The SAL, in conjunction with the Virginia Dept. of Forestry received a bronze medal from the Association of Natural Resource Educational Professionals (ANREP) for our urban tree canopy work in Virginia.
The SAL recently completed tree canopy assessments for the City of Virginia Beach, Virginia and Howard County, Maryland.
The City of Bowie, Maryland is establishing an urban tree canopy goal based on an assessment conducted by the SAL and the Maryland Department of Natural Resources.
Jarlath O'Neil-Dunne, RSENR Geospatial Analyst, gave a presentation on "Mapping the Green Infrastructure" at the 2009 eCognition User Meeting in Munich, Germany.
Jarlath O'Neil-Dunne, RSENR Geospatial Analyst, received an award from 1986 Nobel Prize winner Dr. Gerd Binnig in recognition of his expertise employing the object-based image analysis techniques developed by Dr. Binnig to advance the understanding of urban ecosystems.
Jarlath O'Neil-Dunne, RSENR Geospatial Analyst, gave a workshop on object-based image analysis techniques for extracting information from high-resolution remotely sensed data at the 2009 AmericaView fall technical meeting at the USGS EROS Data Center in Sioux Falls, SD.
Showing posts with label image interpretation. Show all posts
Showing posts with label image interpretation. Show all posts
Friday, January 8, 2010
Monday, September 14, 2009
Advocates and officials debate use of tree fund mitigation monies to fund UTC survey; Denton, TX
City may commission tree survey Denton Record Chronicle News for Denton County, Texas Local News:
Some advocates oppose cost of proposal, use of money from tree fund
12:09 AM CDT on Monday, September 14, 2009
By Lowell Brown / Staff Writer
A new phase of Denton’s ongoing tree code overhaul will start this week, as the City Council considers funding a citywide tree canopy survey.
The city would spend an estimated $30,000 to $40,000 on a joint project with the University of North Texas to measure the amount of tree coverage in and around Denton under a plan the council will discuss Tuesday. City planners say the project would help them set target percentages for tree preservation and find wooded land the city might want to buy and protect. No vote is scheduled.
Some tree advocates have criticized the plan, in part because it would use money from the city’s tree fund, which collects fines from developers who illegally clear-cut or fail to meet the city’s minimum standards for onsite tree preservation. They argue that the fund should be spent on protecting trees, not counting them.
Some advocates oppose cost of proposal, use of money from tree fund
12:09 AM CDT on Monday, September 14, 2009
By Lowell Brown / Staff Writer
A new phase of Denton’s ongoing tree code overhaul will start this week, as the City Council considers funding a citywide tree canopy survey.
The city would spend an estimated $30,000 to $40,000 on a joint project with the University of North Texas to measure the amount of tree coverage in and around Denton under a plan the council will discuss Tuesday. City planners say the project would help them set target percentages for tree preservation and find wooded land the city might want to buy and protect. No vote is scheduled.
Some tree advocates have criticized the plan, in part because it would use money from the city’s tree fund, which collects fines from developers who illegally clear-cut or fail to meet the city’s minimum standards for onsite tree preservation. They argue that the fund should be spent on protecting trees, not counting them.
Monday, September 7, 2009
UVM imagery expert talks about importance of seeing the trees as well as the forests when it comes to UTC assessment; Burlington, VT
Letters from the SAL: Sweat the small stuff:
Sweat the small stuff
Several years ago we performed our first urban tree canopy (UTC) assessment in Baltimore City, which lead to Baltimore City establishing one of the first UTC goals in the nation (40%). The land cover data used to determine Baltimore's existing tree canopy percentage of 20% came from the Strategic Urban Forest Assessment (SUFA) dataset. SUFA relied on pixel-based classifiers to extract land cover information from 2001 IKONOS satellite imagery.
Sweat the small stuff
Several years ago we performed our first urban tree canopy (UTC) assessment in Baltimore City, which lead to Baltimore City establishing one of the first UTC goals in the nation (40%). The land cover data used to determine Baltimore's existing tree canopy percentage of 20% came from the Strategic Urban Forest Assessment (SUFA) dataset. SUFA relied on pixel-based classifiers to extract land cover information from 2001 IKONOS satellite imagery.
Monday, May 25, 2009
University of Vermont video walks viewers through UTC assessment process using Rockville, MD as case study
Letters from the SAL: Urban Tree Canopy Assessment - Rockville, MD:
The video below presents the results of the urban tree canopy (UTC) assessment we just completed for Rockville, MD. High resolution land cover is the basis for the UTC assessment. Rockville is covered by both leaf-on color infrared imagery and LiDAR data, but mapping land cover proved to considerably more challenging than we expected. Some filtering was performed on the LiDAR data, resulting in a very inconsistent first return dataset (we did not have access to the point cloud). By taking a data fusion approch, combining the LiDAR and imagery in Definiens we were able to get around this, but it was not easy. I discuss these issues a bit in the video, but hope to cover the process in more detail in a future post. Imagery was prepped using ERDAS IMAGINE. LiDAR data was prepped using QT Modeler. The UTC metrics are generated using a geoprocessing model within ArcGIS. Please click on the image below to view the video.
The video below presents the results of the urban tree canopy (UTC) assessment we just completed for Rockville, MD. High resolution land cover is the basis for the UTC assessment. Rockville is covered by both leaf-on color infrared imagery and LiDAR data, but mapping land cover proved to considerably more challenging than we expected. Some filtering was performed on the LiDAR data, resulting in a very inconsistent first return dataset (we did not have access to the point cloud). By taking a data fusion approch, combining the LiDAR and imagery in Definiens we were able to get around this, but it was not easy. I discuss these issues a bit in the video, but hope to cover the process in more detail in a future post. Imagery was prepped using ERDAS IMAGINE. LiDAR data was prepped using QT Modeler. The UTC metrics are generated using a geoprocessing model within ArcGIS. Please click on the image below to view the video.
Subscribe to:
Posts (Atom)