1,720,969 research outputs found
Modeling heat exchanges at the land-atmosphere interface using multi-angular thermal infrared measurements
No full textKeywords: heat transfer, remote sensing, land surface, soil-foliage canopies, anisotropy, foliage temperature, soil temperature, dual-source model.This thesis describes the use of multi - angular radiometric observations of the terrestrial biosphere to characterize and understand thermal heterogeneity towards better models of heat exchange at the land - atmosphere interface. The models and algorithms described in this thesis have been evaluated using data collected during field experiments inChina,USAandSpain. Radiative and convective processes in the canopy space are described first using a 3D model to deal with realistic canopy architecture. Penetration and interception of direct, diffuse and emitted radiance are treated separately taking into account the spatial organization of canopy elements and the angular distribution of leaves. This model is used to analyze the relation between the anisotropy of exitance and the thermal heterogeneity of vegetation canopies. Simpler models of TopOfCanopy (TOC) radiance as a linear mixture of radiance emitted by either four or two canopy components are proposed in view of current Top Of Atmosphere (TOA) bi- angular observations of emittance by space - borne radiometers such as Along Track Scanning Radiometer (ATSR)-2 and Advanced ATSR (AATSR). Comparison with multi-angular, multi - temporal measurements of exitance proved that the two - components model does reproduces observed anisotropy. The initial 3D model is then used to derive analytically four-, dual- and single heat source models to parameterize heat transfer at the land - atmosphere interface. Assumptions necessary to arrive at these parameterizations are identified to document how the parameterizations account for the radiative and convective processes described in detail by the initial 3D model. Field measurements proved that the dual source model agrees with sensible heat flux density better than single source models, independently of the parameterization of the heat transfer resistance. As regards single source models, the best results were obtained with a parameterization of the resistance dependent on the anisotropy of exitance. A novel algorithm has been developed to retrieve soil and foliage component temperatures from the bi-angular observations provided by the ATSR-2 and AATSR systems. This algorithms makes optimal use of information contained in the four spectral channels in the VISible, Near InfraRed and Short Wave InfraRed regions and in the two spectral channels in the Thermal InfraRed region at two view angles to retrieve simultaneously atmospheric column water vapor, aerosols optical depth, vegetation fractional cover, soil and foliage component temperatures. Values of TOC radiance are obtained after correction of atmospheric effects,thenused to invert the simple two - component model to retrieve soil and foliage component temperatures. Agreement with detailed contact and radiometric ground measurements of soil and foliage temperatures was very good. At larger spatial scales the algorithm has been validated in detail with simulated TOA and TOC image data. Direct validation of retrieved soil and foliage temperatures from ATSR-2 observations was less detailed because of the large ATSR footprint, compounded by the large difference between footprint size and shape in the nadir and forward views. At the regional scale sensible heat flux density was modeled using bi-angular ATSR-2 observations of exitance and compared with measurements by Large Aperture Scintillometers at a spatial scale comparable with the ATSR-2 spatial resolution. Agreement was very good and within the accuracy of the Scintillometers
Modeling heat exchanges at the land-atmosphere interface using multi-angular thermal infrared measurements
No full textKeywords: heat transfer, remote sensing, land surface, soil-foliage canopies, anisotropy, foliage temperature, soil temperature, dual-source model.This thesis describes the use of multi - angular radiometric observations of the terrestrial biosphere to characterize and understand thermal heterogeneity towards better models of heat exchange at the land - atmosphere interface. The models and algorithms described in this thesis have been evaluated using data collected during field experiments inChina,USAandSpain. Radiative and convective processes in the canopy space are described first using a 3D model to deal with realistic canopy architecture. Penetration and interception of direct, diffuse and emitted radiance are treated separately taking into account the spatial organization of canopy elements and the angular distribution of leaves. This model is used to analyze the relation between the anisotropy of exitance and the thermal heterogeneity of vegetation canopies. Simpler models of TopOfCanopy (TOC) radiance as a linear mixture of radiance emitted by either four or two canopy components are proposed in view of current Top Of Atmosphere (TOA) bi- angular observations of emittance by space - borne radiometers such as Along Track Scanning Radiometer (ATSR)-2 and Advanced ATSR (AATSR). Comparison with multi-angular, multi - temporal measurements of exitance proved that the two - components model does reproduces observed anisotropy. The initial 3D model is then used to derive analytically four-, dual- and single heat source models to parameterize heat transfer at the land - atmosphere