Habitat classification (mangrove, marsh, water) based on drone imagery taken in spring 2023 in Port Fourchon, LA

This dataset contains habitat classifications based on drone based imagery collected at the location of sites sampled during the Fall 2022 drop sampling season. The imagery includes geospatial coverage of estuarine and adjacent terrestrial habitats, providing detailed landscape features such as vegetation type, water bodies, and land use around each sampling site. The spatial resolution of the satellite imagery allows for precise analysis of habitat variables at multiple scales. The resolution of this data is less than 1 meter.

The satellite imagery used to classify the habitats in this dataset was taken during the spring following our sampling season, but is still within six months of our sampling period. The imagery was analyzed to extract environmental variables, such as land-water ratios, vegetation coverage, and proximity to habitat edges. These variables are crucial for defining habitat characteristics and exploring their relationship to species abundance.

The primary purpose of this dataset is to investigate how habitat scale influences models linking species abundance to landscape metrics. This information is particularly useful for researchers studying estuarine ecosystems, landscape ecology, and habitat management. Data collection and interpretation were conducted by Herbert Leavitt, Dr. James Nelson, and Alex Thomas, with affiliations at the time of sampling being with the University of Louisiana at Lafayette.

本数据集基于2022年秋季样方采样季期间采集的各采样点位置处的无人机（drone）影像，生成了生境分类结果。该影像覆盖了河口及邻近陆地生境的地理空间范围，可提供各采样点周边的植被类型、水体、土地利用等详细景观特征。本卫星影像（satellite imagery）的空间分辨率可支持多尺度下生境变量的精准分析，其数据分辨率低于1米。

本数据集用于生境分类的卫星影像采集于采样季结束后的春季，且与采样时段间隔不超过六个月。研究人员通过对该影像进行分析，提取了多项环境变量，包括水陆比、植被覆盖率以及距生境边缘的距离等。这些变量对于明确生境特征、探究其与物种多度的关联至关重要。

本数据集的核心研究目标为探究生境尺度如何影响物种多度与景观指数间的关联模型。该数据集对于河口生态系统、景观生态学及生境管理领域的研究人员具有重要应用价值。本数据集的数据采集与解读工作由Herbert Leavitt、James Nelson博士及Alex Thomas完成，采样期间其所属机构为路易斯安那大学拉斐特分校（University of Louisiana at Lafayette）。