Using Sentinel-2 Imagery and Machine Learning Algorithms to Assess the Inundation Status of Nebraska Conservation Easements during 2018–2021

Conservation easements (CEs) play an important role in the provision of ecological services. This paper aims to use open-access Sentinel-2 satellites advance existing conservation management capacity a new level near-real-time monitoring and assessment for Nebraska. research uses machine learning Google Earth Engine classify inundation status using imagery during 2018–2021 all CE sites Nebraska, USA. The proposed approach helps monitor at landscape scale efficient low-cost manner. results confirmed effective performance these floodplain or wetland-related sites. under Emergency Watershed Protection-Floodplain Easement (EWPP-FPE) had highest inundated area rate 18.72%, indicating active hydrological areas. Wetlands Reserve Program (WRP) reached mean annual surface water cover 8.07%, core wetland areas were periodically regularly. Other types CEs serving upland purposes lower while uplands provided critical needs soil erosion control. is 0.96% Grassland (GRP). on component reduce improve downstream performance. findings support that with higher frequencies can be considered future practices. four typical wetland-based suggested improved by implementing restoration reduction watershed scale. robust evidence discover information achieve long-term goals easements.