interface. Assumptions necessary to arrive at these parameterizations are identified to document how the parameterizations account for the radiative and convective processes described in detail by the initial 3D model. Field measurements proved that the dual source model agrees with sensible heat flux density better than single source models, independently of the parameterization of the heat transfer resistance. As regards single source models, the best results were obtained with a parameterization of the resistance dependent on the anisotropy of exitance. A novel algorithm has been developed to retrieve soil and foliage component temperatures from the bi-angular observations provided by the ATSR-2 and AATSR systems. This algorithms makes optimal use of information contained in the four spectral channels in the VISible, Near InfraRed and Short Wave InfraRed regions and in the two spectral channels in the Thermal InfraRed region at two view angles to retrieve simultaneously atmospheric column water vapor, aerosols optical depth, vegetation fractional cover, soil and foliage component temperatures. Values of TOC radiance are obtained after correction of atmospheric effects,thenused to invert the simple two - component model to retrieve soil and foliage component temperatures. Agreement with detailed contact and radiometric ground measurements of soil and foliage temperatures was very good. At larger spatial scales the algorithm has been validated in detail with simulated TOA and TOC image data. Direct validation of retrieved soil and foliage temperatures from ATSR-2 observations was less detailed because of the large ATSR footprint, compounded by the large difference between footprint size and shape in the nadir and forward views. At the regional scale sensible heat flux density was modeled using bi-angular ATSR-2 observations of exitance and compared with measurements by Large Aperture Scintillometers at a spatial scale comparable with the ATSR-2 spatial resolution. Agreement was very good and within the accuracy of the Scintillometers
Water productivity analysis from field to regional scale
Full text linkKeywords: distributed modelling, inverse modelling, data assimilation, irrigation water management, salinization, Bhakra Irrigation System,India.In agricultural production systems, a profound water productivity analysis requires quantification of different hydrological variables such as transpiration, evapotranspiration and percolation, and biophysical variables such as dry matter and grain (or seed) production in relation to different irrigation and agricultural management practices.Sirsa district, located in the Bhakra Irrigation System in Haryana (India), has been selected for a case study. The study area, covering 0.42 million ha, is characterized by typical problems of canal water scarcity, poor groundwater quality, rising and declining groundwater levels, waterlogging and secondary salinization, and less than optimal crop production.The field scale ecohydrological Soil-Water-Atmosphere-Plant (SWAP) model when coupled with field experiments, remote sensing and GIS as used in this study, increases the capabilities of reliable simulation of water productivity from field to regional scale.SWAP was calibrated and validated using the observations at different farmer fields representing various combinations of soil, crop, and irrigation amount and its quality. Inverse modelling was used to determine indirectly the soil hydraulic parameters at fieldscale,and the observed soil moisture and salinity profiles were used as system response. The calibrated and validated SWAPincluding detailed crop growth simulations was extended in a distributed mode to quantify the required hydrological and biophysical variables at regional scale. Field experiments, satellite images and existing geographical data were used to derive and aggregate the input parameters and boundary conditions at the appropriate scales. The accuracy and reliability of spatial aggregation of representative input parameters was determined by comparingthe evapotranspiration simulated by distributed SWAP modelling withindependent satellite remote sensing basedevapotranspirationdata at different spatial and temporal scales.The water productivity WP was computed for different scales and in different forms viz., crop yield per unit amount of water used in transpiration T , evapotranspiration ET , or ET plus percolation from field irrigations and seepage losses from the conveyance system. Considerable spatial variation in WP values was observed not only for different crops but also for the same crop. For instance, the WPET , expressed in the terms of grain yield per unit amount of ET , for wheat varied from 1.22 to 1.56 kg m -3 among different farmer fields monitored in Sirsa district during the agricultural year 2001-02. At field scale, the average WPET (kg m -3 ) was 1.39 for wheat, 0.94 for rice and 0.23 for cotton, and represents its average values for the climatic and growing conditions in Northwest India. Factors responsible for low values of WP include a high share (20 to 40%) of soil evaporation into ET for rice, percolation from fields and seepage losses (34 to 43% of the total canal inflow) from the conveyance system. The simulated water and salt limited crop yields were higher than the recorded crop yields, and indicate substantial nutritional, pest and disease stresses. Also, the study revealed a considerable fluctuation of the estimated net groundwater recharge and salt build-up over the main canal commands in Sirsa district. Better crop management, reduction in seepage losses and canal water reallocation (15%) from the northern to the central canal commands are recommended to improve the WP , and to halt the rising and declining groundwater levels.Although ecohydrological models offer predictions for the future, they may become inaccurate due to over- or underparameterisation, especially in case of distributed modelling at regional scale. Therefore,a sequential ' updating ' algorithm has been developed to improve the simulated total dry matter production in SWAP, whenever an observation of total dry matter production is available.</span
