Contemporary Interannual Pond Dynamics in New York State: A 10-meter Spatial Resolution Study Spanning 2018-2023

The state of New York contains a mosaic of ponds (i.e., small waterbodies <5 ha) dispersed across its low coastal plains, river valleys, rolling plateaus, glacier lakes, and forested mountains. These aquatic ecosystems function as pivotal sites for regional biogeochemical cycling, notably methane emissions, and are imperative for the state's socioeconomic development by supporting activities such as agriculture and livestock management. While high-resolution compiled hydrological datasets represented by National Hydrography Dataset Plus High Resolution (NHDPlus HR) have greatly advanced our knowledge of pond distribution in New York, monitoring and understanding their spatiotemporal dynamics remain a major challenge due to the lack of fine-spatial scale time-series products. Here, we utilized freely accessible Sentinel-1 and Sentinel-2 imagery to map annual changes in pond areal extent in New York from 2018 to 2023. To accurately capture these small waterbodies over large areas, we developed a fully automated object-based pond mapping method, where the segmentation scale was adaptively aligned with the size and distribution of ponds and representative training samples were automatically selected from land cover products using rule-based knowledge that enable classifiers to be consistent and locally reliable. We produced interannual pond maps in New York at a spatial resolution of 10 meters, detailing the annual variability of a total of over 110,000 waterbodies larger than 0.1 ha, predominantly ponds smaller than 5 ha in size (>95%). The dynamic pond maps generated in this study can facilitate the analysis of temporal changes in size-abundance relationships and the contribution of ponds to total surface water area variability, offering insights into the evolving imprints of anthropogenic activities and regional climate change.