Indiana University-Purdue University Indianapolis (IUPUI) / Urban forestry is a very important element of urban structures that can improve the environment and life quality within the urban areas. Having an accurate classification of urban forests and grass areas would help improve focused urban tree planting and urban heat wave mitigation efforts. This research project will compare the use of high – resolution aerial imagery and LiDAR data when used to classify canopy and grass areas. The high – resolution image, with 1 – meter resolution, was captured by The National Agriculture Imagery Program (NAIP) on 6/6/2012. Its coordinate system is the North American Datum of 1983 (NAD83). The LiDAR data, with 1.0 – meter average post spacing, was captured by Indiana Statewide Imagery and LiDAR Program from 03/13/2011 to 04/30/2012.The study area is called the Near East Side Community Organization (NESCO) neighborhood. It is located on the east side of downtown Indianapolis, Indiana. Its boundaries are: 65 interstate, East Massachusetts Avenue, East 21st Street, North Emerson Avenue, and the rail road tracks on the south of the East Washington Street. This research will also perform the accuracy assessment based on the results of classifications using high – resolution aerial imagery and LiDAR data in order to determine and explain which method is more accurate to classify urban canopy and grass areas.

Indiana University-Purdue University Indianapolis (IUPUI) / The purpose of this study was to identify urban heat island locations within Center Township, Indiana and to develop a model to determine areas of high social vulnerability. In addition, an urban heat island mitigation strategy was developed for socially vulnerable and highest temperature locations. Land surface temperature was estimated using Landsat ETM+ satellite imagery. Social vulnerability was estimated using principal components analysis and spatial analysis methods such as kernel density functions. These methods incorporate various socioeconomic variables, land surface temperature, and tree canopy cover. Tree canopy cover was extracted using Quickbird imagery among other techniques. Areas with high social vulnerability, high temperature and low tree canopy cover were analyzed and plantable spaces were assessed. The findings of this study will be shared with Keep Indianapolis Beautiful, Inc. so that they can inform their tree planting campaigns that seek to reduce the effects of urban heat islands on socially vulnerable populations.

Indiana University-Purdue University Indianapolis (IUPUI) / 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.