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Sensing Data (sensing + data)
Kinds of Sensing Data Selected AbstractsWater Resources Modeling of the Ganges-Brahmaputra-Meghna River Basins Using Satellite Remote Sensing Data,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2009Bushra Nishat Nishat, Bushra and S.M. Mahbubur Rahman, 2009. Water Resources Modeling of the Ganges-Brahmaputra-Meghna River Basins Using Satellite Remote Sensing Data. Journal of the American Water Resources Association (JAWRA) 45(6):1313-1327. Abstract:, Large-scale water resources modeling can provide useful insights on future water availability scenarios for downstream nations in anticipation of proposed upstream water resources projects in large international river basins (IRBs). However, model set up can be challenging due to the large amounts of data requirement on both static states (soils, vegetation, topography, drainage network, etc.) and dynamic variables (rainfall, streamflow, soil moisture, evapotranspiration, etc.) over the basin from multiple nations and data collection agencies. Under such circumstances, satellite remote sensing provides a more pragmatic and convenient alternative because of the vantage of space and easy availability from a single data platform. In this paper, we demonstrate a modeling effort to set up a water resources management model, MIKE BASIN, over the Ganges, Brahmaputra, and Meghna (GBM) river basins. The model is set up with the objective of providing Bangladesh, the lowermost riparian nation in the GBM basins, a framework for assessing proposed water diversion scenarios in the upstream transboundary regions of India and deriving quantitative impacts on water availability. Using an array of satellite remote sensing data on topography, vegetation, and rainfall from the transboundary regions, we demonstrate that it is possible to calibrate MIKE BASIN to a satisfactory level and predict streamflow in the Ganges and Brahmaputra rivers at the entry points of Bangladesh at relevant scales of water resources management. Simulated runoff for the Ganges and Brahmaputra rivers follow the trends in the rated discharge for the calibration period. However, monthly flow volume differs from the actual rated flow by (,) 8% to (+) 20% in the Ganges basin, by (,) 15 to (+) 12% in the Brahmaputra basin, and by (,) 15 to (+) 19% in the Meghna basin. Our large-scale modeling initiative is generic enough for other downstream nations in IRBs to adopt for their own modeling needs. [source] Interactive editing of digital fault modelsCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 12 2010Jordan Van Aalsburg Abstract We describe an application to interactively create and manipulate digital fault maps, either by tracing existing (paper) fault maps created from geological surveys, or by directly observing fault expressions and earthquake hypocenters in remote sensing data such as high-resolution (,100k × 100k elevation postings) digital elevation models with draped color imagery. Such fault maps serve as input data to finite-element-method simulations of fault interactions, and are crucial to understand regional tectonic processes causing earthquakes, and have tentatively been used to forecast future seismic events or to predict the shaking from likely future earthquakes. This fault editor is designed for immersive virtual reality environments such as CAVEs, and presents users with visualizations of scanned 2D fault maps and textured 3D terrain models, and a set of 3D editing tools to create or manipulate faults. We close with a case study performed by one of our geologist co-authors (Yikilmaz), which evaluates the use of our fault editor in creating a detailed digital fault model of the North Anatolian Fault in Turkey, one of the largest, seismically active strike-slip faults in the world. Yikilmaz, who was directly involved in program development, used our fault editor both in a CAVE and on a desktop computer, and compares it to the industry-standard software package ArcGIS. Copyright © 2009 John Wiley & Sons, Ltd. [source] Geochemical mapping of carbonate sediments in the Makgadikgadi basin, Botswana using moderate resolution remote sensing dataEARTH SURFACE PROCESSES AND LANDFORMS, Issue 6 2006Kevin White Abstract This paper maps the carbonate geochemistry of the Makgadikgadi Pans region of northern Botswana from moderate resolution (500 m pixels) remotely sensed data, to assess the impact of various geomorphological processes on surficial carbonate distribution. Previous palaeo-environmental studies have demonstrated that the pans have experienced several highstands during the Quaternary, forming calcretes around shoreline embayments. The pans are also a significant regional source of dust, and some workers have suggested that surficial carbonate distributions may be controlled, in part, by wind regime. Field studies of carbonate deposits in the region have also highlighted the importance of fluvial and groundwater processes in calcrete formation. However, due to the large area involved and problems of accessibility, the carbonate distribution across the entire Makgadikgadi basin remains poorly understood. The MODIS instrument permits mapping of carbonate distribution over large areas; comparison with estimates from Landsat Thematic Mapper data show reasonable agreement, and there is good agreement with estimates from laboratory analysis of field samples. The results suggest that palaeo-lake highstands, reconstructed here using the SRTM 3 arc-second