Remote sensing reflectance of Pomeranian lakes and the Baltic

Directory of Open Access Journals (Sweden)

Dariusz Ficek

2011-11-01

Full Text Available The remote sensing reflectance Rrs, concentrations of chlorophyll a and other pigments Ci, suspended particulate matter concentrations CSPM and coloured dissolved organic matter absorption coefficient aCDOM(λ were measured in the euphotic zones of 15 Pomeranian lakes in 2007-2010. On the basis of 235 sets of data points obtained from simultaneous estimates of these quantities, we classified the lake waters into three types. The first one, with the lowest aCDOM(440 nm (usually between 0.1 and 1.3 m-1 and chlorophyll a concentrations 1.3 10 m-1, up to 17.4 m-1 in Lake Pyszne; it has a relatively low reflectance (Rrs 4 mg m-3, up to 336 mg m-3 in Lake Gardno. The remote sensing reflectance spectra in these waters always exhibit three peaks (Rrs > 0.005 sr-1: a broad one at 560-580 nm, a smaller one at ca 650 nm and a well-pronounced one at 690-720 nm. These Rrs(λ peaks correspond to the relatively low absorption of light by the various optically active components of the lake water and the considerable scattering (over the entire spectral range investigated due to the high SPM concentrations there. The remote sensing maximum at λ ≈ 690-720 nm is higher still as a result of the natural fluorescence of chlorophyll a. Empirical relationships between the spectral reflectance band ratios at selected wavelengths and the various optically active components for these lake waters are also established: for example, the chlorophyll a concentration in surface water layer Ca = 6.432 e4.556X, where X = [max Rrs (695 ≤ λ ≤ 720 - Rrs(λ = 670] / max Rrs (695 ≤ λ ≤ 720, and the coefficient of determination R2 = 0.95.

Infrared remote sensing for canopy temperature in paddy field and relationship between leaf temperature and leaf color

International Nuclear Information System (INIS)

Wakiyama, Y.

2002-01-01

Infrared remote sensing is used for crop monitoring, for example evaluation of water stress, detection of infected crops and estimation of transpiration and photosynthetic rates. This study was conducted to show another application of remote sensing information. The relationship between rice leaf temperature and chlorophyll content in the leaf blade was investigated by using thermography during the ripening period. The canopy of a rice community fertilized by top dressing was cooler than that not fertilized in a 1999 field experiment. In an experiment using thermocouples to measure leaf temperature, a rice leaf with high chlorophyll content was also cooler than that with a low chlorophyll content. Transpiration resistance and transpiration rate were measured with a porometer. Transpiration rate was higher with increasing chlorophyll content in the leaf blade. Stomatal aperture is related to chlorophyll content in the leaf blade. High degree of stomatal aperture is caused by high chlorophyll content in the leaf blade. As degree of stomatal aperture increases, transpiration rate increases. Therefore the rice leaf got cooler with increasing chlorophyll content in leaf blade. Paddy rice communities with different chlorophyll contents were provided with fertilization of different nitrogen levels on basal and top dressing in a 2000 field experiment. Canopy temperature of the rice community with high chlorophyll content was 0.85°C cooler than that of the rice community with low chlorophyll content. Results of this study revealed that infrared remote sensing could detect difference in chlorophyll contents in rice communities and could be used in fertilizer management in paddy fields. (author)

DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence

Science.gov (United States)

Gastellu-Etchegorry, Jean-Phil; Lauret, Nicolas; Yin, Tiangang; Landier, Lucas; Kallel, Abdelaziz; Malenovsky, Zbynek; Bitar, Ahmad Al; Aval, Josselin; Benhmida, Sahar; Qi, Jianbo;

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers

OpenAIRE

Gamon, John A.

2016-01-01

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a “chlorophyll/carotenoid index” (CCI) that tracks ever...

Chlorophyll-a specific volume scattering function of phytoplankton.

Science.gov (United States)

Tan, Hiroyuki; Oishi, Tomohiko; Tanaka, Akihiko; Doerffer, Roland; Tan, Yasuhiro

2017-06-12

Chlorophyll-a specific light volume scattering functions (VSFs) by cultured phytoplankton in visible spectrum range is presented. Chlorophyll-a specific VSFs were determined based on the linear least squares method using a measured VSFs with different chlorophyll-a concentrations. We found obvious variability of it in terms of spectral and angular shapes of VSF between cultures. It was also presented that chlorophyll-a specific scattering significantly affected on spectral variation of the remote sensing reflectance, depending on spectral shape of b. This result is useful for developing an advance algorithm of ocean color remote sensing and for deep understanding of light in the sea.

Towards a Solid Foundation of Using Remotely Sensed Solar-Induced Chlorophyll Fluorescence for Crop Monitoring and Yield Forecast

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Chen, Y.; Sun, Y.; You, L.; Liu, Y.

2017-12-01

The growing demand for food production due to population increase coupled with high vulnerability to volatile environmental changes poses a paramount challenge for mankind in the coming century. Real-time crop monitoring and yield forecasting must be a key part of any solution to this challenge as these activities provide vital information needed for effective and efficient crop management and for decision making. However, traditional methods of crop growth monitoring (e.g., remotely sensed vegetation indices) do not directly relate to the most important function of plants - photosynthesis and therefore crop yield. The recent advance in the satellite remote sensing of Solar-Induced chlorophyll Fluorescence (SIF), an integrative photosynthetic signal from molecular origin and a direct measure of plant functions holds great promise for real-time monitoring of crop growth conditions and forecasting yields. In this study, we use satellite measurements of SIF from both the Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A and the Orbiting Carbon Observatory-2 (OCO-2) satellites to estimate crop yield using both process-based and statistical models. We find that SIF-based crop yield well correlates with the global yield product Spatial Production Allocation Model (SPAM) derived from ground surveys for all major crops including maize, soybean, wheat, sorghum, and rice. The potential and challenges of using upcoming SIF satellite missions for crop monitoring and prediction will also be discussed.

Tracking diurnal changes of photosynthesis and evapotranspiration using fluorescence, gas exchange and hyperspectral remote sensing measurements

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Wang, S.; Zhang, L.; Guanter, L.; Huang, C.

2017-12-01

Photosynthesis and evapotranspiration (ET) are the two most important activities of vegetation and make a great contribution to carbon, water and energy exchanges. Remote sensing provides opportunities for monitoring these processes across time and space. This study focuses on tracking diurnal changes of photosynthesis and evapotranspiration over soybean using multiple measurement techniques. Diurnal changes of both remote sensing-based indicators, including active and passive chlorophyll fluorescence and biophysical-related parameters, including photosynthesis rate (photo) and leaf stomatal conductance (cond), were observed. Results showed that both leaf-level steady-state fluorescence (Fs) and canopy-level solar-induced chlorophyll fluorescence were linearly correlated to photosynthetically active radiation (PAR) during the daytime. A double-peak diurnal change curve was observed for leaf-level photo and cond but not for Fs or SIF. Photo and cond showed a strong nonlinear (second-order) correlation, indicating that photosynthesis, which might be remotely sensed by SIF, has the opportunity to track short-term changes of ET. Results presented in this report will be helpful for better understanding the relationship between remote-sensing-based indices and vegetation's biophysical processes.

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers.

Science.gov (United States)

Gamon, John A; Huemmrich, K Fred; Wong, Christopher Y S; Ensminger, Ingo; Garrity, Steven; Hollinger, David Y; Noormets, Asko; Peñuelas, Josep

2016-11-15

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying "photosynthetic phenology" from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a "chlorophyll/carotenoid index" (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA's Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology.

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.

Remote sensing bio-control damage on aquatic invasive alien plant ...

African Journals Online (AJOL)

Naeem

Satellite based remote sensing provides a synoptic view of ... information system for multi-temporal analysis (Albright et al., 2004) which ... control damage based on the colour of the foliage using aerial photography and conventional .... It was reported that the ratio of two chlorophyll fluorescence bands can be used to detect ...

Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing

KAUST Repository

Gittings, John; Raitsos, Dionysios E.; Racault, Marie-Fanny; Brewin, Robert J.W.; Pradhan, Yaswant; Sathyendranath, Shubha; Platt, Trevor

2016-01-01

of remotely-sensed chlorophyll-a data (Chl-a, an index of phytoplankton biomass) acquired from the Ocean Colour Climate Change Initiative (OC-CCI) of the European Space Agency (ESA). The improved spatial coverage of OC-CCI data in the Gulf of Aden allows

Remote Sensing of Ocean Color

Science.gov (United States)

Dierssen, Heidi M.; Randolph, Kaylan

The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats

Optical Remote Sensing Algorithm Validation using High-Frequency Underway Biogeochemical Measurements in Three Large Global River Systems

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Kuhn, C.; Richey, J. E.; Striegl, R. G.; Ward, N.; Sawakuchi, H. O.; Crawford, J.; Loken, L. C.; Stadler, P.; Dornblaser, M.; Butman, D. E.

2017-12-01

More than 93% of the world's river-water volume occurs in basins impacted by large dams and about 43% of river water discharge is impacted by flow regulation. Human land use also alters nutrient and carbon cycling and the emission of carbon dioxide from inland reservoirs. Increased water residence times and warmer temperatures in reservoirs fundamentally alter the physical settings for biogeochemical processing in large rivers, yet river biogeochemistry for many large systems remains undersampled. Satellite remote sensing holds promise as a methodology for responsive regional and global water resources management. Decades of ocean optics research has laid the foundation for the use of remote sensing reflectance in optical wavelengths (400 - 700 nm) to produce satellite-derived, near-surface estimates of phytoplankton chlorophyll concentration. Significant improvements between successive generations of ocean color sensors have enabled the scientific community to document changes in global ocean productivity (NPP) and estimate ocean biomass with increasing accuracy. Despite large advances in ocean optics, application of optical methods to inland waters has been limited to date due to their optical complexity and small spatial scale. To test this frontier, we present a study evaluating the accuracy and suitability of empirical inversion approaches for estimating chlorophyll-a, turbidity and temperature for the Amazon, Columbia and Mississippi rivers using satellite remote sensing. We demonstrate how riverine biogeochemical measurements collected at high frequencies from underway vessels can be used as in situ matchups to evaluate remotely-sensed, near-surface temperature, turbidity, chlorophyll-a derived from the Landsat 8 (NASA) and Sentinel 2 (ESA) satellites. We investigate the use of remote sensing water reflectance to infer trophic status as well as tributary influences on the optical characteristics of the Amazon, Mississippi and Columbia rivers.

Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data

Science.gov (United States)

Huang, Jingfeng; Wei, Chen; Zhang, Yao; Blackburn, George Alan; Wang, Xiuzhen; Wei, Chuanwen; Wang, Jing

2015-01-01

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a. PMID:26356842

Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data.

Directory of Open Access Journals (Sweden)

Jingfeng Huang

Full Text Available Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550-560nm and red edge (680-750nm regions; chlorophyll b on the red, (630-660nm, red edge (670-710nm and the near-infrared (800-810nm; carotenoids on the 500-580nm region; and anthocyanins on the green (550-560nm, red edge (700-710nm and near-infrared (780-790nm. For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.

[Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

Science.gov (United States)

Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

2014-11-01

Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

Regional ocean-colour chlorophyll algorithms for the Red Sea

KAUST Repository

Brewin, Robert J.W.; Raitsos, Dionysios E.; Dall'Olmo, Giorgio; Zarokanellos, Nikolaos; Jackson, Thomas; Racault, Marie-Fanny; Boss, Emmanuel S.; Sathyendranath, Shubha; Jones, Burton; Hoteit, Ibrahim

2015-01-01

an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll

Remote Sensing of Suspended Sediments and Shallow Coastal Waters

Science.gov (United States)

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

2002-01-01

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

Proposal for a remote sensing trophic state index based upon Thematic Mapper/Landsat images

Directory of Open Access Journals (Sweden)

Evlyn Márcia Leão de Moraes Novo

2013-12-01

Full Text Available This work proposes a trophic state index based on the remote sensing retrieval of chlorophyll-α concentration. For that, in situ Bidirectional Reflectance Factor (BRF data acquired in the Ibitinga reservoir were resampled to match Landsat/TM spectral simulated bands (TM_sim bands and used to run linear correlation with concurrent measurements of chlorophyll-α concentration. Monte Carlo simulation was then applied to select the most suitable model relating chlorophyll-α concentration and simulated TM/Landsat reflectance. TM4_sim/TM3_sim ratio provided the best model with a R2 value of 0.78. The model was then inverted to create a look-up-table (LUT relating TM4_sim/TM3_sim ratio intervals to chlorophyll-α concentration trophic state classes covering the entire range measured in the reservoir. Atmospheric corrected Landsat TM images converted to surface reflectance were then used to generate a TM4/TM3 ratio image. The ratio image frequency distribution encompassed the range of TM4_sim/TM3_sim ratio indicating agreement between in situ and satellite data and supporting the use of satellite data to map chlorophyll- concentration trophic state distribution in the reservoir. Based on that, the LUT was applied to a Landsat/TM ratio image to map the spatial distribution of chlorophyll- trophic state classes in Ibitinga reservoir. Despite the stochastic selection of TM4_sim/TM3_sim ratio as the best input variable for modeling the chlorophyll-α concentration, it has a physical basis: high concentration of phytoplankton increases the reflectance in the near-infrared (TM4 and decreases the reflectance in the red (TM3. The band ratio, therefore, enhances the relationship between chlorophyll- concentration and remotely sensed reflectance.

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

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Mohammad Haji Gholizadeh

2016-08-01

Full Text Available Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM, chlorophyll-a, and pollutants. A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc. of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a, colored dissolved organic matters (CDOM, Secchi disk depth (SDD, turbidity, total suspended sediments (TSS, water temperature (WT, total phosphorus (TP, sea surface salinity (SSS, dissolved oxygen (DO, biochemical oxygen demand (BOD and chemical oxygen demand (COD.

Comparison of remote sensing and plant trait-based modelling to predict ecosystem services in subalpine grasslands

Czech Academy of Sciences Publication Activity Database

Homolová, Lucie; Schaepman, M. E.; Lamarque, L.; Clevers, J.G.P.W.; de Bello, Francesco; Thuiller, W.; Lavorel, S.

2014-01-01

Roč. 5, č. 8 (2014), č. článku 100. ISSN 2150-8925 Institutional support: RVO:67179843 ; RVO:67985939 Keywords : land-use change * leaf chlorophyll content * imaging spectroscopy * water-content * aviris data * spectral reflectance * hyperspectral data * species richness * area index * vegetation * aisa * biomass * ecosystem properties * ecosystem services * linear regression * remote sensing * spatial heterogeneity * subalpine grasslands Subject RIV: EH - Ecology, Behaviour; EF - Botanics (BU-J) OBOR OECD: Remote sensing; Plant sciences, botany (BU-J) Impact factor: 2.255, year: 2014

Time-sensitive remote sensing

CERN Document Server

Lippitt, Christopher; Coulter, Lloyd

2015-01-01

This book documents the state of the art in the use of remote sensing to address time-sensitive information requirements. Specifically, it brings together a group of authors who are both researchers and practitioners, who work toward or are currently using remote sensing to address time-sensitive information requirements with the goal of advancing the effective use of remote sensing to supply time-sensitive information. The book addresses the theoretical implications of time-sensitivity on the remote sensing process, assessments or descriptions of methods for expediting the delivery and improving the quality of information derived from remote sensing, and describes and analyzes time-sensitive remote sensing applications, with an emphasis on lessons learned. This book is intended for remote sensing scientists, practitioners (e.g., emergency responders or administrators of emergency response agencies), and students, but will also be of use to those seeking to understand the potential of remote sensing to addres...

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

Science.gov (United States)

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

2017-12-01

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

Ecophysiological Remote Sensing of Leaf-Canopy Photosynthetic Characteristics in a Cool-Temperate Deciduous Forest in Japan

Science.gov (United States)

Noda, H. M.; Muraoka, H.

2014-12-01

Satellite remote sensing of structure and function of canopy is crucial to detect temporal and spatial distributions of forest ecosystems dynamics in changing environments. The spectral reflectance of the canopy is determined by optical properties (spectral reflectance and transmittance) of single leaves and their spatial arrangements in the canopy. The optical properties of leaves reflect their pigments contents and anatomical structures. Thus detailed information and understandings of the consequence between ecophysiological traits and optical properties from single leaf to canopy level are essential for remote sensing of canopy ecophysiology. To develop the ecophysiological remote sensing of forest canopy, we have been promoting multiple and cross-scale measurements in "Takayama site" belonging to AsiaFlux and JaLTER networks, located in a cool-temperate deciduous broadleaf forest on a mountainous landscape in Japan. In this forest, in situ measurement of canopy spectral reflectance has been conducted continuously by a spectroradiometer as part of the "Phenological Eyes Network (PEN)" since 2004. To analyze the canopy spectral reflectance from leaf ecophysiological viewpoints, leaf mass per area, nitrogen content, chlorophyll contents, photosynthetic capacities and the optical properties have been measured for dominant canopy tree species Quercus crispla and Betula ermanii throughout the seasons for multiple years.Photosynthetic capacity was largely correlated with chlorophyll contents throughout the growing season in both Q. crispla and B. ermanii. In these leaves, the reflectance at "red edge" (710 nm) changed by corresponding to the changes of chlorophyll contents throughout the seasons. Our canopy-level examination showed that vegetation indices obtained by red edge reflectance have linear relationship with leaf chlorophyll contents and photosynthetic capacity. Finally we apply this knowledge to the Rapid Eye satellite imagery around Takayama site to scale

Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images

Directory of Open Access Journals (Sweden)

Monica Pinardi

2015-04-01

Full Text Available Shallow fluvial lakes are dynamic ecosystems shaped by physical and biological factors and characterized by the coexistence of phytoplankton and macrophytes. Due to multiple interplaying factors, understanding the distribution of phytoplankton in fluvial lakes is a complex but fundamental issue, in the context of increasing eutrophication, climate change, and multiple water uses. We analyze the distribution of phytoplankton by combining remotely sensed maps of chlorophyll-a with a hydrodynamic model in a dammed fluvial lake (Mantua Superior Lake, Northern Italy. The numerical simulation of different conditions shows that the main hydrodynamic effects which influence algal distribution are related to the combined effect of advection due to wind forces and local currents, as well as to the presence of large gyres which induce recirculation and stagnation regions, favoring phytoplankton accumulation. Therefore, the general characters of the phytoplankton horizontal patchiness can be inferred from the results of the hydrodynamic model. Conversely, hyperspectral remote-sensing products can be used to validate this model, as they provide chlorophyll-a distribution maps. The integration of ecological, hydraulic, and remote-sensing techniques may therefore help the monitoring and protection of inland water quality, with important improvements in management actions by policy makers.

Spectral reflectance of carbonate sediments and application to remote sensing classification of benthic habitats

Science.gov (United States)

Louchard, Eric Michael

Remote sensing is a valuable tool in marine research that has advanced to the point that images from shallow waters can be used to identify different seafloor types and create maps of benthic habitats. A major goal of this dissertation is to examine differences in spectral reflectance and create new methods of analyzing shallow water remote sensing data to identify different seafloor types quickly and accurately. Carbonate sediments were used as a model system as they presented a relatively uniform, smooth surface for measurement and are a major bottom type in tropical coral reef systems. Experimental results found that sediment reflectance varied in shape and magnitude depending on pigment content, but only varied in magnitude with variations in grain size and shape. Derivative analysis of the reflectance spectra identified wavelength regions that correlate to chlorophyll a and chlorophyllide a as well as accessory pigments, indicating differences in microbial community structure. Derivative peak height also correlated to pigment content in the sediments. In remote sensing data, chlorophyll a, chlorophyllide a, and some xanthophylls were identified in derivative spectra and could be quantified from second derivative peak height. Most accessory pigments were attenuated by the water column, however, and could not be used to quantify pigments in sediments from remote sensing images. Radiative transfer modeling of remote sensing reflectance showed that there was sufficient spectral variation to separate major sediment types, such as ooid shoals and sediment with microbial layers, from different densities of seagrass and pavement bottom communities. Both supervised classification with a spectral library and unsupervised classification with principal component analysis were used to create maps of seafloor type. The results of the experiments were promising; classified seafloor types correlated with ground truth observations taken from underwater video and were

Remote sensing of ocean currents using ERTS imagery

Science.gov (United States)

Maul, G. A.

1973-01-01

Major ocean currents such as the Loop Current in the eastern Gulf of Mexico have surface manifestations which can be exploited for remote sensing. Surface chlorophyll-a concentrations, which contribute to the shift in color from blue to green in the open sea, were found to have high spatial variability; significantly lower concentrations were observed in the current. The cyclonic edge of the current is an accumulation zone which causes a peak in chlorophyll concentration. The dynamics also cause surface concentrations of algae, which have a high reflectance in the near infrared. Combining these observations gives rise to an edge effect which can show up as a bright lineation on multispectral imagery delimiting the current's boundary under certain environmental conditions. When high seas introduce bubbles, white caps, and foam, the reflectance is dominated by scattering rather than absorption. This has been detected in ERTS imagery and used for current location.

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

Biological and remote sensing perspectives of pigmentation in coral reef organisms.

Science.gov (United States)

Hedley, John D; Mumby, Peter J

2002-01-01

categories. The basis of reflectance is considered as the sum of pigmented components, such as zooxanthellae, host tissues and skeletons of corals. Problems in the empirical in situ measurement of reflectance are identified, such as the differing types of reflectance which can be measured, the interaction of the light field with morphology, and depth-dependent variability of measured reflectance due to fluorescence. The latter is estimated in some cases to introduce an error of up to 20% when depth differs by 8 m. Spectral features useful in discriminating reef benthos are identified and related to pigmentation. The slope in the reflectance spectra between 650 and 690 nm is dependent on chlorophyll-a concentration and can be used to discriminate bare sand with no algal component from chlorophyll-a containing benthos (algae, corals). The slope in reflectance at various locations between 500 and 560 nm can be useful in discriminating bleached and unbleached corals, possibly due to reduced peridinin concentration. Rhodophyta may be discernible by the presence of a dip in reflectance at 570 nm, due to a phycoerythrin absorption peak. However, the utility of some discriminatory criteria in deeper waters is mitigated by the relatively poor transmission of light through water at longer wavelengths (especially > 600 nm). Contrary to suggested categorizations of fluorescent pigments in coral host tissues, it is shown that these pigments form an almost continuous distribution with respect to their excitation and emission peaks. Remote sensing by induced fluorescence is a promising approach, but further details about the variation and distribution of these pigments are required. It is hoped that this review will promote cross-disciplinary collaboration between pigment biologists and the reef remote sensing community. Where possible, the discriminative criteria adopted in remote sensing should be related to biological phenomena, thus lending an intuitive, process-orientated basis for

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

Analysis of Cross-Seasonal Spectral Response from Kettle Holes: Application of Remote Sensing Techniques for Chlorophyll Estimation

Directory of Open Access Journals (Sweden)

Bernd Lennartz

2012-11-01

Full Text Available Kettle holes, small inland water bodies usually less than 1 ha in size, are subjected to pollution, drainage, and structural alteration by intensive land use practices. This study presents the analysis of spectral signatures from kettle holes based on in situ water sampling and reflectance measurements in application for chlorophyll estimation. Water samples and surface reflectance from kettle holes were collected from 6 ponds in 15 field campaigns (5 in 2007 and 10 in 2008, resulting in a total of 80 spectral datasets. We assessed the existing semi-empirical algorithms to determine chlorophyll content for different types of kettle holes using seasonal and cross-seasonal volume reflectance and derivative spectra. Based on this analysis and optical properties of water leaving reflectance from kettle holes, the following typology of the remote signal interpretation was proposed: Submerged vegetation, Phytoplankton dominated and Mixed type.

