本数据集为祁连山国家公园2000、2010和2018年生态承载力空间分布图。\n
综合考虑祁连山国家公园社会经济状况和生态环境特性，从生态系统支撑条件 (生态支撑力) 和压力因素 (社会经济压力) 两个维度构建生态承载力评价指标体系。共选取年平均气温、年降水量、高程、坡度、植被覆盖度、水域湿地面积比、景观破破碎度、植被净初级生产力、生物丰度指数、水源涵养量、水土保持量、单位面积耗水总量、草地载畜压力指数、耕地与建设用地面积比、单位面积社会产值、人口密度16个评价指标。基于模糊层析分析法、熵值法和模糊综合评价模型进行生态承载力评价，得到2000、2010和2018年的祁连山国家公园生态承载力分布图。", "ds_source": "
使用的数据主要包括气象数据 (温度、降水和潜在蒸散量)、土地利用数据、数字高程、归一化植被指数、叶面积指数、土壤数据、植被类型数据、统计年鉴数据 (用水量数据、GDP、人口、牲畜存栏出栏数) 等。", "ds_process_way": "
首先利用基础数据，基于InVEST模型、CASA模型、RUSLE模型、像元二分法、普通克里金插值等计算2000、2010和2018年16个评价指标。其次，将指标进行标准化处理之后，利用模糊层次分析法和熵值法分别计算指标的主观权重和客观权重，并采用模糊综合评价模型确定指标的综合权重。最后，基于指标及其综合权重计算生态承载力。", "ds_quality": "
加工处理过程中，对计算的指标分别进行验证，数据质量较好。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "祁连山国家公园", "ds_acq_lon_east": 103.03777777777778, "ds_acq_lat_south": 36.755, "ds_acq_lon_west": 95.11666666666666, "ds_acq_lat_north": 39.753055555555555, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 793288, "ds_files_count": 2, "ds_format": "tif", "ds_space_res": "30m", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "3d6bec25-b1d8-4ac8-9b03-b9c6f630d0f2.png", "ds_thumb_from": 0, "ds_ref_way": "程弘毅，祁连山国家公园生态承载力空间分布图（2000-2018年），国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2023，doi：10.12072/ncdc.nieer.db2745.2023", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52109486-75ef-4764-a933-6380c6f42432", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.nieer.db2745.2023", "subject_codes": [ "170.45" ], "quality_level": 0, "publish_time": "2023-02-28 16:01:20", "last_updated": "2023-03-01 10:51:09", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.nieer.db2745.2023", "i18n": { "en": { "title": "Spatial distribution of ecological carrying capacity of Qilian Mountain National Park (2000-2018)", "ds_format": "", "ds_source": "
The data used mainly include meteorological data (temperature, precipitation and potential evapotranspiration), land use data, digital elevation, normalized vegetation index, leaf area index, soil data, vegetation type data, statistical yearbook data (water consumption data, GDP, population, livestock inventory), etc.", "ds_quality": "
In the process of processing, the calculated indexes were verified and the data quality was good.", "ds_ref_way": "", "ds_abstract": "
This data set is the spatial distribution of ecological carrying capacity of Qilian Mountain National Park in 2000, 2010 and 2018.\n
Considering the socio-economic status and ecological environment characteristics of the Qilian Mountain National Park, the evaluation index system of ecological carrying capacity is constructed from two dimensions of ecosystem support conditions (ecological support) and pressure factors (socio-economic pressure). A total of 16 evaluation indicators were selected, including annual average temperature, annual precipitation, elevation, slope, vegetation coverage, ratio of water area to wetland area, landscape fragmentation, net primary productivity of vegetation, biological abundance index, water conservation, water and soil conservation, total water consumption per unit area, pressure index of grassland carrying livestock, area ratio of cultivated land to construction land, social output value per unit area, and population density. The ecological carrying capacity of Qilian Mountain National Park in 2000, 2010 and 2018 was evaluated based on the fuzzy tomographic analysis, entropy method and fuzzy comprehensive evaluation model.
", "ds_time_res": "", "ds_acq_place": "Qilian Mountain National Park", "ds_space_res": "30m", "ds_projection": "", "ds_process_way": "First, 16 evaluation indicators in 2000, 2010 and 2018 are calculated based on the basic data, such as InVEST model, CASA model, RUSLE model, pixel dichotomy, ordinary Kriging interpolation, etc. Secondly, after the indicators are standardized, the subjective weight and objective weight of the indicators are calculated by using the fuzzy analytic hierarchy process and entropy method, and the comprehensive weight of the indicators is determined by using the fuzzy comprehensive evaluation model. Finally, the ecological carrying capacity is calculated based on the index and its comprehensive weight.", "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, "ds_topic_tags": [ "祁连山国家公园", "生态承载力", "空间异质性" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "祁连山国家公园" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 ], "ds_contributors": [ { "true_name": "程弘毅", "email": "chenghy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "王义鹏", "email": "958754517@qq.com", "work_for": "兰州大学", "country": "中国" } ], "ds_managers": [ { "true_name": "程弘毅", "email": "chenghy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" } ], "category": "生态" }