Author(s)

Yaw Adu Twumasi^1*, Abena Boatemaa Asare-Ansah¹, Edmund Chukwudi Merem², Priscilla Mawuena Loh¹, John Bosco Namwamba¹, Zhu Hua Ning¹, Harriet Boatemaa Yeboah³, Matilda Anokye¹, Rechael Naa Dedei Armah¹, Caroline Yeboaa Apraku¹, Julia Atayi¹, Diana Botchway Frimpong¹, Ronald Okwemba¹, Judith Oppong¹, Lucinda A. Kangwana¹, Janeth Mjema¹, Leah Wangari Njeri¹, Joyce McClendon-Peralta¹, Valentine Jeruto¹

¹Department of Urban Forestry and Natural Resources, Southern University and A&M College, Baton Rouge, USA.
²Department of Urban and Regional Planning, Jackson State University, Jackson, USA.
³Department of Geography and Tourism Studies, Brock University, Catharines, Canada.

In recent years image fusion method has been used widely in different studies to improve spatial resolution of multispectral images. This study aims to fuse high resolution satellite imagery with low multispectral imagery in order to assist policymakers in the effective planning and management of urban forest ecosystem in Baton Rouge. To accomplish these objectives, Landsat 8 and PlanetScope satellite images were acquired from United States Geological Survey (USGS) Earth Explorer and Planet websites with pixel resolution of 30m and 3m respectively. The reference images (observed Landsat 8 and PlanetScope imagery) were acquired on 06/08/2020 and 11/19/2020. The image processing was performed in ArcMap and used 6-5-4 band combination for Landsat 8 to visually inspect healthy vegetation and the green spaces. The near-infrared (NIR) panchromatic band for PlanetScope was merged with Landsat 8 image using the Create Pan-Sharpened raster tool in ArcMap and applied the Intensity-Hue-Saturation (IHS) method. In addition, location of urban forestry parks in the study area was picked using the handheld GPS and recorded in an excel sheet. This sheet was converted into Excel (.csv) file and imported into ESRI ArcMap to identify the spatial distribution of the green spaces in East Baton Rouge parish. Results show fused images have better contrast and improve visualization of spatial features than non-fused images. For example, roads, trees, buildings appear sharper, easily discernible, and less pixelated compared to the Landsat 8 image in the fused image. The paper concludes by outlining policy recommendations in the form of sequential measurement of urban forest over time to help track changes and allows for better informed policy and decision making with respect to urban forest management.

Remote Sensing, Image Fusion, Multispectral Images, Urban Forest, Landsat 8 Operational Land Imager (OLI), PlanetScope, Baton Rouge

Twumasi, Y. , Asare-Ansah, A. , Merem, E. , Loh, P. , Namwamba, J. , Ning, Z. , Yeboah, H. , Anokye, M. , Armah, R. , Apraku, C. , Atayi, J. , Frimpong, D. , Okwemba, R. , Oppong, J. , Kangwana, L. , Mjema, J. , Njeri, L. , McClendon-Peralta, J. and Jeruto, V. (2022) Fusion of Landsat 8 OLI and PlanetScope Images for Urban Forest Management in Baton Rouge, Louisiana. Journal of Geographic Information System, 14, 444-461. doi: 10.4236/jgis.2022.145024.