Advanced Remote Sensing Research

Science.gov (United States)

Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna

2008-01-01

'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).

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.

Measurements methods and variability assesment of the Norway spruce total leaf area. Implications for remote sensing

Czech Academy of Sciences Publication Activity Database

Homolová, L.; Lukeš, Petr; Malenovský, Z.; Lhotáková, Z.; Kaplan, Věroslav; Hanuš, Jan

2013-01-01

Roč. 27, č. 1 (2013), s. 111-121 ISSN 0931-1890 R&D Projects: GA ČR GA205/09/ 1989 Institutional support: RVO:67179843 Keywords : chlorophyll content * conversion factor * Picea abies * projected leaf area * remote sensing * total leaf area Subject RIV: EH - Ecology, Behaviour Impact factor: 1.869, year: 2013

Improved ocean chlorophyll estimate from remote sensed data: The ...

African Journals Online (AJOL)

Gregg and Conkright (2001) who pioneered the use of the blending technique in an attempt to calibrate ocean chlorophyll, expressed the need for further work to be done in order to obtain improved results. One problem faced when using this technique with spatially sparse data, is distortion of the resulting blended field ...

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

Using hyperspectral remote sensing data for retrieving canopy chlorophyll and nitrogen content

NARCIS (Netherlands)

Clevers, J.G.P.W.; Kooistra, L.

2012-01-01

Plant stress is often expressed as a reduction in amount of biomass or leaf area index (LAI). In addition, stress may affect the plant pigment system, influencing the photosynthetic capacity of plants. Chlorophyll content is the main driver for this primary production. The chlorophyll content is

Assimilation of remotely sensed chlorophyll fluorescence data into the land surface model CLM4

Science.gov (United States)

Wieneke, S.; Ahrends, H. E.; Rascher, U.; Schween, J.; Schickling, A.; Crewell, S.

2013-12-01

Photosynthesis is the most important exchange process of CO2 between the atmosphere and the land-surface. Therefore, the prediction of vegetation response to environmental conditions like increasing CO2 concentrations or plant stress is crucial for a reliable prediction of climate change. Photosynthesis is a complex physiological process that consists of numerous bio-physical sub-processes and chemical reactions. Spatial and temporal patterns of photosynthesis depend on dynamic plant-specific adaptation strategies to highly variable environmental conditions. Photosynthesis can be estimated using land-surface models, but, while state-of-the-art models often rely on Plant Functional Type (PFT) specific constants, they poorly simulate the dynamic adaptation of the physiological status of plant canopies in space and time. Remotely sensed sun-induced chlorophyll fluorescence (SICF) gives us now the possibility to estimate the diurnal dynamic vitality of the photosynthetic apparatus at both, the leaf and canopy levels. We installed within the framework of the Transregio32 project (www.tr32.de) automated hyperspectral fluorescence sensors at an agricultural site (winter wheat) in the Rur catchment area in West Germany at the end of July 2012. End of August, additional measurements of SIFC on nearby temperate grassland site (riparian meadow) and on a sugar beet field were performed. Spatial covering SICF data of the region were obtained during a measurement campaign using the newly developed air-borne hyperspectral sensor HyPlant on the 23 and 27 August 2012. SIFC data and data provided by eddy covariance measurements will be used to update certain model parameters that are normally set as constants. First model results demonstrate that the assimilation of SIFC into the Community Land Model 4 (CLM4) will result in a more realistic simulation of plant-specific adaptation strategies and therefore in a more realistic simulation of photosynthesis in space and time.

Remote sensing vegetation status by laser-induced fluorescence

International Nuclear Information System (INIS)

Günther, K.P.; Dahn, H.G.; Lüdeker, W.

1994-01-01

In November 1989 the EUREKA project LASFLEUR (EU 380) started as an European research effort to investigate the future application of far-field laser-induced plant fluorescence for synoptic, airborne environmental monitoring of vegetation. This report includes a brief introduction in a theoretically approach for the laser-induced fluorescence signals of leaves and their spectral and radiometric behaviour. In addition, a detailed description of the design and realization of the second generation of the far-field fluorescence lidar (DLidaR-2) is given with special regard to the optical and electronical setup, followed by a short explanation of the data processing. The main objectives of the far field measurements are to demonstrate the link between laser-induced fluorescence data and plant physiology and to show the reliability of remote single shot lidar measurements. The data sets include the typical daily cycles of the fluorescence for different global irradiation. As expected from biophysical models, the remotely sensed chlorophyll fluorescence is highly correlated with the carbon fixation rate, while the fluorescence ratio F685 / F730 is only dependent on the chlorophyll concentration. Drought stress measurement of evergreen oaks Quercus pubescens confirm the findings of healthy plants with regard to the fluorescence ratio F685 / F730 while the fluorescence signals of stressed plants show a different behavior than nonstressed plants. Additionally, the corresponding physiological data (porometer and PAM data) are presented. (author)

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

Science.gov (United States)

Shanmugam, Palanisamy; He, Xianqiang; Singh, Rakesh Kumar; Varunan, Theenathayalan

2018-05-01

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.

Multifractal analysis of oceanic chlorophyll maps remotely sensed from space

Directory of Open Access Journals (Sweden)

L. de Montera

2011-03-01

Full Text Available Phytoplankton patchiness has been investigated with multifractal analysis techniques. We analyzed oceanic chlorophyll maps, measured by the SeaWiFS orbiting sensor, which are considered to be good proxies for phytoplankton. The study area is the Senegalo-Mauritanian upwelling region, because it has a low cloud cover and high chlorophyll concentrations. Multifractal properties are observed, from the sub-mesoscale up to the mesoscale, and are found to be consistent with the Corssin-Obukhov scale law of passive scalars. This result indicates that, in this specific region and within this scale range, turbulent mixing would be the dominant effect leading to the observed variability of phytoplankton fields. Finally, it is shown that multifractal patchiness can be responsible for significant biases in the nonlinear source and sink terms involved in biogeochemical numerical models.

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

Science.gov (United States)

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

2007-04-01

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

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

Science.gov (United States)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and

Visible-infrared remote-sensing model and applications for ocean waters. Ph.D. Thesis

Science.gov (United States)

Lee, Zhongping

1994-01-01

Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape

Remote sensing of Essential Biodiversity Variables: new measurements linking ecosystem structure, function and composition

Science.gov (United States)

Schimel, D.; Pavlick, R.; Stavros, E. N.; Townsend, P. A.; Ustin, S.; Thompson, D. R.

2017-12-01

Remote sensing can inform a wide variety of essential biodiversity variables, including measurements that define primary productivity, forest structure, biome distribution, plant communities, land use-land cover change and climate drivers of change. Emerging remote sensing technologies can add significantly to remote sensing of EBVs, providing new, large scale insights on plant and habitat diversity itself, as well as causes and consequences of biodiversity change. All current biodiversity assessments identify major data gaps, with insufficient coverage in critical regions, limited observations to monitor change over time, with very limited revisit of sample locations, as well as taxon-specific biased biases. Remote sensing cannot fill many of the gaps in global biodiversity observations, but spectroscopic measurements in terrestrial and marine environments can aid in assessing plant/phytoplankton functional diversity and efficiently reveal patterns in space, as well as changes over time, and, by making use of chlorophyll fluorescence, reveal associated patterns in photosynthesis. LIDAR and RADAR measurements quantify ecosystem structure, and can precisely define changes due to growth, disturbance and land use. Current satellite-based EBVs have taken advantage of the extraordinary time series from LANDSAT and MODIS, but new measurements more directly reveal ecosystem structure, function and composition. We will present results from pre-space airborne studies showing the synergistic ability of a suite of new remote observation techniques to quantify biodiversity and ecosystem function and show how it changes during major disturbance events.

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-art compendium available for people involved in Remote Sensing in Wind Energy....

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

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.

Investigation into robust spectral indices for leaf chlorophyll estimation

CSIR Research Space (South Africa)

Main, R

2011-11-01

Full Text Available remote sensing data, new users are faced with a plethora of options when choosing an optical index to relate to their chosen or canopy parameter. The literature base regarding optical indices (particularly chlorophyll indices) is wide ranging...

Dustfall Effect on Hyperspectral Inversion of Chlorophyll Content - a Laboratory Experiment

Science.gov (United States)

Chen, Yuteng; Ma, Baodong; Li, Xuexin; Zhang, Song; Wu, Lixin

2018-04-01

Dust pollution is serious in many areas of China. It is of great significance to estimate chlorophyll content of vegetation accurately by hyperspectral remote sensing for assessing the vegetation growth status and monitoring the ecological environment in dusty areas. By using selected vegetation indices including Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI) Double Difference Index (DD) and Red Edge Position Index (REP), chlorophyll inversion models were built to study the accuracy of hyperspectral inversion of chlorophyll content based on a laboratory experiment. The results show that: (1) REP exponential model has the most stable accuracy for inversion of chlorophyll content in dusty environment. When dustfall amount is less than 80 g/m2, the inversion accuracy based on REP is stable with the variation of dustfall amount. When dustfall amount is greater than 80 g/m2, the inversion accuracy is slightly fluctuation. (2) Inversion accuracy of DD is worst among three models. (3) MTCI logarithm model has high inversion accuracy when dustfall amount is less than 80 g/m2; When dustfall amount is greater than 80 g/m2, inversion accuracy decreases regularly and inversion accuracy of modified MTCI (mMTCI) increases significantly. The results provide experimental basis and theoretical reference for hyperspectral remote sensing inversion of chlorophyll content.

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...... state-of-the-art ‘guideline’ available for people involved in Remote Sensing in Wind Energy....

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

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.

The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

Science.gov (United States)

Savastano, K. J.; Leming, T. D.

1975-01-01

An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.

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.

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).

Remote sensing in meteorology, oceanography and hydrology

Energy Technology Data Exchange (ETDEWEB)

Cracknell, A P [ed.

1981-01-01

Various aspects of remote sensing are discussed. Topics include: the EARTHNET data acquisition, processing, and distribution facility the design and implementation of a digital interactive image processing system geometrical aspects of remote sensing and space cartography remote sensing of a complex surface legal aspects of remote sensing remote sensing of pollution, dust storms, ice masses, and ocean waves and currents use of satellite images for weather forecasting. Notes on field trips and work-sheets for laboratory exercises are included.

Volcanic ash supply to the surface ocean – remote sensing of biological responses and their wider biogeochemical significance

Directory of Open Access Journals (Sweden)

Thomas J. Browning

2015-03-01

Full Text Available Transient micronutrient enrichment of the surface ocean can enhance phytoplankton growth rates and alter microbial community structure with an ensuing spectrum of biogeochemical feedbacks. Strong phytoplankton responses to micronutrients supplied by volcanic ash have been reported recently. Here we: (i synthesize findings from these recent studies; (ii report the results of a new remote sensing study of ash fertilization; and (iii calculate theoretical bounds of ash-fertilized carbon export. Our synthesis highlights that phytoplankton responses to ash do not always simply mimic that of iron amendment; the exact mechanisms for this are likely biogeochemically important but are not yet well understood. Inherent optical properties of ash-loaded seawater suggest rhyolitic ash biases routine satellite chlorophyll-a estimation upwards by more than an order of magnitude for waters with 0.5 mg chlorophyll-a m-3. For this reason post-ash-deposition chlorophyll-a changes in oligotrophic waters detected via standard Case 1 (open ocean algorithms should be interpreted with caution. Remote sensing analysis of historic events with a bias less than a factor of 2 provided limited stand-alone evidence for ash-fertilization. Confounding factors were poor coverage, incoherent ash dispersal, and ambiguity ascribing biomass changes to ash supply over other potential drivers. Using current estimates of iron release and carbon export efficiencies, uncertainty bounds of ash-fertilized carbon export for 3 events are presented. Patagonian iron supply to the Southern Ocean from volcanic eruptions is less than that of windblown dust on thousand year timescales but can dominate supply at shorter timescales. Reducing uncertainties in remote sensing of phytoplankton response and nutrient release from ash are avenues for enabling assessment of the oceanic response to large-scale transient nutrient enrichment.

Integration of Remote Sensing Technology Using Sentinel-2A Satellite images For Fertilization and Water Pollution Analysis in Estuaries Inlet of Semarang Eastern Flood Canal

Directory of Open Access Journals (Sweden)

Subiyanto Sawitri

2018-01-01

Full Text Available One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.

Integration of Remote Sensing Technology Using Sentinel-2A Satellite images For Fertilization and Water Pollution Analysis in Estuaries Inlet of Semarang Eastern Flood Canal

Science.gov (United States)

Subiyanto, Sawitri; Ramadhanis, Zainab; Baktiar, Aditya Hafidh

2018-02-01

One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.

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.…

Radar Remote Sensing

Science.gov (United States)

Rosen, Paul A.

2012-01-01

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

A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

NARCIS (Netherlands)

Hommersom, A.; Wernand, M.R.; Peters, S.W.M.; de Boer, J.

2010-01-01

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and

Remote sensing for water quality

International Nuclear Information System (INIS)

Giardino, Claudia

2006-01-01

The application of remote sensing to the study of lakes is begun in years 80 with the lunch of the satellites of second generation. Many experiences have indicated the contribution of remote sensing for the limnology [it

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

Hyperspectral remote sensing application for monitoring and preservation of plant ecosystems

Science.gov (United States)

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

Remote sensing technologies have advanced significantly at last decade and have improved the capability to gather information about Earth’s resources and environment. They have many applications in Earth observation, such as mapping and updating land-use and cover, weather forecasting, biodiversity determination, etc. Hyperspectral remote sensing offers unique opportunities in the environmental monitoring and sustainable use of natural resources. Remote sensing sensors on space-based platforms, aircrafts, or on ground, are capable of providing detailed spectral, spatial and temporal information on terrestrial ecosystems. Ground-based sensors are used to record detailed information about the land surface and to create a data base for better characterizing the objects which are being imaged by the other sensors. In this paper some applications of two hyperspectral remote sensing techniques, leaf reflectance and chlorophyll fluorescence, for monitoring and assessment of the effects of adverse environmental conditions on plant ecosystems are presented. The effect of stress factors such as enhanced UV-radiation, acid rain, salinity, viral infections applied to some young plants (potato, pea, tobacco) and trees (plums, apples, paulownia) as well as of some growth regulators were investigated. Hyperspectral reflectance and fluorescence data were collected by means of a portable fiber-optics spectrometer in the visible and near infrared spectral ranges (450-850 nm and 600-900 nm), respectively. The differences between the reflectance data of healthy (control) and injured (stressed) plants were assessed by means of statistical (Student’s t-criterion), first derivative, and cluster analysis and calculation of some vegetation indices in four most informative for the investigated species regions: green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm). Fluorescence spectra were analyzed at five characteristic wavelengths located at the

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 L.; 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

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.

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

Science.gov (United States)

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

2017-12-01

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

Mississippi Sound Remote Sensing Study

Science.gov (United States)

Atwell, B. H.

1973-01-01

The Mississippi Sound Remote Sensing Study was initiated as part of the research program of the NASA Earth Resources Laboratory. The objective of this study is development of remote sensing techniques to study near-shore marine waters. Included within this general objective are the following: (1) evaluate existing techniques and instruments used for remote measurement of parameters of interest within these waters; (2) develop methods for interpretation of state-of-the-art remote sensing data which are most meaningful to an understanding of processes taking place within near-shore waters; (3) define hardware development requirements and/or system specifications; (4) develop a system combining data from remote and surface measurements which will most efficiently assess conditions in near-shore waters; (5) conduct projects in coordination with appropriate operating agencies to demonstrate applicability of this research to environmental and economic problems.

An extended PROSPECT: Advance in the leaf optical properties model separating total chlorophylls into chlorophyll a and b.

Science.gov (United States)

Zhang, Yao; Huang, Jingfeng; Wang, Fumin; Blackburn, George Alan; Zhang, Hankui K; Wang, Xiuzhen; Wei, Chuanwen; Zhang, Kangyu; Wei, Chen

2017-07-25

The PROSPECT leaf optical model has, to date, well-separated the effects of total chlorophyll and carotenoids on leaf reflectance and transmittance in the 400-800 nm. Considering variations in chlorophyll a:b ratio with leaf age and physiological stress, a further separation of total plant-based chlorophylls into chlorophyll a and chlorophyll b is necessary for advanced monitoring of plant growth. In this study, we present an extended version of PROSPECT model (hereafter referred to as PROSPECT-MP) that can combine the effects of chlorophyll a, chlorophyll b and carotenoids on leaf directional hemispherical reflectance and transmittance (DHR and DHT) in the 400-800 nm. The LOPEX93 dataset was used to evaluate the capabilities of PROSPECT-MP for spectra modelling and pigment retrieval. The results show that PROSPECT-MP can both simultaneously retrieve leaf chlorophyll a and b, and also performs better than PROSPECT-5 in retrieving carotenoids concentrations. As for the simulation of DHR and DHT, the performances of PROSPECT-MP are similar to that of PROSPECT-5. This study demonstrates the potential of PROSPECT-MP for improving capabilities of remote sensing of leaf photosynthetic pigments (chlorophyll a, chlorophyll b and carotenoids) and for providing a framework for future refinements in the modelling of leaf optical properties.

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.

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.

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

Directory of Open Access Journals (Sweden)

Jan U. H. Eitel

2010-03-01

Full Text Available Active ground optical remote sensing (AGORS devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and do not require spectral reference readings. Besides measuring red (590–670 nm and near-infrared (>760 nm reflectance AGORS devices have recently become available that also measure red-edge (730 nm reflectance. We tested the hypothesis that the additional availability of red-edge reflectance information would improve AGORS of plant stress induced chlorophyll breakdown in Scots pine (Pinus sylvestris. Our results showed that the availability of red-edge reflectance information improved AGORS estimates of stress induced variation in chlorophyll concentration (r2 > 0.73, RMSE < 1.69 when compared to those without (r2 = 0.57, RMSE = 2.11.

Detection of vegetation LUE based on chlorophyll fluorescence separation algorithm from Fraunhofer line

Science.gov (United States)

Liu, Liangyun; Zhang, Bing

2009-09-01

Photosynthetic efficiency is very important, and not yet generally assessable by remote sensing. Much research has proved the possibility of the separation of solar-induced chlorophyll fluorescence (ChlF) from the reflected hyperspectral data. As the 'probe' of plant photosynthesis, it is possible to detect photosynthetic light use efficiency (LUE) by the separated solar-induced ChlF. A diurnal experiment was carried out on winter wheat on Apr. 18, 2008, and the canopy radiance spectra and leaf LUE data were measured synchronously. The solar-induced chlorophyll fluorescence signals at 760nm and 688nm were separated from the reflected radiance spectral based on Fraunhofer lines in two oxygen absorption bands. The result showed that LUE was negatively correlated to the separated chlorophyll signals. The statistical models for LUE based on the solar-induced chlorophyll fluorescence values at 688 nm and 760 nm bands had correlation coefficients (R2) of 0.64 and 0.78, respectively. In addition, photochemical reflectance index (PRI) was also linked to LUE, and a statistical model for LUE based on PRI has a correlation coefficient (R2) of 0.66. The presented method provides a novel solution for monitoring LUE from remote sensing data.

Subsurface water parameters: optimization approach to their determination from remotely sensed water color data.

Science.gov (United States)

Jain, S C; Miller, J R

1976-04-01

A method, using an optimization scheme, has been developed for the interpretation of spectral albedo (or spectral reflectance) curves obtained from remotely sensed water color data. This method used a two-flow model of the radiation flow and solves for the albedo. Optimization fitting of predicted to observed reflectance data is performed by a quadratic interpolation method for the variables chlorophyll concentration and scattering coefficient. The technique is applied to airborne water color data obtained from Kawartha Lakes, Sargasso Sea, and Nova Scotia coast. The modeled spectral albedo curves are compared to those obtained experimentally, and the computed optimum water parameters are compared to ground truth values. It is shown that the backscattered spectral signal contains information that can be interpreted to give quantitative estimates of the chlorophyll concentration and turbidity in the waters studied.

Image Fusion Technologies In Commercial Remote Sensing Packages

OpenAIRE

Al-Wassai, Firouz Abdullah; Kalyankar, N. V.

2013-01-01

Several remote sensing software packages are used to the explicit purpose of analyzing and visualizing remotely sensed data, with the developing of remote sensing sensor technologies from last ten years. Accord-ing to literature, the remote sensing is still the lack of software tools for effective information extraction from remote sensing data. So, this paper provides a state-of-art of multi-sensor image fusion technologies as well as review on the quality evaluation of the single image or f...

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...