Propagation of drought through groundwater systems
Full text linkIndex words: drought, groundwater, simulation, synthetic data, extreme eventsThe transformation of droughts as a result of the propagation through groundwater systems is examined by comparing droughts in time series of groundwater recharge, levels and discharge. The groundwater system was simulated mostly as a reservoir, characterised by a reservoir coefficient j (d). Different aquifer characteristics were simulated using a range of j-values. A groundwater system causes attenuation and increasing persistence in the discharge. The attenuation decreases the drought severity, whereas the increasing persistence makes the cumulative probability distribution of both drought duration and severity steeper. This means that recharge and discharge from fast responding catchments (small j) have a large number of relativelyunseveredroughts, whereas slowly responding catchments have fewer droughts, but a larger probability of severe droughts. To evaluate the overall performance of the groundwater system with respect to drought, a new performance criterion has been introduced. This criterion shows that groundwater reservoirs with intermediately fast response (j approximately 200 d) have the lowest overall performance. The highest overall performance occurs for slowly responding systems. The influence of the characteristics of the recharge has been examined by using recharge from two catchments: the sub-humid Pangcatchment(UK) and the semi-arid Upper-Guadianacatchment(ES). The most important difference between the two catchments with respect to the propagation of drought is the difference in seasonality. The strong seasonality for the Pang prevents the pooling of droughts. For the semi-aridcatchment, the increase in the number of severe droughts as a result of the propagation through the groundwater system was much higher and thus the overall performance was much lower. For the Pangcatchment, a physically based groundwater flow model was used to examine the spatial distribution of drought. After normalising the groundwater levels with the standard deviation, the variations in the persistence dominate the drought behaviour in the groundwater levels. Thus the cumulative probabilitydistributionclose to the stream was less steep than at the interfluves. Finally, non-linearity in the groundwater level-discharge relationship increases the drought duration and, for most droughts, the severity
Tropical forest mapping using polarimetric and interferometric SAR data
Full text linkA study was made of the potential of the combined use of C-, L- and P-band polarimetric and C- and L-band interferometric airborne SAR data for tropical forest mapping. These data were collected with the NASA/JPL AirSAR during the PacRim-2 2000 campaign in Indonesia. The Sungai Wain forest reserve and its surrounding area near Balikpapan city, located in the province of East-Kalimantan, Indonesia, was chosen as study site. This site covers an area of 10 x 60 km2, which consists of a wide variety and complex mosaic of vegetation and land cover types. Extensive and detailed ground data measurements were made.The approach presented in this thesis includes new elements such as (1) slope correction, using InSAR, (2) mapping, using a new reversible transform technique and (3) Iterated Conditional Modes (ICM), using prior knowledge such as height and texture. The C-band InSAR DEM allowed for a correction of the disturbing effects of relief on the backscatter level. The new method based on a reversible transform of the covariance matrix was introduced to describe the full polarimetric information of land cover type target properties, allowing for the development of simple and robust classifiers. The ICM approach was extended using additional information such as 3-D textural information derived from the InSAR DEM. This approach was demonstrated using a substantial ground truth data set of land cover observations; the result was then validated using a large independent data set with a different legend structure. The results show that most land cover types can be accurately mapped. The land cover classification result reached 88.9% accuracy for a commonly used legend, while for the independent data set, using a 'radar' legend with more classes, the result improved to 93.8%. Validation of the results by inter-comparison provided large consistency. The best results of land cover type classification are obtained for the C- and P-band and for the C-, L- and P-band fully polarimetric combinations, for which the additional use of relief correction and texture had no noticeable effects. Biomass data were collected for a large number of forests transects and several non-forest plots. The linear relationships between biomass and the radar responses in C-, L- and P-band were not strong. It is evident that this result is caused by the complexity of vegetation, frequent forest fires and the effect of radar saturation at a certain biomass level.his study has provided the first experiences with this kind of new technology and methodology in Indonesia. It may offer a substantia) contribution to the developments of similar approaches for tropical forest regions in general, especially in those areas where it is difficult to obtain data from optical sensors
