TY - JOUR
T1 - Estimating the aboveground biomass for planted forests based on stand age and environmental variables
AU - Peng, Dailiang
AU - Zhang, Helin
AU - Liu, Liangyun
AU - Huang, Wenjiang
AU - Huete, Alfredo R.
AU - Zhang, Xiaoyang
AU - Wang, Fumin
AU - Yu, Le
AU - Xie, Qiaoyun
AU - Wang, Cheng
AU - Luo, Shezhou
AU - Li, Cunjun
AU - Zhang, Bing
N1 - Funding Information:
Funding: This study was supported by the National Natural Science Foundation of China (41571423, 41671435, and 41871328), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19090112, and XDA19080304), and National Key Research and Development Program of China (2016YFB0501501).
Funding Information:
This study was supported by the National Natural Science Foundation of China (41571423, 41671435, and 41871328), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19090112, and XDA19080304), and National Key Research and Development Program of China (2016YFB0501501). We thank Xiao Zhang, YanWang, Xuemin Jiao, Yong Hu, ZhihuiWang, Peipei Ding, Fubao Xu, and Zhenwang Li from the Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, for their help with data acquisition and processing.
Publisher Copyright:
© 2019 by the authors.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - Measuring forest aboveground biomass (AGB) at local to regional scales is critical to understanding their role in regional and global carbon cycles. The Three-North Shelterbelt Forest Program (TNSFP) is the largest ecological restoration project in the world, and has been ongoing for over 40 years. In this study, we developed models to estimate the planted forest aboveground biomass (PF_AGB) for Yulin, a typical area in the project. Surface reflectances in the study area from 1978 to 2013 were obtained from Landsat series images, and integrated forest z-scores were constructed to measure afforestation and the stand age of planted forest. Normalized difference vegetation index (NDVI) was combined with stand age to develop an initial model to estimate PF_AGB. We then developed additional models that added environment variables to our initial model, including climatic factors (average temperature, total precipitation, and total sunshine duration) and a topography factor (slope). The model which combined the total precipitation and slope greatly improved the accuracy of PF_AGB estimation compared to the initial model, indicating that the environmental variables related to water distribution indirectly affected the growth of the planted forest and the resulting AGB. Afforestation in the study area occurred mainly in the early 1980s and early 21st century, and the PF_AGB in 2003 was 2.3 times than that of 1998, since the fourth term TNSFP started in 2000. The PF_AGB in 2013 was about 3.33 times of that in 2003 because many young trees matured. The leave-one-out cross-validation (LOOCV) approach showed that our estimated PF_AGB had a significant correlation with field-measured data (correlation coefficient (r) = 0.89, p < 0.001, root mean square error (RMSE) = 6.79 t/ha). Our studies provided a method to estimate long time series PF_AGB using satellite repetitive measures, particularly for arid or semi-arid areas.
AB - Measuring forest aboveground biomass (AGB) at local to regional scales is critical to understanding their role in regional and global carbon cycles. The Three-North Shelterbelt Forest Program (TNSFP) is the largest ecological restoration project in the world, and has been ongoing for over 40 years. In this study, we developed models to estimate the planted forest aboveground biomass (PF_AGB) for Yulin, a typical area in the project. Surface reflectances in the study area from 1978 to 2013 were obtained from Landsat series images, and integrated forest z-scores were constructed to measure afforestation and the stand age of planted forest. Normalized difference vegetation index (NDVI) was combined with stand age to develop an initial model to estimate PF_AGB. We then developed additional models that added environment variables to our initial model, including climatic factors (average temperature, total precipitation, and total sunshine duration) and a topography factor (slope). The model which combined the total precipitation and slope greatly improved the accuracy of PF_AGB estimation compared to the initial model, indicating that the environmental variables related to water distribution indirectly affected the growth of the planted forest and the resulting AGB. Afforestation in the study area occurred mainly in the early 1980s and early 21st century, and the PF_AGB in 2003 was 2.3 times than that of 1998, since the fourth term TNSFP started in 2000. The PF_AGB in 2013 was about 3.33 times of that in 2003 because many young trees matured. The leave-one-out cross-validation (LOOCV) approach showed that our estimated PF_AGB had a significant correlation with field-measured data (correlation coefficient (r) = 0.89, p < 0.001, root mean square error (RMSE) = 6.79 t/ha). Our studies provided a method to estimate long time series PF_AGB using satellite repetitive measures, particularly for arid or semi-arid areas.
KW - Aboveground biomass (AGB)
KW - Planted forest
KW - Stand age
KW - Three-North Shelterbelt Forest Program (TNSFP)
KW - Time-series Landsat images
UR - http://www.scopus.com/inward/record.url?scp=85073456919&partnerID=8YFLogxK
U2 - 10.3390/rs11192270
DO - 10.3390/rs11192270
M3 - Article
VL - 11
JO - Remote Sensing
JF - Remote Sensing
IS - 19
M1 - 2270
ER -