基于RapidEye遥感影像的比值密度分割法在岩溶石漠化调查中的应用——以云南鹤庆县为例

涂杰楠; 杨亮; 梁丽新; 童立强; 郭兆成; 刘婷; 贺鹏

doi:10.11932/karst20150313

基于RapidEye遥感影像的比值密度分割法在岩溶石漠化调查中的应用——以云南鹤庆县为例

doi: 10.11932/karst20150313

1.
中国国土资源航空物探遥感中心
2.
内蒙古地质矿产勘查院
3.
内蒙古自治区地质调查院
4.
中国地质大学

基金项目: 地质大调查项目“西南岩溶石漠化遥感调查与地面监测（1212011220958）”

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出版历程
- 发布日期: 2015-06-25

The band ratio and density slice method based on RapidEye remote sensing images and its application to investigation of karst rocky desertification:A case study in Heqing county, Yunnan Province

1.
China Aero Geophysical Survey & Remote Sensing Center for Land and Resources
2.
Geology and Mineral Exploration Institute of Inner Mongolia
3.
Geological Survey Institute of Inner Mongolia
4.
China University of Geosciences

摘要

摘要: 高分辨率遥感图像是大比例尺石漠化遥感解译工作的重要信息源。文章以云南省鹤庆县为研究区，采用2011年RapidEye多光谱遥感影像，在对灰岩与针叶林—草体混合标准光谱曲线及不同裸岩率亮度值剖面曲线分析的基础上，运用波段比值法和密度分割法，结合野外现场踏勘和地理底图，开展大比例尺石漠化遥感解译，获得如下调查结果：全县石漠化面积为188.82 km2，占全县总面积的8.13%，占岩溶面积的25.48%，其中重度面积有10.31 km2，占石漠化总面积的5.46%，中度面积有42.28 km2，占石漠化总面积的22.39%，轻度面积有136.23 km2，占石漠化总面积的71.15%。野外验证石漠化等级判对率为84%，达到技术规范要求，这表明文章采用的方法可有效运用于大比例尺岩溶石漠化信息的提取。
- 遥感 /
- 石漠化 /
- 密度分割 /
- 波段比值
Abstract: Heqing county is located in northwestern Yunnan Province, the southwestern margin of the Yangzi platform, E 100°01′～100°29′ and N25°57′～26°42′, the southern end of the traverse mountains in western Yunnan and the east of the Yunling range. Karst mountainous plateaus and basin landforms dominate this region with a total land area of 2,323.54 km2, including exposed carbonate rock 741 km2, representing typical karst rocky desertification (KRD for short). The research on KRD is of great significance to soil erosion management and improvement of geological and ecological environments in Heqing county. The KRD interpretation based on high-resolution remote sensing images is one of the important methods in large-scale investigations to this phenomenon. At present, visual interpretation is still the main approach for KRD interpretation with high-resolution remote sensing images. To improve the accuracy and speed of the KRD interpretation, a method of band ratio and density slice for KRD investigation is proposed. This study took Heqing county as an example and RapidEye multispectral remote sensing image of 2011 as information source. On the basis of standard spectral curves of limestone and conifer-meadow mix, and combining with analyzing profile curves of different rock coverage DN values, we applied the band ratio and density slice method to investigation of large-scale KRD in Heqing county. After indoor interpretation, we went to the field to validate the accuracy of the interpretation results and modify them. At last, we obtained the KRD data of Heqing county. The investigation results show that the area of KRD in Heqing county is 188.82 km2, which accounts for 8.13% of the whole county area and 25.48% of the karst area. The area of severe KRD is 10.31 km2, which accounts for 5.46% of the total KRD area. The moderate KRD area is 42.28 km2, which accounts for 22.39% of the whole. And the mild KRD area is 136.23 km2, accounting for 71.15%. Through the field validation, the correct ratio of KRD interpretation is 84%, which can meet the interpretation demand and the technical specification. So it is concluded that the band ratio and density slice method can be applied to large-scale KRD remote sensing investigation effectively.
- remote sensing interpretation /
- rocky desertification /
- density slice /
- band ratio

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参考文献(17)

[1]	童立强. 西南岩溶石山地区石漠化信息自动提取技术研究［J］. 国土资源遥感, 2003(4):35-39.
[2]	李丽, 童立强, 李小慧. 基于植被覆盖度的石漠化遥感信息提取方法研究［J］. 国土资源遥感, 2010(2):59-62.
[3]	胡顺光, 张增祥, 夏奎菊. 遥感石漠化信息的提取［J］. 地球信息科学学报, 2010,12(6):870-879.
[4]	夏学齐, 田庆久, 杜凤兰. 石漠化程度遥感信息提取方法研究［J］. 遥感学报, 2006,10(4):469-474.
[5]	陈起伟, 兰安军, 熊康宁, 等. 基于遥感光谱特征的喀斯特石漠化信息提取［J］. 贵州师范大学学报(自然科学版), 2003, 21(4): 82-87.
[6]	熊平生, 袁道先, 谢世友. 我国南方岩溶山区石漠化基本问题研究进展［J］. 中国岩溶, 2010, 29(4): 355-362.
[7]	Wang S J, Liu Q M, Zhang D F. Karst rocky desertification in southwestern China: geomorphology, landuse, impact and rehabilitation［J］. Land Degradation & Development, 2004,15(2): 115-121.
[8]	王世杰. 喀斯特石漠化概念演绎及其科学内涵的讨论［J］. 中国岩溶, 2002, 21(2): 101-105.
[9]	李阳冰, 王世杰, 容丽. 关于喀斯特石漠和石漠化概念的讨论［J］. 中国沙漠, 2004, 24(6): 689-695.
[10]	李雪冬, 杨广斌, 张旭亚. 基于RS和GIS的喀斯特山区生态系统构成与格局及转化分析：以贵州毕节地区为例［J］. 中国岩溶, 2014, 33(1): 82-90.
[11]	郭红艳, 王月容, 卢琦. 岩溶石漠化地区生态系统服务价值评价:以金沙县为例［J］. 中国岩溶, 2013, 32(2): 211-217, 224.
[12]	杨奇勇, 蒋忠诚, 李晖. 基于Google Earth的果化示范区石漠化评估［J］. 中国岩溶, 2013, 32(1): 95-99.
[13]	雷阳艾, 严健, 杨海林, 等. 滇西鹤庆地区铝土矿床地质特征及找矿前景分析［J］. 矿物学报, 2013, 33(4): 478-484.
[14]	EyeFindTMBrochure［EBOL］. www.blackbridge.com/rapideye/upload/eyefind.pdf
[15]	刘建军.古河道型砂岩铀矿遥感综合信息提取方法研究［D］. 成都理工大学,1999: 12-13.
[16]	田淑芳, 詹骞. 遥感地质学［M］. 北京:地质出版社,2013:257-258.
[17]	R N Clark, G A Swayze, R Wise, etc. USGS Digital Spectral Library splib06a［DB/OL］.speclab.cr.usgs.gov/spectral.lib06/ds231/datatable.html