and applications of data. This new edition features updated and expanded material, including greater coverage of applications from across earth, environmental, atmospheric, and oceanographic sciences. Illustrated with remotely sensed colo

  8. Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling.

    Science.gov (United States)

    Walz, Yvonne; Wegmann, Martin; Leutner, Benjamin; Dech, Stefan; Vounatsou, Penelope; N'Goran, Eliézer K; Raso, Giovanna; Utzinger, Jürg

    2015-01-01

    Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d'Ivoire using high- and moderate-resolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixel-based modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

  9. Remotely sensed monitoring of small reservoir dynamics: a Bayesian approach

    NARCIS (Netherlands)

    Eilander, D.M.; Annor, F.O.; Iannini, L.; Van de Giesen, N.C.

    2014-01-01

    Multipurpose small reservoirs are important for livelihoods in rural semi-arid regions. To manage and plan these reservoirs and to assess their hydrological impact at a river basin scale, it is important to monitor their water storage dynamics. This paper introduces a Bayesian approach for monitorin

  10. High resolution remote sensing image segmentation based on graph theory and fractal net evolution approach

    Science.gov (United States)

    Yang, Y.; Li, H. T.; Han, Y. S.; Gu, H. Y.

    2015-06-01

    Image segmentation is the foundation of further object-oriented image analysis, understanding and recognition. It is one of the key technologies in high resolution remote sensing applications. In this paper, a new fast image segmentation algorithm for high resolution remote sensing imagery is proposed, which is based on graph theory and fractal net evolution approach (FNEA). Firstly, an image is modelled as a weighted undirected graph, where nodes correspond to pixels, and edges connect adjacent pixels. An initial object layer can be obtained efficiently from graph-based segmentation, which runs in time nearly linear in the number of image pixels. Then FNEA starts with the initial object layer and a pairwise merge of its neighbour object with the aim to minimize the resulting summed heterogeneity. Furthermore, according to the character of different features in high resolution remote sensing image, three different merging criterions for image objects based on spectral and spatial information are adopted. Finally, compared with the commercial remote sensing software eCognition, the experimental results demonstrate that the efficiency of the algorithm has significantly improved, and the result can maintain good feature boundaries.

  11. Optical remote sensing

    CERN Document Server

    Prasad, Saurabh; Chanussot, Jocelyn

    2011-01-01

    Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data: challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, patter

  12. REMOTE SENSING IN OCEANOGRAPHY.

    Science.gov (United States)

    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

  13. Optical Remote Sensing Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Optical Remote Sensing Laboratory deploys rugged, cutting-edge electro-optical instrumentation for the collection of various event signatures, with expertise in...

  14. Remotely Sensed Monitoring of Small Reservoir Dynamics: A Bayesian Approach

    Directory of Open Access Journals (Sweden)

    Dirk Eilander

    2014-01-01

    Full Text Available Multipurpose small reservoirs are important for livelihoods in rural semi-arid regions. To manage and plan these reservoirs and to assess their hydrological impact at a river basin scale, it is important to monitor their water storage dynamics. This paper introduces a Bayesian approach for monitoring small reservoirs with radar satellite images. The newly developed growing Bayesian classifier has a high degree of automation, can readily be extended with auxiliary information and reduces the confusion error to the land-water boundary pixels. A case study has been performed in the Upper East Region of Ghana, based on Radarsat-2 data from November 2012 until April 2013. Results show that the growing Bayesian classifier can deal with the spatial and temporal variability in synthetic aperture radar (SAR backscatter intensities from small reservoirs. Due to its ability to incorporate auxiliary information, the algorithm is able to delineate open water from SAR imagery with a low land-water contrast in the case of wind-induced Bragg scattering or limited vegetation on the land surrounding a small reservoir.

  15. Theory and approach of information retrievals from electromagnetic scattering and remote sensing

    CERN Document Server

    Jin, Ya-Qiu

    2006-01-01

    Covers several hot topics in current research of electromagnetic scattering, and radiative transfer in complex and random media, polarimetric scattering and SAR imagery technology, data validation and information retrieval from space-borne remote sensing, computational electromagnetics, etc.Including both forward modelling and inverse problems, analytic theory and numerical approachesAn overall summary of the author's works during most recent yearsAlso presents some insight for future research topics.

  16. A Look-up-table Approach to Inverting Remotely Sensed Ocean Color Data

    Science.gov (United States)

    2016-06-13

    failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2006 2...REPORT TYPE 3. DATES COVERED 00-00-2006 to 00-00-2006 4. TITLE AND SUBTITLE A Look-up-table Approach to Inverting Remotely Sensed Ocean Color Data...takes into consideration the spectral response function implicitly through the radiometric calibration of multiple color filtered measurements of a

  17. Hyperspectral remote sensing

    CERN Document Server

    Eismann, Michael

    2012-01-01

    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. This book provides a holistic treatment that captures its multidisciplinary nature, emphasizing the physical principles of hyperspectral remote sensing.

  18. Improving remote sensing research and education in developing countries: Approaches and recommendations

    Science.gov (United States)

    Haack, Barry; Ryerson, Robert

    2016-03-01

    Since the 1970s, a number of different models have been used to develop basic and applied science capacities of remote sensing in developing countries. Those efforts have had varied levels of success. One of the more effective capacity building efforts is extended training workshops held within the targeted developing country institution with existing resources. The extending training format requires participant teams to complete a remote sensing project for their country in their organization. The basic science activity of developing country scientists was documented by a review of six remote sensing journals which determined that a very small percentage of remote sensing manuscript authors are from developing countries. Many developing countries have established internal remote sensing capacities but many others have not. Given the potential importance of remote sensing for natural resource assessment and monitoring as well as economic decision making, more attention must be given to assisting those countries in hardware, software, internet capacity and technical assistance.

  19. A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals

    Directory of Open Access Journals (Sweden)

    W. T. Crow

    2009-01-01

    Full Text Available A number of recent studies have focused on enhancing runoff prediction via the assimilation of remotely-sensed surface soil moisture retrievals into a hydrologic model. The majority of these approaches have viewed the problem from purely a state or parameter estimation perspective in which remotely-sensed soil moisture estimates are assimilated to improve the characterization of pre-storm soil moisture conditions in a hydrologic model, and consequently, its simulation of runoff response to subsequent rainfall. However, recent work has demonstrated that soil moisture retrievals can also be used to filter errors present in satellite-based rainfall accumulation products. This result implies that soil moisture retrievals have potential benefit for characterizing both antecedent moisture conditions (required to estimate sub-surface flow intensities and subsequent surface runoff efficiencies and storm-scale rainfall totals (required to estimate the total surface runoff volume. In response, this work presents a new sequential data assimilation system that exploits remotely-sensed surface soil moisture retrievals to simultaneously improve estimates of both pre-storm soil moisture conditions and storm-scale rainfall accumulations. Preliminary testing of the system, via a synthetic twin data assimilation experiment based on the Sacramento hydrologic model and data collected from the Model Parameterization Experiment, suggests that the new approach is more efficient at improving stream flow predictions than data assimilation techniques focusing solely on the constraint of antecedent soil moisture conditions.

  20. Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook

    National Research Council Canada - National Science Library

    Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Raso, Giovanna; Utzinger, Jürg

    2015-01-01

    .... Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support...

  1. Remote sensing image registration approach based on a retrofitted SIFT algorithm and Lissajous-curve trajectories.

    Science.gov (United States)

    Song, Zhi-li; Li, Sheng; George, Thomas F

    2010-01-18

    Through retrofitting the descriptor of a scale-invariant feature transform (SIFT) and developing a new similarity measure function based on trajectories generated from Lissajous curves, a new remote sensing image registration approach is constructed, which is more robust and accurate than prior approaches. In complex cases where the correct rate of feature matching is below 20%, the retrofitted SIFT descriptor improves the correct rate to nearly 100%. Mostly, the similarity measure function makes it possible to quantitatively analyze the temporary change of the same geographic position.

  2. Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

    Science.gov (United States)

    Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

    2016-11-01

    The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

  3. Quantifying Phycocyanin Concentration in Cyanobacterial Algal Blooms from Remote Sensing Reflectance-A Quasi Analytical Approach

    Science.gov (United States)

    Mishra, S.; Mishra, D. R.; Tucker, C.

    2011-12-01

    Cyanobacterial harmful algal blooms (CHAB) are notorious for depleting dissolved oxygen level, producing various toxins, causing threats to aquatic life, altering the food-web dynamics and the overall ecosystem functioning in inland lakes, estuaries, and coastal waters. Most of these algal blooms produce various toxins that can damage cells, tissues and even cause mortality of living organisms. Frequent monitoring of water quality in a synoptic scale has been possible by the virtue of remote sensing techniques. In this research, we present a novel technique to monitor CHAB using remote sensing reflectance products. We have modified a multi-band quasi analytical algorithm that determines phytoplankton absorption coefficients from above surface remote sensing reflectance measurements using an inversion method. In situ hyperspectral remote sensing reflectance data were collected from several highly turbid and productive aquaculture ponds. A novel technique was developed to further decompose the phytoplankton absorption coefficients at 620 nm and obtain phycocyanin absorption coefficient at the same wavelength. An empirical relationship was established between phycocyanin absorption coefficients at 620 nm and measured phycocyanin concentrations. Model calibration showed strong relationship between phycocyanin absorption coefficients and phycocyanin pigment concentration (r2=0.94). Validation of the model in a separate dataset produced a root mean squared error of 167 mg m-3 (phycocyanin range: 26-1012 mg m-3). Results demonstrate that the new approach will be suitable for quantifying phycocyanin concentration in cyanobacteria dominated turbid productive waters. Band architecture of the model matches with the band configuration of the Medium Resolution Imaging Spectrometer (MERIS) and assures that MERIS reflectance products can be used to quantify phycocyanin in cyanobacterial harmful algal blooms in optically complex waters.

  4. Remote Sensing Information Gateway

    Science.gov (United States)

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

  5. A novel information transferring approach for the classification of remote sensing images

    Science.gov (United States)

    Gao, Jianqiang; Xu, Lizhong; Shen, Jie; Huang, Fengchen; Xu, Feng

    2015-12-01

    Traditional remote sensing images classification methods focused on using a large amount of labeled target data to train an efficient classification model. However, these approaches were generally based on the target data without considering a host of auxiliary data or the additional information of auxiliary data. If the valuable information from auxiliary data could be successfully transferred to the target data, the performance of the classification model would be improved. In addition, from the perspective of practical application, these valuable information from auxiliary data should be fully used. Therefore, in this paper, based on the transfer learning idea, we proposed a novel information transferring approach to improve the remote sensing images classification performance. The main rationale of this approach is that first, the information of the same areas associated with each pixel is modeled as the intra-class set, and the information of different areas associated with each pixel is modeled as the inter-class set, and then the obtained texture feature information of each area from auxiliary is transferred to the target data set such that the inter-class set is separated and intra-class set is gathered as far as possible. Experiments show that the proposed approach is effective and feasible.

  6. Modeling uncertainties in estimation of canopy LAI from hyperspectral remote sensing data - A Bayesian approach

    Science.gov (United States)

    Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

    2017-04-01

    Hyperspectral remote sensing data carry information on the leaf area index (LAI) of forests, and thus in principle, LAI can be estimated based on the data by inverting a forest reflectance model. However, LAI is usually not the only unknown in a reflectance model; especially, the leaf spectral albedo and understory reflectance are also not known. If the uncertainties of these parameters are not accounted for, the inversion of a forest reflectance model can lead to biased estimates for LAI. In this paper, we study the effects of reflectance model uncertainties on LAI estimates, and further, investigate whether the LAI estimates could recover from these uncertainties with the aid of Bayesian inference. In the proposed approach, the unknown leaf albedo and understory reflectance are estimated simultaneously with LAI from hyperspectral remote sensing data. The feasibility of the approach is tested with numerical simulation studies. The results show that in the presence of unknown parameters, the Bayesian LAI estimates which account for the model uncertainties outperform the conventional estimates that are based on biased model parameters. Moreover, the results demonstrate that the Bayesian inference can also provide feasible measures for the uncertainty of the estimated LAI.

  7. Remote-sensing based approach to forecast habitat quality under climate change scenarios

    Science.gov (United States)

    Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

    2017-01-01

    As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological

  8. Remote-sensing based approach to forecast habitat quality under climate change scenarios.

    Science.gov (United States)

    Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

    2017-01-01

    As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological

  9. Remote sensing based approach for monitoring urban growth in Mexico city, Mexico: A case study

    Science.gov (United States)

    Obade, Vincent

    The world is experiencing a rapid rate of urban expansion, largely contributed by the population growth. Other factors supporting urban growth include the improved efficiency in the transportation sector and increasing dependence on cars as a means of transport. The problems attributed to the urban growth include: depletion of energy resources, water and air pollution; loss of landscapes and wildlife, loss of agricultural land, inadequate social security and lack of employment or underemployment. Aerial photography is one of the popular techniques for analyzing, planning and minimizing urbanization related problems. However, with the advances in space technology, satellite remote sensing is increasingly being utilized in the analysis and planning of the urban environment. This article outlines the strengths and limitations of potential remote sensing techniques for monitoring urban growth. The selected methods include: Principal component analysis, Maximum likelihood classification and "decision tree". The results indicate that the "classification tree" approach is the most promising for monitoring urban change, given the improved accuracy and smooth transition between the various land cover classes

  10. A multitemporal remote sensing approach to parsimonious streamflow modeling in a southcentral Texas watershed, USA

    Directory of Open Access Journals (Sweden)

    B. P. Weissling

    2007-01-01

    Full Text Available Soil moisture condition plays a vital role in a watershed's hydrologic response to a precipitation event and is thus parameterized in most, if not all, rainfall-runoff models. Yet the soil moisture condition antecedent to an event has proven difficult to quantify both spatially and temporally. This study assesses the potential to parameterize a parsimonious streamflow prediction model solely utilizing precipitation records and multi-temporal remotely sensed biophysical variables (i.e.~from Moderate Resolution Imaging Spectroradiometer (MODIS/Terra satellite. This study is conducted on a 1420 km2 rural watershed in the Guadalupe River basin of southcentral Texas, a basin prone to catastrophic flooding from convective precipitation events. A multiple regression model, accounting for 78% of the variance of observed streamflow for calendar year 2004, was developed based on gauged precipitation, land surface temperature, and enhanced vegetation Index (EVI, on an 8-day interval. These results compared favorably with streamflow estimations utilizing the Natural Resources Conservation Service (NRCS curve number method and the 5-day antecedent moisture model. This approach has great potential for developing near real-time predictive models for flood forecasting and can be used as a tool for flood management in any region for which similar remotely sensed data are available.

  11. A Remote Sensing Approach to Estimate Vertical Profile Classes of Phytoplankton in a Eutrophic Lake

    Directory of Open Access Journals (Sweden)

    Kun Xue

    2015-10-01

    Full Text Available The extension and frequency of algal blooms in surface waters can be monitored using remote sensing techniques, yet knowledge of their vertical distribution is fundamental to determine total phytoplankton biomass and understanding temporal variability of surface conditions and the underwater light field. However, different vertical distribution classes of phytoplankton may occur in complex inland lakes. Identification of the vertical profile classes of phytoplankton becomes the key and first step to estimate its vertical profile. The vertical distribution profile of phytoplankton is based on a weighted integral of reflected light from all depths and is difficult to determine by reflectance data alone. In this study, four Chla vertical profile classes (vertically uniform, Gaussian, exponential and hyperbolic were found to occur in three in situ vertical surveys (28 May, 19–24 July and 10–12 October in a shallow eutrophic lake, Lake Chaohu. We developed and validated a classification and regression tree (CART to determine vertical phytoplankton biomass profile classes. This was based on an algal bloom index (Normalized Difference algal Bloom Index, NDBI applied to both in situ remote sensing reflectance (Rrs and MODIS Rayleigh-corrected reflectance (Rrc data in combination with data of local wind speed. The results show the potential of retrieving Chla vertical profiles information from integrated information sources following a decision tree approach.

  12. A multitemporal remote sensing approach to parsimonious streamflow modeling in a southcentral Texas watershed, USA

    Science.gov (United States)

    Weissling, B. P.; Xie, H.; Murray, K. E.

    2007-01-01

    Soil moisture condition plays a vital role in a watershed's hydrologic response to a precipitation event and is thus parameterized in most, if not all, rainfall-runoff models. Yet the soil moisture condition antecedent to an event has proven difficult to quantify both spatially and temporally. This study assesses the potential to parameterize a parsimonious streamflow prediction model solely utilizing precipitation records and multi-temporal remotely sensed biophysical variables (i.e.~from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite). This study is conducted on a 1420 km2 rural watershed in the Guadalupe River basin of southcentral Texas, a basin prone to catastrophic flooding from convective precipitation events. A multiple regression model, accounting for 78% of the variance of observed streamflow for calendar year 2004, was developed based on gauged precipitation, land surface temperature, and enhanced vegetation Index (EVI), on an 8-day interval. These results compared favorably with streamflow estimations utilizing the Natural Resources Conservation Service (NRCS) curve number method and the 5-day antecedent moisture model. This approach has great potential for developing near real-time predictive models for flood forecasting and can be used as a tool for flood management in any region for which similar remotely sensed data are available.

  13. A Multi-Sensor Remote Sensing Approach for Railway Corridor Ground Hazard Management

    Science.gov (United States)

    Kromer, Ryan; Hutchinson, Jean; Lato, Matt; Gauthier, Dave; Edwards, Tom

    2015-04-01

    Characterizing and monitoring ground hazard processes is a difficult endeavor along mountainous transportation corridors. This is primarily due to the quantity of hazard sites, complex topography, limited and sometimes hazardous access to sites, and obstructed views. The current hazard assessment approach for Canadian railways partly relies on the ability of inspection employees to assess hazard from track level, which isn't practical in complex slope environments. Various remote sensing sensors, implemented on numerous platforms have the potential to be used in these environments. They are frequently found to be complementary in their use, however, an optimum combination of these approaches has not yet been found for an operational rail setting. In this study, we investigate various cases where remote sensing technologies have been used to characterize and monitor ground hazards along railway corridors across the Canadian network, in order to better understand failure mechanisms, identify hazard source zones and to provide early warning. Since early 2012, a series of high resolution gigapixel images, Terrestrial Laser Scanning (TLS), Aerial laser scanning (ALS), ground based photogrammetry, oblique aerial photogrammetry (from helicopter and Unmanned Aerial Vehicle (UAV) platforms), have been collected at ground hazard sites throughout the Canadian rail network. On a network level scale, comparison of sequential ALS scanning data has been found to be an ideal methodology for observing large-scale change and prioritizing high hazard sites for more detailed monitoring with terrestrial methods. The combination of TLS and high resolution gigapixel imagery at various temporal scales has allowed for a detailed characterization of the hazard level posed by the slopes, the identification of the main failure modes, an analysis of hazard activity, and the observation failure precursors such as deformation, rockfall and tension crack opening. At sites not feasible for ground

  14. LIDAR and atmosphere remote sensing

    CSIR Research Space (South Africa)

    Venkataraman, S

    2008-05-01

    Full Text Available and to consist of theory and practical exercises • Theory: Remote sensing process, Photogrammetry, introduction to multispectral, remote sensing systems, Thermal infra-red remote sensing, Active and passive remote sensing, LIDAR, Application of remotely... Aerosol measurements and cloud characteristics head2right Water vapour measurements in the lower troposphere region up to 8 km head2right Ozone measurements in the troposphere regions up to 18 km Slide 22 © CSIR 2008 www...

  15. Introduction to remote sensing

    CERN Document Server

    Campbell, James B

    2012-01-01

    A leading text for undergraduate- and graduate-level courses, this book introduces widely used forms of remote sensing imagery and their applications in plant sciences, hydrology, earth sciences, and land use analysis. The text provides comprehensive coverage of principal topics and serves as a framework for organizing the vast amount of remote sensing information available on the Web. Including case studies and review questions, the book's four sections and 21 chapters are carefully designed as independent units that instructors can select from as needed for their courses. Illustrations in

  16. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  17. Fundamentals of polarimetric remote sensing

    CERN Document Server

    Schott, John R

    2009-01-01

    This text is for those who need an introduction to polarimetric signals to begin working in the field of polarimetric remote sensing, particularly where the contrast between manmade objects and natural backgrounds are the subjects of interest. The book takes a systems approach to the physical processes involved with formation, collection, and analysis of polarimetric remote sensing data in the visible through longwave infrared. Beginning with a brief review of the polarized nature of electromagnetic energy and radiometry, Dr. Schott then introduces ways to characterize a beam of polarized ene

  18. Remote sensing in soil science.

    NARCIS (Netherlands)

    Mulders, M.A.

    1987-01-01

    This book provides coverage of remote sensing techniques and their application in soil science. A clear, step-by-step approach to the various aspects ensures that the reader will gain a good grasp of the subject so that he can apply the techniques to his own field of study. The book opens with an in

  19. Decision tree approach for classification of remotely sensed satellite data using open source support

    Indian Academy of Sciences (India)

    Richa Sharma; Aniruddha Ghosh; P K Joshi

    2013-10-01

    In this study, an attempt has been made to develop a decision tree classification (DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source data mining software. The classified image is compared with the image classified using classical ISODATA clustering and Maximum Likelihood Classifier (MLC) algorithms. Classification result based on DTC method provided better visual depiction than results produced by ISODATA clustering or by MLC algorithms. The overall accuracy was found to be 90% (kappa = 0.88) using the DTC, 76.67% (kappa = 0.72) using the Maximum Likelihood and 57.5% (kappa = 0.49) using ISODATA clustering method. Based on the overall accuracy and kappa statistics, DTC was found to be more preferred classification approach than others.

  20. EPA REMOTE SENSING RESEARCH

    Science.gov (United States)

    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...

  1. Section summary: Remote sensing

    Science.gov (United States)

    Belinda Arunarwati Margono

    2013-01-01

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

  2. Remote sensing: best practice

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Gareth [Sgurr Energy (Canada)

    2011-07-01

    This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

  3. A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding

    Science.gov (United States)

    Tattaris, Maria; Reynolds, Matthew P.; Chapman, Scott C.

    2016-01-01

    Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency. PMID:27536304

  4. A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding

    Directory of Open Access Journals (Sweden)

    Maria Tattaris

    2016-08-01

    Full Text Available Remote sensing (RS of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle, with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT and a vegetation index (NDVI, to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30-100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5-1m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 x 2.4 m due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.

  5. Analyzing initial geomorphologic processes and structures: An alternative remote sensing approach

    Science.gov (United States)

    Gerwin, Werner; Raab, Thomas; Seiffert, Thomas

    2010-05-01

    The initial phase of the ecosystem development is usually characterized by overall imbalances and, thus, a huge dynamic of the ongoing processes. Especially the formation of surface structures due to erosion and sedimentation processes alters both the morphology and behaviour of the system. However, the quantification of these processes is not trivial. Some methods like classical terrestrial erosion measurement techniques might have undesirable effects on the ecosystem itself. Others, like laser scanning techniques do not influence the system but are very cost-intensive. An alternative method might be the photogrammetric analysis of aerial photographs. This technique allows for the calculation of precise digital elevation models not only with a high spatial but also temporal resolution. The amount of erosion and sedimentation processes can be quantified if digital elevation models calculated for different moments are compared. A pilot study for an innovative and cost efficient approach was carried out to study the evolution of small-scaled landforms with special emphasis on erosion gullies. The test site for this technique was an approximately 1 ha sub-site of an artificial catchment which represents the initial stage of an establishing ecosystem with still ongoing erosive landform evolution processes. Due to the fact that the investigated catchment has been left to an unrestricted succession, disturbances by scientific measurements have to be minimized. Therefore, the comparatively cost efficient remote sensing tool was tested to overcome this methodological problem. The study was conducted in summer 2009, four years after final levelling of the catchments' surface. Aerial photographs were taken by a commercial digital camera using an innovative microdrone-based tool. The pictures were analysed using a commercial remote sensing software for digital photogrammetry to calculate digital elevation models of the site. The results of this pilot study are promising

  6. Approach and status for a unified national plan for satellite remote sensing research and development

    Science.gov (United States)

    Butera, Kristine; Okerson, David J.

    1987-01-01

    Public Law 98-365, the Land Remote-Sensing Commercialization Act of 1984, requires that the Secretary of the Department of Commerce and the Administrator of the National Aeronautics and Space Administration 'shall, within one year after the date of the Law's enactment and biennially thereafter, jointly develop and transmit to the Congress a report that includes (1) a unified national plan for remote-sensing research and development applied to the earth and its atmosphere; (2) a compilation of progress in the relevant on-going research and development activities of Federal agencies; and (3) an assessment of the state of our knowledge of the Earth and its atmosphere, the needs for additional research (including research related to operational Federal remote-sensing space programs), and opportunities available for further progress'. NASA and NOAA have organized a series of public forums to encourage interest and discussion of the national plan.

  7. Practical Approach To Building A Mid-Wave Remote Sensing System

    Energy Technology Data Exchange (ETDEWEB)

    Pyke, Benjamin J. [Univ. of Arizona, Tucson, AZ (United States)

    2017-01-01

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

  8. A Remote Sensing Based Approach For Modeling and Assessing Glacier Hazards

    Science.gov (United States)

    Huggel, C.; Kääb, A.; Salzmann, N.; Haeberli, W.; Paul, F.

    Glacier-related hazards such as ice avalanches and glacier lake outbursts can pose a significant threat to population and installations in high mountain regions. They are well documented in the Swiss Alps and the high data density is used to build up sys- tematic knowledge of glacier hazard locations and potentials. Experiences from long research activities thereby form an important basis for ongoing hazard monitoring and assessment. However, in the context of environmental changes in general, and the highly dynamic physical environment of glaciers in particular, historical experience may increasingly loose its significance with respect to impact zone of hazardous pro- cesses. On the other hand, in large and remote high mountains such as the Himalayas, exact information on location and potential of glacier hazards is often missing. There- fore, it is crucial to develop hazard monitoring and assessment concepts including area-wide applications. Remote sensing techniques offer a powerful tool to narrow current information gaps. The present contribution proposes an approach structured in (1) detection, (2) evaluation and (3) modeling of glacier hazards. Remote sensing data is used as the main input to (1). Algorithms taking advantage of multispectral, high-resolution data are applied for detecting glaciers and glacier lakes. Digital terrain modeling, and classification and fusion of panchromatic and multispectral satellite im- agery is performed in (2) to evaluate the hazard potential of possible hazard sources detected in (1). The locations found in (1) and (2) are used as input to (3). The models developed in (3) simulate the processes of lake outbursts and ice avalanches based on hydrological flow modeling and empirical values for average trajectory slopes. A probability-related function allows the model to indicate areas with lower and higher risk to be affected by catastrophic events. Application of the models for recent ice avalanches and lake outbursts show

  9. Coniferous needle-leaves, shots and canopies : a remote sensing approach

    NARCIS (Netherlands)

    Yanez Rausell, L.

    2014-01-01

    Coniferous forests are important in the regulation of the Earth’s climate and thus continuous monitoring of these ecosystems is crucial to better understand potential responses to climate change. Optical remote sensing (RS) provides powerful methods for the estimation of essential climate

  10. Establishing a sea bottom model by applying a multi-sensor acoustic remote sensing approach

    NARCIS (Netherlands)

    Siemes, K.

    2013-01-01

    Detailed information about the oceanic environment is essential for many applications in the field of marine geology, marine biology, coastal engineering, and marine operations. Especially, knowledge of the properties of the sediment body is often required. Acoustic remote sensing techniques have be

  11. Sustainable transport planning using GIS and remote sensing: an integrated approach

    Science.gov (United States)

    Giorgoudis, Marios D.; Hadjimitsis, Diofantos G.; Shiftan, Yoram

    2014-08-01

    The main advantage of using GIS is its ability to access and analyze spatially distributed data. The applications of GIS to transportation can be viewed as involving either on data retrieval; data integrator; or data analysis. The use of remote sensing can assist the retrieval of land use changes. Indeed, the integration of GIS and remote sensing will be used to fill the gap in the smart transport planning. A four step research is going to be done in order to try to integrate the usage of GIS and remote sensing to sustainable transport planning. The proposed research will be held in the city of Limassol, Cyprus. The data that are going to be used are data that are going to be collected through questionnaires, and other available data from the Cyprus Public Works Department and from the Remote Sensing Laboratory and Geo-Environment Research Lab of the Cyprus University of Technology. Overall, statistical analysis and market segmentation of data will be done, the land usage will be examined, and a scenario building on mode choice will be held. This paper presents an overview of the methodology that will be adopted.

  12. Functional classification of spatially heterogeneous environments: the Land Cover Mosaic approach in remote sensing

    NARCIS (Netherlands)

    Obbink, M.H.

    2011-01-01

    Tropical rainforest areas are difficult to classify in the digital analysis of remote sensing data because of spatial heterogeneity. Often many technical solutions are adopted to reduce the ‘problem’ of spatial heterogeneity. This thesis describes theory and methods that now use this het

  13. Coniferous needle-leaves, shots and canopies : a remote sensing approach

    NARCIS (Netherlands)

    Yanez Rausell, L.

    2014-01-01

    Coniferous forests are important in the regulation of the Earth’s climate and thus continuous monitoring of these ecosystems is crucial to better understand potential responses to climate change. Optical remote sensing (RS) provides powerful methods for the estimation of essential climate vari

  14. Advanced laser remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, J.; Czuchlewski, S.; Karl, R. [and others

    1996-11-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory. Remote measurement of wind velocities is critical to a wide variety of applications such as environmental studies, weather prediction, aircraft safety, the accuracy of projectiles, bombs, parachute drops, prediction of the dispersal of chemical and biological warfare agents, and the debris from nuclear explosions. Major programs to develop remote sensors for these applications currently exist in the DoD and NASA. At present, however, there are no real-time, three-dimensional wind measurement techniques that are practical for many of these applications and we report on two new promising techniques. The first new technique uses an elastic backscatter lidar to track aerosol patterns in the atmosphere and to calculate three dimensional wind velocities from changes in the positions of the aerosol patterns. This was first done by Professor Ed Eloranta of the University of Wisconsin using post processing techniques and we are adapting Professor Eloranta`s algorithms to a real-time data processor and installing it in an existing elastic backscatter lidar system at Los Alamos (the XM94 helicopter lidar), which has a compatible data processing and control system. The second novel wind sensing technique is based on radio-frequency (RF) modulation and spatial filtering of elastic backscatter lidars. Because of their compactness and reliability, solid state lasers are the lasers of choice for many remote sensing applications, including wind sensing.

  15. ANALYSIS OF COMBINED UAV-BASED RGB AND THERMAL REMOTE SENSING DATA: A NEW APPROACH TO CROWD MONITORING

    Directory of Open Access Journals (Sweden)

    S. Schulte

    2017-08-01

    Full Text Available Collecting vast amount of data does not solely help to fulfil information needs related to crowd monitoring, it is rather important to collect data that is suitable to meet specific information requirements. In order to address this issue, a prototype is developed to facilitate the combination of UAV-based RGB and thermal remote sensing datasets. In an experimental approach, image sensors were mounted on a remotely piloted aircraft and captured two video datasets over a crowd. A group of volunteers performed diverse movements that depict real world scenarios. The prototype is deriving the movement on the ground and is programmed in MATLAB. This novel detection approach using combined data is afterwards evaluated against detection algorithms that only use a single data source. Our tests show that the combination of RGB and thermal remote sensing data is beneficial for the field of crowd monitoring regarding the detection of crowd movement.

  16. Efficient approach to designing a Schmidt-Cassegrain objective for a remote sensing satellite.

    Science.gov (United States)

    Tawfik, Tamer M

    2009-12-10

    This paper presents an efficient approach to designing a Schmidt-Cassegrain objective for a remote sensing satellite. The objective is required to have multispectral operational bands, with three spectral channels distributed along the range (0.5 to 0.9 mum), as well as a panchromatic channel; 4 degrees field of view; distortion smaller than 0.3%; and a modulation transfer function, at 50 lines/mm spatial frequency, better than 0.5 and 0.35 at the center and edge of the field of view. The proposed design approach is based on Slyusarev's theory of aberrations and optical design. An image quality index is formulated as a function of optical system component powers and axial distances. For each combination of parameters, there exists a possible solution that can be realized into a thin lens system by solving Seidel sum equations. The final design is then reached by a simple and quick optimization step. The best three designs are compared in terms of initial values of optical system parameters and final design specifications. The best system image quality is thoroughly analyzed. All three presented designs meet and exceed the required design specifications.

  17. Jellyfish prediction of occurrence from remote sensing data and a non-linear pattern recognition approach

    Science.gov (United States)

    Albajes-Eizagirre, Anton; Romero, Laia; Soria-Frisch, Aureli; Vanhellemont, Quinten

    2011-11-01

    Impact of jellyfish in human activities has been increasingly reported worldwide in recent years. Segments such as tourism, water sports and leisure, fisheries and aquaculture are commonly damaged when facing blooms of gelatinous zooplankton. Hence the prediction of the appearance and disappearance of jellyfish in our coasts, which is not fully understood from its biological point of view, has been approached as a pattern recognition problem in the paper presented herein, where a set of potential ecological cues was selected to test their usefulness for prediction. Remote sensing data was used to describe environmental conditions that could support the occurrence of jellyfish blooms with the aim of capturing physical-biological interactions: forcing, coastal morphology, food availability, and water mass characteristics are some of the variables that seem to exert an effect on jellyfish accumulation on the shoreline, under specific spatial and temporal windows. A data-driven model based on computational intelligence techniques has been designed and implemented to predict jellyfish events on the beach area as a function of environmental conditions. Data from 2009 over the NW Mediterranean continental shelf have been used to train and test this prediction protocol. Standard level 2 products are used from MODIS (NASA OceanColor) and MERIS (ESA - FRS data). The procedure for designing the analysis system can be described as following. The aforementioned satellite data has been used as feature set for the performance evaluation. Ground truth has been extracted from visual observations by human agents on different beach sites along the Catalan area. After collecting the evaluation data set, the performance between different computational intelligence approaches have been compared. The outperforming one in terms of its generalization capability has been selected for prediction recall. Different tests have been conducted in order to assess the prediction capability of the

  18. A novel approach to co registering multi-temporal remotely sensed data in a vulnerability monitoring framework

    Science.gov (United States)

    Harb, Mostapha; De Vecchi, Daniele; Dell'Acqua, Fabio

    2014-05-01

    The paper introduces a novel approach for the geometric co registration of optical remote sensing imagery. In the context of disaster mitigation and preparedness, a multi-temporal set of several remote sensing images often has to be processed separately to extract the required information. Then, a comparison among the obtained results would provide clues towards the time-evolving extent and distribution of risk. Therefore, it is of significant importance to achieve a proper geometric matching among the compared images. The traditional procedure of using manually-determined ground control points is not viable for large stacks of images, and automated methods may fail short of ensuring image conformity. The established method uses image data itself to effectively perform the co registration among the images relying on feature extraction and matching, without the necessity of using ground control points (GCPs). The approach has been tested using both high and medium resolution images on different test cases in a context of multi-risk vulnerability monitoring. The obtained results were highly promising in resolving the mismatching problem of objects in images taken from different dates and allowing smooth extraction of vulnerability proxies from multi-temporal moderate resolution optical satellite images. In conclusion, the methodology would be a useful contribution towards easing the tracking of temporal variation of ground features in the wide domain of risk-related application of remote sensing (e.g. urban development, deforestation, wild fire, damage assessment...) Keywords: Risk monitoring, remote sensing, optical imagery, geometric co registration

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

    Science.gov (United States)

    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.

  20. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  1. Remote Sensing and the Earth.

    Science.gov (United States)

    Brosius, Craig A.; And Others

    This document is designed to help senior high school students study remote sensing technology and techniques in relation to the environmental sciences. It discusses the acquisition, analysis, and use of ecological remote data. Material is divided into three sections and an appendix. Section One is an overview of the basics of remote sensing.…

  2. Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

    Science.gov (United States)

    Smith, James A.; Blattner, Tim; Messmer, Peter

    2010-01-01

    The broad-scale reductions and shifts that may be expected under climate change in the availability and quality of stopover habitat for long-distance migrants is an area of increasing concern for conservation biologists. Researchers generally have taken two broad approaches to the modeling of migration behaviour to understand the impact of these changes on migratory bird populations. These include models based on causal processes and their response to environmental stimulation, "mechanistic models", or models that primarily are based on observed animal distribution patterns and the correlation of these patterns with environmental variables, i.e. "data driven" models. Investigators have applied the latter technique to forecast changes in migration patterns with changes in the environment, for example, as might be expected under climate change, by forecasting how the underlying environmental data layers upon which the relationships are built will change over time. The learned geostatstical correlations are then applied to the modified data layers.. However, this is problematic. Even if the projections of how the underlying data layers will change are correct, it is not evident that the statistical relationships will remain the same, i.e. that the animal organism may not adapt its' behaviour to the changing conditions. Mechanistic models that explicitly take into account the physical, biological, and behaviour responses of an organism as well as the underlying changes in the landscape offer an alternative to address these shortcomings. The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies enable the application of the mechanistic models to predict how continental bird migration patterns may change in response to environmental change. In earlier work, we simulated the impact of effects of wetland loss and inter-annual variability on the fitness of

  3. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  4. Remote Sensing Approach for Documenting the Conversion of Mangroves to Aquaculture

    Science.gov (United States)

    Peneva, E.

    2007-12-01

    The loss of mangrove forests to aquaculture, particularly shrimp farming, in coastal Thailand presents serious environmental and societal problems. Shrimp farming is one of the fastest growing aquaculture sectors in many parts of the world, as well as one of the most controversial. In spite of considerable work put into understanding the impacts of shrimp aquaculture, few studies provide detailed assessment of the issue through time. This research compares three change detection techniques (Object-based; Change Vector Analysis (CVA); and Integrated GIS and Remote Sensing) in order to assess the mangrove conversion caused by aquaculture development in Krabi Province, Thailand between 1989, 2001 and 2007 using Landsat TM data. All three methods provide valuable information though each has its own merits. Preliminary results show 40% loss of mangroves between 1989 and 2007, 25% of which is to aquaculture development, 10% to urban, and 5% to agricultural land. This study will help establish a methodology that will aid coastal communities in Southeast Asia in determining sustainable land use management approaches.

  5. An optical remote sensing approach for ecological monitoring of red and green Noctiluca scintillans.

    Science.gov (United States)

    Baliarsingh, S K; Dwivedi, R M; Lotliker, Aneesh A; Sahu, K C; Kumar, T Srinivasa; Shenoi, S S C

    2017-07-01

    An ecosystem disruptive bloom of red Noctiluca scintillans (hereafter Noctiluca) was observed in coastal waters of the north-western Bay of Bengal during April 2014. Based on the principle of phytoplankton group/species specific remote sensing reflectance (Rrs), a technique of detecting green Noctiluca and diatom was developed earlier using Rrs at 443, 488, and 531 nm of Moderate Imaging Spectroradiometer-Aqua (MODIS). This was appropriately modified to detect bloom of red Noctiluca in coastal waters of the Bay of Bengal. Additional Rrs data at longer wavelengths viz. 667 and 678 nm were included in the existing algorithm, and the spectral shapes were accounted to detect the bloom of red Noctiluca. The classification scheme discriminates red Noctiluca from the green form of the same species and diatom. Phytoplankton group/species products were generated using the modified approach and validated with the reported events of red and green Noctiluca blooms in the Indian coastal waters. The present study also highlights two specific results based on MODIS retrieved time-series phytoplankton group/species image analysis: first, the observation of coexistence of diatom, red, and green Noctiluca in coastal waters of the north-western Bay of Bengal, and the second, phytoplankton community shift resulting in red/green Noctiluca proliferation following diatom.

  6. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

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

    Science.gov (United States)

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

    2016-06-01

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

  8. Developing Remote Sensing Applications Through an Engineering Life Cycle Development Approach

    Science.gov (United States)

    Kalluri, S.; Gilruth, P.

    2005-12-01

    Remote sensing applications have become an integral part of several federal and state government agencies for the monitoring and management of natural resources, land use planning and disaster mitigation. Traditionally, remote sensing applications were developed within the academic research community and these algorithms were adopted by the users for various applications. However, it is not a common practice within the academic environment to involve the end users in all stages of the research and development process. During 2000-2005, NASA funded several remote sensing application development projects under the Synergy program to promote the use of Earth Observing System (EOS) satellite data within the federal, state and local agencies. Several universities were funded around the US to develop applications in precision agriculture, management of water and other natural resources, urban planning, disaster mitigation and human health. Each application was aimed at providing spatial datasets derived from EOS satellites as decision aid tools for users within various agencies. One of the important lessons learned within this project was that a planned life cycle development improves the transition of remote sensing research to operations. The application lifecycle can be broadly divided into three stages: user needs and technical feasibility analysis, prototype development, and production and deployment. There are several checks within each phase to ensure that the final operational system adequately meets users needs. Metrics were instituted to track how the applications were being used and to plan improvements. While metrics such as web hits and data downloads could be automated and quantified, other metrics such as benefits to society and environment, impacts on policy, and other institutional benefits were difficult to quantify and monetize. Nonetheless, the metrics were useful for project management and to achieve project goals. Specific examples of applications

  9. Review of Machine Learning Approaches for Biomass and Soil Moisture Retrievals from Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Iftikhar Ali

    2015-12-01

    Full Text Available The enormous increase of remote sensing data from airborne and space-borne platforms, as well as ground measurements has directed the attention of scientists towards new and efficient retrieval methodologies. Of particular importance is the consideration of the large extent and the high dimensionality (spectral, temporal and spatial of remote sensing data. Moreover, the launch of the Sentinel satellite family will increase the availability of data, especially in the temporal domain, at no cost to the users. To analyze these data and to extract relevant features, such as essential climate variables (ECV, specific methodologies need to be exploited. Among these, greater attention is devoted to machine learning methods due to their flexibility and the capability to process large number of inputs and to handle non-linear problems. The main objective of this paper is to provide a review of research that is being carried out to retrieve two critically important terrestrial biophysical quantities (vegetation biomass and soil moisture from remote sensing data using machine learning methods.

