Land Use Land Cover Palos 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，融合了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。本数据集属于一项试点项目的组成部分，涵盖7个研究区域：绍姆堡2023、巴林顿2024、布鲁姆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，如水生植被湿地、林地/森林、开阔水域、道路/不透水地表，以及多种植被与城市地物类型。研究团队开展了光谱与空间分析，以精准划定湿地内高度介于0至0.5米之间的沉水或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。本数据集可为研究区域内的自然景观与人工改造景观提供全面的整体风貌呈现。