Method and device for statistical monitoring of crop rotation and fallow conditions through remote sensing satellite photos
A technology of remote sensing satellites and photos, applied in measuring devices, satellite radio beacon positioning systems, radio wave measurement systems, etc., can solve the problems of different crop rotation and fallow conditions, lack of perfect method system for remote sensing monitoring, etc., and achieve accurate results
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Embodiment 1
[0062] The present embodiment provides a method for statistical monitoring of crop rotation and fallow through remote sensing satellite photos, comprising the following steps:
[0063] S1: Obtain the satellite remote sensing photos of the same area for one year from the end of June of the current year to the end of June of the next year, and divide the cultivated land plots in the satellite remote sensing photos into blocks; (for example, using the 0.8m resolution image of GF-2 based on machine learning The convolution algorithm of the arable land is used to identify the information of the cultivated land, the multi-scale segmentation method is used to identify the ridges and roads of the cultivated land, and the identification results can be further checked and corrected manually by combining with the high-resolution Google Earth image);
[0064] S2: Obtain the average value of NDVI value, Green value and Blue value of each block in each photo, NDVI=(ρ NIR -ρ R ) / (ρ NIR +ρ ...
Embodiment 2
[0083] The present embodiment provides a method for statistical monitoring of crop rotation and fallow through remote sensing satellite photos, comprising the following steps:
[0084] S1: Obtain satellite remote sensing photos of the same area for one year from the end of June of the current year to the end of June of the next year;
[0085] S2: Obtain the NDVI value, Green value and Blue value of each pixel in each photo, NDVI=(ρ NIR -ρ R ) / (ρ NIR +ρ R ), Green=ρ G / (ρ R +ρ G +ρ B ), Blue=ρ G / (ρ R +ρ G +ρ B ), ρ NIR , ρ R , ρ G , ρ B Respectively represent the reflectivity of the near-infrared band, the reflectance of the red band, the reflectance of the green band, and the reflectance of the blue band;
[0086] S3: Judging the NDVI value, Green value and Blue value of each pixel in the satellite remote sensing photo, the judgment is based on the following conditions:
[0087] If the conditions 1 and 5 are met and the condition 2 is not met, it is fallow and...
Embodiment 3
[0104] The present embodiment provides a device for statistical monitoring of crop rotation and fallow through remote sensing satellite photos, including:
[0105] Including, image acquisition module, image processing module, classification calibration module and result output module;
[0106] The image acquisition module is used to obtain satellite remote sensing photos of the same region for the whole year from the end of June of the current year to the end of June of the next year;
[0107] The image processing module is used to obtain the NDVI value, Green value and Blue value of each pixel in each photo, or first divide the cultivated land plot in the satellite remote sensing photo and obtain each image in each photo. The average of the NDVI, Green and Blue values of the blocks,
[0108] Among them, NDVI=(ρ NIR -ρ R ) / (ρ NIR +ρ R ), Green=ρ G / (ρ R +ρ G +ρ B ), Blue=ρ G / (ρ R +ρ G +ρ B ), ρ NIR , ρ R , ρ G , ρ B Respectively represent the reflectivity o...
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