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Citation |
Potter C. Appl. Spat. Anal. Policy 2021; 14(1): 153-166. |
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Copyright |
(Copyright © 2021, Holtzbrinck Springer Nature Publishing Group) |
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DOI |
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PMID |
unavailable |
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Abstract |
The city of New Orleans is still recovering from Hurricane Katrina and continues to experience numerous negative effects from the lingering storm damage to its urban forest cover. The goal of this study was to analyze recent changes in area coverage of all trees, shrubs, and herbaceous lawns in neighborhoods of New Orleans, particularly in three of the most severely areas damaged by the flooding of 2005, down to the scale of individual blocks, and on all demolished lots and properties conveyed new ownership since 2010. Object-based classification for 4-band aircraft imagery from the National Agriculture Imagery Program (NAIP) was used to generate high-resolution maps of large tree canopy cover and vacant lots for the city of New Orleans. Field surveys and online map street photos were used to determine the accuracy of new city-wide maps of large tree canopy area. Based on 2017 NAIP image analysis of Katrina-flooded areas, results showed that the Lakeview neighborhood had the greatest number of large trees and the highest density of tree canopy area (at 11% cover), compared to the Lower Ninth Ward and Seventh Ward neighborhoods (both at 9% cover). However, vacant lots mapped in the Lower Ninth Ward were (on average) over twice as large in area as the vacant lot polygons in the other two neighborhoods studied. It was further estimated that 70% of the total area in the Lower Ninth Ward remains covered by vacant lots with shrub and herbaceous cover. The absolute number of lots was also highest for the Lower Ninth Ward with respect to demolished properties with a continuing net greening trend between 2010 and 2017. It is concluded that an object-based classification method can generate accurate high-resolution maps of large tree canopy cover and vacant vegetated lots for the city of New Orleans. Language: en |
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Keywords |
Flooding; New Orleans; Remote sensing; Shrubs; Tree cover |