Long-term composited Normalized Difference Vegetation Index (NDVI) for the greater Phoenix, Arizona, USA, metropolitan area and the surrounding Sonoran desert derived from annual and seasonal Landsat imagery, 1998 to 2023

### overview This data package consists of multiple decades of normalized difference vegetation index (NDVI) raster data across the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) study area within metropolitan Phoenix, Arizona (USA), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). To serve as a proxy measurement of vegetation greenness and productivity across years and seasons, NDVI was derived from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of the spectral index, can be found in the data package metadata (see 'Methods and Protocols') and accompanying Javascript code. ### citations - Gorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202:18–27. https://doi.org/10.1016/j.rse.2017.06.031### 概况 本数据包包含美国亚利桑那州凤凰城都会区范围内的亚利桑那州中部-凤凰城长期生态研究（CAP LTER）研究区数十年间的归一化差分植被指数（Normalized Difference Vegetation Index, NDVI）栅格数据，该数据按年份与四个气象季节（冬季、春季、夏季、秋季）进行时间聚合。为作为多年度、多季节植被绿度与生产力的替代测量指标，该NDVI由30米分辨率的Landsat 5至9级地表反射率影像的年度与季间合成产物反演得到。所有影像检索与数据处理工作均通过谷歌地球引擎（Google Earth Engine，Gorelick等，2017）与R语言程序完成。数据处理方法的完整说明（包括影像按年份与季节的聚合流程以及该光谱指数的计算过程）可在数据包元数据（参见「方法与流程」部分）及配套的JavaScript代码中查阅。 ### 引用文献 - Gorelick N、Hancher M、Dixon M 等（2017）《谷歌地球引擎：面向所有人的行星级地理空间分析》，《环境遥感》202卷：18–27。https://doi.org/10.1016/j.rse.2017.06.031