Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images
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School of Computer Science and Information, Southwest Forestry University, Kunming 650224, China
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Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
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Department of Microbiology and Plant Biology, and Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
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Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
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Centre for Mountain Ecosystem Studies (CMES), Kunming Institute of Botany (CAS), Lanhei Road132,Heilongtan, Kunming 650201, China
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World Agroforestry Centre (ICRAF), Central and East Asia Office, Lanhei Road132, Heilongtan, Kunming 650201, China
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College of Information & Electrical Engineering, China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Academic Editors: Nicolas Baghdadi and Prasad S. Thenkabail
Remote Sens. 2015, 7(1), 1048-1073; https://doi.org/10.3390/rs70101048
Received: 10 September 2014
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Revised: 5 January 2015
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Accepted: 12 January 2015
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Published: 19 January 2015
(This article belongs to the Special Issue Mapping the Dynamics of Forest Plantations in Tropical and Subtropical Regions from Multi-Source Remote Sensing)
Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees) and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation) and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old) based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR) and optical remote sensing in the characterization of rubber plantations and their expansion over time.
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Keywords:
stand age; rubber plantations; phenology; Xishuangbanna; Landsat; PALSAR
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MDPI and ACS Style
Kou, W.; Xiao, X.; Dong, J.; Gan, S.; Zhai, D.; Zhang, G.; Qin, Y.; Li, L. Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images. Remote Sens. 2015, 7, 1048-1073. https://doi.org/10.3390/rs70101048
AMA Style
Kou W, Xiao X, Dong J, Gan S, Zhai D, Zhang G, Qin Y, Li L. Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images. Remote Sensing. 2015; 7(1):1048-1073. https://doi.org/10.3390/rs70101048
Chicago/Turabian StyleKou, Weili, Xiangming Xiao, Jinwei Dong, Shu Gan, Deli Zhai, Geli Zhang, Yuanwei Qin, and Li Li. 2015. "Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images" Remote Sensing 7, no. 1: 1048-1073. https://doi.org/10.3390/rs70101048
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