Land Use Land Cover Barrington 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构建，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（Light Detection and Ranging, LiDAR）数据。本数据集隶属于一项试点项目，涵盖7个研究区域：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。其分类体系包含丰富的地物类别，涵盖水生植被湿地（Aquatic Vegetation Wetlands）、林地/森林（Woodland or Forest）、开阔水域（Open Water）、道路/不透水地表（Roads or Impervious Surfaces），以及各类植被与城市地物。研究团队通过光谱与空间分析，精准勾画了湿地内高度介于0至0.5米的沉水或浮水水生植被分布区域。高光谱与激光雷达数据的融合，实现了植被类型、群落结构及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工改造景观的整体格局。