本数据集全面涵盖了巢湖流域、滁河流域、里下河地区及长三角示范区在2000年、2010年和2020年三个关键时间节点的人口密度分布情况，按高程带划分的精细化统计与分析。采用12.5米空间分辨率的高精度遥感解析技术，数据集提供了各高程带内的人口数量及全流域人口的详细统计结果。\n
高程带划分方法，更深入地理解人口分布与地形特征之间的复杂关系，以及这种关系如何随时间而演变。对于评估地形条件对人类居住选择的影响、预测未来人口分布格局以及制定针对性的区域发展规划具有重要意义。此外，通过对比三个时间节点的数据，数据集还展现了人口分布随时间的动态变化特征，为研究人员提供了宝贵的时间序列数据支持。这些变化特征不仅反映了社会经济条件的变迁，也隐含了自然环境对人类活动空间分布的影响。\n
本数据集为理解巢湖流域、滁河流域、里下河地区及长三角示范区的人口密度分布及其与地形高程的关系提供了详实的数据基础，对于区域规划、人口管理、环境保护等多个领域的研究与实践工作均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年的人口栅格数据，数据来自于国家及地方统计局发布的人口普查数据、经济统计数据以及专业GIS数据源。", "ds_process_way": "
（1）根据预设的高程带划分标准，使用ArcGIS的“栅格重分类”工具对人口栅格数据进行分类，得到各高程带的人口分布栅格。\n
（2）提取各高程带的人口：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，从人口栅格数据中提取出各高程带的人口总数。", "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人口密度情况，旨在动态跟踪和解析流域内人口、经济、重要保护对象的时空分布变化。结合地形、圩区、堤防等的空间分布信息以及洪水淹没和风险信息，利用这些数据评估承灾体的暴露性和危险性变化，识别流域内的主要风险点及风险对象，并及时进行排查。\n
采用了多种权威数据源，包括国家及地方统计局发布的人口普查数据、经济统计数据以及专业GIS数据源等，确保了数据的权威性和准确性。利用GIS软件和算法，进行了高精度空间分析，包括人口密度计算、时空分布变化分析等，确保了数据的空间分布和精度满足高标准要求。", "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": 318595985, "ds_files_count": 61, "ds_format": "*.adf", "ds_space_res": "30m", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "Albers Equal Area Conic Projection System", "ds_thumbnail": "e2d76a81-279d-460b-b82f-41d965a83b56.png", "ds_thumb_from": 0, "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": [ "170.45" ], "quality_level": 3, "publish_time": "2025-03-27 16:07:38", "last_updated": "2025-06-30 11:34:28", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NHRI.DB6775.2025", "i18n": { "en": { "title": "Data Set on Population Density in the Chaohu Lake Basin, Chu River Basin, Lishang River Area, and Yangtze River Delta Demonstration Area (2000-2020)", "ds_format": "*.adf", "ds_source": "
Population 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 census data released by the national and local statistical bureaus, economic statistics data, and specialized GIS data sources.", "ds_quality": "
This dataset focuses on the population density situation in the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River area, and the Yangtze River Delta Demonstration Area, aiming at dynamically tracking and parsing the changes in the spatial and temporal distribution of the population, the economy, and the important objects of protection in the basin. Combined with the spatial distribution information of topography, polder, embankment, etc., as well as flood inundation and risk information, these data are utilized to assess the changes in exposure and danger of the disaster-bearing body, to identify the main risk points and risk objects in the basin, and to carry out timely investigation.\n
A variety of authoritative data sources were used, including census data released by national and local statistical bureaus, economic statistics, and specialized GIS data sources to ensure the authority and accuracy of the data. Using GIS software and algorithms, high-precision spatial analyses were carried out, including population density calculations and analysis of changes in spatial and temporal distribution, to ensure that the spatial distribution and accuracy of the data met the requirements of high standards.", "ds_ref_way": "", "ds_abstract": "
This dataset comprehensively covers the distribution of population density in the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River area and the Yangtze River Delta Demonstration Area at three key time points, 2000, 2010 and 2020, with refined statistics and analysis by elevation bands. Adopting high-precision remote sensing analysis technology with 12.5-meter spatial resolution, the dataset provides detailed statistics on the number of people within each elevation band and the population of the whole basin.\n
The elevation band delineation method provides a deeper understanding of the complex relationship between population distribution and topographic features, and how this relationship evolves over time. It is of great significance for assessing the impact of topographic conditions on human settlement choices, predicting future population distribution patterns, and formulating targeted regional development plans. In addition, by comparing the data at the three time points, the dataset also demonstrates the dynamic change characteristics of population distribution over time, providing researchers with valuable time series data support. These changing features not only reflect the changes in socio-economic conditions, but also imply the influence of the natural environment on the spatial distribution of human activities.\n
This dataset provides a detailed data base for understanding the distribution of population density and its relationship with topographic elevation in the Chaohu Lake Basin, the Chu River Basin, the Lishiahe River area and the Yangtze River Delta Demonstration Area, and it is of great value for research and practice in the fields of regional planning, population management and environmental protection.
", "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) Classify the population raster data according to the preset elevation zones, using the “raster reclassification” tool of ArcGIS to get the population distribution raster of each elevation zone.\n
(2) Extract the population of each elevation zone: Use the “Regional Analysis” or “Extract by Mask” function of ArcGIS to extract the total population of each elevation zone from the population raster data, using the raster of the elevation zone as a mask. The total population of each elevation zone is extracted from the population raster data using the elevation zone 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", "人口密度", "遥感影像" ], "ds_subject_tags": [ "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": "其他" }