本数据以2000年-2017年MODIS的植被指数MOD13A3和Albedo MCD43A3数据产品为数据源，数据分辩率为1KM，月合成，利用MRT工具，进行数据拼接、投影转换等影像处理，再利用中巴经济走廊区域边界，采用Python批量裁剪，采用荒漠化差值指数（DDI）评价中巴经济走廊荒漠化程度，以归一化植被指数（NDVI）与地表反照率（Albedo）为监测指标，通过构造Albedo-NDVI特征空间，并利用Albedo和NDVI之间负相关的关系，构建DDI公式，完成2000–2017年中巴经济走廊荒漠化分类专题数据集，直观反映中巴经济走廊荒漠化程度，为定量评价荒漠化严重程度提供参考。该数据可为中巴经济走廊区域科学研究提供基础数据支持。
", "ds_source": "涉及MOD13A3和MCD43A3数据包括：h23v04、h23v05、h23v06、h24v04、h24v05、h24v06，数据分辩率为1KM，月合成；中巴经济走廊区域边界。
", "ds_process_way": "基于年度NDVI和年度Albedo构建的荒漠化差值指数，需要以NDVI的年度最大值，Albedo 的年度最小值作为基础数据。
", "ds_quality": "采用高分辨率数据来评价荒漠化分级数据的质量。以2010年数据为例，选取8副landsat 7 影像数据在小范围上进行验证，计算8副影像的NDVI值，然后转换成植被盖度，根据荒漠化指标分级标准评价各个验证区土地的荒漠化程度。在每个影像上选取各级别荒漠化验证点30个，与数据集所得结果进行比较，并计算Kappa系数，其中总体评价精度达到80.83%，Kappa系数为73.89% ，
", "ds_acq_start_time": "2000-03-01 00:00:00", "ds_acq_end_time": "2017-12-31 00:00:00", "ds_acq_place": "中巴经济走廊区域", "ds_acq_lon_east": 80.26666666666667, "ds_acq_lat_south": 23.766666666666666, "ds_acq_lon_west": 60.31666666666667, "ds_acq_lat_north": 40.916666666666664, "ds_acq_alt_low": -36.0, "ds_acq_alt_high": 8378.0, "ds_share_type": "login-access", "ds_total_size": 148550552, "ds_files_count": 2, "ds_format": "GEOTIFF", "ds_space_res": "1000.0m", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "Geographic", "ds_thumbnail": "0464e947-96a0-452d-903b-a4040d6debba.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "为保障平台科技资源的权益、扩展平台中心的服务、提升科技资源的应用潜力，请资源使用者在使用资源所产生的研究成果中（包括公开发表的论文、论著、数据产品和未公开发表的研究报告、数据产品等成果），明确注明资源来源和资源作者。", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2021-12-28 09:24:29", "last_updated": "2023-09-04 10:12:30", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.nieer.2020.1360", "i18n": { "en": { "title": "Annual desertification distribution data set of China Pakistan Economic Corridor (2000-2017)", "ds_format": "GEOTIFF", "ds_source": "The data involved in mod13a3 and mcd43a3 include: h23v04, h23v05, h23v06, h24v04, h24v05, h24v06, with a resolution of 1km, monthly composition; the regional boundary of China Pakistan Economic Corridor.
", "ds_quality": "High resolution data are used to evaluate the quality of desertification classification data. Taking the 2010 data as an example, eight Landsat 7 images were selected to verify in a small scale, and the NDVI values of 8 images were calculated, and then converted into vegetation coverage. The desertification degree of each verification area was evaluated according to the desertification index classification standard. In each image, 30 desertification verification points were selected and compared with the results of the data set, and the kappa coefficient was calculated. The overall evaluation accuracy was 80.83%, and the kappa coefficient was 73.89%
", "ds_ref_way": "", "ds_abstract": "Based on MODIS vegetation index mod13a3 and albedo from 2000 to 2017 Mcd43a3 data product is used as data source, the resolution of data is 1km, monthly synthesis, MRT tools are used to perform data splicing, projection conversion and other image processing, and then the regional boundary of China Pakistan Economic Corridor is used to cut Python batch, and the desertification difference index (DDI) is used to evaluate the desertification degree of the China Pakistan Economic Corridor, and the normalized vegetation index (NDVI) and surface albedo (albedo) are used to evaluate the desertification degree of the China Pakistan Economic Corridor ）In order to monitor indicators, by constructing the albedo NDVI feature space and using the negative correlation between albedo and NDVI, the DDI formula was constructed, and the thematic data set of desertification classification of China Pakistan Economic Corridor from 2000 to 2017 was completed, which directly reflected the desertification degree of China Pakistan Economic Corridor and provided reference for quantitative evaluation of desertification severity. The data can provide basic data support for regional scientific research of China Pakistan Economic Corridor.
", "ds_time_res": "月", "ds_acq_place": "China-Pakistan Economic Corridor Region", "ds_space_res": "1000.0m", "ds_projection": "Geographic", "ds_process_way": "Based on the annual NDVI and annual albedo, the annual maximum value of NDVI and the annual minimum value of albedo should be taken as the basic data.
", "ds_ref_instruction": "In order to protect the rights and interests of the platform's scientific and technological resources, expand the service of the platform center, and enhance the application potential of the scientific and technological resources, resource users are requested to clearly indicate the resource sources and resource authors in the research results (including published papers, monographs, data products and unpublished research reports and data products) generated by the use of resources." } }, "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, "ds_topic_tags": [ "MOD13A3", "中巴经济走廊", "Albedo地表反照率", "DDI荒漠化差异指数", "NDVI", "荒漠化分布", "MCD43B3", "NDVI-Albedo特征空间" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中巴经济走廊" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2017 ], "ds_contributors": [ { "true_name": "康建芳", "email": "kangjf@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": "敏玉芳", "email": "myf@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": "冯克庭", "email": "fengkt@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "" }, { "true_name": "艾鸣浩", "email": "aimh@lzb.ac.cn", "work_for": "中科院西北研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "敏玉芳", "email": "myf@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": "敏玉芳", "email": "myf@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": "沙漠与荒漠化" }