  10. REMOTE SENSING AND GIS APPROACHES TOWARD SUSTAINABLE MANAGEMENT OF MARINE AQUACULTURE IN INDONESIA

    Directory of Open Access Journals (Sweden)

    I Nyoman Radiarta

    2013-12-01

    Full Text Available The sustainable marine aquaculture (mariculture has become increasingly important with the dramatic growth of the sector. To ensure long-term sustainability, planning is an important process that will stimulate and guide the evaluation of the sector. Many of the mariculture issues are entirely spatial in nature (e.g. siting, zoning, or have important spatial elements (potential mariculture areas, impact of mariculture, competition for space with other users. Satellite remote sensing integrated with geographic information systems (GIS can play a major role in all geographic and spatial aspects of the development and management of mariculture. The potential capabilities of evolving GIS and remote sensing for the sustainability of mariculture provide a powerful tool for the efficient and cost effective management. These technologies are also useful for facilitating the decision making process in relation to mariculture. In this paper attempt to simply describe a number of ways in which GIS and remote sensing could be usefully employed as an aid to support sustainable mariculture development.

  11. Sensitivity analysis in remote sensing

    CERN Document Server

    Ustinov, Eugene A

    2015-01-01

    This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...

  12. Remote Sensing and Imaging Physics

    Science.gov (United States)

    2012-03-07

    Program Manager AFOSR/RSE Air Force Research Laboratory Remote Sensing and Imaging Physics 7 March 2012 Report Documentation Page Form...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Remote Sensing And Imaging Physics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...Imaging of Space Objects •Information without Imaging •Predicting the Location of Space Objects • Remote Sensing in Extreme Conditions •Propagation

  13. Integrating spatial statistics and remote sensing.

    NARCIS (Netherlands)

    Stein, A.; Bastiaanssen, W.G.M.; Bruin, de S.; Cracknell, A.P.; Curran, P.J.; Fabbri, A.G.; Gorte, B.G.H.; Groenigen, van J.W.; Meer, van der F.D.; Saldana, A.

    1998-01-01

    This paper presents an integrated approach towards spatial statistics for remote sensing. Using the layer concept in Geographical Information Systems we treat successively elements of spatial statistics, scale, classification, sampling and decision support. The layer concept allows to combine contin

  14. Spatially Explicit Large Area Biomass Estimation: Three Approaches Using Forest Inventory and Remotely Sensed Imagery in a GIS

    Science.gov (United States)

    Wulder, Michael A.; White, Joanne C.; Fournier, Richard A.; Luther, Joan E.; Magnussen, Steen

    2008-01-01

    Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the area of interest (i.e., inventories not spatially exhaustive), or by the omission of inventory attributes required for biomass estimation. These spatial and attributional gaps in the forest inventory may result in an underestimation of large area AGB. The continuous nature and synoptic coverage of remotely sensed data have led to their increased application for AGB estimation over large areas, although the use of these data remains challenging in complex forest environments. In this paper, we present an approach to generating spatially explicit estimates of large area AGB by integrating AGB estimates from multiple data sources; 1. using a lookup table of conversion factors applied to a non-spatially exhaustive forest inventory dataset (R2 = 0.64; RMSE = 16.95 t/ha), 2. applying a lookup table to unique combinations of land cover and vegetation density outputs derived from remotely sensed data (R2 = 0.52; RMSE = 19.97 t/ha), and 3. hybrid mapping by augmenting forest inventory AGB estimates with remotely sensed AGB estimates where there are spatial or attributional gaps in the forest inventory data. Over our 714,852 ha study area in central Saskatchewan, Canada, the AGB estimate generated from the forest inventory was approximately 40 Mega tonnes (Mt); however, the inventory estimate represents only 51% of the total study area. The AGB estimate generated from the remotely sensed outputs that overlap those made from the forest inventory based approach differ by only 2 %; however in total, the remotely sensed estimate is 30 % greater (58 Mt) than the estimate generated from the forest inventory when the entire study area is accounted for. Finally, using the hybrid approach, whereby

  15. Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

    Science.gov (United States)

    Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

    2015-01-01

    Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

  16. Asthma Early Warning System in New York City (aewsnyc) Using Remote Sensing Approaches

    Science.gov (United States)

    Hassebo, Yasser; Rahman, Zahidur

    2011-06-01

    Asthma is estimated to affect approximately 17.3 million Americans, including 5 million children less than 18 years of age. Of these 5 million children, 1.3 million are less than 5 years of age. Asthma is a major public health problem in NYC particularly in Bronx. 12.5% of new Yorkers have been diagnosed with asthma. 300,000 children in NYC have been diagnosed with asthma up to year of 2000. NYC children were almost twice as likely to be hospitalized due to asthma attacks as the average of US child in 2000. Queens county's diesel pollution risk ranks as the 10th unhealthiest in the US compared to over than 3000 counties. Asthma symptoms are consistent with exposure to a high level of a respiratory irritant gas, smoke fume, vapor, aerosol, particulate matter (PM10 and PM2.5), and dust. Some types these environmental gaseous such as sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) can exacerbate preexisting respiratory symptoms in the short-term. Control of air pollution related diseases such as asthma, cancer, and bronchitis is difficult and inefficient due to the uncertainty in the air pollution transportation. Asthma control relies on air pollution detection and reduction. Asthma control can be improved by applying spatial tools such as Remote Sensing (RS), Geographical Information Systems (GIS). The project long-term goal is to develop a model to predict an Asthma Early Warning System for NYC (AEWSNYC), using two approaches: (1) satellite data error correction collaboratively with (2) Ground-based multiwavelength lidar measurements and NASA back trajectory tools. The proposed method can be used to create an efficient asthma control model globally.

  17. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  18. A Remote-Sensing Mission

    Science.gov (United States)

    Hotchkiss, Rose; Dickerson, Daniel

    2008-01-01

    Sponsored by NASA and the JASON Education Foundation, the remote Sensing Earth Science Teacher Education Program (RSESTeP) trains teachers to use state-of-the art remote-sensing technology with the idea that participants bring back what they learn and incorporate it into Earth science lessons using technology. The author's participation in the…

  19. Merging Alternate Remotely-Sensed Soil Moisture Retrievals Using a Non-Static Model Combination Approach

    Directory of Open Access Journals (Sweden)

    Seokhyeon Kim

    2016-06-01

    Full Text Available Soil moisture is an important variable in the coupled hydrologic and climate system. In recent years, microwave-based soil moisture products have been shown to be a viable alternative to in situ measurements. A popular way to measure the performance of soil moisture products is to calculate the temporal correlation coefficient (R against in situ measurements or other appropriate reference datasets. In this study, an existing linear combination method improving R was modified to allow for a non-static or nonstationary model combination as the basis for improving remotely-sensed surface soil moisture. Previous research had noted that two soil moisture products retrieved using the Japan Aerospace Exploration Agency (JAXA and Land Parameter Retrieval Model (LPRM algorithms from the same Advanced Microwave Scanning Radiometer 2 (AMSR2 sensor are spatially complementary in terms of R against a suitable reference over a fixed period. Accordingly, a linear combination was proposed to maximize R using a set of spatially-varying, but temporally-fixed weights. Even though this approach showed promising results, there was room for further improvements, in particular using non-static or dynamic weights that take account of the time-varying nature of the combination algorithm being approximated. The dynamic weighting was achieved by using a moving window. A number of different window sizes was investigated. The optimal weighting factors were determined for the data lying within the moving window and then used to dynamically combine the two parent products. We show improved performance for the dynamically-combined product over the static linear combination. Generally, shorter time windows outperform the static approach, and a 60-day time window is suggested to be the optimum. Results were validated against in situ measurements collected from 124 stations over different continents. The mean R of the dynamically-combined products was found to be 0.57 and 0

  20. An artificial neural network approach to estimate evapotranspiration from remote sensing and AmeriFlux data

    Institute of Scientific and Technical Information of China (English)

    Zhuoqi CHEN; Runhe SHI; Shupeng Zhang

    2013-01-01

    A simple and accurate method to estimate evapotranspiration (ET) is essential for dynamic monitoring of the Earth system at a large scale.In this paper,we developed an artificial neural network (ANN) model forced by remote sensing and AmeriFlux data to estimate ET.First,the ANN was trained with ET measurements made at 13 AmeriFlux sites and land surface products derived from satellite remotely sensed data (normalized difference vegetation index,land surface temperature and surface net radiation) for the period 2002-2006.ET estimated with the ANN was then validated by ET observed at five AmeriFlux sites during the same period.The validation sites covered five different vegetation types and were not involved in the ANN training.The coefficient of determination (R2) value for comparison between estimated and measured ET was 0.77,the root-meansquare error was 0.62 mm/d,and the mean residual was -0.28.The simple model developed in this paper captured the seasonal and interarnual variation features of ET on the whole.However,the accuracy of estimated ET depended on the vegetation types,among which estimated ET showed the best result for deciduous broadleaf forest compared to the other four vegetation types.

  1. Denoising approach for remote sensing image based on anisotropic diffusion and wavelet transform algorithm

    Science.gov (United States)

    Wang, Xiaojun; Lai, Weidong

    2011-08-01

    In this paper, a combined method have been put forward for one ASTER detected image with the wavelet filter to attenuate the noise and the anisotropic diffusion PDE(Partial Differential Equation) for further recovering image contrast. The model is verified in different noising background, since the remote sensing image usually contains salt and pepper, Gaussian as well as speckle noise. Considered the features that noise existing in wavelet domain, the wavelet filter with Bayesian estimation threshold is applied for recovering image contrast from the blurring background. The proposed PDE are performing an anisotropic diffusion in the orthogonal direction, thus preserving the edges during further denoising process. Simulation indicates that the combined algorithm can more effectively recover the blurred image from speckle and Gauss noise background than the only wavelet denoising method, while the denoising effect is also distinct when the pepper-salt noise has low intensity. The combined algorithm proposed in this article can be integrated in remote sensing image analyzing to obtain higher accuracy for environmental interpretation and pattern recognition.

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

    Science.gov (United States)

    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.

  3. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    Directory of Open Access Journals (Sweden)

    M. Marshall

    2013-03-01

    Full Text Available Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET, a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET, driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

  4. A Dynamic Remote Sensing Data-Driven Approach for Oil Spill Simulation in the Sea

    Directory of Open Access Journals (Sweden)

    Jining Yan

    2015-05-01

    Full Text Available In view of the fact that oil spill remote sensing could only generate the oil slick information at a specific time and that traditional oil spill simulation models were not designed to deal with dynamic conditions, a dynamic data-driven application system (DDDAS was introduced. The DDDAS entails both the ability to incorporate additional data into an executing application and, in reverse, the ability of applications to dynamically steer the measurement process. Based on the DDDAS, combing a remote sensor system that detects oil spills with a numerical simulation, an integrated data processing, analysis, forecasting and emergency response system was established. Once an oil spill accident occurs, the DDDAS-based oil spill model receives information about the oil slick extracted from the dynamic remote sensor data in the simulation. Through comparison, information fusion and feedback updates, continuous and more precise oil spill simulation results can be obtained. Then, the simulation results can provide help for disaster control and clean-up. The Penglai, Xingang and Suizhong oil spill results showed our simulation model could increase the prediction accuracy and reduce the error caused by empirical parameters in existing simulation systems. Therefore, the DDDAS-based detection and simulation system can effectively improve oil spill simulation and diffusion forecasting, as well as provide decision-making information and technical support for emergency responses to oil spills.

  5. An introduction to quantitative remote sensing. [data processing

    Science.gov (United States)

    Lindenlaub, J. C.; Russell, J.

    1974-01-01

    The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

  6. Signal processing for remote sensing

    CERN Document Server

    Chen, CH

    2007-01-01

    Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seism

  7. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available (s)) is the data vector for a pixel located at s θ(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba...(s) is an unknown ground class to which pixel s belongs Objective is to classify the pixel at location s to the one of the k clusters Classification of remotely sensed images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image...

  8. AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION

    Institute of Scientific and Technical Information of China (English)

    Fu Wei; Xing Guangzhong; Hou Lantian; Qin Qiming; Wang Wenjun

    2006-01-01

    In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection.

  9. Novel Approach for Estimating Nitrogen Content in Paddy Fields Using Low Altitude Remote Sensing System

    Science.gov (United States)

    Saberioon, M. M.; Gholizadeh, A.

    2016-06-01

    Concerns over the use of nitrogen have been increasing due to the high cost of fertilizers and environmental pollutions caused by excess nitrogen application in agricultural fields. Several methods are available to assess the amount of nitrogen in crops, however, they are expensive, time-consuming, inaccurate, and/or require specialists to operate the tools. Researcher recently suggested remote sensing and specifically Low Altitude Remote Sensing (LARS) system of chlorophyll content in crop canopies as a low-cost alternative to estimate plant nitrogen status. The main objective of this study was to develop and test a new Vegetation Index (VI) to determine the status of nitrogen and chlorophyll content in rice leaf by analysing and considering all Visible (Vis) bands. Besides, capability of introduced VI has compared with all known VIs in both Vis and Near Infrared (NIR) bands in canopy scale. To develop the VI, images from 6-pannel leaf colour chart were acquired using Basler Scout scA640-70fc under light-emitting diode lighting, in which principal component analysis was used to retain the lower order principal component to develop a new index called IPCA. A conventional digital camera mounted to an Unmanned Aerial Vehicle (UAV) was also used to acquire images over the rice canopy in Vis bands. Simultaneously, Tetracam agriculture digital camera was employed to acquire rice canopy image in Vis-NIR bands. The results indicated that the proposed index at canopy (r = 0.78) scale could be used as a sensor to determine the status of chlorophyll content consequently for monitoring nitrogen in rice plant through different growth stages. Moreover, results confirmed that a lowcost LARS system would be suited for high spatial and temporal resolution images and data analysis for proper assessment of key nutrients in crop farming in a fast, inexpensive and non-destructive way.

  10. Using remote sensing products to classify landscape. A multi-spatial resolution approach

    Science.gov (United States)

    García-Llamas, Paula; Calvo, Leonor; Álvarez-Martínez, José Manuel; Suárez-Seoane, Susana

    2016-08-01

    The European Landscape Convention encourages the inventory and characterization of landscapes for environmental management and planning actions. Among the range of data sources available for landscape classification, remote sensing has substantial applicability, although difficulties might arise when available data are not at the spatial resolution of operational interest. We evaluated the applicability of two remote sensing products informing on land cover (the categorical CORINE map at 30 m resolution and the continuous NDVI spectral index at 1 km resolution) in landscape classification across a range of spatial resolutions (30 m, 90 m, 180 m, 1 km), using the Cantabrian Mountains (NW Spain) as study case. Separate landscape classifications (using topography, urban influence and land cover as inputs) were accomplished, one per each land cover dataset and spatial resolution. Classification accuracy was estimated through confusion matrixes and uncertainty in terms of both membership probability and confusion indices. Regarding landscape classifications based on CORINE, both typology and number of landscape classes varied across spatial resolutions. Classification accuracy increased from 30 m (the original resolution of CORINE) to 90m, decreasing towards coarser resolutions. Uncertainty followed the opposite pattern. In the case of landscape classifications based on NDVI, the identified landscape patterns were geographically structured and showed little sensitivity to changes across spatial resolutions. Only the change from 1 km (the original resolution of NDVI) to 180 m improved classification accuracy. The value of confusion indices increased with resolution. We highlight the need for greater effort in selecting data sources at the suitable spatial resolution, matching regional peculiarities and minimizing error and uncertainty.

  11. Detecting surface coal mining areas from remote sensing imagery: an approach based on object-oriented decision trees

    Science.gov (United States)

    Zeng, Xiaoji; Liu, Zhifeng; He, Chunyang; Ma, Qun; Wu, Jianguo

    2017-01-01

    Detecting surface coal mining areas (SCMAs) using remote sensing data in a timely and an accurate manner is necessary for coal industry management and environmental assessment. We developed an approach to effectively extract SCMAs from remote sensing imagery based on object-oriented decision trees (OODT). This OODT approach involves three main steps: object-oriented segmentation, calculation of spectral characteristics, and extraction of SCMAs. The advantage of this approach lies in its effective integration of the spectral and spatial characteristics of SCMAs so as to distinguish the mining areas (i.e., the extracting areas, stripped areas, and dumping areas) from other areas that exhibit similar spectral features (e.g., bare soils and built-up areas). We implemented this method to extract SCMAs in the eastern part of Ordos City in Inner Mongolia, China. Our results had an overall accuracy of 97.07% and a kappa coefficient of 0.80. As compared with three other spectral information-based methods, our OODT approach is more accurate in quantifying the amount and spatial pattern of SCMAs in dryland regions.

  12. Remote sensing of oil slicks

    Digital Repository Service at National Institute of Oceanography (India)

    Fondekar, S.P.; Rao, L.V.G.

    the drawback of expensive conventional surveying methods. An airborne remote sensing system used for monitoring and surveillance of oil comprises different sensors such as side-looking airborne radar, synthetic aperture radar, infrared/ultraviolet line scanner...

  13. Scale issues in remote sensing

    CERN Document Server

    Weng, Qihao

    2014-01-01

    This book provides up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. The book is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as a supplemental reading for graduate level students.

  14. A new approach to accurate validation of remote sensing retrieval of evapotranspiration based on data fusion

    Directory of Open Access Journals (Sweden)

    C. Sun

    2010-03-01

    Full Text Available The study presented a new method of validating the remote-sensing (RS retrieval of evapotranspiration (ET under the support of a distributed hydrological model: Soil and Water Assessment Tool (SWAT. In this method, the output runoff data based on a fusion of ET data, meteorological data and rainfall data, etc. were compared with the observed runoff data, so as to carry out validation analysis. A new pattern of validating the ET data obtained from RS retrieval, which was more appropriate than the conventional means of observing the ET at several limited stations based on eddy covariance, was proposed. It has integrated the advantage of high requirement of ET with high spatial resolution in the distributed hydrological model and that of the capacity of providing ET with high spatial resolution in RS methods.

    First, the ET data in five years (2000–2004 were retrieved with RS according to the principle of energy balance. The temporal/spatial ditribution of monthly ET data and related causes were analyzed in the year of 2000, and the monthly ET in the five years was calculated according to the PM model. Subsequently, the results of the RS retrieval of ET and the PM-based ET calculation were compared and validated. Finnaly, the ET data obtained from RS retrieval was evaluated with the new method, under the support of SWAT, meteorologic data, Digital Elevation Model (DEM, landuse data and soil data, etc. as the input, being compared with the PM-based ET.

    According to the ET data analysis, it can be inferred that the ET obtained from RS retrieval was more continuous and stable with less saltation, while the PM-based ET presented saltation, especially in the year of 2000 and 2001. The correlation coefficient between the monthly ET in two methods reaches 0.8914, which could be explained by the influence from clouds and the inadequate representativeness of the meteorologic stations. Moreover, the PM-based ET was smaller than the ET

  15. Data Quality in Remote Sensing

    Science.gov (United States)

    Batini, C.; Blaschke, T.; Lang, S.; Albrecht, F.; Abdulmutalib, H. M.; Barsi, Á.; Szabó, G.; Kugler, Zs.

    2017-09-01

    The issue of data quality (DQ) is of growing importance in Remote Sensing (RS), due to the widespread use of digital services (incl. apps) that exploit remote sensing data. In this position paper a body of experts from the ISPRS Intercommission working group III/IVb "DQ" identifies, categorises and reasons about issues that are considered as crucial for a RS research and application agenda. This ISPRS initiative ensures to build on earlier work by other organisations such as IEEE, CEOS or GEO, in particular on the meritorious work of the Quality Assurance Framework for Earth Observation (QA4EO) which was established and endorsed by the Committee on Earth Observation Satellites (CEOS) but aims to broaden the view by including experts from computer science and particularly database science. The main activities and outcomes include: providing a taxonomy of DQ dimensions in the RS domain, achieving a global approach to DQ for heterogeneous-format RS data sets, investigate DQ dimensions in use, conceive a methodology for managing cost effective solutions on DQ in RS initiatives, and to address future challenges on RS DQ dimensions arising in the new era of the big Earth data.

  16. Unsupervised change detection in VHR remote sensing imagery - an object-based clustering approach in a dynamic urban environment

    Science.gov (United States)

    Leichtle, Tobias; Geiß, Christian; Wurm, Michael; Lakes, Tobia; Taubenböck, Hannes

    2017-02-01

    Monitoring of changes is one of the most important inherent capabilities of remote sensing. The steadily increasing amount of available very-high resolution (VHR) remote sensing imagery requires highly automatic methods and thus, largely unsupervised concepts for change detection. In addition, new procedures that address this challenge should be capable of handling remote sensing data acquired by different sensors. Thereby, especially in rapidly changing complex urban environments, the high level of detail present in VHR data indicates the deployment of object-based concepts for change detection. This paper presents a novel object-based approach for unsupervised change detection with focus on individual buildings. First, a principal component analysis together with a unique procedure for determination of the number of relevant principal components is performed as a predecessor for change detection. Second, k-means clustering is applied for discrimination of changed and unchanged buildings. In this manner, several groups of object-based difference features that can be derived from multi-temporal VHR data are evaluated regarding their discriminative properties for change detection. In addition, the influence of deviating viewing geometries when using VHR data acquired by different sensors is quantified. Overall, the proposed workflow returned viable results in the order of κ statistics of 0.8-0.9 and beyond for different groups of features, which demonstrates its suitability for unsupervised change detection in dynamic urban environments. With respect to imagery from different sensors, deviating viewing geometries were found to deteriorate the change detection result only slightly in the order of up to 0.04 according to κ statistics, which underlines the robustness of the proposed approach.

  17. A hidden state space modeling approach for improving glacier surface velocity estimates using remotely sensed data

    Science.gov (United States)

    Henke, D.; Schubert, A.; Small, D.; Meier, E.; Lüthi, M. P.; Vieli, A.

    2014-12-01

    A new method for glacier surface velocity (GSV) estimates is proposed here which combines ground- and space-based measurements with hidden state space modeling (HSSM). Examples of such a fusion of physical models with remote sensing (RS) observations were described in (Henke & Meier, Hidden State Space Models for Improved Remote Sensing Applications, ITISE 2014, p. 1242-1255) and are currently adapted for GSV estimation. GSV can be estimated using in situ measurements, RS methods or numerical simulations based on ice-flow models. In situ measurements ensure high accuracy but limited coverage and time consuming field work, while RS methods offer regular observations with high spatial coverage generally not possible with in situ methods. In particular, spaceborne Synthetic Aperture Radar (SAR) can obtain useful images independent of daytime and cloud cover. A ground portable radar interferometer (GPRI) is useful for investigating a particular area in more detail than is possible from space, but provides local coverage only. Several processing methods for deriving GSV from radar sensors have been established, including interferometry and offset tracking (Schubert et al, Glacier surface velocity estimation using repeat TerraSAR-X images. ISPRS Journal of P&RS, p. 49-62, 2013). On the other hand, it is also possible to derive glacier parameters from numerical ice-flow modeling alone. Given a well-parameterized model, GSV can in theory be derived and propagated continuously in time. However, uncertainties in the glacier flow dynamics and model errors increase with excessive propagation. All of these methods have been studied independently, but attempts to combine them have only rarely been made. The HSSM we propose recursively estimates the GSV based on 1) a process model making use of temporal and spatial interdependencies between adjacent states, and 2) observations (RS and optional in situ). The in situ and GPRI images currently being processed were acquired in the

  18. Remote Sensing of Environmental Pollution

    Science.gov (United States)

    North, G. W.

    1971-01-01

    Environmental pollution is a problem of international scope and concern. It can be subdivided into problems relating to water, air, or land pollution. Many of the problems in these three categories lend themselves to study and possible solution by remote sensing. Through the use of remote sensing systems and techniques, it is possible to detect and monitor, and in some cases, identify, measure, and study the effects of various environmental pollutants. As a guide for making decisions regarding the use of remote sensors for pollution studies, a special five-dimensional sensor/applications matrix has been designed. The matrix defines an environmental goal, ranks the various remote sensing objectives in terms of their ability to assist in solving environmental problems, lists the environmental problems, ranks the sensors that can be used for collecting data on each problem, and finally ranks the sensor platform options that are currently available.

  19. Derivative vegetation indices as a new approach in remote sensing of vegetation

    Institute of Scientific and Technical Information of China (English)

    Svetlana M.KOCHUBEY; Taras A.KAZANTSEV

    2012-01-01

    This paper focuses on the advantages of derivative vegetation indices over simple reflectancebased indices that are traditionally used for remote sensing of vegetation.The idea of using reflectance derivatives instead of simple reflectance spectra was proposed several decades ago.Despite this,it has not been widely used in monitoring systems because the derivatives lack reliable parameters.In addition,most satellite monitoring systems are not equipped with hyperspectral sensors,which are considered necessary for operating with the reflectance derivatives.Here,we present original data indicating that the chlorophyll-related derivative index D725/D702 we derived can be accurately estimated from a reflectance spectrum of 10 nm resolution that would be suitable for most satellite-based sensors.Furthermore,the index is not sensitive to soil reflectance and can therefore be used for testing of open crops.Presence of blanc reflectance is also unnecessary.Preliminary results of index testing are presented.Perspectives on using this and other derivative indices are discussed.

  20. Remote sensing approach to map riparian vegetation of the Colorado River Ecosystem, Grand Canyon area, Arizona

    Science.gov (United States)

    Nguyen, U.; Glenn, E.; Nagler, P. L.; Sankey, J. B.

    2015-12-01

    Riparian zones in the southwestern U.S. are usually a mosaic of vegetation types at varying states of succession in response to past floods or droughts. Human impacts also affect riparian vegetation patterns. Human- induced changes include introduction of exotic species, diversion of water for human use, channelization of the river to protect property, and other land use changes that can lead to deterioration of the riparian ecosystem. This study explored the use of remote sensing to map an iconic stretch of the Colorado River in the Grand Canyon National Park, Arizona. The pre-dam riparian zone in the Grand Canyon was affected by annual floods from spring run-off from the watersheds of Green River, the Colorado River and the San Juan River. A pixel-based vegetation map of the riparian zone in the Grand Canyon, Arizona, was produced from high-resolution aerial imagery. The map was calibrated and validated with ground survey data. A seven-step image processing and classification procedure was developed based on a suite of vegetation indices and classification subroutines available in ENVI Image Processing and Analysis software. The result was a quantitative species level vegetation map that could be more accurate than the qualitative, polygon-based maps presently used on the Lower Colorado River. The dominant woody species in the Grand Canyon are now saltcedar, arrowweed and mesquite, reflecting stress-tolerant forms adapted to alternated flow regimes associated with the river regulation.

  1. Estuarine Sediment Deposition during Wetland Restoration: A GIS and Remote Sensing Modeling Approach

    Science.gov (United States)

    Newcomer, Michelle; Kuss, Amber; Kentron, Tyler; Remar, Alex; Choksi, Vivek; Skiles, J. W.

    2011-01-01

    Restoration of the industrial salt flats in the San Francisco Bay, California is an ongoing wetland rehabilitation project. Remote sensing maps of suspended sediment concentration, and other GIS predictor variables were used to model sediment deposition within these recently restored ponds. Suspended sediment concentrations were calibrated to reflectance values from Landsat TM 5 and ASTER using three statistical techniques -- linear regression, multivariate regression, and an Artificial Neural Network (ANN), to map suspended sediment concentrations. Multivariate and ANN regressions using ASTER proved to be the most accurate methods, yielding r2 values of 0.88 and 0.87, respectively. Predictor variables such as sediment grain size and tidal frequency were used in the Marsh Sedimentation (MARSED) model for predicting deposition rates for three years. MARSED results for a fully restored pond show a root mean square deviation (RMSD) of 66.8 mm (<1) between modeled and field observations. This model was further applied to a pond breached in November 2010 and indicated that the recently breached pond will reach equilibrium levels after 60 months of tidal inundation.

  2. Examining Spatiotemporal Urbanization Patterns in Kathmandu Valley, Nepal: Remote Sensing and Spatial Metrics Approaches

    Directory of Open Access Journals (Sweden)

    Rajesh Bahadur Thapa

    2009-09-01

    Full Text Available This paper examines the spatiotemporal pattern of urbanization in Kathmandu Valley using remote sensing and spatial metrics techniques. The study is based on 33-years of time series data compiled from satellite images. Along with new developments within the city fringes and rural villages in the valley, shifts in the natural environment and newly developed socioeconomic strains between residents are emerging. A highly dynamic spatial pattern of urbanization is observed in the valley. Urban built-up areas had a slow trend of growth in the 1960s and 1970s but have grown rapidly since the 1980s. The urbanization process has developed fragmented and heterogeneous land use combinations in the valley. However, the refill type of development process in the city core and immediate fringe areas has shown a decreasing trend in the neighborhood distances between land use patches, and an increasing trend towards physical connectedness, which indicates a higher probability of homogenous landscape development in the upcoming decades.

  3. A new approach to dual-band polarimetric radar remote sensing image classification

    Institute of Scientific and Technical Information of China (English)

    XU Junyi; YANG Jian; PENG Yingning

    2005-01-01

    It is very important to efficiently represent the target scattering characteristics in applications of polarimetric radar remote sensing. Three probability mass functions are introduced in this paper for target representation: using similarity parameters to describe target average scattering mechanism, using the eigenvalues of a target coherency matrix to describe target scattering randomness, and using radar received power to describe target scattering intensity. The concept of cross-entropy is employed to measure the difference between two scatterers based on the probability mass functions. Three parts of difference between scatterers are measured separately as the difference of average scattering mechanism, the difference of scattering randomness and the difference of scattering intensity, so that the usage of polarimetric data can be highly efficient and flexible. The supervised/unsupervised image classification schemes and their simplified versions are established based on the minimum cross-entropy principle. They are demonstrated to have better classification performance than the maximum likelihood classifier based on the Wishart distribution assumption, both in supervised and in unsupervised classification.

  4. Remote sensing and GIS approach for water-well site selection, southwest Iran

    Science.gov (United States)

    Rangzan, K.; Charchi, A.; Abshirini, E.; Dinger, J.

    2008-01-01

    The Pabdeh-Lali Anticline of northern Khuzestan province is located in southwestern Iran and occupies 790 km2. This structure is situated in the Zagros folded belt. As a result of well-developed karst systems in the anticlinal axis, the water supply potential is high and is drained by many peripheral springs. However, there is a scarcity of water for agriculture and population centers on the anticlinal flanks, which imposes a severe problem in terms of area development. This study combines remotely sensed (RS) data and a geographical information system (GIS) into a RSGIS technique to delineate new areas for groundwater development and specific sites for drilling productive water wells. Toward these goals, RS data were used to develop GIS layers for lithology, structural geology, topographic slope, elevation, and drainage density. Field measurements were made to create spring-location and groundwater-quality GIS layers. Subsequently, expert choice and relational methods were used in a GIS environment to conjunctively analyze all layers to delineate preferable regions and 43 individual sites in which to drill water wells. Results indicate that the most preferred areas are, in preferential order, within recent alluvial deposits, the Bakhtiyari Conglomerates, and the Aghajari Sandstone. The Asmari Limestone and other units have much lower potential for groundwater supplies. Potential usefulness of the RSGIS method was indicated when six out of nine producing wells recently drilled by the Khozestan Water and Power Authority (which had no knowledge of this study) were located in areas preferentially selected by this technique.

  5. Application of Remote Sensing and Participatory Soil Erosion Assessment Approach for Soil Erosion Mapping in a Watershed

    Directory of Open Access Journals (Sweden)

    Krishna Prasad BHANDARI

    2014-10-01

    Full Text Available This research addresses the problem of soil erosion in the Phewa watershed, Pokhara, Nepal, through remote sensing application of the Revised Universal Soil Loss Equation (RUSLE model, and Participatory Geographic Information System (PGIS based Erosion Damage Assessment (EDA. Acceleration of soil erosion is due to anthropogenic factors, such as construction of roads without conservation, intensive agriculture, and socio-economic activities. The aim of the study is to identify the major causes of soil erosion by application of remote sensing; RUSLE and PGIS based EDA for soil erosion reduction management. The methodologies employed include structured questionnaires, focus groups, stakeholders’ sketches, and application of remote sensing and GIS on RUSLE model. The RUSLE model results indicate that the rate of soil erosion in the Phewa watershed varies from 0 to 206.78 t/ha/yr, and the mean annual rate of soil loss was 14.71 t/ha/yr in 2010. The PGIS based EDA resulted in different classes of severity (stable, slight, moderate, severe, very severe which were similar to the quantified results of RUSLE, except for the dense forest class in Land Use and Land Cover (LULC. Erosion-prone maps were developed through PGIS based EDA by stakeholders and use of the RUSLE model. Maps showed that the soil erosion risk areas were similar on both maps. The stakeholders’ sketched map, with knowledge gained from PGIS based EDA, RS and GIS technology for their conservation practices, could help to reduce soil erosion. The study identifies that the major issues are soil and agriculture management practices, and concludes that there is a link between RS and GIS and the estimated erosion by the RUSLE model. Thus, the RS and GIS techniques and PGIS based EDA approach can benefit stakeholders in applying better measures for soil erosion management.

  6. Photogrammetry - Remote Sensing and Geoinformation

    Science.gov (United States)

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

    2012-07-01

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

  7. Investigating chlorophyll and nitrogen levels of mangroves at Al-Khor, Qatar: an integrated chemical analysis and remote sensing approach.

    Science.gov (United States)

    Al-Naimi, Noora; Al-Ghouti, Mohammad A; Balakrishnan, Perumal

    2016-05-01

    Mangroves are unique ecosystems that dominate tropical and subtropical coastlines around the world. They provide shelter and nursery to wide variety of species such as fish and birds. Around 73 species of mangroves were recognized around the world. In Qatar, there is only one mangrove species Avicennia marina that is predominant along the northeastern coast. Assessing the health of these valuable ecosystems is vital for protection, management, and conservation of those resources. In this study, an integrated approach of chemical and remote sensing analysis was implemented to investigate the current status of the mangrove trees in Al-Khor, Qatar. Fifteen different A. marina trees from different locations in the mangrove forest were examined for their chlorophyll and nitrogen content levels. Soil analysis was also conducted to understand the effect of moisture on nitrogen availability. Results shows that currently, mangroves are in a good status in terms of nitrogen availability and chlorophyll levels which are related and both are key factors for photosynthesis. Remote sensing techniques were used for chlorophyll prediction. The results showed that these methods have the potential to be used for chlorophyll prediction and estimation.

  8. Mesquite encroachment impact on southern New Mexico rangelands: remote sensing and geographic information systems approach

    Science.gov (United States)

    Mohamed, Ahmed H.; Holechek, Jerry L.; Bailey, Derek W.; Campbell, Carol L.; Demers, Michael N.

    2011-01-01

    Honey mesquite (Prosopis glandulosa Torr.) invasion can negatively impact grazing capacity, spatial livestock distribution, and forage production in Chihuahuan Desert rangelands. High spatial resolution remote sensing data can be used to develop maps of shrub encroachment for arid rangelands. The objective of this study was to map changes in honey mesquite abundance and to evaluate honey mesquite impacts on perennial grass production at the Chihuahuan Desert Rangeland Research Center in south-central New Mexico using high resolution satellite imagery. The project employed QuickBird ortho-ready satellite imagery with spatial resolution of 2.4 m in multispectral bands and panchromatic resolution of 0.6 m for the study area on May 19, 2009. We used a maximum likelihood supervised classification algorithm to distinguish honey mesquite from other land cover categories. We then measured grass production (kg/ha) in May, 2009 on 10 permanent, evenly spaced key areas in each pasture. We identified 12×60 m plots from the classified map and used these to calculate honey mesquite canopy cover on the 40 transects across the study area. Areas classified as dominated by honey mesquite estimated from image analyses encompassed 143, 50, 92, and 136 hectares in pastures 1, 4, 14, and 15, respectively. Regression analyses showed that increasing levels of honey mesquite canopy cover corresponded to lower perennial grass forage production (r2 = 0.73, n = 40). Our findings indicate that classification of high-resolution satellite imagery is a very useful tool for mapping invasive shrubs and determining their influence on forage production in desert landscapes.

  9. Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Palubinskas, G.

    2016-06-01

    Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods `better' satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald's protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property `better' should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

  10. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... of the compendium, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state......-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  11. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    The Remote Sensing in Wind Energy Compendium provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind this compendium began in year 2008 at Risø DTU during the first PhD Summer School: Remote Sensing in Wind Energy. Thus...... in the Meteorology and Test and Measurements Programs from the Wind Energy Division at Risø DTU in the PhD Summer Schools. We hope to add more topics in future editions and to update as necessary, to provide a truly state-of-the-art compendium available for people involved in Remote Sensing in Wind Energy....

  12. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Badger, Merete

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art ‘guideline’ available for people involved in Remote Sensing...... in Wind Energy....

  13. Remote Sensing for Wind Energy

    DEFF Research Database (Denmark)

    Peña, Alfredo; Hasager, Charlotte Bay; Lange, Julia

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risø) during the first PhD Summer School: Remote Sensing in Wind Energy...... for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

  14. Remote sensing for urban planning

    Science.gov (United States)

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

    1994-01-01

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

  15. The Fundamental Framework of Remote Sensing Validation System

    Science.gov (United States)

    Jiang, X.-G.; Xi, X.-H.; Wu, M.-J.; Li, Z.-L.

    2009-04-01

    Remote sensing is a very complicated course. It is influenced by many factors, such as speciality of remote sensing sensor, radiant transmission characteristic of atmosphere, work environment of remote sensing platform, data transmission, data reception, data processing, and property of observed object etc. Whether the received data is consistent with the design specifications? Can the data meet the demands of remote sensing applications? How about the accuracy of the data products, retrieval products and application products of remote sensing? It is essential to carry out the validation to assess the data quality and application potential. Validation is effective approach to valuate remote sensing products. It is the significant link between remote sensing data and information. Research on remote sensing validation is very important for sensor development, data quality analysis and control. This paper focuses on the study of remote sensing validation and validation system. Different from the previous work done by other researchers, we study the validation from the viewpoint of systematic engineering considering that validation is involved with many aspects as talked about. Validation is not just a single and simple course. It is complicated system. Validation system is the important part of whole earth observation system. First of all, in this paper the category of remote sensing validation is defined. Remote sensing validation includes not only the data products validation, but also the retrieval products validation and application products validation. Second, the new concept, remote sensing validation system, is proposed. Then, the general framework, software structure and functions of validation system are studied and put forward. The validation system is composed of validation field module, data acquirement module, data processing module, data storage and management module, data scaling module, and remote sensing products validation module. And finally the

  16. An improved approach for remotely sensing water stress impacts on forest C uptake.

    Science.gov (United States)

    Sims, Daniel A; Brzostek, Edward R; Rahman, Abdullah F; Dragoni, Danilo; Phillips, Richard P

    2014-09-01

    Given that forests represent the primary terrestrial sink for atmospheric CO2 , projections of future carbon (C) storage hinge on forest responses to climate variation. Models of gross primary production (GPP) responses to water stress are commonly based on remotely sensed changes in canopy 'greenness' (e.g., normalized difference vegetation index; NDVI). However, many forests have low spectral sensitivity to water stress (SSWS) - defined here as drought-induced decline in GPP without a change in greenness. Current satellite-derived estimates of GPP use a vapor pressure deficit (VPD) scalar to account for the low SWSS of forests, but fail to capture their responses to water stress. Our objectives were to characterize differences in SSWS among forested and nonforested ecosystems, and to develop an improved framework for predicting the impacts of water stress on GPP in forests with low SSWS. First, we paired two independent drought indices with NDVI data for the conterminous US from 2000 to 2011, and examined the relationship between water stress and NDVI. We found that forests had lower SSWS than nonforests regardless of drought index or duration. We then compared satellite-derived estimates of GPP with eddy-covariance observations of GPP in two deciduous broadleaf forests with low SSWS: the Missouri Ozark (MO) and Morgan Monroe State Forest (MMSF) AmeriFlux sites. Model estimates of GPP that used VPD scalars were poorly correlated with observations of GPP at MO (r(2) = 0.09) and MMSF (r(2) = 0.38). When we included the NDVI responses to water stress of adjacent ecosystems with high SSWS into a model based solely on temperature and greenness, we substantially improved predictions of GPP at MO (r(2) = 0.83) and for a severe drought year at the MMSF (r(2) = 0.82). Collectively, our results suggest that large-scale estimates of GPP that capture variation in SSWS among ecosystems could improve predictions of C uptake by forests under drought. © 2014 John Wiley & Sons

  17. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

    Science.gov (United States)

    Kilpatrick, Adam D; Lewis, Megan M; Ostendorf, Bertram

    2015-01-01

    A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural

  18. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

    Directory of Open Access Journals (Sweden)

    Adam D Kilpatrick

    Full Text Available A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2 area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction and maintenance of full 100% stocking regime (Full Stocking Maintained (P = 0.00000132. While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling

  19. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

    Science.gov (United States)

    Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

    2013-02-01

    Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was

  20. Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jingxiong; LI Deren

    2005-01-01

    This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification.By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated.It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly.Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy.Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.