Multi-Spectral Remote Sensing of Phytoplankton Pigment Absorption Properties in Cyanobacteria Bloom Waters: A Regional Example in the Western Basin of Lake Erie

Directory of Open Access Journals (Sweden)

Guoqing Wang

2017-12-01

Full Text Available Phytoplankton pigments absorb sunlight for photosynthesis, protect the chloroplast from damage caused by excess light energy, and influence the color of the water. Some pigments act as bio-markers and are important for separation of phytoplankton functional types. Among many efforts that have been made to obtain information on phytoplankton pigments from bio-optical properties, Gaussian curves decomposed from phytoplankton absorption spectrum have been used to represent the light absorption of different pigments. We incorporated the Gaussian scheme into a semi-analytical model and obtained the Gaussian curves from remote sensing reflectance. In this study, a series of sensitivity tests were conducted to explore the potential of obtaining the Gaussian curves from multi-spectral satellite remote sensing. Results showed that the Gaussian curves can be retrieved with 35% or less mean unbiased absolute percentage differences from MEdium Resolution Imaging Spectrometer (MERIS and Moderate Resolution Imaging Spectroradiometer (MODIS-like sensors. Further, using Lake Erie as an example, the spatial distribution of chlorophyll a and phycocyanin concentrations were obtained from the Gaussian curves and used as metrics for the spatial extent of an intense cyanobacterial bloom occurred in Lake Erie in 2014. The seasonal variations of Gaussian absorption properties in 2011 were further obtained from MERIS imagery. This study shows that it is feasible to obtain Gaussian curves from multi-spectral satellite remote sensing data, and the obtained chlorophyll a and phycocyanin concentrations from these Gaussian peak heights demonstrated potential application to monitor harmful algal blooms (HABs and identification of phytoplankton groups from satellite ocean color remote sensing semi-analytically.

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.

Impact of measurement uncertainties on determination of chlorophyll-specific absorption coefficient for marine phytoplankton

OpenAIRE

McKee, D.; Röttgers, R.; Neukermans, G.; Calzado, V.S.; Trees, C.; Ampolo-Rella, M.; Neil, C.; Cunningham, A.

2014-01-01

Understanding variability in the chlorophyll-specific absorption of marine phytoplankton, aph*Chl (λ), is essential for primary production modelling, calculation of underwater light field characteristics, and development of algorithms for remote sensing of chlorophyll concentrations. Previous field and laboratory studies have demonstrated significant apparent variability in aph*Chl (λ) for natural samples and algal cultures. However, the potential impact of measurement uncertain...

Growth studies of Mytilus californianus using satellite surface temperatures and chlorophyll data for coastal Oregon

Science.gov (United States)

Price, J.; Lakshmi, V.

2013-12-01

The advancement of remote sensing technology has led to better understanding of the spatial and temporal variation in many physical and biological parameters, such as, temperature, salinity, soil moisture, vegetation cover, and community composition. This research takes a novel approach in understanding the temporal and spatial variability of mussel body growth using remotely sensed surface temperatures and chlorophyll-a concentration. Within marine rocky intertidal ecosystems, temperature and food availability influence species abundance, physiological performance, and distribution of mussel species. Current methods to determine the temperature mussel species experience range from in-situ field observations, temperature loggers, temperature models, and using other temperature variables. However, since the temperature that mussel species experience is different from the air temperature due to physical and biological characteristics (size, color, gaping, etc.), it is difficult to accurately predict the thermal stresses they experience. Methods to determine food availability (chlorophyll-a concentration used as a proxy) for mussel species are mostly done at specific study sites using water sampling. This implies that analysis of temperature and food availability across large spatial scales and long temporal scales is not a trivial task given spatial heterogeneity. However, this is an essential step in determination of the impact of changing climate on vulnerable ecosystems such as the marine rocky intertidal system. The purpose of this study was to investigate the potential of using remotely sensed surface temperatures and chlorophyll-a concentration to better understand the temporal and spatial variability of the body growth of the ecologically and economically important rocky intertidal mussel species, Mytilus californianus. Remotely sensed sea surface temperature (SST), land surface temperature (LST), intertidal surface temperature (IST), chlorophyll

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....

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...

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

Science.gov (United States)

Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

2016-01-01

Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

Application of Hyperspectral Remote Sensing Techniques to Evaluate Water Quality in Turbid Coastal Waters of South Carolina.

Science.gov (United States)

Ali, K. A.; Ryan, K.

2014-12-01

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide valuable ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. Existing remote sensing ocean color products, such as the water quality proxy chlorophyll-a, are based on ocean derived bio-optical models that are primarily calibrated in Case 1 type waters. These traditional models fail to work when applied in turbid (Case 2 type), coastal waters due to spectral interference from other associated color producing agents such as colored dissolved organic matter and suspended sediments. In this work, we introduce a novel technique for the predictive modeling of chlorophyll-a using a multivariate-based approach applied to in situ hyperspectral radiometric data collected from the coastal waters of Long Bay, South Carolina. This method uses a partial least-squares regression model to identify prominent wavelengths that are more sensitive to chlorophyll-a relative to other associated color-producing agents. The new model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 μg/L. This approach capitalizes on the spectral advantage gained from current and future hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. The utility of this tool is in its versatility to a diverse set of coastal waters and its use by coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

Best practices in Remote Sensing for REDD+

DEFF Research Database (Denmark)

Dons, Klaus; Grogan, Kenneth

2012-01-01

due to steep terrain, • phenological gradients across natural, agricultural and forestry ecosystems including plantations and • the need to serve the REDD-specific context of deforestation and forest degradation across spatial and temporal scales make remote sensing based approaches particularly...... be expected from remote sensing imagery and the provided information shall help to better anticipate problems that will be encountered when acquiring, analyzing and interpreting remote sensing data. Beyond remote sensing, it may be a good point of departure for a large group of scientists with a diverse...... and governance, and deforestation and forest degradation processes. The second part summarizes the available literature on remote sensing based good practices for REDD. It largely draws from the documents of the Intergovernmental Panel on Climate Change (IPCC), the United Nations Framework Convention on Climate...

Chlorophyll modulation of mixed layer thermodynamics in a mixed-layer isopycnal general circulation model - An example from Arabian Sea and Equatorial Pacific

Digital Repository Service at National Institute of Oceanography (India)

Nakamoto, S.; PrasannaKumar, S.; Oberhuber, J.M.; Saito, H.; Muneyama, K.

and supported by quasi-steady upwelling. Remotely sensed chlorophyll pigment concentrations from the Coastal Zone Color Scanner (CZCS) are used to investigate the chlorophyll modulation of ocean mixed layer thermodynamics in a bulk mixed-layer model, embedded...

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 K.; Leimgruber, Peter; Morisette, Jeffrey T.; Musinsky, John; Pintea, Lilian; Prados, Ana; Radeloff, Volker C.; Rowen, Mary; Saatchi, Sassan; Schill, Steve; Tabor, Karyn; Turner, Woody; Vodacek, Anthony; Vogelmann, James; Wegmann, Martin; Wilkie, David; Wilson, Cara

2014-01-01

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to

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

Remote sensing for oil spill detection and response

International Nuclear Information System (INIS)

Engelhardt, F.R.

1999-01-01

This paper focuses on the use of remote sensing for marine oil spill detection and response. The surveillance and monitoring of discharges, and the main elements of effective surveillance are discussed. Tactical emergency response and the requirements for selecting a suitable remote sensing approach, airborne remote sensing systems, and the integration of satellite and airborne imaging are examined. Specifications of satellite surveillance systems potentially usable for oil spill detection, and specifications of airborne remote sensing systems suitable for oil spill detection, monitoring and supplemental actions are tabulated, and a schema of integrated satellite-airborne remote sensing (ISARS) is presented. (UK)

Satellite Remote Sensing: Aerosol Measurements

Science.gov (United States)

Kahn, Ralph A.

2013-01-01

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Using optical remote sensing techniques to track the development of ozone-induced stress

Energy Technology Data Exchange (ETDEWEB)

Meroni, Michele, E-mail: michele.meroni@unimib.i [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy); Panigada, Cinzia; Rossini, Micol [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy); Picchi, Valentina [CNR, Plant Virology Institute, Milan Unit, Milan (Italy); Department of Tree Science, Entomology and Plant Pathology ' G. Scaramuzzi' , University of Pisa, Pisa (Italy); Cogliati, Sergio; Colombo, Roberto [Remote Sensing of Environmental Dynamics Laboratory, DISAT, University of Milan-Bicocca, Piazza della Scienza, 1, 20126 Milan (Italy)

2009-05-15

In this paper, a literature review about optical remote sensing (RS) of O{sub 3} stress is presented. Studies on O{sub 3}-induced effects on vegetation reflectance have been conducted since late '70s based on the analysis of optical RS data. Literature review reveals that traditional RS techniques were able to detect changes in leaf and canopy reflectance related to O{sub 3}-induced stress when visible symptoms already occurred. Only recently, advanced RS techniques using hyperspectral sensors, demonstrated the feasibility of detecting the stress in its early phase by monitoring excess energy dissipation pathways such as chlorophyll fluorescence and non-photochemical quenching (NPQ). Steady-state fluorescence (Fs), measured by exploiting the Fraunhofer line depth principle and NPQ related xanthophyll-cycle, estimated through the photochemical reflectance index (PRI) responded to O{sub 3} fumigation before visible symptoms occurred. This opens up new possibilities for the early detection of vegetation O{sub 3} stress by means of hyperspectral RS. - Possibilities for the early detection of vegetation O{sub 3} stress by means of optical remote sensing are discussed.

Using optical remote sensing techniques to track the development of ozone-induced stress

International Nuclear Information System (INIS)

Meroni, Michele; Panigada, Cinzia; Rossini, Micol; Picchi, Valentina; Cogliati, Sergio; Colombo, Roberto

2009-01-01

In this paper, a literature review about optical remote sensing (RS) of O 3 stress is presented. Studies on O 3 -induced effects on vegetation reflectance have been conducted since late '70s based on the analysis of optical RS data. Literature review reveals that traditional RS techniques were able to detect changes in leaf and canopy reflectance related to O 3 -induced stress when visible symptoms already occurred. Only recently, advanced RS techniques using hyperspectral sensors, demonstrated the feasibility of detecting the stress in its early phase by monitoring excess energy dissipation pathways such as chlorophyll fluorescence and non-photochemical quenching (NPQ). Steady-state fluorescence (Fs), measured by exploiting the Fraunhofer line depth principle and NPQ related xanthophyll-cycle, estimated through the photochemical reflectance index (PRI) responded to O 3 fumigation before visible symptoms occurred. This opens up new possibilities for the early detection of vegetation O 3 stress by means of hyperspectral RS. - Possibilities for the early detection of vegetation O 3 stress by means of optical remote sensing are discussed.

Remote sensing for agriculture, ecosystems, and hydrology

International Nuclear Information System (INIS)

Engman, E.T.

1998-01-01

This volume contains the proceedings of SPIE's remote sensing symposium which was held September 22--24, 1998, in Barcelona, Spain. Topics of discussion include the following: calibration techniques for soil moisture measurements; remote sensing of grasslands and biomass estimation of meadows; evaluation of agricultural disasters; monitoring of industrial and natural radioactive elements; and remote sensing of vegetation and of forest fires

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.

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.

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.

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

Developing status of satellite remote sensing and its application

International Nuclear Information System (INIS)

Zhang Wanliang; Liu Dechang

2005-01-01

This paper has discussed the latest development of satellite remote sensing in sensor resolutions, satellite motion models, load forms, data processing and its application. The authors consider that sensor resolutions of satellite remote sensing have increased largely. Valid integration of multisensors is a new idea and technology of satellite remote sensing in the 21st century, and post-remote sensing application technology is the important part of deeply applying remote sensing information and has great practical significance. (authors)

Current perspective on remote sensing

International Nuclear Information System (INIS)

Goodman, R.H.

1992-01-01

Surveillance and tracking of oil spills has been a feature of most spill response situations for many years. The simplest and most direct method uses visual observations from an aircraft and hand-plotting of the data on a map. This technique has proven adequate for most small spills and for responses in fair weather. As the size of the spill increases or the weather deteriorates, there is a need to augment visual aerial observations with remote sensing methods. Remote sensing and its associated systems are one of the most technically complex and sophisticated elements of an oil spill response. During the past few years, a number of initiatives have been undertaken to use contemporary electronic and computing systems to develop new and improved remote sensing systems

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

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

Remote sensing of wetlands applications and advances

CERN Document Server

Tiner, Ralph W; Klemas, Victor V

2015-01-01

Effectively Manage Wetland Resources Using the Best Available Remote Sensing Techniques Utilizing top scientists in the wetland classification and mapping field, Remote Sensing of Wetlands: Applications and Advances covers the rapidly changing landscape of wetlands and describes the latest advances in remote sensing that have taken place over the past 30 years for use in mapping wetlands. Factoring in the impact of climate change, as well as a growing demand on wetlands for agriculture, aquaculture, forestry, and development, this text considers the challenges that wetlands pose for remote sensing and provides a thorough introduction on the use of remotely sensed data for wetland detection. Taking advantage of the experiences of more than 50 contributing authors, the book describes a variety of techniques for mapping and classifying wetlands in a multitude of environments ranging from tropical to arctic wetlands including coral reefs and submerged aquatic vegetation. The authors discuss the advantages and di...

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

Environmental monitoring by means of remote sensing

International Nuclear Information System (INIS)

Theilen-Willige, B.

1993-01-01

Aircraft and satellite aerial photographs represent indispensible tools for environmental observation today. They contribute to a systematic inventory of important environmental parameters such as climate, vegetation or surface water. Their great importance lies in the continuous monitoring of large regions so that changes in environmental conditions are quickly detected. This book provides an overview of the capabilities of remote sensing in environmental monitoring and in the recognition of environmental problems as well as of the usefulness of remote sensing data for environmental planning. Also addressed is the role of remote sensing in the monitoring of natural hazards such as earthquakes and volcano eruptions as well as problems of remote sensing technology transfer to developing countries. (orig.) [de

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.

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

Integrating remote sensing and spatially explicit epidemiological modeling

Science.gov (United States)

Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

2015-04-01

Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

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.

Comparison of chlorophyll in the Red Sea derived from MODIS-Aqua and in vivo fluorescence

KAUST Repository

Brewin, Robert J W; Raitsos, Dionysios E.; Pradhan, Yaswant; Hoteit, Ibrahim

2013-01-01

The Red Sea is a unique marine environment but relatively unexplored. The only available long-term biological dataset at large spatial and temporal scales is remotely-sensed chlorophyll observations (an index of phytoplankton biomass) derived using

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.

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

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

Hyperspectral remote sensing

National Research Council Canada - National Science Library

Eismann, Michael Theodore

2012-01-01

..., and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment...

PHOTOGRAMMETRY – REMOTE SENSING AND GEOINFORMATION

Directory of Open Access Journals (Sweden)

M. A. Lazaridou

2012-07-01

Full Text Available 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.

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...

Oil spill remote sensing sensors and aircraft

International Nuclear Information System (INIS)

Fingas, M.; Fruhwirth, M.; Gamble, L.

1992-01-01

The most common form of remote sensing as applied to oil spills is aerial remote sensing. The technology of aerial remote sensing, mainly from aircraft, is reviewed along with aircraft-mounted remote sensors and aircraft modifications. The characteristics, advantages, and limitations of optical techniques, infrared and ultraviolet sensors, fluorosensors, microwave and radar sensors, and slick thickness sensors are discussed. Special attention is paid to remote sensing of oil under difficult circumstances, such as oil in water or oil on ice. An infrared camera is the first sensor recommended for oil spill work, as it is the cheapest and most applicable device, and is the only type of equipment that can be bought off-the-shelf. The second sensor recommended is an ultraviolet and visible-spectrum device. The laser fluorosensor offers the only potential for discriminating between oiled and un-oiled weeds or shoreline, and for positively identifying oil pollution on ice and in a variety of other situations. However, such an instrument is large and expensive. Radar, although low in priority for purchase, offers the only potential for large-area searches and foul-weather remote sensing. Most other sensors are experimental or do not offer good potential for oil detection or mapping. 48 refs., 8 tabs

Operational Use of Remote Sensing within USDA

Science.gov (United States)

Bethel, Glenn R.

2007-01-01

A viewgraph presentation of remote sensing imagery within the USDA is shown. USDA Aerial Photography, Digital Sensors, Hurricane imagery, Remote Sensing Sources, Satellites used by Foreign Agricultural Service, Landsat Acquisitions, and Aerial Acquisitions are also shown.

Multi-source remote sensing data management system

International Nuclear Information System (INIS)

Qin Kai; Zhao Yingjun; Lu Donghua; Zhang Donghui; Wu Wenhuan

2014-01-01

In this thesis, the author explored multi-source management problems of remote sensing data. The main idea is to use the mosaic dataset model, and the ways of an integreted display of image and its interpretation. Based on ArcGIS and IMINT feature knowledge platform, the author used the C# and other programming tools for development work, so as to design and implement multi-source remote sensing data management system function module which is able to simply, conveniently and efficiently manage multi-source remote sensing data. (authors)

Spatiotemporal chlorophyll-a dynamics on the Louisiana continental shelf derived from a dual satellite imagery algorithm

Science.gov (United States)

A monthly time series of remotely sensed chlorophyll-a (Chlars) over the Louisiana continental shelf (LCS) was developed and examined for its relationship to river discharge, nitrate concentration, total phosphorus concentration, photosynthetically available radiation (PAR), wind...

Remote sensing and resource exploration

International Nuclear Information System (INIS)

El-Baz, F.; Hassan, M.H.A.; Cappellini, V.

1989-01-01

The purpose of the Workshop was to study in depth the application of remote sensing technology to the fields of archaeology, astronomy, geography, geology, and physics. Some emphasis was placed on utilizing remote sensing methods and techniques in the search for water, mineral and land resources. The Workshop was attended by 90 people from 35 countries. The proceedings of this meeting includes 15 papers, 12 of them have a separate abstract in the INIS Database. Refs, figs and tabs

Prospecting for coal in China with remote sensing

Energy Technology Data Exchange (ETDEWEB)

Ke-long Tan; Yu-qing Wan; Sun-xin Sun; Gui-bao Bao; Jing-shui Kuang [Aerophotogrammetry and Remote Sensing Center of China Coal, Xi' an (China)

2008-12-15

In China it is important to explore coal prospecting by taking advantage of modern remote sensing and geographic information system technologies. Given a theoretical basis for coal prospecting by remote sensing, the methodologies and existing problems are demonstrated systematically by summarizing past practices of coal prospecting with remote sensing. A new theory of coal prospecting with remote sensing is proposed. In uncovered areas, coal resources can be prospected by direct interpretation. In coal bearing strata of developed areas covered by thin Quaternary strata or vegetation, prospecting for coal can be carried out by indirect interpretation of geomorphology and vegetation. For deeply buried underground deposits, coal prospecting can rely on tectonic structures, interpretation and analysis of new tectonic clues and regularity of coal formation and preservation controlled by tectonic structures. By applying newly hyper-spectral, multi-polarization, multi-angle, multi-temporal and multi-resolution remote sensing data and carrying out integrated analysis of geographic attributes, ground attributes, geophysical exploration results, geochemical exploration results, geological drilling results and remote sensing data by GIS tools, coal geology resources and mineralogical regularities can be explored and coal resource information can be acquired with some confidence. 12 refs., 4 figs., 3 tabs.

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…

Physics teaching by infrared remote sensing of vegetation

Science.gov (United States)

Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

2018-05-01

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

National Satellite Land Remote Sensing Data Archive

Science.gov (United States)

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

2013-01-01

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

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.

History and future of remote sensing technology and education

Science.gov (United States)

Colwell, R. N.

1980-01-01

A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.

Remote sensing for vineyard management

Science.gov (United States)

Philipson, W. R.; Erb, T. L.; Fernandez, D.; Mcleester, J. N.

1980-01-01

Cornell's Remote Sensing Program has been involved in a continuing investigation to assess the value of remote sensing for vineyard management. Program staff members have conducted a series of site and crop analysis studies. These include: (1) panchromatic aerial photography for planning artificial drainage in a new vineyard; (2) color infrared aerial photography for assessing crop vigor/health; and (3) color infrared aerial photography and aircraft multispectral scanner data for evaluating yield related factors. These studies and their findings are reviewed.

Remote sensing of coral reefs and their physical environment

International Nuclear Information System (INIS)

Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T.

2004-01-01

There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas

Remote sensing of coral reefs and their physical environment

Energy Technology Data Exchange (ETDEWEB)

Mumby, Peter J.; Skirving, William; Strong, Alan E.; Hardy, John T.; LeDrew, Ellsworth F.; Hochberg, Eric J.; Stumpf, Rick P.; David, Laura T

2004-02-01

There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas.

Response of the equatorial Pacific to chlorophyll pigment in a mixed layer isopycnal ocean general circulation model

Digital Repository Service at National Institute of Oceanography (India)

Nakamoto, S.; PrasannaKumar, S.; Oberhuber, J.M.; Ishizaka, J.; Muneyama, K.; Frouin, R.

The influence of phytoplankton on the upper ocean dynamics and thermodynamics in the equatorial Pacific is investigated using an isopycnal ocean general circulation model (OPYC) coupled with a mixed layer model and remotely sensed chlorophyll...

Remote Sensing of Landslides—A Review

Directory of Open Access Journals (Sweden)

Chaoying Zhao

2018-02-01

Full Text Available Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.

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

Remote sensing of coastal area near Bari : results of marine campaign performed with lidar fluorosensor; Rapporto sulla campagna di misura con LIDAR fluorosensore effettuate sul mare di Bari

Energy Technology Data Exchange (ETDEWEB)

Barbini, R.; Colao, F.; Fantoni, R.; Palucci, A.; Ribezzo, S. [ENEA, Centro Ricerche Frascati, Rome (Italy). Dip. Innovazione

1995-12-01

The lidar fluorosensor, built at ENEA Frascati to remotely monitor the sea-water quality by collecting the water Raman back scattering and induced fluorescence from dispersed oils, suspended matter and chlorophyll, has been employed in a marine campaign in the southern Adriatic sea. To this aim, the lidar fluorosensor has been installed on a coastal guard boat and operated during the cruise. Extensive calibration measurements have been undertaken by using this system, both in laboratory and during the campaigns, to analyze sea water samples taken at several places along the Italian coasts. Absolute values of organic matter, chlorophyll concentrations have been obtained by calibrating the locally and remotely sensed lidar data with standard physical-chemical methods.

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.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

Science.gov (United States)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

Use of microwave remote sensing in salinity estimation

International Nuclear Information System (INIS)

Singh, R.P.; Kumar, V.; Srivastav, S.K.

1990-01-01

Soil-moisture interaction and the consequent liberation of ions causes the salinity of waters. The salinity of river, lake, ocean and ground water changes due to seepage and surface runoff. We have studied the feasibility of using microwave remote sensing for the estimation of salinity by carrying out numerical calculations to study the microwave remote sensing responses of various models representative of river, lake and ocean water. The results show the dependence of microwave remote sensing responses on the salinity and surface temperature of water. The results presented in this paper will be useful in the selection of microwave sensor parameters and in the accurate estimation of salinity from microwave remote sensing data

Online catalog access and distribution of remotely sensed information

Science.gov (United States)

Lutton, Stephen M.

1997-09-01

Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.

