TITLE:
Fusion of Landsat 8 OLI and PlanetScope Images for Urban Forest Management in Baton Rouge, Louisiana
AUTHORS:
Yaw Adu Twumasi, Abena Boatemaa Asare-Ansah, Edmund Chukwudi Merem, Priscilla Mawuena Loh, John Bosco Namwamba, Zhu Hua Ning, Harriet Boatemaa Yeboah, Matilda Anokye, Rechael Naa Dedei Armah, Caroline Yeboaa Apraku, Julia Atayi, Diana Botchway Frimpong, Ronald Okwemba, Judith Oppong, Lucinda A. Kangwana, Janeth Mjema, Leah Wangari Njeri, Joyce McClendon-Peralta, Valentine Jeruto
KEYWORDS:
Remote Sensing, Image Fusion, Multispectral Images, Urban Forest, Landsat 8 Operational Land Imager (OLI), PlanetScope, Baton Rouge
JOURNAL NAME:
Journal of Geographic Information System,
Vol.14 No.5,
October
19,
2022
ABSTRACT: 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.