Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Geoinformation from the past = compu...
~
Herold, Hendrik.
Linked to FindBook
Google Book
Amazon
博客來
Geoinformation from the past = computational retrieval and retrospective monitoring of historical land use /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Geoinformation from the past/ by Hendrik Herold.
Reminder of title:
computational retrieval and retrospective monitoring of historical land use /
Author:
Herold, Hendrik.
Published:
Wiesbaden :Springer Fachmedien Wiesbaden : : 2018.,
Description:
xxiv, 192 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Land use - History. -
Online resource:
http://dx.doi.org/10.1007/978-3-658-20570-6
ISBN:
9783658205706
Geoinformation from the past = computational retrieval and retrospective monitoring of historical land use /
Herold, Hendrik.
Geoinformation from the past
computational retrieval and retrospective monitoring of historical land use /[electronic resource] :by Hendrik Herold. - Wiesbaden :Springer Fachmedien Wiesbaden :2018. - xxiv, 192 p. :ill., digital ;24 cm.
Hendrik Herold explores potentials and hindrances of using retrospective geoinformation for monitoring, communicating, modeling, and eventually understanding the complex and gradually evolving processes of land cover and land use change. Based on a comprehensive review of literature, available data sets, and suggested algorithms, the author proposes approaches for the two major challenges: To address the diversity of geographical entity representations over space and time, image segmentation is considered a global non-linear optimization problem, which is solved by applying a metaheuristic algorithm. To address the uncertainty inherent to both the data source itself as well as its utilization for change detection, a probabilistic model is developed. Experimental results demonstrate the capabilities of the methodology, e.g., for geospatial data science and earth system modeling. Contents Monitoring and Modeling Land Change Geoinformation from Digital Images An Adaptive Map Image Analysis Approach Modeling Uncertainty for Change Analysis Target Groups Researchers, lecturers, and students from the fields of geoscience, geography, urban and landscape ecology, land change science, earth system science, digital humanities Town and country planners, map librarians, historians The Author Hendrik Herold holds a doctoral degree from Dresden University of Technology, Germany, where he studied Geography, Geology, and Meteorology.
ISBN: 9783658205706
Standard No.: 10.1007/978-3-658-20570-6doiSubjects--Topical Terms:
586803
Land use
--History.
LC Class. No.: HD156 / .H476 2018
Dewey Class. No.: 910.285
Geoinformation from the past = computational retrieval and retrospective monitoring of historical land use /
LDR
:02467nmm a2200313 a 4500
001
2132744
003
DE-He213
005
20180802160808.0
006
m d
007
cr nn 008maaau
008
181005s2018 gw s 0 eng d
020
$a
9783658205706
$q
(electronic bk.)
020
$a
9783658205690
$q
(paper)
024
7
$a
10.1007/978-3-658-20570-6
$2
doi
035
$a
978-3-658-20570-6
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HD156
$b
.H476 2018
072
7
$a
RGW
$2
bicssc
072
7
$a
SCI030000
$2
bisacsh
072
7
$a
TEC036000
$2
bisacsh
082
0 4
$a
910.285
$2
23
090
$a
HD156
$b
.H561 2018
100
1
$a
Herold, Hendrik.
$3
3299573
245
1 0
$a
Geoinformation from the past
$h
[electronic resource] :
$b
computational retrieval and retrospective monitoring of historical land use /
$c
by Hendrik Herold.
260
$a
Wiesbaden :
$b
Springer Fachmedien Wiesbaden :
$b
Imprint: Springer Spektrum,
$c
2018.
300
$a
xxiv, 192 p. :
$b
ill., digital ;
$c
24 cm.
520
$a
Hendrik Herold explores potentials and hindrances of using retrospective geoinformation for monitoring, communicating, modeling, and eventually understanding the complex and gradually evolving processes of land cover and land use change. Based on a comprehensive review of literature, available data sets, and suggested algorithms, the author proposes approaches for the two major challenges: To address the diversity of geographical entity representations over space and time, image segmentation is considered a global non-linear optimization problem, which is solved by applying a metaheuristic algorithm. To address the uncertainty inherent to both the data source itself as well as its utilization for change detection, a probabilistic model is developed. Experimental results demonstrate the capabilities of the methodology, e.g., for geospatial data science and earth system modeling. Contents Monitoring and Modeling Land Change Geoinformation from Digital Images An Adaptive Map Image Analysis Approach Modeling Uncertainty for Change Analysis Target Groups Researchers, lecturers, and students from the fields of geoscience, geography, urban and landscape ecology, land change science, earth system science, digital humanities Town and country planners, map librarians, historians The Author Hendrik Herold holds a doctoral degree from Dresden University of Technology, Germany, where he studied Geography, Geology, and Meteorology.
650
0
$a
Land use
$x
History.
$3
586803
650
0
$a
Information storage and retrieval systems
$x
Land use.
$3
586953
650
0
$a
Geographic information systems.
$3
542758
650
1 4
$a
Geography.
$3
524010
650
2 4
$a
Geographical Information Systems/Cartography.
$3
890881
650
2 4
$a
Environmental Science and Engineering.
$3
1569104
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-658-20570-6
950
$a
Earth and Environmental Science (Springer-11646)
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9341479
電子資源
11.線上閱覽_V
電子書
EB HD156 .H476 2018
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login