东北三省2020-2022年间10 m空间分辨率耕地资源空间分布数据集

doi:10.19788/j.issn.2096-6369.230202

农业大数据学报 ›› 2023, Vol. 5 ›› Issue (2): 2-8.doi: 10.19788/j.issn.2096-6369.230202

• “共享杯”农业科学专业赛优秀作品 • 上一篇下一篇

东北三省2020-2022年间10 m空间分辨率耕地资源空间分布数据集

申格¹(), 刘航², 李丹丹³, 陈实⁴, 邹金秋^3,^*()

1.浙江财经大学土地与城乡发展研究院，杭州 310018
2.浙江财经大学东方学院，浙江嘉兴 314408
3.中国农业科学院农业资源与农业区划研究所，北京 100081
4.池州学院地理与规划学院，安徽池州 247000

收稿日期:2023-06-06 出版日期:2023-06-26 发布日期:2023-08-15
通讯作者: 邹金秋
作者简介:申格，博士，助理研究员，研究方向：农业遥感及农业土地系统可持续；E-mail：shenge@zufe.edu.cn。
基金资助:
国家重点研发计划课题(2022YFF0711803);浙江省自然科学基金(LQ23D010001)

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

SHEN Ge¹(), LIU Hang², LI DanDan³, CHEN Shi⁴, ZOU JinQiu^3,^*()

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:2023-06-06 Online:2023-06-26 Published:2023-08-15
Contact: ZOU JinQiu

摘要/Abstract

摘要：

及时准确地获取耕地空间分布数据对于农业生产管理、种植结构调整、保障粮食安全等具有重要意义。本研究以东北三省（黑龙江省、辽宁省、吉林省）为研究区，基于哨兵二号（Sentinel-2）卫星影像数据，建立每一省份特定年份的耕地与非耕地样本12个月份的归一化差分植被指数（NDVI）数据集库；利用Google Earth Engine遥感计算平台，依据耕地与非耕地样本的NDVI的差异性特征进行监督分类，建立了黑龙江省、辽宁省、吉林省等东北三省2020—2022年间逐年10 m空间分辨率耕地资源空间分布数据集。该数据集为东北地区最近年份的耕地资源空间分布数据集更新，可为该地区的黑土地科学保护、“藏粮于地，藏粮于技”战略实施以及粮食安全保障提供数据支撑和科学服务。

关键词: 耕地资源, 遥感, Sentinel-2, Google Earth Engine

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

申格, 刘航, 李丹丹, 陈实, 邹金秋. 东北三省2020-2022年间10 m空间分辨率耕地资源空间分布数据集[J]. 农业大数据学报, 2023, 5(2): 2-8.

SHEN Ge, LIU Hang, LI DanDan, CHEN Shi, ZOU JinQiu. 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.

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参考文献 13

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波段	中央波长 (μm)	空间分辨率 (m)
波段1 -沿海气溶胶	0.443	60
波段2 - 蓝	0.49	10
波段3 - 绿	0.56	10
波段4 - 红	0.665	10
波段5 - 植被红边	0.705	20
波段6 -植被红边	0.74	20
波段7 -植被红边	0.783	20
波段8 - 近红外	0.842	10
波段8A -植被红边	0.865	20
波段9 - 水蒸气	0.945	60
波段10 - 短波红外线－卷云	1.375	60
波段11 -短波红外线	1.61	20
波段12 -短波红外线	2.19	20

时段	黑龙江省			辽宁省			吉林省
时段	2020	2021	2022	2020	2021	2022	2020	2021	2022
1月	1119	1109	1119	419	399	419	473	479	473
2月	1048	1030	1054	379	385	393	456	467	469
3月	1151	1152	1173	420	427	424	506	498	502
4月	1137	1129	1156	410	412	414	477	473	473
5月	1145	1156	1190	424	422	425	496	498	500
6月	1124	1093	1153	405	401	398	497	480	486
7月	1137	1157	1194	410	422	421	476	498	498
8月	1141	1160	1188	425	424	421	504	498	503
9月	1134	1105	1149	403	386	397	484	474	482
10月	1138	1151	1205	419	424	431	498	497	511
11月	1072	1099	1103	392	412	425	481	487	503
12月	1156	1122	0	441	424	0	503	488	0
小计	13502	13463	12684	4947	4938	4568	5851	5837	5400
总计	71190

地区	2020	2021	2022
黑龙江省	95.24	93.88	89.80
辽宁省	97.81	97.08	91.24
吉林省	96.27	95.65	93.16

东北三省2020-2022年间10 m空间分辨率耕地资源空间分布数据集

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

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