Application Status and Development Trend of Multi-source Remote Sensing Data in Forest Resource Monitoring

doi:10.11924/j.issn.1000-6850.casb2022-0503

Abstract

Abstract:

In this paper, the application status and development trend of multi-source remote sensing in forest resource monitoring are described. Compared with traditional forest resource monitoring, which involves a large amount of manpower to carry out field investigation, satellite remote sensing and UAV remote sensing have obvious advantages in forest resource monitoring. In the forest resource monitoring research based on multi-source remote sensing data, this paper focuses on the comparison of the application of five kinds of multi-source remote sensing on forest resource monitoring, including: forest disease and insect monitoring, stand height measurement, forest canopy structure measurement, tree species composition and forest classification, and forest biomass measurement. Resource satellite, microwave remote sensing, imaging spectroscopy and new technologies and methods of forest resource monitoring in three-dimensional remote sensing, such as deep learning intelligent classification and multi-source remote sensing fusion technology, will become new means for multi-source remote sensing forest resource monitoring in the future. The application of differential GPS, three-dimensional remote sensing and hyperspectral images combined with mathematical computer technology can improve the accuracy of different levels of forest resource estimation. The automation and informatization of UAV remote sensing will be the development trend of UAV remote sensing application in forest resource monitoring. In addition, the long endurance capability and multiple types of sensors will further improve the accurate monitoring of forest resources by UAV remote sensing.

Key words: multi-source remote sensing, forest resource monitoring, satellite remote sensing, UAV remote sensing

ZHANG Juan, LIAO Juyang, LIU Yan, WANG Ling, LI Qiaoyun, WU Linshi, HUANG Yaqi. Application Status and Development Trend of Multi-source Remote Sensing Data in Forest Resource Monitoring[J]. Chinese Agricultural Science Bulletin, 2023, 39(19): 159-164.

Figures/Tables 5

References 51

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一级	二级	三级
林地	有林地	针叶林地
		阔叶林地
		混交林地
	疏林地	—
	未成林地	—
	灌木林地	—
	苗圃地	—
	无立木林地	—
	宜林地	宜林荒山荒地
	宜林地	宜林沙荒地
	辅助生产林地	—
非林地	农地	—
	水域	—
	未利用地	—
	其他土地	—

一级	二级	三级
林地	有林地	针叶林地
		阔叶林地
		混交林地
	疏林地	—
	未成林地	—
	灌木林地	—
	苗圃地	—
	无立木林地	—
	宜林地	宜林荒山荒地
	宜林地	宜林沙荒地
	辅助生产林地	—
非林地	农地	—
	水域	—
	未利用地	—
	其他土地	—

传感器	输出数据	应用
高光谱遥感	全波段光谱信息	森林资源类型分类^[8]，森林病虫害监测^[9]，森林树种分类^[10]，森林冠层结构^[11-12]
高分辨率遥感	高空间分辨率影像	森林提取^[13]，森林郁闭度提取^[13]，森林小班蓄积量估测^[14]
多光谱遥感	多波段光谱信息	森林土地覆盖信息^[15]，森林类型^[15]，植被覆盖度^[15]，森林参数模型^[15]
星载雷达	高程数据文件、陆地测高数据文件等	森林林分树高^[16-17]，森林结构参数^[18]，森林地上生物量^[19]

传感器	输出数据	应用
高光谱遥感	全波段光谱信息	森林资源类型分类^[8]，森林病虫害监测^[9]，森林树种分类^[10]，森林冠层结构^[11-12]
高分辨率遥感	高空间分辨率影像	森林提取^[13]，森林郁闭度提取^[13]，森林小班蓄积量估测^[14]
多光谱遥感	多波段光谱信息	森林土地覆盖信息^[15]，森林类型^[15]，植被覆盖度^[15]，森林参数模型^[15]
星载雷达	高程数据文件、陆地测高数据文件等	森林林分树高^[16-17]，森林结构参数^[18]，森林地上生物量^[19]

传感器	输出数据	应用
高光谱传感器	全波段光谱信息	森林病虫害监测^[25-26]，树种组成识别^[27-28]
可见光传感器	数字正射影像(DOM)，数字表面模型(DSM)	森林病虫害监测^[29]，林分树高测定^[30-31]，森林冠层结构与属性测定^[32-33]，树种组成识别^[3,34]，森林生物量测定^[22]
多光谱传感器	多波段光谱信息	森林冠层结构与属性测定^[35]，森林病虫害监测^[36]
热红外相机	温度图谱	森林冠层结构与属性测定^[37]，森林病虫害监测^[38]
激光雷达	点云，数字地表模型(DSM)，数字地面模型(DTM)	森林冠层结构与属性测定^[39-40]，森林生物量测定^[41]