What We Do

IGISc uses GIS, drone mapping, and remote sensing to monitor meadow restoration and greenhouse gas benefits, supporting long-term environmental conservation and restoration planning.

The IGISc is working in collaboration with Dr. Lara Cushing as a part of her JPB Environmental Health Fellows Program on a project to assign estimates of exposure to greenspace to pregnant women study participants part of a larger research question examining disparities in infant health that disproportionately affect racial/ethnic minorities. Estimates of exposure have been developed from existing secondary spatial datasets including the NLCD land cover classifications as well as MODIS and Sentinel-2 imagery (to derive NDVI) and based on the address of study participants and the dates during which they were pregnant. Summary exposure metrics have been created using several different buffer distances from each participant’s home. Additional geospatial exposure metrics include average nitrogen dioxide concentrations (NO2, a marker of traffic-related air pollution) as well as a static noise metric. The project involves a subset of study participants delivering in San Francisco. 

Image above: Schematic of  workflow to develop 'green space' metric. *Address points are fictitious. 

Credit: Ana Pelegrini

The IGISc is working with Dr. Emma Sanchez (SF State) on a project to map the fast food environment of public schools in California. Using network analysis, service areas were created for each school and fast food locations were tallied. This work will support research examining the link between the rate of change in the fast food environment of a school and socioeconomic characteristics of the surrounding neighborhoods as part of a larger study on population-level childhood obesity disparities over time.

Current Project Lead: Chloe Martin

Current Project Staff:

Previous Project Leads: Anna Studwell, Aiko Weverka and Seth Hiatt

Previous Project Staff: Ana Pelegrini Guimares, Karina Fastovsky, Franklin Dingemans, and Biniam Mengisteab

The IGISc is developing methods for mapping meadows, wetlands, streams and gullies using drone-mounted multispectral cameras.  Wetland mapping is in cooperation with the SF Bay National Estuarine Research Reserve and the San Francisco Estuary Institute.

The IGISc is working with Dr. Barbara Holzman (SFSU Professor Emeritus) on developing methods for monitoring and mapping non-native vegetation on the Farallon Islands.

The IGISc is working with Dr. David Rebanal (Assistant Professor of Community Health Education) to create an index to measure the ethnic/racial absolute clustering dimension of residential segregation. Dr. Rebanal is studying the effect of racial residential segregation and immigrant political participation on the mental health status of Asian Americans in California.

This research focuses on applications of 2D discrete Fourier transforms for karst and spur & groove coral reefs, using ArcGIS geoprocessing tools extended with numerical methods in the NumPy Python module. Ten-meter digital elevation data from Puerto Rico and Kentucky holokarst landscapes and five-meter bathymetry from more unidirectional spur and groove coral reefs at Midway Atoll were analyzed. The method identifies the dominant contributing waves in frequency space, and analyzed power contributions by 5° and 15° azimuth bins. Simulated karst and spur & groove landscapes were used to evaluate the grain of waveform orientation solutions.

In support of The Nature Conservancy's Migratory Bird Program, the IGISc recently developed R and Python scripts to automate the conversion of the Cornell Bird Lab's Spatio-Temporal Exploratory Model eBird observation data into maps focusing on California's central valley. These maps were then converted into gifs to display observation probability of different species over a calendar year. The example shown here shows the relative probability of observing a ruddy duck (Oxyura jamaicensis). The darker the hue, the lower the probability of observation.

Project Lead: Aiko Weverka
Project Staff: Seth Hiatt and Biniam Mengisteab

In order to improve campus planning, accessibility, safety, and maintenance operations, the IGISc has partnered with campus Facilities and Accessibility Offices to develop an interactive map for use by campus students, employees, and visitors. The interface will allow users to query, for instance, building and room locations, event venues, tree species, entrances, or select the most efficient routes between locations. A demo version is currently available. For more information contact Seth Hiatt.

Project Lead: Seth Hiatt

Project Staff: Anne McTavish

The Low Income Investment Fund (LIIF) of San Francisco is leveraging webmap technology to create more efficient management practices of child care facilities and encourage an open and collaborative process. The Child Care Internet Mapping Project was developed in response to this move towards the development of effective management strategies for the hundreds of child care facilities throughout the City and County of San Francisco. An ArcGIS Server-powered website provides LIIF and its partners with the ability to spatially query, identify, and generate reports on child care facilities in relation to specific cultural, demographic, and physical features of the City and County of San Francisco. Department/Affiliate: Geography, Low Income Investment Fund (CCSF)

Project Lead: Seth Hiatt

Project Staff: Barry Nickel and Jesse Cohen

COSMIC is a constellation of satellites used to measure climate variables such as temperature and water vapor at different altitudes. In order to make the data easier to access and analyze, the IGISc is using Python and PostGIS to store and deliver the data to users via an internet mapping application. Users will be able to select data sets based on location, time, and altitude, and download the data in a format that is easily read in a GIS or statistical package such as R.

Changes in climate impact the frequency and quality of cloud coverage, and in turn the amount and quality of sunlight reaching the surface of the earth. Equations derived from observerd data collected at carbon flux towers are being applied to gridded global datasets derived from MODIS satellite imagery in order to investigate how the global carbon budget might be effected by changes in cloud coverage associated with anthropogenic climate change.

Project Lead: Andrew Oliphant

Project Staff: William Goedecke