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

Marcello, Javier; Eugenio, Francisco

doi:10.3390/books978-3-03921-757-1

dc.contributor.author	Marcello, Javier	*
dc.contributor.author	Eugenio, Francisco	*
dc.date.accessioned	2021-02-12T07:35:59Z
dc.date.available	2021-02-12T07:35:59Z
dc.date.issued	2019	*
dc.date.submitted	2019-12-09 11:49:16	*
dc.identifier	42624	*
dc.identifier.uri	https://directory.doabooks.org/handle/20.500.12854/62022
dc.description.abstract	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.	*
dc.language	English	*
dc.subject	TA1-2040	*
dc.subject	T1-995	*
dc.subject	TA170-171	*
dc.subject.classification	thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology	en_US
dc.subject.other	very high-resolution Pléiades imagery	*
dc.subject.other	surface convergence	*
dc.subject.other	data augmentation	*
dc.subject.other	acquisition geometry	*
dc.subject.other	SVM classification	*
dc.subject.other	urban water mapping	*
dc.subject.other	beaver dam analogue	*
dc.subject.other	agriculture parcel segmentation	*
dc.subject.other	morphological building index	*
dc.subject.other	airborne hypespectral imagery	*
dc.subject.other	sunglint correction	*
dc.subject.other	water index	*
dc.subject.other	over-segmentation index (OSI)	*
dc.subject.other	High-resolution satellite imagery	*
dc.subject.other	multi-resolution segmentation (MRS)	*
dc.subject.other	GaoFen-2 (GF-2)	*
dc.subject.other	benthic mapping	*
dc.subject.other	scene classification	*
dc.subject.other	greenhouse extraction	*
dc.subject.other	edge constraint	*
dc.subject.other	Deformable CNN	*
dc.subject.other	built-up areas extraction	*
dc.subject.other	ultra-dense connection	*
dc.subject.other	seagrass	*
dc.subject.other	beaver mimicry	*
dc.subject.other	forested mountain	*
dc.subject.other	natural hazards	*
dc.subject.other	remote sensing	*
dc.subject.other	dimensionality reduction techniques	*
dc.subject.other	road extraction	*
dc.subject.other	landslide monitoring	*
dc.subject.other	Slumgullion landslide	*
dc.subject.other	synthetic aperture radar	*
dc.subject.other	building detection	*
dc.subject.other	Worldview-2	*
dc.subject.other	saliency index	*
dc.subject.other	under-segmentation index (USI)	*
dc.subject.other	texture analysis	*
dc.subject.other	fast marching method	*
dc.subject.other	video satellite	*
dc.subject.other	CNN	*
dc.subject.other	capsule	*
dc.subject.other	super-resolution	*
dc.subject.other	feature distillation	*
dc.subject.other	shadow detection	*
dc.subject.other	PrimaryCaps	*
dc.subject.other	semiautomatic	*
dc.subject.other	compensation unit	*
dc.subject.other	superpixels	*
dc.subject.other	riparian	*
dc.subject.other	QuickBird	*
dc.subject.other	submesoscale	*
dc.subject.other	linear unmixing	*
dc.subject.other	accuracy assessment	*
dc.subject.other	composite error index (CEI)	*
dc.subject.other	cyanobacteria	*
dc.subject.other	local feature points	*
dc.subject.other	Faster R-CNN	*
dc.subject.other	occluded object detection	*
dc.subject.other	error index of total area (ETA)	*
dc.subject.other	large displacements	*
dc.subject.other	threshold stability	*
dc.subject.other	remote sensing imagery	*
dc.subject.other	water column correction	*
dc.subject.other	canopy height model	*
dc.subject.other	spiral eddy	*
dc.subject.other	sub-pixel offset tracking	*
dc.subject.other	consensus	*
dc.subject.other	stream restoration	*
dc.subject.other	western Baltic Sea	*
dc.subject.other	Worldview	*
dc.subject.other	very high-resolution image	*
dc.subject.other	CapsNet	*
dc.subject.other	atmospheric correction	*
dc.title	Very High Resolution (VHR) Satellite Imagery: Processing and Applications	*
dc.type	book
oapen.identifier.doi	10.3390/books978-3-03921-757-1	*
oapen.relation.isPublishedBy	46cabcaa-dd94-4bfe-87b4-55023c1b36d0	*
oapen.relation.isbn	9783039217571	*
oapen.relation.isbn	9783039217564	*
oapen.pages	262	*
oapen.edition	1st	*

Fichier(s) constituant ce document

Fichiers	Taille	Format	Vue
Il n'y a pas de fichiers associés à ce document.

Ce document figure dans la(les) collection(s) suivante(s)

Imported or submitted locally

Afficher la notice abrégée

Excepté là où spécifié autrement, la license de ce document est décrite en tant que https://creativecommons.org/licenses/by-nc-nd/4.0/