Reprint

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Edited by
November 2019
262 pages
  • ISBN978-3-03921-756-4 (Paperback)
  • ISBN978-3-03921-757-1 (PDF)

This book is a reprint of the Special Issue Very High Resolution (VHR) Satellite Imagery: Processing and Applications that was published in

Engineering
Environmental & Earth Sciences
Summary

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.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND license
Keywords
road extraction; very high-resolution image; fast marching method; semiautomatic; edge constraint; beaver mimicry; beaver dam analogue; QuickBird; riparian; stream restoration; Worldview; benthic mapping; seagrass; airborne hypespectral imagery; Worldview-2; atmospheric correction; sunglint correction; water column correction; dimensionality reduction techniques; SVM classification; linear unmixing; building detection; built-up areas extraction; local feature points; saliency index; morphological building index; Deformable CNN; Faster R-CNN; data augmentation; occluded object detection; very high-resolution Pléiades imagery; canopy height model; acquisition geometry; forested mountain; accuracy assessment; remote sensing imagery; super-resolution; ultra-dense connection; feature distillation; video satellite; compensation unit; urban water mapping; water index; shadow detection; threshold stability; agriculture parcel segmentation; superpixels; consensus; texture analysis; multi-resolution segmentation (MRS); greenhouse extraction; over-segmentation index (OSI); under-segmentation index (USI); error index of total area (ETA); composite error index (CEI); GaoFen-2 (GF-2); synthetic aperture radar; landslide monitoring; sub-pixel offset tracking; Slumgullion landslide; natural hazards; large displacements; remote sensing; scene classification; CNN; capsule; PrimaryCaps; CapsNet; High-resolution satellite imagery; submesoscale; spiral eddy; cyanobacteria; surface convergence; western Baltic Sea