中国地理科学 ›› 2017, Vol. 27 ›› Issue (4): 600-613.doi: 10.1007/s11769-017-0880-z

• 论文 • 上一篇    下一篇

Spatio-temporal Variations in Plantation Forests' Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations (1986-2015)

SHEN Wenjuan1,2, LI Mingshi1,2, WEI Anshi3   

  1. 1. College of Forestry, Nanjing Forestry University, Nanjing 210037, China;
    2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China;
    3. Guangdong Provincial Center for Forest Resources Monitoring, Guangzhou 510173, China
  • 收稿日期:2016-03-10 修回日期:2016-07-08 出版日期:2017-08-27 发布日期:2017-06-30
  • 通讯作者: LI Mingshi.E-mail:nfulms@njfu.edu.cn E-mail:nfulms@njfu.edu.cn
  • 基金资助:

    Under the auspices of the ‘948’ Project sponsored by the State Forestry Administration (SFA) of China (No. 2014-4-25), National Natural Science Foundation of China (No. 31670552, 31270587), Doctorate Fellowship Foundation of Nanjing Forestry University, the PAPD (Priority Academic Program Development) of Jiangsu Provincial Universities, Graduate Research and Innovation Projects in Jiangsu Province (No. KYLX15_0908)

Spatio-temporal Variations in Plantation Forests' Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations (1986-2015)

SHEN Wenjuan1,2, LI Mingshi1,2, WEI Anshi3   

  1. 1. College of Forestry, Nanjing Forestry University, Nanjing 210037, China;
    2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China;
    3. Guangdong Provincial Center for Forest Resources Monitoring, Guangzhou 510173, China
  • Received:2016-03-10 Revised:2016-07-08 Online:2017-08-27 Published:2017-06-30
  • Contact: LI Mingshi.E-mail:nfulms@njfu.edu.cn E-mail:nfulms@njfu.edu.cn
  • Supported by:

    Under the auspices of the ‘948’ Project sponsored by the State Forestry Administration (SFA) of China (No. 2014-4-25), National Natural Science Foundation of China (No. 31670552, 31270587), Doctorate Fellowship Foundation of Nanjing Forestry University, the PAPD (Priority Academic Program Development) of Jiangsu Provincial Universities, Graduate Research and Innovation Projects in Jiangsu Province (No. KYLX15_0908)

摘要:

Forest disturbance plays a vital role in modulating carbon storage, biodiversity and climate change. Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study. A Landsat time series stack (LTSS) was fed to the vegetation change tracker model (VCT) to map long-term changes in plantation forests' disturbance and recovery, followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations, magnitudes and rates of plantations' disturbance and recovery. And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%. A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%. Forest disturbance rates' change trend was characterized by a decline first, followed by an increase, then giving way to a decline again. An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001, disturbance rate of 4.51% in 1994 was a notable anomaly, while after 2001 there was a sharp ascending change, forest disturbance rate spiked in 2007 (5.84%). After that, there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015 (2.59%). Two obvious spikes in post-disturbance recovery rates occurred in 1995 (0.26%) and 2008 (0.41%). Overall, forest recovery rates were lower than forest disturbance rates. Moreover, forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery (LandTrendr) algorithms in Fogang County have been conducted, with LandTrendr finding mostly much more disturbance than VCT. Overall, disturbances and recoveries in northern Guangdong were triggered mostly by timber needs, policies and decisions of the local governments. This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

关键词: plantation, Landsat dense time series, remote sensing, forest disturbance and recovery, driving forces, northern Guangdong

Abstract:

Forest disturbance plays a vital role in modulating carbon storage, biodiversity and climate change. Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study. A Landsat time series stack (LTSS) was fed to the vegetation change tracker model (VCT) to map long-term changes in plantation forests' disturbance and recovery, followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations, magnitudes and rates of plantations' disturbance and recovery. And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%. A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%. Forest disturbance rates' change trend was characterized by a decline first, followed by an increase, then giving way to a decline again. An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001, disturbance rate of 4.51% in 1994 was a notable anomaly, while after 2001 there was a sharp ascending change, forest disturbance rate spiked in 2007 (5.84%). After that, there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015 (2.59%). Two obvious spikes in post-disturbance recovery rates occurred in 1995 (0.26%) and 2008 (0.41%). Overall, forest recovery rates were lower than forest disturbance rates. Moreover, forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery (LandTrendr) algorithms in Fogang County have been conducted, with LandTrendr finding mostly much more disturbance than VCT. Overall, disturbances and recoveries in northern Guangdong were triggered mostly by timber needs, policies and decisions of the local governments. This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

Key words: plantation, Landsat dense time series, remote sensing, forest disturbance and recovery, driving forces, northern Guangdong