  1. Remote sensing of natural phenomena

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2014-06-01

    Full Text Available There has always been a need to directly perceive and study the events whose extent is beyond people's possibilities. In order to get new data and to make observations and studying much more objective in comparison with past syntheses - a new method of examination called remote sensing has been adopted. The paper deals with the principles and elements of remote sensing, as well as with the basic aspects of using remote research in examining meteorological (weather parameters and the conditions of the atmosphere. The usage of satellite images is possible in all phases of the global and systematic research of different natural phenomena when airplane and satellite images of different characteristics are used and their analysis and interpretation is carried out by viewing and computer added procedures. Introduction Remote sensing of the Earth enables observing and studying global and local events that occur on it. Satellite images are nowadays used in geology, agriculture, forestry, geodesy, meteorology, spatial and urbanism planning, designing of infrastructure and other objects, protection from natural and technological catastrophes, etc. It it possible to use satellite images in all phases of global and systematic research of different natural phenomena. Basics of remote sensing Remote sensing is a method of the acquisition and interpretation of information about remote objects without making a physical contact with them. The term Daljinska detekcija is a literal translation of the English term Remote Sensing. In French it isTeledetection, in German - Fernerkundung, in Russian - дистанционие иследования. We also use terms such as: remote survailance, remote research, teledetection, remote methods, and distance research. The basic elements included in Remote Sensing are: object, electromagnetic energy, sensor, platform, image, analysis, interpretation and the information (data, fact. Usage of satellite remote research in

  2. Remote Sensing of Water Pollution

    Science.gov (United States)

    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.

  3. Quantifying the spatio-temporal dynamics of woody plant encroachment using an integrative remote sensing, GIS, and spatial modeling approach

    Science.gov (United States)

    Buenemann, Michaela

    Despite a longstanding universal concern about and intensive research into woody plant encroachment (WPE)---the replacement of grasslands by shrub- and woodlands---our accumulated understanding of the process has either not been translated into sustainable rangeland management strategies or with only limited success. In order to increase our scientific insights into WPE, move us one step closer toward the sustainable management of rangelands affected by or vulnerable to the process, and identify needs for a future global research agenda, this dissertation presents an unprecedented critical, qualitative and quantitative assessment of the existing literature on the topic and evaluates the utility of an integrative remote sensing, GIS, and spatial modeling approach for quantifying the spatio-temporal dynamics of WPE. Findings from this research suggest that gaps in our current understanding of WPE and difficulties in devising sustainable rangeland management strategies are in part due to the complex spatio-temporal web of interactions between geoecological and anthropogenic variables involved in the process as well as limitations of presently available data and techniques. However, an in-depth analysis of the published literature also reveals that aforementioned problems are caused by two further crucial factors: the absence of information acquisition and reporting standards and the relative lack of long-term, large-scale, multi-disciplinary research efforts. The methodological framework proposed in this dissertation yields data that are easily standardized according to various criteria and facilitates the integration of spatially explicit data generated by a variety of studies. This framework may thus provide one common ground for scientists from a diversity of fields. Also, it has utility for both research and management. Specifically, this research demonstrates that the application of cutting-edge remote sensing techniques (Multiple Endmember Spectral Mixture

  4. Remote Sensing Best Paper Award 2013

    OpenAIRE

    Prasad Thenkabail

    2013-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for 2013. Nominations were selected by the Editor-in-Chief and selected editorial board members from among all the papers published in 2009. Reviews and research papers were evaluated separately.

  5. Monitoring Land Use/Land Cover Changes in a River Basin due to Urbanization using Remote Sensing and GIS Approach

    Science.gov (United States)

    Shukla, S.; Khire, M. V.; Gedam, S. S.

    2014-11-01

    Faster pace of urbanization, industrialization, unplanned infrastructure developments and extensive agriculture result in the rapid changes in the Land Use/Land Cover (LU/LC) of the sub-tropical river basins. Study of LU/LC transformations in a river basin is crucial for vulnerability assessment and proper management of the natural resources of a river basin. Remote sensing technology is very promising in mapping the LU/LC distribution of a large region on different spatio-temporal scales. The present study is intended to understand the LU/LC changes in the Upper Bhima river basin due to urbanization using modern geospatial techniques such as remote sensing and GIS. In this study, the Upper Bhima river basin is divided into three adjacent sub-basins: Mula-Mutha sub-basin (ubanized), Bhima sub-basin (semi-urbanized) and Ghod sub-basin (unurbanized). Time series LU/LC maps were prepared for the study area for a period of 1980, 2002 and 2009 using satellite datasets viz. Landsat MSS (October, 1980), Landsat ETM+ (October, 2002) and IRS LISS III (October 2008 and November 2009). All the satellite images were classified into five LU/LC classes viz. built-up lands, agricultural lands, waterbodies, forests and wastelands using supervised classification approach. Post classification change detection method was used to understand the LU/LC changes in the study area. Results reveal that built up lands, waterbodies and agricultural lands are increasing in all the three sub-basins of the study area at the cost of decreasing forests and wastelands. But the change is more drastic in urbanized Mula-Mutha sub-basin compared to the other two sub-basins.

  6. Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

    Science.gov (United States)

    Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

    2017-10-01

    , with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

  7. 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).

    Science.gov (United States)

    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

  8. Remote sensing research in geographic education: An alternative view

    Science.gov (United States)

    Wilson, H.; Cary, T. K.; Goward, S. N.

    1981-01-01

    It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

  9. Remote sensing and water resources

    CERN Document Server

    Champollion, N; Benveniste, J; Chen, J

    2016-01-01

    This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives. Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of th...

  10. Remote sensing of natural resources

    CERN Document Server

    Wang, Guangxing

    2013-01-01

    "… a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. … state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources."-Yuhong He, University of Toronto Mississauga, Ontario, Canada"The list of topics covered is so complete that I would recommend the book to anyone teaching a graduate course on vegetation analysis through digital image analysis. … I recommend this book then for anyone doing advanced digital image analysis and environmental GIS courses who want to cover topics related to applied remote sensing work involving vegetation analysis."-Charles Roberts, Florida Atlantic University, Boca Raton, USA, in Economic Bota...

  11. Remote Sensing Information Science Research

    Science.gov (United States)

    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.

  12. Remote sensing in biological oceanography

    Science.gov (United States)

    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.

  13. Remote sensing for wind energy

    Energy Technology Data Exchange (ETDEWEB)

    Pena, A.; Bay Hasager, C.; Lange, J. [Technical Univ. of Denmark. DTU Wind Energy, DTU Risoe Campus, Roskilde (Denmark) (and others

    2013-06-15

    The Remote Sensing in Wind Energy report provides a description of several topics and it is our hope that students and others interested will learn from it. The idea behind it began in year 2008 at DTU Wind Energy (formerly Risoe) during the first PhD Summer School: Remote Sensing in Wind Energy. Thus it is closely linked to the PhD Summer Schools where state-of-the-art is presented during the lecture sessions. The advantage of the report is to supplement with in-depth, article style information. Thus we strive to provide link from the lectures, field demonstrations, and hands-on exercises to theory. The report will allow alumni to trace back details after the course and benefit from the collection of information. This is the third edition of the report (first externally available), after very successful and demanded first two, and we warmly acknowledge all the contributing authors for their work in the writing of the chapters, and we also acknowledge all our colleagues in the Meteorology and Test and Measurements Sections from DTU Wind Energy in the PhD Summer Schools. We hope to continue adding more topics in future editions and to update and improve as necessary, to provide a truly state-of-the-art 'guideline' available for people involved in Remote Sensing in Wind Energy. (Author)

  14. An overview of GNSS remote sensing

    Science.gov (United States)

    Yu, Kegen; Rizos, Chris; Burrage, Derek; Dempster, Andrew G.; Zhang, Kefei; Markgraf, Markus

    2014-12-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters.

  15. Remote sensing science - new concepts and applications

    Energy Technology Data Exchange (ETDEWEB)

    Gerstl, S.A.; Cooke, B.J.; Henderson, B.G.; Love, S.P.; Zardecki, A.

    1996-10-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The science and technology of satellite remote sensing is an emerging interdisciplinary field that is growing rapidly with many global and regional applications requiring quantitative sensing of earth`s surface features as well as its atmosphere from space. It is possible today to resolve structures on the earth`s surface as small as one meter from space. If this high spatial resolution is coupled with high spectral resolution, instant object identification can also be achieved. To interpret these spectral signatures correctly, it is necessary to perform a computational correction on the satellite imagery that removes the distorting effects of the atmosphere. This project studied such new concepts and applied innovative new approaches in remote sensing science.

  16. Runoff simulation using distributed hydrological modeling approach, remote sensing and GIS techniques: A case study from an Indian agricultural watershed

    Science.gov (United States)

    Chowdary, V. M.; Desai, V. R.; Gupta, M.; Jeyaram, A.; Murthy, Y. V. N. K.

    2012-07-01

    Distributed hydrological modeling has the capability of simulating distributed watershed basin processes, by dividing a heterogeneous and complex land surface divided into computational elements such as Hydrologic Response Units (HRU), grid cell or sub watersheds. The present study was taken up to simulate spatial hydrological processes from a case study area of Kansavati watershed in Purulia district of West Bengal, India having diverse geographical features using distributed hydrological modelling approach. In the present study, overland flow in terms of direct runoff from storm rainfall was computed using USDA Soil Conservation Services (SCS) curve number technique and subsequently it served as input to channel routing model. For channel flow routing, Muskingum-Cunge flood routing technique was used, specifically to route surface runoff from the different sub watershed outlet points to the outlet point of the watershed. Model parameters were derived for each grid cell either from remote sensing data or conventional maps under GIS environment. For distributed approach, validation show reasonable fit between the simulated and measured data and CMR value in all the cases is negative and ranges from -0.1 to - 0.3. Further, this study investigates the effect of cell size on runoff simulation for different grid cell sizes of 23, 46, 92, 184, 368, 736, 1472 m resolution. The difference between simulated and observed runoff values increases with the increase of grid size beyond 184 m more prominently. Further, this model can be used to evaluate futuristic water availability scenarios for an agricultural watershed in eastern India.

  17. Remote sensing using airships

    Energy Technology Data Exchange (ETDEWEB)

    Lavan, C.K. Jr. [Loral Defense Systems-Akron, OH (United States)

    1996-10-01

    Loral Defense Systems-Akron (LDSA) has developed a laser-based mine detection system in response to the US Navy`s requirements for detecting, localizing and classifying mines in deep water shipping channels. This sensor system was tested recently at the Navy`s David Taylor Research Center (DTRC) at Bethesda, MD and at the US Army`s Camp Perry near Lake Erie. The testing at Camp Perry involved installation of the sensor system on the Goodyear Tim & Rubber Company`s airship {open_quotes}Spirit of Akron{close_quotes} and the conduct of control flight test experiments over Lake Erie. Resultant imagery has been analyzed in terms of water optical properties. Further tests are planned in a multispectral mode incorporating both active illumination and passive detection. The system can be extended to the detection of Unexploded Ordnance (UXO) in government test ranges and to detection of other devices both buried and at the surface. The utility of the airship (blimp) makes the approach practical due to long endurance, wide speed range and platform flexibility. 14 figs.

  18. Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

    Directory of Open Access Journals (Sweden)

    Angela Lausch

    2017-02-01

    Full Text Available Stress in forest ecosystems (FES occurs as a result of land-use intensification, disturbances, resource limitations or unsustainable management, causing changes in forest health (FH at various scales from the local to the global scale. Reactions to such stress depend on the phylogeny of forest species or communities and the characteristics of their impacting drivers and processes. There are many approaches to monitor indicators of FH using in-situ forest inventory and experimental studies, but they are generally limited to sample points or small areas, as well as being time- and labour-intensive. Long-term monitoring based on forest inventories provides valuable information about changes and trends of FH. However, abrupt short-term changes cannot sufficiently be assessed through in-situ forest inventories as they usually have repetition periods of multiple years. Furthermore, numerous FH indicators monitored in in-situ surveys are based on expert judgement. Remote sensing (RS technologies offer means to monitor FH indicators in an effective, repetitive and comparative way. This paper reviews techniques that are currently used for monitoring, including close-range RS, airborne and satellite approaches. The implementation of optical, RADAR and LiDAR RS-techniques to assess spectral traits/spectral trait variations (ST/STV is described in detail. We found that ST/STV can be used to record indicators of FH based on RS. Therefore, the ST/STV approach provides a framework to develop a standardized monitoring concept for FH indicators using RS techniques that is applicable to future monitoring programs. It is only through linking in-situ and RS approaches that we will be able to improve our understanding of the relationship between stressors, and the associated spectral responses in order to develop robust FH indicators.

  19. A spatial-spectral approach for deriving high signal quality eigenvectors for remote sensing image transformations

    DEFF Research Database (Denmark)

    Rogge, Derek; Bachmann, Martin; Rivard, Benoit

    2014-01-01

    -line surveys, or temporal data sets as computational burden becomes significant. In this paper we present a spatial-spectral approach to deriving high signal quality eigenvectors for image transformations which possess an inherently ability to reduce the effects of noise. The approach applies a spatial...

  20. Hyperspectral Remote Sensing of Foliar Nitrogen Content

    Science.gov (United States)

    Knyazikhin, Yuri; Schull, Mitchell A.; Stenberg, Pauline; Moettus, Matti; Rautiainen, Miina; Yang, Yan; Marshak, Alexander; Carmona, Pedro Latorre; Kaufmann, Robert K.; Lewis, Philip; Disney, Mathias I.; Vanderbilt, Vern; Davis, Anthony B.; Baret, Frederic; Jacquemoud, Stephane; Lyapustin, Alexei; Myneni, Ranga B.

    2013-01-01

    A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact - it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

  1. Measurement Strategies for Remote Sensing Applications

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Theiler, J.; Smith, B.; Love, S.P.; LaDelfe, P.C.; Cooke, B.J.; Clodius, W.B.; Borel, C.C.; Bender, S.C.

    1999-03-06

    Remote sensing has grown to encompass many instruments and observations, with concomitant data from a huge number of targets. As evidenced by the impressive growth in the number of published papers and presentations in this field, there is a great deal of interest in applying these capabilities. The true challenge is to transition from directly observed data sets to obtaining meaningful and robust information about remotely sensed targets. We use physics-based end-to-end modeling and analysis techniques as a framework for such a transition. Our technique starts with quantified observables and signatures of a target. The signatures are propagated through representative atmospheres to realistically modeled sensors. Simulated data are then propagated through analysis routines, yielding measurements that are directly compared to the original target attributes. We use this approach to develop measurement strategies which ensure that our efforts provide a balanced approach to obtaining substantive information on our targets.

  2. A Hybrid Remote Sensing Approach for Detecting the Florida Red Tide

    Science.gov (United States)

    Carvalho, G. A.; Minnett, P. J.; Banzon, V.; Baringer, W.

    2008-12-01

    Harmful algal blooms (HABs) have caused major worldwide economic losses commonly linked with health problems for humans and wildlife. In the Eastern Gulf of Mexico the toxic marine dinoflagellate Karenia brevis is responsible for nearly annual, massive red tides causing fish kills, shellfish poisoning, and acute respiratory irritation in humans: the so-called Florida Red Tide. Near real-time satellite measurements could be an effective method for identifying HABs. The use of space-borne data would be a highly desired, low-cost technique offering the remote and accurate detection of K. brevis blooms over the West Florida Shelf, bringing tremendous societal benefits to the general public, scientific community, resource managers and medical health practitioners. An extensive in situ database provided by the Florida Fish and Wildlife Conservation Commission's Research Institute was used to examine the long-term accuracy of two satellite- based algorithms at detecting the Florida Red Tide. Using MODIS data from 2002 to 2006, the two algorithms are optimized and their accuracy assessed. It has been found that the sequential application of the algorithms results in improved predictability characteristics, correctly identifying ~80% of the cases (for both sensitivity and specificity, as well as overall accuracy), and exhibiting strong positive (70%) and negative (86%) predictive values.

  3. A practical and automated approach to large area forest disturbance mapping with remote sensing.

    Science.gov (United States)

    Ozdogan, Mutlu

    2014-01-01

    In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover

  4. A practical and automated approach to large area forest disturbance mapping with remote sensing.

    Directory of Open Access Journals (Sweden)

    Mutlu Ozdogan

    Full Text Available In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i creating masks for water, non-forested areas, clouds, and cloud shadows; ii identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR difference image; iii filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission, issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for

  5. Biogeochemical cycling and remote sensing

    Science.gov (United States)

    Peterson, D. L.

    1985-01-01

    Research is underway at the NASA Ames Research Center that is concerned with aspects of the nitrogen cycle in terrestrial ecosystems. An interdisciplinary research group is attempting to correlate nitrogen transformations, processes, and productivity with variables that can be remotely sensed. Recent NASA and other publications concerning biogeochemical cycling at global scales identify attributes of vegetation that could be related or explain the spatial variation in biologically functional variables. These functional variables include net primary productivity, annual nitrogen mineralization, and possibly the emission rate of nitrous oxide from soils.

  6. Innovative Approaches to Remote Sensing in NASA's Earth System Science Pathfinder (ESSP) Program

    Science.gov (United States)

    Peri, Frank; Volz, Stephen

    2013-01-01

    NASA's Earth Venture class (EV) of mission are competitively selected, Principal Investigator (PI) led, relatively low cost and narrowly focused in scientific scope. Investigations address a full spectrum of earth science objectives, including studies of the atmosphere, oceans, land surface, polar ice regions, and solid Earth. EV has three program elements: EV-Suborbital (EVS) are suborbital/airborne investigations; EV-Mission (EVM) element comprises small complete spaceborne missions; and EV-Instrument (EVI) element develops spaceborne instruments for flight as missions-of-opportunity (MoO). To ensure the success of EV, the management approach of each element is tailored according to the specific needs of the element.

  7. Remote Sensing Wind and Wind Shear System.

    Science.gov (United States)

    Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

  8. The next step in shallow coral reef monitoring: combining remote sensing and in situ approaches.

    Science.gov (United States)

    Scopélitis, Julie; Andréfouët, Serge; Phinn, Stuart; Arroyo, Lara; Dalleau, Mayeul; Cros, Annick; Chabanet, Pascale

    2010-11-01

    Most current coral reef management is supported by mapping and monitoring limited in record length and spatial extent. These deficiencies were addressed in a multidisciplinary study of cyclone impacts on Aboré Reef, New-Caledonia. Local knowledge, high thematic-resolution maps, and time-series satellite imagery complemented classical in situ monitoring methods. Field survey stations were selected from examination of pre- and post-cyclone images and their post-cyclone coral communities documented in terms of substrata, coral morphologies, live coral cover, and taxonomy. Time-series maps of hierarchically defined coral communities created at spatial scales documenting the variability among communities (29-45 classes) and suggesting the processes that affected them. The increased spatial coverage and repeatability of this approach significantly improved the recognition and interpretation of coral communities' spatio-temporal variability. It identified precise locations of impacted areas and those exhibiting coral recovery and resilience. The approach provides a comprehensive suite of information on which to base reef-scale conservation actions.

  9. A novel approach to model exposure of coastal-marine ecosystems to riverine flood plumes based on remote sensing techniques.

    Science.gov (United States)

    Álvarez-Romero, Jorge G; Devlin, Michelle; Teixeira da Silva, Eduardo; Petus, Caroline; Ban, Natalie C; Pressey, Robert L; Kool, Johnathan; Roberts, Jason J; Cerdeira-Estrada, Sergio; Wenger, Amelia S; Brodie, Jon

    2013-04-15

    Increased loads of land-based pollutants are a major threat to coastal-marine ecosystems. Identifying the affected marine areas and the scale of influence on ecosystems is critical to assess the impacts of degraded water quality and to inform planning for catchment management and marine conservation. Studies using remotely-sensed data have contributed to our understanding of the occurrence and influence of river plumes, and to our ability to assess exposure of marine ecosystems to land-based pollutants. However, refinement of plume modeling techniques is required to improve risk assessments. We developed a novel, complementary, approach to model exposure of coastal-marine ecosystems to land-based pollutants. We used supervised classification of MODIS-Aqua true-color satellite imagery to map the extent of plumes and to qualitatively assess the dispersal of pollutants in plumes. We used the Great Barrier Reef (GBR), the world's largest coral reef system, to test our approach. We combined frequency of plume occurrence with spatially distributed loads (based on a cost-distance function) to create maps of exposure to suspended sediment and dissolved inorganic nitrogen. We then compared annual exposure maps (2007-2011) to assess inter-annual variability in the exposure of coral reefs and seagrass beds to these pollutants. We found this method useful to map plumes and qualitatively assess exposure to land-based pollutants. We observed inter-annual variation in exposure of ecosystems to pollutants in the GBR, stressing the need to incorporate a temporal component into plume exposure/risk models. Our study contributes to our understanding of plume spatial-temporal dynamics of the GBR and offers a method that can also be applied to monitor exposure of coastal-marine ecosystems to plumes and explore their ecological influences. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Remote Sensing and Reflectance Profiling in Entomology.

    Science.gov (United States)

    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.

  11. Introductory remote sensing principles and concepts principles and concepts

    CERN Document Server

    Gibson, Paul

    2013-01-01

    Introduction to Remote Sensing Principles and Concepts provides a comprehensive student introduction to both the theory and application of remote sensing. This textbook* introduces the field of remote sensing and traces its historical development and evolution* presents detailed explanations of core remote sensing principles and concepts providing the theory required for a clear understanding of remotely sensed images.* describes important remote sensing platforms - including Landsat, SPOT and NOAA * examines and illustrates many of the applications of remotely sensed images in various fields.

  12. LWIR Microgrid Polarimeter for Remote Sensing Studies

    Science.gov (United States)

    2010-02-28

    Polarimeter for Remote Sensing Studies 5b. GRANT NUMBER FA9550-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1. Scott Tyo 5e. TASK...and tested at the University of Arizona, and preliminary images are shown in this final report. 15. SUBJECT TERMS Remote Sensing , polarimetry 16...7.0 LWIR Microgrid Polarimeter for Remote Sensing Studies J. Scott Tyo College of Optical Sciences University of Arizona Tucson, AZ, 85721 tyo

  13. Basic Remote Sensing Investigations for Beach Reconnaissance.

    Science.gov (United States)

    Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in

  14. Preface: Remote Sensing in Coastal Environments

    OpenAIRE

    Deepak R. Mishra; Gould, Richard W.

    2016-01-01

    The Special Issue (SI) on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology i...

  15. Change detection for Lake Burullus, Egypt using remote sensing and GIS approaches.

    Science.gov (United States)

    Mohsen, A; Elshemy, M; Zeidan, B A

    2016-12-13

    Lake Burullus is the second largest natural coastal lake in Egypt. It has an economic importance for fish yield. However, several anthropogenic activities such as industrial, agriculture, and reclamation activities lead to a deterioration of its water quality and a decrease of the water body area of the lake. This study aims to detect the spatiotemporal changes of Lake Burullus in the period 1972-2015 using 12 Landsat {(1,3-MSS), (4,5-TM), and (7-ETM+)} imageries and water indices approach. To extract water feature from imageries, the Normalized Difference Water Index (NDWI) and the Water Ratio Index (WRI) were applied. The NDWI was applied to the MSS imageries. For other TM and ETM+ imageries, the WRI was applied. Obtained results show a significant decrease in the water area of the Lake Burullus, where it lost about (49%) of its surface area during the period from the year 1972 to the year 2015. A rapid decrease in the lake surface area was noticed through the period from 1972 to 1984. A prediction model was built depending on the calculated water area of the lake. Finally, the multi-temporal maps of the lake surface area are overlaid to produce a map for the changes of the lake surface area using Geographic Information System (GIS).

  16. Characterization of the Montane Huntington Wildlife Forest Ecosystem Using Machine Learning Approaches from Remote Sensing Data

    Science.gov (United States)

    Li, Manqi

    Montane forests are susceptible to various stressors such as land use and climate change. Consequently, research on characterizing montane forest ecosystems should be conducted on a continuous basis for sustainable forest management. In this research, forest type mapping and change analysis, and biomass/carbon stock quantification were performed over a mountainous forest located in the central Adirondack Park, NY, by employing machine learning techniques at the plot level. Multi-temporal Landsat TM data were used to classify forest type cover and to detect forest cover changes for the past 20 years. Forest biomass and carbon stock quantification was then performed using full waveform LiDAR data collected in September 2011. Accuracies from the two case studies were in support of the versatility of machine learning approaches for forest and ecological investigation. Topographic characteristics affected the classification accuracy as well as the forest type change for the past 20 years. LiDAR-derived metrics, especially height-based ones, proved useful for quantifying biomass/carbon stock. Keywords: Landsat TM, full waveform LiDAR, forest classification, forest change analysis, biomass, carbon stock, machine learning

  17. Advances in Remote Sensing Approaches for Hazard Mitigation and Natural Resource Protection in Pacific Latin America: A Workshop for Advanced Graduate Students, Post- Doctoral Researchers, and Junior Faculty

    Science.gov (United States)

    Gierke, J. S.; Rose, W. I.; Waite, G. P.; Palma, J. L.; Gross, E. L.

    2008-12-01

    Though much of the developing world has the potential to gain significantly from remote sensing techniques in terms of public health and safety, they often lack resources for advancing the development and practice of remote sensing. All countries share a mutual interest in furthering remote sensing capabilities for natural hazard mitigation and resource development. With National Science Foundation support from the Partnerships in International Research and Education program, we are developing a new educational system of applied research and engineering for advancing collaborative linkages among agencies and institutions in Pacific Latin American countries (to date: Guatemala, El Salvador, Nicaragua, Costa Rica, Panama, and Ecuador) in the development of remote sensing tools for hazard mitigation and water resources management. The project aims to prepare students for careers in science and engineering through their efforts to solve suites of problems needing creative solutions: collaboration with foreign agencies; living abroad immersed in different cultures; and adapting their academic training to contend with potentially difficult field conditions and limited resources. The ultimate goal of integrating research with education is to encourage cross-disciplinary, creative, and critical thinking in problem solving and foster the ability to deal with uncertainty in analyzing problems and designing appropriate solutions. In addition to traditional approaches for graduate and undergraduate research, we have built new educational systems of applied research and engineering: (1) the Peace Corp/Master's International program in Natural Hazards which features a 2-year field assignment during service in the U.S. Peace Corps, (2) the Michigan Tech Enterprise program for undergraduates, which gives teams of students from different disciplines the opportunity to work for three years in a business-like setting to solve real-world problems, and (3) a unique university exchange

  18. Increased tree establishment in Lithuanian peat bogs--insights from field and remotely sensed approaches.

    Science.gov (United States)

    Edvardsson, Johannes; Šimanauskienė, Rasa; Taminskas, Julius; Baužienė, Ieva; Stoffel, Markus

    2015-02-01

    Over the past century an ongoing establishment of Scots pine (Pinus sylvestris L.), sometimes at accelerating rates, is noted at three studied Lithuanian peat bogs, namely Kerėplis, Rėkyva and Aukštumala, all representing different degrees of tree coverage and geographic settings. Present establishment rates seem to depend on tree density on the bog surface and are most significant at sparsely covered sites where about three-fourth of the trees have established since the mid-1990s, whereas the initial establishment in general was during the early to mid-19th century. Three methods were used to detect, compare and describe tree establishment: (1) tree counts in small plots, (2) dendrochronological dating of bog pine trees, and (3) interpretation of aerial photographs and historical maps of the study areas. In combination, the different approaches provide complimentary information but also weigh up each other's drawbacks. Tree counts in plots provided a reasonable overview of age class distributions and enabled capturing of the most recently established trees with ages less than 50 years. The dendrochronological analysis yielded accurate tree ages and a good temporal resolution of long-term changes. Tree establishment and spread interpreted from aerial photographs and historical maps provided a good overview of tree spread and total affected area. It also helped to verify the results obtained with the other methods and an upscaling of findings to the entire peat bogs. The ongoing spread of trees in predominantly undisturbed peat bogs is related to warmer and/or drier climatic conditions, and to a minor degree to land-use changes. Our results therefore provide valuable insights into vegetation changes in peat bogs, also with respect to bog response to ongoing and future climatic changes. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Remote Sensing of shallow sea floor for digital earth environment

    Science.gov (United States)

    Yahya, N. N.; Hashim, M.; Ahmad, S.

    2014-02-01

    Understanding the sea floor biodiversity requires spatial information that can be acquired from remote sensing satellite data. Species volume, spatial patterns and species coverage are some of the information that can be derived. Current approaches for mapping sea bottom type have evolved from field observation, visual interpretation from aerial photography, mapping from remote sensing satellite data along with field survey and hydrograhic chart. Remote sensing offers most versatile technique to map sea bottom type up to a certain scale. This paper reviews the technical characteristics of signal and light interference within marine features, space and remote sensing satellite. In addition, related image processing techniques that are applicable to remote sensing satellite data for sea bottom type digital mapping is also presented. The sea bottom type can be differentiated by classification method using appropriate spectral bands of satellite data. In order to verify the existence of particular sea bottom type, field observations need to be carried out with proper technique and equipment.

  20. Use of remote sensing in agriculture

    Science.gov (United States)

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

    1974-01-01

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

  1. Assessing commercial livestock appropriation of the productive capacity of US drylands: A remote sensing approach

    Science.gov (United States)

    Washington-Allen, R. A.; Mitchell, J. E.; Oslen, H. E.

    2008-12-01

    The "State of Nation's Ecosystems" by the Heinz Institute and the recent "Millennium Ecosystem Assessment of Drylands" concluded that the amount of desertification and the extent to which human management actions contribute to this process is unknown at national to global spatial scales. This is primarily due to lack of studies at these large spatial scales and the temporal scales (> a 15-year time series of data) necessary to separate the effects of anthropogenic practices from climate change on Drylands. Consequently, this research seeks to develop procedures for determining 1) the area of Drylands within the United States where commercial grazing livestock occur or the livestock ecological footprint and 2) the impact of the footprint on the US's productive capacity. Our approach has been to develop a pilot geodatabase of year 2002 data that includes administrative boundaries, the Moderate Resolution Infrared Spectroradiometer's (MODIS) measures of gross and net primary productivity (GPP and NPP, respectively), US Department of Agriculture's National Agricultural Statistics Service's (USDA-NASS) county-level data on cattle, sheep, and goat inventories, transportation and power consumption networks, dryland extent, and land cover/land use. Secondly, the ratio of 1-km2 gridded mean annual potential evapotranspiration (MAPET) to mean annual precipitation (MAP) data were used to define the 50-year mean dryland extent in accordance with the United Nations Convention to Combat Desertification's definition of Drylands, the aridity index (AI) ≤ 0.65. Urban features, including transportation, power consumption, and land use/land cover, were subtracted from this dryland map to further refine it. The NASS tabular data was then related to the counties boundary map thus producing a county-level livestock number map that was then intersected with the dryland extent map to yield the US livestock ecological footprint. Lastly, this footprint map was then converted to a

  2. Did Groundwater Processes Shape the Saharan Landscape during the Previous Wet Periods? a Remote Sensing and Geostatistical Approach

    Science.gov (United States)

    Farag, A. Z. A.; Sultan, M.; Elkadiri, R.; Abdelhalim, A.

    2014-12-01

    An integrated approach using remote sensing, landscape analysis and statistical methods was conducted to assess the role of groundwater sapping in shaping the Saharan landscape. A GIS-based logistic regression model was constructed to automatically delineate the spatial distribution of the sapping features over areas occupied by the Nubian Sandstone Aquifer System (NSAS): (1) an inventory was compiled of known locations of sapping features identified either in the field or from satellite datasets (e.g. Orbview-3 and Google Earth Digital Globe imagery); (2) spatial analyses were conducted in a GIS environment and seven geomorphological and geological predisposing factors (i.e. slope, stream density, cross-sectional and profile curvature, minimum and maximum curvature, and lithology) were identified; (3) a binary logistic regression model was constructed, optimized and validated to describe the relationship between the sapping locations and the set of controlling factors and (4) the generated model (prediction accuracy: 90.1%) was used to produce a regional sapping map over the NSAS. Model outputs indicate: (1) groundwater discharge and structural control played an important role in excavating the Saharan natural depressions as evidenced by the wide distribution of sapping features (areal extent: 1180 km2) along the fault-controlled escarpments of the Libyan Plateau; (2) proximity of mapped sapping features to reported paleolake and tufa deposits suggesting a causal effect. Our preliminary observations (from satellite imagery) and statistical analyses together with previous studies in the North Western Sahara Aquifer System (North Africa), Sinai Peninsula, Negev Desert, and The Plateau of Najd (Saudi Arabia) indicate extensive occurrence of sapping features along the escarpments bordering the northern margins of the Saharan-Arabian Desert; these areas share similar hydrologic settings with the NSAS domains and they too witnessed wet climatic periods in the Mid

  3. A Novel Remote Sensing Approach for Determining 20th Century Multi-Decadal Glacial Change Across the Antarctic Peninsula

    Science.gov (United States)

    Miller, P. E.; Mills, J. P.; Fox, A. J.; Clarke, L. E.; King, M. A.

    2014-12-01

    The Antarctic Peninsula (AP) is a mountain glacier system comprised of over 400 glaciers, and is an important contributor to historical and future sea level rise. Assessment and monitoring of AP glaciers is crucial for understanding sensitivity to climate change. However, whilst retreat of glacier fronts and the behaviour of individual glaciers has been extensively documented, wide-area assessment of AP glacier mass change is lacking. This research addresses this by unlocking a unique historical archive of aerial imagery through a remote sensing approach. This is enabling quantitative, wide-area assessment of glacier change across the AP. Understanding AP change over the 20th Century is vital for modelling future changes. However, satellite measurements span only a few decades, and to-date there has been no means of quantifying change over longer periods. However, this research presents a novel methodology to extract 3D measurements from an archive of > 30,000 aerial images dating back to the 1940s. This overcomes the requirement for ground control by employing an automated registration technique. Control is derived from digital elevations models (DEMs) generated from present-day ASTER satellite imagery. Through least squares surface matching, DEMs extracted from archival imagery are registered to scale-stable ASTER DEMs to determine relative change. This minimises offsets between the two DEMs, allowing robust determination of elevation changes. The spatial pattern of 20thC change is being assessed at 50 benchmark glaciers distributed across the AP, for periods of up to 65 years. In complement, a temporally refined assessment is being undertaken at 10 glaciers with multiple epochs of aerial imagery. Results to-date indicate a general trend of surface lowering, most notably over frontal regions. Spatial and temporal patterns of change will be used to investigate the drivers of AP change and establish a suite of benchmark glaciers for future monitoring.

  4. Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

    Science.gov (United States)

    Lo, C. P.; Quattrochi, Dale A.

    2003-01-01

    Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

  5. Vegetation cover change detection and assessment in arid environment using multi-temporal remote sensing images and ecosystem management approach

    Science.gov (United States)

    Abdelrahman Aly, Anwar; Mosa Al-Omran, Abdulrasoul; Shahwan Sallam, Abdulazeam; Al-Wabel, Mohammad Ibrahim; Shayaa Al-Shayaa, Mohammad

    2016-04-01

    Vegetation cover (VC) change detection is essential for a better understanding of the interactions and interrelationships between humans and their ecosystem. Remote sensing (RS) technology is one of the most beneficial tools to study spatial and temporal changes of VC. A case study has been conducted in the agro-ecosystem (AE) of Al-Kharj, in the center of Saudi Arabia. Characteristics and dynamics of total VC changes during a period of 26 years (1987-2013) were investigated. A multi-temporal set of images was processed using Landsat images from Landsat4 TM 1987, Landsat7 ETM+2000, and Landsat8 to investigate the drivers responsible for the total VC pattern and changes, which are linked to both natural and social processes. The analyses of the three satellite images concluded that the surface area of the total VC increased by 107.4 % between 1987 and 2000 and decreased by 27.5 % between years 2000 and 2013. The field study, review of secondary data, and community problem diagnosis using the participatory rural appraisal (PRA) method suggested that the drivers for this change are the deterioration and salinization of both soil and water resources. Ground truth data indicated that the deteriorated soils in the eastern part of the Al-Kharj AE are frequently subjected to sand dune encroachment, while the southwestern part is frequently subjected to soil and groundwater salinization. The groundwater in the western part of the ecosystem is highly saline, with a salinity ≥ 6 dS m-1. The ecosystem management approach applied in this study can be used to alike AE worldwide.

  6. Autofocus method for scanning remote sensing cameras.

    Science.gov (United States)

    Lv, Hengyi; Han, Chengshan; Xue, Xucheng; Hu, Changhong; Yao, Cheng

    2015-07-10

    Autofocus methods are conventionally based on capturing the same scene from a series of positions of the focal plane. As a result, it has been difficult to apply this technique to scanning remote sensing cameras where the scenes change continuously. In order to realize autofocus in scanning remote sensing cameras, a novel autofocus method is investigated in this paper. Instead of introducing additional mechanisms or optics, the overlapped pixels of the adjacent CCD sensors on the focal plane are employed. Two images, corresponding to the same scene on the ground, can be captured at different times. Further, one step of focusing is done during the time interval, so that the two images can be obtained at different focal plane positions. Subsequently, the direction of the next step of focusing is calculated based on the two images. The analysis shows that the method investigated operates without restriction of the time consumption of the algorithm and realizes a total projection for general focus measures and algorithms from digital still cameras to scanning remote sensing cameras. The experiment results show that the proposed method is applicable to the entire focus measure family, and the error ratio is, on average, no more than 0.2% and drops to 0% by reliability improvement, which is lower than that of prevalent approaches (12%). The proposed method is demonstrated to be effective and has potential in other scanning imaging applications.

  7. A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches

    Directory of Open Access Journals (Sweden)

    Venkateswarlu Dheeravath

    2010-01-01

    Full Text Available This paper presents an exhaustive review of global croplands and their water use, for the end of last millennium, mapped using remote sensing and non-remote sensing approaches by world’s leading researchers on the subject. A comparison at country scale of global cropland area estimated by these studies had a high R2-value of 0.89–0.94. The global cropland area estimates amongst different studies are quite close and range between 1.47–1.53 billion hectares. However, significant uncertainties exist in determining irrigated areas which, globally, consume nearly 80% of all human water use. The estimates show that the total water use by global croplands varies between 6,685 to 7,500 km3 yr−1 and of this around 4,586 km3 yr−1 is by rainfed croplands (green water use and the rest by irrigated croplands (blue water use. Irrigated areas use about 2,099 km3 yr−1 (1,180 km3 yr−1 of blue water and the rest from rain that falls over irrigated croplands. However, 1.6 to 2.5 times the blue water required by irrigated croplands is actually withdrawn from reservoirs or pumping of ground water, suggesting an irrigation efficiency of only between 40–62 percent. The weaknesses, trends, and future directions to precisely estimate the global croplands are examined. Finally, the paper links global croplands and their water use to a paradigm for ensuring future food security.

  8. Geological remote sensing in Africa

    Science.gov (United States)

    Sabins, Floyd F., Jr.; Bailey, G. Bryan; Abrams, Michael J.

    1987-01-01

    Programs using remote sensing to obtain geologic information in Africa are reviewed. Studies include the use of Landsat MSS data to evaluate petroleum resources in sedimentary rock terrains in Kenya and Sudan and the use of Landsat TM 30-m resolution data to search for mineral deposits in an ophiolite complex in Oman. Digitally enhanced multispectral SPOT data at a scale of 1:62,000 were used to map folds, faults, diapirs, bedding attitudes, and stratigraphic units in the Atlas Mountains in northern Algeria. In another study, SIR-A data over a vegetated and faulted area of Sierra Leone were compared with data collected by the Landsat MSS and TM systems. It was found that the lineaments on the SIR-A data were more easily detected.

  9. Lunar remote sensing and measurements

    Science.gov (United States)

    Moore, H.J.; Boyce, J.M.; Schaber, G.G.; Scott, D.H.

    1980-01-01

    Remote sensing and measurements of the Moon from Apollo orbiting spacecraft and Earth form a basis for extrapolation of Apollo surface data to regions of the Moon where manned and unmanned spacecraft have not been and may be used to discover target regions for future lunar exploration which will produce the highest scientific yields. Orbital remote sensing and measurements discussed include (1) relative ages and inferred absolute ages, (2) gravity, (3) magnetism, (4) chemical composition, and (5) reflection of radar waves (bistatic). Earth-based remote sensing and measurements discussed include (1) reflection of sunlight, (2) reflection and scattering of radar waves, and (3) infrared eclipse temperatures. Photographs from the Apollo missions, Lunar Orbiters, and other sources provide a fundamental source of data on the geology and topography of the Moon and a basis for comparing, correlating, and testing the remote sensing and measurements. Relative ages obtained from crater statistics and then empirically correlated with absolute ages indicate that significant lunar volcanism continued to 2.5 b.y. (billion years) ago-some 600 m.y. (million years) after the youngest volcanic rocks sampled by Apollo-and that intensive bombardment of the Moon occurred in the interval of 3.84 to 3.9 b.y. ago. Estimated fluxes of crater-producing objects during the last 50 m.y. agree fairly well with fluxes measured by the Apollo passive seismic stations. Gravity measurements obtained by observing orbiting spacecraft reveal that mare basins have mass concentrations and that the volume of material ejected from the Orientale basin is near 2 to 5 million km 3 depending on whether there has or has not been isostatic compensation, little or none of which has occurred since 3.84 b.y. ago. Isostatic compensation may have occurred in some of the old large lunar basins, but more data are needed to prove it. Steady fields of remanent magnetism were detected by the Apollo 15 and 16 subsatellites

  10. Natural Resource Information System. Remote Sensing Studies.

    Science.gov (United States)

    Leachtenauer, J.; And Others

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

  11. Remote sensing and reflectance profiling in entomology

    Science.gov (United States)

    Remote sensing is about characterizing the status of objects and/or classifies their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be ground-based, and therefore acquired at a high spatial resolutio...

