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| 耕地遥感识别研究进展与展望 |
| Progress and prospect of cultivated land extraction research using remote sensing |
| Received:August 25, 2020 |
| DOI：10.13254/j.jare.2020.0457 |
| 中文关键词: 耕地，数据源，分类算法，时相，分类对象 |
| 英文关键词: cultivated land, data source, classification algorithm, temporal, classification object |
| 基金项目:国家自然科学基金项目（U1901601）；广东省科技兴农-农业科技创新及推广项目（2019KJ102） |
| Author Name | Affiliation | E-mail | | XIONG Xi-liu | College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China | | | HU Yue-ming | College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China
Key Laboratory of Ministry of Natural Resources for Construction Land Transformation, Guangzhou 510642, China | | | WEN Ning | Hunan Land and Resources Planning Institute, Changsha 410007, China | 413093882@qq.com | | LIU Luo | College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China
Key Laboratory of Ministry of Natural Resources for Construction Land Transformation, Guangzhou 510642, China | | | XIE Jian-wen | College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China
Key Laboratory of Ministry of Natural Resources for Construction Land Transformation, Guangzhou 510642, China | | | LEI Fan | Hunan Second Surveying and Mapping Institute, Changsha 410119, China | | | XIAO Li | Hunan Land and Resources Planning Institute, Changsha 410007, China | | | TANG Tie | Hunan Land and Resources Planning Institute, Changsha 410007, China | |
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| 中文摘要: |
| 快速、准确获取耕地数量及其分布信息是研究耕地时空格局和生态效应的基础，也是及时制定应对粮食问题对策的迫切需求。近年来，随着卫星遥感技术的迅猛发展，遥感以其宏观性、实时性以及经济性为耕地信息快速获取提供了可能性。本文归纳了遥感技术应用于识别耕地信息的研究进展，总结了国内外耕地信息提取研究中常用的数据源、分类算法、时相选择、分类对象，讨论了上述四大类在提取耕地信息过程中的优缺点。随着传感器数量不断增加，遥感影像时间分辨率、空间分辨率及光谱分辨率不断提高，分类算法的不断涌现，基于多源遥感数据，集成智能分类算法识别耕地将成为必然的发展趋势。 |
| 英文摘要: |
| Rapidly and accurately extracted cultivated land quantity and distribution information is the basis for studying the spatiotemporal patterns and ecological effects of cultivated land, and there is an urgent need for timely formulation of corresponding countermeasures for food problems. In recent years, the advancement of remote sensing technology has provided the possibility for the rapid acquisition of cultivated land information owing to the macroscopic, real-time, and economical properties of the technology. This paper summarized the research progress of the application of remote sensing technology in the extraction of cultivated land, commonly used data sources, classification algorithms, and temporal and classification objects in the research of domestic and foreign cultivated land extraction methods, and discussed the advantages and disadvantages of the above four categories in the process of extracting cultivated land information. With the increasing number of sensors, the temporal resolution, spatial resolution, and spectral resolution of remote sensing images are continuously improving, and the classification algorithm is constantly updated. Based on multi-source remote sensing data, the integration of intelligent classification algorithms for identifying cultivated land will become an inevitable development trend. |
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