Publications

The urgency to address ecosystem loss is paramount, as both land use change and climate change will continue to rapidly alter and degrade natural ecosystems and reduce the many services they provide. To support conservation actions that mitigate impacts from these dual threats, we have developed potential World Terrestrial Ecosystem (WTE) distributions for 2050 following IPCC best...

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat...

Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline...

With the ever-increasing number of civil and commercial remote-sensing satellite launches in recent years, the Earth Observation community needs to better understand the quality of new data products as they become available for scientific research purposes.

The Joint Agency Commercial Imagery Evaluation (JACIE) was formed to leverage resources from several Federal agencies for the characterization of remote sensing data and to share those results across the remote sensing community (U.S. Geological Survey, 2024). Remote sensing data and the quality of that data are vital to (1) understanding the physical world and (2) supporting the science...

This paper reviews trends in GeoAI research and discusses cutting-edge ad- vances in GeoAI and its roles in accelerating environmental and social sciences. It ad- dresses ongoing attempts to improve the predictability of GeoAI models and recent re- search aimed at increasing model explainability and reproducibility to ensure trustworthy geospatial findings. The paper also provides...

Linguistic representation of geographic knowledge is semantically complex and particularly challenging when employing geographic information technology to automate interpreted analysis dealing with unstructured knowledge. This study describes an approach called GrammarToGraph (G2G) that applies dependency grammar rules through natural language processing to transform annotation data into

The goal of the U.S. Geological Survey’s (USGS) 3D Elevation Program (3DEP) is to facilitate the acquisition of nationwide lidar data. Although data meet USGS lidar specifications, some point cloud tiles include noisy and incorrectly classified points. The enhanced accuracy of classified point clouds can improve support for many downstream applications such as hydrologic analysis, urban...

Mountain regions harbor unique and rich biodiversity, forming an important part of our global life support system. This rich biodiversity underpins the ecological intactness and functioning of mountain ecosystems, which are imperative for the provision of key ecosystem services. A considerable amount of data are required to assess ecological intactness and ecosystem functioning and...

Studies have shown that digital surface models and point clouds generated by the United States Department of Agriculture’s National Agriculture Imagery Program (NAIP) can measure basic forest parameters such as canopy height. However, all measured forest parameters from these studies are evaluated using the differences between NAIP digital surface models (DSMs) and available lidar...

The United States Geological Survey (USGS) coordinates the collection of hydrographic features derived from remotely sensed interferometric synthetic aperture radar (IfSAR) elevation and intensity data in Alaska. Hydrographic features are cartographic representations of surface water features such as stream, rivers, lakes, ponds, canals, etc. Collection and validation procedures involve...

Reducing detail on polyline features aids in legibility, allowing features to appear more distinct and preventing coalescence with other features. Current metrics for evaluating generalization outcomes emphasize geometric change rather than legibility. The present study reports on development and testing of a vector-based metric of the discernibility of a single polyline feature or group...