2000年黑河流域人口格网化数据基于2000年的1：10万土地利用数据和各县人口统计数据生成。
\n\n用主成分分析和因子分析法从11 个区划指标中提取出四个因子，利用因子得分进行分层聚类，把黑河流域分为4 个人口分布特征区域。基于2000年各县人口统计数据建立农村居民地、耕地面积与农村人口之间的线性回归模型，控制各区县内的人口总数，采取不同人口分布特征区域区别对待的原则对人口系数做必要调整，中游绿洲修正耕地人口分布系数，上游山区和下游荒漠绿洲区增加草地人口分布系数。采用加幂指数模型模拟流域城市人口密度的空间分布。基于以上方法最终获得黑河流域25m 格网的人口空间分布结果和尺度上推后的1km 格网数据。
\n\n在乡镇级别对人口空间化结果进行精度验证，并与已有数据库（GPW 1995、UNEP/GRID1995、LandScan 2002 和cn2000pop）估计的黑河流域人口数据进行比较分析，结果均表明本研究采用的方法和模型可以获得更高精度的流域人口空间分布数据。
", "ds_source": "2000年的1：10万土地利用数据和各县人口统计数据
", "ds_process_way": "主成分分析和因子分析法
", "ds_quality": "在乡镇级别对人口空间化结果进行精度验证，并与已有数据库（GPW 1995、UNEP/GRID1995、LandScan 2002 和cn2000pop）估计的黑河流域人口数据进行比较分析，结果均表明本研究采用的方法和模型可以获得更高精度的流域人口空间分布数据。
", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2015-12-31 00:00:00", "ds_acq_place": "黑河流域", "ds_acq_lon_east": 102.01666666666667, "ds_acq_lat_south": 37.416666666666664, "ds_acq_lon_west": 97.23305555555555, "ds_acq_lat_north": 42.416666666666664, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 14194458, "ds_files_count": 3, "ds_format": "栅格", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "+proj=longlat +datum=WGS84 +no_defs ", "ds_thumbnail": "0efeac71-5cbf-4eaa-80bd-7ffa9b06f51d.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e", "ds_serv_man": "黑河计划数据管理中心", "ds_serv_phone": "0931-4967287", "ds_serv_mail": "westdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4520" ], "quality_level": 3, "publish_time": "2020-04-08 17:27:51", "last_updated": "2023-08-23 16:47:01", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.Westdc.2020.448", "i18n": { "en": { "title": "Gridded population data of the Heihe river basin in 2000", "ds_format": "Raster", "ds_source": "1:10 million land use data and county population statistics in 2000
", "ds_quality": "At the township level, the accuracy of the results of population spatialization is verified, and compared with the population data of Heihe River Basin estimated by the existing databases (GPW 1995, UNEP / grid1995, landscan 2002 and cn2000pop). The results show that the methods and models used in this study can obtain more accurate spatial distribution data of population in the basin.
", "ds_ref_way": "", "ds_abstract": "In 2000, the population grid data of Heihe River Basin was generated based on 1:100000 land use data and population statistics data of each county in 2000.
\nUsing principal component analysis and factor analysis, four factors are extracted from 11 regionalization indexes, and the Heihe River Basin is divided into four population distribution characteristic regions by using factor scores for hierarchical clustering. The linear regression model between rural residential land, cultivated land area and rural population is established based on the population statistical data of each county in 2000. The total population of each district and county is controlled. The population coefficient is adjusted according to the principle of different population distribution characteristics. The cultivated land population distribution coefficient is modified in the middle green continent, and the grassland population distribution is increased in the upstream mountainous area and the downstream desert oasis area Coefficient. The spatial distribution of urban population density in river basin is simulated by using the exponential model. Based on the above methods, the population spatial distribution results of 25m grid in Heihe River Basin and the data of 1km grid on scale are finally obtained.
\nAt the township level, the accuracy of the results of population spatialization is verified, and compared with the population data of Heihe River Basin estimated by the existing databases (GPW 1995, UNEP / grid1995, landscan 2002 and cn2000pop). The results show that the methods and models used in this study can obtain more accurate spatial distribution data of population in the basin.
", "ds_time_res": "", "ds_acq_place": "Heihe River Basin", "ds_space_res": "", "ds_projection": "+proj=longlat +datum=WGS84 +no_defs ", "ds_process_way": "Principal component analysis and factor analysis
", "ds_ref_instruction": "In order to respect intellectual property rights, protect the rights and interests of data authors, expand the services of data centers, and evaluate the application potential of data, data users are requested to clearly indicate the data source and data authors in the research results (including published papers, works, data products and unpublished research reports, data products, etc.) produced by using data. For data reprinted (secondary or multiple releases), the author must also indicate the source of the original data." } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/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, "belong_to_nieer": false, "ds_topic_tags": [ "人口数据空间化", "距离衰减模型", "城市边缘距离", "人口", "格网化", "土地利用" ], "ds_subject_tags": [ "人文地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域" ], "ds_time_tags": [ 2000 ], "ds_contributors": [ { "true_name": "马明国", "email": "mmg@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王雪梅", "email": "", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "马明国", "email": "mmg@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "马明国", "email": "mmg@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "基础地理" }