Tropical forest mapping at regional scale using the GRFM SAR mosaics over the Amazon in South America
Full text linkThe work described in this thesis concerns the estimation of tropical forest vegetation cover in the Amazon region using as data source a continental scale high resolution (100 m) radar mosaic as data source. The radar mosaic was compiled by the Jet Propulsion Laboratory (NASA JPL) using approximately 2500 JERS-1 L-band scenes acquired in the context of the Global Rain Forest Mapping project by the National Agency for Space Development of Japan (NASDA).A novel classification scheme was developed for this purpose.The underpinning method is based on a wavelet signal decomposition/reconstruction technique. In the wavelet reconstruction algorithm, an adaptive wavelet coefficient threshold is introduced to distinguish wavelet maxima related to the transition between classes from maxima related to textural within-class variation.Two image-labeling techniquesare tested and compared: i) a region-growing algorithm and ii) a per-pixel two-stage hybrid classifier.The large data volume problem was tackled by developing a special purpose processing chain that works on partially overlapping tiles extracted from the mosaicQuantitative validation and error analysis of the classifiers' performance and their generalization capability to regional scale are carried out using, as reference, maps derived from Landsat Thematic Mapper. A first result of the validation process is that the wavelet classifier provides a classification accuracy of 87% in forest/non-forest mapping. The analysis by site reveals that class degraded-forest is the major source of classification errors. The discrepancy between TM maps and SAR maps increases with increasing landscape spatial fragmentation.A test on relative performances between the wavelet-based region growing segmentation technique and a conventional clustering technique (ISODATA) shows that the wavelet-based technique provides better accuracy and is capable of generalizing over the entire data set.The issue of detecting the degraded-forest class - generally ignored by Amazonian deforestation mapping programs - is tackled using data acquired by both optical and SAR instruments . For optical data, a three-stage classification procedure is developed for detecting degraded forest classes in Landsat TM images. For SAR data, a multi-temporal speckle filtering technique is used to improve the signal to noise ratio.Forestdegradation, characterized by small isolated and elongated bare soil regions regularly distributed in forest areas, is visually detectable in the filtered imagery.Starting from the consideration that the discrepancy between TM maps and SAR maps increases with the landscape spatial fragmentation we test an inductive learning methodology, capable of correcting SAR regional-scale maps using local classification estimates at a higher resolution , is tested.Finally some ideas and projects are put forward which are meant to be working hypotheses for future actions and practical approaches to reduce the pressure over the tropical forest ecosystem
Water productivity analysis from field to regional scale
No full textKeywords: distributed modelling, inverse modelling, data assimilation, irrigation water management, salinization, Bhakra Irrigation System,India.In agricultural production systems, a profound water productivity analysis requires quantification of different hydrological variables such as transpiration, evapotranspiration and percolation, and biophysical variables such as dry matter and grain (or seed) production in relation to different irrigation and agricultural management practices.Sirsa district, located in the Bhakra Irrigation System in Haryana (India), has been selected for a case study. The study area, covering 0.42 million ha, is characterized by typical problems of canal water scarcity, poor groundwater quality, rising and declining groundwater levels, waterlogging and secondary salinization, and less than optimal crop production.The field scale ecohydrological Soil-Water-Atmosphere-Plant (SWAP) model when coupled with field experiments, remote sensing and GIS as used in this study, increases the capabilities of reliable simulation of water productivity from field to regional scale.SWAP was calibrated and validated using the observations at different farmer fields representing various combinations of soil, crop, and irrigation amount and its quality. Inverse modelling was used to determine indirectly the soil hydraulic parameters at fieldscale,and the observed soil moisture and salinity profiles were used as system response. The calibrated and validated SWAPincluding detailed crop growth simulations was extended in a distributed mode to quantify the required hydrological and biophysical variables at regional scale. Field experiments, satellite images and existing geographical data were used to derive and aggregate the input parameters and boundary conditions at the appropriate scales. The accuracy and reliability of spatial aggregation of representative input parameters