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河海大学 地球科学与工程学院,江苏 南京,210098
收稿日期:2013-06-20,
修回日期:2013-08-09,
网络出版日期:2013-12-25,
纸质出版日期:2013-12-25
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安如 徐晓峰 李晓雪 梁欣. 黄河源玛多县“黑土滩”遥感定量识别[J]. 光学精密工程, 2013,21(12): 3183-3190
AN Ru XU Xiao-feng LI Xiao-xue LIANG Xin. “Black Soil Land” recognition at Maduo County in source region of Yellow River based on quantitative remote sensing[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3183-3190
安如 徐晓峰 李晓雪 梁欣. 黄河源玛多县“黑土滩”遥感定量识别[J]. 光学精密工程, 2013,21(12): 3183-3190 DOI: 10.3788/OPE.20132112.3183.
AN Ru XU Xiao-feng LI Xiao-xue LIANG Xin. “Black Soil Land” recognition at Maduo County in source region of Yellow River based on quantitative remote sensing[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3183-3190 DOI: 10.3788/OPE.20132112.3183.
采用混合像元分解方法提取黑土滩信息以实现玛多县黑土滩的遥感识别。以Roberts提出的多端元混合像元分解(MESMA)模型为基础,分析玛多县的地物组成并提取端元;针对MESMA在本研究区应用存在的不足,优化了分解策略和机制,并利用改进后的MESMA,结合"黑土滩"的形成机制提取研究区的黑土滩信息。最后,采用实测数据对本文黑土滩识别结果进行精度验证,得到的精度为82.81%,较MESMA方法的71.09%有明显提高,说明改进后的MESMA可以有效识别黑土滩。利用本文方法得到玛多县黑土滩面积为1.592103 km2,主要分布在玛多县北部。该方法在保证"黑土滩"提取精度的同时,效率较传统的目视解译方法有了明显改善。该方法亦适用于其他复杂环境地表组分信息的提取。
The Multiple Endmember Spectral Mixture Analysis(MESMA)was used to extract the information to identify the Black Soil Land in a remote sensing image.Based on the MESMA proposed by Robert
the surface features in Maduo were analyzed while the endmembers were extracted. In consideration of the insufficient in applying MESMA to this research area
the decomposition strategy and its mechanism were optimized
then along with the formation mechanism of black soil land
modified MESMA was applied to extraction of the black soil land information. Identified results of black soil land was verified by the measured data
which shows the identifying accuracy is 82.81%
significantly higher than the accuracy of 71.09% from the MESMA and proves that the improved MESMA can identify the Black Soil Land effectively. On the basis of the improved MESMA
it indicates that the black soil land accounts for 1.592103 km2 in Maduo County
and it mainly distributes in the northern Maduo County.In conclusion
the extracting efficiency for Black Soil Land has improved significantly as compared to that of visual interpretation method in guaranteeing the extraction accuracy. Preliminary analysis demonstrates that this method can also be applied to the extraction of surface composition information in other complex environments.
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