  12. Planning and Implementation of Remote Sensing Experiments.

    Science.gov (United States)

    Contents: TEKTITE II experiment-upwelling detection (NASA Mx 138); Design of oceanographic experiments (Gulf of Mexico, Mx 159); Design of oceanographic experiments (Gulf of Mexico, Mx 165); Experiments on thermal pollution; Remote sensing newsletter; Symposium on remote sensing in marine biology and fishery resources.

  13. Preface: Remote Sensing of Water Resources

    OpenAIRE

    Deepak R. Mishra; Eurico J. D’Sa; Sachidananda Mishra

    2016-01-01

    The Special Issue (SI) on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  14. Technology Progress Report for Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; DONG Xiaolong; LIU Heguang

    2004-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for China's lunar exploration satellite (Chang'E-1), meteorological satellite FY-3 and ocean dynamic measurement satellite (HY-2) are reported.

  15. Digital methods and remote sensing in archaeology archaeology in the age of sensing

    CERN Document Server

    Campana, Stefano

    2016-01-01

    This volume debuts the new scope of Remote Sensing, which was first defined as the analysis of data collected by sensors that were not in physical contact with the objects under investigation (using cameras, scanners, and radar systems operating from spaceborne or airborne platforms). A wider characterization is now possible: Remote Sensing can be any non-destructive approach to viewing the buried and nominally invisible evidence of past activity. Spaceborne and airborne sensors, now supplemented by laser scanning, are united using ground-based geophysical instruments and undersea remote sensing, as well as other non-invasive techniques such as surface collection or field-walking survey. Now, any method that enables observation of evidence on or beneath the surface of the earth, without impact on the surviving stratigraphy, is legitimately within the realm of Remote Sensing. The new interfaces and senses engaged in Remote Sensing appear throughout the book. On a philosophical level, this is about the landscap...

  16. Glacial lake outburst flood risk assessment using combined approaches of remote sensing, GIS and dam break modelling

    Directory of Open Access Journals (Sweden)

    Arpit Aggarwal

    2016-01-01

    Full Text Available A great number of glacial lakes have appeared in many mountain regions across the world during the last half-century due to receding of glaciers and global warming. In the present study, glacial lake outburst flood (GLOF risk assessment has been carried out in the Teesta river basin located in the Sikkim state of India. First, the study focuses on accurate mapping of the glaciers and glacial lakes using multispectral satellite images of Landsat and Indian Remote Sensing satellites. For glacier mapping, normalized difference snow index (NDSI image and slope map of the area have been utilized. NDSI approach can identify glaciers covered with clean snow but debris-covered glaciers cannot be mapped using NDSI method alone. For the present study, slope map has been utilized along with the NDSI approach to delineate glaciers manually. Glacial lakes have been mapped by supervised maximum likelihood classification and normalized difference water index followed by manual editing afterwards using Google Earth images. Second, the first proper inventory of glacial lakes for Teesta basin has been compiled containing information of 143 glacial lakes. Third, analysis of these lakes has been carried out for identification of potentially dangerous lakes. Vulnerable lakes have been identified on the basis of parameters like surface area, position with respect to parent glacier, growth since 2009, slope, distance from the outlet of the basin, presence of supraglacial lakes, presence of other lakes in downstream, condition of moraine, condition of the terrain around them, etc. From these criterions, in total, 18 lakes have been identified as potentially dangerous glacial lakes. Out of these 18 lakes, further analysis has been carried out for the identification of the most vulnerable lake. Lake 140 comes out to be the most vulnerable for a GLOF event. Lastly, for this potentially dangerous lake, different dam break parameters have been generated using satellite data

  17. An overview of GNSS remote sensing

    OpenAIRE

    Kegen, Yu; Rizos, Chris; Burrage, Derek; Dempster, Andrew; Zhang, Kefei; Markgraf, Markus

    2014-01-01

    The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing - the atmosphere, oceans or Earth surface - was first proposed more than two decades ago. Since then, GNSS remote ...

  18. Educational activities of remote sensing archaeology (Conference Presentation)

    Science.gov (United States)

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

    2016-10-01

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

  19. Introduction to Remote Sensing Image Registration

    Science.gov (United States)

    Le Moigne, Jacqueline

    2017-01-01

    For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

  20. Remote sensing of vegetation and soil moisture

    Science.gov (United States)

    Kong, J. A.; Shin, R. T. (Principal Investigator)

    1983-01-01

    Progress in the investigation of problems related to the remote sensing of vegetation and soil moisture is reported. Specific topics addressed include: (1) microwave scattering from periodic surfaces using a rigorous modal technique; (2) combined random rough surface and volume scattering effects; (3) the anisotropic effects of vegetation structures; (4) the application of the strong fluctuation theory to the the study of electromagnetic wave scattering from a layer of random discrete scatterers; and (5) the investigation of the scattering of a plane wave obliquely incident on a half space of densely distributed spherical dielectric scatterers using a quantum mechanical potential approach.

  1. Ten ways remote sensing can contribute to conservation.

    Science.gov (United States)

    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

  2. Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

    Science.gov (United States)

    El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

    2012-12-01

    The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary

  3. MICROWAVE REMOTE SENSING IN SOIL QUALITY ASSESSMENT

    Directory of Open Access Journals (Sweden)

    S. K. Saha

    2012-08-01

    Full Text Available Information of spatial and temporal variations of soil quality (soil properties is required for various purposes of sustainable agriculture development and management. Traditionally, soil quality characterization is done by in situ point soil sampling and subsequent laboratory analysis. Such methodology has limitation for assessing the spatial variability of soil quality. Various researchers in recent past showed the potential utility of hyperspectral remote sensing technique for spatial estimation of soil properties. However, limited research studies have been carried out showing the potential of microwave remote sensing data for spatial estimation of various soil properties except soil moisture. This paper reviews the status of microwave remote sensing techniques (active and passive for spatial assessment of soil quality parameters such as soil salinity, soil erosion, soil physical properties (soil texture & hydraulic properties; drainage condition; and soil surface roughness. Past and recent research studies showed that both active and passive microwave remote sensing techniques have great potentials for assessment of these soil qualities (soil properties. However, more research studies on use of multi-frequency and full polarimetric microwave remote sensing data and modelling of interaction of multi-frequency and full polarimetric microwave remote sensing data with soil are very much needed for operational use of satellite microwave remote sensing data in soil quality assessment.

  4. Multiple classifier system for remote sensing image classification: a review.

    Science.gov (United States)

    Du, Peijun; Xia, Junshi; Zhang, Wei; Tan, Kun; Liu, Yi; Liu, Sicong

    2012-01-01

    Over the last two decades, multiple classifier system (MCS) or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird), hyperspectral image (OMISII) and multi-spectral image (Landsat ETM+). Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.

  5. Multiple Classifier System for Remote Sensing Image Classification: A Review

    Directory of Open Access Journals (Sweden)

    Yi Liu

    2012-04-01

    Full Text Available Over the last two decades, multiple classifier system (MCS or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird, hyperspectral image (OMISII and multi-spectral image (Landsat ETM+.Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.

  6. Hyperspectral remote sensing for terrestrial applications

    Science.gov (United States)

    Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Murali Krishna Gumma,; Venkateswarlu Dheeravath,

    2015-01-01

    Remote sensing data are considered hyperspectral when the data are gathered from numerous wavebands, contiguously over an entire range of the spectrum (e.g., 400–2500 nm). Goetz (1992) defines hyperspectral remote sensing as “The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element of an image it is possible to derive a complete reflectance spectrum.” However, Jensen (2004) defines hyperspectral remote sensing as “The simultaneous acquisition of images in many relatively narrow, contiguous and/or non contiguous spectral bands throughout the ultraviolet, visible, and infrared portions of the electromagnetic spectrum.

  7. An international organization for remote sensing

    Science.gov (United States)

    Helm, Neil R.; Edelson, Burton I.

    1991-01-01

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

  8. Remote sensing and urban public health

    Science.gov (United States)

    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.

  9. Preface: Remote Sensing in Coastal Environments

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-08-01

    Full Text Available The Special Issue (SI on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology in the coastal zone. This preface provides a brief summary of each article published in the SI.

  10. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  11. Analysis of potential urban unstable areas and landslide-induced damages on Volterra historical site through a remote sensing approach

    Science.gov (United States)

    Del Soldato, Matteo; Bianchini, Silvia; Nolesini, Teresa; Frodella, William; Casagli, Nicola

    2017-04-01

    Multisystem remote sensing techniques were exploited to provide a comprehensive overview of Volterra (Italy) site stability with regards to its landscape, urban fabric and cultural heritage. Interferometric Synthetic Aperture Radar (InSAR) techniques allow precise measurements of Earth surface displacement, as well as the detection of building deformations on large urban areas. In the field of cultural heritage conservation Infrared thermography (IRT) provides surface temperature mapping and therefore detects various potential criticalities, such as moisture, seepage areas, cracks and structural anomalies. Between winter 2014 and spring 2015 the historical center and south-western sectors of Volterra (Tuscany region, central Italy) were affected by instability phenomena. The spatial distribution, typology and effect on the urban fabrics of the landslide phenomena were investigated by analyzing the geological and geomorphological settings, traditional geotechnical monitoring and advanced remote sensing data such as Persistent Scatterers Interferometry (PSI). The ground deformation rates and the maximum settlement values derived from SAR acquisitions of historical ENVISAT and recent COSMO-SkyMed sensors, in 2003-2009 and 2010-2015 respectively, were compared with background geological data, constructive features, in situ evidences and detailed field inspections in order to classify landslide-damaged buildings. In this way, the detected movements and their potential correspondences with recognized damages were investigated in order to perform an assessment of the built-up areas deformations and damages on Volterra. The IRT technique was applied in order to survey the surface temperature of the historical Volterra wall-enclosure, and allowed highlighting thermal anomalies on this cultural heritage element of the site. The obtained results permitted to better correlate the landslide effects of the recognized deformations in the urban fabric, in order to provide useful

  12. An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems.

    Science.gov (United States)

    Emadi, Mostafa; Baghernejad, Majid; Pakparvar, Mojtaba; Kowsar, Sayyed Ahang

    2010-05-01

    This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0-30, 30-60, and 60-90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0-30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 x 150 m(2)) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.

  13. Hyperspectral Remote Sensing for Tropical Rain Forest

    Directory of Open Access Journals (Sweden)

    Kamaruzaman Jusoff

    2009-01-01

    Full Text Available Problem statement: Sensing, mapping and monitoring the rain forest in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions and are now included in climate change negotiations. Approach: We reviewed the potential for air and spaceborne hyperspectral sensing to identify and map individual tree species measure carbon stocks, specifically Aboveground Biomass (AGB and provide an overview of a range of approaches that have been developed and used to map tropical rain forest across a diverse set of conditions and geographic areas. We provided a summary of air and spaceborne hyperspectral remote sensing measurements relevant to mapping the tropical forest and assess the relative merits and limitations of each. We then provided an overview of modern techniques of mapping the tropical forest based on species discrimination, leaf chlorophyll content, estimating aboveground forest productivity and monitoring forest health. Results: The challenges in hyperspectral Imaging of tropical forests is thrown out to researchers in such field as to come with the latest techniques of image processing and improved mapping resolution leading towards higher precision mapping accuracy. Some research results from an airborne hyperspectral imaging over Bukit Nanas forest reserve was shared implicating high potential of such very high resolution imaging techniques for tropical mixed dipterocarp forest inventory and mapping for species discrimination, aboveground forest productivity, leaf chlorophyll content and carbon mapping. Conclusion/Recommendations: We concluded that while spaceborne hyperspectral remote sensing has often been discounted as inadequate for the task, attempts to map with airborne sensors are still insufficient in tropical developing countries like Malaysia. However, we demonstrated this with a case

  14. Suntracker for atmospheric remote sensing

    Science.gov (United States)

    Hawat, Toufic-Michel; Camy-Peyret, Claude; Torguet, Roger J.

    1998-05-01

    A heliostat is designed and built to track the sun for optical remote sensing of the stratosphere from a balloon- borne pointed gondola. The tracking mechanism is controlled by two direct torque motors used to drive a single flat acquisition mirror. A horizontal turntable, rigidly attached to the azimuth drive, supports the elevation assembly. A position sensor receiving a small part of the solar beam reflected off the main acquisition mirror is used for the fine servo control. Using a CCD camera prepointing of the acquisition mirror is achieved when the sun is in the field of view of the heliostat. This system is coupled with a high-resolution (0.02-cm-1) Fourier transform IR spectrometer to retrieve stratospheric trace species concentration profiles. The suntracker directs the solar radiation in a stable direction along the spectrometer optical axis. The pointing precision is 1 arcmin from a stratospheric gondola, which has static and dynamic angular excursions up to 6 deg. The heliostat coupled to the Limb Profile Monitor of the Atmosphere instrument performs successfully on several balloon flights. The description, ground tests, and balloon flight results of the suntracker are presented.

  15. Machine learning in geosciences and remote sensing

    Institute of Scientific and Technical Information of China (English)

    David J. Lary; Amir H. Alavi; Amir H. Gandomi; Annette L. Walker

    2016-01-01

    Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regres-sion or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the ef-ficiency of ML for tackling the geosciences and remote sensing problems.

  16. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  17. Integrating remote sensing with GIS-based multi-criteria evaluation approach for Karst rocky desertification assessment in Southwest of China

    Science.gov (United States)

    Zhang, Z.; Xu, W.; Zhou, W.; Zhang, L.; Xiao, Y.; Ou, X.; Ouyang, Z.

    2014-02-01

    The increasing exploitation of Karst resources is leading to severe environmental impacts, as Karst frequently occurs in the most fragile and vulnerable environments. This paper presents a multi-criteria evaluation (MCE) approach in a spatial context to support Karst rocky desertification (KRD) assessment by integrating remote sensing data with GIS. The study area is located in Wenshan Prefecture, Yunnan Province, Southwest of China. Criteria and impact factors for KRD first were identified and weighted through pairwise comparison method. A GIS fuzzy set membership function was then used to generate gradient effects of each criterion, and a clustering method based on K-mean algorithms was used to classify KRD into several descending rank zones (or levels). Both ROC and error matrix assessments indicated that the MCE approach is better than the NDVI approach. In addition, we found it is useful to integrate the topographic and human disturbance factors into KRD mapping and assessment, compared with most of the previous KRD assessment studies mainly focused on developing vegetation or land cover information in karst regions by using remote sensing alone. Furthermore, the integrated MCE approach is robust, flexible, and easy to be implemented. It also explicitly includes the quantitative and qualitative information, for instance, opinions of decision makers and experts as well as characteristics of the landscape.

  18. Remote sensing applications to hydrologic modeling

    Science.gov (United States)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  19. Hyperspectral remote sensing for light pollution monitoring

    Directory of Open Access Journals (Sweden)

    P. Marcoionni

    2006-06-01

    Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.

  20. Application of Spaceborne Remote Sensing to Archaeology

    Science.gov (United States)

    Crippen, Robert E.

    1997-01-01

    Spaceborne remote sensing data have been underutilized in archaeology for a variety of seasons that are slowly but surely being overcome. Difficulties have included cost/availability of data, inadequate resolution, and data processing issues.

  1. GNSS remote sensing theory, methods and applications

    CERN Document Server

    Jin, Shuanggen; Xie, Feiqin

    2014-01-01

    This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. It contains detailed theory and study cases to help the reader put the material into practice.

  2. NOAA Coastal Mapping Remote Sensing Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Remote Sensing Division is responsible for providing data to support the Coastal Mapping Program, Emergency Response efforts, and the Aeronautical Survey Program...

  3. Biophysical applications of satellite remote sensing

    CERN Document Server

    Hanes, Jonathan

    2014-01-01

    Including an introduction and historical overview of the field, this comprehensive synthesis of the major biophysical applications of satellite remote sensing includes in-depth discussion of satellite-sourced biophysical metrics such as leaf area index.

  4. Quantification of greenhouse gas (GHG) emissions from wastewater treatment plants using a ground-based remote sensing approach

    Science.gov (United States)

    Delre, Antonio; Mønster, Jacob; Scheutz, Charlotte

    2016-04-01

    The direct release of nitrous oxide (N2O) and methane (CH4) from wastewater treatment plants (WWTP) is important because it contributes to the global greenhouse gases (GHGs) release and strongly effects the WWTP carbon footprint. Biological nitrogen removal technologies could increase the direct emission of N2O (IPCC, 2006), while CH4 losses are of environmental, economic and safety concern. Currently, reporting of N2O and CH4 emissions from WWTPs are performed mainly using methods suggested by IPCC which are not site specific (IPCC, 2006). The dynamic tracer dispersion method (TDM), a ground based remote sensing approach implemented at DTU Environment, was demonstrated to be a novel and successful tool for full-scale CH4 and N2O quantification from WWTPs. The method combines a controlled release of tracer gas from the facility with concentration measurements downwind of the plant (Mønster et al., 2014; Yoshida et al., 2014). TDM in general is based on the assumption that a tracer gas released at an emission source, in this case a WWTP, disperses into the atmosphere in the same way as the GHG emitted from process units. Since the ratio of their concentrations remains constant along their atmospheric dispersion, the GHG emission rate can be calculated using the following expression when the tracer gas release rate is known: EGHG=Qtr*(CGHG/Ctr)*(MWGHG/MWtr) EGHG is the GHG emission in mass per time, Qtr is the tracer release in mass per time, CGHG and Ctr are the concentrations measured downwind in parts per billion subtracted of their background values and integrated over the whole plume, and MWGHG and MWtr are the molar weights of GHG and tracer gas respectively (Mønster et al. 2014). In this study, acetylene (C2H2) was used as tracer. Downwind plume concentrations were measured driving along transects with two cavity ring down spectrometers (Yoshida et al., 2014). TDM was successfully applied in different seasons at several Scandinavian WWTPs characterized by

  5. Remote sensing, imaging, and signal engineering

    Energy Technology Data Exchange (ETDEWEB)

    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.

  6. Freeware for GIS and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Lena Halounová

    2007-12-01

    Full Text Available Education in remote sensing and GIS is based on software utilization. The software needs to be installed in computer rooms with a certain number of licenses. The commercial software equipment is therefore financially demanding and not only for universities, but especially for students. Internet research brings a long list of free software of various capabilities. The paper shows a present state of GIS, image processing and remote sensing free software.

  7. Preface: Remote Sensing of Water Resources

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-02-01

    Full Text Available The Special Issue (SI on “Remote Sensing of Water Resources” presents a diverse range of papers studying remote sensing tools, methods, and models to better monitor water resources which include inland, coastal, and open ocean waters. The SI is comprised of fifteen articles on widely ranging research topics related to water bodies. This preface summarizes each article published in the SI.

  8. Talisman-Saber 2009 Remote Sensing Experiment

    Science.gov (United States)

    2012-03-30

    Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/7230--12-9404 Talisman -Saber 2009 Remote Sensing Experiment March 30, 2012 Approved for... Talisman -Saber 2009 Remote Sensing Experiment Charles M. Bachmann, Robert A. Fusina, Marcos J. Montes, Rong-Rong Li, Carl Gross, C. Reid Nichols,* John C...sensor were used to build shallow water bathymetric charts and trafficability maps that were provided to military planners during Exercise Talisman

  9. Remote sensing of coastal and ocean studies

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.

    the sensors on board 2 satellites or aircrafts (and vice versa). Hence, they cannot be used in remote sensing. Similarly, long waves like radio waves are also not used in remote sensing because of their poor information carrying capacity. Only visible, infra..., infra-red radiation is also affected by clouds (though less significantly). This requires atmospheric corrections to be applied to such data. At present, sea surface temperatures are routinely being retrieved from the sensor called AVBRR (Advanced Vary...

  10. Remote Sensing Digital Image Analysis An Introduction

    CERN Document Server

    Richards, John A

    2013-01-01

    Remote Sensing Digital Image Analysis provides the non-specialist with a treatment of the quantitative analysis of satellite and aircraft derived remotely sensed data. Since the first edition of the book there have been significant developments in the algorithms used for the processing and analysis of remote sensing imagery; nevertheless many of the fundamentals have substantially remained the same.  This new edition presents material that has retained value since those early days, along with new techniques that can be incorporated into an operational framework for the analysis of remote sensing data. The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image processing in remote sensing.  The presentation level is for the mathematical non-specialist.  Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a leve...

  11. Benthic habitat mapping using hyperspectral remote sensing

    Science.gov (United States)

    Vélez-Reyes, Miguel; Goodman, James A.; Castrodad-Carrau, Alexey; Jiménez-Rodriguez, Luis O.; Hunt, Shawn D.; Armstrong, Roy

    2006-09-01

    Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.

  12. Towards improved characterization of northern wetlands (or other landscapes) by remote sensing - a rapid approach to collect ground truth data

    Science.gov (United States)

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

    2017-04-01

    The calibration and validation of remote sensing land cover products is highly dependent on accurate ground truth data, which are costly and practically challenging to collect. This study evaluates a novel and efficient alternative to field surveys and UAV imaging commonly applied for this task. The method consists of i) a light weight, water proof, remote controlled RGB-camera mounted on an extendable monopod used for acquiring wide-field images of the ground from a height of 4.5 meters, and ii) a script for semi-automatic image classification. In the post-processing, the wide-field images are corrected for optical distortion and geometrically rectified so that the spatial resolution is the same over the surface area used for classification. The script distinguishes land surface components by color, brightness and spatial variability. The method was evaluated in wetland areas located around Abisko, northern Sweden. Proportional estimates of the six main surface components in the wetlands (wet and dry Sphagnum, shrub, grass, water, rock) were derived for 200 images, equivalent to 10 × 10 m field plots. These photo plots were then used as calibration data for a regional scale satellite based classification which separates the six wetland surface components using a Sentinel-1 time series. The method presented in this study is accurate, rapid, robust and cost efficient in comparison to field surveys (time consuming) and drone mapping (which require low wind speeds and no rain, suffer from battery limited flight times, have potential GPS/compass errors far north, and in some areas are prohibited by law).

  13. A Warning System for Rainfall-Induced Debris Flows: A Integrated Remote Sensing and Data Mining Approach

    Science.gov (United States)

    Elkadiri, R.; Sultan, M.; Nurmemet, I.; Al Harbi, H.; Youssef, A.; Elbayoumi, T.; Zabramwi, Y.; Alzahrani, S.; Bahamil, A.

    2014-12-01

    We developed methodologies that heavily rely on observations extracted from a wide-range of remote sensing data sets (TRMM, Landsat ETM, ENVISAT, ERS, SPOT, Orbview, GeoEye) to develop a warning system for rainfall-induced debris flows in the Jazan province in the Red Sea Hills. The developed warning system integrates static controlling factors and dynamic triggering factors. The algorithm couples a susceptibility map with a rainfall I-D curve, both are developed using readily available remote sensing datasets. The static susceptibility map was constructed as follows: (1) an inventory was compiled for debris flows identified from high spatial resolution datasets and field verified; (2) 10 topographical and land cover predisposing factors (i.e. slope angle, slope aspect, normalized difference vegetation index, topographical position index, stream power index, flow accumulation, distance to drainage line, soil weathering index, elevation and topographic wetness index) were generated; (3) an artificial neural network model (ANN) was constructed, optimized and validated; (4) a debris-flow susceptibility map was generated using the ANN model and refined (using differential backscatter coefficient radar images). The rainfall threshold curve was derived as follows: (1) a spatial database was generated to host temporal co-registered and radiometrically and atmospherically corrected Landsat images; (2) temporal change detection images were generated for pairs of successively acquired Landsat images and criteria were established to identify "the change" related to debris flows, (3) the duration and intensity of the precipitation event that caused each of the identified debris flow events was assumed to be that of the most intense event within the investigated period; and (4) the I-D curve was extracted using data (intensity and duration of precipitation) for the inventoried events. Our findings include: (1) the spatial controlling factors with the highest predictive power of

  14. Tunnel-Site Selection by Remote Sensing Techniques

    Science.gov (United States)

    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

  15. Remote Sensing Best Paper Award for the Year 2014

    OpenAIRE

    Prasad Thenkabail

    2014-01-01

    Remote Sensing has started to institute a “Best Paper” award to recognize the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing. We are pleased to announce the first “Remote Sensing Best Paper Award” for the year 2014.

  16. Remote Sensing and the Kyoto Protocol: A Workshop Summary

    Science.gov (United States)

    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

  17. Research Dynamics of the Classification Methods of Remote Sensing Images

    Institute of Scientific and Technical Information of China (English)

    Yan; ZHANG; Baoguo; WU; Dong; WANG

    2013-01-01

    As the key technology of extracting remote sensing information,the classification of remote sensing images has always been the research focus in the field of remote sensing. The paper introduces the classification process and system of remote sensing images. According to the recent research status of domestic and international remote sensing classification methods,the new study dynamics of remote sensing classification,such as artificial neural networks,support vector machine,active learning and ensemble multi-classifiers,were introduced,providing references for the automatic and intelligent development of remote sensing images classification.

  18. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing

    Directory of Open Access Journals (Sweden)

    Deqing Liu

    2016-08-01

    Full Text Available In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC. The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  19. A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing.

    Science.gov (United States)

    Liu, Deqing; Luan, Xiaoning; Guo, Jinjia; Cui, Tingwei; An, Jubai; Zheng, Ronger

    2016-08-23

    In hope of developing a method for oil spill detection in laser remote sensing, a series of refined and crude oil samples were investigated using time-resolved fluorescence in conjunction with parallel factors analysis (PARAFAC). The time resolved emission spectra of those investigated samples were taken by a laser remote sensing system on a laboratory basis with a detection distance of 5 m. Based on the intensity-normalized spectra, both refined and crude oil samples were well classified without overlapping, by the approach of PARAFAC with four parallel factors. Principle component analysis (PCA) has also been operated as a comparison. It turned out that PCA operated well in classification of broad oil type categories, but with severe overlapping among the crude oil samples from different oil wells. Apart from the high correct identification rate, PARAFAC has also real-time capabilities, which is an obvious advantage especially in field applications. The obtained results suggested that the approach of time-resolved fluorescence combined with PARAFAC would be potentially applicable in oil spill field detection and identification.

  20. A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach

    Directory of Open Access Journals (Sweden)

    Lauren Dunkin

    2016-07-01

    Full Text Available Nesting habitat for the federally endangered loggerhead sea turtle (Caretta caretta were designated as critical in 2014 for beaches along the Atlantic Coast and Gulf of Mexico. Nesting suitability is routinely determined based on site specific information. Given the expansive geographic location of the designated critical C. caretta nesting habitat and the highly dynamic coastal environment, understanding nesting suitability on a regional scale is essential for monitoring the changing status of the coast as a result of hydrodynamic forces and maintenance efforts. The increasing spatial resolution and temporal frequency of remote sensing data offers the opportunity to study this dynamic environment on a regional scale. Remote sensing data were used as input into the spatially-explicit, multi-criteria decision support model to determine nesting habitat suitability. Results from the study indicate that the morphological parameters used as input into the model are well suited to provide a regional level approach with the results from the optimized model having sensitivity and detection prevalence values greater than 80% and the detection rate being greater than 70%. The approach can be implemented in various geographic locations to better communicate priorities and evaluate management strategies as a result of changes to the dynamic coastal environment.

  1. Exploring the role of green and blue infrastructure in reducing temperature in Iskandar Malaysia using remote sensing approach

    Science.gov (United States)

    Kanniah, K. D.; sheikhi, A.; Kang, C. S.

    2014-02-01

    Development of cities has led to various environmental problems as a consequence of non sustaibale town planning. One of the strategies to make cities a livable place and to achieve low levels of CO2 emissions (low carbon cities or LCC) is the integration of the blue and green infrastructure into the development and planning of new urban areas. Iskandar Malaysia (IM) located in the southern part of Malaysia is a special economic zone that has major urban centres. The planning of these urban centres will incorporate LCC strategies to achieve a sustainable development. The role of green (plants) and blue bodies (lakes and rivers) in moderating temperature in IM have been investigated in the current study. A remotely sensed satellite imagery was used to calculate the vegetation density and land surface temperature (LST). The effect of lakes in cooling the surrounding temperature was also investigated. Results show that increasing vegetation density by 1% can decrease the LST by 0.09°C. As for the water bodies we found as the distance increased from the lake side the temperature also increased about 1.7°C and the reduction in air humidity is 9% as the distance increased to 100 meter away from the lake.

  2. Flood risks in urbanized areas – multi-sensoral approaches using remotely sensed data for risk assessment

    Directory of Open Access Journals (Sweden)

    H. Taubenböck

    2011-02-01

    Full Text Available Estimating flood risks and managing disasters combines knowledge in climatology, meteorology, hydrology, hydraulic engineering, statistics, planning and geography – thus a complex multi-faceted problem. This study focuses on the capabilities of multi-source remote sensing data to support decision-making before, during and after a flood event. With our focus on urbanized areas, sample methods and applications show multi-scale products from the hazard and vulnerability perspective of the risk framework. From the hazard side, we present capabilities with which to assess flood-prone areas before an expected disaster. Then we map the spatial impact during or after a flood and finally, we analyze damage grades after a flood disaster. From the vulnerability side, we monitor urbanization over time on an urban footprint level, classify urban structures on an individual building level, assess building stability and quantify probably affected people. The results show a large database for sustainable development and for developing mitigation strategies, ad-hoc coordination of relief measures and organizing rehabilitation.

  3. Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach

    Science.gov (United States)

    Galeana-Pizaña, J. Mauricio; López-Caloca, Alejandra; López-Quiroz, Penélope; Silván-Cárdenas, José Luis; Couturier, Stéphane

    2014-08-01

    Forest conservation is considered an option for mitigating the effect of greenhouse gases on global climate, hence monitoring forest carbon pools at global and local levels is important. The present study explores the capability of remote-sensing variables (vegetation indices and textures derived from SPOT-5; backscattering coefficient and interferometric coherence of ALOS PALSAR images) for modeling the spatial distribution of above-ground biomass in the Environmental Conservation Zone of Mexico City. Correlation and spatial autocorrelation coefficients were used to select significant explanatory variables in fir and pine forests. The correlation for interferometric coherence in HV polarization was negative, with correlations coefficients r = -0.83 for the fir and r = -0.75 for the pine forests. Regression-kriging showed the least root mean square error among the spatial interpolation methods used, with 37.75 tC/ha for fir forests and 29.15 tC/ha for pine forests. The results showed that a hybrid geospatial method, based on interferometric coherence data and a regression-kriging interpolator, has good potential for estimating above-ground biomass carbon.

  4. Target Detection: Remote Sensing Techniques for Defence Applications

    Directory of Open Access Journals (Sweden)

    B. B. Chaudhuri

    1995-10-01

    Full Text Available The tremendous development in remote sensing technology in the recent past has opened up new challenges in defence applications. On important area of such applications is in target detection. This paper describes both classical and newly developed approaches to detect the targets by using remotely-sensed digital images. The classical approach includes statistical classification methods and image processing techniques. The new approach deals with a relatively new sensor technology, namely, synthetic aperture radar (SAR systems and fast developing tools, like neural networks and multisource data integration for analysis and interpretation. With SAR images, it is possible to detect targets or features of a target that is otherwise not possible. Neural networks and multisource data integration tools also have a great potential in analysing and interpreting remote sensing data for target detection.

  5. Near-earth orbital guidance and remote sensing

    Science.gov (United States)

    Powers, W. F.

    1972-01-01

    The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

  6. Sensing our Environment: Remote sensing in a physics classroom

    Science.gov (United States)

    Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

    2017-04-01

    Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora

  7. Multiscale and Multitemporal Urban Remote Sensing

    Science.gov (United States)

    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.

  8. remote sensing data combinations - global AOD maps

    Science.gov (United States)

    Kinne, S.

    2009-04-01

    More accurate and more complete measurement-based data-sets are needed to constrain the freedom of global modeling and raise confidence in model predictions. In remote sensing, different methods and sensors frequently yield estimates for the same (or a strongly related) atmospheric property. For maximum benefit to data-users (e.g. input or evaluation data to modeling) - in the context of differences in sensor capabilities and retrieval limitations - there is a desire to combine the strengths of these individual data sources for superior products. In a demonstration, different multi-annual global monthly maps for aerosol optical depth (AOD) from satellite remote sensing been compared and scored against local quality reference data from ground remote sensing. The regionally best performing satellite data-sets have been combined into global monthly AOD maps. As expected, this satellite composite scores better than any individual satellite retrieval. Further improvements are achieved by merging statistics of ground remote sensing into the composite. The global average mid-visible AOD of this remote sensing composite is near 0.13 annually, with lower values during northern hemispheric fall and winter (0.12) and larger values during northern hemispheric spring and summer (0.14). This measurement based data composite also reveals characteristic deficiencies in global modeling: Modeling tends to overestimates AOD over the northern mid-latitudes and to underestimate AOD over tropical and sub-tropical land regions. Also noteworthy are AOD underestimates by modeling in remote oceanic regions, though only in relative sense as AOD values in that region as small. The AOD remote sensing data composite is far from perfect, but it demonstrates the extra value of data-combinations.

  9. Multi-Data Approach for remote sensing-based regional crop rotation mapping: A case study for the Rur catchment, Germany

    Science.gov (United States)

    Waldhoff, Guido; Lussem, Ulrike; Bareth, Georg

    2017-09-01

    Spatial land use information is one of the key input parameters for regional agro-ecosystem modeling. Furthermore, to assess the crop-specific management in a spatio-temporal context accurately, parcel-related crop rotation information is additionally needed. Such data is scarcely available for a regional scale, so that only modeled crop rotations can be incorporated instead. However, the spectrum of the occurring multiannual land use patterns on arable land remains unknown. Thus, this contribution focuses on the mapping of the actually practiced crop rotations in the Rur catchment, located in the western part of Germany. We addressed this by combining multitemporal multispectral remote sensing data, ancillary information and expert-knowledge on crop phenology in a GIS-based Multi-Data Approach (MDA). At first, a methodology for the enhanced differentiation of the major crop types on an annual basis was developed. Key aspects are (i) the usage of physical block data to separate arable land from other land use types, (ii) the classification of remote sensing scenes of specific time periods, which are most favorable for the differentiation of certain crop types, and (iii) the combination of the multitemporal classification results in a sequential analysis strategy. Annual crop maps of eight consecutive years (2008-2015) were combined to a crop sequence dataset to have a profound data basis for the mapping of crop rotations. In most years, the remote sensing data basis was highly fragmented. Nevertheless, our method enabled satisfying crop mapping results. As an example for the annual crop mapping workflow, the procedure and the result of 2015 are illustrated. For the generation of the crop sequence dataset, the eight annual crop maps were geometrically smoothened and integrated into a single vector data layer. The resulting dataset informs about the occurring crop sequence for individual areas on arable land, so that crop rotation schemes can be derived. The

  10. Remote sensing of vegetation at regional scales

    Science.gov (United States)

    Hall, F. G.

    1984-01-01

    Relations between spectroscopy and the concept of inferring surface cover type and condition from measurements of reflected or emitted radiation are examined, taking into account the observation of 'spectral signatures'. It has now become evident that the paradigm which had provided the basis for the spectroscopic identification of materials, is incomplete when applied to the inference of type and condition of materials in a natural environment. It was found that one could not collect a remote sensing signature from an unknown ground cover class at a particular time and place and match that signature with an a priori catalog value to infer the properties of the unknown cover class. The spectroscopy paradigm was, therefore, largely abandoned in favor of decision theoretic approaches. Attention is given to the temporal greenness profile feature space, the crop stage of development estimation using a temporal greenness profile, the temporal greenness profile for crop yield, and applications to regional scales.

  11. Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

    Science.gov (United States)

    Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

    2010-01-01

    Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

  12. Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

    Directory of Open Access Journals (Sweden)

    Marc Cattet

    2010-11-01

    Full Text Available Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC. Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI, inversion algorithm, data fusion, and the integration of remote sensing (RS and geographic information system (GIS.

  13. Simulation of large-scale tropical tuna movements in relation with daily remote sensing data: the artificial life approach.

    Science.gov (United States)

    Dagorn, L; Petit, M; Stretta, J M

    1997-01-01

    Tunas are known to be able to travel long distances. The aim of this paper is to propose new ethological models which reproduce some tuna movements using the dynamics of their environment. We use sea surface temperature animations (from remote sensing data) to model the South West Indian Ocean, and French purse seiners data are used to estimate movements of fish. The objective of the models will be to find a northern movement from the Mozambique Channel to the Seychelles Islands at the appropriate time (May-July). The initial model uses our ecological knowledge of tunas, i.e. the search behavior for high concentrations of food commonly associated with thermal fronts. In some cases, this simple model creates some northern movements from the Mozambique Channel, but it cannot be used to reproduce large-scale movements between the Mozambique Channel and the Seychelles Islands. The next generation model is created where tuna behaviors are modeled by an artificial neural network, using a genetic algorithm to adjust the connection weights. The tuna school-network receives daily information from its local environment and chooses the best actions in order to be able to pass from the Mozambique Channel to the Seychelles Islands at the appropriate time. One neural network emerges and represents an adaptive behavior able to interpret daily sea surface temperatures to mimic large-scale tuna movements. This artificial behavior can be generalized to each possible departure position from the Mozambique Channel. This modelling represents a new tool to study large-scale movements of pelagic fish, and is a first step towards real-time management of fisheries.

  14. Forecasting Skills of a Multi-Model Approach with Variational Data Assimilation of Remote Sensing Data in the Upper Main Basin

    Science.gov (United States)

    Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Krahe, Peter

    2016-04-01

    Ensemble forecasting has been increasingly applied in flow forecasting systems to provide users a better understanding of forecast uncertainty and consequently to take better-informed decisions. In order to produce ensemble forecasts, probabilistic numerical weather predictions (NWP) are commonly forced into a deterministic hydrological model to generate streamflow ensembles. The approach aims at the representation of meteorological uncertainty and neglects uncertainty of the hydrological sub-system. A complementary approach is the use of a probabilistic model pool in combination with a data assimilation technique to represent the uncertainty of historical data and the hydrological model. We present the assessment of the forecasting skills of a multi-model approach in combination with a simultaneous data assimilation of multiple observations using a 4Dvar method. The model pool is based on the variation of the spatial discretization of a conceptual HBV rainfall-runoff model and different parameter sets with an equivalent calibration. The approach enables the assimilation of streamflow data and remote sensing products for snow coverage, snow water equivalent and soil moisture to provide a set of initial conditions for the forecast. In comparison to the standard implementation of an Ensemble Kalman Filter, structural and parametric uncertainty is represented in the model pool and therefore does not propagate out of the system over time. The framework is applied to the Upper Main basin in Germany. It is a data-dense environment with well-calibrated rainfall-runoff models. We present the model performance and address the ability of the model pool to represent model uncertainty over a historical period. The lead time performance of the model is assessed for perfect forecasts, i.e. by forcing the model with observed data, remote sensing products from the H-SAF project and several deterministic and probabilistic NWP. The assessment of lead-time performance demonstrates

  15. Utilization of remote sensing observations in hydrologic models

    Science.gov (United States)

    Ragan, R. M.

    1977-01-01

    Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

  16. A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

    Science.gov (United States)

    Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

    1998-01-01

    ' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

  17. Remote sensing applications in environmental research

    CERN Document Server

    Srivastava, Prashant K; Gupta, Manika; Islam, Tanvir

    2014-01-01

    Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today's sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

  18. Acoustic Remote Sensing of Rogue Waves

    Science.gov (United States)

    Parsons, Wade; Kadri, Usama

    2016-04-01

    We propose an early warning system for approaching rogue waves using the remote sensing of acoustic-gravity waves (AGWs) - progressive sound waves that propagate at the speed of sound in the ocean. It is believed that AGWs are generated during the formation of rogue waves, carrying information on the rogue waves at near the speed of sound, i.e. much faster than the rogue wave. The capability of identifying those special sound waves would enable detecting rogue waves most efficiently. A lot of promising work has been reported on AGWs in the last few years, part of which in the context of remote sensing as an early detection of tsunami. However, to our knowledge none of the work addresses the problem of rogue waves directly. Although there remains some uncertainty as to the proper definition of a rogue wave, there is little doubt that they exist and no one can dispute the potential destructive power of rogue waves. An early warning system for such extreme waves would become a demanding safety technology. A closed form expression was developed for the pressure induced by an impulsive source at the free surface (the Green's function) from which the solution for more general sources can be developed. In particular, we used the model of the Draupner Wave of January 1st, 1995 as a source and calculated the induced AGW signature. In particular we studied the AGW signature associated with a special feature of this wave, and characteristic of rogue waves, of the absence of any local set-down beneath the main crest and the presence of a large local set-up.

