Rice yield remote sensing estimation method based on MODIS data

Abstract

The invention discloses a rice yield remote sensing estimation method based on MODIS data, which comprises: 1) acquiring the MODIS09 remote sensing data in the growth process of the rice in the region to be monitored, and calculating an vegetation index EVI and a water index LSWI; 2) extracting a rice pixel based on the relation between the water index LSW1 and the vegetation index EVI; 3) acquiring the vegetation index EVI corresponding to the rice in different stages; 4) calculating the average of the vegetation indexes EVIs of different set administrative regions in different stages to acquire the average EVI of the set administrative regions; 5) establishing a statistical model for the average EVI of the set administrative regions and the rice yield; and 6) estimating the rice yields of the set administrative regions using the vegetation index EVI in the growth period of rice in the year to be estimated, and calculating the rice yield of the region to be monitored. The temporal resolution, the spatial resolution and the estimation precision of the invention are relatively high, and the invention is applicable to monitoring rice yield in a large scale.

Description

technical field [0001] The invention relates to the application of satellite remote sensing and earth observation to the field of rice per unit yield, in particular to a method for estimating rice per unit yield by remote sensing based on MODIS data. Background technique [0002] Traditional rice production estimation is slow, heavy workload and high cost. At present, the channels for obtaining rice production data can be summarized as follows: statistical departments at all levels calculate data based on crop yield sampling surveys and general survey data, agricultural sector general survey data, and meteorological departments calculate based on previous meteorological conditions and forecast models production data. Compared with conventional statistical methods, remote sensing technology has unique advantages in extracting rice planting area and estimating yield. Remote sensing technology has the characteristics of multi-spectrum, multi-temporal and macro characteristics...

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the disadvantages of low time and space resolution and low precision of existing rice yield remote sensing estimation methods, which are not suitable for large-scale monitoring of rice yield, the present invention provides a relatively high time and space resolution and yield estimation accuracy, which is suitable for large-scale Remote Sensing Estimation Method of Rice Yield Based on MODIS Data for Range Monitoring of Rice Yield

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