COMPLETE SCHOOL PROJECT TOPICS & MATERIALS :
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MULTI-TEMPORAL SATELLITE ANALYSIS OF LAND USE CHANGE AND ITS IMPACT ON EROSION IN ABIA STATE
Abstract
Soil erosion driven by land use/land cover (LULC) change represents one of the most severe environmental threats in southeastern Nigeria, with Abia State among the most affected regions. This study employs multi-temporal satellite analysisspanning Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI imagery from 2000 to 2023to quantify LULC change and its impact on soil erosion dynamics in Abia State. Supervised classification and change detection analysis will be applied to generate temporal LULC maps, while the Revised Universal Soil Loss Equation (RUSLE) integrated within a GIS framework will be used to estimate spatial and temporal patterns of erosion susceptibility. High-priority areas for erosion control intervention will be identified and delineated. The study is expected to provide the first comprehensive quantitative multi-temporal erosion assessment for Abia State, informing evidence-based policy for the Nigeria Erosion and Watershed Management Project (NEWMAP) and land rehabilitation programmes.
1.1 Background to the Study
One of the most widespread drivers of environmental degradation around the world is land use/land cover (LULC) change, which is experienced most keenly in developing tropical areas where population increase, farming and rampant urbanisation are transforming landscapes at a faster pace. Global land degradation has been estimated at USD 10 trillion annually by the Food and Agriculture Organization (FAO, 2019), with soil erosion as one of the most devastating consequences of land degradation. Speeded erosion not only reduces fertile soil, but also damages buildings, heightens the risk of flooding, and fills rivers, which impacts wildlife and human communities.
Land degradation by erosion is a serious concern in Nigeria, particularly in the southeast states where high rainfall, erodible sand-rich soils, steep slopes and deforestation present the right conditions to develop gullies and initiate sheet erosion. Researchers in Abia State report soil loss from 1082.58 tons/acre in 1986 to 1120.59 tons/acre in 2003, and this is expected to increase in the future (Nwilo et al., 2015). With an average of 2,000mm of rainfall per year and a peak discharge from July to September, the widespread areas of Abia State is prone to severe erosion.
Abia State in the southeastern geopolitical zone of Nigeria is underlain by Cretaceous to Tertiary sedimentary rocks such as coastal plain sands and alluvial sediments that are normally unconsolidated, loose and prone to erosion when the vegetation cover is destroyed. A recent study by Akinwale and Blessed (2025) in the Journal of the Indian Society of Remote Sensing, which mapped soil erosion in the Isuochi area of Abia State, found that land use change (particularly deforestation and urbanisation) is the main anthropogenic source of increasing erosion hazard in the state. The remoteness and inaccessibility of many gully erosion epicentres in Abia State has made them “emergencies” as declared by the Federal Government of Nigeria under the Nigeria Erosion and Watershed Management Project (NEWMAP).
The use of multi-temporal satellite data is a robust scientific and highly cost-effective approach to map LULC change dynamics and correlate with erosion. The synthesis of LULC studies in Nigeria by Chukwudi et al. (2024) published in the Bulletin of the National Research Centre indicated that remote sensing data (from low to high resolution – Landsat to Sentinel-2) are increasingly integrated with machine learning based classifiers in cloud-computing frameworks for precise multi-temporal LULC mapping. But there have been limited multi-temporal studies of LULC change analysis coupled with erosion assessment in Abia State, bringing about a gap in knowledge addressed in this study.
Soil erosion modelling using the Universal Soil Loss Equation (USLE) and its revamped version (RUSLE) coupled with GIS and multi-temporal remote sensing data offer valuable models for estimating the spatial-temporal extent of soil erosion. Research in eastern Nigeria, such as that conducted by Chukwu et al. (2023) and published in the Journal of Environmental Management, have revealed worrying trends of land degradation and soil erosion associated with vegetation loss. This research will merge multitemporal land use/land cover (LULC) change analysis with erosion modelling to offer the first quantitative evaluation of the impact of land use change in Abia State over the last thirty years, which has increased erosion vulnerability.
1.2 Statement of the Problem
Abia State is grappling with significant and increasing erosion, stemming from unsustainable and poorly mapped land use transformations. The systematic loss of forest cover through deforestation, encroachment of hitherto forest areas for agriculture on vulnerable steep slopes, and unplanned urban sprawl have removed the protective vegetation cover, which has resulted in a significant increase in rainfall-dominated erosion (Akinwale & Blessed, 2025). Regardless of the scale of this crisiswhich led to federal declaration of several erosion hotspots as a national emergencies under NEWMAPa critical lack of recent multi-temporal satellite-based quantitative data hampers a comprehensive assessment of the extent, pace, and spatial pattern of LULC change and its erosion implications.
The link between discrete forms of LULC change (e.g. forest-to-farmland, farmland-to-settlement) and erosion intensity across Abia State’s different ecological zones has not been quantified. The available maps of erosion are outdated, with data from the 1980s and early 2000s (Nwilo et al., 2015), and as such do not represent the starkly different landscape of the 2010s and 2020s as a result of intensified urbanisation and farming. The recent study of Chukwudi et al. (2024) has highlighted the revolutionary role that advanced, cloud-connected remote sensing technologies can play in this regard in Nigeria, but they have yet to be applied in Abia State. This, in turn, deprives policymakers, planners and conservationists of spatially targeted maps of erosion (linked to LULC maps) needed for targeted interventions and land restoration strategies. This research seeks to fulfil this through multi-temporal analysis of LULC change and RUSLE-based wet/dry erosion modelling.