  19. Remote sensing of sagebrush canopy nitrogen

    Science.gov (United States)

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

    2012-01-01

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

  20. Assessing degradation across a land-use gradient in the Kruger National Park area using advanced remote sensing modalities

    CSIR Research Space (South Africa)

    Van Aardt, JAN

    2011-01-01

    Full Text Available relatively novel remote sensing approaches, namely imaging spectroscopy (hyperspectral remote sensing) and light detection and ranging (lidar), have the potential to alleviate this constraint. Specifically, the Carnegie Airborne Observatory, a state...

  1. Thermal infrared remote sensing sensors, methods, applications

    CERN Document Server

    Kuenzer, Claudia

    2013-01-01

    This book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techni

  2. Remotely sensing the photochemical reflectance index, PRI

    Science.gov (United States)

    Vanderbilt, Vern; Daughtry, Craig; Dahlgren, Robert

    2015-09-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside leaves in a plant stand. Developed by1,2, PRI evolved from laboratory reflectance measurements of individual leaves. Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We compared values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. Our results show the polarized leaf surface reflection should be removed when calculating PRI and that the leaf physiology information is in leaf interior reflectance, not leaf transmittance.

  3. Offshore winds mapped from satellite remote sensing

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    2014-01-01

    the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost....... The advantages of microwave satellite remote sensing are 1) horizontal spatial coverage, 2) long data archives and 3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to 6 observations per day with near...

  4. Monitoring water quality by remote sensing

    Science.gov (United States)

    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.

  5. Space remote sensing systems an introduction

    CERN Document Server

    Chen, H S

    1985-01-01

    Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

  6. Geobotanical Remote Sensing for Geothermal Exploration

    Energy Technology Data Exchange (ETDEWEB)

    Pickles, W L; Kasameyer, P W; Martini, B A; Potts, D C; Silver, E A

    2001-05-22

    This paper presents a plan for increasing the mapped resource base for geothermal exploration in the Western US. We plan to image large areas in the western US with recently developed high resolution hyperspectral geobotanical remote sensing tools. The proposed imaging systems have the ability to map visible faults, surface effluents, historical signatures, and discover subtle hidden faults and hidden thermal systems. Large regions can be imaged at reasonable costs. The technique of geobotanical remote sensing for geothermal signatures is based on recent successes in mapping faults and effluents the Long Valley Caldera and Mammoth Mountain in California.

  7. Remote sensing of land surface phenology

    Science.gov (United States)

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

    2014-01-01

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

  8. A technology path to distributed remote sensing

    Science.gov (United States)

    Fountain, Glen H.; Gold, Robert E.; Jenkins, Robert E.; Lew, Ark L.; Raney, R. Keith

    2000-03-01

    The Johns Hopkins University Applied Physics Laboratory (APL) has been engaged for over 40 years in Earth science missions spanning geodesy to atmospheric science. In parallel, APL's Advanced Technology Program is supporting research in autonomy, scalable architectures, miniaturization, and instrument innovation. These are key technologies for the development of affordable observation programs that could benefit from distributed remote sensing. This paper brings these applications and technology themes together in the form of an innovative, three-satellite remote sensing scenario. This pathfinding mission fills an important scientific niche, and relies on state-of-the-art small-satellite technology.

  9. Remote sensing/vegetation classification. [California

    Science.gov (United States)

    Parker, I. E.

    1981-01-01

    The CALVEG classification system for identification of vegetation is described. This hierarchical system responds to classification requirements and to interpretation of vegetation at various description levels, from site description to broad identification levels. The system's major strength is its flexibility in application of remote sensing technology to assess, describe and communicate data relative to vegetative resources on a state-wide basis. It is concluded that multilevel remote sensing is a cost effective tool for assessment of the natural resource base. The CLAVEG system is found to be an economically efficient tool for both existing and potential vegetation.

  10. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  11. Kite Aerial Photography as a Tool for Remote Sensing

    Science.gov (United States)

    Sallee, Jeff; Meier, Lesley R.

    2010-01-01

    As humans, we perform remote sensing nearly all the time. This is because we acquire most of our information about our surroundings through the senses of sight and hearing. Whether viewed by the unenhanced eye or a military satellite, remote sensing is observing objects from a distance. With our current technology, remote sensing has become a part…

  12. Recent Progresses in Atmospheric Remote Sensing Research in China-- Chinese National Report on Atmospheric Remote Sensing Research in China during 1999-2003

    Institute of Scientific and Technical Information of China (English)

    邱金桓; 陈洪滨

    2004-01-01

    Progresses of atmospheric remote sensing research in China during 1999-2003 are summarily introduced.This research includes: (1) microwave remote sensing of the atmosphere; (2) Lidar remote sensing; (3)remote sensing of aerosol optical properties; and (4) other research related to atmospheric remote sensing,including GPS remote sensing of precipitable water vapor and radiation model development.

  13. Long-term monitoring for conservation management: Lessons from a case study integrating remote sensing and field approaches in floodplain forests.

    Science.gov (United States)

    Rodríguez-González, Patricia María; Albuquerque, António; Martínez-Almarza, Miguel; Díaz-Delgado, Ricardo

    2017-02-09

    Implementing long-term monitoring programs that effectively inform conservation plans is a top priority in environmental management. In floodplain forests, historical pressures interplay with the complex multiscale dynamics of fluvial systems and require integrative approaches to pinpoint drivers for their deterioration and ecosystem services loss. Combining a conceptual framework such as the Driver-Pressure-State-Impact-Response (DPSIR) with the development of valid biological indicators can contribute to the analysis of the driving forces and their effects on the ecosystem in order to formulate coordinated conservation measures. In the present study, we evaluate the initial results of a decade (2004-2014) of floodplain forest monitoring. We adopted the DPSIR framework to summarize the main drivers in land use and environmental change, analyzed the effects on biological indicators of foundation trees and compared the consistency of the main drivers and their effects at two spatial scales. The monitoring program was conducted in one of the largest and best preserved floodplain forests in SW Europe located within Doñana National Park (Spain) which is dominated by Salix atrocinerea and Fraxinus angustifolia. The program combined field (in situ) surveys on a network of permanent plots with several remote sensing sources. The accuracy obtained in spectral classifications allowed shifts in species cover across the whole forest to be detected and assessed. However, remote sensing did not reflect the ecological status of forest populations. The field survey revealed a general decline in Salix populations, especially in the first five years of sampling -a factor probably associated with a lag effect from past human impact on the hydrology of the catchment and recent extreme climatic episodes (drought). In spite of much reduced seed regeneration, a resprouting strategy allows long-lived Salix individuals to persist in complex spatial dynamics. This suggests the beginning

  14. User requirements for hydrological models with remote sensing input

    Energy Technology Data Exchange (ETDEWEB)

    Kolberg, Sjur

    1997-10-01

    Monitoring the seasonal snow cover is important for several purposes. This report describes user requirements for hydrological models utilizing remotely sensed snow data. The information is mainly provided by operational users through a questionnaire. The report is primarily intended as a basis for other work packages within the Snow Tools project which aim at developing new remote sensing products for use in hydrological models. The HBV model is the only model mentioned by users in the questionnaire. It is widely used in Northern Scandinavia and Finland, in the fields of hydroelectric power production, flood forecasting and general monitoring of water resources. The current implementation of HBV is not based on remotely sensed data. Even the presently used HBV implementation may benefit from remotely sensed data. However, several improvements can be made to hydrological models to include remotely sensed snow data. Among these the most important are a distributed version, a more physical approach to the snow depletion curve, and a way to combine data from several sources. 1 ref.

  15. Combining Citizen Science Phenological Observations with Remote Sensing Data

    Science.gov (United States)

    Delbart, Nicolas; Beaubien, Elisabeth; Kergoat, Laurent; Deront, Lise; Le Toan, Thuy

    2016-08-01

    Citizen science is efficient to collect data about plant phenology across large areas such as Canada and independently for each species. However, such time series are often discontinuous and observations are not evenly distributed. On the other hand, remote sensing provides a synoptic view on phenology but does not inform about inter-species differences in phenological response to climate variability.Existing interactions between the two types of data are so far essentially limited to the evaluation of remote sensing methods by citizen science data, which proved quite efficient. Here we first use such an approach to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. We analyze the interspecies differences in phenology at the scale of so- called "pheno-regions" delineated using remote sensing green-up maps.

  16. Wind Predictability and Remote Sensing Techniques,

    Science.gov (United States)

    The report presents the unclassified findings from the Investigation of Airborne Wind Sensing Systems conducted under AIRTASK A30303/323/70F17311002. Included is a summary of the current accuracy of wind speed and direction forecasts, a list of possible methods for remote sensing meteorological data, a list of areas of application of the given methods and a list of contacts made for information relevant to this evaluation. (Author)

  17. Combining interior and exterior characteristics for remote sensing image denoising

    Science.gov (United States)

    Peng, Ni; Sun, Shujin; Wang, Runsheng; Zhong, Ping

    2016-04-01

    Remote sensing image denoising faces many challenges since a remote sensing image usually covers a wide area and thus contains complex contents. Using the patch-based statistical characteristics is a flexible method to improve the denoising performance. There are usually two kinds of statistical characteristics available: interior and exterior characteristics. Different statistical characteristics have their own strengths to restore specific image contents. Combining different statistical characteristics to use their strengths together may have the potential to improve denoising results. This work proposes a method combining statistical characteristics to adaptively select statistical characteristics for different image contents. The proposed approach is implemented through a new characteristics selection criterion learned over training data. Moreover, with the proposed combination method, this work develops a denoising algorithm for remote sensing images. Experimental results show that our method can make full use of the advantages of interior and exterior characteristics for different image contents and thus improve the denoising performance.

  18. PLANT INCORPORATED PROTECTANT CROP MONITORING USING REMOTE SENSING

    Science.gov (United States)

    The extent of past and anticipated plantings of transgenic corn in the United States requires a new approach to monitor this important crop for the development of pest resistance. Remote sensing by aerial and/or satellite images may provide a method of identifying transgenic pest...

  19. Estimation of Forest Degradation with Remote Sensing and GIS Analysis

    DEFF Research Database (Denmark)

    Dons, Klaus

    +). An indirect remote sensing (RS) approach has been suggested to map the infrastructure used for degradation rather than the actual change in forest canopy cover. This offers a way to delineate intact forest land and to model and estimate emissions from forest degradation in the non‐intact forest land – thereby...

  20. Remote Sensing-based Drought Monitoring Approach and Research Progress%以遥感为基础的干旱监测方法研究进展

    Institute of Scientific and Technical Information of China (English)

    周磊; 武建军; 张洁

    2015-01-01

    Drought is a serious natural disaster. It is doing increasingly damage to the human environment as the drought events occur more frequently. Real-time and effective drought monitoring is an effective means to reduce the losses caused by drought. Since the beginning of 20th century, a lot of drought indices have been de-veloped for monitoring the occurrence and variation of drought. Drought is a complex natural disaster. Howev-er, each drought index has its own advantages and weaknesses in drought monitoring. Almost all the drought indices are based on specific geographical and temporal scales;it is difficult to spread its applicability all over the world. Because of the meteorological drought indices using discrete, point-based meteorological measure-ments collected at weather station locations, the results have restricted level of spatial precision for monitoring drought patterns. Remote sensing technology provides alternative data for operational drought monitoring, with advanced temporal and spatial characteristics. However, additional information still needs to be incorpo-rated so as to thoroughly explain the anomaly in vegetation caused by drought. Besides, to achieve a more ac-curate description of drought characteristics, drought intensity differences caused by vegetation type, tempera-ture, elevation, manmade irrigation, and other factors under the same water condition must be considered. Therefore, effective drought monitoring indicator should both reflect soil moisture, vegetation condition and take into account vegetation type, temperature, and man-made factors leading to regional drought differences. Aiming at the problem mentioned above, the satellite based drought indices, and integrated meteorological and remote sensed drought indices was reviewed in our research. Firstly, this paper summarized the widely used drought monitoring models which were based on remote sensing data. The remote sensing drought monitoring approach was summarized by dividing

  1. Satellite Remote Sensing in Offshore Wind Energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Astrup, Poul

    2013-01-01

    Satellite remote sensing of ocean surface winds are presented with focus on wind energy applications. The history on operational and research-based satellite ocean wind mapping is briefly described for passive microwave, scatterometer and synthetic aperture radar (SAR). Currently 6 GW installed...

  2. Remote sensing and today's forestry issues

    Science.gov (United States)

    Sayn-Wittgenstein, L.

    1977-01-01

    The actual and the desirable roles of remote sensing in dealing with current forestry issues, such as national forest policy, supply and demand for forest products and competing demands for forest land are discussed. Topics covered include wood shortage, regional timber inventories, forests in tropical and temperate zones, Skylab photography, forest management and protection, available biomass studies, and monitoring.

  3. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  4. Multisensor image fusion guidelines in remote sensing

    Science.gov (United States)

    Pohl, C.

    2016-04-01

    Remote sensing delivers multimodal and -temporal data from the Earth's surface. In order to cope with these multidimensional data sources and to make the most of them, image fusion is a valuable tool. It has developed over the past few decades into a usable image processing technique for extracting information of higher quality and reliability. As more sensors and advanced image fusion techniques have become available, researchers have conducted a vast amount of successful studies using image fusion. However, the definition of an appropriate workflow prior to processing the imagery requires knowledge in all related fields - i.e. remote sensing, image fusion and the desired image exploitation processing. From the findings of this research it can be seen that the choice of the appropriate technique, as well as the fine-tuning of the individual parameters of this technique, is crucial. There is still a lack of strategic guidelines due to the complexity and variability of data selection, processing techniques and applications. This paper gives an overview on the state-of-the-art in remote sensing image fusion including sensors and applications. Putting research results in image fusion from the past 15 years into a context provides a new view on the subject and helps other researchers to build their innovation on these findings. Recommendations of experts help to understand further needs to achieve feasible strategies in remote sensing image fusion.

  5. Remote sensing information sciences research group

    Science.gov (United States)

    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.

  6. Remote Sensing Analysis of Forest Disturbances

    Science.gov (United States)

    Asner, Gregory P. (Inventor)

    2015-01-01

    The present invention provides systems and methods to automatically analyze Landsat satellite data of forests. The present invention can easily be used to monitor any type of forest disturbance such as from selective logging, agriculture, cattle ranching, natural hazards (fire, wind events, storms), etc. The present invention provides a large-scale, high-resolution, automated remote sensing analysis of such disturbances.

  7. Satellite Remote Sensing for Monitoring and Assessment

    Science.gov (United States)

    Remote sensing technology has the potential to enhance the engagement of communities and managers in the implementation and performance of best management practices. This presentation will use examples from U.S. numeric criteria development and state water quality monitoring prog...

  8. Advances in Remote Sensing of Flooding

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2015-11-01

    Full Text Available With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS-based urban flood vulnerability and risk maps.

  9. Integration of observations, modelling approaches and remote sensing to address ecosystem response to climate change and disturbance in Africa

    Science.gov (United States)

    Falge, Eva; Brümmer, Christian

    2017-04-01

    Park, South Africa, Setting up individual-based models to predict ecosystem dynamics under (post-) disturbance management, Monitoring vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change, and Investigations of livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Despite recent advances, major innovations in understanding carbon cycle, greenhouse gases, air quality and measures of adaptation to and mitigation of climate change are still limited by the lack of global accessibility and comparability of relevant data (open data issues), long-term and sustainable interdisciplinary and trans-institutional research collaborations, and ongoing effective dialogues on multiple levels (policy, science, society).

  10. Study on the response of ecological capacity to land-use/cover change in Wuhan city: a remote sensing and GIS based approach.

    Science.gov (United States)

    Wang, Ying; Li, Xiangmei; Li, Jiangfeng

    2014-01-01

    This research examined the spatiotemporal patterns of land-use/cover and the dynamics of ecological capacity in response to land-use/cover change in Wuhan city, central China. The data were derived from five years' remote-sensed images, that is, 1990, 1995, 2000, 2005, and 2010. This paper used an integrated approach of remote sensing and GIS techniques, ecological capacity and the bilateral dynamic degree models. The results are as follows. (1) From 1990 to 2010, remarkable changes in land-use/cover have occurred within the studied area, and the most prominent characteristics of the changes were continuous decline of arable land and rapid increase of built-up land. (2) The total ecological capacity dropped from 450.55 × 10(4) ghm(2) in 1990 to 447.35 × 10(4) ghm(2) in 2010. The eastern, western, and southern parts had higher ecological capacity whereas the northwestern hilly areas and the central district had lower ecological capacity. (3) Due to the conversion from arable land to built-up land, the ecological capacity losses during 1990-1995, 1995-2000, 2000-2005, and 2005-2010 were 155.52 × 10(2) ghm(2), 114.12 × 10(2) ghm(2), 455.48 × 10(2) ghm(2), and 325.26 × 10(2) ghm(2), respectively. The study would contribute to better understanding of the effects of land-use dynamics and the evolution of ecological capacity, which can provide scientific basis for land management and environment protection.

  11. Geometric calibration of high-resolution remote sensing sensors

    Institute of Scientific and Technical Information of China (English)

    LIANG Hong-you; GU Xing-fa; TAO Yu; QIAO Chao-fei

    2007-01-01

    This paper introduces the applications of high-resolution remote sensing imagery and the necessity of geometric calibration for remote sensing sensors considering assurance of the geometric accuracy of remote sensing imagery. Then the paper analyzes the general methodology of geometric calibration. Taking the DMC sensor geometric calibration as an example, the paper discusses the whole calibration procedure. Finally, it gave some concluding remarks on geometric calibration of high-resolution remote sensing sensors.

  12. Remote Oxygen Sensing by Ionospheric Excitation (ROSIE

    Directory of Open Access Journals (Sweden)

    K. S. Kalogerakis

    2009-05-01

    Full Text Available The principal optical observable emission resulting from ionospheric modification (IM experiments is the atomic oxygen red line at 630 nm, originating from the O(1D–3P transition. Because the O(1D atom has a long radiative lifetime, it is sensitive to collisional relaxation and an observed decay faster than the radiative rate can be attributed to collisions with atmospheric species. In contrast to the common practice of ignoring O-atoms in interpreting such observations in the past, recent experimental studies on the relaxation of O(1D by O(3P have revealed the dominant role of oxygen atoms in controlling the lifetime of O(1D at altitudes relevant to IM experiments. Using the most up-to-date rate coefficients for collisional relaxation of O(1D by O, N2, and O2, it is now possible to analyze the red line decays observed in IM experiments and thus probe the local ionospheric composition. In this manner, we can demonstrate an approach to remotely detect O-atoms at the altitudes relevant to IM experiments, which we call remote oxygen sensing by ionospheric excitation (ROSIE. The results can be compared with atmospheric models and used to study the temporal, seasonal, altitude and spatial variation of ionospheric O-atom density in the vicinity of heating facilities. We discuss the relevance to atmospheric observations and ionospheric heating experiments and report an analysis of representative IM data.

  13. GPS Remote Sensing Measurements Using Aerosonde UAV

    Science.gov (United States)

    Grant, Michael S.; Katzberg, Stephen J.; Lawrence, R. W.

    2005-01-01

    In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

  14. Towards operational environmental applications using terrestrial remote sensing

    NARCIS (Netherlands)

    Veldkamp JG; Velde RJ van de; LBG

    1996-01-01

    Dit rapport beschrijft de resultaten van het Beleidscommissie Remote Sensing (BCRS) project 'Verankering van toepassingen van terrestrische remote sensing bij RIVM'. Het had ten eerste tot doel te voldoen aan de voorwaarden, zoals gesteld in de inventarisatie van remote sensing als

  15. The application of hyperspectral remote sensing to coast environment investigation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Liang; ZHANG bing; CHEN Zhengchao; ZHENG Lanfen; TONG Qingxi

    2009-01-01

    Requirements for monitoring the coastal zone environment are first summarized. Then the application of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

  16. Applications of Remote Sensing to Alien Invasive Plant Studies

    Directory of Open Access Journals (Sweden)

    Gregory P. Asner

    2009-06-01

    Full Text Available Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions.

  17. Unravelling remote sensing signatures of plants contaminated with gasoline and diesel: an approach using the red edge spectral feature.

    Science.gov (United States)

    Sanches, I D; Souza Filho, C R; Magalhães, L A; Quitério, G C M; Alves, M N; Oliveira, W J

    2013-03-01

    Pipeline systems used to transport petroleum products represent a potential source of soil pollution worldwide. The design of new techniques that may improve current monitoring of pipeline leakage is imperative. This paper assesses the remote detection of small leakages of liquid hydrocarbons indirectly, through the analysis of spectral features of contaminated plants. Leaf and canopy spectra of healthy plants were compared to spectra of plants contaminated with diesel and gasoline, at increasing rates of soil contamination. Contamination effects were observed both visually in the field and thorough changes in the spectral reflectance patterns of vegetation. Results indicate that the remote detection of small volumes of gasoline and diesel contaminations is feasible based on the red edge analysis of leaf and canopy spectra of plants. Brachiaria grass ranks as a favourable choice to be used as an indicator of HCs leakages along pipelines. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. An experiment using mid and thermal infrared in quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    The concept of quantum remote sensing and the differences between quantum remote sensing and remote sensing is introduced, an experiment about the uses of mid and thermal infrared in quantum remote sensing is described and results are analyzed.

  19. Remote Sensing and Remote Control Activities in Europe and America: Part 2--Remote Sensing Ground Stations in Europe,

    Science.gov (United States)

    2007-11-02

    Development tasks and products of remote sensing ground stations in Europe are represented by the In-Sec Corporation and the Schlumberger Industries Corporation. The article presents the main products of these two corporations.

  20. Remote sensing for disaster mitigation of Sinabung

    Science.gov (United States)

    Tampubolon, T.; Yanti, J.

    2016-05-01

    Indonesia, a country with many active volcanoes, potentially occur natural disaster due to eruptions. One of volcanoes at Indonesia was Sinabung mountain, that located on Karo Regency, North Sumatera 3°10'12″ N 98°23'31" E, 2,460 masl. A fasile and new observation method for mapping the erupted areas was remote sensing. the remote sensing consisted of Landsat 8 OLI that was published on February 8th 2015 as input data ENVI 4.7 and ArcGIS 10 as mapping tools. The Land surface temperature (LST) was applied on mapping this resulted. The highest LST was 90.929657 °C. In addition, the LST distribution indicated that the flowing lava through south east. Therefore, the south east areas should be considered as mitigated areas.

  1. Review of oil spill remote sensing.

    Science.gov (United States)

    Fingas, Merv; Brown, Carl

    2014-06-15

    Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Above-ground tree outside forest (TOF) phytomass and carbon estimation in the semiarid region of southern Haryana: A synthesis approach of remote sensing and field data

    Indian Academy of Sciences (India)

    Kuldeep Singh; Pritam Chand

    2012-12-01

    Trees outside forest (TOF) play an important role in global carbon cycling, since they are large pools of carbon as well as potential carbon sinks and sources to the atmosphere. In view of the importance of biomass estimates in the global carbon (C) cycle, the present study demonstrates the potential of the standwise tree outside forest inventory data and finer spatial resolution of IRS-P6 LISS-IV satellite data to classify TOF, to estimate above-ground TOF phytomass and the carbon content of TOF in a semiarid region of the southern Haryana, India. The study reports that above-ground TOF phytomass varied from 1.26 tons/ha in the scattered trees in the rural/urban area to 91.5 tons/ha in the dense linear TOF along the canal. The total above-ground TOF phytomass and carbon content was calculated as 367.04 and 174.34 tons/ha, respectively in the study area. The study results conclude that the classification of TOF and estimation of phytomass and carbon content in TOF can be successfully achieved through the combined approach of Remote Sensing and GIS based spatial technique with the supplement of field data. The present approach will help to find out the potential carbon sequestration zone in the semi-arid region of southern Haryana, India.

  3. Processing Remote Sensing Data with Python

    OpenAIRE

    Dillon, Ryan J., 1984-

    2013-01-01

    With public access available for numerous satellite imaging products, modelling in atmospheric and oceanographic applications has become increasingly more prevalent. Though there are numerous tools available for geospatial development, their use is more commonly applied towards mapping applications. With this being the case, there are a number of valuable texts for using these tools in such mapping applications; though, documentation for processing of remote sensing datasets is limited to ...

  4. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  5. Remote sensing application on geothermal exploration

    Science.gov (United States)

    Gaffar, Eddy Z.

    2013-09-01

    Geothermal energy is produced when water coming down from the surface of the earth and met with magma or hot rocks, which the heat comes from the very high levels of magma rises from the earth. This process produced a heated fluid supplied to a power generator system to finally use as energy. Geothermal field usually associated with volcanic area with a component from igneous rocks and a complex geological structures. The fracture and fault structure are important geological structures associated with geothermal. Furthermore, their geothermal manifestations also need to be evaluated associated their geological structures. The appearance of a geothermal surface manifestation is close to the structure of the fracture and the caldera volcanic areas. The relationship between the fault and geothermal manifestations can be seen in the form of a pattern of alignment between the manifestations of geothermal locations with other locations on the fault system. The use of remote sensing using electromagnetic radiation sensors to record images of the Earth's environment that can be interpreted to be a useful information. In this study, remote sensing was applied to determine the geological structure and mapping of the distribution of rocks and alteration rocks. It was found that remote sensing obtained a better localize areas of geothermal prospects, which in turn could cut the chain of geothermal exploration to reduce a cost of geothermal exploration.

  6. A Review of Wetland Remote Sensing.

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-04-05

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.

  7. A Review of Wetland Remote Sensing

    Science.gov (United States)

    Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

    2017-01-01

    Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers. PMID:28379174

  8. An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon

    Science.gov (United States)

    Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E. O. C.; Arai, Egidio; Simonetti, Dario; Achard, Frédéric

    2017-09-01

    Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the

  9. MTF online compensation in space optical remote sensing camera

    Science.gov (United States)

    Qu, Youshan; Zhai, Bo; Han, Yameng; Zhou, Jiang

    2015-02-01

    An ordinary space optical remote sensing camera is an optical diffraction-limited system and a low-pass filter from the theory of Fourier Optics, and all the digital imaging sensors, whether the CCD or CMOS, are low-pass filters as well. Therefore, when the optical image with abundant high-frequency components passes through an optical imaging system, the profuse middle-frequency information is attenuated and the rich high-frequency information is lost, which will blur the remote sensing image. In order to overcome this shortcoming of the space optical remote sensing camera, an online compensating approach of the Modulation Transfer Function in the space cameras is designed. The designed method was realized by a hardware analog circuit placed before the A/D converter, which was composed of adjustable low-pass filters with a calculated value of quality factor Q. Through the adjustment of the quality factor Q of the filters, the MTF of the processed image is compensated. The experiment results display that the realized compensating circuit in a space optical camera is capable of improving the MTF of an optical remote sensing imaging system 30% higher than that of no compensation. This quantized principle can efficiently instruct the MTF compensating circuit design in practice.

  10. The use of remote sensing for landslide studies in Europe

    Science.gov (United States)

    Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

    2013-04-01

    results can be obtained combining remote sensing with ground based networks data and in field observations, as this can allow defining the deformation patterns of a landslide and its relationship with the triggering conditions . According to the research and working experience of the compilers, remote sensing is generally considered to have a medium effectiveness/reliability for landslide studies. Moreover this depends also on how remote sensing is used: an increase in the number of used remote sensing data type (aerial photos, satellite optical, satellite radar etc.), corresponds to a growth of the degree of effectiveness/reliability. In general the number of parameters detectable through remote sensing is linked to the number of techniques employed: an increase in the number of measured parameters is related to an increase in the number of the techniques used, both for monitoring and for detection/mapping. Many answers reported the possibility of detecting more than one parameters by only using radar technologies: this could be considered as an indicator of a better efficiency of radar with respect to optical techniques. The results of the questionnaire thus contribute to draw a sketch of the use of remote sensing in current landslide studies and show that remote sensing can be considered a powerful and well established instrument for landslides mapping, monitoring and hazard analysis and highlight that a wide range of available techniques and source data can be approached depending on the size and velocity of the investigated phenomena

  11. Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches

    Directory of Open Access Journals (Sweden)

    Daniel Asare-Kyei

    2015-07-01

    Full Text Available Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI. Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.

  12. A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Sofia Siachalou

    2015-03-01

    Full Text Available Vegetation monitoring and mapping based on multi-temporal imagery has recently received much attention due to the plethora of medium-high spatial resolution satellites and the improved classification accuracies attained compared to uni-temporal approaches. Efficient image processing strategies are needed to exploit the phenological information present in temporal image sequences and to limit data redundancy and computational complexity. Within this framework, we implement the theory of Hidden Markov Models in crop classification, based on the time-series analysis of phenological states, inferred by a sequence of remote sensing observations. More specifically, we model the dynamics of vegetation over an agricultural area of Greece, characterized by spatio-temporal heterogeneity and small-sized fields, using RapidEye and Landsat ETM+ imagery. In addition, the classification performance of image sequences with variable spatial and temporal characteristics is evaluated and compared. The classification model considering one RapidEye and four pan-sharpened Landsat ETM+ images was found superior, resulting in a conditional kappa from 0.77 to 0.94 per class and an overall accuracy of 89.7%. The results highlight the potential of the method for operational crop mapping in Euro-Mediterranean areas and provide some hints for optimal image acquisition windows regarding major crop types in Greece.

  13. Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

    Science.gov (United States)

    Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

    2017-06-20

    The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

  14. Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an artificial neural network approach

    Science.gov (United States)

    Wandera, Loise; Mallick, Kaniska; Kiely, Gerard; Roupsard, Olivier; Peichl, Mathias; Magliulo, Vincenzo

    2017-04-01

    Upscaling instantaneous evapotranspiration retrieved at any specific time-of-day (ETi) to daily evapotranspiration (ETd) is a key challenge in mapping regional ET using polar orbiting sensors. Various studies have unanimously cited the shortwave incoming radiation (RS) to be the most robust reference variable explaining the ratio between ETd and ETi . This study aims to contribute in ETi upscaling for global studies using the ratio between daily and instantaneous incoming shortwave radiation (RSd / RSi) as a factor for converting ETi to ETd. This paper proposes an artificial neural network (ANN) machine-learning algorithm first to predict RSd from RSi followed by using the RSd / RSi ratio to convert ETi to ETd across different terrestrial ecosystems. Using RSi and RSd observations from multiple sub-networks of the FLUXNET database spread across different climates and biomes (to represent inputs that would typically be obtainable from remote sensors during the overpass time) in conjunction with some astronomical variables (e.g. solar zenith angle, day length, exoatmospheric shortwave radiation), we developed the ANN model for reproducing RSd and further used it to upscale ETi to ETd. The efficiency of the ANN is evaluated for different morning and afternoon times of day, under varying sky conditions, and also at different geographic locations. RS-based upscaled ETd produced a significant linear relation (R 2 = 0.65 to 0.69), low bias (-0.31 to -0.56 MJ m-2 d -1 ; approx. 4 %), and good agreement (RMSE 1.55 to 1.86 MJ m-2 d -1 ; approx. 10 %) with the observed ETd, although a systematic overestimation of ETd was also noted under persistent cloudy sky conditions. Inclusion of soil moisture and rainfall information in ANN training reduced the systematic overestimation tendency in predominantly overcast days. An intercomparison with existing upscaling method at daily, 8-day, monthly, and yearly temporal resolution revealed a robust performance of the ANNdriven RS

  15. Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an artificial neural network approach

    Science.gov (United States)

    Wandera, Loise; Mallick, Kaniska; Kiely, Gerard; Roupsard, Olivier; Peichl, Matthias; Magliulo, Vincenzo

    2017-01-01

    Upscaling instantaneous evapotranspiration retrieved at any specific time-of-day (ETi) to daily evapotranspiration (ETd) is a key challenge in mapping regional ET using polar orbiting sensors. Various studies have unanimously cited the shortwave incoming radiation (RS) to be the most robust reference variable explaining the ratio between ETd and ETi. This study aims to contribute in ETi upscaling for global studies using the ratio between daily and instantaneous incoming shortwave radiation (RSd / RSi) as a factor for converting ETi to ETd.This paper proposes an artificial neural network (ANN) machine-learning algorithm first to predict RSd from RSi followed by using the RSd / RSi ratio to convert ETi to ETd across different terrestrial ecosystems. Using RSi and RSd observations from multiple sub-networks of the FLUXNET database spread across different climates and biomes (to represent inputs that would typically be obtainable from remote sensors during the overpass time) in conjunction with some astronomical variables (e.g. solar zenith angle, day length, exoatmospheric shortwave radiation), we developed the ANN model for reproducing RSd and further used it to upscale ETi to ETd. The efficiency of the ANN is evaluated for different morning and afternoon times of day, under varying sky conditions, and also at different geographic locations. RS-based upscaled ETd produced a significant linear relation (R2 = 0.65 to 0.69), low bias (-0.31 to -0.56 MJ m-2 d-1; approx. 4 %), and good agreement (RMSE 1.55 to 1.86 MJ m-2 d-1; approx. 10 %) with the observed ETd, although a systematic overestimation of ETd was also noted under persistent cloudy sky conditions. Inclusion of soil moisture and rainfall information in ANN training reduced the systematic overestimation tendency in predominantly overcast days. An intercomparison with existing upscaling method at daily, 8-day, monthly, and yearly temporal resolution revealed a robust performance of the ANN-driven RS-based ETi

  16. OPTIMAL WAVELET FILTER DESIGN FOR REMOTE SENSING IMAGE COMPRESSION

    Institute of Scientific and Technical Information of China (English)

    Yang Guoan; Zheng Nanning; Guo Shugang

    2007-01-01

    A new approach for designing the Biorthogonal Wavelet Filter Bank (BWFB) for the purpose of image compression is presented in this letter. The approach is decomposed into two steps.First, an optimal filter bank is designed in theoretical sense based on Vaidyanathan's coding gain criterion in SubBand Coding (SBC) system. Then the above filter bank is optimized based on the criterion of Peak Signal-to-Noise Ratio (PSNR) in JPEG2000 image compression system, resulting in a BWFB in practical application sense. With the approach, a series of BWFB for a specific class of applications related to image compression, such as remote sensing images, can be fast designed. Here,new 5/3 BWFB and 9/7 BWFB are presented based on the above approach for the remote sensing image compression applications. Experiments show that the two filter banks are equally performed with respect to CDF 9/7 and LT 5/3 filter in JPEG2000 standard; at the same time, the coefficients and the lifting parameters of the lifting scheme are all rational, which bring the computational advantage, and the ease for VLSI implementation.

  17. Collaborative Approaches to Increase the Utility of Spatial Data for the Wildfire Management Community Through NASA's Applied Remote Sensing Training Program

    Science.gov (United States)

    McCullum, A. J. K.; Schmidt, C.; Blevins, B.; Weber, K.; Schnase, J. L.; Carroll, M.; Prados, A. I.

    2015-12-01

    The utility of spatial data products and tools to assess risk and effectively manage wildfires has increased, highlighting the need for communicating information about these new capabilities to decision makers, resource managers, and community leaders. NASA's Applied Remote Sensing Training (ARSET) program works directly with agencies and policy makers to develop in-person and online training courses that teach end users how to access, visualize, and apply NASA Earth Science data in their profession. The expansion of ARSET into wildfire applications began in 2015 with a webinar and subsequent in-person training hosted in collaboration with Idaho State University's (ISU) GIS Training and Research Center (TReC). These trainings featured presentations from the USDA Forest Service's Remote Sensing Training and Applications Center, the Land Processes DAAC, Northwest Nazarene University, NASA Goddard Space Flight Center, and ISU's GIS TReC. The webinar focused on providing land managers, non-governmental organizations, and international management agencies with an overview of 1) remote sensing platforms for wildfire applications, 2) products for pre- and post-fire planning and assessment, 3) the use of terrain data, 4) new techniques and technologies such as Unmanned Aircraft Systems and the Soil Moisture Active Passive Mission (SMAP), and 5) the RECOVER Decision Support System. This training highlighted online tools that engage the wildfire community through collaborative monitoring and assessment efforts. Webinar attendance included 278 participants from 178 organizations in 42 countries and 33 US states. The majority of respondents (93%) from a post-webinar survey indicated they displayed improvement in their understanding of specific remote-sensing data products appropriate for their work needs. With collaborative efforts between federal, state, and local agencies and academic institutions, increased use of NASA Earth Observations may lead to improved near real

  18. A Team Approach to the Development of Gamma Ray and x Ray Remote Sensing and in Situ Spectroscopy for Planetary Exploration Missions

    Science.gov (United States)

    Trombka, J. I.; Floyd, S.; Ruitberg, A.; Evans, L.; Starr, R.; Metzger, A.; Reedy, R.; Drake, D.; Moss, C.; Edwards, B.

    1993-01-01

    An important part of the investigation of planetary origin and evolution is the determination of the surface composition of planets, comets, and asteroids. Measurements of discrete line X-ray and gamma ray emissions from condensed bodies in space can be used to obtain both qualitative and quantitative elemental composition information. The Planetary Instrumentation Definition and Development Program (PIDDP) X-Ray/Gamma Ray Team has been established to develop remote sensing and in situ technologies for future planetary exploration missions.

  19. A spatial-temporal Hopfield neural network approach for super-resolution land cover mapping with multi-temporal different resolution remotely sensed images

    Science.gov (United States)

    Li, Xiaodong; Ling, Feng; Du, Yun; Feng, Qi; Zhang, Yihang

    2014-07-01

    The mixed pixel problem affects the extraction of land cover information from remotely sensed images. Super-resolution mapping (SRM) can produce land cover maps with a finer spatial resolution than the remotely sensed images, and reduce the mixed pixel problem to some extent. Traditional SRMs solely adopt a single coarse-resolution image as input. Uncertainty always exists in resultant fine-resolution land cover maps, due to the lack of information about detailed land cover spatial patterns. The development of remote sensing technology has enabled the storage of a great amount of fine spatial resolution remotely sensed images. These data can provide fine-resolution land cover spatial information and are promising in reducing the SRM uncertainty. This paper presents a spatial-temporal Hopfield neural network (STHNN) based SRM, by employing both a current coarse-resolution image and a previous fine-resolution land cover map as input. STHNN considers the spatial information, as well as the temporal information of sub-pixel pairs by distinguishing the unchanged, decreased and increased land cover fractions in each coarse-resolution pixel, and uses different rules in labeling these sub-pixels. The proposed STHNN method was tested using synthetic images with different class fraction errors and real Landsat images, by comparing with pixel-based classification method and several popular SRM methods including pixel-swapping algorithm, Hopfield neural network based method and sub-pixel land cover change mapping method. Results show that STHNN outperforms pixel-based classification method, pixel-swapping algorithm and Hopfield neural network based model in most cases. The weight parameters of different STHNN spatial constraints, temporal constraints and fraction constraint have important functions in the STHNN performance. The heterogeneity degree of the previous map and the fraction images errors affect the STHNN accuracy, and can be served as guidances of selecting the

  20. Characterization of Vegetation using the UC Davis Remote Sensing Testbed

    Science.gov (United States)

    Falk, M.; Hart, Q. J.; Bowen, K. S.; Ustin, S. L.

    2006-12-01

    Remote sensing provides information about the dynamics of the terrestrial biosphere with continuous spatial and temporal coverage on many different scales. We present the design and construction of a suite of instrument modules and network infrastructure with size, weight and power constraints suitable for small scale vehicles, anticipating vigorous growth in unmanned aerial vehicles (UAV) and other mobile platforms. Our approach provides the rapid deployment and low cost acquisition of high aerial imagery for applications requiring high spatial resolution and revisits. The testbed supports a wide range of applications, encourages remote sensing solutions in new disciplines and demonstrates the complete range of engineering knowledge required for the successful deployment of remote sensing instruments. The initial testbed is deployed on a Sig Kadet Senior remote controlled plane. It includes an onboard computer with wireless radio, GPS, inertia measurement unit, 3-axis electronic compass and digital cameras. The onboard camera is either a RGB digital camera or a modified digital camera with red and NIR channels. Cameras were calibrated using selective light sources, an integrating spheres and a spectrometer, allowing for the computation of vegetation indices such as the NDVI. Field tests to date have investigated technical challenges in wireless communication bandwidth limits, automated image geolocation, and user interfaces; as well as image applications such as environmental landscape mapping focusing on Sudden Oak Death and invasive species detection, studies on the impact of bird colonies on tree canopies, and precision agriculture.

  1. Advances in remote sensing of vegetation function and traits

    KAUST Repository

    Houborg, Rasmus

    2015-07-09

    Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.

  2. NEON Airborne Remote Sensing of Terrestrial Ecosystems

    Science.gov (United States)

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

    2012-12-01

    The National Ecological Observatory Network (NEON) is the continental-scale research platform that will collect information on ecosystems across the United States to advance our understanding and ability to forecast environmental change at the continental scale. One of NEON's observing systems, the Airborne Observation Platform (AOP), will fly an instrument suite consisting of a high-fidelity visible-to-shortwave infrared imaging spectrometer, a full waveform small footprint LiDAR, and a high-resolution digital camera on a low-altitude aircraft platform. NEON AOP is focused on acquiring data on several terrestrial Essential Climate Variables including bioclimate, biodiversity, biogeochemistry, and land use products. These variables are collected throughout a network of 60 sites across the Continental United States, Alaska, Hawaii and Puerto Rico via ground-based and airborne measurements. Airborne remote sensing plays a critical role by providing measurements at the scale of individual shrubs and larger plants over hundreds of square kilometers. The NEON AOP plays the role of bridging the spatial scales from that of individual organisms and stands to the scale of satellite-based remote sensing. NEON is building 3 airborne systems to facilitate the routine coverage of NEON sites and provide the capacity to respond to investigator requests for specific projects. The first NEON imaging spectrometer, a next-generation VSWIR instrument, was recently delivered to NEON by JPL. This instrument has been integrated with a small-footprint waveform LiDAR on the first NEON airborne platform (AOP-1). A series of AOP-1 test flights were conducted during the first year of NEON's construction phase. The goal of these flights was to test out instrument functionality and performance, exercise remote sensing collection protocols, and provide provisional data for algorithm and data product validation. These test flights focused the following questions: What is the optimal remote

  3. International Models and Methods of Remote Sensing Education and Training.

    Science.gov (United States)

    Anderson, Paul S.

