Degradation of Urban Green Spaces in Lagos, Nigeria: Evidence from Satellite and Demographic Data

Abstract

The study aimed to assess the potential of using Remote Sensing (RS) data to evaluate the changes of urban green spaces in Lagos, Nigeria. Landsat Thematic Mapper and Landsat 8 (Operational Land Imager) data pair of May 4, 1986, December 12, 2002 and January 1, 2019 covering Lagos Government Authority (LGA) were used for this study. Supervised image classification technique using Maximum Likelihood Classifier (MLC) was used to create base map which was then used for ground truthing. Random Forest (RF) classification technique using RF classifier was utilized in this study to generate the final land use land cover map. RF is an ensemble learning method for classification that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification). Lagos census population data was also used in this study to model population projection. Extrapolation of the model was used to predict data for the years, 2020 and 2040. Results of the study revealed a reduction of urban green spaces due to agriculture and settlement. While the remote mapping revealed the gradual dispersion of ecosystem degradation indicators spread across the state, there exists clusters of areas vulnerable to environmental hazards across Lagos. To mitigate these risks, the paper offered recommendations ranging from the need for effective policy to green planning education for city managers, developers and risk assessment.

Comparison of performance characteristics of two malaria rapid diagnostic tests in detecting malaria infection among febrile patients in Urban Area of Lagos, Nigeria

“…Matched blood and urine samples were collected from two study sites in Lagos: a missionary hospital in Amukoko, Ajeromi Ifelodun Local Government Area (LGA) and a secondary public health facility in Surulere LGA. Amukoko is a densely populated urban area of Lagos with population density of 687,316 and human population in Lagos as at 2019 population was estimated to be 13,903,620 (Twumasi et al, 2020 (Twumasi et al, 2020).…”

How do individual-level factors influence the adoption of low-carbon technology? Proposing and validating the bioeconomy technology acceptance model in the context of Africa

“…Furthermore, carbon footprints in many locations in Lagos did not comply with both local and international standards (Bola-Popoola et al, 2019;Okafor et al, 2021). These challenges are compounded by Lagos' coastal location and other demographic trends (Bhattacharya et al, 2020;Twumasi et al, 2020). The choice of the three external psychological variables-subjective knowledge, environmental attitude, and belief about climate change-was influenced by Stern's Value-Belief-Norm (VBN) theory of environmentalism (Stern, 2000;Kim and Kim, 2018;Liu and Wu, 2020;Rizkalla and Erhan, 2020).…”

Functional mapping of green spaces in the Bălți urban ecosystem

“…Existența și calitatea spațiilor verzi atât din zonele urbane, cât și din cele rurale este dictată de nivelul de dezvoltare a societății, precum și de planul de management aplicat la momentul respectiv. Astfel, pentru elaborarea unui plan de management, este necesar de a cunoaște în detalii spațiile verzi din zona urbană, atât sub aspect cantitativ, cât și calitativ [16].…”