Land Use Land Cover Bloom Township 2024

This land use and land cover (LULC) classification dataset was generated using advanced remote sensing techniques, combining high-resolution airborne hyperspectral imagery from 2023 and LiDAR data from 2022. This data set is part of a pilot program, one of seven areas: Schaumburg 2023, Barrington 2024, Bloom 2024, Lake 2024, Palos 2024, Stickney 2024, & Thornton 2024. The classification scheme includes a wide range of classes, such as Aquatic Vegetation Wetlands, Woodland or Forest, Open Water, Roads or Impervious Surfaces, and various types of vegetation and urban features. Spectral and spatial analyses were conducted to delineate areas of submersed or floating aquatic vegetation between 0-0.5m in height within wetland locations. The integration of hyperspectral and LiDAR data allowed for precise distinction between vegetation types, structures, and other land cover classes. This dataset offers a comprehensive view of both natural and human-modified landscapes in the study area.本土地利用与土地覆盖（Land Use and Land Cover, LULC）分类数据集依托先进遥感技术生成，融合了2023年采集的高分辨率机载高光谱影像与2022年的激光雷达（LiDAR）数据。本数据集属于一项试点项目的组成部分，覆盖七个研究区域，分别为绍姆堡2023、巴林顿2024、布卢姆2024、莱克2024、帕洛斯2024、斯蒂克尼2024以及桑顿2024。其分类体系包含多类地物，涵盖水生植被湿地、林地或森林、开阔水域、道路或不透水面，以及多种植被与城市地物类别。研究团队通过光谱与空间分析，对湿地内高度介于0至0.5米的沉水或浮水水生植被分布区域进行了精准划定。高光谱与激光雷达数据的融合，实现了植被类型、群落结构以及其他土地覆盖类别的精细区分。本数据集可全面呈现研究区域内自然景观与人工改造景观的整体格局。