digital elevation model, have left behind surficial carbonate deposits, which can be mapped by the MODIS instrument. Copyright © 2006 John Wiley & Sons, Ltd. [source] Net primary productivity mapped for Canada at 1-km resolutionGLOBAL ECOLOGY, Issue 2 2002J Liu Abstract Aim To map net primary productivity (NPP) over the Canadian landmass at 1-km resolution. Location Canada. Methods A simulation model, the Boreal Ecosystem Productivity Simulator (BEPS), has been developed. The model uses a sunlit and shaded leaf separation strategy and a daily integration scheme in order to implement an instantaneous leaf-level photosynthesis model over large areas. Two key driving variables, leaf area index (every 10 days) and land cover type (annual), are derived from satellite measurements of the Advanced Very High Resolution Radiometer (AVHRR). Other spatially explicit input data are also prepared, including daily meteorological data (radiation, precipitation, temperature, and humidity), available soil water holding capacity (AWC) and forest biomass. The model outputs are compared with ground plot data to ensure that no significant systematic biases are created. Results The simulation results show that Canada's annual net primary production was 1.22 Gt C year,1 in 1994, 78% attributed to forests, mainly the boreal forest, without considering the contribution of the understorey. The NPP averaged over the entire landmass was ~140 g C m,2 year,1 in 1994. Geographically, NPP varied greatly among ecozones and provinces/territories. The seasonality of NPP is characterized by strong summer photosynthesis capacities and a short growing season in northern ecosystems. Conclusions This study is the first attempt to simulate Canada-wide NPP with a process-based model at 1-km resolution and using a daily step. The statistics of NPP are therefore expected to be more accurate than previous analyses at coarser spatial or temporal resolutions. The use of remote sensing data makes such simulations possible. BEPS is capable of integrating the effects of climate, vegetation, and soil on plant growth at a regional scale. BEPS and its parameterization scheme and products can be a basis for future studies of the carbon cycle in mid-high latitude ecosystems. [source] Impact of spatial variations of land surface parameters on regional evaporation: a case study with remote sensing dataHYDROLOGICAL PROCESSES, Issue 9 2001Hussein O. Farah Abstract Most precipitation in watersheds is consumed by evaporation, thus techniques to appraise regional evaporation are important to assess the availability of water resources. Many algorithms to estimate evaporation from remotely sensed spectral data have been developed in the recent past. In addition to differences in the physical parameterization of surface fluxes, these algorithms have different solutions for describing spatial variations of the parameters in the soil,vegetation,atmosphere,transfer (SVAT) continuum. In this study, the necessity to spatially distinguish SVAT parameters for computing surface heat fluxes is analysed for the Naivasha watershed in the Kenyan Rift Valley. Landsat Thematic Mapper (TM) spectral data have been used to first delineate the watershed into 15 hydrological units using surface temperature, normalized difference vegetation index and surface albedo as attributes. Thereafter, semi-empirical relationships between these TM-based parameters and other SVAT parameters have been applied to compute the spatial variation of SVAT parameters and the associated evaporation from the different hydrological units. The impact of using watershed-constant or watershed-distributed SVAT parameters on the fluxes is analysed. The determination of watershed averaged evaporation with area-aggregated SVAT parameters is feasible without significant loss of accuracy. Distributed evaporation in heterogeneous watersheds, however, can be investigated only with remote sensing flux algorithms that can account for spatially variable air temperature, surface roughness, surface albedo and the stability correction of the temperature profile due to buoyancy. Erroneous results can be expected if area-aggregated SVAT parameters are used to calculate local evaporation. As most of the recently developed remote sensing flux algorithms are based on areal constant SVAT parameters, direct applications in watersheds are still limited. Copyright © 2001 John Wiley & Sons, Ltd. [source] Using a historical map as a baseline in a land-cover change study of northeast TanzaniaAFRICAN JOURNAL OF ECOLOGY, Issue 2009Lowe Börjeson Abstract Vegetation data in an early 20th century map from northern Tanzania are presented and discussed for its potential of expanding the analytical time-frame in studies of land-use and land-cover change. The starting point is that much research on land-use and land-cover change suffers from a time-frame bias, caused by limitations in remote sensing data. At the same time, the use of historical maps as a complementary data-set is rather insignificant. Can information in historical maps be used to extend the baseline in land-use and land-cover change studies? The historical context of the vegetation data is evaluated, and as an illustration of its potential for interdisciplinary research on land-cover and ecosystems change, a section of the map is juxtaposed with a recent pollen record specifically addressing the impact of a ,large infrequent disturbance' (LID) event at the end of the 19th century. It is concluded that the vegetation data in the map are not