Geoinformation from the Past Computational Retrieval and Retrospective Monitoring of Historical Land Use /

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Herold, Hendrik (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03229nam a2200433 4500
001 978-3-658-20570-6
003 DE-He213
005 20191027051027.0
007 cr nn 008mamaa
008 171221s2018 gw | s |||| 0|eng d
020 |a 9783658205706  |9 978-3-658-20570-6 
024 7 |a 10.1007/978-3-658-20570-6  |2 doi 
040 |d GrThAP 
050 4 |a GA1-1776 
072 7 |a RGW  |2 bicssc 
072 7 |a SCI030000  |2 bisacsh 
072 7 |a RGW  |2 thema 
082 0 4 |a 910.285  |2 23 
100 1 |a Herold, Hendrik.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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. 
250 |a 1st ed. 2018. 
264 1 |a Wiesbaden :  |b Springer Fachmedien Wiesbaden :  |b Imprint: Springer Spektrum,  |c 2018. 
300 |a XXIV, 192 p. 49 illus., 5 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
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 Geographical information systems. 
650 0 |a Environmental sciences. 
650 1 4 |a Geographical Information Systems/Cartography.  |0 http://scigraph.springernature.com/things/product-market-codes/J13000 
650 2 4 |a Environmental Science and Engineering.  |0 http://scigraph.springernature.com/things/product-market-codes/G37000 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783658205690 
776 0 8 |i Printed edition:  |z 9783658205713 
856 4 0 |u https://doi.org/10.1007/978-3-658-20570-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-EES 
950 |a Earth and Environmental Science (Springer-11646)