Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satell...Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.展开更多
Remote sensing and climate digital products have become increasingly available in recent years.Access to these products has favored a variety of Digital Earth studies,such as the analysis of the impact of global warmi...Remote sensing and climate digital products have become increasingly available in recent years.Access to these products has favored a variety of Digital Earth studies,such as the analysis of the impact of global warming over different biomes.The study of the Amazon forest response to drought has recently received particular attention from the scientific community due to the occurrence of extreme droughts and anomalous warming over the last decade.This paper focuses on the differences observed between surface thermal anomalies obtained from remote sensing moderate resolution imaging spectroradiometer(MODIS)and climatic(ERA-Interim)monthly products over the Amazon forest.With a few exceptions,results show that the spatial pattern of standardized anomalies is similar for both products.In terms of absolute anomalies,the differences between the two products show a bias near to zero with a standard deviation of around 0.2 K,although the differences can be up to 1 K over particular regions and months.Despite this general agreement,the proper filtering of MODIS daily values in order to construct a new monthly product showed a dramatic reduction in the number of reliable pixels during the rainy season,while for the dry season this reduction is only seen in Northern Amazonia.展开更多
文摘Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.
基金funded by the University of Valencia[UV-INV-PRECOMP13-115366]Ministerio de Ciencia e Innovación[CEOS-Spain,AYA2011-29334-C02-01],CONICYT[Fondecyt Iniciacion–1130359]the University of Chile[Ayuda U Viajes,VID-Uchile 2014–2015].
文摘Remote sensing and climate digital products have become increasingly available in recent years.Access to these products has favored a variety of Digital Earth studies,such as the analysis of the impact of global warming over different biomes.The study of the Amazon forest response to drought has recently received particular attention from the scientific community due to the occurrence of extreme droughts and anomalous warming over the last decade.This paper focuses on the differences observed between surface thermal anomalies obtained from remote sensing moderate resolution imaging spectroradiometer(MODIS)and climatic(ERA-Interim)monthly products over the Amazon forest.With a few exceptions,results show that the spatial pattern of standardized anomalies is similar for both products.In terms of absolute anomalies,the differences between the two products show a bias near to zero with a standard deviation of around 0.2 K,although the differences can be up to 1 K over particular regions and months.Despite this general agreement,the proper filtering of MODIS daily values in order to construct a new monthly product showed a dramatic reduction in the number of reliable pixels during the rainy season,while for the dry season this reduction is only seen in Northern Amazonia.
