Land use land cover (LULC) analysis in Nigeria: a systematic review of data, methods, and platforms with future prospects
Abstract Understanding land use and land cover (LULC) classification is critical for addressing environmental and human needs, particularly in developing countries. Nigeria is a developing country experiencing rapid population growth and economic development leading to increased LULC changes. While...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-12-01
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| Series: | Bulletin of the National Research Centre |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42269-024-01286-z |
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| Summary: | Abstract Understanding land use and land cover (LULC) classification is critical for addressing environmental and human needs, particularly in developing countries. Nigeria is a developing country experiencing rapid population growth and economic development leading to increased LULC changes. While many studies have been done on LULC changes, there is a need for a comprehensive review of existing knowledge and limitations of LULC analyses in Nigeria. Hence, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method, this review paper presents a systematic review of LULC analyses in Nigeria by examining the adopted remote sensing data, pre-classified global and regional LULC maps, and classification and validation methods. This paper draws attention to the significant growth in LULC studies and highlights a need for awareness and access to existing and readily available LULC data. This review provides a broad overview of LULC data, classification methods, focus, scale, and constraints associated with LULC analysis in Nigeria. Also, it provides probable solutions to the challenges and GEE-based LULC classification scripts. There is a need to create and prioritize a national LULC data repository to ensure sustainable land monitoring and management in Nigeria. This will facilitate the spatial and temporal assessment of LULC at different scales and regions. High-resolution imagery and advanced classification methods such as deep learning need to be adopted to ensure accurate land cover analysis at different scales. Also, increased awareness programs, collaboration, and capacity-building initiatives will be beneficial to addressing current and emerging challenges related to LULC studies in Nigeria. |
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| ISSN: | 2522-8307 |