Multi-source remote sensing data-based ghost phenomenon recognition and analysis method
A technology of remote sensing data and analysis methods, applied in image analysis, image data processing, data processing applications, etc.
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Embodiment 1
[0038] Such as figure 1 As shown, in this embodiment, a method for identifying and analyzing ghost town phenomena based on multi-source remote sensing data is provided, including the following steps,
[0039] S1. Obtain the land index parameters and population index parameters of the target area;
[0040] S2. Obtain the time, space and scene characteristics of the ghost town phenomenon in the target area based on the land index parameters and population index parameters in the target area, and construct an improved ghost town index that includes various feature-related index parameters;
[0041] S3. Grading and evaluating the improved ghost town index, correspondingly forming categories of different levels of ghost town phenomena, and realizing the identification and analysis of the temporal and spatial distribution of ghost town phenomena in the target area and their level classification.
[0042] In this embodiment, the identification and analysis method provided by the pre...
Embodiment 2
[0070] In this embodiment, the execution process of the recognition and analysis method provided by the present invention will be described in detail in combination with specific examples. The test data used MCD12Q1 land cover data with a resolution of 500m and NPP-VIIRS luminous remote sensing data, as well as GlobeLand30 land cover data with a resolution of 30m and Landsat 7ETM+ images, and the coordinate system was WGS84. The test area is oriented to Nanning, Liuzhou, Guilin, Wuzhou, Beihai, Fangchenggang, Qinzhou, Guigang, Chongzuo, Laibin, Hezhou, Yulin, Baise and Hechi in the Guangxi Zhuang Autonomous Region along the Silk Road Economic Belt in 2008 and 2010. Correspondingly referring to the data of the China Urban Statistical Yearbook and the China Urban Construction Statistical Yearbook, based on the above-mentioned various types of ghost town indices, the temporal and spatial distribution of ghost town phenomena and their corresponding degrees in the experimental area ...
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