Review of research on remote sensing with digital map. Remote sensing to suchi chizu no ketsugo ni yoru kenkyu no shokai

Energy Technology Data Exchange (ETDEWEB)

Tanaka, S; Sugimura, T [Remote Sensing Technology Center of Japan, Tokyo (Japan)

1990-12-05

This paper describes the relationship between remote sensing and digital map. The relation between remote sensing and digital map is roughly classified into two kinds. One of them is utilization of remote sensing and digital map in combination to analyze phenomena, and the other is normalization of remote sensing data by use of digital map. For examples of utilizing remote sensing and digital map, there are the creation of a perspective image of ground scene from Landsat MSS data by use of a mesh type digital map of the orthogonal co-ordinates, and the creation of an image of the enviromental research along roads from satilite data by use of a vector type digital map. Furthermore, this paper introduces a procedure of correcting geographical strains by use of a digital map and converting a radar image to corrected plane image, and the use of a digital map in the global scale for the analysis of floods and other purposes. 20 refs., 5 figs., 1 tab.

Remote sensing in operational range management programs in Western Canada

Science.gov (United States)

Thompson, M. D.

1977-01-01

A pilot program carried out in Western Canada to test remote sensing under semi-operational conditions and display its applicability to operational range management programs was described. Four agencies were involved in the program, two in Alberta and two in Manitoba. Each had different objectives and needs for remote sensing within its range management programs, and each was generally unfamiliar with remote sensing techniques and their applications. Personnel with experience and expertise in the remote sensing and range management fields worked with the agency personnel through every phase of the pilot program. Results indicate that these agencies have found remote sensing to be a cost effective tool and will begin to utilize remote sensing in their operational work during ensuing seasons.

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...

Current NASA Earth Remote Sensing Observations

Science.gov (United States)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;

Geological remote sensing signatures of terrestrial impact craters

International Nuclear Information System (INIS)

Garvin, J.B.; Schnetzler, C.; Grieve, R.A.F.

1988-01-01

Geological remote sensing techniques can be used to investigate structural, depositional, and shock metamorphic effects associated with hypervelocity impact structures, some of which may be linked to global Earth system catastrophies. Although detailed laboratory and field investigations are necessary to establish conclusive evidence of an impact origin for suspected crater landforms, the synoptic perspective provided by various remote sensing systems can often serve as a pathfinder to key deposits which can then be targetted for intensive field study. In addition, remote sensing imagery can be used as a tool in the search for impact and other catastrophic explosion landforms on the basis of localized disruption and anomaly patterns. In order to reconstruct original dimensions of large, complex impact features in isolated, inaccessible regions, remote sensing imagery can be used to make preliminary estimates in the absence of field geophysical surveys. The experienced gained from two decades of planetary remote sensing of impact craters on the terrestrial planets, as well as the techniques developed for recognizing stages of degradation and initial crater morphology, can now be applied to the problem of discovering and studying eroded impact landforms on Earth. Preliminary results of remote sensing analyses of a set of terrestrial impact features in various states of degradation, geologic settings, and for a broad range of diameters and hence energies of formation are summarized. The intention is to develop a database of remote sensing signatures for catastrophic impact landforms which can then be used in EOS-era global surveys as the basis for locating the possibly hundreds of missing impact structures

Accuracy Dimensions in Remote Sensing

Science.gov (United States)

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

2018-04-01

The technological developments in remote sensing (RS) during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS), which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users' needs. The present paper gives the theoretic overview of the issue, besides selected, practice

ACCURACY DIMENSIONS IN REMOTE SENSING

Directory of Open Access Journals (Sweden)

Á. Barsi

2018-04-01

Full Text Available The technological developments in remote sensing (RS during the past decade has contributed to a significant increase in the size of data user community. For this reason data quality issues in remote sensing face a significant increase in importance, particularly in the era of Big Earth data. Dozens of available sensors, hundreds of sophisticated data processing techniques, countless software tools assist the processing of RS data and contributes to a major increase in applications and users. In the past decades, scientific and technological community of spatial data environment were focusing on the evaluation of data quality elements computed for point, line, area geometry of vector and raster data. Stakeholders of data production commonly use standardised parameters to characterise the quality of their datasets. Yet their efforts to estimate the quality did not reach the general end-user community running heterogeneous applications who assume that their spatial data is error-free and best fitted to the specification standards. The non-specialist, general user group has very limited knowledge how spatial data meets their needs. These parameters forming the external quality dimensions implies that the same data system can be of different quality to different users. The large collection of the observed information is uncertain in a level that can decry the reliability of the applications. Based on prior paper of the authors (in cooperation within the Remote Sensing Data Quality working group of ISPRS, which established a taxonomy on the dimensions of data quality in GIS and remote sensing domains, this paper is aiming at focusing on measures of uncertainty in remote sensing data lifecycle, focusing on land cover mapping issues. In the paper we try to introduce how quality of the various combination of data and procedures can be summarized and how services fit the users’ needs. The present paper gives the theoretic overview of the issue, besides

Optical/Infrared Signatures for Space-Based Remote Sensing

National Research Council Canada - National Science Library

Picard, R. H; Dewan, E. M; Winick, J. R; O'Neil, R. R

2007-01-01

This report describes work carried out under the Air Force Research Laboratory's basic research task in optical remote-sensing signatures, entitled Optical / Infrared Signatures for Space-Based Remote Sensing...

Chlorophyll Detection and Mapping of Shallow Water Impoundments Using Image Spectrometry

International Nuclear Information System (INIS)

Artigas, F.; Pechmann, I.; Marti, A.; Yao, N.; Pechmann, I.

2008-01-01

There exists a common perception that chlorophyll a concentrations in tidal coastal waters are unsuitable to be captured by remote sensing techniques because of high water turbidity. In this study, we use band index measurements to separate active chlorophyll pigments from other constituents in the water. Published single- and multiband spectral indices are used to establish a relationship between algal chlorophyll concentration and reflectance data. We find an index which is suitable to map chlorophyll gradients in the impoundments, ditches, and associated waterways of the Hackensack Meadow lands (NJ, USA). The resulting images clearly depict the spatial distribution of plant pigments and their relationship with the biological conditions of the waters in the estuary. Since these biological conditions are often determined by land usage, the methods in this paper provide a simple tool to address water quality management issues in fragmented urban estuaries.

New advance in the research of post-remote sensing application technology. Series of 'proposition and consideration of post-remote sensing application technology'

International Nuclear Information System (INIS)

Liu Dechang; Ye Fawang

2005-01-01

Based on deep consideration in post-remote sensing application technology, this article pays more attention to its technological meaning. The application idea of post-remote sensing application technology to uranium exploration is also discussed. The proposition and research on new concept of post-remote sensing application technology is an important search and of important theoretical and practical significance to uranium exploration. (authors)

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

Comprehensive, integrated, remote sensing at DOE sites

International Nuclear Information System (INIS)

Lackey, J.G.; Burson, Z.G.

1985-01-01

The Department of Energy has established a program called Comprehensive, Integrated Remote Sensing (CIRS). The overall objective of the program is to provide a state-of-the-art data base of remotely sensed data for all users of such information at large DOE sites. The primary types of remote sensing provided, at present, consist of the following: large format aerial photography, video from aerial platforms, multispectral scanning, and airborne nuclear radiometric surveys. Implementation of the CIRS Program by EG and G Energy Measurements, Inc. began with field operations at the Savannah River Plant in 1982 and is continuing at that DOE site at a level of effort of about $1.5 m per year. Integrated remote sensing studies were subsequently extended to the West Valley Demonstration Project in this summer and fall of 1984. It is expected that the Program will eventually be extended to cover all large DOE sites on a continuing basis

Polarimetric Remote Sensing of Atmospheric Particulate Pollutants

Science.gov (United States)

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

2018-04-01

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

Annotated bibliography of remote sensing methods for monitoring desertification

Science.gov (United States)

Walker, A.S.; Robinove, Charles J.

1981-01-01

Remote sensing techniques are valuable for locating, assessing, and monitoring desertification. Remotely sensed data provide a permanent record of the condition of the land in a format that allows changes in land features and condition to be measured. The annotated bibliography of 118 items discusses remote sensing methods that may be applied to desertification studies.

Possibility of continuous monitoring of environment around the nuclear plant using satellite remote sensing

International Nuclear Information System (INIS)

Sasaki, Takanori; Tanabu, Yoshimine; Fujita, Shigetaka; Zhao Wenhui

2008-01-01

Interest in nuclear power generation is increasing by rising of power demand and environmental concern. It is important more and more to confirm and show the safety operation of nuclear plants, which is useful to remove anxiety of residents. Satellite remote sensing is one of the way of it. Large observation width and long and continuous observation period are advantage of satellite remote sensing. In addition, it is very important to be able to monitor without visitation on the site. We have continued local area environmental analysis using various satellites. MODIS on Terra and Aqua which are NASA satellites received by Hachinohe Institute of Technology is mainly used. According to these results, we have shown that combined analysis of various information parameters such as land surface temperature, geographical changes, vegetation, etc. is very effective to monitor environmental changes. In these analyses, error detection is very important. Therefore, enough storage data with continuously monitoring in usual state is necessary. Moreover, it is thought that the confirmation of stable operation of plants by means of continuous monitoring can contribute to reduce residents' anxiety of nuclear power plant. Additionally, in the case that the change of influence on surroundings is detected, it is possible to grasp the situation and take measure in early stage by error detection. In this paper, as an possible example of continuous monitoring using satellite remote sensing, we introduce the result of analysis and investigation of which changes of sea surface temperature and chlorophyll concentration on the sea around power plant. (author)

Preface to: Pan Ocean Remote Sensing Conference (PORSEC)

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.

Conference (PORSEC), earlier known as the Paci c Ocean Remote Sensing Conference (PORSEC), was formed in 1992 to provide a venue for international cooperation in the increasingly important area of remote sensing of the ocean. Many countries that border... and ocean dynamics, and modeling with satellite sensor (mainly microwave) data. Some of the presentations are of regional interest, while others will nd an audience beyond the satellite remote sensing community. These rst results through their simple...

Sun-induced Chlorophyll fluorescence and PRI improve remote sensing GPP estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Science.gov (United States)

Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2015-07-01

This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different Nitrogen (N) and Phosphorous (P) availability. Sun-induced chlorophyll Fluorescence yield computed at 760 nm (Fy760), scaled-photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and Normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy-chambers on the same locations sampled by the spectrometers. We hypothesized that light-use efficiency (LUE) models driven by remote sensing quantities (RSM) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as proxy for LUE and NDVI or MTCI as fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed significantly higher GPP in the N fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was tightly related to plant N content (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments but it is affected by N availability. Results from a cross validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv = 140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However, residual analyses

Chlorophyll and sediment distribution study of the Gulf of Kutch using remote sensing

Digital Repository Service at National Institute of Oceanography (India)

Kunte, P.D.; Takahiro Osawa; Yasuhiro Sugimori

This study is largely based on the resulting series of SeaWiFS images and OCM images of Gulf of Kutch, which shows chlorophyll distribution on about 160 (cloud-free) dates between October 1998 and August 2001 period and sediment distribution pattern...

Modelling size-fractionated primary production in the Atlantic Ocean from remote sensing

Science.gov (United States)

Brewin, Robert J. W.; Tilstone, Gavin H.; Jackson, Thomas; Cain, Terry; Miller, Peter I.; Lange, Priscila K.; Misra, Ankita; Airs, Ruth L.

2017-11-01

Marine primary production influences the transfer of carbon dioxide between the ocean and atmosphere, and the availability of energy for the pelagic food web. Both the rate and the fate of organic carbon from primary production are dependent on phytoplankton size. A key aim of the Atlantic Meridional Transect (AMT) programme has been to quantify biological carbon cycling in the Atlantic Ocean and measurements of total primary production have been routinely made on AMT cruises, as well as additional measurements of size-fractionated primary production on some cruises. Measurements of total primary production collected on the AMT have been used to evaluate remote-sensing techniques capable of producing basin-scale estimates of primary production. Though models exist to estimate size-fractionated primary production from satellite data, these have not been well validated in the Atlantic Ocean, and have been parameterised using measurements of phytoplankton pigments rather than direct measurements of phytoplankton size structure. Here, we re-tune a remote-sensing primary production model to estimate production in three size fractions of phytoplankton (10 μm) in the Atlantic Ocean, using measurements of size-fractionated chlorophyll and size-fractionated photosynthesis-irradiance experiments conducted on AMT 22 and 23 using sequential filtration-based methods. The performance of the remote-sensing technique was evaluated using: (i) independent estimates of size-fractionated primary production collected on a number of AMT cruises using 14C on-deck incubation experiments and (ii) Monte Carlo simulations. Considering uncertainty in the satellite inputs and model parameters, we estimate an average model error of between 0.27 and 0.63 for log10-transformed size-fractionated production, with lower errors for the small size class (10 μm), and errors generally higher in oligotrophic waters. Application to satellite data in 2007 suggests the contribution of cells 2 μm to total

Remote Sensing: Physics And Environmental Applications

International Nuclear Information System (INIS)

EI Raey, M.

2007-01-01

Full text: Basic principles of remote sensing of environment are outlined emphasizing inherent physical and target properties leading to proper identification and classification. Basic processing techniques are discussed. Applications of remote sensing techniques in various aspects of environmental monitoring and assessment is surveyed with emphasis on aspects of main concern to developing communities such as planning, sea level impacts, mine detection and earthquake prediction are all outlined and discussed

Freeware for GIS and Remote Sensing

OpenAIRE

Lena Halounová

2007-01-01

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.

Portable remote sensing image processing system; Kahangata remote sensing gazo shori system

Energy Technology Data Exchange (ETDEWEB)

Fujikawa, S; Uchida, K; Tanaka, S; Jingo, H [Dowa Engineering Co. Ltd., Tokyo (Japan); Hato, M [Earth Remote Sensing Data Analysis Center, Tokyo (Japan)

1997-10-22

Recently, geological analysis using remote sensing data has been put into practice due to data with high spectral resolution and high spatial resolution. There has been a remarkable increase in both software and hardware of personal computer. Software is independent of hardware due to Windows. It has become easy to develop softwares. Under such situation, a portable remote sensing image processing system coping with Window 95 has been developed. Using this system, basic image processing can be conducted, and present location can be displayed on the image in real time by linking with GPS. Accordingly, it is not required to bring printed images for the field works of image processing. This system can be used instead of topographic maps for overseas surveys. Microsoft Visual C++ ver. 2.0 is used for the software. 1 fig.

Remote sensing terminology: past experience and recent needs

Science.gov (United States)

Kancheva, Rumiana

2013-10-01

Terminology is a key issue for a better understanding among people using various languages. Terminology accuracy is essential during all phases of international cooperation. It is crucial to keep up with the latest quantitative and qualitative developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have wide and ever extending applications in various domains of human activity. The importance of the correct use of remote sensing terms refers not only to people working in this field but also to experts in many disciplines who handle remote sensing data and information products. The paper is devoted to terminology issues that refer to all aspects of remote sensing research and application areas. The attention is drawn on the recent needs and peculiarities of compiling specialized dictionaries in the subject area of remote sensing. Details are presented about the work in progress on the preparation of an English-Bulgarian dictionary of remote sensing terms focusing on Earth observations and geoinformation science. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. Any interest in cooperation and initiating of suchlike collaborative multilingual projects is welcome and highly appreciated.

Proceedings of the eighth thematic conference on geologic remote sensing

International Nuclear Information System (INIS)

Balmer, M.L.; Lange, F.F.; Levi, C.G.

1991-01-01

These proceedings contain papers presented at the Eighth Thematic Conference on Geologic Remote Sensing. This meeting was held April 29-May 2, 1991, in Denver, Colorado, USA. The conference was organized by the Environmental Research Institute of Michigan, in Cooperation with an international program committee composed primarily of geologic remote sensing specialists. The meeting was convened to discuss state-of-the-art exploration, engineering, and environmental applications of geologic remote sensing as well as research and development activities aimed at increasing the future capabilities of this technology. The presentations in these volumes address the following topics: Spectral Geology; U.S. and International Hydrocarbon Exploration; Radar and Thermal Infrared Remote Sensing; Engineering Geology and Hydrogeology; Minerals Exploration; Remote Sensing for Marine and Environmental Applications; Image Processing and Analysis; Geobotanical Remote Sensing; Data Integration and Geographic Information Systems

A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods

Directory of Open Access Journals (Sweden)

Elahe Akbari

2017-12-01

Full Text Available Oceans/Seas are important components of Earth that are affected by global warming and climate change. Recent studies have indicated that the deeper oceans are responsible for climate variability by changing the Earth’s ecosystem; therefore, assessing them has become more important. Remote sensing can provide sea surface data at high spatial/temporal resolution and with large spatial coverage, which allows for remarkable discoveries in the ocean sciences. The deep layers of the ocean/sea, however, cannot be directly detected by satellite remote sensors. Therefore, researchers have examined the relationships between salinity, height, and temperature of the oceans/Seas to estimate their subsurface water temperature using dynamical models and model-based data assimilation (numerical based and statistical approaches, which simulate these parameters by employing remotely sensed data and in situ measurements. Due to the requirements of comprehensive perception and the importance of global warming in decision making and scientific studies, this review provides comprehensive information on the methods that are used to estimate ocean/sea subsurface water temperature from remotely and non-remotely sensed data. To clarify the subsurface processes, the challenges, limitations, and perspectives of the existing methods are also investigated.

Remote Sensing Image in the Application of Agricultural Tourism Planning

Directory of Open Access Journals (Sweden)

Guojing Fan

2013-06-01

Full Text Available This paper introduces the processing technology of high resolution remote sensing image, the specific making process of tourism map and different remote sensing data in the key application of tourism planning and so on. Remote sensing extracts agricultural tourism planning information, improving the scientificalness and operability of agricultural tourism planning. Therefore remote sensing image in the application of agricultural tourism planning will be the inevitable trend of tourism development.

Coastal remote sensing – towards integrated coastal research and management

CSIR Research Space (South Africa)

Lück-Vogel, Melanie

2012-10-01

Full Text Available coastal resources and anthropogenic infrastructure for a safer future. What is the role of remote sensing? The coastal zone connects terrestrial biophysical systems with marine systems. Some marine ecosystems cannot function without intact inland... for the development of sound integrated management solutions. To date, however, remote sensing applications usually focus on areas landward from the highwater line (?terrestrial? remote sensing), while ?marine? remote sensing does not pay attention to the shallow...

Forest structural assessment using remote sensing technologies: an ...

African Journals Online (AJOL)

-Natal and MONDI Business Paper have recently embarked on a remote sensing cooperative. The primary focus of this cooperative is to explore the potential benefits associated with using remote sensing for forestry-related activities.

The HydroColor App: Above Water Measurements of Remote Sensing Reflectance and Turbidity Using a Smartphone Camera

Science.gov (United States)

Leeuw, Thomas; Boss, Emmanuel

2018-01-01

HydroColor is a mobile application that utilizes a smartphone’s camera and auxiliary sensors to measure the remote sensing reflectance of natural water bodies. HydroColor uses the smartphone’s digital camera as a three-band radiometer. Users are directed by the application to collect a series of three images. These images are used to calculate the remote sensing reflectance in the red, green, and blue broad wavelength bands. As with satellite measurements, the reflectance can be inverted to estimate the concentration of absorbing and scattering substances in the water, which are predominately composed of suspended sediment, chlorophyll, and dissolved organic matter. This publication describes the measurement method and investigates the precision of HydroColor’s reflectance and turbidity estimates compared to commercial instruments. It is shown that HydroColor can measure the remote sensing reflectance to within 26% of a precision radiometer and turbidity within 24% of a portable turbidimeter. HydroColor distinguishes itself from other water quality camera methods in that its operation is based on radiometric measurements instead of image color. HydroColor is one of the few mobile applications to use a smartphone as a completely objective sensor, as opposed to subjective user observations or color matching using the human eye. This makes HydroColor a powerful tool for crowdsourcing of aquatic optical data. PMID:29337917

The HydroColor App: Above Water Measurements of Remote Sensing Reflectance and Turbidity Using a Smartphone Camera.

Science.gov (United States)

Leeuw, Thomas; Boss, Emmanuel

2018-01-16

HydroColor is a mobile application that utilizes a smartphone's camera and auxiliary sensors to measure the remote sensing reflectance of natural water bodies. HydroColor uses the smartphone's digital camera as a three-band radiometer. Users are directed by the application to collect a series of three images. These images are used to calculate the remote sensing reflectance in the red, green, and blue broad wavelength bands. As with satellite measurements, the reflectance can be inverted to estimate the concentration of absorbing and scattering substances in the water, which are predominately composed of suspended sediment, chlorophyll, and dissolved organic matter. This publication describes the measurement method and investigates the precision of HydroColor's reflectance and turbidity estimates compared to commercial instruments. It is shown that HydroColor can measure the remote sensing reflectance to within 26% of a precision radiometer and turbidity within 24% of a portable turbidimeter. HydroColor distinguishes itself from other water quality camera methods in that its operation is based on radiometric measurements instead of image color. HydroColor is one of the few mobile applications to use a smartphone as a completely objective sensor, as opposed to subjective user observations or color matching using the human eye. This makes HydroColor a powerful tool for crowdsourcing of aquatic optical data.

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

Science.gov (United States)

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

2017-12-01

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

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.

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.

Chlorophyll-a Concentration Retrieval in the Optically Complex Waters of the St. Lawrence Estuary and Gulf Using Principal Component Analysis

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Julien Laliberté

2018-02-01

Full Text Available Empirical methods based on band ratios to infer chlorophyll-a concentration by satellite do not perform well over the optically complex waters of the St. Lawrence Estuary and Gulf. Using a dataset of 93 match-ups, we explore an alternative method relying on empirical orthogonal functions (EOF to develop an algorithm that relates the satellite-derived remote sensing reflectances to in situ chlorophyll-a concentration for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS. Results show that an accuracy of 41% at retrieving chlorophyll-a concentration can be reached using the EOF method compared to 140% for the widely-used Ocean Chlorophyll 4 (OC4v4 empirical algorithm, 53% for the Garver-Siegel-Maritorena (GSM01 and 54% for the Generalized Inherent Optical Property (GIOP semi-analytical algorithms. This result is possible because the EOF approach is able to extract region-specific radiometric features from the satellite remote sensing reflectances that are related to absorption properties of optical components (water, coloured dissolved organic matter and chlorophyll-a using the visible SeaWiFS channels. The method could easily be used with other ocean-colour satellite sensors (e.g., MODIS, MERIS, VIIRS, OLCI to extend the time series for the St. Lawrence Estuary and Gulf waters.

