TY - BOOK ID - 61122606 TI - Very High Resolution (VHR) Satellite Imagery: Processing and Applications AU - Marcello, Javier AU - Eugenio, Francisco PY - 2019 SN - 3039217577 3039217569 PB - MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - very high-resolution Pléiades imagery KW - surface convergence KW - data augmentation KW - acquisition geometry KW - SVM classification KW - urban water mapping KW - beaver dam analogue KW - agriculture parcel segmentation KW - morphological building index KW - airborne hypespectral imagery KW - sunglint correction KW - water index KW - over-segmentation index (OSI) KW - High-resolution satellite imagery KW - multi-resolution segmentation (MRS) KW - GaoFen-2 (GF-2) KW - benthic mapping KW - scene classification KW - greenhouse extraction KW - edge constraint KW - Deformable CNN KW - built-up areas extraction KW - ultra-dense connection KW - seagrass KW - beaver mimicry KW - forested mountain KW - natural hazards KW - remote sensing KW - dimensionality reduction techniques KW - road extraction KW - landslide monitoring KW - Slumgullion landslide KW - synthetic aperture radar KW - building detection KW - Worldview-2 KW - saliency index KW - under-segmentation index (USI) KW - texture analysis KW - fast marching method KW - video satellite KW - CNN KW - capsule KW - super-resolution KW - feature distillation KW - shadow detection KW - PrimaryCaps KW - semiautomatic KW - compensation unit KW - superpixels KW - riparian KW - QuickBird KW - submesoscale KW - linear unmixing KW - accuracy assessment KW - composite error index (CEI) KW - cyanobacteria KW - local feature points KW - Faster R-CNN KW - occluded object detection KW - error index of total area (ETA) KW - large displacements KW - threshold stability KW - remote sensing imagery KW - water column correction KW - canopy height model KW - spiral eddy KW - sub-pixel offset tracking KW - consensus KW - stream restoration KW - western Baltic Sea KW - Worldview KW - very high-resolution image KW - CapsNet KW - atmospheric correction UR - https://www.unicat.be/uniCat?func=search&query=sysid:61122606 AB - Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing. ER -