植被叶面积指数（leaf area index,LAI）也称叶面积系数，可表征植被对光线的吸收和拦截以及植被生长状况，通常被定义为单位面积内所含的植被叶片表面积之和。因该指数可反映研究区内植被叶片的疏密程度及植被的生长状况，所以精确获取LAI显得极为重要。在LAI的获取过程中，遥感信息技术因其可实时动态有效监测植被特征且作业周期短等显著优势而被广泛应用，该技术为植被生化参数的有效研究奠定了基础。", "ds_source": "
数据来源于NASA官网(https://ladsweb.modaps.eosdis.nasa.gov)\n
涉及MCD15A2H数据包括：h25v04，h25v05，h26v05，数据分辩率为500m，8天合成，数据格式为hdf。", "ds_process_way": "
原始产品，未经处理。", "ds_quality": "
数据质量良好。\n
LAI数据有效范围0-100，放缩因子为0.1，填充值范围249-255，其中：249表示 “未分类”或无法确定的土地覆盖类型；250表示城镇/建成区的土地覆盖类型；251表示“永久”湿地/泛滥沼泽的土地类型；252表示常年积雪或冰覆盖的土地；253表示贫瘠、稀疏的植被(如岩石、苔原、沙漠等)；254表示永久性盐碱地或内陆水体覆盖区；255表示用于计算MCD15A2数据的源数据MOD09等地表反射红外近红外波段数据出现填充值时，对应MCD15A2像元填充为255，有的填充为254。", "ds_acq_start_time": "2018-01-01 00:00:00", "ds_acq_end_time": "2022-12-31 00:00:00", "ds_acq_place": "甘肃省", "ds_acq_lon_east": 108.7075, "ds_acq_lat_south": 32.596111111111114, "ds_acq_lon_west": 92.33777777777777, "ds_acq_lat_north": 42.79333333333333, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 5202898664, "ds_files_count": 700, "ds_format": "hdf", "ds_space_res": "500m", "ds_time_res": "8日", "ds_coordinate": "无", "ds_projection": "/", "ds_thumbnail": "ee26c72d-19b5-47e4-9bab-7f9ec6be75a7.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "526ff655-4cd4-4650-bb86-6fd3481dfb65", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2023-12-27 09:59:54", "last_updated": "2025-05-29 16:22:21", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.GSEER.DB4147.2023", "i18n": { "en": { "title": "Gansu Province MCD15A2 Leaf Area Index LAI (2018-2022)", "ds_format": "hdf", "ds_source": "
The data is sourced from NASA's official website（ https://ladsweb.modaps.eosdis.nasa.gov ）\n
The data related to MCD15A2H includes: h25v04, h25v05, h26v05, with a data resolution of 500m, synthesized in 8 days, and formatted in HDF.", "ds_quality": "
The data quality is good.\n
The valid range of LAI data is 0-100, with a scaling factor of 0.1 and a filling value range of 249-255, where 249 represents unclassified or undetermined land cover types; 250 represents the land cover type of urban/built-up areas; 251 represents the land type of \"permanent\" wetlands/flood marshes; 252 represents land covered with snow or ice all year round; 253 represents barren and sparse vegetation (such as rocks, tundra, desert, etc.); 254 represents permanent saline alkali land or inland water cover area; 255 indicates that when the source data MOD09 and other surface reflection infrared near-infrared band data used to calculate MCD15A2 data have fill values, the corresponding MCD15A2 pixel fill is 255, and some fill is 254.", "ds_ref_way": "", "ds_abstract": "
Leaf area index (LAI), also known as leaf area coefficient, can characterize the absorption and interception of light by vegetation, as well as the growth status of vegetation. It is usually defined as the sum of the surface areas of vegetation leaves per unit area. Accurately obtaining LAI is extremely important because this index can reflect the density of vegetation leaves and the growth status of vegetation in the study area. In the process of obtaining LAI, remote sensing information technology is widely used due to its significant advantages such as real-time dynamic and effective monitoring of vegetation characteristics and short operation cycle. This technology lays the foundation for effective research on vegetation biochemical parameters.
", "ds_time_res": "8日", "ds_acq_place": "Gansu Province", "ds_space_res": "500m", "ds_projection": "/", "ds_process_way": "Original product, untreated.", "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": [ "甘肃省", "地表温度" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "甘肃省" ], "ds_time_tags": [ 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "张耀南", "email": "yaonan@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": "李红星", "email": "lihongxing@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": "遥感及产品" }