Remote sensing programs and courses in engineering and water resources

Science.gov (United States)

Kiefer, R. W.

1981-01-01

The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

Project THEMIS: A Center for Remote Sensing.

Science.gov (United States)

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

Remote sensing and eLearning 2.0 for school education

Science.gov (United States)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2010-10-01

The "Remote Sensing in Schools" project aims at improving the integration of "Satellite remote sensing" into school teaching. Therefore, it is the project's overall objective to teach students in primary and secondary schools the basics and fields of application of remote sensing. Existing results show that many teachers are interested in remote sensing and at same time motivated to integrate it into their teaching. Despite the good intention, in the end, the implementation often fails due to the complexity and poor set-up of the information provided. Therefore, a comprehensive and well-structured learning platform on the topic of remote sensing is developed. The platform shall allow a structured introduction to the topic.

POLARIMETRIC REMOTE SENSING OF ATMOSPHERIC PARTICULATE POLLUTANTS

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Z. Li

2018-04-01

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

Identifying Distribution of Chlorophyll-a Concentration Using Landsat 8 OLI on Marine Waters Area of Cirebon

Science.gov (United States)

Buditama, Gilang; Damayanti, Astrid; Giok Pin, Tjiong

2017-12-01

Phytoplankton is a microscopic plant that has a function to produces oxygen and organic substances. It also plays a role as a main producer in the food chain of a marine ecosystem. Chlorophyll-a is a colour pigment most common in phytoplankton species, so that the concentration level of chlorophyll-a can be used as an indicator of the abundance of phytoplankton cells, and as a reference for predicting organic potency in the aquatic area. This research discusses about the spatial and temporal distribution of chlorophyll-a and its correlation with salinity and total suspended solid (TSS), in the seawaters of Cirebon, West Java. The goal of this research is to be a source of information for fishermen, and other stakeholders whose related subjects in the field of marine and fisheries to predict fertile water regions and can also be used as an indicator in discovering potential areas to catch pelagic fish in Cirebon seawaters. Chlorophyll-a concentration, salinity, and TSS are identified using remote sensing data such as Landsat-8 OLI multi temporal images according to dry and wet month parameters in the 2014-2015. The results of the processed image are then validated between in-situ measurements in the field and remote sensing imagery at the same time. This research utilizes descriptive analysis, and statistics with spatial approach. The results of the research show that temporally, chlorophyll-a levels have a tendency to be higher in wet months compared to dry months, while chlorophyll-a is higher in areas near the coastline compared to open sea areas. The distribution of chlorophyll-a concentration is affected by salinity and TSS distribution, where salinity has the negative relationship and TSS has the positive relationship with chlorophyll-a distribution.

Review of Remote Sensing Needs and Applications in Africa

Science.gov (United States)

Brown, Molly E.

2007-01-01

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

Economic optimization and evolutionary programming when using remote sensing data

OpenAIRE

Shamin Roman; Alberto Gabriel Enrike; Uryngaliyeva Ayzhana; Semenov Aleksandr

2018-01-01

The article considers the issues of optimizing the use of remote sensing data. Built a mathematical model to describe the economic effect of the use of remote sensing data. It is shown that this model is incorrect optimisation task. Given a numerical method of solving this problem. Also discusses how to optimize organizational structure by using genetic algorithm based on remote sensing. The methods considered allow the use of remote sensing data in an optimal way. The proposed mathematical m...

The Potential and Uptake of Remote Sensing in Insurance: A Review

Directory of Open Access Journals (Sweden)

Jan de Leeuw

2014-11-01

Full Text Available Global insurance markets are vast and diverse, and may offer many opportunities for remote sensing. To date, however, few operational applications of remote sensing for insurance exist. Papers claiming potential application of remote sensing typically stress the technical possibilities, without considering its contribution to customer value for the insured or to the profitability of the insurance industry. Based on a systematic search of available literature, this review investigates the potential and actual support of remote sensing to the insurance industry. The review reveals that research on remote sensing in classical claim-based insurance described in the literature revolve around crop damage and flood and fire risk assessment. Surprisingly, the use of remote sensing in claim-based insurance appears to be instigated by government rather than the insurance industry. In contrast, insurance companies are offering various index insurance products that are based on remote sensing. For example, remotely sensed index insurance for rangelands and livestock are operational, while various applications in crop index insurance are being considered or under development. The paper discusses these differences and concludes that there is particular scope for application of remote sensing by the insurance industry in index insurance because (1 indices can be constructed that correlate well with what is insured; (2 these indices can be delivered at low cost; and (3 it opens up new markets that are not served by claim-based insurance. The paper finally suggests that limited adoption of remote sensing in insurance results from a lack of mutual understanding and calls for greater cooperation between the insurance industry and the remote sensing community.

Photogrammetry and remote sensing education subjects

Science.gov (United States)

Lazaridou, Maria A.; Karagianni, Aikaterini Ch.

2017-09-01

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

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.

Application of remote sensing in aquatic ecosystems

Science.gov (United States)

Yousef, Foad

I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll alpha and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.

Preliminary results of fisheries investigation associated with Skylab-3. [remotely sensed distribution and abundance of gamefish in Gulf of Mexico

Science.gov (United States)

Savastano, K. J. (Principal Investigator); Pastula, E. J., Jr.; Woods, G.; Faller, K.

1974-01-01

The author has identified the following significant results. This investigation is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area in the northeastern Gulf of Mexico has made possible the identification of fisheries significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature, and turbidity have been inferred from aircraft sensor data. Cloud cover and delayed receipt have inhibited the use of Skylab data. The first step toward establishing the feasibility of utilizing remotely sensed data to assess amd monitor the distribution of ocean gamefish has been taken with the successful identification of fisheries significant oceanographic parameters and the demonstration of the capability of measuring most of these parameters remotely.

ESA remote-sensing programme - Present activities and future plans

Energy Technology Data Exchange (ETDEWEB)

Plevin, J [ESA, Directorate of Planning and Future Programmes, Paris, France; Pryke, I [ESA, Directorate of Applications Programmes, Toulouse, France

1979-02-01

The present activities and future missions of the ESA program of spaceborne remote sensing of earth resources and environment are discussed. Program objectives have been determined to be the satisfaction of European regional needs by agricultural, land use, water resources, coastal and polar surveys, and meeting the requirements of developing nations in the areas of agricultural production, mineral exploration and disaster warning and assessment. The Earthnet system of data processing centers presently is used for the distribution of remote sensing data acquired by NASA satellites. Remote sensing experiments to be flown aboard Spacelab are the Metric Camera, to test high resolution mapping capabilities of a large format camera, and the Microwave Remote-Sensing Experiment, which operates as a two-frequency scatterometer, a synthetic aperture radar and a passive microwave radiometer. Studies carried out on the definition of future remote sensing satellite systems are described, including studies of system concepts for land applications and coastal monitoring satellites.

Remote sensing by satellite - Technical and operational implications for international cooperation

Science.gov (United States)

Doyle, S. E.

1976-01-01

International cooperation in the U.S. Space Program is discussed and related to the NASA program for remote sensing of the earth. Satellite remote sensing techniques are considered along with the selection of the best sensors and wavelength bands. The technology of remote sensing satellites is considered with emphasis on the Landsat system configuration. Future aspects of remote sensing satellites are considered.

RSComPro: An Open Communication Protocol for Remote Sensing Systems

DEFF Research Database (Denmark)

Vasiljevic, Nikola; Trujillo, Juan-José

The remote sensing protocol (RSComPro) is a communication protocol, which has been developed for controlling multiple remote sensing systems simultaneously through a UDP/IP and TPC/IP network. This protocol is meant to be open to the remote sensing community. The scope is the implementation of so...

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

Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data

Directory of Open Access Journals (Sweden)

Wei Tu

2018-01-01

Full Text Available Portraying urban functional zones provides useful insights into understanding complex urban systems and establishing rational urban planning. Although several studies have confirmed the efficacy of remote sensing imagery in urban studies, coupling remote sensing and new human sensing data like mobile phone positioning data to identify urban functional zones has still not been investigated. In this study, a new framework integrating remote sensing imagery and mobile phone positioning data was developed to analyze urban functional zones with landscape and human activity metrics. Landscapes metrics were calculated based on land cover from remote sensing images. Human activities were extracted from massive mobile phone positioning data. By integrating them, urban functional zones (urban center, sub-center, suburbs, urban buffer, transit region and ecological area were identified by a hierarchical clustering. Finally, gradient analysis in three typical transects was conducted to investigate the pattern of landscapes and human activities. Taking Shenzhen, China, as an example, the conducted experiment shows that the pattern of landscapes and human activities in the urban functional zones in Shenzhen does not totally conform to the classical urban theories. It demonstrates that the fusion of remote sensing imagery and human sensing data can characterize the complex urban spatial structure in Shenzhen well. Urban functional zones have the potential to act as bridges between the urban structure, human activity and urban planning policy, providing scientific support for rational urban planning and sustainable urban development policymaking.

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...

Remote sensing education in NASA's technology transfer program

Science.gov (United States)

Weinstein, R. H.

1981-01-01

Remote sensing is a principal focus of NASA's technology transfer program activity with major attention to remote sensing education the Regional Program and the University Applications Program. Relevant activities over the past five years are reviewed and perspective on future directions is presented.

Remote Sensing Terminology in a Global and Knowledge-Based World

Science.gov (United States)

Kancheva, Rumiana

The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy

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

Retrieval operators of remote sensing applications

International Nuclear Information System (INIS)

Ahmad, T.; Shah, A.

2014-01-01

A set of operators of remote sensing applications have been proposed to fulfill most of the Functional Requirements (FR). These operators capture the functions of the applications, which can be considered as the services provided by the applications. In general, a good application meets maximum FR from user. In this paper, we have defined a remote sensing application by a set, having all images created at dissimilar time instances, and each image is categorized into set of different layers. (author)

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.

Remote sensing of canopy nitrogen at regional scale in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index

Science.gov (United States)

Loozen, Yasmina; Rebel, Karin T.; Karssenberg, Derek; Wassen, Martin J.; Sardans, Jordi; Peñuelas, Josep; De Jong, Steven M.

2018-05-01

Canopy nitrogen (N) concentration and content are linked to several vegetation processes. Therefore, canopy N concentration is a state variable in global vegetation models with coupled carbon (C) and N cycles. While there are ample C data available to constrain the models, widespread N data are lacking. Remotely sensed vegetation indices have been used to detect canopy N concentration and canopy N content at the local scale in grasslands and forests. Vegetation indices could be a valuable tool to detect canopy N concentration and canopy N content at larger scale. In this paper, we conducted a regional case-study analysis to investigate the relationship between the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) time series from European Space Agency (ESA) Envisat satellite at 1 km spatial resolution and both canopy N concentration (%N) and canopy N content (N g m-2, of ground area) from a Mediterranean forest inventory in the region of Catalonia, in the northeast of Spain. The relationships between the datasets were studied after resampling both datasets to lower spatial resolutions (20, 15, 10 and 5 km) and at the original spatial resolution of 1 km. The results at higher spatial resolution (1 km) yielded significant log-linear relationships between MTCI and both canopy N concentration and content: r2 = 0.32 and r2 = 0.17, respectively. We also investigated these relationships per plant functional type. While the relationship between MTCI and canopy N concentration was strongest for deciduous broadleaf and mixed plots (r2 = 0.24 and r2 = 0.44, respectively), the relationship between MTCI and canopy N content was strongest for evergreen needleleaf trees (r2 = 0.19). At the species level, canopy N concentration was strongly related to MTCI for European beech plots (r2 = 0.69). These results present a new perspective on the application of MTCI time series for canopy N detection.

CYBERNETIC BASIS AND SYSTEM PRACTICE OF REMOTE SENSING AND SPATIAL INFORMATION SCIENCE

Directory of Open Access Journals (Sweden)

X. Tan

2017-09-01

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

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

Science.gov (United States)

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

2017-09-01

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

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes

DEFF Research Database (Denmark)

Bøgh, Eva; Houborg, R; Bienkowski, J

2013-01-01

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and they play a significant role in the global cycles of carbon, nitrogen and water. Remote sensing data from satellites can be used to estimate leaf area index (LAI), leaf......). Predictabilities of SVIs and REGFLEC simulations generally improved when constrained to single land use categories (wheat, maize, barley, grass) across the European landscapes, reflecting sensitivity to canopy structures. Predictability further improved when constrained to local (10 × 10 km2) landscapes, thereby...

Use of Remote Sensing for Decision Support in Africa

Science.gov (United States)

Policelli, Frederick S.

2007-01-01

Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

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

Some problems on remote sensing geology for uranium prospecting

International Nuclear Information System (INIS)

Yang Tinghuai.

1988-01-01

Remote sensing is a kind of very effective method which can be used in all stages of geological prospecting. Geological prospecting with remote sensing method must be based on different genetic models of ore deposits, characteristics of geology-landscape and comprehensive analysis for geophysical and geochemical data, that is, by way of conceptual model prospecting. The prospecting results based on remote sensing geology should be assessed from three aspects such as direct, indirect and potential ones

An Integrated Field and Hyperspectral Remote Sensing Method for the Estimation of Pigments Content of Stipa Purpurea in Shenzha, Tibet

Directory of Open Access Journals (Sweden)

Bo Kong

2017-01-01

Full Text Available Stipa purpurea is the representative type of alpine grassland in Tibet and the surviving and development material for herdsmen. This paper takes Shenzha County as the research area. Based on the analysis of typical hyperspectral variables sensitive to chlorophyll content of Stipa purpurea, 10 spectral variables with significant correlation with chlorophyll were extracted. The estimation model of chlorophyll was established. The photosynthetic pigment contents in the Shenzha area were calculated by using HJ-1A remote sensing images. The results show that (1 there are significant correlations between chlorophyll content and spectral variables; in particular, the coefficient of Chlb in Stipa purpurea with RVI is the largest (0.728; (2 10 variables are correlated with chlorophyll, and the order of correlation is Chlb > Chla > Chls; (3 for the estimation of Chla, the EVI is the best variable. RVI, NDVI, and VI2 are suitable for Chlb; RVI and NDVI are also suitable for the estimation of Chls; (4 the mean estimated content of Chla in Stipa bungeana is about 4.88 times that of Chlb, while Cars is slightly more than Chlb; (5 the distribution of Chla is opposite to Chlb and Chls content in water area.

Multi- and hyperspectral geologic remote sensing: A review

Science.gov (United States)

van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie

2012-02-01

Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly

Bayesian object-based estimation of LAI and chlorophyll from a simulated Sentinel-2 top-of-atmosphere radiance image

NARCIS (Netherlands)

Laurent, V.C.E.; Schaepman, M.E.; Verhoef, W.; Weyermann, J.; Chavez Oyanadel, R.O.

2014-01-01

Leaf area index (LAI) and chlorophyll content (Cab) are important vegetation variables which can be monitored using remote sensing (RS). Physically-based approaches have higher transferability and are therefore better suited than empirically-based approaches for estimating LAI and Cab at global

Opportunities for Increasing Societal Value of Remote Sensing Data ...

African Journals Online (AJOL)

Opportunities for Increasing Societal Value of Remote Sensing Data in South Africa's Strategic Development Priorities: A Review. ... Despite the enormous capital required to fund remote sensing initiatives, governments ... HOW TO USE AJOL.

Assessing the accuracy of remote sensing techniques in vegetation ...

African Journals Online (AJOL)

Assessing the accuracy of remote sensing techniques in vegetation fractions estimation. ... This study aimed at exploring different remote sensing (RS) techniques for quantitatively measuring vegetation and bare soil ... HOW TO USE AJOL.

Mapping Water Use and Drought with Satellite Remote Sensing

OpenAIRE

Anderson, Martha

2014-01-01

Mapping water use and drought with satellite remote sensing. Martha C. Anderson, Bill Kustas, Feng Gao, Kate Semmens. USDA-Agricultural Research Service Hydrology and Remote Sensing Laboratory, Beltsville, MD. Chris Hain NOAA-NESDIS

Remote sensing of land surface phenology

Science.gov (United States)

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

2014-01-01

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

Development of airborne remote sensing data assimilation system

International Nuclear Information System (INIS)

Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

2014-01-01

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

Popularization of remote sensing education and general course construction in undergraduate education

International Nuclear Information System (INIS)

Wang, Jing'ai; Sheng, Zhongyao; Yu, Han

2014-01-01

The construction of a course focused on remote sensing is important because it cultivates college students' geographic abilities and popularizes remote sensing technology. Using internet datasets, this article compares data from general undergraduate courses at almost 100 universities located in the United States and China with 3 years of experimental teaching data from the general undergraduate ''Remote sensing Region'' course at Beijing Normal University. The comparison focuses on curricular concepts, course content, website construction and the popularity of the remote sensing topic. Our research shows that the ''remote sensing region'' course can promote the geographic abilities of college students by popularizing remote sensing observation technology. The course can improve the overall quality of college students by breaking major barriers, and it can promote global and national consciousness by presenting material with global and regional relevancy. Remote sensing imaging has become known as the third most intuitive geographic language after text and maps. The general remote sensing course have the three following developmental qualities: interdisciplinarity, popularization and internationalization

Remote sensing and change detection in rangelands | Palmer ...

African Journals Online (AJOL)

To most land managers, remote sensing has remained illusive, seldom allowing the manager to use it to its full potential. In contrast, the policy maker, backed by GIS laboratories and remote sensing specialists, is confronted by plausible scenarios of degradation and transformation. After intervening, he is seldom active long ...

Research on active imaging information transmission technology of satellite borne quantum remote sensing

Science.gov (United States)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

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.

Remote Sensing Image Registration Using Multiple Image Features

Directory of Open Access Journals (Sweden)

Kun Yang

2017-06-01

Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

Use of Openly Available Satellite Images for Remote Sensing Education

Science.gov (United States)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

Searches over graphs representing geospatial-temporal remote sensing data

Science.gov (United States)

Brost, Randolph; Perkins, David Nikolaus

2018-03-06

Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

Landsat's role in ecological applications of remote sensing.

Science.gov (United States)

Warren B. Cohen; Samuel N. Goward

2004-01-01

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

Integrated remotely sensed datasets for disaster management

Science.gov (United States)

McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

2008-10-01

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

Remote sensing applications for the dam industry

Energy Technology Data Exchange (ETDEWEB)

Pryse-Phillips, A.; Woolgar, R. [Hatch Ltd., St. John' s, NL (Canada); Puestow, T.; Warren, S. [Memorial Univ. of Newfoundland, St. John' s, NL (Canada). C-Core; Rogers, K. [Nalcor Energy, St. John' s, NL (Canada); Khan, A. [Government of Newfoundland and Labrador, St. Johns, NL (Canada)

2009-07-01

There has been an increase in the earth observation missions providing satellite imagery for operational monitoring applications. This technique has been found to be especially useful for the surveillance of large, remote areas, which is challenging to achieve in a cost-effective manner by conventional field-based or aerial means. This paper discussed the utility of satellite-based monitoring for different applications relevant to hydrology and water resources management. Emphasis was placed on the monitoring of river ice covers in near, real-time and water resources management. The paper first outlined river ice monitoring using remote sensing on the Lower Churchill River. The benefits of remote sensing over traditional survey methods for the dam industry was then outlined. Satellite image acquisition and interpretation for the Churchill River was then presented. Several images were offered. Watershed physiographic characterization using remote sensing was also described. It was concluded that satellite imagery proved to be a useful tool to develop physiographic characteristics when conducting rainfall-runoff modelling. 3 refs., 1 tab., 11 figs.

REMOTE SENSING FOR ENVIRONMENTAL COMPLIANCE MONITORING

Science.gov (United States)

I. Remote Sensing Basics A. The electromagnetic spectrum demonstrates what we can see both in the visible and beyond the visible part of the spectrum through the use of various types of sensors. B. Resolution refers to what a remote sensor can see and how often. 1. Sp...

Geological remote sensing

Science.gov (United States)

Bishop, Charlotte; Rivard, Benoit; de Souza Filho, Carlos; van der Meer, Freek

2018-02-01

Geology is defined as the 'study of the planet Earth - the materials of which it is made, the processes that act on these materials, the products formed, and the history of the planet and its life forms since its origin' (Bates and Jackson, 1976). Remote sensing has seen a number of variable definitions such as those by Sabins and Lillesand and Kiefer in their respective textbooks (Sabins, 1996; Lillesand and Kiefer, 2000). Floyd Sabins (Sabins, 1996) defined it as 'the science of acquiring, processing and interpreting images that record the interaction between electromagnetic energy and matter' while Lillesand and Kiefer (Lillesand and Kiefer, 2000) defined it as 'the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation'. Thus Geological Remote Sensing can be considered the study of, not just Earth given the breadth of work undertaken in planetary science, geological features and surfaces and their interaction with the electromagnetic spectrum using technology that is not in direct contact with the features of interest.

A NDVI assisted remote sensing image adaptive scale segmentation method

Science.gov (United States)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Remote Sensing of shallow sea floor for digital earth environment

International Nuclear Information System (INIS)

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

2014-01-01

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

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...

Subsurface remote sensing

International Nuclear Information System (INIS)

Schweitzer, Jeffrey S.; Groves, Joel L.

2002-01-01

Subsurface remote sensing measurements are widely used for oil and gas exploration, for oil and gas production monitoring, and for basic studies in the earth sciences. Radiation sensors, often including small accelerator sources, are used to obtain bulk properties of the surrounding strata as well as to provide detailed elemental analyses of the rocks and fluids in rock pores. Typically, instrument packages are lowered into a borehole at the end of a long cable, that may be as long as 10 km, and two-way data and instruction telemetry allows a single radiation instrument to operate in different modes and to send the data to a surface computer. Because these boreholes are often in remote locations throughout the world, the data are frequently transmitted by satellite to various locations around the world for almost real-time analysis and incorporation with other data. The complete system approach that permits rapid and reliable data acquisition, remote analysis and transmission to those making decisions is described

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.

Forest biodiversity and its assessment by remote sensing

International Nuclear Information System (INIS)

Innes, J.L.; Koch, B.

