中国科学数据（中英文网络版）2023，Vol.8Issue(4)：329-339,11.DOI:10.11922/11-6035.noda.2023.0003.zh
2020-2022年三江平原主要农作物种植分布遥感监测数据集
A dataset of remote sensing monitoring of planting distribution for major crops in Sanjiang Plain from 2020 to 2022
摘要
Abstract
Sanjiang Plain,renowned for its expansive and fertile black soil,serves as a crucial hub for commodity grain production in China.The per capita cultivated land area and per capita grain output in the region are five times the national average.Accurate crop acreage information is of great significance for understanding regional food security and agricultural development planning in Sanjiang Plain.In this paper,we used the Sentinel-2 satellite remote sensing data of time series and the survey data of typical ground features in Sanjiang Plain to screen the feature bands of major crops and typical ground features of surrounding areas.Using the random forest classification algorithm,we extracted the data to produce a dataset of remote sensing monitoring of planting distribution for major crops(rice,corn and soybean)in Sanjiang Plain from 2020 to 2022.Based on field survey data,it has been verified that the overall accuracy of the three crops extraction in 2020,2021 and 2022 stands at 95.18％,95.0％and 94.5％,and the Kappa coefficients of these three years are 0.924,0.925 and 0.919.This dataset can not only offer basic data for the analysis of temporal and spatial changes of crop planting distribution in Sanjiang Plain,but also contribute to informed decision-making in agricultural production management for the region.Furthermore,it can support the development of agricultural informatization as well as the preservation and utilization of black soil resources.关键词
三江平原/Sentinel-2数据/作物分类Key words
Sanjiang Plain/Sentinel-2/classification of crops引用本文复制引用
乔树亭,叶回春,刘荣豪,郭安廷,张冰瑞,钱彬祥,魏鹏,黄文江..2020-2022年三江平原主要农作物种植分布遥感监测数据集[J].中国科学数据（中英文网络版）,2023,8(4):329-339,11.基金项目
中国科学院战略性先导科技专项(XDA28100500) （XDA28100500）
国家自然科学基金项目(42001384) （42001384）
中国科学院青年创新促进会项目(2021119).Strategic Leading Science and Technology Project,Chinese Academy of Sciences(XDA28100500) （2021119）
National Natural Science Foundation of China(42001384) （42001384）
Youth Innovation Promotion Association Project of Chinese Academy of Sciences(2021119). （2021119）