    A classification of remote sensing courses throughout the world, the world-wide need for sensing instruction, and alternative instructional methods for meeting those needs are discussed. Remote sensing involves aerial photointerpretation or the use of satellite and other non-photographic imagery; its focus is to interpret what is in the photograph…

  4. Satellite Remote Sensing of Snow Depth on Antarctic Sea Ice: An Inter-Comparison of Two Empirical Approaches

    OpenAIRE

    Stefan Kern; Burcu Ozsoy-Çiçek

    2016-01-01

    Snow on Antarctic sea ice plays a key role for sea ice physical processes and complicates retrieval of sea ice thickness using altimetry. Current methods of snow depth retrieval are based on satellite microwave radiometry, which perform best for dry, homogeneous snow packs on level sea ice. We introduce an alternative approach based on in-situ measurements of total (sea ice plus snow) freeboard and snow depth, which we use to compute snow depth on sea ice from Ice, Cloud, and land Elevation S...

  5. Hyperspectral remote sensing of wild oyster reefs

    Science.gov (United States)

    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

  6. Remote sensing for land management and planning

    Science.gov (United States)

    Woodcock, Curtis E.; Strahler, Alan H.; Franklin, Janet

    1983-05-01

    The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States. Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners. Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes

  7. Optical Remote Sensing Potentials for Looting Detection

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-10-01

    Full Text Available Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social impact. In recent years, the employment of remote sensing technologies using ground-based and/or space-based sensors has assisted in dealing with this issue. Novel remote sensing techniques have tackled heritage destruction occurring in war-conflicted areas, as well as illicit archeological activity in vast areas of archaeological interest with limited surveillance. The damage performed by illegal activities, as well as the scarcity of reliable information are some of the major concerns that local stakeholders are facing today. This study discusses the potential use of remote sensing technologies based on the results obtained for the archaeological landscape of Ayios Mnason in Politiko village, located in Nicosia district, Cyprus. In this area, more than ten looted tombs have been recorded in the last decade, indicating small-scale, but still systematic, looting. The image analysis, including vegetation indices, fusion, automatic extraction after object-oriented classification, etc., was based on high-resolution WorldView-2 multispectral satellite imagery and RGB high-resolution aerial orthorectified images. Google Earth© images were also used to map and diachronically observe the site. The current research also discusses the potential for wider application of the presented methodology, acting as an early warning system, in an effort to establish a systematic monitoring tool for archaeological areas in Cyprus facing similar threats.

  8. Shape saliency for remote sensing image

    Science.gov (United States)

    Xu, Sheng; Hong, Huo; Fang, Tao; Li, Deren

    2007-11-01

    In this paper, a shape saliency measure for only shape feature of each object in the image is described. Instead biologically-inspired bottom-up Itti model, the dissimilarity is measured by the shape feature. And, Fourier descriptor is used for measuring dissimilarity in this paper. In the model, the object is determined as a salient region, when it is far different from others. Different value of the saliency is ranged to generate a saliency map. It is shown that the attention shift processing can be recorded. Some results from psychological images and remote sensing images are shown and discussed in the paper.

  9. Remote sensing and actuation using unmanned vehicles

    CERN Document Server

    Chao, Haiyang

    2012-01-01

    Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.

  10. Characrterizing frozen ground with multisensor remote sensing

    Science.gov (United States)

    Csatho, B. M.; Ping, C.; Everett, L. R.; Kimble, J. M.; Michaelson, G.; Tremper, C.

    2006-12-01

    We have a physically based, conceptual understanding of many of the significant interactions that impact permafrost-affected soils. Our observationally based knowledge, however, is inadequate in many cases to quantify these interactions or to predict their net impact. To pursue key goals, such as understanding the response of permafrost-affected soil systems to global environmental changes and their role in the carbon balance, and to transform our conceptual understanding of these processes into quantitative knowledge, it is necessary to acquire geographically diverse sets of fundamental observations at high spatial and often temporal resolution. The main goals of the research presented here are developing methods for mapping soil and permafrost distributions in polar environment as well as characterizing glacial and perglacial geomorphology from multisensor, multiresolution remotely sensed data. The sheer amount of data and the disparate data sets (e.g., LIDAR, stereo imagery, multi- hyperspectral, and SAR imagery) make the joint interpretation (fusion) a daunting task. We combine remote sensing, pattern recognition and landscape analysis techniques for the delineation of soil landscape units and other geomorphic features, for inferring the physical properties and composition of the surface, and for generating numerical measurements of geomorphic features from remotely sensed data. Examples illustrating the concept are presented from the North Slope of Alaska and from the McMurdo Sound region in Antarctica. (1) On the North Slope, Alaska we separated different vegetative, soil and landscape units along the Haul Road. Point-source soils (pedon) data and field spectrometry data have been acquired at different units to provide ground-truth for the satellite image interpretation. (2) A vast amount of remote sensing data, such as multi- and hyperspectral (Landsat, SPOT, ASTER, HYPERION) and SAR satellite imagery (ERS, RADARSAT and JERS), high resolution topographic

  11. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  12. Optical remote sensing of the earth

    Science.gov (United States)

    Goetz, A. F. H.; Wellman, J. B.; Barnes, W. L.

    1985-01-01

    In the present assessment of the contributions of optical earth resources remote sensing in the 0.4-15.0 micron region, attention is given to underlying principles, applications to scientific disciplines such as geology, hydrology and oceanography, the recent development history of the requisite sensors, and sensor development trends. Development status characterizations are given for thematic mapping, modular optoelectronic multispectral scanning, the telescope/CCD 'SPOT' program of France, the thermal IR multispectral scanner for mineral signature identification, airborne imaging spectrometry, and the Advanced Visible and IR Imaging Spectrometer that is nearing deployment. Technology development trends and the capabilities they portend are projected.

  13. Branching model for vegetation. [polarimetric remote sensing

    Science.gov (United States)

    Yueh, Simon H.; Kong, J. A.; Jao, Jen K.; Shin, Robert T.; Le Toan, Thuy

    1992-01-01

    In the present branching model for remote sensing of vegetation, the frequency and angular responses of a two-scale cylinder cluster are calculated to illustrate the importance of vegetation architecture. Attention is given to the implementation of a two-scale branching model for soybeans, where the relative location of soybean plants is described by a pair of distribution functions. Theoretical backscattering coefficients evaluated by means of hole-correction pair distribution are in agreement with extensive data collected from soybean fields. The hole-correction approximation is found to be the more realistic.

  14. Remote shock sensing and notification system

    Science.gov (United States)

    Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.

    2008-11-11

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  15. Remote shock sensing and notification system

    Energy Technology Data Exchange (ETDEWEB)

    Muralidharan, Govindarajan [Knoxville, TN; Britton, Charles L [Alcoa, TN; Pearce, James [Lenoir City, TN; Jagadish, Usha [Knoxville, TN; Sikka, Vinod K [Oak Ridge, TN

    2010-11-02

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interface circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitter with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  16. Evaluation of mass balance, 4D-Var, and hybrid approaches to constraining NOx emissions using OMI NO2 remote sensing measurements.

    Science.gov (United States)

    Qu, Z.

    2015-12-01

    Nitrogen oxides (NOx) contribute to photochemical smog, tropospheric ozone and aerosol, and human health problems. Remote sensing observations provide a valuable means of constraining emissions of NOx, and thus improving our ability to use air quality models for further understanding these issues. Traditional top-down estimates have provided important constraints for NOx emission inventories in China, but are either time-consuming (e.g., 4D-Var) or only crudely represent the influence of atmospheric transport and chemistry (e.g., mass balance). Here, we combine mass balance and 4D-Var approaches, and investigate the improvements in simulated NOx column density over China. Scaling factors derived from the mass balance approach with OMI observations are first applied to NOx emissions. In this process, a smoothing kernel is used to account for emissions from adjacent grid cells, and optimized NOx emissions are derived using maximum likelihood estimation, which weigh top-down and bottom up estimates by their relative errors. This is followed by subsequent inversion using an adjoint-based 4D-Var approach with GEOS-Chem at the 0.5x0.667 degree resolution. We consider the correlations between errors in neighboring grid cells by using off-diagonal terms in scaling factors' error covariance matrix. An optimal value of the regularization parameter is selected using an L-curve and minimization of total error. We compare the solutions obtained using this hybrid approach with that obtained from standard 4D-Var, as well as to the direct solution from the mass balance approach itself. Differences between these methods in specific grid cells are investigated. We demonstrate the effect of transport and chemistry on the performance of mass balance and 4D-Var, identifying cases where the smoothing kernel and weighting errors in mass balance can cause the scaling factor to be in a direction that occasionally increases residual error. This study shows potential to facilitate decadal

  17. Remote sensing and vegetation mapping in South Africa

    Directory of Open Access Journals (Sweden)

    M. L. Jarman

    1983-12-01

    Full Text Available The kinds of imagery, types of data and general relationships between scale of study, scale of mapping and scale of remote sensing products that are appropriate to the South African situation for visual and digital analysis are presented. The type of remote sensing product and processing, the type of field exercise appropriate to each, and the purpose of producing maps at each scale are discussed. Lack of repetitive imagery to date has not allowed for the full investigation of monitoring potential and careful planning at national level is needed to ensure availability of imagery for monitoring purposes. Map production processes which are rapid and accurate should be utilized. An integrated approach to vegetation mapping and surveying, which incorporates the best features of both visual and digital processing, is recommended for use.

  18. Remote sensing and vegetation mapping in South Africa

    Directory of Open Access Journals (Sweden)

    M. L. Jarman

    1983-12-01

    Full Text Available The kinds of imagery, types of data and general relationships between scale of study, scale of mapping and scale of remote sensing products that are appropriate to the South African situation for visual and digital analysis are presented. The type of remote sensing product and processing, the type of field exercise appropriate to each, and the purpose of producing maps at each scale are discussed. Lack of repetitive imagery to date has not allowed for the full investigation of monitoring potential and careful planning at national level is needed to ensure availability of imagery for monitoring purposes. Map production processes which are rapid and accurate should be utilized. An integrated approach to vegetation mapping and surveying, which incorporates the best features of both visual and digital processing, is recommended for use.

  19. Remote sensing for rural development planning in Africa

    Science.gov (United States)

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

    1983-01-01

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

  20. Accurate Annotation of Remote Sensing Images via Active Spectral Clustering with Little Expert Knowledge

    Directory of Open Access Journals (Sweden)

    Gui-Song Xia

    2015-11-01

    Full Text Available It is a challenging problem to efficiently interpret the large volumes of remotely sensed image data being collected in the current age of remote sensing “big data”. Although human visual interpretation can yield accurate annotation of remote sensing images, it demands considerable expert knowledge and is always time-consuming, which strongly hinders its efficiency. Alternatively, intelligent approaches (e.g., supervised classification and unsupervised clustering can speed up the annotation process through the application of advanced image analysis and data mining technologies. However, high-quality expert-annotated samples are still a prerequisite for intelligent approaches to achieve accurate results. Thus, how to efficiently annotate remote sensing images with little expert knowledge is an important and inevitable problem. To address this issue, this paper introduces a novel active clustering method for the annotation of high-resolution remote sensing images. More precisely, given a set of remote sensing images, we first build a graph based on these images and then gradually optimize the structure of the graph using a cut-collect process, which relies on a graph-based spectral clustering algorithm and pairwise constraints that are incrementally added via active learning. The pairwise constraints are simply similarity/dissimilarity relationships between the most uncertain pairwise nodes on the graph, which can be easily determined by non-expert human oracles. Furthermore, we also propose a strategy to adaptively update the number of classes in the clustering algorithm. In contrast with existing methods, our approach can achieve high accuracy in the task of remote sensing image annotation with relatively little expert knowledge, thereby greatly lightening the workload burden and reducing the requirements regarding expert knowledge. Experiments on several datasets of remote sensing images show that our algorithm achieves state

  1. A remote sensing approach for estimating the location and rate of urban irrigation in semi-arid climates

    Science.gov (United States)

    Johnson, Tyler D.; Belitz, Kenneth

    2012-01-01

    Urban irrigation is an important component of the hydrologic cycle in many areas of the arid and semiarid western United States. This paper describes a new approach that uses readily available datasets to estimate the location and rate of urban irrigation. The approach provides a repeatable methodology at 1/3 km2 resolution across a large urbanized area (500 km2). For this study, Landsat Thematic Mapper satellite imagery, air photos, climatic records, and a land-use map were used to: (1) identify the fraction of irrigated landscaping in urban areas, and (2) estimate the monthly rate of irrigation being applied to those areas. The area chosen for this study was the San Fernando Valley in Southern California. Identifying irrigated areas involved the use of 29 satellite images, air photos, and a land-use map. The fraction of a pixel that consists of irrigated landscaping (Firr) was estimated using a linear-mixture model of two land-cover endmembers (selected pixels within a satellite image that represent a targeted land-cover). The two endmembers were impervious and fully-irrigated landscaping. In the San Fernando Valley, we used airport buildings, runways, and pavement to represent the impervious endmember; golf courses and parks were used to represent the fully irrigated endmember. The average Firr using all 29 satellite scenes was 44%. Firr calculated from hand-digitizing using air photos for 13 randomly selected single-family-residential neighborhoods showed similar results (42%). Estimating the rate of irrigation required identification of a third endmember: areas that consisted of urban vegetation but were not irrigated. This "nonirrigated" endmember was used to compute a Normalized Difference Vegetation Index (NDVI) surplus, defined as the difference between the NDVI signals of the irrigated and nonirrigated endmembers. The NDVI signals from irrigated areas remains relatively constant throughout the year, whereas the signal from nonirrigated areas rises and

  2. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research.Key contents of basic research in remote sensing,including modeling,inversion,scaling and scientific experiments,are reviewed.Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  3. An Overview on Data Mining of Nighttime Light Remote Sensing

    Directory of Open Access Journals (Sweden)

    LI Deren

    2015-06-01

    Full Text Available When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future

  4. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    2013-09-30

    WA 98105 phone: (206) 685-2609 fax: (206) 543-6785 email: jessup@apl.washington.edu Robert A. Holman Merrick Haller, Alexander Kuropov, Tuba...Ozkan-Haller Oregon State University Corvallis, OR 97331 phone: (541) 737-2914 fax: (541) 737-2064 email: holman @coas.oregonstate.edu Steve...Infrared Remote Sensing and Lidar– UW: Chickadel and Jessup B. Electro-Optical Remote Sensing – OSU: Holman C. Microwave Remote Sensing – UW

  5. [A review on polarization information in the remote sensing detection].

    Science.gov (United States)

    Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

    2010-04-01

    Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

  6. SYMPOSIUM ON REMOTE SENSING IN THE POLAR REGIONS

    Science.gov (United States)

    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

  7. Basic research in the field of thermal infrared remote sensing

    Institute of Scientific and Technical Information of China (English)

    徐冠华

    2000-01-01

    This overview paper points out that one of the problems impeding further development of remote sensing is that not much attention has been paid to basic research. Key contents of basic research in remote sensing, including modeling, inversion, scaling and scientific experiments, are reviewed. Significance of basic research is demonstrated through summarizing the intentions and progress of the project "Quantitative Remote Sensing Research on Land Surface Energy Exchange".

  8. A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields

    Directory of Open Access Journals (Sweden)

    Assefa M. Melesse

    2007-06-01

    upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water- balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields.

  9. A Combined Remote Sensing-Numerical Modelling Approach to the Stability Analysis of Delabole Slate Quarry, Cornwall, UK

    Science.gov (United States)

    Havaej, Mohsen; Coggan, John; Stead, Doug; Elmo, Davide

    2016-04-01

    Rock slope geometry and discontinuity properties are among the most important factors in realistic rock slope analysis yet they are often oversimplified in numerical simulations. This is primarily due to the difficulties in obtaining accurate structural and geometrical data as well as the stochastic representation of discontinuities. Recent improvements in both digital data acquisition and incorporation of discrete fracture network data into numerical modelling software have provided better tools to capture rock mass characteristics, slope geometries and digital terrain models allowing more effective modelling of rock slopes. Advantages of using improved data acquisition technology include safer and faster data collection, greater areal coverage, and accurate data geo-referencing far exceed limitations due to orientation bias and occlusion. A key benefit of a detailed point cloud dataset is the ability to measure and evaluate discontinuity characteristics such as orientation, spacing/intensity and persistence. This data can be used to develop a discrete fracture network which can be imported into the numerical simulations to study the influence of the stochastic nature of the discontinuities on the failure mechanism. We demonstrate the application of digital terrestrial photogrammetry in discontinuity characterization and distinct element simulations within a slate quarry. An accurately geo-referenced photogrammetry model is used to derive the slope geometry and to characterize geological structures. We first show how a discontinuity dataset, obtained from a photogrammetry model can be used to characterize discontinuities and to develop discrete fracture networks. A deterministic three-dimensional distinct element model is then used to investigate the effect of some key input parameters (friction angle, spacing and persistence) on the stability of the quarry slope model. Finally, adopting a stochastic approach, discrete fracture networks are used as input for 3D

  10. Remotely Sensing the Photochemical Reflectance Index (PRI)

    Science.gov (United States)

    Vanderbilt, Vern

    2015-01-01

    In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.

  11. Theory of Geological Anomaly in Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Geological anomaly is geological body or complex body with obviously different compositions, structures or orders of genesis as compared with those in the surrounding areas. Geological anomaly, restrained by the geological factors closely associated with ore-forming process, is an important clue to ore deposits. The geological anomaly serves as a geological sign to locate ore deposits. Therefore, it is very important to study how to define the characteristics of geological anomaly and further to locate the changes in these characteristics. In this paper, the authors propose the geological anomaly based on the remote-sensing images and data, and expound systematically such image features as scale, size, boundary, morphology and genesis of geological anomalies. Then the authors introduce the categorization of the geological anomalies according to their geneses. The image characteristics of some types of geological anomalies, such as the underground geological anomaly, are also explained in detail. Based on the remote-sensing interpretation of these geological anomalies, the authors conclude that the forecasting and exploration of ore deposits should be focused on the following three aspects: (1) the analysis of geological setting and geological anomaly; (2) the analysis of circular geological anomaly, and (3) the comprehensive forecasting of ore deposits and the research into multi-source information.

  12. Environmental impact prediction using remote sensing images

    Institute of Scientific and Technical Information of China (English)

    Pezhman ROUDGARMI; Masoud MONAVARI; Jahangir FEGHHI; Jafar NOURI; Nematollah KHORASANI

    2008-01-01

    Environmental impact prediction is an important step in many environmental studies. Awide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005~2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.

  13. Remote sensing application for property tax evaluation

    Science.gov (United States)

    Jain, Sadhana

    2008-02-01

    This paper presents a study for linking remotely sensed data with property tax related issues. First, it discusses the key attributes required for property taxation and evaluates the capabilities of remote sensing technology to measure these attributes accurately at parcel level. Next, it presents a detailed case study of six representative wards of different characteristics in Dehradun, India, that illustrates how measurements of several of these attributes supported by field survey can be combined to address the issues related to property taxation. Information derived for various factors quantifies the property taxation contributed by an average dwelling unit of the different income groups. Results show that the property tax calculated in different wards varies between 55% for the high-income group, 32% for the middle-income group, 12% for the low-income group and 1% for squatter units. The study concludes that higher spatial resolution satellite data and integrates social survey helps to assess the socio-economic status of the population for tax contribution purposes.

  14. Land remote sensing commercialization: A status report

    Science.gov (United States)

    Bishop, W. P.; Heacock, E. L.

    1984-01-01

    The current offer by the United States Department of Commerce to transfer the U.S. land remote sensing program to the private sector is described. A Request for Proposals (RFP) was issued, soliciting offers from U.S. firms to provide a commercial land remote sensing satellite system. Proposals must address a complete system including satellite, communications, and ground data processing systems. Offerors are encouraged to propose to take over the Government LANDSAT system which consists of LANDSAT 4 and LANDSAT D'. Also required in proposals are the market development procedures and plans to ensure that commercialization is feasible and the business will become self-supporting at the earliest possible time. As a matter of Federal Policy, the solicitation is designed to protect both national security and foreign policy considerations. In keeping with these concerns, an offeror must be a U.S. Firm. Requirements for data quality, quantity, distribution and delivery are met by current operational procedures. It is the Government's desire that the Offeror be prepared to develop and operate follow-on systems without Government subsidies. However, to facilitate rapid commercialization, an offeror may elect to include in his proposal mechanisms for short term government financial assistance.

  15. Hyperspectral Remote Sensing of Urban Areas: An Overview of Techniques and Applications

    Directory of Open Access Journals (Sweden)

    Helmi Z.M. Shafri

    2012-06-01

    Full Text Available Over the past two decades, hyperspectral remote sensing from airborne and satellite systems has been used as a data source for numerous applications. Hyperspectral imaging is quickly moving into the mainstream of remote sensing and is being applied to remote sensing research studies. Hyperspectral remote sensing has great potential for analysing complex urban scenes. However, operational applications within urban environments are still limited, despite several studies that have explored the capabilities of hyperspectral data to map urban areas. In this paper, we review the methods for urban classification using hyperspectral remote sensing data and their applications. The general trends indicate that combined spatial-spectral and sensor fusion approaches are the most optimal for hyperspectral urban analysis. It is also clear that urban hyperspectral mapping is currently limited to airborne data, despite the availability of spaceborne hyperspectral systems. Possible future research directions are also discussed.

  16. Method of determining forest production from remotely sensed forest parameters

    Science.gov (United States)

    Corey, J.C.; Mackey, H.E. Jr.

    1987-08-31

    A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

  17. Levee Health Monitoring With Radar Remote Sensing

    Science.gov (United States)

    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

  18. Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population

    Science.gov (United States)

    Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnet, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; vanDonkelaar, Aaron; hide

    2013-01-01

    Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6e10% increases in respiratory and allergic health outcomes per interquartile range (3.97 mg m3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20e64) in the national study population. Risk estimates for air pollution and respiratory/ allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05).

  19. TCR backscattering characterization for microwave remote sensing

    Science.gov (United States)

    Riccio, Giovanni; Gennarelli, Claudio

    2014-05-01

    A Trihedral Corner Reflector (TCR) is formed by three mutually orthogonal metal plates of various shapes and is a very important scattering structure since it exhibits a high monostatic Radar Cross Section (RCS) over a wide angular range. Moreover it is a handy passive device with low manufacturing costs and robust geometric construction, the maintenance of its efficiency is not difficult and expensive, and it can be used in all weather conditions (i.e., fog, rain, smoke, and dusty environment). These characteristics make it suitable as reference target and radar enhancement device for satellite- and ground-based microwave remote sensing techniques. For instance, TCRs have been recently employed to improve the signal-to-noise ratio of the backscattered signal in the case of urban ground deformation monitoring [1] and dynamic survey of civil infrastructures without natural corners as the Musmeci bridge in Basilicata, Italy [2]. The region of interest for the calculation of TCR's monostatic RCS is here confined to the first quadrant containing the boresight direction. The backscattering term is presented in closed form by evaluating the far-field scattering integral involving the contributions related to the direct illumination and the internal bouncing mechanisms. The Geometrical Optics (GO) laws allow one to determine the field incident on each TCR plate and the patch (integration domain) illuminated by it, thus enabling the use of a Physical Optics (PO) approximation for the corresponding surface current densities to consider for integration on each patch. Accordingly, five contributions are associated to each TCR plate: one contribution is due to the direct illumination of the whole internal surface; two contributions originate by the impinging rays that are simply reflected by the other two internal surfaces; and two contributions are related to the impinging rays that undergo two internal reflections. It is useful to note that the six contributions due to the

  20. Comparing Three Approaches of Evapotranspiration Estimation in Mixed Urban Vegetation: Field-Based, Remote Sensing-Based and Observational-Based Methods

    Directory of Open Access Journals (Sweden)

    Hamideh Nouri

    2016-06-01

    Full Text Available Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications, highly treated drinking water is used for nearly all of Australia’s urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, particularly urban parklands, is of growing concern. The estimation of evapotranspiration (ET and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water, and climate characteristics. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia. In this paper, two practical ET estimation approaches are compared to a detailed Soil Water Balance (SWB analysis over a one year period. One approach is the Water Use Classification of Landscape Plants (WUCOLS method, which is based on expert opinion on the water needs of different classes of landscape plants. The other is a remote sensing approach based on the Enhanced Vegetation Index (EVI from Moderate Resolution Imaging Spectroradiometer (MODIS sensors on the Terra satellite. Both methods require knowledge of reference ET calculated from meteorological data. The SWB determined that plants consumed 1084 mm·yr−1 of water in ET with an additional 16% lost to drainage past the root zone, an amount sufficient to keep salts from accumulating in the root zone. ET by MODIS EVI was 1088 mm·yr−1, very close to the SWB estimate, while WUCOLS estimated the total water requirement at only 802 mm·yr−1, 26% lower than the SWB estimate and 37% lower than the amount actually added including the drainage fraction. Individual monthly ET by MODIS was not accurate, but these errors were cancelled out to give good agreement on an annual time step. We

  1. Scientific Programming Using Java and C: A Remote Sensing Example

    Science.gov (United States)

    Prados, Donald; Johnson, Michael; Mohamed, Mohamed A.; Cao, Chang-Yong; Gasser, Jerry; Powell, Don; McGregor, Lloyd

    1999-01-01

    This paper presents results of a project to port code for processing remotely sensed data from the UNIX environment to Windows. Factors considered during this process include time schedule, cost, resource availability, reuse of existing code, rapid interface development, ease of integration, and platform independence. The approach selected for this project used both Java and C. By using Java for the graphical user interface and C for the domain model, the strengths of both languages were utilized and the resulting code can easily be ported to other platforms. The advantages of this approach are discussed in this paper.

  2. Remote Sensing Training for Middle School through the Center of Excellence in Remote Sensing Education

    Science.gov (United States)

    Hayden, L. B.; Johnson, D.; Baltrop, J.

    2012-12-01

    Remote sensing has steadily become an integral part of multiple disciplines, research, and education. Remote sensing can be defined as the process of acquiring information about an object or area of interest without physical contact. As remote sensing becomes a necessity in solving real world problems and scientific questions an important question to consider is why remote sensing training is significant to education and is it relevant to training students in this discipline. What has been discovered is the interest in Science, Technology, Engineering and Mathematics (STEM) fields, specifically remote sensing, has declined in our youth. The Center of Excellence in Remote Sensing Education and Research (CERSER) continuously strives to provide education and research opportunities on ice sheet, coastal, ocean, and marine science. One of those continued outreach efforts are Center for Remote Sensing of Ice Sheets (CReSIS) Middle School Program. Sponsored by the National Science Foundation CReSIS Middle School Program offers hands on experience for middle school students. CERSER and NSF offer students the opportunity to study and learn about remote sensing and its vital role in today's society as it relate to climate change and real world problems. The CReSIS Middle School Program is an annual two-week effort that offers middle school students experience with remote sensing and its applications. Specifically, participants received training with Global Positioning Systems (GPS) where the students learned the tools, mechanisms, and applications of a Garmin 60 GPS. As a part of the program the students were required to complete a fieldwork assignment where several longitude and latitude points were given throughout campus. The students had to then enter the longitude and latitude points into the Garmin 60 GPS, navigate their way to each location while also accurately reading the GPS to make sure travel was in the right direction. Upon completion of GPS training the

  3. Integrated Approach (Geophysics and Remote Sensing) to identify Water-bearing Dyke Swarms and Fractured Basement in the Sinai Peninsula, Egypt

    Science.gov (United States)

    Mohamed, L.; Sultan, M.; Ahmed, M. E.; Sauck, W.; Abouelmagd, A. A.; Chouinard, K.

    2012-12-01

    An integrated approach utilizing Very Low Frequency (VLF) and magnetic field surveying and temporal remote sensing data including: (1) Advanced Space Borne Thermal Emission and Reflection (ASTER) data, (2) European Remote Sensing (ERS-1 and ERS-2) radar imagery, and (3) Tropical Rainfall Measuring Mission (TRMM) was used to delineate water-bearing sub-vertical shear zones within the basement complex of the Sinai Peninsula. The following steps were undertaken: (1) the shear zones and dyke swarms within the basement complex were delineated using false color ASTER band and band ratio images; (2) the spatial and temporal precipitation events over the basement complex were then identified from TRMM data, and (3) finally, observations extracted from temporal radar and thermal ASTER bands were used to identify the water-bearing shear zones and dyke swarms. A fracture or dyke was deemed to be water bearing if: (1) it witnessed a large increase in its reflectivity and emissivity compared to its surroundings following a precipitation event, and maintained such differences for periods ranging from days to months. Field observations and VLF investigations were then applied to test the validity of our satellite-based methodologies for locating targeted aquifer types and for refining the satellite-based selections. The VLF detects conductive water-saturated subvertical breccia zones in bedrock. Thirty two VLF transects were collected in September of 2011 and July of 2012 along with 10 magnetic profiles at the same VLF locations. Both VLF and magnetic transects were acquired along a traverse perpendicular to the dike orientations with station separations ranging from 10 to 25 m. The VLF receiver (T-VLF) measures the distortion of the normally horizontal electromagnetic flux lines by local electrical conductors. At each VLF station, and for each frequency used, the following were measured: the tilt of the electromagnetic field, from the horizontal (given in percentage), the

  4. An overview of remote sensing of chlorophyll fluorescence

    Science.gov (United States)

    Xing, Xiao-Gang; Zhao, Dong-Zhi; Liu, Yu-Guang; Yang, Jian-Hong; Xiu, Peng; Wang, Lin

    2007-03-01

    Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyl l - a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

  5. Satellite Based Education and Training in Remote Sensing and Geo-Information AN E-Learning Approach to Meet the Growing Demands in India

    Science.gov (United States)

    Raju, P. L. N.; Gupta, P. K.

    2012-07-01

    One of the prime activities of Indian Space Research Organisation's (ISRO) Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA) conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE) using NASA's Advanced Telecommunication Satellite (i.e. ATS 6) with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS) established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS) and Geographical Information System (GIS), mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and Geoinformation, capacity

  6. Cloud vertical distribution from radiosonde, remote sensing, and model simulations

    Science.gov (United States)

    Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Yoo, Hyelim; Cribb, Maureen

    2014-08-01

    Knowledge of cloud vertical structure is important for meteorological and climate studies due to the impact of clouds on both the Earth's radiation budget and atmospheric adiabatic heating. Yet it is among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product over the Southern Great Plains and along with ground-based and space-borne remote sensing products, use it to evaluate cloud layer distributions simulated by the National Centers for Environmental Prediction global forecast system (GFS) model. The primary objective of this study is to identify advantages and limitations associated with different cloud layer detection methods and model simulations. Cloud occurrence frequencies are evaluated on monthly, annual, and seasonal scales. Cloud vertical distributions from all datasets are bimodal with a lower peak located in the boundary layer and an upper peak located in the high troposphere. In general, radiosonde low-level cloud retrievals bear close resemblance to the ground-based remote sensing product in terms of their variability and gross spatial patterns. The ground-based remote sensing approach tends to underestimate high clouds relative to the radiosonde-based estimation and satellite products which tend to underestimate low clouds. As such, caution must be exercised to use any single product. Overall, the GFS model simulates less low-level and more high-level clouds than observations. In terms of total cloud cover, GFS model simulations agree fairly well with the ground-based remote sensing product. A large wet bias is revealed in GFS-simulated relative humidity fields at high levels in the atmosphere.

  7. Can we map swelling clays with remote sensing?

    Science.gov (United States)

    van der Meer, Freek

    Swelling soils are soils containing clay minerals that change volume with water content. The original volume of natural soils may change up to 150 percent with increasing water content, which creates major geological hazards that cause extensive damage worldwide. Current engineering practice for delineating areas of potential high swell builds on extensive laboratory analysis, including X-ray diffraction analysis for establishing clay mineralogy and Atterberg limits for deriving the swelling index. This is labour-intensive and thus expensive. Of key importance in assessing the swelling potential of soils is accurate mapping of clay mineralogy and amount (particularly of high swelling smectite and low swelling kaolinite-group minerals) and mapping of soil moisture. For applications related to slope instability processes, surface height and surface deformation need to be examined. Results from spectral analysis of clay mineral spectra presented in this paper show that careful examination of absorption bands allows the characterization and mapping of the clay mineralogy of the soil, which, in conjunction with spectral unmixing, may lead to surface fractions of the various clay minerals. This can potentially be empirically linked with current engineering tests. Remote sensing perspectives for spatial reproduction of these results are further examined in this paper. Imaging spectrometry ( ie, data acquisition in many narrow spectral bands that allow images of reflectance spectra to be derived) may provide insight in surface mineralogy, while microwave remote sensing could deliver soil moisture information. Interferometric SAR (InSAR) is one method of remotely sensed elevation mapping; other remote sensing approaches include radar and laser altimetry and the derivation of digital terrain data from stereoscopic imagery ( ie, Spot, MOMS, etc). This paper could form the basis for formulating a number of research projects within a framework of mapping swelling potential of

  8. Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria.

    Science.gov (United States)

    Stumpf, Richard P; Davis, Timothy W; Wynne, Timothy T; Graham, Jennifer L; Loftin, Keith A; Johengen, Thomas H; Gossiaux, Duane; Palladino, Danna; Burtner, Ashley

    2016-04-01

    Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments - since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins - especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of

  9. Remotely Sensed, catchment scale, estimations of flow resistance

    Science.gov (United States)

    Carbonneau, P.; Dugdale, S. J.

    2009-12-01

    Despite a decade of progress in the field of fluvial remote sensing, there are few published works using this new technology to advance and explore fundamental ideas and theories in fluvial geomorphology. This paper will apply remote sensing methods in order to re-visit a classic concept in fluvial geomorphology: flow resistance. Classic flow resistance equations such as those of Strickler and Keulegan typically use channel slope, channel depth or hydraulic radius and some measure channel roughness usually equated to the 50th or 84th percentile of the bed material size distribution. In this classic literature, empirical equations such as power laws are usually calibrated and validated with a maximum of a few hundred data points. In contrast, fluvial remote sensing methods are now capable of delivering millions of high resolution data points in continuous, catchment scale, surveys. On the river Tromie in Scotland, a full dataset or river characteristics is now available. Based on low altitude imagery and NextMap topographic data, this dataset has a continuous sampling of channel width at a resolution of 3cm, of depth and median grain size at a resolution of 1m, and of slope at a resolution of 5m. This entire data set is systematic and continuous for the entire 20km length of the river. When combined with discharge at the time of data acquisition, this new dataset offers the opportunity to re-examine flow resistance equations with a 2-4 orders of magnitude increase in calibration data. This paper will therefore re-examine the classic approaches of Strickler and Keulagan along with other more recent flow resistance equations. Ultimately, accurate predictions of flow resistance from remotely sensed parameters could lead to acceptable predictions of velocity. Such a usage of classic equations to predict velocity could allow lotic habitat models to account for microhabitat velocity at catchment scales without the recourse to advanced and computationally intensive

  10. Developing particle emission inventories using remote sensing (PEIRS).

    Science.gov (United States)

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

    2017-01-01

    Information regarding the magnitude and distribution of PM2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM2.5. This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R(2) = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.

  11. Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

    Science.gov (United States)

    Stumpf, Rick P; Davis, Timothy W.; Wynne, Timothy T.; Graham, Jennifer; Loftin, Keith A.; Johengen, T.H.; Gossiaux, D.; Palladino, D.; Burtner, A.

    2016-01-01

    Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates

  12. Malaria Modeling using Remote Sensing and GIS Technologies

    Science.gov (United States)

    Kiang, Richard

    2004-01-01

    Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

  13. Malaria Modeling using Remote Sensing and GIS Technologies

    Science.gov (United States)

    Kiang, Richard

    2004-01-01

    Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

  14. A Linear Feature-Based Approach for the Registration of Unmanned Aerial Vehicle Remotely-Sensed Images and Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Shijie Liu

    2016-01-01

    Full Text Available Compared with traditional manned airborne photogrammetry, unmanned aerial vehicle remote sensing (UAVRS has the advantages of lower cost and higher flexibility in data acquisition. It has, therefore, found various applications in fields such as three-dimensional (3D mapping, emergency management, and so on. However, due to the instability of the UAVRS platforms and the low accuracy of the onboard exterior orientation (EO observations, the use of direct georeferencing image data leads to large location errors. Light detection and ranging (LiDAR data, which is highly accurate 3D information, is treated as a complementary data source to the optical images. This paper presents a semi-automatic approach for the registration of UAVRS images and airborne LiDAR data based on linear control features. The presented approach consists of three main components, as follows. (1 Buildings are first separated from the point cloud by the integrated use of height and size filtering and RANdom SAmple Consensus (RANSAC plane fitting, and the 3D line segments of the building ridges and boundaries are semi-automatically extracted through plane intersection and boundary regularization with manual selections; (2 the 3D line segments are projected to the image space using the initial EO parameters to obtain the approximate locations, and all the corresponding 2D line segments are semi-automatically extracted from the UAVRS images. Meanwhile, the tie points of the UAVRS images are generated using a Förstner operator and least-squares image matching; and (3 by use of the equations derived from the coplanarity constraints of the linear control features and the colinear constraints of the tie points, block bundle adjustment is carried out to update the EO parameters of the UAVRS images in the coordinate framework of the LiDAR data, achieving the co-registration of the two datasets. Experiments were performed to demonstrate the validity and effectiveness of the presented

  15. An empirical approach to the remote sensing of the chlorophyll in the optically complex waters of the Estuary and Gulf of Saint-Lawrence

    Science.gov (United States)

    Yayla, K. Mehmet

    Data from five research cruises performed between 1997 and 2001 were processed in order to investigate the potential for improving remote sensing algorithms in the Estuary and Gulf of St. Lawrence. Measured in situ parameters included concentration-dependent indicators of the three critical, optically-active constituents, chlorophyll, Coloured Dissolved Organic Matter (CDOM) and Suspended Particulate Matter (SPM). The radiometric dataset used to investigate different types of algorithms consisted of multi-band above-surface remote sensing reflectance (Rrs) estimates. These estimates were computed from downwelling surface irradiance and upwelling sub-surface radiance measurements acquired using a SeaWiFS Profiler Multichannel Radiometer (SPMR). The chlorophyll data varied from approximately 0.1 to 17.3 mg.m -3 in the study region which extended from stations near the Saguenay River to the outer extremes of the Gulf of St. Lawrence. The CDOM and SPM concentration indicators were lower in the Gulf compared to the Estuary. Moderate correlation between in situ measurements was found between chlorophyll and SPM, as well as between CDOM and SPM. Chlorophyll and CDOM were virtually uncorrelated. The standard SeaWiFS Case-I chlorophyll retrieval algorithm, OC4v4, was applied to SPMR data acquired over a significant number of sampling stations (N=169). Algorithm shortcomings were noted when the OC4v4 algorithm was applied directly to the study region. Specific shortcomings, the overestimation of low, and underestimation of high chlorophyll concentrations were consistent with previous findings in coastal regions and particularly with previous findings in the NW Atlantic and in high latitude regions. In addition, the algorithmic output was found to be fairly strongly correlated with CDOM and SPM. A perturbation approach, based on the analysis of residuals between OC4v4 estimates and in situ data, showed that the retrieved chlorophyll biases (overestimates) were dependent on

  16. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  17. Remote Sensing of Parasitic Nematodes in Plants

    Science.gov (United States)

    Lawrence, Gary W.; King, Roger; Kelley, Amber T.; Vickery, John

    2007-01-01

    A method and apparatus for remote sensing of parasitic nematodes in plants, now undergoing development, is based on measurement of visible and infrared spectral reflectances of fields where the plants are growing. Initial development efforts have been concentrated on detecting reniform nematodes (Rotylenchulus reniformis) in cotton plants, because of the economic importance of cotton crops. The apparatus includes a hand-held spectroradiometer. The readings taken by the radiometer are processed to extract spectral reflectances at sixteen wavelengths between 451 and 949 nm that, taken together, have been found to be indicative of the presence of Rotylenchulus reniformis. The intensities of the spectral reflectances are used to estimate the population density of the nematodes in an area from which readings were taken.

  18. Toward interactive search in remote sensing imagery

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Do [Los Alamos National Laboratory; Harvey, Neal [Los Alamos National Laboratory; Theile, James [Los Alamos National Laboratory

    2010-01-01

    To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new design criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.

  19. Remote sensing and characterization of anomalous debris

    Science.gov (United States)

    Sridharan, R.; Beavers, W.; Lambour, R.; Gaposchkin, E. M.; Kansky, J.; Stansbery, E.

    1997-01-01

    The analysis of orbital debris data shows a band of anomalously high debris concentration in the altitude range between 800 and 1000 km. Analysis indicates that the origin is the leaking coolant fluid from nuclear power sources that powered a now defunct Soviet space-based series of ocean surveillance satellites. A project carried out to detect, track and characterize a sample of the anomalous debris is reported. The nature of the size and shape of the sample set, and the possibility of inferring the composition of the droplets were assessed. The technique used to detect, track and characterize the sample set is described and the results of the characterization analysis are presented. It is concluded that the nature of the debris is consistent with leaked Na-K fluid, although this cannot be proved with the remote sensing techniques used.