1998-01-01

Several international conventions and agreements have stressed the importance of the assessment of forest biodiversity. However, the methods by which such assessments can be made remain unclear. Remote sensing represents an important tool for looking at ecosystem diversity and various structural aspects of individual ecosystems. It provides a means to make assessments across several different spatial scales, and is also critical for assessments of changes in ecosystem pattern over time. Many different forms of remote sensing are available. While lately the emphasis on laser scanner and synthetic aperture radar data has increased, most work to date has used photographs and digital optical imagery, primarily from airborne and spaceborne platforms. These provide the opportunity to assess different phenomena from the landscape to the stand scale. Remote sensing provides the most efficient tool available for determining landscape-scale elements of forest biodiversity, such as the relative proportion of matrix and patches and their physical arrangement. At intermediate scales, remote sensing provides an ideal tool for evaluating the presence of corridors and the nature of edges. At the stand scale, remote sensing technologies are likely to deliver an increasing amount of information about the structural attributes of forest stands, such as the nature of the canopy surface, the presence of layering within the canopy and presence of (very) coarse woody debris on the forest floor. Given the rate of development in the technology, even greater usage is likely in the future. (author)

What is a picture worth? A history of remote sensing

Science.gov (United States)

Moore, Gerald K.

1979-01-01

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

Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

International Nuclear Information System (INIS)

Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

1993-01-01

Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI's obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics

Remote sensing for the geobotanical and biogeochemical assessment of environmental contamination

Energy Technology Data Exchange (ETDEWEB)

Wickham, J.; Chesley, M.; Lancaster, J.; Mouat, D.

1993-01-01

Under Contract Number DE-AC08-90NV10845, the DOE has funded the Desert Research Institute (DRI) to examine several aspects of remote sensing, specifically with respect to how its use might help support Environmental Restoration and Waste Management (ERWM) activities at DOE sites located throughout the country. This report represents partial fulfillment of DRI`s obligations under that contract and includes a review of relevant literature associated with remote sensing studies and our evaluation and recommendation as to the applicability of various remote sensing techniques for DOE needs. With respect to DOE ERWM activities, remote sensing may be broadly defined as collecting information about a target without actually being in physical contact with the object. As the common platforms for remote sensing observations are aircraft and satellites, there exists the possibility to rapidly and efficiently collect information over DOE sites that would allow for the identification and monitoring of contamination related to present and past activities. As DOE sites cover areas ranging from tens to hundreds of square miles, remote sensing may provide an effective, efficient, and economical method in support of ERWM activities. For this review, remote sensing has been limited to methods that employ electromagnetic (EM) energy as the means of detecting and measuring target characteristics.

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...

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)

1999 IEEE international geoscience and remote sensing symposium

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-07-01

The theme of IGARSS'99, ``Remote Sensing of the System Earth--A Challenge for the 21st Century,'' shows how earth observation based on satellite remote sensing can significantly contribute to the future study of the environment and the changes it is undergoing, whether from natural causes or human activities. The wide range of topics offers an interdisciplinary approach and suggests integrated techniques and theory in remote sensing are essential for modeling and understanding the environment. Topics covered include: new instrumentation and future systems; high resolution SAR/InSAR; earth system science educational initiative; data fusion; radar sensing of ice sheets; image processing techniques; clouds and ice particles; internal waves; natural hazards and disaster monitoring; advanced passive and active sensors and sensor calibration; radar assessment of rain, oil spills and natural slicks; data standards and distribution; and vegetation monitoring using BRDF approaches.

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.

Spatial Autocorrelation and Uncertainty Associated with Remotely-Sensed Data

Directory of Open Access Journals (Sweden)

Daniel A. Griffith

2016-06-01

Full Text Available Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pixels in realistically-sized remotely-sensed images, a situation that more recently has changed. Recent advances in spatial statistical estimation theory support the extraction of information and the distilling of knowledge from remotely-sensed images in a way that accounts for latent spatial autocorrelation. This paper summarizes an effective methodological approach to achieve this end, illustrating results with a 2002 remotely sensed-image of the Florida Everglades, and simulation experiments. Specifically, uncertainty of spatial autocorrelation parameter in a spatial autoregressive model is modeled with a beta-beta mixture approach and is further investigated with three different sampling strategies: coterminous sampling, random sub-region sampling, and increasing domain sub-regions. The results suggest that uncertainty associated with remotely-sensed data should be cast in consideration of spatial autocorrelation. It emphasizes that one remaining challenge is to better quantify the spatial variability of spatial autocorrelation estimates across geographic landscapes.

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.

Methods of training the graduate level and professional geologist in remote sensing technology

Science.gov (United States)

Kolm, K. E.

1981-01-01

Requirements for a basic course in remote sensing to accommodate the needs of the graduate level and professional geologist are described. The course should stress the general topics of basic remote sensing theory, the theory and data types relating to different remote sensing systems, an introduction to the basic concepts of computer image processing and analysis, the characteristics of different data types, the development of methods for geological interpretations, the integration of all scales and data types of remote sensing in a given study, the integration of other data bases (geophysical and geochemical) into a remote sensing study, and geological remote sensing applications. The laboratories should stress hands on experience to reinforce the concepts and procedures presented in the lecture. The geologist should then be encouraged to pursue a second course in computer image processing and analysis of remotely sensed data.

Remote sensing technology: symposium proceedings

International Nuclear Information System (INIS)

1985-01-01

Papers were presented in four subject areas: applications of remote sensing; data analysis, digital and analog; acquisition systems; and general. Abstracts of individual items from the conference were prepared separately for the data base

Ground based remote sensing and physiological measurements provide novel insights into canopy photosynthetic optimization in arctic shrubs

Science.gov (United States)

Magney, T. S.; Griffin, K. L.; Boelman, N.; Eitel, J.; Greaves, H.; Prager, C.; Logan, B.; Oliver, R.; Fortin, L.; Vierling, L. A.

2014-12-01

Because changes in vegetation structure and function in the Arctic are rapid and highly dynamic phenomena, efforts to understand the C balance of the tundra require repeatable, objective, and accurate remote sensing methods for estimating aboveground C pools and fluxes over large areas. A key challenge addressing the modelling of aboveground C is to utilize process-level information from fine-scale studies. Utilizing information obtained from high resolution remote sensing systems could help to better understand the C source/sink strength of the tundra, which will in part depend on changes in photosynthesis resulting from the partitioning of photosynthetic machinery within and among deciduous shrub canopies. Terrestrial LiDAR and passive hyperspectral remote sensing measurements offer an effective, repeatable, and scalable method to understand photosynthetic performance and partitioning at the canopy scale previously unexplored in arctic systems. Using a 3-D shrub canopy model derived from LiDAR, we quantified the light regime of leaves within shrub canopies to gain a better understanding of how light interception varies in response to the Arctic's complex radiation regime. This information was then coupled with pigment sampling (i.e., xanthophylls, and Chl a/b) to evaluate the optimization of foliage photosynthetic capacity within shrub canopies due to light availability. In addition, a lab experiment was performed to validate evidence of canopy level optimization via gradients of light intensity and leaf light environment. For this, hyperspectral reflectance (photochemical reflectance index (PRI)), and solar induced fluorescence (SIF)) was collected in conjunction with destructive pigment samples (xanthophylls) and chlorophyll fluorescence measurements in both sunlit and shaded canopy positions.

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.

Ontology-based classification of remote sensing images using spectral rules

Science.gov (United States)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

Directory of Open Access Journals (Sweden)

Peng Liang

2017-12-01

Full Text Available Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1 remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.

Remote-sensing image encryption in hybrid domains

Science.gov (United States)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

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

Noninvasive Remote Sensing Techniques for Infrastructures Diagnostics

Directory of Open Access Journals (Sweden)

Angelo Palombo

2011-01-01

Full Text Available The present paper aims at analyzing the potentialities of noninvasive remote sensing techniques used for detecting the conservation status of infrastructures. The applied remote sensing techniques are ground-based microwave radar interferometer and InfraRed Thermography (IRT to study a particular structure planned and made in the framework of the ISTIMES project (funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme. To exploit the effectiveness of the high-resolution remote sensing techniques applied we will use the high-frequency thermal camera to measure the structures oscillations by high-frequency analysis and ground-based microwave radar interferometer to measure the dynamic displacement of several points belonging to a large structure. The paper describes the preliminary research results and discusses on the future applicability and techniques developments for integrating high-frequency time series data of the thermal imagery and ground-based microwave radar interferometer data.

Physical control of interannual variations of the winter chlorophyll bloom in the northern Arabian Sea

Directory of Open Access Journals (Sweden)

M. G. Keerthi

2017-08-01

Full Text Available The northern Arabian Sea hosts a winter chlorophyll bloom, triggered by convective overturning in response to cold and dry northeasterly monsoon winds. Previous studies of interannual variations of this bloom only relied on a couple of years of data and reached no consensus on the associated processes. The current study aims at identifying these processes using both  ∼  10 years of observations (including remotely sensed chlorophyll data and physical parameters derived from Argo data and a 20-year-long coupled biophysical ocean model simulation. Despite discrepancies in the estimated bloom amplitude, the six different remotely sensed chlorophyll products analysed in this study display a good phase agreement at seasonal and interannual timescales. The model and observations both indicate that the interannual winter bloom fluctuations are strongly tied to interannual mixed layer depth anomalies ( ∼  0.6 to 0.7 correlation, which are themselves controlled by the net heat flux at the air–sea interface. Our modelling results suggest that the mixed layer depth control of the bloom amplitude ensues from the modulation of nutrient entrainment into the euphotic layer. In contrast, the model and observations both display insignificant correlations between the bloom amplitude and thermocline depth, which precludes a control of the bloom amplitude by daily dilution down to the thermocline depth, as suggested in a previous study.

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...

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.

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.

Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

Science.gov (United States)

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-01-01

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. PMID:25386759

Advanced and applied remote sensing of environmental conditions

Science.gov (United States)

Slonecker, E. Terrence; Fisher, Gary B.; Marr, David A.; Milheim, Lesley E.; Roig-Silva, Coral M.

2013-01-01

"Remote sensing” is a general term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth’s surface. Remotely sensed data are fundamental to geographic science. The U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

HYDROPT: A fast and flexible method to retrieve chlorophyll-a from multispectral satellite observations of optically complex coastal waters

NARCIS (Netherlands)

van der Woerd, H.J.; Pasterkamp, R.

2008-01-01

We present a generic innovative algorithm for remote sensing of coastal waters that can deal with a large range of concentrations of chlorophyll-a, SPM and CDOM and their inherent optical properties. The algorithm is based on the exact solutions of the HYDROLIGHT numerical radiative transfer model

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.

Classification of remotely sensed images

CSIR Research Space (South Africa)

Dudeni, N

2008-10-01

Full Text Available For this research, the researchers examine various existing image classification algorithms with the aim of demonstrating how these algorithms can be applied to remote sensing images. These algorithms are broadly divided into supervised...

To what extent can vegetation change and plant stress be surveyed by remote sensing?

Energy Technology Data Exchange (ETDEWEB)

Toemmervik, Hans

1998-12-31

Air pollution from the nickel processing industry in the Kola region of Russia accounts for a large part of the environmental problems in the north-eastern parts of Norway and Finland. The objectives of this thesis were to examine if vegetation damage and plant stress can be surveyed by remote sensing and to assess the use of chlorophyll fluorescence measurements to detect plant stress in the field. The study was carried out in the border area between Norway and Russia. Two spaceborne and one airborne sensors were used. Changes in vegetation cover could be monitored with a degree of accuracy varying from 75 to 83%. A hybrid classification method monitored changes in both lichen dominated vegetation and in vegetation cover types dominated by dwarf shrubs and green plants, which were significantly associated with the differences in SO{sub 2} emission during the period from 1973 to 1994. Vegetation indices, change detection maps and prediction maps provided information on biomass and coverage of green vegetation. This was associated with the differences in the SO{sub 2} emissions during the same period. The vegetation and land cover types with the greatest stress and damage had the largest modelled SO{sub 2} concentration levels in the ground air layer while the vegetation cover types with the lowest degree of stress had the lowest. Comparison of the airborne casi map with the previously processed Landsat TM map from the same area showed that the casi map separated the complete vegetation cover into more detail than the Landsat TM map. The casi images indicated a red-edge shift for the medium to heavily damaged vegetation cover types. Problems with using airborne remote sensing by casi include variable clouds, lack of synoptic view, and cost. The variation in chlorophyll fluorescence of 11 plant species at 16 sites was most influenced by precipitation, temperature and continentality. 373 refs., 49 figs., 37 tabs.

Remote Sensing of Irrigated Agriculture: Opportunities and Challenges

Directory of Open Access Journals (Sweden)

Chelsea Cervantes

2010-09-01

Full Text Available Over the last several decades, remote sensing has emerged as an effective tool to monitor irrigated lands over a variety of climatic conditions and locations. The objective of this review, which summarizes the methods and the results of existing remote sensing studies, is to synthesize principle findings and assess the state of the art. We take a taxonomic approach to group studies based on location, scale, inputs, and methods, in an effort to categorize different approaches within a logical framework. We seek to evaluate the ability of remote sensing to provide synoptic and timely coverage of irrigated lands in several spectral regions. We also investigate the value of archived data that enable comparison of images through time. This overview of the studies to date indicates that remote sensing-based monitoring of irrigation is at an intermediate stage of development at local scales. For instance, there is overwhelming consensus on the efficacy of vegetation indices in identifying irrigated fields. Also, single date imagery, acquired at peak growing season, may suffice to identify irrigated lands, although to multi-date image data are necessary for improved classification and to distinguish different crop types. At local scales, the mapping of irrigated lands with remote sensing is also strongly affected by the timing of image acquisition and the number of images used. At the regional and global scales, on the other hand, remote sensing has not been fully operational, as methods that work in one place and time are not necessarily transferable to other locations and periods. Thus, at larger scales, more work is required to indentify the best spectral indices, best time periods, and best classification methods under different climatological and cultural environments. Existing studies at regional scales also establish the fact that both remote sensing and national statistical approaches require further refinement with a substantial investment of

JEarth | Analytical Remote Sensing Imagery Application for Researchers and Practitioners

Science.gov (United States)

Prashad, L.; Christensen, P. R.; Anwar, S.; Dickenshied, S.; Engle, E.; Noss, D.

2009-12-01

The ASU 100 Cities Project and the ASU Mars Space Flight Facility (MSFF) present JEarth, a set of analytical Geographic Information System (GIS) tools for viewing and processing Earth-based remote sensing imagery and vectors, including high-resolution and hyperspectral imagery such as TIMS and MASTER. JEarth is useful for a wide range of researchers and practitioners who need to access, view, and analyze remote sensing imagery. JEarth stems from existing MSFF applications: the Java application JMars (Java Mission-planning and Analysis for Remote Sensing) for viewing and analyzing remote sensing imagery and THMPROC, a web-based, interactive tool for processing imagery to create band combinations, stretches, and other imagery products. JEarth users can run the application on their desktops by installing Java-based open source software on Windows, Mac, or Linux operating systems.

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

Science.gov (United States)

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

2012-12-01

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

Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications

Science.gov (United States)

Hunt, E. Raymond; Daughtry, Craig S.T.; Mirsky, Steven B.; Hively, W. Dean

2014-01-01

An important application of unmanned aircraft systems (UAS) may be remote-sensing for precision agriculture, because of its ability to acquire images with very small pixel sizes from low altitude flights. The objective of this study was to compare information obtained from two different pixel sizes, one about a meter (the size of a small vegetation plot) and one about a millimeter. Cereal rye (Secale cereale) was planted at the Beltsville Agricultural Research Center for a winter cover crop with fall and spring fertilizer applications, which produced differences in biomass and leaf chlorophyll content. UAS imagery was simulated by placing a Fuji IS-Pro UVIR digital camera at 3-m height looking nadir. An external UV-IR cut filter was used to acquire true-color images; an external red cut filter was used to obtain color-infrared-like images with bands at near-infrared, green, and blue wavelengths. Plot-scale Green Normalized Difference Vegetation Index was correlated with dry aboveground biomass ( ${mbi {r}} = 0.58$ ), whereas the Triangular Greenness Index (TGI) was not correlated with chlorophyll content. We used the SamplePoint program to select 100 pixels systematically; we visually identified the cover type and acquired the digital numbers. The number of rye pixels in each image was better correlated with biomass ( ${mbi {r}} = 0.73$ ), and the average TGI from only leaf pixels was negatively correlated with chlorophyll content ( ${mbi {r}} = -0.72$ ). Thus, better information for crop requirements may be obtained using very small pixel sizes, but new algorithms based on computer vision are needed for analysis. It may not be necessary to geospatially register large numbers of photographs with very small pixel sizes. Instead, images could be analyzed as single plots along field transects.

Operational programs in forest management and priority in the utilization of remote sensing

Science.gov (United States)

Douglass, R. W.

1978-01-01

A speech is given on operational remote sensing programs in forest management and the importance of remote sensing in forestry is emphasized. Forest service priorities in using remote sensing are outlined.

Innovative progress and sustainable development of remote sensing for uranium geology

International Nuclear Information System (INIS)

Liu Dechang; Zhao Yingjun; Ye Fawang

2009-01-01

The paper reviewes the innovative process of remote sensing for the uranium geology in Beijing Research Institute of Uranium Geology (BRIUG), discusses the science and technology progress of uranium geology due to remote sensing technique, and the way how to keep sustainable development of the remote sensing for uranium geology so as to play an important role in the uranium geology in the future. (authors)

CSIR-NLC mobile LIDAR for atmosphere remote sensing

CSIR Research Space (South Africa)

Sivakumar, V

2009-07-01

Full Text Available Africa. 2Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Lynwood Road, Pretoria 0002, South Africa. 3Tshwane University of Technology, Pretoria 0001, South Africa. ABSTRACT A mobile LIDAR (LIght Detection... obtained using the CSIR-NLC mobile LIDAR in a 23 hour field campaign at the University of Pretoria. Index Terms— Atmospheric measurements, Remote sensing, Aerosols, Air pollution, Meteorology 1. INTRODUCTION Remote sensing is a technique...

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...

An improved optimum-path forest clustering algorithm for remote sensing image segmentation

Science.gov (United States)

Chen, Siya; Sun, Tieli; Yang, Fengqin; Sun, Hongguang; Guan, Yu

2018-03-01

Remote sensing image segmentation is a key technology for processing remote sensing images. The image segmentation results can be used for feature extraction, target identification and object description. Thus, image segmentation directly affects the subsequent processing results. This paper proposes a novel Optimum-Path Forest (OPF) clustering algorithm that can be used for remote sensing segmentation. The method utilizes the principle that the cluster centres are characterized based on their densities and the distances between the centres and samples with higher densities. A new OPF clustering algorithm probability density function is defined based on this principle and applied to remote sensing image segmentation. Experiments are conducted using five remote sensing land cover images. The experimental results illustrate that the proposed method can outperform the original OPF approach.

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

Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

Science.gov (United States)

Trinh, R. C.; Holt, B.; Gierach, M.

2016-02-01

Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also

Information mining in remote sensing imagery

Science.gov (United States)

Li, Jiang

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

Research on remote sensing image pixel attribute data acquisition method in AutoCAD

Science.gov (United States)

Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui

2013-07-01

The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.

Remote-Sensing Estimation of Phytoplankton Size Classes From GOCI Satellite Measurements in Bohai Sea and Yellow Sea

Science.gov (United States)

Sun, Deyong; Huan, Yu; Qiu, Zhongfeng; Hu, Chuanmin; Wang, Shengqiang; He, Yijun

2017-10-01

Phytoplankton size class (PSC), a measure of different phytoplankton functional and structural groups, is a key parameter to the understanding of many marine ecological and biogeochemical processes. In turbid waters where optical properties may be influenced by terrigenous discharge and nonphytoplankton water constituents, remote estimation of PSC is still a challenging task. Here based on measurements of phytoplankton diagnostic pigments, total chlorophyll a, and spectral reflectance in turbid waters of Bohai Sea and Yellow Sea during summer 2015, a customized model is developed and validated to estimate PSC in the two semienclosed seas. Five diagnostic pigments determined through high-performance liquid chromatography (HPLC) measurements are first used to produce weighting factors to model phytoplankton biomass (using total chlorophyll a as a surrogate) with relatively high accuracies. Then, a common method used to calculate contributions of microphytoplankton, nanophytoplankton, and picophytoplankton to the phytoplankton assemblage (i.e., Fm, Fn, and Fp) is customized using local HPLC and other data. Exponential functions are tuned to model the size-specific chlorophyll a concentrations (Cm, Cn, and Cp for microphytoplankton, nanophytoplankton, and picophytoplankton, respectively) with remote-sensing reflectance (Rrs) and total chlorophyll a as the model inputs. Such a PSC model shows two improvements over previous models: (1) a practical strategy (i.e., model Cp and Cn first, and then derive Cm as C-Cp-Cn) with an optimized spectral band (680 nm) for Rrs as the model input; (2) local parameterization, including a local chlorophyll a algorithm. The performance of the PSC model is validated using in situ data that were not used in the model development. Application of the PSC model to GOCI (Geostationary Ocean Color Imager) data leads to spatial and temporal distribution patterns of phytoplankton size classes (PSCs) that are consistent with results reported from

Scaling gross ecosystem production at Harvard Forest with remote sensing: a comparison of estimates from a constrained quantum-use efficiency model and eddy correlation

International Nuclear Information System (INIS)

Waring, R.H.; Law, B.E.; Goulden, M.L.; Bassow, S.L.; McCreight, R.W.; Wofsy, S.C.; Bazzaz, F.A.

1995-01-01

Two independent methods of estimating gross ecosystem production (GEP) were compared over a period of 2 years at monthly integrals for a mixed forest of conifers and deciduous hardwoods at Harvard Forest in central Massachusetts. Continuous eddy flux measurements of net ecosystem exchange (NEE) provided one estimate of GEP by taking day to night temperature differences into account to estimate autotrophic and heterotrophic respiration. GEP was also estimated with a quantum efficiency model based on measurements of maximum quantum efficiency (Qmax), seasonal variation in canopy phenology and chlorophyll content, incident PAR, and the constraints of freezing temperatures and vapour pressure deficits on stomatal conductance. Quantum efficiency model estimates of GEP and those derived from eddy flux measurements compared well at monthly integrals over two consecutive years (R 2 = 0–98). Remotely sensed data were acquired seasonally with an ultralight aircraft to provide a means of scaling the leaf area and leaf pigmentation changes that affected the light absorption of photosynthetically active radiation to larger areas. A linear correlation between chlorophyll concentrations in the upper canopy leaves of four hardwood species and their quantum efficiencies (R 2 = 0–99) suggested that seasonal changes in quantum efficiency for the entire canopy can be quantified with remotely sensed indices of chlorophyll. Analysis of video data collected from the ultralight aircraft indicated that the fraction of conifer cover varied from < 7% near the instrument tower to about 25% for a larger sized area. At 25% conifer cover, the quantum efficiency model predicted an increase in the estimate of annual GEP of < 5% because unfavourable environmental conditions limited conifer photosynthesis in much of the non-growing season when hardwoods lacked leaves

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.

