基于Landsat 5TM/7ETM+/8OLI 地表反射率集合中的遥感影像，分别使用LEDAPS和LaSRC算法，进行大气辐射校正，并通过CFMASK算法去除的云、雪等影响，然后通过红色波段和近红外波段计算各幅图像的NDVI值，最后合成每年5月到9月间祁连山地区每个像元最大NDVI值。本数据集数据，空间分辩率为30 m，每一年合成1幅影像。Landsat 5 NDVI 时间序列为1986—2011年，Landsat 7 NDVI 时间序列为1999—2019年，Landsat 8 NDVI 时间序列为2013—2019年。本数据集为L1级别数据，可用于大范围的植被指数时间序列对比分析。
", "ds_source": "源数据为Landsat 5 TM影像、Landsat 7 ETM+影像和Landsat 8 OLI影像，空间分辩率为30 m。
", "ds_process_way": "（1）基于Landsat 5/7/8 地表反射率集合中的遥感影像，分别使用LEDAPS和LaSRC算法，进行大气辐射校正；\n（2）通过CFMASK算法去除的云、雪等影响，然后通过红色波段和近红外波段计算各幅图像的NDVI值；\n（3）最后合成每年4月到10月间祁连山地区每个像元最大NDVI值，数据有效范围-1—1。
", "ds_quality": "受到Landsat源影像质量的影响，本数据集图像存在部分缺失。\nLandsat LT05数据：在1986—1989年期间存在条带缺失，1990—2000年期间数据正常，2001—2002年期间存在条带缺失，2003—2011年数据基本正常，2011年11月之后Landsat 5 TM传感器坏了之后，再无相关数据。\nLandsat LT07数据：1999—2002年数据正常，2003年5月起 Landsat 7 ETM +传感器扫描线校正器（SLC）发生故障，导致数据出现条带，需进行插补。 Landsat 7卫星将于2020年退役。\nLandsat LT08数据：2013年至今数据正常。\n本数据集为L1级别数据，如需更精确的数据结果，需要结合DEM和实测点上高程数据进行进一步校正。
", "ds_acq_start_time": "1986-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "祁连山地区", "ds_acq_lon_east": 103.9, "ds_acq_lat_south": 35.830000000000005, "ds_acq_lon_west": 93.5, "ds_acq_lat_north": 39.980000000000004, "ds_acq_alt_low": 1040.0, "ds_acq_alt_high": 5993.0, "ds_share_type": "login-access", "ds_total_size": 70387882505, "ds_files_count": 272, "ds_format": "栅格/GeoTIFF", "ds_space_res": "30 m", "ds_time_res": "1年", "ds_coordinate": "WGS84", "ds_projection": "+proj=longlat +datum=WGS84 +no_defs", "ds_thumbnail": "a9f71fb8-1b0a-4607-9526-88930d04d134.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "本数据由“中国科学院西北生态环境资源研究院甘肃省祁连山生态环境研究中心”制作，用户在使用数据时请在正文中明确声明数据的来源，并在参考文献部分引用本元数据提供的引用方式。", "ds_from_station": null, "organization_id": "8fa8eec3-a891-44cd-b60e-f6af19a16bba", "ds_serv_man": "张成琦", "ds_serv_phone": "0931-4967575", "ds_serv_mail": "chengqizhang@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2020-12-07 17:03:59", "last_updated": "2025-06-30 16:26:11", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.qlsst.2020.19", "i18n": { "en": { "title": "Annual maximum NDVI dataset with 30m resolution synthesized from Landsat 5TM/7ETM+/8OLI images in the Qilian Mountains region (1986-2019)", "ds_format": "Raster/GeoTIFF", "ds_source": "The source data consists of Landsat 5 TM images, Landsat 7 ETM+images, and Landsat 8 OLI images, with a spatial resolution of 30 m
", "ds_quality": "Due to the impact of Landsat source image quality, there are some missing images in this dataset.\nLandsat LT05 data: There were missing bands between 1986 and 1989, normal data between 1990 and 2000, missing bands between 2001 and 2002, basically normal data between 2003 and 2011, and no relevant data after the Landsat 5 TM sensor broke down in November 2011.\nLandsat LT07 data: The data was normal from 1999 to 2002. However, since May 2003, the Landsat 7 ETM+sensor scan line corrector (SLC) has malfunctioned, resulting in data bands that require interpolation. The Landsat 7 satellite will be retired in 2020.\nLandsat LT08 data: Normal data since 2013.\nThis dataset is L1 level data. To obtain more accurate data results, it is necessary to combine DEM and elevation data from measured points for further calibration.
", "ds_ref_way": "", "ds_abstract": "Based on the Landsat 5TM/7ETM+/8OLI surface reflectance collection of remote sensing images, LEDAPS and LaSRC algorithms were used for atmospheric radiation correction, and the effects of clouds, snow, etc. were removed by CFMASK algorithm. Then, the NDVI values of each image were calculated using the red and near-infrared bands, and finally the maximum NDVI value of each pixel in the Qilian Mountains area was synthesized from May to September each year. This dataset has a spatial resolution of 30 meters and synthesizes one image per year. The Landsat 5 NDVI time series is from 1986 to 2011, the Landsat 7 NDVI time series is from 1999 to 2019, and the Landsat 8 NDVI time series is from 2013 to 2019. This dataset is L1 level data and can be used for large-scale vegetation index time series comparative analysis.
", "ds_time_res": "1年", "ds_acq_place": "Qilian Mountains region", "ds_space_res": "30 m", "ds_projection": "+proj=longlat +datum=WGS84 +no_defs", "ds_process_way": "(1) Based on remote sensing images from Landsat 5/7/8 surface reflectance sets, LEDAPS and LaSRC algorithms were used for atmospheric radiation correction;\n(2) Remove the influence of clouds, snow, etc. through the CFMASK algorithm, and then calculate the NDVI values of each image through the red and near-infrared bands;\n(3) Finally, the maximum NDVI value of each pixel in the Qilian Mountains region from April to October each year was synthesized, with a valid range of -1-1.
", "ds_ref_instruction": "\r\nThis data is produced by \"Gansu Qilian Mountain Ecological Environment Research Center of Northwest Institute of Ecological Environment and Resources, Chinese Academy of Sciences\". When using the data, users should clearly state the source of the data in the text, and quote the reference method provided by this metadata in the reference section." } }, "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": [ "MOD13A2", "MODIS", "祁连山", "NDVI", "生态遥感" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "祁连山地区" ], "ds_time_tags": [ 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 ], "ds_contributors": [ { "true_name": "张举涛", "email": "jutzhang@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": "张成琦", "email": "chengqizhang@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": "冯起", "email": "qifeng@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": "朱猛", "email": "zhumeng@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_meta_authors": [ { "true_name": "张举涛", "email": "jutzhang@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": "张成琦", "email": "chengqizhang@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": "遥感及产品" }