The Experts below are selected from a list of 55629 Experts worldwide ranked by ideXlab platform
Pierre Couteron - One of the best experts on this subject based on the ideXlab platform.
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Linear vs non-linear learning methods A comparative study for forest above ground biomass, estimation from texture analysis of satellite images
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, 2017Co-Authors: Hippolyte Tapamo, Adamou Mfopou, Blaise Ngonmang, Pierre Couteron, Olivier MongaAbstract:The aboveground biomass estimation is an important question in the scope of Reducing Emission from Deforestation and Forest Degradation (REDD framework of the UNCCC). It is particularly challenging for tropical countries because of the scarcity of accurate ground forest inventory data and of the complexity of the forests. Satellite-borne remote sensing can help solve this problem considering the increasing availability of optical very high spatial resolution images that provide information on the forest structure via texture analysis of the canopy grain. For example, the FOTO (FOurier Texture Ordination) proved relevant for forest biomass prediction in several tropical regions. It uses PCA and linear regression and, in this paper, we suggest applying classification methods such as k-NN (k-nearest neighbors), SVM (support vector machines) and Random Forests to texture descriptors extracted from images via Fourier spectra. Experiments have been carried out on simulated images produced by the software DART (Discrete Anisotropic Radiative Transfer) in reference to information (3D stand mockups) from forests of DRC (Democratic Republic of Congo), CAR (Central African Republic) and Congo. On this basis, we show that some classification techniques may yield a gain in prediction accuracy of 18 to 20%
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Attenuating the bidirectional texture variation of satellite images of tropical forest canopies
Remote Sensing of Environment, 2015Co-Authors: Nicolas Barbier, Pierre CouteronAbstract:Quantifying and mapping dense tropical forest structure at region to country level have become pressing needs, notably but not exclusively for assessing carbon stocks as part of the Reducing Emission from Deforestation and forest Degradation (REDD +) process. Fourier texture features from very high spatial resolution passive optical data have shown good potential as non-saturating proxies for stand parameters, including above-ground biomass, within required standards of precision and accuracy. These proxies are, however, sensitive to acquisition geometry (sun–view angles), even for acquisition geometries usually in use in VHR sensors, hampering regional or multi-temporal studies combining multiple acquisitions. Our aim was to improve the understanding of this variation formalized in the bidirectional texture function (BTF), and find ways to mitigate it. We used simulated stands and the Discrete Anisotropic Radiative Transfer (DART) model, as well as a collection of Ikonos images over a forest site near Santarem (Para, Brazil). BTF proved dependent on forest structure and displayed strong anisotropy with respect to forward vs. backward scattering modes. But it remained approximately constant over a large range of angular configurations in forward mode, thereby allowing operational use without any correction. This range could be broadened by correcting bias using empirical BTF fitting or (more practically) by inter-calibrating Fourier spectra when some overlap area is available between images. Prediction of a forest structure parameter (View the MathML sourceD̂max, the estimated maximum trunk diameter class) using images in varying configurations then remained unbiased and below 15% relative RMSE except in the vicinity (± 10° in the principal bidirectional plane) of the hotspot direction. Near hotspot directions need to be proscribed, as the absence of visible shadows impedes textural description. These results, and the increasing availability of large swath VHR sensor constellations (e.g. SPOT 6–7), open the way to operational broad scale applications for forest characterization, above-ground biomass mapping and multitemporal degradation monitoring.
Daniel J Ashworth - One of the best experts on this subject based on the ideXlab platform.
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application rate affects the degradation rate and hence Emissions of chloropicrin in soil
Science of The Total Environment, 2018Co-Authors: Daniel J Ashworth, Scott R Yates, Mike Stanghellini, Ian J Van WesenbeeckAbstract:Increasingly stringent regulations to control soil-air Emissions of soil fumigants has led to much research effort aimed at Reducing Emission potential. Using laboratory soil columns, we aimed to investigate the relationship between chloropicrin (CP) application rate and its Emissions from soil across a wide range of CP applications (equivalent to 56-392kgha-1). In contrast to the known behavior of other fumigants, total Emission percentages were strongly and positively related to application rate (i.e., initial mass), ranging from 4 to 34% across the application rate range. When combined, data from a previous study and the present study showed good overall comparability in terms of CP application rate vs. Emission percentage, yielding a second-order polynomial relationship with an R2 value of 0.93 (n=12). The study revealed that mass losses of CP were strongly disproportional to application rate, also showing a polynomial relationship. Based on degradation studies, we consider that a shorter half-life (faster degradation) at lower application rates limited the amount of CP available for Emission. The non-linear relationship between CP application rate and CP Emissions (both as % of that applied and as total mass) suggests that low application rates likely lead to disproportionally low Emission losses compared with higher application rates; such a relationship could be taken into account when assessing/mitigating risk, e.g., in the setting of buffer zone distances.
Nicolas Barbier - One of the best experts on this subject based on the ideXlab platform.
