Tools and libraries for processing satellite images (push-broom, frame and push-frame), including rigorous sensor model (RSM) refinement, rational function model (RFM) refinement, orthorectification, sub-pixel image correlation, and 3D surface displacement extraction. ...
For example, the resolution of TM Landsat remote sensing images in the United States is 29 m, that of the SPOT satellite in France is 10 m, and that of the IKONOS satellite is 1 m. The characteristics of rich ground information reflected by satellite remote sensing images and the ability ...
This project is reliant upon the use of remote sensing for the detection and delineation of landslides. Therefore optical satellite images, such as medium resolution ASTER, and high resolution SPOT 5, will be combined with topographic data to analyse the landslide prone areas. The specific ...
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This study aims to delineate landslide susceptibility maps using the Analytical Hierarchy Process (AHP) method for the Great Xi’an Region, China, which is a key planning project for urban construction in Shaanxi Province, China from 2021 to 2035. Multiple data as elevation, slope, aspect, curva...
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We used only the LOS mean velocity fields calculated from the Sentinel 1 A/B images, which cover the same time interval. Initially, we resampled the mean LOS velocities for the ascending and descending tracks onto a similar grid with 100‐m pixel spacing using a nearest neighbor procedure to...
satellite SAR images were processed to produce both SqueeSAR™ and Temporary Coherent Scatterers data, which are PSI (Persistent Scatterer Interferometry) data conceived as evolution of PSInSAR™ approach and particularly suited for non-urban and rural areas characterized by low density of coherent ...
VK also thank people of Urni and Tapri town, Kinnaur for helpful discussion during field. SLC acknowledges the financial help by the Indian Space Research Organization (ISRO) through TDP project for debris flow modelling. We are thankful to the Editorial Advisor (Prof. M. Santosh), Associate ...
However, these models fail for images with intricate textures and intensive spectral heterogeneity (Goetz et al. 2015). Thus, machine learning (ML) models such as decision trees, support vector machines (SVMs), artificial neural networks (ANN), and random forest (RF) are applied to address ...