  20. Remote sensing of balsam fir forest vigor

    Science.gov (United States)

    Luther, Joan E.; Carroll, Allen L.

    1997-12-01

    The potential of remote sensing to monitor indices of forest health was tested by examining the spectral separability of plots with different balsam fir, Abies balsamea (L.) Mill, vigor. Four levels of vigor were achieved with controlled experimental manipulations of forest stands. In order of increasing vigor, the treatments were root pruning, control, thinning and thinning in combination with fertilization. Spectral reflectance of branchlets from each plot were measured under laboratory conditions using a field portable spectroradiometer with a spectral range from 350 - 2500 nm. Branchlets were discriminated using combinations of factor and discriminant analyses techniques with classification accuracies of 91% and 83% for early and late season analyses, respectively. Relationships between spectral reflectance measurements at canopy levels, stand vigor, and foliage quality for an insect herbivore will be analyzed further in support of future large scale monitoring of balsam fir vulnerability to insect disturbance.

  1. Benefits to world agriculture through remote sensing

    Science.gov (United States)

    Buffalano, A. C.; Kochanowski, P.

    1976-01-01

    Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy, and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 300 to 400 million dollars annually for the rest of the world.

  2. Biomass Burning Emissions from Fire Remote Sensing

    Science.gov (United States)

    Ichoku, Charles

    2010-01-01

    Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

  3. Multisensor image fusion techniques in remote sensing

    Science.gov (United States)

    Ehlers, Manfred

    Current and future remote sensing programs such as Landsat, SPOT, MOS, ERS, JERS, and the space platform's Earth Observing System (Eos) are based on a variety of imaging sensors that will provide timely and repetitive multisensor earth observation data on a global scale. Visible, infrared and microwave images of high spatial and spectral resolution will eventually be available for all parts of the earth. It is essential that efficient processing techniques be developed to cope with the large multisensor data volumes. This paper discusses data fusion techniques that have proved successful for synergistic merging of SPOT HRV, Landsat TM and SIR-B images. It is demonstrated that these techniques can be used to improve rectification accuracies, to depicit greater cartographic detail, and to enhance spatial resolution in multisensor image data sets.

  4. Adaptive Remote Sensing Texture Compression on GPU

    Directory of Open Access Journals (Sweden)

    Xiao-Xia Lu

    2010-11-01

    Full Text Available Considering the properties of remote sensing texture such as strong randomness and weak local correlation, a novel adaptive compression method based on vector quantizer is presented and implemented on GPU. Utilizing the property of Human Visual System (HVS, a new similarity measurement function is designed instead of using Euclid distance. Correlated threshold between blocks can be obtained adaptively according to the property of different images without artificial auxiliary. Furthermore, a self-adaptive threshold adjustment during the compression is designed to improve the reconstruct quality. Experiments show that the method can handle various resolution images adaptively. It can achieve satisfied compression rate and reconstruct quality at the same time. Index is coded to further increase the compression rate. The coding way is designed to guarantee accessing the index randomly too. Furthermore, the compression and decompression process is speed up with the usage of GPU, on account of their parallelism.

  5. Unsupervised classification of remote multispectral sensing data

    Science.gov (United States)

    Su, M. Y.

    1972-01-01

    The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

  6. Recent Progresses of Microwave Marine Remote Sensing

    Science.gov (United States)

    Yang, Jingsong; Ren, Lin; Zheng, Gang; Wang, He; He, Shuangyan; Wang, Juan; Li, Xiaohui

    2016-08-01

    It is presented in this paper the recent progresses of Dragon 3 Program (ID. 10412) in the field of microwave marine remote sensing including (1) ocean surface wind fields from full polarization synthetic aperture radars (SAR), (2) joint retrieval of directional ocean wave spectra from SAR and wave spectrometer, (3) error analysis on ENVISAT ASAR wave mode significant wave height (SWH) retrievals using triple collocation model, (4) typhoon observation from SAR and optical sensors, (5) ocean internal wave observation from SAR and optical sensors, (6) ocean eddy observation from SAR and optical sensors, (7) retrieval models of water vapor and wet tropospheric path delay for the HY-2A calibration microwave radiometer, (8) calibration of SWH from HY-2A satellite altimeter.

  7. Remote sensing with laser spectrum radar

    Science.gov (United States)

    Wang, Tianhe; Zhou, Tao; Jia, Xiaodong

    2016-10-01

    The unmanned airborne (UAV) laser spectrum radar has played a leading role in remote sensing because the transmitter and the receiver are together at laser spectrum radar. The advantages of the integrated transceiver laser spectrum radar is that it can be used in the oil and gas pipeline leak detection patrol line which needs the non-contact reflective detection. The UAV laser spectrum radar can patrol the line and specially detect the swept the area are now in no man's land because most of the oil and gas pipelines are in no man's land. It can save labor costs compared to the manned aircraft and ensure the safety of the pilots. The UAV laser spectrum radar can be also applied in the post disaster relief which detects the gas composition before the firefighters entering the scene of the rescue.

  8. Urban environmental health applications of remote sensing

    Science.gov (United States)

    Rush, M.; Goldstein, J.; Hsi, B. P.; Olsen, C. B.

    1974-01-01

    An urban area was studied through the use of the inventory-by-surrogate method rather than by direct interpretation of photographic imagery. Prior uses of remote sensing in urban and public research are examined. The effects of crowding, poor housing conditions, air pollution, and street conditions on public health are considered. Color infrared photography was used to categorize land use features and the grid method was used in photo interpretation analysis. The incidence of shigella and salmonella, hepatitis, meningitis, tuberculosis, myocardial infarction and veneral disease were studied, together with mortality and morbidity rates. Sample census data were randomly collected and validated. The hypothesis that land use and residential quality are associated with and act as an influence upon health and physical well-being was studied and confirmed.

  9. Diverse Planning for UAV Control and Remote Sensing.

    Science.gov (United States)

    Tožička, Jan; Komenda, Antonín

    2016-12-21

    Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

  10. Diverse Planning for UAV Control and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Jan Tožička

    2016-12-01

    Full Text Available Unmanned aerial vehicles (UAVs are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

  11. A selected bibliography: Remote sensing applications in wildlife management

    Science.gov (United States)

    Carneggie, David M.; Ohlen, Donald O.; Pettinger, Lawrence R.

    1980-01-01

    Citations of 165 selected technical reports, journal articles, and other publications on remote sensing applications for wildlife management are presented in a bibliography. These materials summarize developments in the use of remotely sensed data for wildlife habitat mapping, habitat inventory, habitat evaluation, and wildlife census. The bibliography contains selected citations published between 1947 and 1979.

  12. Estimation of Areal Soil Water Content through Microwave Remote Sensing

    NARCIS (Netherlands)

    Oevelen, van P.J.

    2000-01-01

    In this thesis the use of microwave remote sensing to estimate soil water content is investigated. A general framework is described which is applicable to both passive and active microwave remote sensing of soil water content. The various steps necessary to estimate areal soil water content are disc

  13. Hydrological Application of Remote Sensing: Surface States -- Snow

    Science.gov (United States)

    Hall, Dorothy K.; Kelly, Richard E. J.; Foster, James L.; Chang, Alfred T. C.

    2004-01-01

    Remote sensing research of snow cover has been accomplished for nearly 40 years. The use of visible, near-infrared, active and passive-microwave remote sensing for the analysis of snow cover is reviewed with an emphasis on the work on the last decade.

  14. Remote sensing observation used in offshore wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

    2008-01-01

    Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

  15. Deriving harmonised forest information in Europe using remote sensing methods

    DEFF Research Database (Denmark)

    Seebach, Lucia Maria

    the need for harmonised forest information can be satisfied using remote sensing methods. In conclusion, the study showed that it is possible to derive harmonised forest information of high spatial detail in Europe with remote sensing. The study also highlighted the imperative provision of accuracy...

  16. Potential benefits of remote sensing: Theoretical framework and empirical estimate

    Science.gov (United States)

    Eisgruber, L. M.

    1972-01-01

    A theoretical framwork is outlined for estimating social returns from research and application of remote sensing. The approximate dollar magnitude is given of a particular application of remote sensing, namely estimates of corn production, soybeans, and wheat. Finally, some comments are made on the limitations of this procedure and on the implications of results.

  17. Streamflow modelling by remote sensing: a contribution to digital earth

    NARCIS (Netherlands)

    Tan, M.L.; Latif, A.B.; Pohl, C.; Duan, Z.

    2014-01-01

    Remote sensing contributes valuable information to streamflow estimates. This paper discusses its relevance to the digital earth concept. The authors categorize the role of remote sensing in streamflow modelling and estimation. This paper emphasizes the applications and challenges of satellite-based

  18. Application of remote sensing to agricultural field trials.

    NARCIS (Netherlands)

    Clevers, J.G.P.W.

    1986-01-01

    Remote sensing techniques enable quantitative information about a field trial to be obtained instantaneously and non-destructively. The aim of this study was to identify a method that can reduce inaccuracies in field trial analysis, and to identify how remote sensing can support and/or replace conve

  19. Remote sensing fire and fuels in southern California

    Science.gov (United States)

    Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen

    2011-01-01

    Airborne remote sensing at infrared wavelengths has the potential to quantify large-fire properties related to energy release or intensity, residence time, fuel-consumption rate, rate of spread, and soil heating. Remote sensing at a high temporal rate can track fire-line outbreaks and acceleration and spotting ahead of a fire front. Yet infrared imagers and imaging...

  20. Study on spectral structure of quantum remote sensing

    Institute of Scientific and Technical Information of China (English)

    BI; Siwen; HAN; Jixia

    2006-01-01

    A study of the use of fine spectral structure in quantum remote sensing, including an expression, begins with a summary of present-day applications of spectrum remote sensing, which is followed by a theoretical discussion of the influence of electronic spin upon hydrogen-like atom energy levels and the calculation of spectral line in the absence of a circumstance field.

  1. Quantitative Application Study on Remote Sensing of Suspended Sediment

    Institute of Scientific and Technical Information of China (English)

    CHEN Yi-mei; XU Su-dong; LIN Qiang

    2012-01-01

    Quantitative application on remote sensing of suspended sediment is an important aspect of the engineering application of remote sensing study.In this paper,the Xiamen Bay is chosen as the study area.Eleven different phases of the remote sensing data are selected to establish a quantitative remote sensing model to map suspended sediment by using remote sensing images and the quasi-synchronous measured sediment data.Based on empirical statistics developed are the conversion models between instantaneous suspended sediment concentration and tidally-averaged suspended sediment concentration as well as the conversion models between surface layer suspended sediment concentration and the depth-averaged suspended sediment concentration.On this basis,the quantitative application integrated model on remote sensing of suspended sediment is developed.By using this model as well as multi-temporal remote sensing images,multi-year averaged suspended sediment concentration of the Xiamen Bay are predicted.The comparison between model prediction and observed data shows that the multi-year averaged suspended sediment concentration of studied sites as well as the concentration difference of neighboring sites can be well predicted by the remote sensing model with an error rate of 21.61% or less,which can satisfy the engineering requirements of channel deposition calculation.

  2. Technology Progress Report for Spaceborne Microwave Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    JHANG Jingshan; LIU Heguang; DONG Xiaolong

    2006-01-01

    In this presentation, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments formeteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (H J-1C) and China's lunar exploration satellite (Chang'E-1), are reported.

  3. Progress for Spaceborne Microwave Remote Sensing in China

    Institute of Scientific and Technical Information of China (English)

    JIANG Jingshan; LIU Heguang; DONG Xiaolong

    2008-01-01

    In this paper, technological progress for China's microwave remote sensing is introduced. New developments of the microwave remote sensing instruments for meteorological satellite FY-3, ocean dynamic measurement satellite (HY-2), environment small SAR satellite (HJ-1C) and China's lunar exploration satellite (Chang'E-1), geostationary orbit meteorological satellite FY-4M,are reported.

  4. Remote sensing monitoring of the global ozonosphere

    Science.gov (United States)

    Genco, S.; Bortoli, D.; Ravegnani, F.

    2013-10-01

    The use of CFCs, which are the main responsible for the ozone depletion in the upper atmosphere and the formation of the so-called "ozone hole" over Antarctic Region, was phase out by Montreal Protocol (1989). CFCs' concentration is recently reported to decrease in the free atmosphere, but severe episodes of ozone depletion in both Arctic and Antarctic regions are still occurring. Nevertheless the complete recovery of the Ozone layer is expected by about 2050. Recent simulation of perturbations in stratospheric chemistry highlight that circulation, temperature and composition are strictly correlated and they influence the global climate changes. Chemical composition plays an important role in the thermodynamic of the atmosphere, as every gaseous species can absorb and emit in different wavelengths, so their different concentration is responsible for the heating or cooling of the atmosphere. Therefore long-term observations are required to monitor the evolution of the stratospheric ozone layer. Measurements from satellite remote sensing instruments, which provide wide coverage, are supplementary to selective ground-based observations which are usually better calibrated, more stable in time and cover a wider time span. The combination of the data derived from different space-borne instruments calibrated with ground-based sensors is needed to produce homogeneous and consistent long-term data records. These last are required for robust investigations and especially for trend analysis. Here, we perform a review of the major remote-sensing techniques and of the principal datasets available to study the evolution of ozone layer in the past decades and predict future behavio

  5. A Remote Sensing and GIS Approach to Study the Long-Term Vegetation Recovery of a Fire-Affected Pine Forest in Southern Greece

    Directory of Open Access Journals (Sweden)

    Foula Nioti

    2015-06-01

    Full Text Available Management strategies and silvicultural treatments of fire-prone ecosystems often rely on knowledge of the regeneration potential and long-term recovery ability of vegetation types. Remote sensing and GIS applications are valuable tools providing cost-efficient information on vegetation recovery patterns and their associated environmental factors. In this study we used an ordinal classification scheme to describe the land cover changes induced by a wildfire that occurred in 1983 in Pinus brutia woodlands on Karpathos Aegean Island, south-eastern Greece. As a proxy variable that indicates ecosystem recovery, we also estimated the difference between the NDVI and NBR indices a few months (1984 and almost 30 years after the fire (2012. Environmental explanatory variables were selected using a digital elevation model and various thematic maps. To identify the most influential environmental factors contributing to woodland recovery, binary logistic regression and linear regression techniques were applied. The analyses showed that although a large proportion of the P. brutia woodland has recovered 26 years after the fire event, a considerable amount of woodland had turned into scrub vegetation. Altitude, slope inclination, solar radiation, and pre-fire woodland physiognomy were identified as dominant factors influencing the vegetation’s recovery probability. Additionally, altitude and inclination are the variables that explain changes in the satellite remote sensing vegetation indices reflecting the recovery potential. Pinus brutia showed a good post-fire recovery potential, especially in parts of the study area with increased moisture availability.

  6. Strategies for using remotely sensed data in hydrologic models

    Science.gov (United States)

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

    1981-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

  8. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    Science.gov (United States)

    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.

  9. Recent advances in remote sensing and geoinformation processing for land degradation assessment

    CERN Document Server

    Roeder, Achim

    2009-01-01

    Acknowledgements Contributors Achim Röder & Joachim Hill, Remote sensing and geoinformation processing in land degradation assessment-an introduction Part 1 Setting the scene: principles in remote sensing and spatial scene modelling for land degradation assessmentEric F. Lambin, Helmut Geist, James F. Reynolds & D. Mark Stafford-Smith, Coupled human-environment system approaches to desertification: Linking people to pixels Susan L. Ustin, Alacia Palacios-Orueta, Michael L. Whiting, Stéphane Jacquemoud & Lin Li, Remote sensing based assessm

  10. Remote Chemical Sensing Using Quantum Cascade Lasers

    Energy Technology Data Exchange (ETDEWEB)

    Harper, Warren W.; Schultz, John F.

    2003-01-30

    Spectroscopic chemical sensing research at Pacific Northwest National Laboratory (PNNL) is focused on developing advanced sensors for detecting the production of nuclear, chemical, or biological weapons; use of chemical weapons; or the presence of explosives, firearms, narcotics, or other contraband of significance to homeland security in airports, cargo terminals, public buildings, or other sensitive locations. For most of these missions, the signature chemicals are expected to occur in very low concentrations, and in mixture with ambient air or airborne waste streams that contain large numbers of other species that may interfere with spectroscopic detection, or be mistaken for signatures of illicit activity. PNNL’s emphasis is therefore on developing remote and sampling sensors with extreme sensitivity, and resistance to interferents, or selectivity. PNNL’s research activities include: 1. Identification of signature chemicals and quantification of their spectral characteristics, 2. Identification and development of laser and other technologies that enable breakthroughs in sensitivity and selectivity, 3. Development of promising sensing techniques through experimentation and modeling the physical phenomenology and practical engineering limitations affecting their performance, and 4. Development and testing of data collection methods and analysis algorithms. Close coordination of all aspects of the research is important to ensure that all parts are focused on productive avenues of investigation. Close coordination of experimental development and numerical modeling is particularly important because the theoretical component provides understanding and predictive capability, while the experiments validate calculations and ensure that all phenomena and engineering limitations are considered.

  11. Comparison of remote sensing and fixed-site monitoring approaches for examining air pollution and health in a national study population

    Science.gov (United States)

    Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnett, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; van Donkelaar, Aaron; Peters, Paul A.; Johnson, Markey

    2013-12-01

    Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6-10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m-3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20-64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is

  12. A combined remote sensing and modeling based approach to identify sustainable pathways for urban and peri-urban agriculture in China

    Science.gov (United States)

    Wattenbach, M.; Delgado, J. M.; Roessner, S.; Bochow, M.; Güntner, A.; Kropp, J.; Cantu Ros, A. G.; Hattermann, F.; Kolbe, T.; Sodoudi, S.; Cubasch, U. Ulrich; Zeitz, J.; Ross, L.; Böckel, K.; Fang, C.; Bo, L.; Pan, G.

    2012-04-01

    As the world's biggest economy, China is becoming the biggest consumer of resources globally. Given this trend, the over-proportional fast increase in urbanization presents China with fundamental problems. Among the most urgent ones is the increasing loss of agricultural land as urbanization takes place in the most productive regions along the coast. The latter is being responsible for a shift in agriculture production towards climatically less favorable areas. At the same time, the loss of green areas in and around growing cities is increasing the effect of the urban heat island. The perception of the potential risks related to this phenomenon, in the context of climate change, has led the Shanghai city administration to increase its urban-greening efforts, expanding the per capita area of green from 1m2 in 1990 to 12.5m2 in 2008. In this context, this paper aims at identifying the influence of urban and peri-urban agriculture (UPA) on the sustainability of the urban regions of Shanghai and Nanjing. In particular, it focuses on the effects of UPA on the greenhouse gas (GHG) emissions, soil nutrients and water balances, local climate and the structure and functions of the urbanized areas. We propose an interdisciplinary framework combining remote sensing, model simulations and GHG field observations and targeted at identifying "win-win" strategies for sustainable planning pathways showing high potentials for UPA. The framework is based on spatial scenario modeling, automatic classification of urban structure types and on a prototype of a high-quality spatial database consisting of a 3D city model. Dynamic boundary conditions for climate and urban development are provided by state of the art models. These approaches meet the needs of stakeholders and planners in China. A special emphasis is put on interdependencies between small holder farming in the urban and peri-urban zone and climate change adaptation and mitigation strategies focusing on improved management of

  13. International Commercial Remote Sensing Practices and Policies: A Comparative Analysis

    Science.gov (United States)

    Stryker, Timothy

    /geography, civil government, and have provided for appropriate measures for monitoring and compliance. This approach provides a valuable framework for companies, investors, customers, and foreign partners. The clearly-defined ground rules are designed to facilitate full private sector competition, innovation, and domestic and international market development. International market development remains a key issue for the U.S. Government and for U.S. industry in general. NOAA has learned of some interest by foreign governments in promulgating new laws and regulations to address this growing industry. However, to date, most governments have yet to publicize new commercial remote sensing laws or regulations. In some instances, data policies for commercial remote sensing have been developed, but only in the context of government-owned and operated systems, or private systems in which a government is the controlling shareholder. Other than some initial consultations and limited agreements between supplier nations, there has to date been little overall international coordination of commercial remote sensing policies and practices. The result has been an uncertain and non- uniform international business environment, which can cause difficulties for all commercial remote sensing operators. Related international market distortions inhibit the maturation of the industry and the normalization of business practices. This situation may make it more difficult for key stakeholders to make decisions on investments, purchases, regulatory affairs, and international partnerships. To put this growing industry on a more level footing, there should be further coordination

  14. Remote sensing methods for power line corridor surveys

    Science.gov (United States)

    Matikainen, Leena; Lehtomäki, Matti; Ahokas, Eero; Hyyppä, Juha; Karjalainen, Mika; Jaakkola, Anttoni; Kukko, Antero; Heinonen, Tero

    2016-09-01

    To secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments

  15. Multi- and hyperspectral remote sensing of tropical marine benthic habitats

    Science.gov (United States)

    Mishra, Deepak R.

    Tropical marine benthic habitats such as coral reef and associated environments are severely endangered because of the environmental degradation coupled with hurricanes, El Nino events, coastal pollution and runoff, tourism, and economic development. To monitor and protect this diverse environment it is important to not only develop baseline maps depicting their spatial distribution but also to document their changing conditions over time. Remote sensing offers an important means of delineating and monitoring coral reef ecosystems. Over the last twenty years the scientific community has been investigating the use and potential of remote sensing techniques to determine the conditions of the coral reefs by analyzing their spectral characteristics from space. One of the problems in monitoring coral reefs from space is the effect of the water column on the remotely sensed signal. When light penetrates water its intensity decreases exponentially with increasing depth. This process, known as water column attenuation, exerts a profound effect on remotely sensed data collected over water bodies. The approach presented in this research focuses on the development of semi-analytical models that resolves the confounding influence water column attenuation on substrate reflectance to characterize benthic habitats from high resolution remotely sensed imagery on a per-pixel basis. High spatial resolution satellite and airborne imagery were used as inputs in the models to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). These parameters were subsequently used in various bio-optical algorithms to deduce bottom albedo and then to classify the benthos, generating a detailed map of benthic habitats. IKONOS and QuickBird multispectral satellite data and AISA Eagle hyperspectral airborne data were used in this research for benthic habitat mapping along the north shore of Roatan Island, Honduras. The AISA Eagle classification was

  16. Satellite remote-sensing technologies used in forest fire management

    Institute of Scientific and Technical Information of China (English)

    TIAN Xiao-rui; Douglas J. Mcrae; SHU Li-fu; WANG Ming-yu; LI Hong

    2005-01-01

    Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.

  17. Predicting wheat production at regional scale by integration of remote sensing data with a simulation model

    NARCIS (Netherlands)

    Jongschaap, R.E.E.; Schouten, L.S.M.

    2005-01-01

    Optical remote sensing satellite data (SPOT HRV XS, Landsat 5 TM) were used to estimate winter wheat area in a pilot area of 5 × 5 km in the Southeast of France. The approach was scaled up to a larger area of 45 × 50 km and finally to the regional level covering several departments. Microwave remote

  18. Predicting wheat production at regional scale by integration of remote sensing data with a simulation model

    NARCIS (Netherlands)

    Jongschaap, R.E.E.; Schouten, L.S.M.

    2005-01-01

    Optical remote sensing satellite data (SPOT HRV XS, Landsat 5 TM) were used to estimate winter wheat area in a pilot area of 5 × 5 km in the Southeast of France. The approach was scaled up to a larger area of 45 × 50 km and finally to the regional level covering several departments. Microwave remote

  19. Commercial future: making remote sensing a media event

    Science.gov (United States)

    Lurie, Ian

    1999-12-01

    The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.

  20. Can Hyperspectral Remote Sensing Detect Species Specific Biochemicals ?

    Science.gov (United States)

    Vanderbilt, V. C.; Daughtry, C. S.

    2011-12-01

    Discrimination of a few plants scattered among many plants is a goal common to detection of agricultural weeds, invasive plant species and illegal Cannabis clandestinely grown outdoors, the subject of this research. Remote sensing technology provides an automated, computer based, land cover classification capability that holds promise for improving upon the existing approaches to Cannabis detection. In this research, we investigated whether hyperspectral reflectance of recently harvested, fully turgid Cannabis leaves and buds depends upon the concentration of the psychoactive ingredient Tetrahydrocannabinol (THC) that, if present at sufficient concentration, presumably would allow species-specific identification of Cannabis.

  1. NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

    the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

  2. NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

    Science.gov (United States)

    Giardino, Marco J.

    2008-01-01

    the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

  3. FRACTAL DIMENSION OF URBAN EXPANSION BASED ON REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    IACOB I. CIPRIAN

    2012-11-01

    Full Text Available Fractal Dimension of Urban Expansion Based on Remote Sensing Images: In Cluj-Napoca city the process of urbanization has been accelerated during the years and implication of local authorities reflects a relevant planning policy. A good urban planning framework should take into account the society demands and also it should satisfy the natural conditions of local environment. The expansion of antropic areas it can be approached by implication of 5D variables (time as a sequence of stages, space: with x, y, z and magnitude of phenomena into the process, which will allow us to analyse and extract the roughness of city shape. Thus, to improve the decision factor we take a different approach in this paper, looking at geometry and scale composition. Using the remote sensing (RS and GIS techniques we manage to extract a sequence of built-up areas (from 1980 to 2012 and used the result as an input for modelling the spatialtemporal changes of urban expansion and fractal theory to analysed the geometric features. Taking the time as a parameter we can observe behaviour and changes in urban landscape, this condition have been known as self-organized – a condition which in first stage the system was without any turbulence (before the antropic factor and during the time tend to approach chaotic behaviour (entropy state without causing an disequilibrium in the main system.

  4. Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

    Science.gov (United States)

    Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

    2017-06-12

    Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

  5. Retrieval of Remote Sensing Images Using Colour and Texture Attribute

    CERN Document Server

    Maheswary, Priti

    2009-01-01

    Grouping images into semantically meaningful categories using low-level visual feature is a challenging and important problem in content-based image retrieval. The groupings can be used to build effective indices for an image database. Digital image analysis techniques are being used widely in remote sensing assuming that each terrain surface category is characterized with spectral signature observed by remote sensors. Even with the remote sensing images of IRS data, integration of spatial information is expected to assist and to improve the image analysis of remote sensing data. In this paper we present a satellite image retrieval based on a mixture of old fashioned ideas and state of the art learning tools. We have developed a methodology to classify remote sensing images using HSV color features and Haar wavelet texture features and then grouping them on the basis of particular threshold value. The experimental results indicate that the use of color and texture feature extraction is very useful for image r...

  6. Computational Ghost Imaging for Remote Sensing

    Science.gov (United States)

    Erkmen, Baris I.

    2012-01-01

    This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In

  7. Remote Sensing of Ionosphere by IONOLAB Group

    Science.gov (United States)

    Arikan, Feza

    2016-07-01

    Ionosphere is a temporally and spatially varying, dispersive, anisotropic and inhomogeneous medium that is characterized primarily by its electron density distribution. Electron density is a complex function of spatial and temporal variations of solar, geomagnetic, and seismic activities. Ionosphere is the main source of error for navigation and positioning systems and satellite communication. Therefore, characterization and constant monitoring of variability of the ionosphere is of utmost importance for the performance improvement of these systems. Since ionospheric electron density is not a directly measurable quantity, an important derivable parameter is the Total Electron Content (TEC), which is used widely to characterize the ionosphere. TEC is proportional to the total number of electrons on a line crossing the atmosphere. IONOLAB is a research group is formed by Hacettepe University, Bilkent University and Kastamonu University, Turkey gathered to handle the challenges of the ionosphere using state-of-the-art remote sensing and signal processing techniques. IONOLAB group provides unique space weather services of IONOLAB-TEC, International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model based IRI-Plas-MAP, IRI-Plas-STEC and Online IRI-Plas-2015 model at www.ionolab.org. IONOLAB group has been working for imaging and monitoring of ionospheric structure for the last 15 years. TEC is estimated from dual frequency GPS receivers as IONOLAB-TEC using IONOLAB-BIAS. For high spatio-temporal resolution 2-D imaging or mapping, IONOLAB-MAP algorithm is developed that uses automated Universal Kriging or Ordinary Kriging in which the experimental semivariogram is fitted to Matern Function with Particle Swarm Optimization (PSO). For 3-D imaging of ionosphere and 1-D vertical profiles of electron density, state-of-the-art IRI-Plas model based IONOLAB-CIT algorithm is developed for regional reconstruction that employs Kalman Filters for state

  8. NASA Remote Sensing Research as Applied to Archaeology

    Science.gov (United States)

    Giardino, Marco J.; Thomas, Michael R.

    2002-01-01

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

  9. APPLICATION OF REMOTE SENSING TECHNOLOGY TO POPULATION ESTIMATION

    Institute of Scientific and Technical Information of China (English)

    ZHANG Bao-guang

    2003-01-01

    This paper attempts to explore a new avenue of urban small-regional population estimation by remote sensing technology, creatively and comprehensively for the first time using a residence count method, area (density) method and model method, incorporating the application experience of American scholars in the light of the state of our country. Firstly, the author proposes theoretical basis for population estimation by remote sensing, on the basis of analysing and evaluating the history and state quo of application of methods of population estimation by remote sens-ing. Secondly, two original types of mathematical models of population estimation are developed on the basis of remote sensing data, taking Tianjin City as an example. By both of the mathematical models the regional population may be estimated from remote sensing variable values with high accuracy. The number of the independent variables in the lat-ter model is somewhat smaller and the collection of remote sensing data is somewhat easier, but the deviation is a little larger. Finally, some viewpoints on the principled problems about the practical application of remote sensing to popu-lation estimation are put forward.

  10. THE USE OF REMOTE SENSING, REGRESSION QUANTILES, AND GIS APPROACHES FOR MODELING OF SCALLOP LARVAE: A Case Study in Funka Bay, Hokkaido, Japan

    Directory of Open Access Journals (Sweden)

    I Nyoman Radiarta

    2011-12-01

    Full Text Available In the development of scallop cultivation in Japan, larvae collection and propagation become an important factor. Although the monitoring program has been conducted, modeling of species distribution is becoming an important tool for understanding the effects of environmental changes and resources management. This study was conducted to construct a model for providing estimation of the scallop larvae distribution in Funka Bay, Hokkaido, Japan using the integration of remote sensing, Regression Quantile (RQ and Geographic Information System (GIS-based model. Data on scallop larvae were collected during one year spawning season from April to July 2003. Environmental parameters were extracted from multi sensor remotely sensed data (chlorophyll-a and sea surface temperature and a hydrographic chart (water depth. These parameters together with larvae data were then analyzed using RQ. Finally, spatial models were constructed within a GIS by combining the RQ models with digital map of environmental parameters. The results show that the model was best explained by using only sea surface temperature. The highest larvae densities were predicted in a relatively broad distribution along with the shallow water regions (Toyoura and Sawara to Yakumo and the deeper water areas (center of the bay. The spatial model built from the RQ provided robust estimation of the scallop larvae distributions in the study area, as confirmed by model validation using independent data. These findings could contribute on the monitoring program in this region in order to distinguish the potential areas for an effective spat collection.

  11. In Situ/Remote Sensing Integration to Assess Forest Health—A Review

    Directory of Open Access Journals (Sweden)

    Marion Pause

    2016-06-01

    Full Text Available For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted.

  12. Quantitative interpretation of Great Lakes remote sensing data

    Science.gov (United States)

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

    1980-01-01

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

  13. Remote sensing of rainfall for debris-flow hazard assessment

    Science.gov (United States)

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,

    2003-01-01

    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

  14. A catalog system for remote-sensing data

    Science.gov (United States)

    Singh, R. S.; Scherz, J. P.

    1974-01-01

    The Practical System for Cataloging, Indexing, and Retrieval of Remote Sensing Data developed by the Interdisciplinary Remote Sensing Group at the University of Wisconsin consists of a card catalog, a site-index-map, a site-index-file, an industry-index-file, and a project-index-file. The system is designed for retrieval of remote-sensing data which include imagery, magnetic tapes, flight logs, maps, ground-truth reports, and research reports containing raw data. It can be operated by conventional library methods, but provision has been made for digitizing the system for computer retrieval.

  15. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  16. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    1997-01-01

    This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, s

  17. Anomaly Detection from Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Qiandong Guo

    2016-12-01

    Full Text Available Hyperspectral remote sensing imagery contains much more information in the spectral domain than does multispectral imagery. The consecutive and abundant spectral signals provide a great potential for classification and anomaly detection. In this study, two real hyperspectral data sets were used for anomaly detection. One data set was an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS data covering the post-attack World Trade Center (WTC and anomalies are fire spots. The other data set called SpecTIR contained fabric panels as anomalies compared to their background. Existing anomaly detection algorithms including the Reed–Xiaoli detector (RXD, the blocked adaptive computation efficient outlier nominator (BACON, the random selection based anomaly detector (RSAD, the weighted-RXD (W-RXD, and the probabilistic anomaly detector (PAD are reviewed here. The RXD generally sets strict assumptions to the background, which cannot be met in many scenarios, while BACON, RSAD, and W-RXD employ strategies to optimize the estimation of background information. The PAD firstly estimates both background information and anomaly information and then uses the information to conduct anomaly detection. Here, the BACON, RSAD, W-RXD, and PAD outperformed the RXD in terms of detection accuracy, and W-RXD and PAD required less time than BACON and RSAD.

  18. Visibility assesment using remote sensing data

    Science.gov (United States)

    Toanca, Florica; Vasilescu, Jeni; Nicolae, Doina; Stefan, Sabina

    2016-04-01

    Severe weather events like fog have a high impact on all kinds of traffic operations. During the last decade was proven the capability of remote sensing equipments to detect fog cases in terms of duration, occurrence and dissipation. Therefore, in this study the data from Väïsälä CL31 ceilometer and Raman Depolarization Lidar installed at Magurele, Romania (44.35 N, 26.03 E) were used. The backscatter coefficient from Ceilometer and extinction coefficient and different lidar ratios (LR) values from Lidar were used in order to determine horizontal visibility during the fog events in Magurele area. Ceilometer backscatter coefficient profiles are obtained with a time resolution of 16 s and up to 7.5 km altitude. . A neural network algorithm was used to calculate the lidar ratio values for different aerosol types and also for different relative humidity. Thus, for continental aerosol the LR value is 58srad, for continental polluted is 60srad and for smoke LR is 55srad. The average visibility computed for radiation fog , dominant type (57 cases) occurring in Magurele, during 2012-2014 was 50m. An important result is that the dependence of horizontal visibility for radiation fog at Magurele on LR is insignificant. This means that radiation, meteorological and geographical factors influence fog generation more much than aerosol type.

  19. Assessment of Watershed Drought Using Remote Sensing

    Science.gov (United States)

    Chataut, S.; Piechota, T.

    2005-12-01

    This paper focuses on drought assessment of the Upper Colorado River Basin (UCRB) using remote sensing. Lee's Ferry discharge data for Colorado river in the UCRB and the various Palmer Drought Indices (PDI) such as Palmer Hydrological Drought Indices (PHDI), Palmer Drought Severity Index (PDSI), and Palmer Z Index (ZINDX) for the five climatic divisions of the UCRB for last 100 years will be analyzed to find out the best climatic division in the UCRB for carrying out the further analysis between the Normalized Difference Vegetation Index (NDVI) obtained from 5 km resolution Advanced Very High Radiometric Radar (AVHRR) data and the various PDI. The multivariate statistical technique called rotated principal component analysis will be carried out in the time series of the NDVI data in order to avoid multicollinearity and to extract the component that significantly explains the variance in the dataset. The corresponding significant principal scores will be correlated with the PDI to derive relationship between the NDVI and PDI. Preliminary analysis has shown that there is significant correlation between the NDVI and the various PDI, which implies that NDVI could be used as an important data source to detect and monitor the drought condition in the UCRB.

  20. Remote sensing applied to forest resources

    Science.gov (United States)

    Hernandezfilho, P. (Principal Investigator)

    1984-01-01

    The development of methodologies to classify reforested areas using remotely sensed data is discussed. A preliminary study was carried out in northeast of the Sao Paulo State in 1978. The reforested areas of Pinus spp and Eucalyptus spp were based on the spectral, spatial and temporal characteristics fo LANDSAT imagery. Afterwards, a more detailed study was carried out in the Mato Grosso do Sul State. The reforested areas were mapped in functions of the age (from: 0 to 1 year, 1 to 2 years, 2 to 3 years, 3 to 4 years, 4 to 5 years and 5 to 6 years) and of the heterogeneity stand (from: 0 to 20%, 20 to 40%, 40 to 60%, 60 to 80% and 80 to 100%). The relative differences between the artificial forest areas, estimated from LANDSAT data and ground information, varied from -8.72 to +9.49%. The estimation of forest volume through a multistage sampling technique, with probability proportional to size, is also discussed.

  1. An Ecophysiological Model for Remote Sensing of GPP

    Science.gov (United States)

    Tu, K. P.

    2010-12-01

    Remote sensing light use efficiency (LUE) models of terrestrial gross primary productivity (GPP) are currently limited by three main problems: 1) the ability to distinguish light absorption by the photosynthetically-active (FAPAR) and the non-photosynthetically active (FIPAR) portions of the canopy, 2) the spatial and temporal variation of the maximum LUE within and across biomes, and 3) parameterization of temperature and moisture scalars for different vegetation types. We address these three issues by 1) using the Enhanced Vegetation Index (EVI) or Soil-Adjusted Vegetation Index (SAVI) to estimate light absorption by the photosynthetically active fraction of the canopy (FAPAR), as opposed to using NDVI which appears to be sensitive to the non-photosynthetically active fraction and is therefore more indicative of the total canopy light interception (FIPAR), 2) estimating the maximum unstressed LUE based on the maximum quantum yield of photosynthesis, a physiological and well-constrained parameter, and 3) inferring seasonal variation in temperature and moisture stress using the phenological information in FAPAR time series, with a unique temperature optimum (Topt) determined for each pixel and moisture stress estimated from relative changes in FAPAR. In this approach, the model can be applied entirely with remote sensing observations of EVI (or EVI2 or SAVI), air temperature (Tair), and incident photosynthetically-active radiation (PAR). Aside from improved parameterization of stress functions based entirely on remote sensing observations, this approach is similar to previous LUE models based on the quantum yield of photosynthesis. However, it differs in that we incorporate recent evidence indicating that the time-averaged quantum yield is roughly one-half that of the instantaneous maximum quantum yield. This translates to time-averaged rates of GPP being roughly one-half the maximum instantaneous rates or GPPmean=GPPmax/2, consistent with studies showing strong

  2. The Archaeological Application of Multi-Sensor Remote Sensing Data in Qin Yongcheng Site

    Science.gov (United States)

    Wang, M.; Wan, Y.; Zhao, Z.

    2017-09-01

    Remote sensing archaeology bases on the use of remote sensing images and interpretation of the principles. The historic relics and sites are resulted from human activities and have constantly caused influences on the soil component, moisture content, temperature, vegetation growth and so on. Based on this thought, this paper proposed a new remote sensing model and approach that integrates optical and thermal infrared remote sensing data for archaeology. Taking the Qin Yongcheng site as the example, this method conducts a comprehensive analysis of key factors affecting archaeological application, that is, LST estimated with Landsat TM data, soil brightness, humidity and greenness obtained from GF-1 data, and then interprets the potential site targets. By conducting the field verification, it is shown that the interpreted potential sites are well consisted with the field investigations and have a high interpretation precision. It can provide a guide for further archaeological research.

  3. Remote sensing validation through SOOP technology: implementation of Spectra system

    Science.gov (United States)

    Piermattei, Viviana; Madonia, Alice; Bonamano, Simone; Consalvi, Natalizia; Caligiore, Aurelio; Falcone, Daniela; Puri, Pio; Sarti, Fabio; Spaccavento, Giovanni; Lucarini, Diego; Pacci, Giacomo; Amitrano, Luigi; Iacullo, Salvatore; D'Andrea, Salvatore; Marcelli, Marco

    2017-04-01

    The development of low-cost instrumentation plays a key role in marine environmental studies and represents one of the most innovative aspects of marine research. The availability of low-cost technologies allows the realization of extended observatory networks for the study of marine phenomena through an integrated approach merging observations, remote sensing and operational oceanography. Marine services and practical applications critically depends on the availability of large amount of data collected with sufficiently dense spatial and temporal sampling. This issue directly influences the robustness both of ocean forecasting models and remote sensing observations through data assimilation and validation processes, particularly in the biological domain. For this reason it is necessary the development of cheap, small and integrated smart sensors, which could be functional both for satellite data validation and forecasting models data assimilation as well as to support early warning systems for environmental pollution control and prevention. This is particularly true in coastal areas, which are subjected to multiple anthropic pressures. Moreover, coastal waters can be classified like case 2 waters, where the optical properties of inorganic suspended matter and chromophoric dissolved organic matter must be considered and separated by the chlorophyll a contribution. Due to the high costs of mooring systems, research vessels, measure platforms and instrumentation a big effort was dedicated to the design, development and realization of a new low cost mini-FerryBox system: Spectra. Thanks to the modularity and user-friendly employment of the system, Spectra allows to acquire continuous in situ measures of temperature, conductivity, turbidity, chlorophyll a and chromophoric dissolved organic matter (CDOM) fluorescences from voluntary vessels, even by non specialized operators (Marcelli et al., 2014; 2016). This work shows the preliminary application of this technology to

  4. A Remotely Sensed Global Terrestrial Drought Severity Index

    Science.gov (United States)

    Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

    2012-12-01

    Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

  5. Appendix E: Research papers. Use of remote sensing in landscape stratification for environmental impact assessment

    Science.gov (United States)

    Stanturf, J. A.; Heimbuch, D. G.

