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内蒙古退耕还林工程区林冠覆盖率卫星遥感监测

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内蒙古新一轮退耕还林还草工程于2015年启动,是内蒙古生态环境建设恢复的重大举措.本文利用2022年生长季Sentinel-2A影像及地形数据,结合实地测量数据,基于GEE平台采用梯度提升树回归模型(GBRT),对内蒙古新一轮退耕还林工程区林冠覆盖率进行反演分析.结果表明,模型验证决定系数(R2)为0.87,均方根误差(RMSE)为0.079,平均绝对误差(MAE)为0.062.内蒙古新一轮退耕还林工程区林冠覆盖率均值为0.147,其分布存在明显的空间差异,受植被配置类型、种植年份和地理环境等因素影响,总体从西向东逐渐递增.利用Sentinel-2A影像和地形数据可以有效地估测退耕还林工程区林冠覆盖率,对低林冠覆盖率区域的反演提供参考.
Satellite remote sensing monitoring of canopy cover of conversion of farmland to forestland project area in the Inner Mongolia
The new period of returning farmland to forestland and grassland project is launched in 2015, which is amajor measure to restore the ecological environment of the Inner Mongolia. Using the Sentinel-2A images and terrain data in the 2022 growing season, combined with field measurement data, and based on the GEE platform, the gradient boostingreg ression tree(GBRT) is used to invert the canopy cover of the new period of farmland to forestland project area in the Inner Mongolia. The results show that the model verification coefficient of determination (R2) is 0.87,the root mean square error (RMSE) is 0.079 and the mean absolute error (MAE) is 0.062. The average canopy cover in the new period of returning farmland to forestland project areas in Inner Mongolia is 0.147. There are obvious spatial differences in its distribution, which is affected by factors such as vegetation configuration type, planting year, and geographical environment. It generally increases gradually from west to east. Sentinel-2A images and terrain data can be used to effectively estimate canopy cover in the conversion of farmland to forestland project area, providing a reference for the inversion of low canopy cover areas.

conversion of farmland to forestlandcanopy covergradient boosting regression treeInner Mongolia

格根塔娜、王天璨、王建和、沈通、月亮高可

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内蒙古自治区林业与草原工作总站,内蒙古 呼和浩特010010

中国科学院空天信息创新研究院,北京100094

中国科学院大学,北京100101

重庆交通大学,重庆404100

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退耕还林 林冠覆盖率 梯度提升树 内蒙古

能力培育项目

2024

测绘通报
测绘出版社

测绘通报

CSTPCD北大核心
影响因子:1.027
ISSN:0494-0911
年,卷(期):2024.(6)
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