2020 年新疆和中亚五国范围 30m 耕地种植强度空间分布产品 (GCI30_2020)是从全球产品中按新疆和中亚五国边界挑选出来的，未做任何其他的加工处理，保留了原数据的地理空间信息、数据精度和数据组织形式。数据格式Geotiff，空间分辨率30m，按10°×10°格网组织，覆盖新疆范围的有6个格网，覆盖中亚五国的有14个格网。
", "ds_source": "2020 年全球 30m 耕地种植强度空间分布产品 (GCI30_2020)的研制主要采用2019-2021年间中高分辨率遥感数据。由于南北半球不同纬度农作物生育期差异，使得全球不同地区的耕地种植强度空间分布研究所需遥感数据在时段选择上存在不同，北半球大部分地区采用 2019年2月2日-2022年2月1日期间的数据；南半球大部分地区采用2018年11月1日-2021年10月31日期间的数据；部分地区由于物候期特殊，采用2018年8月下旬至2021年8月中旬的数据。产品地理范围包括东经180°到西经180°和南纬60°到北纬80°，南北半球高纬度地区及海洋不在监测范围之内。
\n全球产品采用分块方式存储，分块文件按10°×10°格网组织，共有293个格网。各影像块按左上角经纬度进行编码，纬度在前，经度在后，纬度2位数字加上南北纬（S/N）标识前缀、经度为3位数字加上东西经（E/W）标识前缀，其中纬度0 度处用N、经度0 度处用E 标识。数据产品中，每个分块文件包含2 个图层，其中图层一是2019-2021 年间各耕地像元种植作物的次数，数值类型为整型，有效值小于100，数值100 代表背景像元；图层二是2020 年耕地像元种植作物的次数，数值类型为整型，数值1代表单季种植模式，数值2代表双季种植模式，数值3代表双及以上种植模式，数值100 代表背景像元。
", "ds_process_way": "未做地理信息处理。
", "ds_quality": "产品精度评价方面，数据生产过程中，全流程使用标准算法生成，无人工干预，数据客观公正；数据导出后，有专人负责数据质量检查，所有共享的293个数据块均符合质量要求。在全球8 个10° ×10°区域的精度验证显示30m 分辨率耕地复种指数算法的平均精度为90.4%；进一步在全球不同农业生态区进行分层抽样，确定了3662 个复种指数验证样本，对全球数据产品进行精度验证，总体精度为92.9%。
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1901330306, "ds_files_count": 39, "ds_format": "GeoTiff格式", "ds_space_res": "30米", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "4a7ab24c-ffa3-47dd-9bc3-b60826daee57.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "张淼.2020 年全球 30m 耕地种植强度空间分布产品 (GCI30_2020),可持续发展大数据国际研究中心,2022.doi:10.12237/casearth.62ff4caa819aec75a535cbe7", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 1, "publish_time": "2025-08-06 16:30:59", "first_publish_time": null, "last_updated": "2025-08-06 16:30:59", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "extra": null, "files_shape": [ { "name": "cropping_intensity_30m_2019_2021_CA", "size": null, "is_dir": true }, { "name": "cropping_intensity_30m_2019_2021_XJ", "size": null, "is_dir": true } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "Spatial distribution products of planting intensity of 30m cultivated land in Xinjiang and five Central Asian countries in 2020 (GCI30_2020)", "ds_abstract": "The 2020 spatial distribution product of planting intensity of 30m cultivated land in Xinjiang and the five Central Asian countries (GCI30_2020) was selected from global products according to the borders of Xinjiang and the five Central Asian countries. No other processing was carried out, and the original data was retained. Geospatial information, data accuracy and data organization form. The data format Geotiff, with a spatial resolution of 30m, is organized as a 10°×10° grid. There are 6 grids covering Xinjiang and 14 grids covering five Central Asian countries.
", "ds_source": "The development of the Global Spatial Distribution Product for Planting Intensity of 30m Cultivated Land in 2020 (GCI30_2020) mainly uses medium and high resolution remote sensing data from 2019 to 2021. Due to the differences in crop growth periods at different latitudes in the northern and southern hemispheres, the remote sensing data required for studying the spatial distribution of cultivated land planting intensity in different regions of the world have different time periods. Most areas in the northern hemisphere use data from February 2, 2019 to February 1, 2022; Most areas in the southern hemisphere use data from November 1, 2018 to October 31, 2021; Due to the special phenological period in some areas, data from late August 2018 to mid-August 2021 are used. The geographical range of the product includes 180° east longitude to 180° west longitude and 60° south latitude to 80° north latitude. High latitude areas in the northern and southern hemispheres and oceans are not within the monitoring range.
\nGlobal products are stored in a segmented manner, and segmented files are organized in a 10°×10° grid, with a total of 293 grids. Each image block is encoded according to the latitude and longitude in the upper left corner, with latitude at the front and longitude at the back. The latitude is 2 digits plus the south and north latitude (S/N) identification prefix, and the longitude is 3 digits plus the east-west longitude (E/W) identification prefix. Among them, N is used at 0 degrees latitude and E is used at 0 degrees longitude. In the data product, each block file contains 2 layers, of which layer 1 is the number of times crops were planted by each cultivated cell from 2019 to 2021. The numerical type is integer, and the effective value is less than 100. The value of 100 represents the background cell; Layer 2 is the number of times crops were planted by cultivated land cells in 2020. The numerical type is integer. The value 1 represents a single-season planting pattern, the value 2 represents a dual-season planting pattern, the value 3 represents a dual-season planting pattern and the value 100 represents a background cell.
", "ds_process_way": "No geographical information processing was performed.
", "ds_quality": "In terms of product accuracy evaluation, during the data production process, the entire process is generated using standard algorithms without manual intervention, and the data is objective and fair; after the data is exported, a special person is responsible for data quality inspection, and all shared 293 data blocks meet quality requirements. Accuracy verification in 8 10° ×10° regions around the world showed that the average accuracy of the 30-m resolution cultivated land multiple cropping index algorithm was 90.4%. Further stratified sampling was carried out in different agricultural ecological regions around the world, and 3662 multiple cropping index verification samples were identified. For accuracy verification of global data products, the overall accuracy was 92.9%.
", "ds_ref_instruction": "Zhang Miao. 2020 Global Spatial Distribution Products of Planting Intensity of 30m Arable Land (GCI30_2020), International Research Center for Big Data for Sustainable Development, 2022.doi:10.12237/casearth.62ff4caa819aec75a535cbe7", "ds_format": "GeoTiff format", "ds_space_res": "30 meters", "ds_time_res": "years" } }, "license_type": null, "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "强度", "种植", "耕地" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "吉尔吉斯斯坦", "土库曼斯坦", "塔吉克斯坦", "新疆", "乌兹别克斯坦", "哈萨克斯坦" ], "ds_time_tags": [ 2020 ], "ds_contributors": [ "李锦" ], "ds_meta_authors": [ "李锦" ], "ds_managers": [ "李锦" ], "category": "农业" }