本数据集详细记录了巢湖流域、滁河流域、里下河地区以及长三角示范区在2000年、2010年和2020年三个重要时间节点的GDP数据，采用12.5米空间分辨率的高精度遥感解析技术，这些数据按照高程带进行了精细划分，旨在揭示不同地形高度对经济活动分布的影响及其随时间的变化趋势。\n
数据集能够直观看到各高程带经济总量的绝对增长，还能洞察到经济活动在不同高程区域间的相对转移和集聚情况。通过对比三个时间点的数据，数据集清晰地描绘了各流域及示范区GDP随高程变化的时空演变特征。这些特征不仅反映了地形条件对经济发展的制约与促进作用，也揭示了区域经济结构的调整与优化过程。\n
本数据集为深入研究巢湖流域、滁河流域、里下河地区及长三角示范区的经济发展与地形高程之间的关系提供了丰富而详实的数据支持，对于区域经济规划、政策制定以及可持续发展研究等领域具有重要的参考价值。", "ds_source": "
收集到巢湖流域、滁河流域、里下河地区、长三角示范区在2000年、2010年、2020年的GDP栅格数据，数据来自于国家及地方统计局、经济研究机构等发布的官方GDP数据，以及企业调研、市场研究报告。", "ds_process_way": "
（1）根据高程带划分标准，使用ArcGIS的“栅格重分类”工具对GDP栅格数据进行重分类，即根据每个高程带对GDP进行划分。\n
（2）提取各高程带的GDP：使用ArcGIS的“区域分析”或“按掩膜提取”功能，以高程带栅格为掩膜，从GDP栅格数据中提取出各高程带的GDP值。", "ds_quality": "
本数据集专注于巢湖流域、滁河流域、里下河地区以及长三角示范区的GDP情况，旨在通过动态跟踪和解析流域内人口、经济等重要因素的时空分布变化，为评估承灾体暴露性和危险性的变化、识别流域内的主要风险点及风险对象提供数据支持。\n
整合了国家及地方统计局、经济研究机构等发布的官方GDP数据，以及企业调研、市场研究报告等多元数据源，确保数据的权威性和全面性。\n
利用GIS技术将GDP数据与地理空间信息相结合，实现了高精度空间化处理，能够准确反映各流域内的经济分布状况。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "巢湖流域,滁河流域,里下河地区,长三角示范区", "ds_acq_lon_east": 122.26, "ds_acq_lat_south": 30.8, "ds_acq_lon_west": 116.39, "ds_acq_lat_north": 34.63, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 3704353, "ds_files_count": 37, "ds_format": "*.adf", "ds_space_res": "30m", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "Albers Equal Area Conic Projection System", "ds_thumbnail": "40708a25-f8f3-43e9-80e0-a5554b6c005b.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "37eb642a-c117-47e4-a677-07ecffb4b8b7", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2025-03-27 15:59:34", "last_updated": "2025-06-30 11:40:07", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NHRI.DB6774.2025", "i18n": { "en": { "title": "GDP dataset of Chaohu Lake Basin, Chu River Basin, Lishang River Region and Yangtze River Delta Demonstration Area (2000-2020", "ds_format": "*.adf", "ds_source": "
GDP raster data for the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River Region, and the Yangtze River Delta Demonstration Area in 2000, 2010, and 2020 were collected from official GDP data released by national and local statistical bureaus, economic research organizations, and other official GDP data, as well as from corporate research and market research reports.", "ds_quality": "
This dataset focuses on the GDP of the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River Region and the Yangtze River Delta Demonstration Zone, and is designed to dynamically track and analyze the changes in the spatial and temporal distribution of the population, the economy and other important factors in the basin, so as to provide data support for the assessment of the changes in the exposure and the risk of disaster-bearing bodies, and for the identification of the main risk points and risk objects in the basin.\n
Integrates official GDP data released by national and local statistical bureaus and economic research organizations, as well as corporate research, market research reports and other multiple data sources to ensure the authority and comprehensiveness of the data.\n
Using GIS technology to combine GDP data with geospatial information, it realizes high-precision spatialization processing, and is able to accurately reflect the economic distribution within each basin.", "ds_ref_way": "", "ds_abstract": "
This dataset records the GDP data of the Chaohu Lake Basin, Chu River Basin, Lishiahe River area and the Yangtze River Delta Demonstration Area at three important time nodes, 2000, 2010 and 2020, and adopts the high-precision remote sensing analysis technology with a spatial resolution of 12.5 meters, which is finely divided into elevation bands, aiming to reveal the impacts of different topographic heights on the distribution of economic activities and their trends over time. The data are finely divided into elevation bands, aiming to reveal the effects of different terrain heights on the distribution of economic activities and their trends over time.\n
The dataset is able to visualize the absolute growth of the total economic volume in each elevation zone, and also provides insight into the relative transfer and agglomeration of economic activities among different elevation zones. By comparing the data at three time points, the dataset clearly depicts the spatial and temporal evolution characteristics of GDP with elevation changes in each watershed and demonstration area. These features not only reflect the constraining and promoting effects of topographic conditions on economic development, but also reveal the adjustment and optimization process of regional economic structure.\n
This dataset provides rich and detailed data support for the in-depth study of the relationship between economic development and topographic elevation in the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River Region and the Yangtze River Delta Demonstration Area, and is of great value in the fields of regional economic planning, policy making, and sustainable development research.
", "ds_time_res": "", "ds_acq_place": "Chaohu River Basin, Chuhe River Basin, Lixiahe Region, Yangtze River Delta Demonstration Zone", "ds_space_res": "30m", "ds_projection": "", "ds_process_way": "(1) According to the standard of elevation band classification, use the “raster reclassification” tool of ArcGIS to reclassify the raster data of GDP, i.e., classify the GDP according to each elevation band.\n
(2) Extract the GDP of each elevation zone: Use the “Regional Analysis” or “Extract by Mask” function of ArcGIS to extract the GDP values of each elevation zone from the GDP raster data, using the elevation zone raster as a mask. GDP value of each elevation band from the GDP raster data, using the elevation band raster as a mask.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "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": [ "示范区", "GDP" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "巢湖流域", "滁河流域", "里下河地区", "长三角示范区" ], "ds_time_tags": [ 2000, 2010, 2020 ], "ds_contributors": [ { "true_name": "胡庆芳", "email": "hqf_work@163.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "胡庆芳", "email": "hqf_work@163.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "胡庆芳", "email": "hqf_work@163.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "category": "遥感及产品" }