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Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method

Sun, Zhongchang and Leinenkugel, Patrick and Guo, Huadong and Huang, Chong and Künzer, Claudia (2017) Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method. Journal of Applied Remote Sensing, 11 (2), pp. 1-21. Society of Photo-optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JRS.11.026011 ISSN 1931-3195

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Natural tropical rainforests in China’s Xishuangbanna region have undergone dramatic conversion to rubber plantations in recent decades, resulting in altering the region’s environment and ecological systems. Therefore, it is of great importance for local environmental and ecological protection agencies to research the distribution and expansion of rubber plantations. The objective of this paper is to monitor dynamic changes of rubber plantations in China’s Xishuangbanna region based on multitemporal Landsat images (acquired in 1989, 2000, and 2013) using a C5.0-based decision-tree method. A practical and semiautomatic data processing procedure for mapping rubber plantations was proposed. Especially, haze removal and deshadowing were proposed to perform atmospheric and topographic correction and reduce the effects of haze, shadow, and terrain. Our results showed that the atmospheric and topographic correction could improve the extraction accuracy of rubber plantations, especially in mountainous areas. The overall classification accuracies were 84.2%, 83.9%, and 86.5% for the Landsat images acquired in 1989, 2000, and 2013, respectively. This study also found that the Landsat-8 images could provide significant improvement in the ability to identify rubber plantations. The extracted maps showed the selected study area underwent rapid conversion of natural and seminatural forest to a rubber plantations from 1989 to 2013. The rubber plantation area increased from 2.8% in 1989 to 17.8% in 2013, while the forest/woodland area decreased from 75.6% in 1989 to 44.8% in 2013. The proposed data processing procedure is a promising approach to mapping the spatial distribution and temporal dynamics of rubber plantations on a regional scale.

Item URL in elib:https://elib.dlr.de/112669/
Document Type:Article
Title:Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sun, Zhongchangsunzc (at) radi.ac.cnUNSPECIFIED
Leinenkugel, Patrickpatrick.leinenkugel (at) dlr.deUNSPECIFIED
Künzer, Claudiaclaudia.kuenzer (at) dlr.deUNSPECIFIED
Date:May 2017
Journal or Publication Title:Journal of Applied Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1117/1.JRS.11.026011
Page Range:pp. 1-21
Publisher:Society of Photo-optical Instrumentation Engineers (SPIE)
Keywords:rubber plantation, C5.0, classification, dynamic change Analysis, Landsat
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Leinenkugel, Patrick
Deposited On:04 Jul 2017 11:06
Last Modified:11 Apr 2019 08:47

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