A substantial portion of the projected future stress on U.S. water resources arises from external factors. Specifically, the rising incomes and populations overseas drive an increased demand for food. This demand, in turn, affects the virtual water trade embedded in exported crops. Here, you can explore the estimated contribution of global drivers in future stress on water resources as estimated by SIMPLE-G model.
Open NotebookThis exercise shows how to apply Machine Learning Models to explore the relationship between urban tree canopy, land cover, and land surface temperature. It lays out an initial modeling approach that combines exploratory data analysis with KNN regression and decision tree models to better understand the patterns of the data and for prediction purposes in the R environment.
Open NotebookThis exercise shows how to use Census API to get data from the Census Bureau website and explore demographic changes over time near transit stops to identify areas which might be experiencing transit-induced gentrification.
Open NotebookThe main focus of this work is to gain practical experience in applying deep learning techniques to real-world spatial problems, at the cutting edge of GeoAI.
Open NotebookOver the last decade, the Great Salt Lake has experienced a significant loss of water due to a combination of climate and anthropogenic changes. This workflow evaluates the effectiveness of the National Water Model’s retrospective simulations in capturing changes in inflows to this terminal lake.
Open NotebookThis work focuses on big data processing, network modeling, and geovisualization with R. Using circos maps and community detection algorithms, this workflow analyzes changes in global trade dynamics due to natural and social disturbances, contributing to sustainability fields.
Open NotebookUsing Google Earth Engine, this group mapped and analyzed the changing extent of the wildland-urban interface from 2011-present across the continental US and characterized risk and socioeconomic factors using NASA SEDAC’s Social Vulnerability Index and LANDFIRE’s Wildfire Risk to Communities data to evaluate areas at greatest risk to wildfire.
Open NotebookWith a grid-resolving economic model (SIMPLE-G), this group simulated how heat stress affects labor productivity in the agricultural sector and generates cascading impacts on farming for the continental US at fine spatial scales.
Open NotebookExplore the application of the Segmentation Models Library for streamline delineation in this hands-on Jupyter notebook. Fine-tune pre-trained models like UNet, LinkNet, PSPNet, and FPN to achieve accurate streamlines segmentation.
Open NotebookThis notebook demonstrates uses and functionality of the API interface provided by IPUMS for NHGIS to access and request data in a reproducible and documentable Python workflow.
Open NotebookA demonstration of how to access, subset, and visualize Analysis of Record for Calibration (AORC) forcing data that is stored in HydroShare’s THREDDS catalog
Open NotebookThis study proposes a framework employing spatial metrics (Bivariate Moran’s I and LISA) to discover where and whether socially vulnerable populations are more exposed to flood inundation risks induced by dam failures. This notebook, in particular, demonstrates the socioeconomic characteristics of at-risk populations, focusing on 345 dams in the conterminous United States.
Open NotebookWRFHydro is a leading-edge, open-source community hydrometeorological and hydrologic modelling system developed by NCAR. The I-GUIDE platform integrates various state-of-the-art cyberinfrastructure (CI) capabilities to support Community Hydrological Modelling. It is the code base for the NOAA National Water Model (NWM).
Open Notebook