Tracking bamboo dynamics in Zhejiang, China, using time-series of Landsat data from 1990 to 2014

作者:Li, MN (Li, Mengna)[ 1 ] ; Li, CC (Li, Congcong)[ 2 ] ; Jiang, H (Jiang, Hong)[ 3 ] ; Fang, CY (Fang, Chengyuan)[ 3 ] ; Yang, J (Yang, Jun)[ 2 ] ; Zhu, ZL (Zhu, Zhiliang)[ 4 ] ; Shi, L (Shi, Lei)[ 5 ] ; Liu, SR (Liu, Shirong)[ 5 ] ; Gong, P (Gong, Peng)[ 1,2 ]

INTERNATIONAL JOURNAL OF REMOTE SENSING

卷: 37  期: 7  页: 1714-1729

DOI: 10.1080/01431161.2016.1165885

出版年: 2016

摘要

Bamboo is an important vegetation type and provides a number of critical ecosystem services. Reliable and consistent information on bamboo distribution is required to better estimate its effect on climate change mitigation and socio-economic development. However, such information is rare over a large spatial area. In this study, we evaluate the contribution of different features in the identification of bamboo stands and determine a more discriminative set of features. We propose a bamboo mapping system including feature extraction and feature selection and derive the long-term trends of bamboo distribution in Zhejiang Province, China, using time-series of Landsat data from 1990 to 2014, with an increment of 5 years (1990, 1995, 2000, 2005, 2010, and 2014). The resultant maps of bamboo in the six epochs were evaluated using independent validation samples. The overall accuracies (OAs) of all six epochs range from 85.9% to 90.7%. We found that bamboo distribution in Zhejiang substantially increased from 1990 to 2014, particularly during the 2000s. Based on the produced maps, the area of bamboo in this region increased from 5363 +/- 490 km(2) in 1990 to 11671 +/- 653 km(2) in 2014, which is consistent with the National Forest Resource Inventory (NFRI) data. Our study demonstrates the capability of time-series of Landsat data for continuous monitoring of bamboo at a large spatial scale.

通讯作者地址: Gong, P (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Tsinghua Univ, Minist Edu, Ctr Earth Syst Sci, Key Lab Earth Syst Modelling, Beijing 100084, Peoples R China

[ 3 ] Zhejiang Agr & Forest Univ, Nurturing Stn State Key Lab Subtrop Silviculture, Linan, Peoples R China

[ 4 ] US Geol Survey, 959 Natl Ctr, Reston, VA 22092 USA

 [ 5 ] State Forestry Adm Peoples Republ China, Int Ctr Bamboo & Rattan, Beijing, Peoples R China