Remote Sensing of Mangrove Ecosystems: A Review

Directory of Open Access Journals (Sweden)

Stefan Dech

2011-04-01

Full Text Available Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove

Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes

Directory of Open Access Journals (Sweden)

Gongliang Yu

2014-04-01

Full Text Available Satellite remote sensing is a highly useful tool for monitoring chlorophyll-a concentration (Chl-a in water bodies. Remote sensing algorithms based on near-infrared-red (NIR-red wavelengths have demonstrated great potential for retrieving Chl-a in inland waters. This study tested the performance of a recently developed NIR-red based algorithm, SAMO-LUT (Semi-Analytical Model Optimizing and Look-Up Tables, using an extensive dataset collected from five Asian lakes. Results demonstrated that Chl-a retrieved by the SAMO-LUT algorithm was strongly correlated with measured Chl-a (R2 = 0.94, and the root-mean-square error (RMSE and normalized root-mean-square error (NRMS were 8.9 mg∙m−3 and 72.6%, respectively. However, the SAMO-LUT algorithm yielded large errors for sites where Chl-a was less than 10 mg∙m−3 (RMSE = 1.8 mg∙m−3 and NRMS = 217.9%. This was because differences in water-leaving radiances at the NIR-red wavelengths (i.e., 665 nm, 705 nm and 754 nm used in the SAMO-LUT were too small due to low concentrations of water constituents. Using a blue-green algorithm (OC4E instead of the SAMO-LUT for the waters with low constituent concentrations would have reduced the RMSE and NRMS to 1.0 mg∙m−3 and 16.0%, respectively. This indicates (1 the NIR-red algorithm does not work well when water constituent concentrations are relatively low; (2 different algorithms should be used in light of water constituent concentration; and thus (3 it is necessary to develop a classification method for selecting the appropriate algorithm.

Monitoring of Gangotri glacier using remote sensing and ground ...

Indian Academy of Sciences (India)

Dozier J 1989a Remote sensing of snow in the visible and near-infrared wavelengths; In: Theory and Applications of. Optical Remote Sensing (ed.) Asrar G (New York: John. Wiley and Sons), pp. 527–547. Dozier J 1989b Spectral signature of alpine snow cover from the Landsat Thematic Mapper; Rem. Sens. Environ. 28.

Filtering remotely sensed chlorophyll concentrations in the Red Sea using a space-time covariance model and a Kalman filter

KAUST Repository

Dreano, Denis

2015-04-27

A statistical model is proposed to filter satellite-derived chlorophyll concentration from the Red Sea, and to predict future chlorophyll concentrations. The seasonal trend is first estimated after filling missing chlorophyll data using an Empirical Orthogonal Function (EOF)-based algorithm (Data Interpolation EOF). The anomalies are then modeled as a stationary Gaussian process. A method proposed by Gneiting (2002) is used to construct positive-definite space-time covariance models for this process. After choosing an appropriate statistical model and identifying its parameters, Kriging is applied in the space-time domain to make a one step ahead prediction of the anomalies. The latter serves as the prediction model of a reduced-order Kalman filter, which is applied to assimilate and predict future chlorophyll concentrations. The proposed method decreases the root mean square (RMS) prediction error by about 11% compared with the seasonal average.

Filtering remotely sensed chlorophyll concentrations in the Red Sea using a space-time covariance model and a Kalman filter

KAUST Repository

Dreano, Denis; Mallick, Bani; Hoteit, Ibrahim

2015-01-01

A statistical model is proposed to filter satellite-derived chlorophyll concentration from the Red Sea, and to predict future chlorophyll concentrations. The seasonal trend is first estimated after filling missing chlorophyll data using an Empirical Orthogonal Function (EOF)-based algorithm (Data Interpolation EOF). The anomalies are then modeled as a stationary Gaussian process. A method proposed by Gneiting (2002) is used to construct positive-definite space-time covariance models for this process. After choosing an appropriate statistical model and identifying its parameters, Kriging is applied in the space-time domain to make a one step ahead prediction of the anomalies. The latter serves as the prediction model of a reduced-order Kalman filter, which is applied to assimilate and predict future chlorophyll concentrations. The proposed method decreases the root mean square (RMS) prediction error by about 11% compared with the seasonal average.

Remote sensing: a tool for park planning and management

Science.gov (United States)

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

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

A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images

Directory of Open Access Journals (Sweden)

Xiuhong Zhang

2018-01-01

Full Text Available With the rapid development of remote sensing technology, the quantity and variety of remote sensing images are growing so quickly that proactive and personalized access to data has become an inevitable trend. One of the active approaches is remote sensing image recommendation, which can offer related image products to users according to their preference. Although multiple studies on remote sensing retrieval and recommendation have been performed, most of these studies model the user profiles only from the perspective of spatial area or image features. In this paper, we propose a spatiotemporal recommendation method for remote sensing data based on the probabilistic latent topic model, which is named the Space-Time Periodic Task model (STPT. User retrieval behaviors of remote sensing images are represented as mixtures of latent tasks, which act as links between users and images. Each task is associated with the joint probability distribution of space, time and image characteristics. Meanwhile, the von Mises distribution is introduced to fit the distribution of tasks over time. Then, we adopt Gibbs sampling to learn the random variables and parameters and present the inference algorithm for our model. Experiments show that the proposed STPT model can improve the capability and efficiency of remote sensing image data services.

Synergies of multiple remote sensing data sources for REDD+ monitoring

NARCIS (Netherlands)

Sy, de V.; Herold, M.; Achard, F.; Asner, G.P.; Held, A.; Kellndorfer, J.; Verbesselt, J.

2012-01-01

Remote sensing technologies can provide objective, practical and cost-effective solutions for developing and maintaining REDD+ monitoring systems. This paper reviews the potential and status of available remote sensing data sources with a focus on different forest information products and synergies

Remote Sensing Data Visualization, Fusion and Analysis via Giovanni

Science.gov (United States)

Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.

2007-01-01

We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.

POLARIZATION REMOTE SENSING PHYSICAL MECHANISM, KEY METHODS AND APPLICATION

Directory of Open Access Journals (Sweden)

B. Yang

2017-09-01

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

A Student-Friendly Graphical User Interface to Extract Data from Remote Sensing Level-2 Products.

Science.gov (United States)

Bernardello, R.

2016-02-01

Remote sensing era has provided an unprecedented amount of publicly available data. The United States National Aeronautics and Space Administration Goddard Space Flight Center (NASA-GSFC) has achieved remarkable results in the distribution of these data to the scientific community through the OceanColor web page (http://oceancolor.gsfc.nasa.gov/). However, the access to these data, is not straightforward and needs a certain investment of time in learning the use of existing software. Satellite sensors acquire raw data that are processed through several steps towards a format usable by the scientific community. These products are distributed in Hierarchical Data Format (HDF) which often represents the first obstacle for students, teachers and scientists not used to deal with extensive matrices. We present here SATellite data PROcessing (SATPRO) a newly developed Graphical User Interface (GUI) designed in MATLAB environment to provide an easy, immediate yet reliable way to select and extract Level-2 data from NASA SeaWIFS and MODIS-Aqua databases for oceanic surface temperature and chlorophyll. Since no previous experience with MATLAB is required, SATPRO allows the user to explore the available dataset without investing any software-learning time. SATPRO is an ideal tool to introduce undergraduate students to the use of remote sensing data in oceanography and can also be useful for research projects at the graduate level.

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...

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...

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

The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best

The Potential of AI Techniques for Remote Sensing

Science.gov (United States)

Estes, J. E.; Sailer, C. T. (Principal Investigator); Tinney, L. R.

1984-01-01

The current status of artificial intelligence AI technology is discussed along with imagery data management, database interrogation, and decision making. Techniques adapted from the field of artificial intelligence (AI) have significant, wide ranging impacts upon computer-assisted remote sensing analysis. AI based techniques offer a powerful and fundamentally different approach to many remote sensing tasks. In addition to computer assisted analysis, AI techniques can also aid onboard spacecraft data processing and analysis and database access and query.

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...

Remote sensing from UAVs for hydrological monitoring

DEFF Research Database (Denmark)

Bandini, Filippo; Garcia, Monica; Bauer-Gottwein, Peter

compared to other technologies: compared to field based techniques, remote sensing with UAVs is a non-destructive technique, less time consuming, ensures a reduced time between acquisition and interpretation of data and gives the possibility to access remote and unsafe areas. Compared to full...... will be able to record the spectral signatures of water and land surfaces with a pixel resolution of around 15 cm, whereas the thermal camera will sense water and land surface temperature with a resolution of 40 cm. Post-processing of data from the thermal camera will allow retrieving vegetation and soil...

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...

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...

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...

Recent developments in remote sensing for coastal and marine applications

CSIR Research Space (South Africa)

Lück-Vogel, Melanie

2017-01-01

Full Text Available at the coast is that it is in a permanent state of change. Remote sensing, whether from orbiting (space-borne) or air-borne platforms, can greatly assist in the task of monitoring coastal environments. In particular, remote sensing enables simultaneous or near...

Mapping of Landscape Cover Using Remote Sensing and GIS in ...

African Journals Online (AJOL)

Tadesse

present study, Remote Sensing (RS) and Geographical Information System (GIS) techniques were used. Remotely sensed .... growing stock in Tahno range of Dehradun Forest Division. Okhandiara (2008) .... areas on an image by identifying 'training' sites of known targets and then extrapolating those spectral signatures to ...

The potential of remote sensing technology for the detection and ...

African Journals Online (AJOL)

Internationally, a number of studies have successfully used remote sensing technology to monitor forest damage. Remote sensing technology allows for instantaneous methods of assessments whereby ground assessments would be impossible on a regular basis. This paper provides an overview of how advances in ...

A remote sensing driven distributed hydrological model of the Senegal River basin

DEFF Research Database (Denmark)

Stisen, Simon; Jensen, Karsten Høgh; Sandholt, Inge

2008-01-01

outputs of AET from both model setups was carried out. This revealed substantial differences in the spatial patterns of AET for the examined subcatchment, in spite of similar values of predicted discharge and average AET. The potential for driving large scale hydrological models using remote sensing data......Distributed hydrological models require extensive data amounts for driving the models and for parameterization of the land surface and subsurface. This study investigates the potential of applying remote sensing (RS) based input data in a hydrological model for the 350,000 km2 Senegal River basin...... in West Africa. By utilizing remote sensing data to estimate precipitation, potential evapotranspiration (PET) and leaf area index (LAI) the model was driven entirely by remote sensing based data and independent of traditional meteorological data. The remote sensing retrievals were based on data from...

Water Column Correction for Coral Reef Studies by Remote Sensing

Directory of Open Access Journals (Sweden)

Maria Laura Zoffoli

2014-09-01

Full Text Available 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.

Water Column Correction for Coral Reef Studies by Remote Sensing

Science.gov (United States)

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

2014-01-01

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

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. [...

Surveillance and remote sensing: ITOPF participation

International Nuclear Information System (INIS)

Nichols, J.A.

1992-01-01

Although the Federation does not sponsor or undertake surveillance and remote sensing research and development projects, it is a potential user of remote sensing equipment when responding to oil spills. Indeed, the Federation has already made use of suitably equipped aircraft on a number of occasions in Europe. Several countries in north west Europe, viz. France, Germany, Netherlands, Norway, Sweden and the U.K., operate aircraft fitted with broadly similar systems comprising side-looking airborne radar (SLAR), infra-red line scanners (IRLS) and ultra-violet line scanners (UVLS). These aircraft are used routinely for the detection of operational discharges of oil from ships in violation of the International Convention on the Prevention of Pollution from Ships 73/78 (MARPOL 73/78)

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

Science.gov (United States)

2017-03-01

at reasonable logistical or financial costs . Remote sensing provides an attractive alternative. We discuss the range of different sensors that are...DARLA: Data Assimilation and Remote Sensing for Littoral Applications Final Report Award Number: N000141010932 Andrew T. Jessup Chris Chickadel...20. Radermacher, M., M. Wengrove, J. V. de Vries, and R. Holman (2014), Applicability of video-derived bathymetry estimates to nearshore current

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

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

Science.gov (United States)

Guild, Liane

2016-01-01

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

Regional ocean-colour chlorophyll algorithms for the Red Sea

KAUST Repository

Brewin, Robert J.W.

2015-05-18

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.

A remote sensing and GIS-enabled asset management system (RS-GAMS).

Science.gov (United States)

2013-04-01

Under U.S. Department of Transportation (DOT) Commercial Remote Sensing and : Spatial Information (CRS&SI) Technology Initiative 2 of the Transportation : Infrastructure Construction and Condition Assessment, an intelligent Remote Sensing and : GIS-b...

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

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...

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Watermarking techniques for electronic delivery of remote sensing images

Science.gov (United States)

Barni, Mauro; Bartolini, Franco; Magli, Enrico; Olmo, Gabriella

2002-09-01

Earth observation missions have recently attracted a growing interest, mainly due to the large number of possible applications capable of exploiting remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products. Such a need is a very crucial one, because the Internet and other public/private networks have become preferred means of data exchange. A critical issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: assessment of the requirements imposed by remote sensing applications on watermark-based copyright protection, and modification of two well-established digital watermarking techniques to meet such constraints. More specifically, the concept of near-lossless watermarking is introduced and two possible algorithms matching such a requirement are presented. Experimental results are shown to measure the impact of watermark introduction on a typical remote sensing application, i.e., unsupervised image classification.

First European Workshop on 'Remote sensing in mineral exploration'

International Nuclear Information System (INIS)

Van Wambeke, L.; Sanderson, D.J.; Dolan, J.M.

1986-01-01

The First European Workshop on 'Remote sensing in mineral exploration' organized by the Commission of the European Communities in February 1985 took stock of the results obtained within the European Community on the application of remote sensing techniques in exploration. The papers presented in this publication are essentially based on data obtained with the first generation of satellites and some airborne experiments. Important progress in data processing and interpretation has been made in the EEC since 1979 and is continuing to be made. The main aim is to provide the EC mining industry with a new tool for exploration. Significant results have already been obtained with the EEC playing an important role in the promotion of this relatively new technique. The main R and D trend is towards an integration of multidata sets (remote sensing, geochemical, geophysical and other data) to improve the methodology for delineating new targets in exploration. Another general trend is the participation of mining companies in remote sensing experiments. Further improvement for exploration is expected in the near future with the thematic mapper and the spot imageries as well as new airborne sensors

AN INTERACTIVE WEB-BASED ANALYSIS FRAMEWORK FOR REMOTE SENSING CLOUD COMPUTING

Directory of Open Access Journals (Sweden)

X. Z. Wang

2015-07-01

Full Text Available Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users’ private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook

An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

Science.gov (United States)

Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

2015-07-01

Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write

Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2

Science.gov (United States)

Frankenberg, Christian; Odell, Chris; Berry, Joseph; Guanter, Luis; Joiner, Joanna; Kohler, Philipp; Pollock, Randy; Taylor, Thomas E.

2014-01-01

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 nm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm(exp -2)sr(exp -1) nm(exp -1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies.We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

Study on edge-extraction of remote sensing image

International Nuclear Information System (INIS)

Wen Jianguang; Xiao Qing; Xu Huiping

2005-01-01

Image edge-extraction is an important step in image processing and recognition, and also a hot spot in science study. In this paper, based on primary methods of the remote sensing image edge-extraction, authors, for the first time, have proposed several elements which should be considered before processing. Then, the qualities of several methods in remote sensing image edge-extraction are systematically summarized. At last, taking Near Nasca area (Peru) as an example the edge-extraction of Magmatic Range is analysed. (authors)

Using remotely-sensed data for optimal field sampling

CSIR Research Space (South Africa)

Debba, Pravesh

2008-09-01

Full Text Available 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... studies are: where to sample, what to sample and how many samples to obtain. Conventional sampling techniques are not always suitable in environmental studies and scientists have explored the use of remotely-sensed data as ancillary information to aid...

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

Directory of Open Access Journals (Sweden)

Linyi Li

2017-01-01

Full Text Available In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Earth and atmospheric remote sensing; Proceedings of the Meeting, Orlando, FL, Apr. 2-4, 1991

Science.gov (United States)

Curran, Robert J. (Editor); Smith, James A. (Editor); Watson, Ken (Editor)

1991-01-01

The papers presented in this volume address the technical aspects of earth and atmospheric remote sensing. Topics discussed include spaceborne and ground-based applications of laser remote sensing, advanced applications of lasers in remote sensing, laser ranging applications, data analysis and systems for biospheric processes, measurements for biospheric processes, and remote sensing for geology and geophysics. Papers are presented on a space-qualified laser transmitter for lidar applications, solid state lasers for planetary exploration, automated band selection for multispectral meteorological applications, aerospace remote sensing of natural water organics, and remote sensing of volcanic ash hazards to aircraft.

Sun-induced chlorophyll fluorescence and photochemical reflectance index improve remote-sensing gross primary production estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Science.gov (United States)

Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2015-11-01

This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different nitrogen (N) and phosphorous (P) availability. Sun-induced chlorophyll fluorescence yield computed at 760 nm (Fy760), scaled photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy chambers on the same locations sampled by the spectrometers. We tested whether light-use efficiency (LUE) models driven by remote-sensing quantities (RSMs) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed higher GPP in the N-fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was closely related to the mean of plant N content across treatments (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments, but it is affected by N availability. Results from a cross-validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv =140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However

Remote Sensing Applications to Water Quality Management in Florida

Science.gov (United States)

Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.

2013-12-01

Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria

Quantitative interpretation of great lakes remote sensing data

International Nuclear Information System (INIS)

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

1980-01-01

Remote sensing has been applied in the past to the surveillance of Great Lakes water quality, but it has been only partially successful because of the completely empirical approach taken in relating the multispectral scanning data at visible and near-infrared wavelengths to water parameters. Any remote sensing approach using water color information must take into account (1) the existence of many different organic and inorganic species throughtout the Greak Lakes, (2) the occurrence of a mixture of species in most locations, and (3) spatial (inter- and interlake as well as vertical) variations in types and concentrations 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 clearly show the advantage of using a radiative transfer model. Spectral absorptance and backscattering coefficients for two inorganic sediments are reported

Coalfire related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfires related CO2 emissions and remote sensing

Energy Technology Data Exchange (ETDEWEB)

Gangopadhyay, P.K.

2008-06-11

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Coalfire related CO2 emissions and remote sensing

International Nuclear Information System (INIS)

Gangopadhyay, P.K.

2008-01-01

Subsurface and surface coalfires are a serious problem in many coal-producing countries. Combustion can occur within the coal seams (underground or surface), in piles of stored coal, or in spoil dumps at the surface. While consuming a non renewable energy source, coalfires promote several environmental problems. Among all GHGs that are emitted from coalfires, CO2 is the most significant because of its high quantity. In connection to this environmental problem, the core aim of the present research is to develop a hyperspectral remote sensing and radiative transfer based model that is able to estimate CO2 concentration (ppmv) from coalfires. Since 1960s remote sensing is being used as a tool to detect and monitoring coalfires. With time, remote sensing has proven a reliable tool to identify and monitor coalfires. In the present study multi-temporal, multi-sensor and multi-spectral thermal remote sensing data are being used to detect and monitor coalfires. Unlike the earlier studies, the present study explores the possibilities of satellite derived emissivity to detect and monitor coalfires. Two methods of emissivity extraction from satellite data were tested, namely NDVI (Normalized Difference Vegetation Index) derived and TES (Temperature emissivity separation) in two study areas situated in India and China and it was observed that the satellite derived emissivity offers a better kinetic surface temperature of the surface to understand the spread and extent of the coalfires more effectively. In order to reduce coalfire related GHG emissions and to achieve more effective fire fighting plans it is crucial to understand the dynamics of coalfire. Multitemporal spaceborne remote sensing data can be used to study the migration and expresses the results as vectors, indicating direction and speed of migration. The present study proposes a 2D model that recognizes an initiation point of coalfire from thermal remote sensing data and considers local geological settings to

Autonomous Coral Reef Survey in Support of Remote Sensing

Directory of Open Access Journals (Sweden)

Steven G. Ackleson

2017-10-01

Full Text Available An autonomous surface vehicle instrumented with optical and acoustical sensors was deployed in Kane'ohe Bay, HI, U.S.A., to provide high-resolution, in situ observations of coral reef reflectance with minimal human presence. The data represented a wide range in bottom type, water depth, and illumination and supported more thorough investigations of remote sensing methods for identifying and mapping shallow reef features. The in situ data were used to compute spectral bottom reflectance and remote sensing reflectance, Rrs,λ, as a function of water depth and benthic features. The signals were used to distinguish between live coral and uncolonized sediment within the depth range of the measurements (2.5–5 m. In situRrs, λ were found to compare well with remotely sensed measurements from an imaging spectrometer, the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS, deployed on an aircraft at high altitude. Cloud cover and in situ sensor orientation were found to have minimal impact on in situRrs, λ, suggesting that valid reflectance data may be collected using autonomous surveys even when atmospheric conditions are not favorable for remote sensing operations. The use of reflectance in the red and near infrared portions of the spectrum, expressed as the red edge height, REHλ, was investigated for detecting live aquatic vegetative biomass, including coral symbionts and turf algae. The REHλ signal from live coral was detected in Kane'ohe Bay to a depth of approximately 4 m with in situ measurements. A remote sensing algorithm based on the REHλ signal was defined and applied to AVIRIS imagery of the entire bay and was found to reveal areas of shallow, dense coral and algal cover. The peak wavelength of REHλ decreased with increasing water depth, indicating that a more complete examination of the red edge signal may potentially yield a remote sensing approach to simultaneously estimate vegetative biomass and bathymetry in shallow water.

A review of remote sensing applications for oil palm studies

Institute of Scientific and Technical Information of China (English)

Khai Loong Chong; Kasturi Devi Kanniah; Christine Pohl; Kian Pang Tan

2017-01-01

Oil palm becomes an increasingly important source of vegetable oil for its production exceeds soybean,sunflower,and rapeseed.The growth of the oil palm industry causes degradation to the environment,especially when the expansion of plantations goes uncontrolled.Remote sensing is a useful tool to monitor the development of oil palm plantations.In order to promote the use of remote sensing in the oil palm industry to support their drive for sustainability,this paper provides an understanding toward the use of remote sensing and its applications to oil palm plantation monitoring.In addition,the existing knowledge gaps are identified and recommendations for further research are given.

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.