likely to be reflecting an extreme situation due to the LID event. Finally, the historical vegetation data were visually compared with a national 1995 land-cover data set, illustrating the possibility of using the map data as a baseline in land-cover change studies. [source] Three-dimensional map building for mobile robot navigation environments using a self-organizing neural networkJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 6 2004Min Young Kim In recent years, mobile robots have been required to become more and more autonomous in such a way that they are able to sense and recognize the three-dimensional space in which they live or work. In this paper, we deal with such an environment map building problem from three-dimensional sensing data for mobile robot navigation. In particular, the problem to be dealt with is how to extract and model obstacles which are not represented on the map but exist in the real environment, so that the map can be newly updated using the modeled obstacle information. To achieve this, we propose a three-dimensional map building method, which is based on a self-organizing neural network technique called "growing neural gas network." Using the obstacle data acquired from the 3D data acquisition process of an active laser range finder, learning of the neural network is performed to generate a graphical structure that reflects the topology of the input space. For evaluation of the proposed method, a series of simulations and experiments are performed to build 3D maps of some given environments surrounding the robot. The usefulness and robustness of the proposed method are investigated and discussed in detail. © 2004 Wiley Periodicals, Inc. [source] Water Resources Modeling of the Ganges-Brahmaputra-Meghna River Basins Using Satellite Remote Sensing Data,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2009Bushra Nishat Nishat, Bushra and S.M. Mahbubur Rahman, 2009. Water Resources Modeling of the Ganges-Brahmaputra-Meghna River Basins Using Satellite Remote Sensing Data. Journal of the American Water Resources Association (JAWRA) 45(6):1313-1327. Abstract:, Large-scale water resources modeling can provide useful insights on future water availability scenarios for downstream nations in anticipation of proposed upstream water resources projects in large international river basins (IRBs). However, model set up can be challenging due to the large amounts of data requirement on both static states (soils, vegetation, topography, drainage network, etc.) and dynamic variables (rainfall, streamflow, soil moisture, evapotranspiration, etc.) over the basin from multiple nations and data collection agencies. Under such circumstances, satellite remote sensing provides a more pragmatic and convenient alternative because of the vantage of space and easy availability from a single data platform. In this paper, we demonstrate a modeling effort to set up a water resources management model, MIKE BASIN, over the Ganges, Brahmaputra, and Meghna (GBM) river basins. The model is set up with the objective of providing Bangladesh, the lowermost riparian nation in the GBM basins, a framework for assessing proposed water diversion scenarios in the upstream transboundary regions of India and deriving quantitative impacts on water availability. Using an array of satellite remote sensing data on topography, vegetation, and rainfall from the transboundary regions, we demonstrate that it is possible to calibrate MIKE BASIN to a satisfactory level and predict streamflow in the Ganges and Brahmaputra rivers at the entry points of Bangladesh at relevant scales of water resources management. Simulated runoff for the Ganges and Brahmaputra rivers follow the trends in the rated discharge for the calibration period. However, monthly flow volume differs from the actual rated flow by (,) 8% to (+) 20% in the Ganges basin, by (,) 15 to (+) 12% in the Brahmaputra basin, and by (,) 15 to (+) 19% in the Meghna basin. Our large-scale modeling initiative is generic enough for other downstream nations in IRBs to adopt for their own modeling needs. [source] Measuring the effects of human impact on vegetation by integrating phytosociology and remote sensing in a fuzzy set approachJOURNAL OF VEGETATION SCIENCE, Issue 5 2003Enrico Feoli Anon. 1954 , Abstract. The response of fragmented vegetation to human impact has been analysed in degraded and degrading areas in Tanzania (Lake Manyara). Phytosociology was integrated with GIS and remote sensing data as follows: (1) a land cover/land use map was obtained by analysing remote sensing data and conducting field verification; (2) phytosociological relevés were randomly sampled in woodland vegetation patches using the map; (3) the pattern of land cover/land use around the relevés was described; (4) gradients of land use intensity (human impact) were obtained based on the descriptions; (5) the response of vegetation types to impacts of gradients was calculated using fuzzy set theory. Two complementary gradients of human impact were defined based on land cover/land use analysis of the remotely sensed data: one related to cultivation intensity and the other to grazing intensity. Response functions of vegetation types (defined by numerical classification) to these gradients demonstrated that the vegetation types are strongly related to the degree of human impact and that the corresponding vegetation patches show different degrees of permeability to the species of the surrounding landscape. [source] Rangeland development of the Mu