Land cover classification data for wetland complexes at Dixie Meadows, Nevada from January 2022 to November 2023

These data were compiled to provide satellite remote sensing observations of landcover in the vicinity of wetlands fed by geothermal springs in Dixie Meadows, Nevada, USA. Objectives of the study were to map landcover of water, vegetation, and soil between January 26, 2022 and November 27, 2023 using available imagery from the Sentinel-2 mission, thereby extending previously published data from October 5, 2015 to January 21, 2022 (Bransky et al., 2023). The US Geological Survey's Southwest Biological Science Center (SBSC) and Grand Canyon Monitoring and Research Center (GCMRC) processed 36 Sentinel-2 satellite images representing bottom of atmosphere surface reflectance and classified them within Google Earth Engine (GEE) using threshold values of the Green Normalized Difference Vegetation Index (gNDVI) and its inverse relationship to the Normalized Difference Water Index (NDWI). The classified image data represent the area covered by five distinct landcover types: open water; mixed shallow surface water, saturated soil, and vegetation; dense green vegetation; moist soil with sparse or small vegetation; dry soil with sparse upland vegetation. These data can be used to evaluate the areal extent of each of the landcover types classified in this study as well as changes in the areal extent of these landcover types between January 26, 2022 and November 27, 2023. Additionally, these data may be used as baseline conditions to evaluate future changes in the areal extent of landcover owing to land use changes or climatic fluctuations.

本数据集旨在提供美国内华达州迪克西草甸（Dixie Meadows）地热泉补给湿地周边的土地覆被卫星遥感观测数据。本研究以哨兵二号（Sentinel-2）卫星公开影像为数据源，绘制2022年1月26日至2023年11月27日期间的水体、植被与土壤土地覆被图，以此延伸2015年10月5日至2022年1月21日的已发表数据集（Bransky等，2023）。美国地质调查局西南生物科学中心（Southwest Biological Science Center, SBSC）与大峡谷监测与研究中心（Grand Canyon Monitoring and Research Center, GCMRC）共处理了36幅表征大气底部地表反射率的哨兵二号卫星影像，并在谷歌地球引擎（Google Earth Engine, GEE）中，以绿色归一化植被指数（Green Normalized Difference Vegetation Index, gNDVI）及其与归一化水体指数（Normalized Difference Water Index, NDWI）的反比关系作为阈值完成影像分类。经分类的影像数据覆盖5类明确的土地覆被类型分布区域：开阔水体；浅表层水-饱和土壤-植被混合覆被；茂密绿色植被；植被稀疏低矮的湿润土壤；伴生稀疏旱地植被的干燥土壤。本数据集可用于评估本研究分类的各类土地覆被类型的分布面积，以及2022年1月26日至2023年11月27日期间各类土地覆被类型的面积变化情况。此外，该数据集可作为基准参照，用于评估因土地利用变化或气候波动引发的未来土地覆被面积变化。