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Document type:
Zeitschriftenaufsatz 
Author(s):
Deigele, Wolfgang; Brandmeier, Melanie; Straub, Christoph 
Title:
A Hierarchical Deep-Learning Approach for Rapid Windthrow Detection on PlanetScope and High-Resolution Aerial Image Data 
Abstract:
Forest damage due to storms causes economic loss and requires a fast response to prevent further damage such as bark beetle infestations. By using Convolutional Neural Networks (CNNs) in conjunction with a GIS, we aim at completely streamlining the detection and mapping process for forest agencies. We developed and tested different CNNs for rapid windthrow detection based on PlanetScope satellite data and high-resolution aerial image data. Depending on the meteorological situation after the stor...    »
 
Keywords:
GISTop_SpatialModelingAndAlgorithms 
Journal title:
Remote Sensing 
Year:
2020 
Journal volume:
12 
Quarter:
3. Quartal 
Month:
Jul 
Journal issue:
13 
Covered by:
Scopus; Web of Science 
Reviewed:
ja 
Language:
en 
Fulltext / DOI:
Publisher:
MDPI AG 
E-ISSN:
2072-4292 
Status:
Verlagsversion / published 
Date of publication:
02.07.2020 
Semester:
SS 20 
TUM Institution:
Lehrstuhl für Geoinformatik