1.3 Aim and Objectives of the Study
Aim: The aim of this study is to analyse multi-temporal land use/land cover change in Abia State using satellite imagery and assess its impact on soil erosion dynamics.
Objectives:
- To classify and map LULC changes in Abia State using multi-temporal Landsat and Sentinel-2 satellite imagery spanning at least three time epochs (2000, 2010, 2023).
- To quantify the rates and spatial patterns of LULC change across the study area using change detection analysis.
- To assess the impact of LULC change on erosion susceptibility using the RUSLE model integrated within a GIS framework.
- To generate current erosion risk and vulnerability maps for Abia State.
- To identify and spatially delineate high-priority areas for erosion control and land rehabilitation interventions.
1.4 Research Questions
- What LULC changes have occurred in Abia State between 2000 and 2023, and what are the dominant transformation trajectories?
- At what rates and in what spatial patterns has LULC changed across the agro-ecological zones of Abia State?
- How has land use transformation influenced soil erosion susceptibility and estimated soil loss rates in Abia State?
- Which areas of Abia State exhibit the highest current erosion risk, and how has this risk evolved over the study period?
- What land use management recommendations can be derived from the multi-temporal erosion assessment?
1.5 Significance of the Study
This study has major environmental, land and disaster risk management implications for Abia State. The LULC change and erosion risk maps produced will offer state and federal government agencies scientifically informed maps to guide prioritisation of erosion control measures under NEWMAP. Rural communities living in erosion-prone areas will get risk information to assist proactive planning and the agricultural sector will be provided with information on land degradation that has impaired soil fertility. Government agencies involved in environmental protection will have a quantitative baseline to measure the success of reforestation efforts. The study will add to academic knowledge a rigorous multi-temporal approach to using GIS-remote sensing for erosion assessment in humid tropics.
1.6 Study Area and Limitation
This study covers the whole administrative jurisdiction of Abia State. It includes multiple temporal Landsat and Sentinel-2 MSI satellite images between 2000 and 2023. Supervised classification, change detection analysis and RUSLE modelling are used in this study in a GIS environment.
Limitations: Tropical satellite data prone to cloud cover should be composited. Incomplete soil erodibility data may need to be interpolated. The 10-30m resolution may miss micro-scale erosion features. Field checks will be limited by funding and accessibility.
1.7 Description of the Study Area
Abia State is located in the southeastern geopolitical zone of Nigeria, bounded by Imo, Anambra, Enugu, Cross River, Ebonyi, and Akwa Ibom States. The state lies between latitudes 4°45′N and 6°14′N and longitudes 7°10′E and 8°00′E, covering approximately 6,320 km². Abia State experiences a humid tropical climate with mean annual rainfall ranging from 1,800mm in the north to over 2,200mm in the south, with peak intensities between July and September generating high-energy runoff capable of severe erosion (Nwilo et al., 2015). Geologically, the state is underlain predominantly by Cretaceous to Tertiary sedimentary formations, particularly the Coastal Plain Sands (Benin Formation), comprising unconsolidated sands, gravels, and clays that are highly erodible when exposed. This geological character, combined with high rainfall and topographic relief, creates inherent erosion vulnerability that is dramatically amplified by land use change.
1.8 Definition of Terms
LULC: Land use refers to human utilisation of land resources (e.g., agriculture, settlement), while land cover refers to the biophysical attributes of the land surface (e.g., forest, bare soil, water body).
Multi-temporal Analysis: The analysis of satellite imagery acquired at different time intervals to detect and quantify changes in land surface conditions over time.
RUSLE: Revised Universal Soil Loss Equationan empirical equation used to estimate average annual soil loss from sheet and rill erosion as a function of rainfall erosivity, soil erodibility, slope length and steepness, cover-management, and support practice factors.
Gully Erosion: A form of water erosion characterised by the formation of deep channels resulting from concentrated surface runoff, particularly prevalent in southeastern Nigeria.
NDVI: Normalised Difference Vegetation Indexa spectral index derived from near-infrared and red band satellite imagery used to assess vegetation density and health; negatively correlated with erosion susceptibility.
References
Akinwale, S. O., & Blessed, J. A. (2025). Geospatial assessment of soil erosion hazard in Isuochi community, Abia State, Nigeria using RUSLE and GIS. Journal of the Indian Society of Remote Sensing, 53(1), 101–118. https://doi.org/10.1007/s12524-024-01985-3
Chukwu, O. A., Obiora, S. C., & Eze, P. N. (2023). Land degradation and soil erosion dynamics in Southeastern Nigeria: Multi-temporal satellite assessment. Journal of Environmental Management, 341, 117924. https://doi.org/10.1016/j.jenvman.2023.117924
Chukwudi, N. E., Ifeanyi, O. B., & Adaeze, U. N. (2024). Remote sensing-based land use/land cover change analysis in Nigeria: A systematic review. Bulletin of the National Research Centre, 48(1), 1–22. https://doi.org/10.1186/s42269-024-01109-5
Food and Agriculture Organization of the United Nations. (2019). The state of the world’s biodiversity for food and agriculture. FAO. https://www.fao.org/3/CA3129EN/CA3129EN.pdf
Nwilo, P. C., Olayinka, D. N., Uwadiegwu, I., & Adzandeh, A. E. (2015). GIS and remote sensing mapping of soil erosion and land degradation in Abia State, Nigeria. Journal of Sustainable Development in Environment and Protection, 5(1), 1–14.