Landuse and Landcover Changes in Anyigba Dekina Local Government Area of Kogi State, Nigeria

The objective of this paper was to investigate the landuse and landcover (LULC) changes in Anyigba, Dekina Local Government Area of Kogi State, Nigeria to evaluate the annual rate of change, predicts future trends, and examines the implications of these changes using Landsat imagery from 1998, 2010, and 2022 obtained from the United States Geological Survey (USGS) and processed by ArcGIS. The findings reveal significant shifts in LULC patterns between 1998 and 2022. Urban areas expanded dramatically by 84.56 km² (1289.02%), with an annual growth rate of 3.52%, while agricultural land, once the dominant category, declined by 52.15 km² (34.58%). Similarly, bare surfaces shrank by 11.30 km² (57.95%). Projections for 2035 indicate continued urban expansion to 176.14 km² (79.50%), coupled with significant reductions in forest/vegetation cover (6.68%), bare surfaces (1.35%), and agricultural land (12.46%).These changes have profound implications, including the loss of forest and vegetation, increased urbanization, declining agricultural land, and diminishing bare surfaces. Such trends pose challenges for sustainable development and necessitate effective planning. The study underscores the importance of regular monitoring, control, and evaluation of LULC dynamics to mitigate haphazard development and its adverse effects on local communities.

Authors

Publication Details

Journal
Journal of applied science and environmental management
Published
2025-03-25
DOI
https://doi.org/10.4314/jasem.v29i3.21
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Landuse and Landcover Changes in Anyigba Dekina Local Government Area of Kogi State, Nigeria

Oluwafemi Oluwole, I. Ademu, H. B. Sylvanus
Journal of applied science and environmental management
Landslides and related hazards
article

Landuse and Landcover Changes in Anyigba Dekina Local Government Area of Kogi State, Nigeria

Oluwafemi Oluwole, I. Ademu, H. B. Sylvanus
article en

Abstract

The objective of this paper was to investigate the landuse and landcover (LULC) changes in Anyigba, Dekina Local Government Area of Kogi State, Nigeria to evaluate the annual rate of change, predicts future trends, and examines the implications of these changes using Landsat imagery from 1998, 2010, and 2022 obtained from the United States Geological Survey (USGS) and processed by ArcGIS. The findings reveal significant shifts in LULC patterns between 1998 and 2022. Urban areas expanded dramatically by 84.56 km² (1289.02%), with an annual growth rate of 3.52%, while agricultural land, once the dominant category, declined by 52.15 km² (34.58%). Similarly, bare surfaces shrank by 11.30 km² (57.95%). Projections for 2035 indicate continued urban expansion to 176.14 km² (79.50%), coupled with significant reductions in forest/vegetation cover (6.68%), bare surfaces (1.35%), and agricultural land (12.46%).These changes have profound implications, including the loss of forest and vegetation, increased urbanization, declining agricultural land, and diminishing bare surfaces. Such trends pose challenges for sustainable development and necessitate effective planning. The study underscores the importance of regular monitoring, control, and evaluation of LULC dynamics to mitigate haphazard development and its adverse effects on local communities.

Journal of applied science and environmental managementVol. 29(3)
Openalex Percentile: Top 90%
Landslides and related hazards
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.