    1980-01-01

    A refinement to the matrix approach to environmental impact assessment is to use landscape units in place of separate environmental elements in the analysis. Landscape units can be delineated by integrating remotely sensed data and available single-factor data. A remote sensing approach to landscape stratification is described and the conditions under which it is superior to other approaches that require single-factor maps are indicated. Flowcharts show the steps necessary to develop classification criteria, delineate units and a map legend, and use the landscape units in impact assessment. Application of the approach to assessing impacts of a transmission line in Montana is presented to illustrate the method.

  6. Gully Erosion Mapping Using Remote Sensing Techniques in the ...

    African Journals Online (AJOL)

    NdifelaniM

    Gully Features Extraction Using Remote Sensing Techniques. Ndifelani .... catchment area and NDVI as threshold and the accuracy indicated a negligible over estimation. In SA, the use of ..... data and software used in this research. We also ...

  7. The U.S. Geological Survey Land Remote Sensing Program

    Science.gov (United States)

    ,

    2007-01-01

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

  8. A Web-Based Airborne Remote Sensing Telemetry Server Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A Web-based Airborne Remote Sensing Telemetry Server (WARSTS) is proposed to integrate UAV telemetry and web-technology into an innovative communication, command,...

  9. Remote sensing in forestry: Application to the Amazon region

    Science.gov (United States)

    Dejesusparada, N. (Principal Investigator); Tardin, A. T.; Dossantos, A.; Filho, P. H.; Shimabukuro, Y. E.

    1981-01-01

    The utilization of satellite remote sensing in forestry is reviewed with emphasis on studies performed for the Brazilian Amazon Region. Timber identification, deforestation, and pasture degradation after deforestation are discussed.

  10. Models for estimation of land remote sensing satellites operational efficiency

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.

    2017-01-01

    The paper deals with the problem of estimation of land remote sensing satellites operational efficiency. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  11. REMOTE SENSING APPLICATIONS FOR SUSTAINABLE WATERSHED MANAGEMENT AND FOOD SECURITY

    Science.gov (United States)

    The integration of IKONOS satellite data, airborne color infrared remote sensing, visualization, and decision support tools is discussed, within the contexts of management techniques for minimizing non-point source pollution in inland waterways, such s riparian buffer restoration...

  12. Remote sensing and geochemistry techniques for the assessment of ...

    African Journals Online (AJOL)

    Chiedza

    in winter because of thermal inversion. High levels of ... land characterised by vents which as conduit for oxygen and spontaneous combustion ... remote sensing data to map heavy metal enrichment and accumulation near the Emalahleni.

  13. Lidar Remote Sensing for Forest Canopy Studies 2014

    Science.gov (United States)

    Remote sensing has facilitated extraordinary advances in modeling, mapping, and the understanding of ecosystems. Conventional sensors have significant limitations for ecological and forest applications. The sensitivity and accuracy of these devices have repeatedly been shown to fall with increasing ...

  14. REMOTE SENSING APPLICATIONS FOR SUSTAINABLE WATERSHED MANAGEMENT AND FOOD SECURITY

    Science.gov (United States)

    The integration of IKONOS satellite data, airborne color infrared remote sensing, visualization, and decision support tools is discussed, within the contexts of management techniques for minimizing non-point source pollution in inland waterways, such s riparian buffer restoration...

  15. Remote sensing application for delineating coastal vegetation - A case study

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.; Wagle, B.G.

    Remote sensing data has been used for mapping coastal vegetation along the Goa Coast, India. The study envisages the use of digital image processing techniques for delineating geomorphic features and associated vegetation, including mangrove, along...

  16. Future Opportunities and Challenges in Remote Sensing of Drought

    Science.gov (United States)

    Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

    2011-01-01

    The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and

  17. Future opportunities and challenges in remote sensing of drought

    Science.gov (United States)

    Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

    2012-01-01

    The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and

  18. Remote Sensing Information Sciences Research Group, year four

    Science.gov (United States)

    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.

  19. Using remotely-sensed data for optimal field sampling

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-09-01

    Full Text Available to carry out a fieldwork sample is an important issue as it avoids subjective judgement and can save on time and costs in the field. STATISTICAL SAMPLING, USING DATA OBTAINED FROM REMOTE SENSING, FINDS APPLICATION IN A VARIETY OF FIELDS... M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical...

  20. Laser And Nonlinear Optical Materials For Laser Remote Sensing

    Science.gov (United States)

    Barnes, Norman P.

    2005-01-01

    NASA remote sensing missions involving laser systems and their economic impact are outlined. Potential remote sensing missions include: green house gasses, tropospheric winds, ozone, water vapor, and ice cap thickness. Systems to perform these measurements use lanthanide series lasers and nonlinear devices including second harmonic generators and parametric oscillators. Demands these missions place on the laser and nonlinear optical materials are discussed from a materials point of view. Methods of designing new laser and nonlinear optical materials to meet these demands are presented.

  1. Validating firn compaction model with remote sensing data

    OpenAIRE

    2011-01-01

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland ...

  2. Remote sensing solutions for when spectrometers no longer are affordable

    Science.gov (United States)

    van Brug, Hedser; Visser, Huib

    2016-10-01

    This paper describes one of the issues that are facing the remote sensing community in the not so far future; scientists ask for certain requirement that cannot be fulfilled either due to cost issues or technological issues. The paper starts with giving a short and quick historical overview of the development of spectrometer based remote sensing systems. Next, the likely end of the spectrometers will be explained, followed by a possible alternative.

  3. Can remote sensing help citizen-science based phenological studies?

    Science.gov (United States)

    Delbart, Nicolas; Elisabeth, Beaubien; Laurent, Kergoat; Thuy, Le Toan

    2017-04-01

    Citizen science networks and remote sensing are both efficient to collect massive data related to phenology. However both differ in their advantages and drawbacks for this purpose. Contrarily to remote sensing, citizen science allows distinguishing species-specific phenological responses to climate variability. On the other hand, large portions of territory of a country like Canada are not covered by citizen science networks, and the time series are often incomplete. The main mode of interaction between both types of data consists in validating the maps showing the ecosystem foliage transition times, such as the green-up date, obtained from remote sensing data with field observations, and in particular those collected by citizen scientists. Thus the citizen science phenology data bring confidence to remote sensing based studies. However, one can merely find studies in which remote sensing is used to improve in any way citizen science based study. Here we present bi-directional interactions between both types of data. We first use phenological data from the PlantWatch citizen science network to show that one remote sensing method green-up date relates to the leaf-out date of woody species but also to the whole plant community phenology at the regional level, including flowering phenology. Second we use a remote sensing time series to constrain the analysis of citizen data to overcome the main drawbacks that is the incompleteness of time series. In particular we analyze the interspecies differences in phenology at the scale of so-called "pheno-regions" delineated using remote sensing green-up maps.

  4. Remote sensing and vegetation stress detection - Problems and progress

    Science.gov (United States)

    Duggin, M. J.; Whitehead, V.

    1983-01-01

    Although considerable progress has been made in applying remote sensing technology to vegetation monitoring, considerable problems still exist in the improvement of techniques for crop type discrimination, stress detection on a large scale, and stress quantification. In this paper, some of the problems remaining in the operational use of remote sensing technology for vegetation stress detection are discussed, and directions in which some of these problems might be solved are proposed.

  5. Remote sensing for quantification of agronomic properties

    Science.gov (United States)

    Sullivan, Dana Grace

    Remote sensing (RS) may be used to rapidly assess surface features and facilitate natural resource management, precision agriculture and soil survey. Information obtained in such a way would streamline data collection and improve diagnostic capabilities. Current RS technology has had limited testing, particularly within the Southeast. Our study was designed to evaluate RS as a rapid assessment tool in three different natural resource applications: nitrogen (N) management in a corn crop (Zea mays L.), assessment of in situ crop residue cover, and quantification of near-surface soil properties. In 2000, study sites were established in four physiographic provinces of Alabama: Tennessee Valley, Ridge and Valley, Appalachian Plateau, and Coastal Plain. Spectral measurements were acquired via spectroradiometer (350--1050 nm), airborne ATLAS multispectral scanner (400--12,500 nm), and IKONOS satellite (450--900 nm). Corn plots were established from fresh-tilled ground in a completely randomized design at the Appalachian Plateau and Coastal Plain study sites in 2000. Plots received four N rates (0, 56, 112, and 168 kg N ha-1 ), and were maintained for three consecutive growing seasons. Spectroradiometer data were acquired biweekly from V6-R2 and ATLAS and IKONOS were acquired per availability. Results showed vegetation indices derived from hand-held spectroradiometer measurements as early as V6-V8 were linearly related to yield and tissue N. ATLAS imagery showed promise at the AP site during the V6 stage (r2 = 0.66), but no significant relationships between plant N and IKONOS imagery were observed. Residue plots (15m x 15m) were established at the Appalachian Plateau and Coastal Plain in 2000 and 200. Residue treatments consisted of hand applied wheat straw cover (0, 10 20, 50, or 80%) arranged in a completely randomized design. Spectroradiometer data were acquired monthly and ATLAS and IKONOS were acquired per availability. Residue cover estimates were best with ATLAS

  6. NASA Remote Sensing Data for Epidemiological Studies

    Science.gov (United States)

    Maynard, Nancy G.; Vicente, G. A.

    2002-01-01

    In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.

  7. Satellite remote sensing of hailstorms in France

    Science.gov (United States)

    Melcón, Pablo; Merino, Andrés; Sánchez, José Luis; López, Laura; Hermida, Lucía

    2016-12-01

    Hailstorms are meteorological phenomena of great interest to the scientific community, owing to their socioeconomic impact, which is mainly on agricultural production. With its global coverage and high spatial and temporal resolution, satellite remote sensing can contribute to monitoring of such events through the development of appropriate techniques. This paper presents an extensive validation in the south of France of a hail detection tool (HDT) developed for the Middle Ebro Valley (MEV). The HDT is based on consecutive application of two filters, a convection mask (CM) and hail mask (HM), using spectral channels of the Meteosat Second Generation (MSG) satellite. The south of France is an ideal area for studying hailstorms, because there is a robust database of hail falls recorded by an extensive network of hailpads managed by the Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA). The results show noticeably poorer performance of the HDT in France relative to that in the MEV, with probability of detection (POD) 60.4% and false alarm rate (FAR) 26.6%. For this reason, a new tool to suit the characteristics of hailstorms in France has been developed. The France Hail Detection Tool (FHDT) was developed using logistic regression from channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor of the MSG. The FHDT was validated, resulting in POD 69.3% and FAR 15.4%, thus improving hail detection in the study area as compared with the previous tool. The new tool was tested in a case study with satisfactory results, supporting its future practical application.

  8. Satellite Remote Sensing in Seismology. A Review

    Directory of Open Access Journals (Sweden)

    Andrew A. Tronin

    2009-12-01

    Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

  9. Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

    Science.gov (United States)

    Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

    2014-01-01

    Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37

  10. KW-SIFT descriptor for remote-sensing image registration

    Institute of Scientific and Technical Information of China (English)

    Xiangzeng Liu; Zheng Tian; Weidong Yan; Xifa Duan

    2011-01-01

    A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.Affine invariant SIFT descriptor is first developed in an elliptical region determined by the Hessian matrix of the feature points.Thereafter,the descriptor is mapped to a feature space induced by a kernel, and a new descriptor is constructed by whitening the mapped descriptor in the feature space, with the transform called KW-SIFT.In a final step, the new descriptor is used to register remote-sensing images.Experimental results for remote-sensing image registration indicate that the proposed method improves the registration performance as compared with other related methods.%@@ A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.Affine invariant SIFT descriptor is first developed in an elliptical region determined by the Hessian matrix of the feature points.Thereafter,the descriptor is mapped to a feature space induced by a kernel, and a new descriptor is constructed by whitening the mapped descriptor in the feature space, with the transform called KW-SIFT.In a final step, the new descriptor is used to register remote-sensing images.Experimental results for remote-sensing image registration indicate that the proposed method improves the registration performance as compared with other related methods.

  11. Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Zhaoqin Li

    2014-11-01

    Full Text Available Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1 scale issue; (2 transportability issue; (3 data availability; and (4 uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

  12. Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

    Science.gov (United States)

    Li, Zhaoqin; Xu, Dandan; Guo, Xulin

    2014-11-07

    Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

  13. Some insights on grassland health assessment based on remote sensing.

    Science.gov (United States)

    Xu, Dandan; Guo, Xulin

    2015-01-29

    Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  14. Standardizing Quality Assessment of Fused Remotely Sensed Images

    Science.gov (United States)

    Pohl, C.; Moellmann, J.; Fries, K.

    2017-09-01

    The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

  15. USING COVARIANCE INTERSECTION FOR CHANGE DETECTION IN REMOTE SENSING IMAGES

    Institute of Scientific and Technical Information of China (English)

    Yang Meng; Zhang Gong

    2011-01-01

    In this paper,an unsupervised change detection technique for remote sensing images acquired on the same geographical area but at different time instances is proposed by conducting Covariance Intersection (CI) to perform unsupervised fusion of the final fuzzy partition matrices from the Fuzzy C-Means (FCM) clustering for the feature space by applying compressed sampling to the given remote sensing images.The proposed approach exploits a CI-based data fusion of the membership function matrices,which are obtained by taking the Fuzzy C-Means (FCM) clustering of the frequency-domain feature vectors and spatial-domain feature vectors,aimed at enhancing the unsupervised change detection performance.Compressed sampling is performed to realize the image local feature sampling,which is a signal acquisition framework based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable recovery.The experimental results demonstrate that the proposed algorithm has a good change detection results and also performs quite well on denoising purpose.

  16. Remote sensing images segmentation by Deriche's filter and neural network

    Science.gov (United States)

    Koffi, Raphael K.; Solaiman, Basel; Mouchot, Marie-Catherine

    1994-12-01

    An image segmentation method for remote sensing data using hybride techniques is proposed. Edge detection approach for segmentation is considered in our study. Our aim is to integrate segmentation results in further processing namely classification. Images of the land from satellite are often corrupted by noise. On one hand, optimal edge detectors insure good noise immunity. On the other hand, the multi-layer perceptron (MLP) neural network has been found to be suited for classification. So we propose to combine these two techniques to improve segmentation process. Satellites for remote sensing provide several images for the same area, coded differently according to spectral bands. In order to bear in mind spectral and spatial information, neighborhood relation of pixels and different bands are taken into consideration during the classification realized by the neural network. Samples which constituate the training set for the MLP are selected from the third, fourth and fifth band and represent edge and non-edge patterns. Each sample vector is composed of the value of a current pixel in the local maxima image (enhancement image obtained by Deriche's filter) and its 8 nearest neighbors. The proposed method provides satisfactory results for our application and compared to other similar methods.

  17. Some Insights on Grassland Health Assessment Based on Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dandan Xu

    2015-01-01

    Full Text Available Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  18. Nonlocal Total Variation Subpixel Mapping for Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Ruyi Feng

    2016-03-01

    Full Text Available Subpixel mapping is a method of enhancing the spatial resolution of images, which involves dividing a mixed pixel into subpixels and assigning each subpixel to a definite land-cover class. Traditionally, subpixel mapping is based on the assumption of spatial dependence, and the spatial correlation information among pixels and subpixels is considered in the prediction of the spatial locations of land-cover classes within the mixed pixels. In this paper, a novel subpixel mapping method for hyperspectral remote sensing imagery based on a nonlocal method, namely nonlocal total variation subpixel mapping (NLTVSM, is proposed to use the nonlocal self-similarity prior to improve the performance of the subpixel mapping task. Differing from the existing spatial regularization subpixel mapping technique, in NLTVSM, the nonlocal total variation is used as a spatial regularizer to exploit the similar patterns and structures in the image. In this way, the proposed method can obtain an optimal subpixel mapping result and accuracy by considering the nonlocal spatial information. Compared with the classical and state-of-the-art subpixel mapping approaches, the experimental results using a simulated hyperspectral image, two synthetic hyperspectral remote sensing images, and a real hyperspectral image confirm that the proposed algorithm can obtain better results in both visual and quantitative evaluations.

  19. Suitability Evaluation for Products Generation from Multisource Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Jining Yan

    2016-12-01

    Full Text Available With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-term series Earth observation, and have, in particular, made standard, automated product generation more popular. However, there is more than one type of data selection for producing a certain remote sensing product; no single remote sensor can cover such a large area at one time. Therefore, we should automatically select the best data source from redundant multisource remote sensing data, or select substitute data if data is lacking, during the generation of remote sensing products. However, the current data selection strategy mainly adopts the empirical model, and has a lack of theoretical support and quantitative analysis. Hence, comprehensively considering the spectral characteristics of ground objects and spectra differences of each remote sensor, by means of spectrum simulation and correlation analysis, we propose a suitability evaluation model for product generation. The model will enable us to obtain the Production Suitability Index (PSI of each remote sensing data. In order to validate the proposed model, two typical value-added information products, NDVI and NDWI, and two similar or complementary remote sensors, Landsat-OLI and HJ1A-CCD1, were chosen, and the verification experiments were performed. Through qualitative and quantitative analysis, the experimental results were consistent with our model calculation results, and strongly proved the validity of the suitability evaluation model. The proposed production suitability evaluation model could assist with standard, automated, serialized product generation. It will play an important role in one-station, value-added information services during the big data era of Earth observation.

  20. Remote sensing of forest insect disturbances: Current state and future directions.

    Science.gov (United States)

    Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

    2017-08-01

    Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

  1. Remote sensing of forest insect disturbances: Current state and future directions

    Science.gov (United States)

    Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

    2017-08-01

    Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

  2. Quarterly literature review of the remote sensing of natural resources

    Science.gov (United States)

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

    1977-01-01

    The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports.

  3. Managing and distributing remote sensing images based on metadata and microimage

    Science.gov (United States)

    Su, Lihong; Deng, Xiaolian; Wang, Jindi; Li, Xiaowen

    2003-06-01

    . By this metadata and microimage approach, the remote sensing images can be browsed, evaluated and ordered on Internet conveniently. It is feasible way to manage the remote sensing images.

  4. System and method for evaluating wind flow fields using remote sensing devices

    Science.gov (United States)

    Schroeder, John; Hirth, Brian; Guynes, Jerry

    2016-12-13

    The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

  5. System and method for evaluating wind flow fields using remote sensing devices

    Energy Technology Data Exchange (ETDEWEB)

    Schroeder, John; Hirth, Brian; Guynes, Jerry

    2016-12-13

    The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

  6. Remote sensing place : Satellite images as visual spatial imaginaries

    NARCIS (Netherlands)

    Shim, David

    How do people come to know the world? How do they get a sense of place and space? Arguably, one of the ways in which they do this is through the practice of remote sensing, among which satellite imagery is one of the most widespread and potent tools of engaging, representing and constructing space.

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

    Science.gov (United States)

    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…

  8. Remote Sensing Time Series Product Tool

    Science.gov (United States)

    Predos, Don; Ryan, Robert E.; Ross, Kenton W.

    2006-01-01

    programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

  9. Water Quality Assessment using Satellite Remote Sensing

    Science.gov (United States)

    Haque, Saad Ul

    2016-07-01

    The two main global issues related to water are its declining quality and quantity. Population growth, industrialization, increase in agriculture land and urbanization are the main causes upon which the inland water bodies are confronted with the increasing water demand. The quality of surface water has also been degraded in many countries over the past few decades due to the inputs of nutrients and sediments especially in the lakes and reservoirs. Since water is essential for not only meeting the human needs but also to maintain natural ecosystem health and integrity, there are efforts worldwide to assess and restore quality of surface waters. Remote sensing techniques provide a tool for continuous water quality information in order to identify and minimize sources of pollutants that are harmful for human and aquatic life. The proposed methodology is focused on assessing quality of water at selected lakes in Pakistan (Sindh); namely, HUBDAM, KEENJHAR LAKE, HALEEJI and HADEERO. These lakes are drinking water sources for several major cities of Pakistan including Karachi. Satellite imagery of Landsat 7 (ETM+) is used to identify the variation in water quality of these lakes in terms of their optical properties. All bands of Landsat 7 (ETM+) image are analyzed to select only those that may be correlated with some water quality parameters (e.g. suspended solids, chlorophyll a). The Optimum Index Factor (OIF) developed by Chavez et al. (1982) is used for selection of the optimum combination of bands. The OIF is calculated by dividing the sum of standard deviations of any three bands with the sum of their respective correlation coefficients (absolute values). It is assumed that the band with the higher standard deviation contains the higher amount of 'information' than other bands. Therefore, OIF values are ranked and three bands with the highest OIF are selected for the visual interpretation. A color composite image is created using these three bands. The water quality

  10. Remote sensing of essential ecosystem functional variables

    Science.gov (United States)

    Alcaraz-Segura, D.; Bagnato, C. E.; Paruelo, J. M.; Berbery, E. H.; Cabello, J.; Castro, A.; Cazorla, B. P.; Epstein, H. E.; Fernández, N.; Jobbagy, E. G.; Oyonarte, C.; Pacheco, M.; Peñas, J.; Vallejos, M.

    2016-12-01

    Essential Biodiversity Variables should inform on the status of the three dimensions recognised for biodiversity: composition, structure and function. Whereas composition and structure (from genes to ecosystems) have been traditionally used to assess biodiversity status, functional components of biodiversity, particularly at the ecosystem level, have been scarcely included. Satellite remote sensing can provide multiple descriptors of ecosystem function, though their relevance as essential biodiversity variables still needs to be assessed. Time-series of spectral data derived from satellite images can inform on key attributes of the dynamics of carbon, water, energy balance, disturbance regime or nutrient cycling. These ecosystem functional attributes can be integrated to identify Ecosystem Functional Types (EFTs), defined as groups of ecosystems with similar dynamics of matter and energy exchanges between the biota and the physical environment. Most popular EFTs used the three most informative metrics of the seasonal curves of spectral vegetation indices as surrogates of the most integrative descriptor of ecosystem functioning, the primary production dynamics: annual mean (estimator of primary production), seasonal coefficient of variation (descriptor of seasonality), and date of maximum (indicator of phenology). To search for simple metrics that could be used as a set of highly informative ecosystem functional attributes, we extended the analysis to the global scale across all terrestrial biomes and to other key dimensions of ecosystem functioning, i.e., albedo and surface temperature (related to the energy balance) and evapotranspiration (related to the water cycle and the energy balance). The three first axes of a Principal Component Analysis run on the average seasonal dynamics of each variable and biome explained from 85% to 97% of variance. From more than 20 summary metrics analysed, the annual mean was highly correlated to the first axis (r2>0.9). The second

  11. Footprint Representation of Planetary Remote Sensing Data

    Science.gov (United States)

    Walter, S. H. G.; Gasselt, S. V.; Michael, G.; Neukum, G.

    The geometric outline of remote sensing image data, the so called footprint, can be represented as a number of coordinate tuples. These polygons are associated with according attribute information such as orbit name, ground- and image resolution, solar longitude and illumination conditions to generate a powerful base for classification of planetary experiment data. Speed, handling and extended capabilites are the reasons for using geodatabases to store and access these data types. Techniques for such a spatial database of footprint data are demonstrated using the Relational Database Management System (RDBMS) PostgreSQL, spatially enabled by the PostGIS extension. Exemplary, footprints of the HRSC and OMEGA instruments, both onboard ESA's Mars Express Orbiter, are generated and connected to attribute information. The aim is to provide high-resolution footprints of the OMEGA instrument to the science community for the first time and make them available for web-based mapping applications like the "Planetary Interactive GIS-on-the-Web Analyzable Database" (PIG- WAD), produced by the USGS. Map overlays with HRSC or other instruments like MOC and THEMIS (footprint maps are already available for these instruments and can be integrated into the database) allow on-the-fly intersection and comparison as well as extended statistics of the data. Footprint polygons are generated one by one using standard software provided by the instrument teams. Attribute data is calculated and stored together with the geometric information. In the case of HRSC, the coordinates of the footprints are already available in the VICAR label of each image file. Using the VICAR RTL and PostgreSQL's libpq C library they are loaded into the database using the Well-Known Text (WKT) notation by the Open Geospatial Consortium, Inc. (OGC). For the OMEGA instrument, image data is read using IDL routines developed and distributed by the OMEGA team. Image outlines are exported together with relevant attribute

  12. Integrating Remote Sensing and Disease Surveillance to Forecast Malaria Epidemics

    Science.gov (United States)

    Wimberly, M. C.; Beyane, B.; DeVos, M.; Liu, Y.; Merkord, C. L.; Mihretie, A.

    2015-12-01

    Advance information about the timing and locations of malaria epidemics can facilitate the targeting of resources for prevention and emergency response. Early detection methods can detect incipient outbreaks by identifying deviations from expected seasonal patterns, whereas early warning approaches typically forecast future malaria risk based on lagged responses to meteorological factors. A critical limiting factor for implementing either of these approaches is the need for timely and consistent acquisition, processing and analysis of both environmental and epidemiological data. To address this need, we have developed EPIDEMIA - an integrated system for surveillance and forecasting of malaria epidemics. The EPIDEMIA system includes a public health interface for uploading and querying weekly surveillance reports as well as algorithms for automatically validating incoming data and updating the epidemiological surveillance database. The newly released EASTWeb 2.0 software application automatically downloads, processes, and summaries remotely-sensed environmental data from multiple earth science data archives. EASTWeb was implemented as a component of the EPIDEMIA system, which combines the environmental monitoring data and epidemiological surveillance data into a unified database that supports both early detection and early warning models. Dynamic linear models implemented with Kalman filtering were used to carry out forecasting and model updating. Preliminary forecasts have been disseminated to public health partners in the Amhara Region of Ethiopia and will be validated and refined as the EPIDEMIA system ingests new data. In addition to continued model development and testing, future work will involve updating the public health interface to provide a broader suite of outbreak alerts and data visualization tools that are useful to our public health partners. The EPIDEMIA system demonstrates a feasible approach to synthesizing the information from epidemiological

  13. Research on compressive fusion for remote sensing images

    Science.gov (United States)

    Yang, Senlin; Wan, Guobin; Li, Yuanyuan; Zhao, Xiaoxia; Chong, Xin

    2014-02-01

    A compressive fusion of remote sensing images is presented based on the block compressed sensing (BCS) and non-subsampled contourlet transform (NSCT). Since the BCS requires small memory space and enables fast computation, firstly, the images with large amounts of data can be compressively sampled into block images with structured random matrix. Further, the compressive measurements are decomposed with NSCT and their coefficients are fused by a rule of linear weighting. And finally, the fused image is reconstructed by the gradient projection sparse reconstruction algorithm, together with consideration of blocking artifacts. The field test of remote sensing images fusion shows the validity of the proposed method.

  14. Research on Key Technology of Mining Remote Sensing Dynamic Monitoring Information System

    Science.gov (United States)

    Sun, J.; Xiang, H.

    2017-09-01

    Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.

  15. Remote sensing strategies for global resource exploration and environmental management

    Science.gov (United States)

    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

  16. A Prototype Network for Remote Sensing Validation in China

    Directory of Open Access Journals (Sweden)

    Mingguo Ma

    2015-04-01

    Full Text Available Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC. The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation. Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.

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

    Science.gov (United States)

    1993-01-01

    should be based on the integration of remotely-sensed data with semi-deterministic agrometeorological models. This approach will allow a...sensed data with semi-deterministic agrometeorological models. This approach will allow a regionalization of the production estimates. Keywords...successfully classified and discriminated fields of maize in Zambia based on a multitemporal analysis of a vegetation index calculated from Landsat Thematic

  18. Acoustic remote sensing of ocean flows

    Digital Repository Service at National Institute of Oceanography (India)

    Joseph, A.; Desa, E.

    Acoustic techniques have become powerful tools for measurement of ocean circulation mainly because of the ability of acoustic signals to travel long distances in water, and the inherently non-invasive nature of measurement. The satellite remote...

  19. Scaling up functional traits for ecosystem services with remote sensing: concepts and methods.

    Science.gov (United States)

    Abelleira Martínez, Oscar J; Fremier, Alexander K; Günter, Sven; Ramos Bendaña, Zayra; Vierling, Lee; Galbraith, Sara M; Bosque-Pérez, Nilsa A; Ordoñez, Jenny C

    2016-07-01

    Ecosystem service-based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot-level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community-weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between

  20. TOGA - A GNSS Reflections Instrument for Remote Sensing Using Beamforming

    Science.gov (United States)

    Esterhuizen, S.; Meehan, T. K.; Robison, D.

    2009-01-01

    Remotely sensing the Earth's surface using GNSS signals as bi-static radar sources is one of the most challenging applications for radiometric instrument design. As part of NASA's Instrument Incubator Program, our group at JPL has built a prototype instrument, TOGA (Time-shifted, Orthometric, GNSS Array), to address a variety of GNSS science needs. Observing GNSS reflections is major focus of the design/development effort. The TOGA design features a steerable beam antenna array which can form a high-gain antenna pattern in multiple directions simultaneously. Multiple FPGAs provide flexible digital signal processing logic to process both GPS and Galileo reflections. A Linux OS based science processor serves as experiment scheduler and data post-processor. This paper outlines the TOGA design approach as well as preliminary results of reflection data collected from test flights over the Pacific ocean. This reflections data demonstrates observation of the GPS L1/L2C/L5 signals.

  1. TOGA - A GNSS Reflections Instrument for Remote Sensing Using Beamforming

    Science.gov (United States)

    Esterhuizen, S.; Meehan, T. K.; Robison, D.

    2009-01-01

    Remotely sensing the Earth's surface using GNSS signals as bi-static radar sources is one of the most challenging applications for radiometric instrument design. As part of NASA's Instrument Incubator Program, our group at JPL has built a prototype instrument, TOGA (Time-shifted, Orthometric, GNSS Array), to address a variety of GNSS science needs. Observing GNSS reflections is major focus of the design/development effort. The TOGA design features a steerable beam antenna array which can form a high-gain antenna pattern in multiple directions simultaneously. Multiple FPGAs provide flexible digital signal processing logic to process both GPS and Galileo reflections. A Linux OS based science processor serves as experiment scheduler and data post-processor. This paper outlines the TOGA design approach as well as preliminary results of reflection data collected from test flights over the Pacific ocean. This reflections data demonstrates observation of the GPS L1/L2C/L5 signals.

  2. Optimal directional view angles for remote-sensing missions

    Science.gov (United States)

    Kimes, D. S.; Holben, B. N.; Tucker, C. J.; Newcomb, W. W.

    1984-01-01

    The present investigation is concerned with the directional, off-nadir viewing of terrestrial scenes using remote-sensing systems from aircraft and satellite platforms, taking into account advantages of such an approach over strictly nadir viewing systems. Directional reflectance data collected for bare soil and several different vegetation canopies in NOAA-7 AVHRR bands 1 and 2 were analyzed. Optimum view angles were recommended for two strategies. The first strategy views the utility of off-nadir measurements as extending spatial and temporal coverage of the target area. The second strategy views the utility of off-nadir measurements as providing additional information about the physical characteristics of the target. Conclusions regarding the two strategies are discussed.

  3. Use of remote sensing for hydrological parameterisation of Alpine catchments

    Directory of Open Access Journals (Sweden)

    H. Bach

    2003-01-01

    Full Text Available Physically-based water balance models require a realistic parameterisation of land surface characteristics of a catchment. Alpine areas are very complex with strong topographically-induced gradients of environmental conditions, which makes the hydrological parameterisation of Alpine catchments difficult. Within a few kilometres the water balance of a region (mountain peak or valley can differ completely. Hence, remote sensing is invaluable for retrieving hydrologically relevant land surface parameters. The assimilation of the retrieved information into the water balance model PROMET is demonstrated for the Toce basin in Piemonte/Northern Italy. In addition to land use, albedos and leaf area indices were derived from LANDSAT-TM imagery. Runoff, modelled by a water balance approach, agreed well with observations without calibration of the hydrological model. Keywords: PROMET, fuzzy logic based land use classification, albedo, leaf area index

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

    Science.gov (United States)

    Mogaji, Kehinde Anthony; Lim, Hwee San

    2017-07-01

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

  5. The role of satellite remote sensing in REDD/MRV

    Science.gov (United States)

    Jonckheere, Inge; Sandoval, Alberto

    2010-05-01

    REDD, which stands for 'Reducing Emissions from Deforestation and Forest Degradation in Developing Countries' - is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. The UN-REDD Programme, a collaborative partnership between FAO, UNDP and UNEP launched in September 2008, supports countries to develop capacity to REDD and to implement a future REDD mechanism in a post- 2012 climate regime. The programme works at both the national and global scale, through support mechanisms for country-driven REDD strategies and international consensus-building on REDD processes. The UN-REDD Programme gathers technical teams from around the world to develop common approaches, analyses and guidelines on issues such as measurement, reporting and verification (MRV) of carbon emissions and flows, remote sensing, and greenhouse gas inventories. Within the partnership, FAO supports countries on technical issues related to forestry and the development of cost effective and credible MRV processes for emission reductions. While at the international level, it fosters improved guidance on MRV approaches, including consensus on principles and guidelines for MRV and training programmes.It provides guidance on how best to design and implement REDD, to ensure that forests continue to provide multiple benefits for livelihoods and biodiversity to societies while storing carbon at the same time. Other areas of work include national forest assessments and monitoring of in-country policy and institutional change. The outcomes about the role of satellite remote sensing technologies as a tool for monitoring, assessment, reporting and verification of carbon credits and co-benefits under the REDD mechanism are here presented.

  6. Remote sensing education and Internet/World Wide Web technology

    Science.gov (United States)

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

    2001-01-01

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

  7. [Analysis of related factors of slope plant hyperspectral remote sensing].

    Science.gov (United States)

    Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling

    2014-09-01

    In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.

  8. Water column correction for coral reef studies by remote sensing.

    Science.gov (United States)

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

    2014-09-11

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

  9. Remote Sensing Open Access Journal: Increasing Impact through Quality Publications

    Directory of Open Access Journals (Sweden)

    Prasad S. Thenkabail

    2014-08-01

    Full Text Available Remote Sensing, an open access journal (http://www.mdpi.com/journal/remotesensing has grown at rapid pace since its first publication five years ago, and has acquired a strong reputation. It is a “pathfinder” being the first open access journal in remote sensing. For those academics who were used to waiting a year or two for their peer-reviewed scientific work to be reviewed, revised, edited, and published, Remote Sensing offers a publication time frame that is unheard of (in most cases, less than four months. However, we do this after multiple peer-reviews, multiple revisions, much editorial scrutiny and decision-making, and professional editing by an editorial office before a paper is published online in our tight time frame, bringing a paradigm shift in scientific publication. As a result, there has been a swift increase in submissions of higher and higher quality manuscripts from the best authors and institutes working on Remote Sensing, Geographic Information Systems (GIS, Global Navigation Satellite System (GNSS, GIScience, and all related geospatial science and technologies from around the world. The purpose of this editorial is to update everyone interested in Remote Sensing on the progress made over the last year, and provide an outline of our vision for the immediate future. [...

  10. Polarization Remote Sensing Physical Mechanism, Key Methods and Application

    Science.gov (United States)

    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.

  11. Scene Classification of Remote Sensing Image Based on Multi-scale Feature and Deep Neural Network

    Directory of Open Access Journals (Sweden)

    XU Suhui

    2016-07-01

    Full Text Available Aiming at low precision of remote sensing image scene classification owing to small sample sizes, a new classification approach is proposed based on multi-scale deep convolutional neural network (MS-DCNN, which is composed of nonsubsampled Contourlet transform (NSCT, deep convolutional neural network (DCNN, and multiple-kernel support vector machine (MKSVM. Firstly, remote sensing image multi-scale decomposition is conducted via NSCT. Secondly, the decomposing high frequency and low frequency subbands are trained by DCNN to obtain image features in different scales. Finally, MKSVM is adopted to integrate multi-scale image features and implement remote sensing image scene classification. The experiment results in the standard image classification data sets indicate that the proposed approach obtains great classification effect due to combining the recognition superiority to different scenes of low frequency and high frequency subbands.

  12. Commercialization of the land remote sensing system: An examination of mechanisms and issues

    Science.gov (United States)

    Cauley, J. K.; Gaelick, C.; Greenberg, J. S.; Logsdon, J.; Monk, T.

    1983-01-01

    In September 1982 the Secretary of Commerce was authorized (by Title II of H.R. 5890 of the 97th Congress) to plan and provide for the management and operation of the civil land remote sensing satellite systems, to provide for user fees, and to plan for the transfer of the ownership and operation of future civil operational land remote sensing satellite systems to the private sector. As part of the planning for transfer, a number of approaches were to be compared including wholly private ownership and operation of the system by an entity competitively selected, mixed government/private ownership and operation, and a legislatively-chartered privately-owned corporation. The results of an analysis and comparison of a limited number of financial and organizational approaches for either transfer of the ownership and operation of the civil operational land remote sensing program to the private sector or government retention are presented.

  13. Tasseled cap transformation for HJ multispectral remote sensing data

    Science.gov (United States)

    Han, Ling; Han, Xiaoyong

    2015-12-01

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

  14. Assessment of biochemical concentrations of vegetation using remote sensing technology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The main biochemicals (such as lignin, protein, cellulose, sugar, starch, chlorophyll and water) of vegetation are directly or indirectly involved in major ecological processes, such as the functions of terrestrial ecosystems (i.e., nutrient-cycling processes, primary production, and decomposition). Remote sensing techniques provide a very convenient way of data acquisition capable of covering a large area several times during one season, so it can play a unique and essential role provided that we can relate remote sensing measurements to the biochemical characteristics of the Earth surface in a reliable and operational way. The application of remote sensing techniques for the estimation of canopy biochemicals was reviewed. Three methods of estimating biochemical concentrations of vegetation were included in this paper: index, stepwise multiple linear regression, and stepwise multiple linear regression based on a model of the forest crown. In addition, the vitality and potential applying value are stressed.

  15. Scientific Programming Using Java: A Remote Sensing Example

    Science.gov (United States)

    Prados, Don; Mohamed, Mohamed A.; Johnson, Michael; Cao, Changyong; Gasser, Jerry

    1999-01-01

    This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

  16. Scientific Programming Using Java: A Remote Sensing Example

    Science.gov (United States)

    Prados, Don; Mohamed, Mohamed A.; Johnson, Michael; Cao, Changyong; Gasser, Jerry

    1999-01-01

    This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

  17. Remote Sensing Image Deblurring Based on Grid Computation

    Institute of Scientific and Technical Information of China (English)

    LI Sheng-yang; ZHU Chong-guang; GE Ping-ju

    2006-01-01

    In general, there is a demand for real-time processing of mass quantity remote sensing images. However, the task is not only data-intensive but also computating-intensive. Distributed processing is a hot topic in remote sensing processing and image deblurring is also one of the most important needs. In order to satisfy the demand for quick processing and deblurring of mass quantity satellite images, we developed a distributed, grid computation-based platform as well as a corresponding middleware for grid computation. Both a constrained power spectrum equalization algorithm and effective block processing measures, which can avoid boundary effect, were applied during the processing. The result is satisfactory since computation efficiency and visual effect were greatly improved. It can be concluded that the technology of spatial information grids is effective for mass quantity remote sensing image processing.

  18. Validating firn compaction model with remote sensing data

    DEFF Research Database (Denmark)

    Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland shows a clear layering. The observed layers from the radar data can be used as an in-situ validation...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...

  19. Water pollution remote sensing for Pearl River Delta

    Science.gov (United States)

    Deng, Ruru; Xiong, Shouping; Qin, Yan

    2008-10-01

    Water pollution on the Delta of Pearl River is increasingly serious and to command the fact of pollution is the key of the control. A remote sensing model for water pollution base on single scattering is deduced in this paper. To avoid the effect by turbidity of water, by analysis the characteristics of the energy composition of multiple scattering, a factor of second scattering is deduced to build a double scattering model, and the practical arithmetic for the calculation of the model is put forwarded and then used to the pollution remote sensing over the Pearl River Delta. The precision of the result is validated by the synchronous measured data on water surface. The result of remote sensing showed that all of the North River, East River and West River are polluted in Pearl River Delta, and the most serious pollution is take place around Guang Zhou City and Dong Guan City.

  20. Magnetoseismology ground-based remote sensing of Earth's magnetosphere

    CERN Document Server

    Menk, Frederick W

    2013-01-01

    Written by a researcher at the forefront of the field, this first comprehensive account of magnetoseismology conveys the physics behind these movements and waves, and explains how to detect and investigate them. Along the way, it describes the principles as applied to remote sensing of near-Earth space and related remote sensing techniques, while also comparing and intercalibrating magnetoseismology with other techniques. The example applications include advanced data analysis techniques that may find wider used in areas ranging from geophysics to medical imaging, and remote sensing using radar systems that are of relevance to defense surveillance systems. As a result, the book not only reviews the status quo, but also anticipates new developments. With many figures and illustrations, some in full color, plus additional computational codes for analysis and evaluation. Aimed at graduate readers, the text assumes knowledge of electromagnetism and physical processes at degree level, but introductory chapters wil...