The nonprofit recently shared a glimpse of its ongoing research with NV5 Geospatial. The update included photos of NV5 Geospatial crews flying over Laredo's skyline while collecting data.
Last year, RGISC launched an urban heat island mapping study, partnering with NOAA to collect on-the-ground temperature data through volunteers and citizen scientists. Laredo was one of 14 cities selected for the 2024 study.
Although data had been collected, RGISC submitted a proposal to the Environmental Justice Data Fund for a complementary study focused on tree canopies in Laredo . Further research revealed a lack of local data in this area.
"In our research, what we found out — well, the lack of — the lack of tree canopy data for Laredo ," said Martin Castro , RGISC watershed director. "The last data set we found that would be usable for something like this was from 2019," he said, noting it wasn't on trees specifically, but lidar data conducted by the Texas General Land Office . "We figured, well, we need to update the data anyways."
Experts from across the country were consulted on tree equity, including Tree Philly, researchers at Harvard, the University of Massachusetts Amherst and the University of Vermont's Spatial Analytics Lab .
Work on the study began in April after RGISC received funding in August 2024 , a total of $438,962.60 to support three projects: Air Quality Monitoring Expansion, Tree Equity Assessment and Community Engagement and Education.
RGISC first went through a vetting process to select lidar technology — a remote sensing tool that uses laser pulses to measure the distance between a sensor and surfaces on the ground — capable of conducting high-quality, detailed scans to count every tree and green space in Laredo for the Tree Equity Assessment. A firm based in Hollywood, Florida , was awarded the bid to gather information across Laredo's landscape.
In late September, NV5 Geospatial crews flew over Laredo to collect the data. As of October, the data is being processed and will be sent to a scientific team at the University of Vermont for compilation. The lidar data will go hand in hand with previous Urban Heat Island Indexing data collected in August 2024 .
"Those are two high-quality data sets that are begging to be complete, so to speak, in a way I think is really groundbreaking for Laredo ," he said. "I don't think there's any other firm or organization, be it public or private, that's really done this before."
The dataset is expected to be finalized by late 2026 and may include recommendations for tree planting based on areas of canopy density and scarcity. It will help prioritize a planting or reforestation plan.
Beyond the scientific standpoint, Castro said the community should be invested in the data, as it could point to solutions for Laredo's high urban heat index.
"The lack of trees and walkable greenspaces is very intersectional to the health of the population. Folks don't want to be out when it's a 105 degrees in the summertime and there's no shade," he said. "High urban heat indexes also cause other issues."
Castro said research has pointed to heat stress and other heat-related health impacts.
Having the dataset, Castro said, means being able to address issues and create equitable climate resilience, adaptation strategies and infrastructure.
"Without the data sets, it would be hard to make a case without the data, to prove that there is a problem. We know it's hot, right?" he said. "This is an issue that Laredo has been dealing with for a long time, and we have the tools and resources (that are) going to make our jobs a little bit easier in order to address these heat issues."
Once the data is finalized, RGISC will share it with local governments and organizations that may need it for urban planning purposes.
"We look forward to the results and seeing not only where we need more trees, but also what areas, if planted, could be served by trees to reduce the high urban heat indexes that Laredo suffers from."
© 2025 the Laredo Morning Times (Laredo, Texas). Distributed by Tribune Content Agency, LLC.
