Satellite remote sensing monitoring of canopy cover of conversion of farmland to forestland project area in the Inner Mongolia

doi:10.13474/j.cnki.11-2246.2024.0624

Abstract

Abstract: 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.

Key words: conversion of farmland to forestland, canopy cover, gradient boosting regression tree, Inner Mongolia

CLC Number:

P237

WANG Tiancan, WANG Jianhe, SHEN Tong, YUE Lianggaoke. Satellite remote sensing monitoring of canopy cover of conversion of farmland to forestland project area in the Inner Mongolia[J]. Bulletin of Surveying and Mapping, 2024, 0(6): 139-145.

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