Us Sandy Land in semiarid China: an analysis using Landsat and NOAA remote sensing dataLAND DEGRADATION AND DEVELOPMENT, Issue 2 2003M. C. Runnström Abstract Degradation of the dry semiarid ecosystems in the Mu Us Sandy Land of north central China was explored using high-resolution satellite images from 1978, 1987 and 1996. This study monitored both changes in grassland biomass production and reclamation activities to detect the nature and scale of land degradation since major economic reforms were introduced in 1978. The position of the high-resolution images within the vegetation cycles was inspected from National Oceanographic and Atmospheric Administration (NOAA) NDVI images at 10-day repetition and seasonal precipitation patterns. A model was developed to categorize changes in the vegetation signal activity from 30,×,30,m pixels into vegetation cover development and land-use changes between 1987 and 1996. A general increase of biomass production was evident despite the rapid increase in numbers of grazing animals. This increase in biomass was confirmed by the NOAA time series, which also revealed annual variability related to the amount and pattern of the seasonal rains. Rangeland conversion to farmland was detected, and this process has increased the area of cultivation almost fivefold. The classified area of cultivation corresponds with reported statistical records, also showing that irrigation features in virtually 100 per cent of the sown area. Signs of declining biological production, indicating land degradation processes, are few. Biomass production has increased, with a gain in the economic output from both crop and animal production. The early start of active measures to halt desertification has increased vegetation cover and lowered wind erosion potential and grasslands seems to be managing the high levels of grazing pressure. Copyright © 2003 John Wiley & Sons, Ltd. [source] Modeling landscape patterns of understory tree regeneration in the Pacific Northwest, USAAPPLIED VEGETATION SCIENCE, Issue 2 2001Michael C. Wimberly Abstract. Vegetation maps serve as the basis for spatial analysis of forest ecosystems and provide initial information for simulations of forest landscape change. Because of the limitations of current remote sensing technology, it is not possible to directly measure forest understory attributes across large spatial extents. Instead we used a predictive vegetation mapping approach to model Tsuga heterophylla and Picea sitchensis seedling patterns in a 3900-ha landscape in the Oregon Coast Range, USA, as a function of Landsat TM imagery, aerial photographs, digital elevation models, and stream maps. Because the models explained only moderate amounts of variability (R2 values of 0.24,0.56), we interpreted the predicted patterns as qualitative spatial trends rather than precise maps. P. sitchensis seedling patterns were tightly linked to the riparian network, with highest densities in coastal riparian areas. T. heterophylla seedlings exhibited complex patterns related to topography and overstory forest cover, and were also spatially clustered around patches of old-growth forest. We hypothesize that the old growth served as refugia for this fire-sensitive species following wildfires in the late 19th and early 20th centuries. Low levels of T. heterophylla regeneration in hardwood-dominated forests suggest that these patches may succeed to shrublands rather than to conifer forest. Predictive models of seedling patterns could be developed for other landscapes where georeferenced inventory plots, remote sensing data, digital elevation models, and climate maps are available. [source] Observed ENSO teleconnections with the South American monsoon systemATMOSPHERIC SCIENCE LETTERS, Issue 1 2010V. Krishnamurthy Abstract This study establishes from observations that there exists a spatially coherent and seasonally persistent association of El Nińo and Southern Oscillation(ENSO) with the South American monsoon variability over a large region that includes central-east part of South America. This result is confirmed using both remote sensing data of outgoing long-wave radiation and in situ rain gauge observations independently. This slowly varying atmospheric pattern has very high daily correlation with the sea surface temperature(SST) over the tropical Pacific and Indian Oceans. The December-to-March seasonal mean of the rainfall is often determined by this ENSO-related pattern. Copyright © 2010 Royal Meteorological Society [source] Dynamical mechanisms controlling the vertical redistribution of dust and the thermodynamic structure of the West Saharan atmospheric boundary layer during summerATMOSPHERIC SCIENCE LETTERS, Issue 1 2009Juan Cuesta Abstract The Saharan atmospheric boundary layer (SABL) plays a significant role in the atmospheric global circulation and directly affects the vertical redistribution of dust originated in the Sahara, the world's largest dust source. Recent measurements have revealed a variety of new dynamical mechanisms that control the structure of the SABL, which are responsible for exchange between the Saharan convective and residual boundary layers. Using new space-borne laser remote sensing data (CALIPSO) and recently published results, we provide an overview of the following known dynamical mechanisms: diurnal vertical mixing, dynamical lifting (density currents and cold air outbreaks) and topographic effects (mountains and albedo anomalies). Copyright © 2009 Royal Meteorological Society [source] | ||||||||||||||||