Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI

Yuanwei QIN, University of Oklahoma Norman Campu, yuanwei.qin@ou.edu (Presenter)
Xiangming Xiao, University of Oklahoma, xiangming.xiao@ou.edu
Jinwei Dong, University of Oklahoma, jinwei.dong@ou.edu
Geli Zhang, University of Oklahoma, geli.zhang@ou.edu
Masanobu Shimada, JAXA, shimada.masanobu@jaxa.jp
Jiyuan Liu, Institute of Geographic Sciences and Natural Resources Research, liujy@igsnrr.ac.cn
Chungan Li, Guangxi Forest Inventory and Planning Institute, gxali@126.com
Weili Kou, Southwest Forestry University, weili.kou@ou.edu
Berrien Moore III, Univ. of Oklahoma, berrien@ou.edu

Forests and their changes are important to the regional and global carbon cycle, biodiversity and ecosystem services. Some uncertainty about forest cover area in China prompts an accurate and updated forest cover map. In this study, we combined ALOS PALSAR orthorectified 50-m mosaic images (FBD mode with HH and HV polarization) and MODIS time series data in 2010 to map forests in China. We used MODIS-based NDVI dataset (MOD13Q1, 250-m spatial resolution) to generate a map of annual maximum NDVI and used it to mask out built-up lands, barren lands, and sparsely vegetated lands. We developed a decision tree classification algorithm to identify forest and non-forest land cover, based on the signature analysis of PLASAR backscatter data. The PALSAR-based algorithm was then applied to produce a forest cover map in China in 2010. The resulting forest/non-forest classification map has an overall accuracy of 96.2% and a Kappa Coefficient of 0.91. The resultant 50-m PALSAR-based forest cover map was compared to five forest cover databases. The total forest area (2.02×106 km2) in China from the PALSAR-based forest map is close to the estimates from the China National Forestry Inventory (1.95×106 km2), JAXA forest map (2.00×106 km2), and FAO FRA (2.07×106 km2). There are good linear relationships between the PALSAR-based forest map and the forest maps from the JAXA, MCD12Q1, and NLCD-China datasets at the province and county scales. All the forest maps have similar spatial distributions of forest/non-forest at pixel scale. Our PALSAR-based forest map recognizes well the agro-forests in China. The results of this study demonstrate the potential of integrating PALSAR images and MODIS images to map forests in large areas with the same threshold values, and the resultant map of forest cover in China can be used for the studies of the forest carbon cycle and ecological restoration projects.

Presentation Type:  Poster

Session:  General Contributions   (Tue 4:35 PM)

Associated Project(s): 

• Xiao, Xiangming: Mapping industrial forest plantations in tropical monsoon Asia through integration of Landsat and PALSAR imagery ...details
• Xiao, Xiangming: Quantifying changes in agricultural intensification and expansion in monsoon Asia during 2000-2010 ...details

Poster Location ID: 216