FOSS4 Conference 2018 article review
Article: Mayunga, J.S., Uhinga, G.A.(2018). Mapping spatiotemporal distribution of mangroves in Mafia Island in Tanzania using Landsat Imagery
Mangroves are important coastal ecosystem that support coastal communities. However, mangroves are under threat in many part of the world, especially in developing countries such as Tanzania. In Tanzania, several laws were initiated to protect mangroves in Mafia Island, an important island that contains 9 mangrove species, but the island has not been thoroughly studied. Therefore, the research mapped the spatiotemporal distribution and the area extent of mangroves in Mafia Island in 1985, 1995, 2006 and 2013. The result indeed showed a three-decade-long decline of mangrove extent in the island with a recent dramatic decline due to shrimp farming and a lack of donor support. This result can provide insight into the level of threat that mangroves undertook and help the decision making processes to protect this unique and important habitat.
The method used was to download Landsat imageries of the island from 4 different years and then train the images for classification using the maximum likelihood algorithm. The approach of the project is similar to a remote sensing project that I did 2 years ago: mapping the shrinking lakes of Wuhan city. Yet, unlike my project which uses ArcMap throughout the project, the project used an open source GIS software ILWIS for image processing and ArcGIS only for the final preparation of the final map. The project also did accuracy assessment of the classification of imageries and the generation of spatial extent maps. I find the fact that the researchers use an open source GIS software over commercial ones to be interesting. The open source softwares are often cheaper to use and incredibly useful for collaboration. These softwares also allow for better customization and sometimes better functioning softwares. Nevertheless, I feel that for this project, using either conventional or open source GIS softwares may produce similar results. The researchers mentioned that these open source softwares are good substitue for the conventional GIS softwares, but did not say how so for their project.