Land Use Land Cover Thornton 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）分类数据集采用先进遥感技术生成，整合了2023年获取的高分辨率机载高光谱影像与2022年的激光雷达（LiDAR）数据。本数据集属于某试点项目的一部分，该项目覆盖七个研究区域，分别为：绍姆堡（Schaumburg）2023、巴林顿（Barrington）2024、布鲁姆（Bloom）2024、莱克（Lake）2024、帕洛斯（Palos）2024、斯蒂克尼（Stickney）2024以及桑顿（Thornton）2024。本次分类体系涵盖多类地物，包括水生植被湿地、林地/森林、开阔水体、道路或不透水地表，以及多种植被与城市地物。研究人员通过光谱与空间分析，精准划定了湿地范围内高度介于0至0.5米的沉水与浮水水生植被分布区域。高光谱影像与激光雷达数据的融合，实现了植被类型、群落结构与其他土地覆盖类别的精准区分。本数据集全面呈现了研究区域内自然景观与人为改造景观的整体状况。