Forest Health Protection Tree Species Metrics Basal Area (Image Service)

Basal Area (BA). 30 meter pixel resolution. Data represents forest conditions circa 2002. These data are a product of a multi-year effort by the FHTET (Forest Health Technology Enterprise Team) Remote Sensing Program to develop raster datasets of forest parameters for each of the tree species measured in the Forest Service’s Forest Inventory and Analysis (FIA) program. This dataset was created to support the 2013–2027 National Insect and Disease Risk Map (NIDRM) assessment. The statistical modeling approach used data-mining software and an archive of geospatial information to find the complex relationships between GIS layers and the presence/abundance of tree species as measured in over 300,000 FIA plot locations. Unique statistical models were developed from predictor layers consisting of climate, terrain, soils, and satellite imagery. Modeled basal area (BA) and stand density index (SDI) datasets for individual tree species were further post-processed to 1) match BA and SDI histograms of FIA data, 2) ensure that the sum of individual species BA and SDI on a pixel did not exceed separately modeled total for all species BA and SDI raster datasets, 3) derive additional tree parameters like quadratic mean diameter and trees per acre. With Landsat image collection dates ranging from 1985 to 2005, and a mean collection date for treed areas of 2002, and FIA plot data generally ranging from 1999 to 2005, the vintage of the base parameter datasets varies based on location, but can be roughly considered as 2002断面积（Basal Area, BA）数据集，像素分辨率为30米，反映约2002年的森林状况。该数据是美国林务局下属森林健康技术企业团队（Forest Health Technology Enterprise Team, FHTET）遥感项目多年研发的成果，旨在为美国林务局森林资源清查与分析（Forest Inventory and Analysis, FIA）项目中测量的各树种构建森林参数栅格数据集。本数据集专为支撑2013–2027年全国病虫害风险图（National Insect and Disease Risk Map, NIDRM）评估工作而创建。 其统计建模方法借助数据挖掘软件与地理空间信息档案，探寻地理信息系统（Geographic Information System, GIS）图层与超过30万个FIA样地中测得的树种存在/丰度之间的复杂关联。研究人员基于气候、地形、土壤与卫星影像等预测因子图层，为各树种构建了专属统计模型。针对单一树种生成的断面积（BA）与林分密度指数（Stand Density Index, SDI）栅格数据集还经过了进一步后处理：1）匹配FIA数据的BA与SDI直方图分布；2）确保单个像素内各树种BA与SDI的总和不超过所有树种合并后单独建模的总BA与SDI栅格数据集数值；3）推导二次平均直径、每英亩株数等额外林木参数。 由于Landsat影像的采集时间跨度为1985年至2005年，林区影像的平均采集时间为2002年，且FIA样地数据的采集时间普遍介于1999年至2005年之间，因此基础参数数据集的时效因区域而异，但整体可近似视为2002年基准。