Wheat yield per unit remote sensing estimation method based on GF-1 data reconstruction

Abstract

The invention relates to the technical field of crop yield prediction, in particular to a wheat yield per unit remote sensing estimation method based on GF-1 data reconstruction, and the method comprises the following steps: 1) collecting and downloading time sequence original MODIS data and GF-1 data in a research area; 2), extracting QA quality parameters of the MODIS; 3) carrying out projection conversion, purification, filtering and cutting on the MODIS data; 4), treating GF-1 data; step 5), substituting the data in the step 3) and the step 4) into the reconstruction model to reconstruct new data; 6) obtaining a wheat planting distribution map and an NDVI map; 7)collecting and treating data in meterological stations, 8) estimating the yield by a yield estimation model, and 9) verifying and analyzing the precision of the yield estimation model. The wheat yield per unit remote sensing estimation method based on GF-1 data reconstruction has the advantages of being accurate in yield estimation, complete in data, high in yield estimation model leakproofness and good in integrity.

Description

technical field [0001] The invention relates to the technical field of crop yield prediction technology, in particular to a method for estimating wheat yield per unit area remote sensing based on GF-1 data reconstruction. Background technique [0002] Crop yield estimation has been a shortcoming in agricultural remote sensing for many years, and the two biggest factors restricting yield estimation are: 1. Lack of satellite time series data; 2. Inaccurate meteorological data; 3. Serious lack of sample data, satellite time series data The chain break makes it impossible to monitor the growth and health of crops in their growth period in real time. Therefore, solving the timeliness and continuity of data is the key to monitoring crops; in addition, the spatial inaccuracy of meteorological data is also an important reason why the production estimation model cannot be accurately established, and the data obtained by meteorological stations cannot accurately represent the data of ...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the existing problems of discontinuous data, low yield estimation accuracy, too low resolution and data affected by meteorological factors, the present invention provides a wheat per unit area yield estimation based on GF-1 data reconstruction with higher accuracy and higher precision. Remote Sensing Estimation Method

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