was determined by comparingthe evapotranspiration simulated by distributed SWAP modelling withindependent satellite remote sensing basedevapotranspirationdata at different spatial and temporal scales.The water productivity WP was computed for different scales and in different forms viz., crop yield per unit amount of water used in transpiration T , evapotranspiration ET , or ET plus percolation from field irrigations and seepage losses from the conveyance system. Considerable spatial variation in WP values was observed not only for different crops but also for the same crop. For instance, the WPET , expressed in the terms of grain yield per unit amount of ET , for wheat varied from 1.22 to 1.56 kg m -3 among different farmer fields monitored in Sirsa district during the agricultural year 2001-02. At field scale, the average WPET (kg m -3 ) was 1.39 for wheat, 0.94 for rice and 0.23 for cotton, and represents its average values for the climatic and growing conditions in Northwest India. Factors responsible for low values of WP include a high share (20 to 40%) of soil evaporation into ET for rice, percolation from fields and seepage losses (34 to 43% of the total canal inflow) from the conveyance system. The simulated water and salt limited crop yields were higher than the recorded crop yields, and indicate substantial nutritional, pest and disease stresses. Also, the study revealed a considerable fluctuation of the estimated net groundwater recharge and salt build-up over the main canal commands in Sirsa district. Better crop management, reduction in seepage losses and canal water reallocation (15%) from the northern to the central canal commands are recommended to improve the WP , and to halt the rising and declining groundwater levels.Although ecohydrological models offer predictions for the future, they may become inaccurate due to over- or underparameterisation, especially in case of distributed modelling at regional scale. Therefore,a sequential ' updating ' algorithm has been developed to improve the simulated total dry matter production in SWAP, whenever an observation of total dry matter production is available
Spaceborne radar monitoring of forest fires and forest cover change : a case study in Kalimantan
Full text linkThe devastation of tropical rain forests has been proven to have a significant effect on global climate change. The sustainability of these forests becomes a major concern for the international community. The Indonesian Ministry of Forestry (MOF) is eager to carry on forest inventory activities and to generate forest resources information.Advanced spaceborne radar techniques are a very promising tool to monitor forests. This technique is complementary with the existing spaceborne optical imagery which suffers too much from cloud cover. Radar provide reliable information on a regular basis and has been applied in various types of applications e.g. forest classification.The approach presented in this thesis includes. Firstly, multi-temporal classification of spaceborne Synthetic Aperture Radar (SAR) data using Iterated Conditional Modes which is proposed as a fast step of Maximum Likelihood classification in order to circumvent the slow image segmentation step. Secondly, slope correction dealing with steep slopes that considerable has geometric distortion. Thirdly, textural analysis has been applied to derive additional information layers in multi-temporal classification from fine structures in the radar images.The study focuses on three test site areas i.e. Sungai Wain test site area, the Gunung Meratustest site area and the NASA AirSAR PacRim-II test site area.This area experienced long drought periods associated with the El Niño Southern Oscillation (ENSO)phenomenon. For this study the severe ENSO event of 1997 - 1998 is of particular interest.Forestfires occur almost every year in this test site area, however,each event is specific in intensity and extent. A longer time series ofradar images takes every event observations into account.The results show high accuracy ranging from 85.2% to 98.8% for almost all land cover types. Slope correction has positive effect, but in accuracy does not seem to be very high. It is showed that the induced slope correction is around 1 dB while values up to 10 dB were expected. The resolution of the digital elevation model is an important factor for the correction of relief in spaceborne SAR data. When the resolution is too coarse, i.e. spatial features of slope correction are coarser than the actual structures; the pattern of relief will be flattened out. Utilization of textural features yields a significant improvement of overall classification accuracy, which increases from 36.5% to 48.5%.The approach developed for the Gunung Meratus has a wide applicability. This approach seemed to be sufficiently mature to apply it for others areas, for example the Mawas and Sebangau peat swamp forest area. This methodology of radar monitoring system may have the potential to become the core system for 'fast illegal logging response' within the Indonesian MOF.The implementation of the SAR monitoring for the Indonesian MOF is speeding up the ongoing decentralization policy. Recommendations are offered here to the Indonesian MOF, particularly for local authorities to enhance their capability in providing fast, accurate, and reliable information on forest condition. This capability will ensure the sustainability of the remaining tropical rain forest in the country
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