Spatio-temporal Analysis of Urban Growth and Its Effects on Wetlands in Rwanda: The Case of Rwampara Wetland in the City of Kigali

Abstract

This study aimed at analyzing the spatio-temporal patterns of urban growth and its effects on Rwampara wetland, located in the City of Kigali, Rwanda. First, the study was based on the application of remote sensing technology, where 4 Landsat images (1987, 1999, 2009 & 2018) were classified using maximum likelihood classification algorithm. This helped in analyzing the Land Use and Land Cover (LULC) trends in the study area. Secondly, it used the existing LULC data for the years 1990, 2000, 2010 and 2018 in order to investigate the overall changes in LULC in Kigali City. Finally, semi-structured interviews were used to collect data from local people and decision-makers about their past and future management strategies of Rwampara wetland. In this regard, 30 local communities (mainly natives from the study area), 15 local government authorities at sector and district levels as well as 4 senior government authorities in the central administration were interviewed. The findings revealed that over the past 4 decades, urban growth in Kigali City has rapidly increased at the expense of resource degradation in Rwampara wetland. Specifically, there has been an increase of about 77% of the built-up area over the last 31 years (1987-2018) which has led to the decrease of the wetland surface area from 24 ha in 1987 to only 7.7 ha in 2018. The results also revealed that demographic factors (i.e. a high population growth rate and high population densities) were mainly responsible for urban growth and degradation of wetland resources in the area under investigation.
 Keywords: urban growth, wetland, wetland resources, wetland degradation, wetland management

Land Use/Land Cover Changes Detection in Lagos City of Nigeria Using Remote Sensing and GIS

“…Precisely, training samples for the specified LULC types have been chosen by demarcating polygons around indicative sites, with pixels surrounded by these polygons and spectral signatures for the corresponding land cover types collected by satellite images [2]. Incorporated the spectral signature into the classification procedure once it was tried satisfactorily.…”

“…A process of detecting land use/land cover (LULC) alteration involves identifying changes to the features or phenomenon over time [1], and it is key to controlling environmental change [2]. Global anthropogenic activities increase considerably and lead to large-scale modifications to the earth's surface, affecting the effectiveness of global systems.…”

Urban Growth Monitoring and Prediction Using Remote Sensing Urban Monitoring Indices Approach and Integrating CA-Markov Model: A Case Study of Lagos City, Nigeria

“…Global cities have undergone significant growth and transformation in recent decades [1,2], accompanied by substantial changes in land use. Urban growth monitoring and prediction play pivotal roles in understanding the evolving dynamics of urban landscapes, offering essential insights for sustainable urban development [3][4][5].…”

Bottom-up assessment of household electricity consumption in dynamic cities of the Global South—Evidence from Kigali, Rwanda

“…At the time of the survey, about 400 Sector Land Managers were working in the 416 administrative sectors in Rwanda. Although Rwanda already uses GIS extensively, the spatial data available mainly focuses on mapping and monitoring various areas of natural science (Warnest et al, 2012;Byizigiro et al, 2020;Ngwijabagabo et al, 2021;Tafahomi and Nadi, 2021), land use and land cover change (Warnest et al, 2012;Akinyemi et al, 2017;Rwanyiziri et al, 2020;Kabeja et al, 2021), solar energy (potential) (Ukwishaka et al, 2021), and the electricity network (ESRI Rwanda et al, 2022;EUCL and ESRI Rwanda, 2022). GIS applications in the health sector and modeling spatio-temporal dynamics of diseases do also exist Nyandwi et al, 2022).…”