Research Progress on Obtaining Cultivated Land Quality Evaluation Indexes by Remote Sensing

被引：0
|
作者：
Zhang C. [1 ,2 ]
Gao L. [1 ]
Yun W. [2 ,3 ]
Li L. [1 ]
Ji W. [1 ]
Ma J. [1 ]
机构：
[1] College of Land Science and Technology, China Agricultural University, Beijing
[2] Key Laboratory of Agricultural Land Quality Monitoring and Control, Ministry of Natural Resources, Beijing
[3] Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing
来源：
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2022年 / 53卷 / 01期
关键词：
Cultivated land quality; Evaluation index; Field utilization status; Remote sensing; Soil; Topographic condition;
D O I：
10.6041/j.issn.1000-1298.2022.01.001
中图分类号：
学科分类号：
摘要：
The data acquisition of cultivated land quality index (CLQI) is the basis of cultivated land quality (CLQ) evaluation. Remote sensing (RS) provides a new method for rapid and large-scale monitoring of CLQ data. Firstly, the connotation and function of CLQ were analyzed. On this basis, bibliometric method was used to summarize the research of CLQI in recent five years. Combined with the research status of CLQ and soil quality, CLQI system was established based on RS, which was divided into three dimensions: topographic conditions, soil properties and field utilization status. Secondly, the research status of various index acquisition methods in different dimensions was analyzed, and the commonly used RS analysis methods and corresponding technical principles were summarized. The basic data can be effectively obtained for field slope, field condition, field road accessibility, forest network degree and other indicators, and the large-scale acquisition method of soil properties were needed further research. Finally, aiming at the problems to be solved in RS monitoring of CLQ, the following suggestions and prospects were put forward: mining the remote sensing characteristics of different scales of CLQI; strengthening the research on automatic extraction of remote sensing information of CLQI; and building a remote sensing big data platform for CLQ evaluation, so as to promote the application of RS in CLQ evaluation. © 2022, Chinese Society of Agricultural Machinery. All right reserved.
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页码：1 / 13
页数：12
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