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

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...

Full description

Saved in:
Bibliographic Details
:
Year of Publication:2019
Language:English
Physical Description:1 electronic resource (262 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993548211204498
ctrlnum (CKB)4100000010106242
(oapen)https://directory.doabooks.org/handle/20.500.12854/62022
(EXLCZ)994100000010106242
collection bib_alma
record_format marc
spelling Marcello, Javier auth
Very High Resolution (VHR) Satellite Imagery: Processing and Applications
Very High Resolution
MDPI - Multidisciplinary Digital Publishing Institute 2019
1 electronic resource (262 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
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.
English
very high-resolution Pléiades imagery
surface convergence
data augmentation
acquisition geometry
SVM classification
urban water mapping
beaver dam analogue
agriculture parcel segmentation
morphological building index
airborne hypespectral imagery
sunglint correction
water index
over-segmentation index (OSI)
High-resolution satellite imagery
multi-resolution segmentation (MRS)
GaoFen-2 (GF-2)
benthic mapping
scene classification
greenhouse extraction
edge constraint
Deformable CNN
built-up areas extraction
ultra-dense connection
seagrass
beaver mimicry
forested mountain
natural hazards
remote sensing
dimensionality reduction techniques
road extraction
landslide monitoring
Slumgullion landslide
synthetic aperture radar
building detection
Worldview-2
saliency index
under-segmentation index (USI)
texture analysis
fast marching method
video satellite
CNN
capsule
super-resolution
feature distillation
shadow detection
PrimaryCaps
semiautomatic
compensation unit
superpixels
riparian
QuickBird
submesoscale
linear unmixing
accuracy assessment
composite error index (CEI)
cyanobacteria
local feature points
Faster R-CNN
occluded object detection
error index of total area (ETA)
large displacements
threshold stability
remote sensing imagery
water column correction
canopy height model
spiral eddy
sub-pixel offset tracking
consensus
stream restoration
western Baltic Sea
Worldview
very high-resolution image
CapsNet
atmospheric correction
3-03921-756-9
Eugenio, Francisco auth
language English
format eBook
author Marcello, Javier
spellingShingle Marcello, Javier
Very High Resolution (VHR) Satellite Imagery: Processing and Applications
author_facet Marcello, Javier
Eugenio, Francisco
author_variant j m jm
author2 Eugenio, Francisco
author2_variant f e fe
author_sort Marcello, Javier
title Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_full Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_fullStr Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_full_unstemmed Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_auth Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_alt Very High Resolution
title_new Very High Resolution (VHR) Satellite Imagery: Processing and Applications
title_sort very high resolution (vhr) satellite imagery: processing and applications
publisher MDPI - Multidisciplinary Digital Publishing Institute
publishDate 2019
physical 1 electronic resource (262 p.)
isbn 3-03921-757-7
3-03921-756-9
illustrated Not Illustrated
work_keys_str_mv AT marcellojavier veryhighresolutionvhrsatelliteimageryprocessingandapplications
AT eugeniofrancisco veryhighresolutionvhrsatelliteimageryprocessingandapplications
AT marcellojavier veryhighresolution
AT eugeniofrancisco veryhighresolution
status_str n
ids_txt_mv (CKB)4100000010106242
(oapen)https://directory.doabooks.org/handle/20.500.12854/62022
(EXLCZ)994100000010106242
carrierType_str_mv cr
is_hierarchy_title Very High Resolution (VHR) Satellite Imagery: Processing and Applications
author2_original_writing_str_mv noLinkedField
_version_ 1796648759932747776
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05141nam-a2201177z--4500</leader><controlfield tag="001">993548211204498</controlfield><controlfield tag="005">20231214132942.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr|mn|---annan</controlfield><controlfield tag="008">202102s2019 xx |||||o ||| 0|eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3-03921-757-7</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)4100000010106242</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/62022</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)994100000010106242</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Marcello, Javier</subfield><subfield code="4">auth</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Very High Resolution (VHR) Satellite Imagery: Processing and Applications</subfield></datafield><datafield tag="246" ind1=" " ind2=" "><subfield code="a">Very High Resolution </subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">MDPI - Multidisciplinary Digital Publishing Institute</subfield><subfield code="c">2019</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 electronic resource (262 p.)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">very high-resolution Pléiades imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">surface convergence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data augmentation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">acquisition geometry</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">SVM classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">urban water mapping</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">beaver dam analogue</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">agriculture parcel segmentation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">morphological building index</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">airborne hypespectral imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sunglint correction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">water index</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">over-segmentation index (OSI)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">High-resolution satellite imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multi-resolution segmentation (MRS)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">GaoFen-2 (GF-2)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">benthic mapping</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">scene classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">greenhouse extraction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">edge constraint</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Deformable CNN</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">built-up areas extraction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">ultra-dense connection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">seagrass</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">beaver mimicry</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">forested mountain</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">natural hazards</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">remote sensing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">dimensionality reduction techniques</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">road extraction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">landslide monitoring</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Slumgullion landslide</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">synthetic aperture radar</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">building detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Worldview-2</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">saliency index</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">under-segmentation index (USI)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">texture analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">fast marching method</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">video satellite</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">CNN</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">capsule</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">super-resolution</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">feature distillation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">shadow detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">PrimaryCaps</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">semiautomatic</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">compensation unit</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">superpixels</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">riparian</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">QuickBird</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">submesoscale</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">linear unmixing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">accuracy assessment</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">composite error index (CEI)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cyanobacteria</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">local feature points</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Faster R-CNN</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">occluded object detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">error index of total area (ETA)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">large displacements</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">threshold stability</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">remote sensing imagery</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">water column correction</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">canopy height model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spiral eddy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sub-pixel offset tracking</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">consensus</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">stream restoration</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">western Baltic Sea</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Worldview</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">very high-resolution image</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">CapsNet</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">atmospheric correction</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-03921-756-9</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Eugenio, Francisco</subfield><subfield code="4">auth</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-12-15 05:37:44 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2020-02-01 22:26:53 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5338735950004498&amp;Force_direct=true</subfield><subfield code="Z">5338735950004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338735950004498</subfield></datafield></record></collection>