Journal of Agricultural Big Data ›› 2025, Vol. 7 ›› Issue (1): 22-30.doi: 10.19788/j.issn.2096-6369.100035

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Fine Classification Dataset of Crops in the Transboundary Basin of the Heilongjiang River Between Russia and China, 2015-2023

LIU Meng1,2(), WANG JuanLe1,3,5,*(), LI Kai1,3, JIANG JiaWei1,4, ZOU WeiHao1,4   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang, Jiangsu 222005, China
    3. University of Chinese Academy of Sciences, College of Resources and Environment, Beijing 100049, China
    4. China University of Mining and Technology, School of Earth Science and Surveying and Mapping Engineering, Beijing 100083, China
    5. Jiangsu Centre for Collaborative Innovation in Geographical Information Resource Development and Ap-plication, Nanjing 210023, China
  • Received:2024-05-16 Accepted:2024-07-31 Online:2025-03-26 Published:2025-02-05
  • Contact: WANG JuanLe

Abstract:

The Heilongjiang transboundary basin region, where the Russian Far East and northeastern China are located, is rich in natural resources and has great potential for the development and utilization of agricultural resources. Facing the crisis of increasing global conflicts and shortage of food supply chain, strengthening the monitoring and development and utilization of agricultural resources in the Heilongjiang basin is of great significance to guarantee global food security. In this dataset, the Heilongjiang transboundary watershed is used as the study area, and machine learning and sample migration methods are applied to construct a comprehensive set of fine classification system for agricultural crops. Based on historical remote sensing image data and the Google Earth Engine (GEE) cloud platform, the classification of major crops such as wheat, corn, soybean and rice in 2015, 2020 and 2023 was completed with an overall accuracy of more than 84% and a Kappa coefficient of more than 0.81, using Landsat images as the data source. The analysis of spatial and temporal changes reveals the pattern and changing characteristics of crops in the Heilongjiang transboundary watershed, and provides decision-making support for the optimal allocation of arable land resources in this watershed.

Data summary:

Item Description
Dataset name
Specific subject area Land resources and information technology
Research topic Fine classification of crops in the transboundary basin of the Heilongjiang River
Time range 2015, 2020, 2023year
Temporal resolution year
Geographical scope Heilongjiang Transboundary Basin
Spatial resolution 10 m, 30 m
Data types and technical formats .tif
Dataset structure This dataset contains fine categorized data of crops in the transboundary basin of Heilongjiang for the years 2015, 2020 and 2023, each year corresponds to 8 Tiff files, totaling 24 records.
Volume of dataset 1.92 GB
Key index in dataset Fine classification of crops (wheat, maize, soybean, rice) in the transboundary basin of the Heilongjiang River
Data accessibility https://cstr.cn/17058.11.sciencedb.agriculture.00041
https://doi.org/10.57760/sciencedb.agriculture.00041
Financial support The ANSO "Belt and Road" International Alliance of Scientific Organizations (Grant No. AN-SO-CR-KP-2022-06), the China Science and Technology Basic Resource Survey Program (Grant No. 2022FY101902), China Engineering Science and Technology Knowledge Center Construction Project (Grant No. CKCEST-2023-1-5)

Key words: crop classification, Sentinel-2, Landsat, Random forest