Object-based delineation of urban tree canopy: assessing change in Oklahoma City, 2006–2013. (January 2019)
- Record Type:
- Journal Article
- Title:
- Object-based delineation of urban tree canopy: assessing change in Oklahoma City, 2006–2013. (January 2019)
- Main Title:
- Object-based delineation of urban tree canopy: assessing change in Oklahoma City, 2006–2013
- Authors:
- Ellis, Emily A.
Mathews, Adam J. - Abstract:
- Abstract: With a burgeoning global population, the pressures of urbanization are increasingly prevalent. The need to quantify urban greenness remains significant due to environmental impact and its relationship with human well-being. Utilizing 1 m discrete-return airborne lidar-derived digital terrain models (DTMs) and digital surface models (DSMs), aerial imagery, and lidar-imagery fusion, this study assesses vegetation, specifically tree canopy, change within Oklahoma City between 2006 and 2013. Specifically, we (1) identify an accurate object-based image analysis (OBIA) method for the detection of urban vegetation outlines, and (2) apply that method to locate and quantify vegetation change and assess spatial patterns in Oklahoma City between 2006 and 2013. The proposed OBIA approach extracts urban vegetation coverage from aerial imagery and lidar-based models with around 89% accuracy. Regarding vegetation change, Oklahoma City lost 9.69 km 2 (3.74 mi 2 ) of tree canopy coverage, which accounted for a 2% loss in total greenness. Highlights: An open source, adoptable object-based method was developed to extract tree canopy in the urban environment. The method was tested using three input datasets: lidar, aerial imagery, and lidar-imagery fusion. The lidar-imagery fusion data yielded the most accurate segmentation results. The object-based method was 89% accurate at extracting tree canopy extents. Between 2006 and 2013, Oklahoma City lost 2% of its urban tree canopy extent.
- Is Part Of:
- Computers, environment and urban systems. Volume 73(2019)
- Journal:
- Computers, environment and urban systems
- Issue:
- Volume 73(2019)
- Issue Display:
- Volume 73, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 73
- Issue:
- 2019
- Issue Sort Value:
- 2019-0073-2019-0000
- Page Start:
- 85
- Page End:
- 94
- Publication Date:
- 2019-01
- Subjects:
- Object-based image analysis -- Remote sensing -- Lidar -- Data fusion -- Tree canopy delineation -- Oklahoma City
City planning -- Data processing -- Periodicals
Regional planning -- Data processing -- Periodicals
303.4834 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01989715 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compenvurbsys.2018.08.006 ↗
- Languages:
- English
- ISSNs:
- 0198-9715
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.914000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8451.xml