Remote sensing information is increasingly being used to quantitatively improve an understanding of how the Earth functions as an ecosystem. Monitoring of vegetation change has become one of the most popular areas of research in multispectral satellite remote sensing applications. Considerable effort has been given to the discrimination of ecosystem succession, seasonal changes, and disturbance...

This study uses derivative spectroscopy to assess qualitative and quantitative information regarding seafloor types that can be extracted from hyperspectral remote sensing reflectance signals. Carbonate sediments with variable concentrations of microbial pigments were used as a model system. Reflectance signals measured directly over sediment bottoms were compared with remotely sensed data from...

Hyperspectral remote sensing images are consisted of several hundreds of contiguous spectral bands that can provide very rich information and has the potential to differentiate land cover classes with similar spectral characteristics. LIDAR data gives detailed height information and thus can be used complementary with Hyperspectral data. In this work, a hyperspectral image is combined with LIDA...

Hyperspectral imaging, due to providing high spectral resolution images, is one of the most important tools in the remote sensing field. Because of technological restrictions hyperspectral sensors has a limited spatial resolution. On the other hand panchromatic image has a better spatial resolution. Combining this information together can provide a better understanding of the target scene. Spec...

Hyperspectral imaging, due to providing high spectral resolution images, is one of the most important tools in the remote sensing field. Because of technological restrictions hyperspectral sensors has a limited spatial resolution. On the other hand panchromatic image has a better spatial resolution. Combining this information together can provide a better understanding of the target scene. Spec...

This paper presents a new kernel framework for hyperspectral images classification. In this paper, a new feature extraction algorithm based on wavelet kernel non-negative matrix factorization (WKNMF) for hyperspectral remote sensing images is proposed. By using the feature of multi-resolution analysis, the new method can improve the nonlinear mapping capability of kernel non-negative matrix fac...

rice cultivated areas and yield information is indispensable for sustainable management and economic policy making for this strategic food crop. introduction of high spectral and special resolution satellite data has enabled production of such information in a timely and accurate manner. knowledge of the spectral reflectance of various land covers is a prerequisite for their identification and ...

Amazônia contains vast stores of carbon in high-diversity ecosystems, yet this region undergoes major changes in precipitation affecting land use, carbon dynamics, and climate. The extent and structural complexity of Amazon forests impedes ground studies of ecosystem functions such as net primary production (NPP), water cycling, and carbon sequestration. Traditional modeling and remote-sensing ...