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

A GF-1, data reconstruction technology, applied in data processing applications, complex mathematical operations, calculations, etc., can solve problems such as low resolution, data affected by meteorological factors, and data discontinuity

CN110245327AActive Publication Date: 2019-09-17徐博
4 Cites 8 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2019-09-17

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

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.
Need to check novelty before this filing date? Find Prior Art

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 ...

Examples

Embodiment Construction

[0090] The core of the invention is to provide a method for estimating wheat yield per unit area remote sensing based on GF-1 data reconstruction.

[0091] Below in conjunction with accompanying drawing, content of the present invention will be further described:

[0092] A method for estimating wheat yield per unit area remote sensing based on GF-1 data, when implemented, includes the following steps:

[0093] Step1: Collect and download time-series MODIS (NDVI 16-day synthetic product) data and GF-1 data (collect time-series data during the complete growth cycle of crops) in the study area

[0094] (1) Data introduction

[0095] MODIS data is a medium-resolution sensor in NASA's Earth Observation Satellite Program. It uses 16-day synthetic NDVI data in EOS-Modis / Terra. The spatial resolution of the image is 250m, and the data format is HDF. It is the vegetation index product MOD13 in MODIS land products;

[0096] The download address of the data is:

[0097] https: / / lpda...