E3S Web Conf.
Volume 206, 20202020 2nd International Conference on Geoscience and Environmental Chemistry (ICGEC 2020)
|Number of page(s)||4|
|Section||Earth Climate Change And Environmental Chemical Pollution Control|
|Published online||11 November 2020|
Farmland productivity estimation based on vegetation indexes from remote sensing data
1 Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, 100035 Beijing, China
2 Aerospace Information Research Institute, Chinese Academy of Science, 100094 Beijing China
3 Shenzhen Development Research Center for Real Estate and Urban Construction, 518000 Shenzhen, China
* Corresponding author: email@example.com
Ensuring food security is a long-term and arduous task. Timely and accurate grasp of grain production capacity information can provide favourable data support for the nation to formulate macroeconomic plans and food policies. With the development of remote sensing technology, it has been widely used in crop yield estimation models. In this paper, the yield of spring maize in Da’an of Jilin province was estimated based on vegetation indexes calculated from Landsat-8 images. The results have shown that the fitting degree and estimation accuracy of yield estimation models at tasselling stage are significantly better than those at milk stage. Among these vegetation indexes, the model based on GNDVI has better fitting degree and estimation accuracy. This paper can provide reference for the post construction evaluation of high standard farmland in China.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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