東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Remote sensing of vegetation = along...

Bodinger, Christian Julian.

Linked to FindBook

Google Book

Amazon

博客來

Remote sensing of vegetation = along a latitudinal gradient in Chile /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Remote sensing of vegetation/ by Christian Julian Bodinger.
Reminder of title:	along a latitudinal gradient in Chile /
Author:	Bodinger, Christian Julian.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2019.,
Description:	xxiii, 108 p. :ill., digital ;24 cm.
[NT 15003449]:	TanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance -- Machine Learning Using SVMs and Random Forest -- Statistical Time-Series Evaluation -- Maps of Land Use and Cover (LULC) -- Time-Series Showing the Impact of ENSO.
Contained By:	Springer eBooks
Subject:	Geoinformatics. -
Online resource:	https://doi.org/10.1007/978-3-658-25120-8
ISBN:	9783658251208

Remote sensing of vegetation = along a latitudinal gradient in Chile /
Bodinger, Christian Julian.

Remote sensing of vegetationalong a latitudinal gradient in Chile /[electronic resource] :by Christian Julian Bodinger. - Wiesbaden :Springer Fachmedien Wiesbaden :2019. - xxiii, 108 p. :ill., digital ;24 cm. - BestMasters,2625-3577. - BestMasters..

TanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance -- Machine Learning Using SVMs and Random Forest -- Statistical Time-Series Evaluation -- Maps of Land Use and Cover (LULC) -- Time-Series Showing the Impact of ENSO.

How is the vegetation distribution influencing the erosion and surface formation in the different eco zones of Chile? To answer this question, it is mandatory to possess fundamental knowledge about plant species habitats, occurrence and their dynamics. In his study Christian Bodinger utilizes satellite imagery in combination with machine learning to derive maps of land use and land cover (LULC) in four study sites along a climatic gradient and to monitor vegetation using monthly Normalized Difference Vegetation Index (NDVI) time series. The findings contribute to a better understanding of climate impacts on Chilean vegetation and serve as a basis of landscape evolution models. Contents TanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance Machine Learning Using SVMs and Random Forest Statistical Time-Series Evaluation Maps of Land Use and Cover (LULC) Time-Series Showing the Impact of ENSO Target Groups Scientists, lecturers and students in the field of geology and ecology Geoscientists and Ecologists with a focus on remote sensing About the Author Christian Bodinger holds a M.Sc. in Physical Geography from the University of Tubingen, Germany. His focus in research lies on remote sensing and image analysis for environmental applications. He is currently working for a company focusing on aquatic remote sensing.

ISBN: 9783658251208

Standard No.: 10.1007/978-3-658-25120-8doiSubjects--Topical Terms:

3216881
Geoinformatics.

LC Class. No.: QK46.5.R44 / B865 2019

Dewey Class. No.: 580.285

Remote sensing of vegetation = along a latitudinal gradient in Chile /
LDR:02648nmm a2200337 a 4500 001 2178468
003 DE-He213
005 20190625151433.0
006 m d
007 cr nn 008maaau
008 191122s2019 gw s 0 eng d
020 $a 9783658251208 $q (electronic bk.)
020 $a 9783658251192 $q (paper)
024 7 $a 10.1007/978-3-658-25120-8 $2 doi
035 $a 978-3-658-25120-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QK46.5.R44 $b B865 2019
072 7 $a RGW $2 bicssc
072 7 $a TEC036000 $2 bisacsh
072 7 $a RGW $2 thema
082 0 4 $a 580.285 $2 23
090 $a QK46.5.R44 $b B667 2019
100 1 $a Bodinger, Christian Julian. $3 3382726
245 1 0 $a Remote sensing of vegetation $h [electronic resource] : $b along a latitudinal gradient in Chile / $c by Christian Julian Bodinger.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Spektrum, $c 2019.
300 $a xxiii, 108 p. : $b ill., digital ; $c 24 cm.
490 1 $a BestMasters, $x 2625-3577
505 0 $a TanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance -- Machine Learning Using SVMs and Random Forest -- Statistical Time-Series Evaluation -- Maps of Land Use and Cover (LULC) -- Time-Series Showing the Impact of ENSO.
520 $a How is the vegetation distribution influencing the erosion and surface formation in the different eco zones of Chile? To answer this question, it is mandatory to possess fundamental knowledge about plant species habitats, occurrence and their dynamics. In his study Christian Bodinger utilizes satellite imagery in combination with machine learning to derive maps of land use and land cover (LULC) in four study sites along a climatic gradient and to monitor vegetation using monthly Normalized Difference Vegetation Index (NDVI) time series. The findings contribute to a better understanding of climate impacts on Chilean vegetation and serve as a basis of landscape evolution models. Contents TanDEM-X DEM, Sentinel Optical and Radar Data, Landsat Surface Reflectance Machine Learning Using SVMs and Random Forest Statistical Time-Series Evaluation Maps of Land Use and Cover (LULC) Time-Series Showing the Impact of ENSO Target Groups Scientists, lecturers and students in the field of geology and ecology Geoscientists and Ecologists with a focus on remote sensing About the Author Christian Bodinger holds a M.Sc. in Physical Geography from the University of Tubingen, Germany. His focus in research lies on remote sensing and image analysis for environmental applications. He is currently working for a company focusing on aquatic remote sensing.
650 0 $a Geoinformatics. $3 3216881
650 0 $a Plants $x Geographic information systems $z Chile. $3 3382727
650 1 4 $a Remote Sensing/Photogrammetry. $3 890882
650 2 4 $a Physical Geography. $3 893400
650 2 4 $a Environmental Geography. $3 2131519
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a BestMasters. $3 2056364
856 4 0 $u https://doi.org/10.1007/978-3-658-25120-8
950 $a Earth and Environmental Science (Springer-11646)