A web-based application for the management and visualization of land-use scenario data

Land-use researchers need the ability to rapidly compare multiple land-use scenarios over a range of spatial and temporal scales, and to visualize spatial and nonspatial data; however, land-use datasets are often distributed in the form of large tabular files and spatial files. These formats are not ideal for the way land-use researchers interact with and share these datasets. The size of these land-use datasets can quickly balloon in size. For example, land-use simulations for the Pacific Northwest, at 1-kilometer resolution, across 20 Monte Carlo realizations, can produce over 17,000 tabular and spatial outputs. A more robust management strategy is to store scenario-based, land-use datasets within a generalized land-use database designed specifically for managing a range of spatial and nonspatial land-use datasets. This type of database facilitates access to, and comparisons among, a range of scenario datasets as well as the generation and storage of metadata.



Methods for sharing land-use datasets with the public, in a way that encourages interaction with and understanding of land-use scenario data, are also lacking. Engaging and intuitive visualization capabilities are needed to effectively introduce non-scientists to the concept of scenarios, and to successfully fulfill the USGS mandate of sharing datasets and science with the public.



This project aimed to facilitate management, sharing, and visualization of land change datasets with the creation of a database-driven web application. In collaboration with the University of California (UC) Berkeley Geospatial Innovation Facility (GIF) and ApexRMS, a web application was developed for visualizing and sharing multiple land-use scenario datasets. The application was built on top of a generalized land-use scenario database, providing a complete package for scenario management and visualization that can easily be applied to a range of scenario datasets. The generalized land-use database, which supports the preservation and sharing of simulation model inputs, outputs, and metadata, can provide a much needed data management solution for land-use researchers. The web viewer will allow researchers to quickly share land-use model results and associated datasets with colleagues and the public. Together these tools will serve as a complete package for managing and visualizing land-use datasets, and as a framework for managing a range of other scenario-based datasets such as carbon stock and carbon flow datasets.



Principal Investigator : Jason T Sherba, Benjamin M Sleeter

Cooperator/Partner : Colin Daniel, Nancy Thomas, Brian Galey, Eric Lehmer

Accomplishments

The accomplishments for this project are described below.

• A limited Python-based API was developed to query and summarize results stored within a .ssim database. This API is a component of the web application and can also be used independently to manage data in a .ssim database. Code and documentation are available on GitHub: https://github.com/usgs/ssim-api.
• A method for adding external datasets to a .ssim database was added to the ST-Sim software package. ST-Sim is freely available at http://www.apexrms.com/state-and-transition-simulation-models/ (content no longer available). This new tool allows users to add land-use scenario datasets from outside sources, so that they can be stored, managed, and served from a .ssim database.
• The UC Berkeley GIF led the development of a web application for sharing and serving land-use and carbon scenario data managed by a .ssim database. A prototype was developed using results from a land-use and carbon model for the Hawaiian Islands. The beta version of web viewer is available at http://beta.landcarbon.org/ (content no longer available) (fig. 3). The prototype also includes an admin console, for application deployment, that allows users to choose a .ssim database to connect to and specify scenarios for visualizing.

Note:  This description is from the Community for Data Integration 2016 Annual Report.