测绘通报 ›› 2022, Vol. 0 ›› Issue (4): 56-60,82.doi: 10.13474/j.cnki.11-2246.2022.0110

• 学术研究 • 上一篇    下一篇

运用NDVI-Albedo特征空间提取石漠化信息

罗杰1,2, 刘绥华1,2, 阮欧1,2, 胡海涛1,2   

  1. 1. 贵州师范大学地理与环境科学学院, 贵州 贵阳 550001;
    2. 贵州省山地资源与环境遥感应用 重点实验室, 贵州 贵阳 550001
  • 收稿日期:2021-08-30 出版日期:2022-04-25 发布日期:2022-04-26
  • 通讯作者: 刘绥华。E-mail:lsh23h@163.com
  • 作者简介:罗杰(1994-),男,硕士生,研究方向为地理信息系统与遥感应用。E-mail:luojie1921@163.com
  • 基金资助:
    国家自然科学基金(61540072;42161029)

Extraction of rocky desertification information using NDVI-Albedo feature space

LUO Jie1,2, LIU Suihua1,2, RUAN Ou1,2, HU Haitao1,2   

  1. 1. School of Geography and Environmental Science, Guizhou Normal University, Guiyang 550001, China;
    2. Guizhou Key Laboratory of Mountainous Resources and Environment Remote Sensing, Guiyang 550001, China
  • Received:2021-08-30 Online:2022-04-25 Published:2022-04-26

摘要: 石漠化是西南喀斯特地貌地区面临的最主要生态环境问题之一,对石漠化进行监测是其防治的一项重要工作。本文以威宁西部典型的石漠化研究区斗古乡为例,基于Landsat 8 OLI遥感数据,计算了研究区归一化植被指数(NDVI)和地表反照率(Albedo),通过NDVI-Albedo特征空间构建石漠化差值指数(RSDDI),对石漠化信息进行提取并对其进行精度验证。研究表明:基于NDVI-Albedo特征空间法构建的石漠化差值指数能够较为准确且便捷地对石漠化信息进行提取与分级,在中度石漠化及重度石漠化的制图精度均达到89%以上,提取效果较好,有利于西南喀斯特地貌地区对石漠化的定量评估与监测。

关键词: 石漠化, NDVI-Albedo特征空间, 遥感, 石漠化差值指数

Abstract: Rocky desertification is one of the most crucial ecological and environmental problems in the karst area of Southwest China. Monitoring rocky desertification is an important task for the prevention and control of rocky desertification. Taking a typical rocky desertification research area of Dougu town in western Weining as an example, based on Landsat8 OLI remote sensing data, the normalized vegetation index(NDVI) and Albedo of the research area are calculated, and the rocky desertification difference index (RSDDI) is constructed through the NDVI-Albedo feature space to extract the rocky desertification information and verify its accuracy. Studies have shown that the rocky desertification difference index constructed based on the NDVI-Albedo feature space method can extract and classify rocky desertification information more accurately and conveniently, and the accuracy of the mapping for moderate rocky desertification and severe rocky desertification is both reaching more than 89%, the extraction effect is excellent, which is conducive to the quantitative assessment and monitoring of rocky desertification in the southwest of China karst area.

Key words: rocky desertification, NDVI-Albedo feature space, remote sensing, RSDDI

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