Journal of Agricultural Big Data >

2023 , Vol. 5 >Issue 2: 2 - 8

DOI: https://doi.org/10.19788/j.issn.2096-6369.230202

A 10 m Spatial Resolution Dataset for the Spatial Distribution of Cropland Resources in the Three Northeastern Provinces from 2020 to 2022

  • Ge SHEN ,
  • Hang LIU ,
  • DanDan LI ,
  • Shi CHEN ,
  • JinQiu ZOU
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  • 1. Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China
    2. Dongfang College, Zhejiang University of Finance and Economics, Jiaxing 314408, Zhejiang, China
    3. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    4. School of Geography and Planning, Chizhou University, Chizhou 247000, Anhui, China

Received date: 2023-06-06

  Online published: 2023-08-15

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Abstract

Timely and accurate acquisition of cropland spatial distribution data is of great significance for agricultural production management, planting structure adjustment and food security. In this study, three northeastern provinces (Heilongjiang, Liaoning and Jilin) were selected as the research area. Based on massive Sentinel-2 data, a 12-month Normalized Difference Vegetation Index (NDVI) dataset of cropland and non-cropland samples in a specific year was established in each province. The Google Earth Engine remote sensing computing platform was used to conduct supervised classification according to the difference characteristics of NDVI between cropland and non-cropland samples, and the spatial distribution data set of cropland resources with 10 m spatial resolution in the three northeastern provinces during 2020-2022 was obtained. The data set is an update of the latest available cropland resource data set, which can provide data support and scientific services for the scientific protection of phaeozem in Northeast China, the implementation of the strategy of "storing grain in land, storing grain in technology" and the guarantee of food security.

Key words： cropland; remote sensing; Sentinel-2; Google Earth Engine

Cite this article

Ge SHEN , Hang LIU , DanDan LI , Shi CHEN , JinQiu ZOU . A 10 m Spatial Resolution Dataset for the Spatial Distribution of Cropland Resources in the Three Northeastern Provinces from 2020 to 2022[J]. Journal of Agricultural Big Data, 2023 , 5(2) : 2 -8 . DOI: 10.19788/j.issn.2096-6369.230202

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