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Attenuating the bidirectional texture variation of satellite images of tropical forest canopies
Remote Sensing of Environment, 2015Co-Authors: Nicolas Barbier, Pierre CouteronAbstract:Quantifying and mapping dense tropical forest structure at region to country level have become pressing needs, notably but not exclusively for assessing carbon stocks as part of the Reducing Emission from Deforestation and forest Degradation (REDD +) process. Fourier texture features from very high spatial resolution passive optical data have shown good potential as non-saturating proxies for stand parameters, including above-ground biomass, within required standards of precision and accuracy. These proxies are, however, sensitive to acquisition geometry (sun–view angles), even for acquisition geometries usually in use in VHR sensors, hampering regional or multi-temporal studies combining multiple acquisitions. Our aim was to improve the understanding of this variation formalized in the bidirectional texture function (BTF), and find ways to mitigate it. We used simulated stands and the Discrete Anisotropic Radiative Transfer (DART) model, as well as a collection of Ikonos images over a forest site near Santarem (Para, Brazil). BTF proved dependent on forest structure and displayed strong anisotropy with respect to forward vs. backward scattering modes. But it remained approximately constant over a large range of angular configurations in forward mode, thereby allowing operational use without any correction. This range could be broadened by correcting bias using empirical BTF fitting or (more practically) by inter-calibrating Fourier spectra when some overlap area is available between images. Prediction of a forest structure parameter (View the MathML sourceD̂max, the estimated maximum trunk diameter class) using images in varying configurations then remained unbiased and below 15% relative RMSE except in the vicinity (± 10° in the principal bidirectional plane) of the hotspot direction. Near hotspot directions need to be proscribed, as the absence of visible shadows impedes textural description. These results, and the increasing availability of large swath VHR sensor constellations (e.g. SPOT 6–7), open the way to operational broad scale applications for forest characterization, above-ground biomass mapping and multitemporal degradation monitoring.
Ian J Van Wesenbeeck - One of the best experts on this subject based on the ideXlab platform.
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application rate affects the degradation rate and hence Emissions of chloropicrin in soil
Science of The Total Environment, 2018Co-Authors: Daniel J Ashworth, Scott R Yates, Mike Stanghellini, Ian J Van WesenbeeckAbstract:Increasingly stringent regulations to control soil-air Emissions of soil fumigants has led to much research effort aimed at Reducing Emission potential. Using laboratory soil columns, we aimed to investigate the relationship between chloropicrin (CP) application rate and its Emissions from soil across a wide range of CP applications (equivalent to 56-392kgha-1). In contrast to the known behavior of other fumigants, total Emission percentages were strongly and positively related to application rate (i.e., initial mass), ranging from 4 to 34% across the application rate range. When combined, data from a previous study and the present study showed good overall comparability in terms of CP application rate vs. Emission percentage, yielding a second-order polynomial relationship with an R2 value of 0.93 (n=12). The study revealed that mass losses of CP were strongly disproportional to application rate, also showing a polynomial relationship. Based on degradation studies, we consider that a shorter half-life (faster degradation) at lower application rates limited the amount of CP available for Emission. The non-linear relationship between CP application rate and CP Emissions (both as % of that applied and as total mass) suggests that low application rates likely lead to disproportionally low Emission losses compared with higher application rates; such a relationship could be taken into account when assessing/mitigating risk, e.g., in the setting of buffer zone distances.
Tiefeng Chen - One of the best experts on this subject based on the ideXlab platform.
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thermal characteristics of dry cooling tower reconstructed from obsolete natural draft wet cooling tower and the relevant thermal system coupling optimization
Applied Thermal Engineering, 2020Co-Authors: Wenjing Ge, Yuanbin Zhao, Wendong Li, Shiwei Song, Tiefeng ChenAbstract:Abstract Natural draft dry cooling tower is attractive in recent decades with its superiority of zero water loss. Some old thermal power plants are under high pressure of waste water Reducing Emission, thus the natural draft wet cooling tower is obsoleted. Reconstructing natural draft wet cooling tower into natural draft dry cooling tower is attractive for the saving of capital expenditure. But it has not been researched before, this study aims to fill this gap. Based on an actual reconstruction case, the operation mode of reconstructed dry cooling system is established and relevant MATLAB programming is realized, which was validated by literature data. The reconstructed system consists of two reconstructed natural draft dry cooling towers, a usual natural draft dry cooling tower and two 660 MW power units. The cooling capacity of reconstructed natural draft dry cooling tower is lower through thermal characteristic comparison with the usual natural draft dry cooling tower. In order to realize the optimal operation, different water distribution schemes are presented and several operation parameters are analyzed. Under the optimized reconstruction design, the annual water saving and annual cost are discussed. The annual water saving is about14.49 million metric tons that is about 8.86 million dollars and the minimum annual cost is about 181.47 million dollars, which brings great economic and environmental benefits.
