Urban Forest Canopy Extraction Using Lidar Data

Abstract

Urban Tree Canopy (UTC) is an important asset in the urban ecological system by reducing the heat, runoff and improving air quality. Estimating the available urban tree canopy is important for decision makers for better understanding of urban ecosystems and helps to improve environmental quality and human health in urban areas and plan conservation activities. This paper reports on an object-oriented tree extraction method developed by using spectral and textural information of High-Resolution (HR) aerial imagery and normalised Digital Surface Model (nDSM) information derived from Light Detection and Ranging (LIDAR) data. The image was segmented by edge-based segmentation algorithm and classified using the Support Vector machine (SVM) algorithm. The results showed that the proposed object-oriented method provides better classification with an overall accuracy of 88%.

RS-GIS Approach on Biomass Energy Potential Estimation of Sugarcane Residues in Medellin, Cebu

“…Due to its ability to produce three dimensional point cloud data, airborne LiDAR technology has been used for vertical feature description. Airborne LiDAR is a laser system that contrasts laser pulses emitted by an airborne sensor with travel time variations, communicating with earth objects, and returning to the sensor [11][12][13]. The application of remote sensing technology extends to science-based resource inventory.…”

Using feature analyst & NAIP imagery to conduct a statewide tree canopy assessment of Georgia

“…Because preservation of forestry resources is a primary goal impacting state policy, this dataset will inform decision makers thereby assisting in improving environmental quality in urbanized locations and planning conservation activities in exurban, rural, or interface locations. 5 The Georgia Forestry Commission is already using this dataset to inform policy makers regarding the health and abundance of trees in Georgia and hopes to fund new projects for comparative analysis soon.…”

“…2 At the time of funding, the 2015 imagery from United States Department of Agriculture 3 was determined to be the most complete statewide file which could feasibly be analyzed. Other researchers have used LiDar [4][5][6][7] or aerial imagery from UAV; 7 however neither of these options fit the objectives of the Georgia Forestry Commission (GFC). First, there is not a currently complete and available LiDar imagery for the state of Georgia; just now in 2018, Georgia has only just began collecting LiDar data and only 82 of the 159 counties in Georgia have been flown.…”