Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"time series of Landsat"”.
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Assessing annual urban change and its impacts on evapotranspiration
… Land Cover Change (LULCC) is a major component of global environmental change, which could result in huge impacts on biodiversity, water yield and quality, climate, soil condition, food security and human welfare. Of all the LULCC types, urbanization is considered to be the most impactful one. …
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Application on Lidar and Time Series Landsat Data for Mapping and Monitoring Wetlands
… over two seasons within the same year. Now that Landsat data are available freely, a multi-temporal approach utilizing images that span multiple seasons and multiple years can potentially be used to characterize wetland dynamics in more detail. In addition, newer remote sensing techniques such as …
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Determining Heat Island Response to Varying Land Cover Changes Between 2004 and 2017 Within the City of Reno, Nevada
The objective of this research was to investigate the role of land cover changes through time in influencing spatial variability of the surface urban heat island of the metropolitan area of Reno-Sparks, Nevada. Free and widely available thermal data from Landsat 7 ETM+ (Enhanced Thematic Mapper …
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Relationships between tree rings and Landsat EVI in the Northeast United States
Changes in the productivity of temperate forests have important implications for atmospheric carbon dioxide (CO2) concentrations, and many efforts have focused on methods to monitor both gross and net primary productivity in temperate forests. Remotely sensed vegetation indices provide spatially …
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A Holistic Analysis for Spatiotemporal Interdependencies of Deforestation, Forest Degradation and Landslide Susceptibility in NE Iran
… study that could visualize different dimensions of anthropogenic-induced forest changes such as forest loss, forest fragmentation, and forest degradation. Besides, the effects of these changes require to be investigated in the natural hazards’ studies in forest regions. This research was …
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Deep learning convolutional neural networks for Landsat-derived land cover mapping
Deep learning is an area of machine learning research that can be applied to image analysis and feature extraction. It uses neural networks (NNs) with many layers (hence deep learning) that can extract feature representations from data and, for example, undertake image segmentation into categorical …
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Deep learning convolutional neural networks for Landsat-derived land cover mapping
Deep learning is an area of machine learning research that can be applied to image analysis and feature extraction. It uses neural networks (NNs) with many layers (hence deep learning) that can extract feature representations from data and, for example, undertake image segmentation into categorical …