The function of remote sensing in support of environmental policy

OpenAIRE

de Leeuw, Jan; Georgiadou, P.Y.; Georgiadou, Yola; Kerle, Norman; de Gier, Alfred; Inoue, Yoshio; Ferwerda, Jelle; Smies, Maarten; Narantuya, Davaa

2010-01-01

Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently lit...

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.

Accurate estimation of motion blur parameters in noisy remote sensing image

Science.gov (United States)

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

2015-05-01

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

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

Science.gov (United States)

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

2014-11-01

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

Advances on application of remote sensing technology to uranium prospecting in northwest of China

International Nuclear Information System (INIS)

Ye Fawang; Liu Dechang; Zhao Yingjun; Zhang Jielin; Fang Maolong

2012-01-01

Some advances on application of remote sensing technology to uranium prospecting in northwest of China since 21st century are presented in this paper. They included: (1) application of ETM multi-spectral remote sensing technology to identify the sandstone-type uranium ore-controlling structure in north of Ordos Basin and investigate the uranium metallogenetic geological conditions in Qiangtang Basin, Tibet, (2) application of ASTER multi-spectral and QuickBird high spatial resolution remote sensing technology to extract and analyze the oil-gas reduced alteration in Bashibulake uranium ore district, Xinjiang, (3) discovery of Salamubulake uranium metallogenetic belt in Keping, Xinjiang, using ASTER multi-spectral, QuickBird high spatial resolution, and CASI/SASI airborne hyper-spectral remote sensing comprehensively, and (4) application of CASI/SASI airborne hyper-spectral remote sensing technology to extract volcanicrock type uranium mineralization alteration in Baiyanghe area, Xinjiang. These application advances show the good application effects of remote sensing technology to uranium exploration in northwest of China, which provides important references for making further uranium prospecting using remote sensing technology. (authors)

Textbooks and technical references for remote sensing

Science.gov (United States)

Rudd, R. D.; Bowden, L. W.; Colwell, R. N.; Estes, J. E.

1980-01-01

A selective bibliography is presented which cites 89 textbooks, monographs, and articles covering introductory and advanced remote sensing techniques, photointerpretation, photogrammetry, and image processing.

Applications of remote sensing to geobotanical prospecting for non-renewable resources

Science.gov (United States)

Birnie, R. W.

1982-01-01

Airborne sensors used in the remote detection of geobotanical anomalies are able to locate mineral deposits. Geobotanical stress is manifested in increased visible spectrum reflectance due to a decrease in chlorophyll content which induces chlorosis. The effectiveness of this method is, however, restricted to soils in which plant root structures are embedded in bedrock-derived soils to a depth sufficient for the production of heavy metal stress. It is noted that Landsat remote sensors are inherently better suited to the detection of overall plant density or biomass changes relating to zones of mineralization.

Mission studies on constellation of LEO satellites with remote-sensing and communication payloads

Science.gov (United States)

Chen, Chia-Ray; Hwang, Feng-Tai; Hsueh, Chuang-Wei

2017-09-01

Revisiting time and global coverage are two major requirements for most of the remote sensing satellites. Constellation of satellites can get the benefit of short revisit time and global coverage. Typically, remote sensing satellites prefer to choose Sun Synchronous Orbit (SSO) because of fixed revisiting time and Sun beta angle. The system design and mission operation will be simple and straightforward. However, if we focus on providing remote sensing and store-and-forward communication services for low latitude countries, Sun Synchronous Orbit will not be the best choice because we need more satellites to cover the communication service gap in low latitude region. Sometimes the design drivers for remote sensing payloads are conflicted with the communication payloads. For example, lower orbit altitude is better for remote sensing payload performance, but the communication service zone will be smaller and we need more satellites to provide all time communication service. The current studies focus on how to provide remote sensing and communication services for low latitude countries. A cost effective approach for the mission, i.e. constellation of microsatellites, will be evaluated in this paper.

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.

Remote earth sensing experiments

Energy Technology Data Exchange (ETDEWEB)

Trifonov, Yu V

1981-01-01

Description of data devices for deriving multi-spectral measuring television measurement data of middle and high resolution through use of second generation Meteor-type satellites. Options for developing a permanent and active remote sensing system in USSR are discussed. It is noted that the present experiment is an important step in that direction. Design and structural data for this particular device and its application in the experiment are covered.

Remote sensing models and methods for image processing

CERN Document Server

Schowengerdt, Robert A

2007-01-01

Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

Remote sensing of wet lands in irrigated areas

Science.gov (United States)

Ham, H. H.

1972-01-01

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

Unmanned aerial systems for photogrammetry and remote sensing: A review

OpenAIRE

Colomina, Ismael; Molina, Pere

2014-01-01

We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last...

Research on Remote Sensing Image Template Processing Based on Global Subdivision Theory

OpenAIRE

Xiong Delan; Du Genyuan

2013-01-01

Aiming at the questions of vast data, complex operation, and time consuming processing for remote sensing image, subdivision template was proposed based on global subdivision theory, which can set up high level of abstraction and generalization for remote sensing image. The paper emphatically discussed the model and structure of subdivision template, and put forward some new ideas for remote sensing image template processing, key technology and quickly applied demonstration. The research has ...

Remote sensing of natural resources. Quarterly literature review, October-December 1980

International Nuclear Information System (INIS)

Gonzales, R.W.; Inglis, M.H.

1981-02-01

This review covers literature pertaining to documented data and data gathering techniques that are performed or obtained remotely from space, aircraft, or ground-based stations. All of the documentation is related to remote sensing sensors or the remote sensing of the natural resources. Section headings are: general; geology; environmental quality; hydrology; vegetation; oceanography; regional planning and land use; data manipulation; and instrumentation and technology

Remote sensing approach to structural modelling

International Nuclear Information System (INIS)

El Ghawaby, M.A.

1989-01-01

Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs

Applications of airborne remote sensing in atmospheric sciences research

Science.gov (United States)

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

1984-01-01

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

National Satellite Land Remote Sensing Data Archive

Science.gov (United States)

Faundeen, John L.; Longhenry, Ryan

2018-06-13

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

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.

Saldanha Bay, South Africa I: the use of ocean colour remote ...

African Journals Online (AJOL)

The efficacy of ocean colour remote sensing in assessing the variability of phytoplankton biomass within Saldanha Bay is examined. Satellite estimates of chlorophyll a (Chl a) were obtained using the maximum peak-height (MPH) algorithm on full-resolution (300 m) data from the Medium Resolution Imaging Spectrometer ...

Remote optical stethoscope and optomyography sensing device

Science.gov (United States)

Golberg, Mark; Polani, Sagi; Ozana, Nisan; Beiderman, Yevgeny; Garcia, Javier; Ruiz-Rivas Onses, Joaquin; Sanz Sabater, Martin; Shatsky, Max; Zalevsky, Zeev

2017-02-01

In this paper we present the usage of photonic remote laser based device for sensing nano-vibrations for detection of muscle contraction and fatigue, eye movements and in-vivo estimation of glucose concentration. The same concept is also used to realize a remote optical stethoscope. The advantage of doing the measurements from a distance is in preventing passage of infections as in the case of optical stethoscope or in the capability to monitor e.g. sleep quality without disturbing the patient. The remote monitoring of glucose concentration in the blood stream and the capability to perform opto-myography for the Messer muscles (chewing) is very useful for nutrition and weight control. The optical configuration for sensing the nano-vibrations is based upon analyzing the statistics of the secondary speckle patterns reflected from various tissues along the body of the subjects. Experimental results present the preliminary capability of the proposed configuration for the above mentioned applications.

Data Analysis Of A Coastal Zone Remote Sensing Campaign By The Nasa C130 Airplane

Science.gov (United States)

Pippi, I.; Radicati, B.

1988-01-01

The principal goal of most of our remote sensing campaigns has been the choice of the best airborne sensors and the selection of the most efficient visible and infrared wavelengths for the remote sensing of the Italian coastal zone. The "1986 C130 European Program" was performed by NASA C130 airplane last summer. In this contest on 30th July a flight over the Tuscan islands and coast was performed. The airplane was equipped with the following main sensors: a Thematic Mapper Simulator (TMS), a Thermal Infrared Multispectral Scanner (TIMS) and an Airborne Imaging Spectrometer (AIS). The images acquired, were firstly corrected for the several types of instrumental noise and errors and after that were correlated with the flight parameters and geometrically corrected. Finally the data were reduced to physical units taking into account the sensors calibration. Particular attention was also paid to the atmospheric effects taken into account by the use of the spectral results of the computer program LOWTRAN-6. First results on sea temperature detection, especially near river or channel estuaries, were reported. At the same time comparison between the thermal infrared channel of the TMS and those of THIS was performed. In addition studies are being made on the relationships among chlorophyll, plankton, yellow substance, oil at sea, total suspended matter, fluorescence and sea color. On that basis, combining the bands of the TMS, tentative image processing is being performed to determinate alga and dissolved organic materials covering.

The benefits of remote sensing for energy policy

International Nuclear Information System (INIS)

Sen, A.

2004-01-01

A strong remote sensing regime is a necessary component of any contemporary national or international energy policy. Energy is essential to the functioning of modem industrial society, and as such it is the responsibility of governments to produce sound national energy policies in order to ensure stable economic growth, ecologically responsible use of energy resources and the health and safety of citizens. Comprehensive, accurate and timely remote sensing data can aid decision making on energy matters in several areas. This paper looks at the benefits that can be realized in resource exploration, weather forecasting and environmental monitoring. Improvements in the technology of remote sensing platforms would be of great value to buyers of energy, sellers of energy and the environment. Furthermore, the utility of such information could be enhanced by efforts of government agencies to communicate it more effectively to the end-user. National energy policies should thus include investments not only in satellite system hardware to collect data, but also in the services required to interpret and distribute the data. (author)

Efficiency of chlorophyll in gross primary productivity: A proof of concept and application in crops.

Science.gov (United States)

Gitelson, Anatoly A; Peng, Yi; Viña, Andrés; Arkebauer, Timothy; Schepers, James S

2016-08-20

One of the main factors affecting vegetation productivity is absorbed light, which is largely governed by chlorophyll. In this paper, we introduce the concept of chlorophyll efficiency, representing the amount of gross primary production per unit of canopy chlorophyll content (Chl) and incident PAR. We analyzed chlorophyll efficiency in two contrasting crops (soybean and maize). Given that they have different photosynthetic pathways (C3 vs. C4), leaf structures (dicot vs. monocot) and canopy architectures (a heliotrophic leaf angle distribution vs. a spherical leaf angle distribution), they cover a large spectrum of biophysical conditions. Our results show that chlorophyll efficiency in primary productivity is highly variable and responds to various physiological and phenological conditions, and water availability. Since Chl is accessible through non-destructive, remotely sensed techniques, the use of chlorophyll efficiency for modeling and monitoring plant optimization patterns is practical at different scales (e.g., leaf, canopy) and under widely-varying environmental conditions. Through this analysis, we directly related a functional characteristic, gross primary production with a structural characteristic, canopy chlorophyll content. Understanding the efficiency of the structural characteristic is of great interest as it allows explaining functional components of the plant system. Copyright © 2016 Elsevier GmbH. All rights reserved.

Remote Sensing of Landscapes with Spectral Images

Science.gov (United States)

Adams, John B.; Gillespie, Alan R.

2006-05-01

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

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

Science.gov (United States)

Zheng, Guang; Moskal, L Monika

2009-01-01

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

Copyright protection of remote sensing imagery by means of digital watermarking

Science.gov (United States)

Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella; Zanini, R.

2001-12-01

The demand for remote sensing data has increased dramatically mainly due to the large number of possible applications capable to exploit remotely sensed data and images. As in many other fields, along with the increase of market potential and product diffusion, the need arises for some sort of protection of the image products from unauthorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred and effective means of data exchange. An important issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. Before applying watermarking techniques developed for multimedia applications to remote sensing applications, it is important that the requirements imposed by remote sensing imagery are carefully analyzed to investigate whether they are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: (1) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection; (2) discussion of a case study where the performance of two popular, state-of-the-art watermarking techniques are evaluated by the light of the requirements at the previous point.

Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review

Directory of Open Access Journals (Sweden)

J. M. Barbosa

2014-01-01

Full Text Available Tropical landscapes are, in general, a mosaic of pasture, agriculture, and forest undergoing various stages of succession. Forest succession is comprised of continuous structural changes over time and results in increases in aboveground biomass (AGB. New remote sensing methods, including sensors, image processing, statistical methods, and uncertainty evaluations, are constantly being developed to estimate biophysical forest changes. We review 318 peer-reviewed studies related to the use of remotely sensed AGB estimations in tropical forest succession studies and summarize their geographic distribution, sensors and methods used, and their most frequent ecological inferences. Remotely sensed AGB is broadly used in forest management studies, conservation status evaluations, carbon source and sink investigations, and for studies of the relationships between environmental conditions and forest structure. Uncertainties in AGB estimations were found to be heterogeneous with biases related to sensor type, processing methodology, ground truthing availability, and forest characteristics. Remotely sensed AGB of successional forests is more reliable for the study of spatial patterns of forest succession and over large time scales than that of individual stands. Remote sensing of temporal patterns in biomass requires further study, in particular, as it is critical for understanding forest regrowth at scales useful for regional or global analyses.

Suppression of Instability on Sensing Signal of Optical Pulse Correlation Measurement in Remote Fiber Sensing

Directory of Open Access Journals (Sweden)

Hirokazu Kobayashi

2012-01-01

response and improve the accuracy of signals at the focused sensing regions. We also experimentally demonstrate remote temperature monitoring over a 30 km-long distance using a remote reference technique, and we estimate the resolution and the measurable span of the temperature variation as (1.1/L∘C and (5.9×10/L°C, respectively, where L is the length of the fiber in the sensing region.

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

Science.gov (United States)

2002-01-01

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes

Remote sensing for wind power potential: a prospector's handbook

Energy Technology Data Exchange (ETDEWEB)

Wade, J.E.; Maule, P.A.; Bodvarsson, G.; Rosenfeld, C.L.; Woolley, S.G.; McClenahan, M.R.

1983-02-01

Remote sensing can aid in identifying and locating indicators of wind power potential from the terrestrial, marine, and atmospheric environments (i.e.: wind-deformed trees, white caps, and areas of thermal flux). It is not considered as a tool for determining wind power potential. A wide variety of remotely sensed evidence is described in terms of the scale at which evidence of wind power can be identified, and the appropriate remote sensors for finding such evidence. Remote sensing can be used for regional area prospecting using small-scale imagery. The information from such small-scale imagery is most often qualitative, and if it is transitory, examination of a number of images to verify presistence of the feature may be required. However, this evidence will allow rapid screening of a large area. Medium-scale imagery provides a better picture of the evidence obtained from small-scale imagery. At this level it is best to use existing imagery. Criteria relating to land use, accessibility, and proximity of candidate sites to nearby transmission lines can also be effectively evaluated from medium-scale imagery. Large-scale imagery provides the most quantitative evidence of the strength of wind. Wind-deformed trees can be identified at a large number of sites using only a few hours in locally chartered aircraft. A handheld 35mm camera can adequately document any evidence of wind. Three case studies that employ remote sensing prospecting techniques are described. Based on remotely sensed evidence, the wind power potential in three geographically and climatically diverse areas of the United States is estimated, and the estimates are compared to actual wind data in those regions. In addition, the cost of each survey is discussed. The results indicate that remote sensing for wind power potential is a quick, cost effective, and fairly reliable method for screening large areas for wind power potential.

[Use of Remote Sensing for Crop and Soil Analysis

Science.gov (United States)

Johannsen, Chris J.

1997-01-01

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

Researching on the process of remote sensing video imagery

Science.gov (United States)

Wang, He-rao; Zheng, Xin-qi; Sun, Yi-bo; Jia, Zong-ren; Wang, He-zhan

Unmanned air vehicle remotely-sensed imagery on the low-altitude has the advantages of higher revolution, easy-shooting, real-time accessing, etc. It's been widely used in mapping , target identification, and other fields in recent years. However, because of conditional limitation, the video images are unstable, the targets move fast, and the shooting background is complex, etc., thus it is difficult to process the video images in this situation. In other fields, especially in the field of computer vision, the researches on video images are more extensive., which is very helpful for processing the remotely-sensed imagery on the low-altitude. Based on this, this paper analyzes and summarizes amounts of video image processing achievement in different fields, including research purposes, data sources, and the pros and cons of technology. Meantime, this paper explores the technology methods more suitable for low-altitude video image processing of remote sensing.

Remote Sensing of Rock Type in the Visible and Near-Infrared,

Science.gov (United States)

Visible and near-infrared spectra of minerals and rocks have been measured and evaluated in terms of remote sensing applications. The authors...difficult or impossible to use in a generalized remote sensing effort in which the composition of all rocks is to be mapped. Instead, this spectral

INTEGRATION OF SPATIAL INFORMATION WITH COLOR FOR CONTENT RETRIEVAL OF REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

Bikesh Kumar Singh

2010-08-01

Full Text Available There is rapid increase in image databases of remote sensing images due to image satellites with high resolution, commercial applications of remote sensing & high available bandwidth in last few years. The problem of content-based image retrieval (CBIR of remotely sensed images presents a major challenge not only because of the surprisingly increasing volume of images acquired from a wide range of sensors but also because of the complexity of images themselves. In this paper, a software system for content-based retrieval of remote sensing images using RGB and HSV color spaces is presented. Further, we also compare our results with spatiogram based content retrieval which integrates spatial information along with color histogram. Experimental results show that the integration of spatial information in color improves the image analysis of remote sensing data. In general, retrievals in HSV color space showed better performance than in RGB color space.

Remote sensing the phytoplankton seasonal succession of the Red Sea.

Science.gov (United States)

Raitsos, Dionysios E; Pradhan, Yaswant; Brewin, Robert J W; Stenchikov, Georgiy; Hoteit, Ibrahim

2013-01-01

The Red Sea holds one of the most diverse marine ecosystems, primarily due to coral reefs. However, knowledge on large-scale phytoplankton dynamics is limited. Analysis of a 10-year high resolution Chlorophyll-a (Chl-a) dataset, along with remotely-sensed sea surface temperature and wind, provided a detailed description of the spatiotemporal seasonal succession of phytoplankton biomass in the Red Sea. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) data, four distinct Red Sea provinces and seasons are suggested, covering the major patterns of surface phytoplankton production. The Red Sea Chl-a depicts a distinct seasonality with maximum concentrations seen during the winter time (attributed to vertical mixing in the north and wind-induced horizontal intrusion of nutrient-rich water in the south), and minimum concentrations during the summer (associated with strong seasonal stratification). The initiation of the seasonal succession occurs in autumn and lasts until early spring. However, weekly Chl-a seasonal succession data revealed that during the month of June, consistent anti-cyclonic eddies transfer nutrients and/or Chl-a to the open waters of the central Red Sea. This phenomenon occurs during the stratified nutrient depleted season, and thus could provide an important source of nutrients to the open waters. Remotely-sensed synoptic observations highlight that Chl-a does not increase regularly from north to south as previously thought. The Northern part of the Central Red Sea province appears to be the most oligotrophic area (opposed to southern and northern domains). This is likely due to the absence of strong mixing, which is apparent at the northern end of the Red Sea, and low nutrient intrusion in comparison with the southern end. Although the Red Sea is considered an oligotrophic sea, sporadic blooms occur that reach mesotrophic levels. The water temperature and the prevailing winds control the nutrient concentrations within the euphotic zone

Remote Sensing the Phytoplankton Seasonal Succession of the Red Sea

KAUST Repository

Raitsos, Dionysios E.

2013-06-05

The Red Sea holds one of the most diverse marine ecosystems, primarily due to coral reefs. However, knowledge on large-scale phytoplankton dynamics is limited. Analysis of a 10-year high resolution Chlorophyll-a (Chl-a) dataset, along with remotely-sensed sea surface temperature and wind, provided a detailed description of the spatiotemporal seasonal succession of phytoplankton biomass in the Red Sea. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) data, four distinct Red Sea provinces and seasons are suggested, covering the major patterns of surface phytoplankton production. The Red Sea Chl-a depicts a distinct seasonality with maximum concentrations seen during the winter time (attributed to vertical mixing in the north and wind-induced horizontal intrusion of nutrient-rich water in the south), and minimum concentrations during the summer (associated with strong seasonal stratification). The initiation of the seasonal succession occurs in autumn and lasts until early spring. However, weekly Chl-a seasonal succession data revealed that during the month of June, consistent anti-cyclonic eddies transfer nutrients and/or Chl-a to the open waters of the central Red Sea. This phenomenon occurs during the stratified nutrient depleted season, and thus could provide an important source of nutrients to the open waters. Remotely-sensed synoptic observations highlight that Chl-a does not increase regularly from north to south as previously thought. The Northern part of the Central Red Sea province appears to be the most oligotrophic area (opposed to southern and northern domains). This is likely due to the absence of strong mixing, which is apparent at the northern end of the Red Sea, and low nutrient intrusion in comparison with the southern end. Although the Red Sea is considered an oligotrophic sea, sporadic blooms occur that reach mesotrophic levels. The water temperature and the prevailing winds control the nutrient concentrations within the euphotic zone

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.

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

Science.gov (United States)

2014-03-01

35th International Symposium on Remote Sensing of Environment (ISRSE35) 22-26 April, 2013, Beijing, China The 35th International Symposium on Remote Sensing of Environment (ISRSE35) was successfully convened in Beijing, China, from April 22nd to 26th, 2013. This was the first event in the ISRSE series being held in China. The symposium was hosted by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, and co-organized by the International Center for Remote Sensing of Environment (ICRSE), the International Society for Photogrammetry and Remote Sensing (ISPRS), the Group on Earth Observations (GEO), the International Society for Digital Earth (ISDE) and the Chinese Academy of Sciences (CAS). The theme of the symposium was ''Earth Observation and Global Environmental Change''. Back in 1962, the first ISRSE was convened at the University of Michigan, USA. Over the past 50 years, Earth observation has advanced significantly, and remote sensing has become a mature technology for observing the Earth and monitoring global environmental change. At present, remote sensing has already entered an era of integrated, coordinated and sustainable global Earth observation and rapid development of spatial information services. It is very exciting to see that remote sensing technologies have become indispensable tools in numerous fields of Earth systems science, and are playing more and more important roles in areas such as land resources surveying and mapping, crop and forest monitoring, mineral exploration, urban development, ocean and coastlines resources surveillance, and in the monitoring and assessment of floods, droughts, forest fires, landslides and earthquakes. Thus, remote sensing has made great contributions to the socio-economic development of the world and it is anticipated that it will provide more powerful support in advancing the fields of Earth systems science and global change research. The 35th ISRSE was a platform for scientists and