Predicting locations for urban tree planting
dc.contributor.advisor | Johnson, Daniel P. (Daniel Patrick), 1971- | |
dc.contributor.author | King, Steven M. | |
dc.contributor.other | Bein, Frederick L. (Frederick Louis), 1943- | |
dc.contributor.other | Lulla, Vijay O. | |
dc.date.accessioned | 2015-02-24T15:17:38Z | |
dc.date.available | 2015-02-24T15:17:38Z | |
dc.date.issued | 2014 | |
dc.degree.date | 2014 | en_US |
dc.degree.discipline | Department of Geography | en |
dc.degree.grantor | Indiana University | en_US |
dc.degree.level | M.S. | en_US |
dc.description | Indiana University-Purdue University Indianapolis (IUPUI) | en_US |
dc.description.abstract | The purpose of this study was to locate the most suitable blocks to plant trees within Indianapolis, Indiana’s Near Eastside Community (NESCO). LiDAR data were utilized, with 1.0 meter average post spacing, captured by the Indiana Statewide Imagery and LiDAR Program from March 13, 2011 to April 30, 2012, to conduct a covertype classification and identify blocks that have low canopies, high impervious surfaces and high surface temperatures. Tree plantings in these blocks can help mitigate the effects of the urban heat island effect. Using 2010 U.S. Census demographic data and the principal component analysis, block groups with high social vulnerability were determined, and tree plantings in these locations could help reduce mortality from extreme heat events. This study also determined high and low priority plantable space in order to emphasize plantable spaces with the potential to shade buildings; this can reduce cooling costs and the urban heat island, and it can maximize the potential of each planted tree. | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/5942 | |
dc.identifier.uri | http://dx.doi.org/10.7912/C2/787 | |
dc.language.iso | en_US | en_US |
dc.rights | CC0 1.0 Universal | |
dc.rights.uri | https://creativecommons.org/publicdomain/zero/1.0 | |
dc.subject | LiDAR | en_US |
dc.subject | urban tree planting | en_US |
dc.subject | social vulnerability | en_US |
dc.subject | principal component analysis | en_US |
dc.subject.lcsh | Optical radar -- Research -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Trees in cities -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Tree planting -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Urban forestry -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Urban heat island -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Geographic information systems -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Forest canopy ecology -- Research -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Heat -- Physiological effect -- Research -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Indianapolis (Ind.) -- Remote-sensing images -- Research | en_US |
dc.subject.lcsh | Heat waves (Meteorology) -- Research -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Eastside (Indianapolis, Ind.) | en_US |
dc.subject.lcsh | Neighborhoods -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Citizens' associations -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Near East Side Community Organization (Indianapolis, Ind.) | en_US |
dc.subject.lcsh | Environmental risk assessment -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Principal components analysis | en_US |
dc.title | Predicting locations for urban tree planting | en_US |
dc.type | Thesis | en |