High resolution habitat map of West Matagorda Bay, Texas, derived from WorldView-2 satellite imagery and lidar data, 2012-2019

This study mapped land cover (water, bare ground, forest, grass, marsh, algal flat, building, bridge culvert, and agriculture) around Matagorda Bay, Texas. The study area was defined by a 2-km buffer around the West Matagorda Bay shoreline and extended from the western portion of the Colorado River Delta through the eastern portion of Matagorda Island, Texas. This study incorporated WorldView-2 (WV-2; acquired on 2012-11-17, 2013-05-05, and 2013-12-16) and lidar (acquired 2018-01-04 - 2018-02-23 and 2019-01-24 – 2019-01-29) to obtain a 2-m resolution habitat map for the entire study area. A novel stacked classification approach was developed to take advantage of high-resolution satellite imagery and airborne lidar point clouds. Ultimately, a rule-based classifier was stacked on a group of machine learning classifiers for multispectral images and a filter classifier for lidar point clouds. The data were created for the Texas Office of the Comptroller project titled “Matagorda Bay Ecosystem Assessment.” Maps of vegetation, sand, and water coverage for discrete dates from 1850 to 2020 are available in related dataset HI.x833.000:0020 (https://doi.org/10.7266/zs2f74bj).本研究针对美国德克萨斯州马塔哥达湾（Matagorda Bay）周边开展土地覆盖制图，涵盖水体、裸地、森林、草地、沼泽、藻滩、建筑、桥涵及农用地共9类地物。研究区范围定义为西马塔哥达湾海岸线周边2公里缓冲带，覆盖从科罗拉多河三角洲西部至德克萨斯州马塔哥达岛东部的区域。本研究采用WorldView-2（WV-2；成像时间为2012-11-17、2013-05-05及2013-12-16）遥感影像与激光雷达（lidar）数据，其中激光雷达数据的获取时段为2018-01-04至2018-02-23以及2019-01-24至2019-01-29，以此生成覆盖全研究区的2米分辨率生境地图。本研究提出一种全新的堆叠分类方法，以充分利用高分辨率卫星影像与机载激光雷达点云的优势。最终，我们将基于规则的分类器堆叠至多光谱影像所用的机器学习分类器组，以及激光雷达点云所用的滤波分类器之上。本数据集为德克萨斯州主计长办公室（Texas Office of the Comptroller）题为“马塔哥达湾生态系统评估（Matagorda Bay Ecosystem Assessment）”的项目所创建。相关数据集HI.x833.000:0020（https://doi.org/10.7266/zs2f74bj）中包含了1850年至2020年各离散时间节点的植被、沙地与水体覆盖分布图。