Flood Susceptibility Mapping of Makera District and Environs in Kaduna South Local Government Area of Kaduna State-Nigeria

The increased flood incidences experienced all over the world due to climate change dynamics call for a concerted effort towards forestalling future hazards. This study thus, identified the areas that are susceptibility to floods in parts of the Makera district of the Kaduna South Local Government Area in Nigeria using geospatial techniques. Geographic Information System (GIS) was used to produce thematic layers of the factors contributing to flooding (elevation, slope, drainage density, rainfall, land use/land cover); and a multi-criteria evaluation particularly the “Analytical Hierarchical process” (AHP) was applied to determine the locations at risk. The various thematic layers were integrated into the weighted overlay tool in the ArcGIS 10.3 environment to generate the final susceptibility map. The overlay tool was also used to determine the elements at risk of flood in the study area. The results show that the areas that were highly susceptible to flood constituted about 39% of the study area, while moderate and low vulnerable areas constituted about 26% and 35%, respectively. The result of the multi-criteria analysis revealed that land use/land cover (0.601) was the factor that contributed the most to flooding in the study area based on the criteria weights followed by rainfall (0.470), drainage density (0.326), elevation (0.144), and slope (0.099), respectively. The study recommends that authorities concerned should ensure strict adherence to land use planning act, such that floodplains are avoided during development of any type.

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Modelling the relationship between climatic variables and land use/land cover classes in Yewa South Local Government Area of Ogun State, Nigeria

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1036/1/012003 ◽

2021 ◽

Vol 1036 (1) ◽

pp. 012003

Author(s):

S A Ojo ◽

J O Olusina ◽

B U Ngene ◽

D O Olukanni

Keyword(s):

Land Use ◽

Local Government ◽

Land Cover ◽

Local Government Area ◽

Climatic Variables ◽

Land Use Land Cover ◽

Ogun State ◽

The Relationship

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Land Use/Land Cover Changes of Ado-Ekiti LGA, Ekiti State, Nigeria Using Remote Sensing Techniques

Journal of Geography Environment and Earth Science International ◽

10.9734/jgeesi/2021/v25i830302 ◽

2021 ◽

pp. 32-42

Author(s):

Ajagbe, Abeeb Babajide ◽

Oguntade, Sodiq Solagbade ◽

Abiade, Idunnu Temitope

Keyword(s):

Remote Sensing ◽

Land Use ◽

Local Government ◽

Land Cover ◽

Water Body ◽

Local Government Area ◽

Land Cover Changes ◽

Landsat 8 ◽

Land Use Land Cover ◽

Bare Surface

Land use assessment and land cover transition need remote sensing (RS) and geographic information systems (GIS). Land use/land cover changes of Ado-Ekiti Local Government Area, Ekiti State, Nigeria, were examined in this research. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were acquired for 1985, 2000, and 2015 respectively. Image scene with path 190 and row 055 was used for the three Landsat Images. A supervised digital image classification approach was used in the study, which was carried out using the ArcMap 10.4 Software. Five land use/land cover categories were recognised and recorded as polygons, including Built-up Areas, Bare surface, water body, Dense Vegetation and Sparse Vegetation. The variations in the area covered by the various polygons were measured in hectares. This study revealed that between 1985 and 2015, there was a significant change in Built-up areas from 1694 hectares to 5656 hectares. However, there was a reduction in water body from 25 hectares in 1985 to 19 hectares in 2015; there was a severe reduction in the bare surface from 4641 hectares in 1985 to 2237 hectares in 2015. Generally, the findings show that the number of people building houses in the study area has grown over time, as many people reside in the outskirts of the Local Government Area, resulting in a decrease in the vegetation and bare surfaces. The maps created in this research will be useful to the Ekiti State Ministry of Land, Housing, Physical Planning, and Urban Development to develop strategies and government policies to benefit people living in the Ado-Ekiti Local Government Area of the State.

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Classification of land use/land cover of Aniocha north local government area, Delta state using satellite imagery

World Journal of Advanced Research and Reviews ◽

10.30574/wjarr.2021.10.3.0273 ◽

2021 ◽

Vol 10 (3) ◽

pp. 207-216

Author(s):

Ugbelase Vincent Nwacholundu ◽

Igbokwe Joel Izuchukwu ◽

Emengini Josephine Ebele ◽

Ejikeme Joseph Onyedika ◽

Igbokwe Esomchukwu Chinagorom

Keyword(s):

Land Use ◽

Local Government ◽

Land Cover ◽

Local Government Area ◽

Thematic Mapper ◽

Population Pressure ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Average Accuracy ◽

Landsat 7

Remote Sensing (RS) and Geographic Information System (GIS) have been established as indispensable tools in the assessment of Land use / Land cover (LULC) change. RS and GIS are important for the monitoring, modelling and mapping of land use and land cover changes across a range of spatial and temporal scales, in order to assess the extent, direction, causes, and effects of the changes. Change detection has provided suitable and wide-ranging information to various decision support systems for natural resource management and sustainable development. The main objective of the study is to assess and evaluate the extent and direction of changes in LULC of Aniocha North Local Government Area (LGA), Delta State, Nigeria to explain the changes and identify some of their effects on both the livelihoods of the local people and the local environment, and also to explore some of the conservation measures designed to overcome problems associated with land use and land cover changes. Landsat 7 Enhanced Thematic Mapper (ETM+) of 2002 with 30 meters resolution and landsat 7 Enhanced Thematic Mapper (ETM) 2014satellite images as well as GIS techniques were used to monitor the changes and to generate maps of the LULC of the area in these periods. Supervised Land Use/Land Cover classification algorithm (Maximum likelihood with null class) was used in the analysis of classification. The classification result of LandSat ETM+ (2002) revealed that farmland accounted for 36.34% of the total LULC class, followed by savannah which accounted for 24.15%. Forest built up area, and waterbody constituted 20.42%, 16.46% and 2.62% respectively. Also, the result of LandSat ETM (2014) shows that forest accounted for 38.59% followed by farmland with 30.93%. Built up area covers 25.55% while savannah and river cover 2.86% and 2.08% respectively. The classification shows 83.26 % average accuracy and 79.16 % overall accuracy for 2002 while the 2014 accuracy assessment showed 95.06% average accuracy and 94.99% overall accuracy. Growing population pressure and its associated problems, such as the increasing demand for land and trees, poor institutional and socio-economic settings, and also unfavorable government policies, such as lack of land tenure security and poor infrastructure development, have been the major driving forces behind the LULC changes.

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Effect of cement factory on land use-land cover in Obajana Lokoja Local Government Area, Kogi State, Nigeria

African Journal of Environmental Science and Technology ◽

10.5897/ajest2017.2327 ◽

2017 ◽

Vol 11 (7) ◽

pp. 384-392

Author(s):

Dalil Musa ◽

Omeiza Amodu Isaiah ◽

Abdullahi Abbas Yahaya ◽

Husaini Abdul

Keyword(s):

Land Use ◽

Local Government ◽

Land Cover ◽

Local Government Area ◽

Land Use Land Cover ◽

Cement Factory

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LAND USE LAND COVER ANALYSIS OF DEGRADED AREAS IN MUBI-NORTH AND GOMBI LOCAL GOVERNMENT AREAS OF ADAMAWA STATE: NIGERIA

International Journal of Advances in Agricultural Science and Technology ◽

10.47856/ijaast.2020.v07i11.015 ◽

2020 ◽

Vol 7 (11) ◽

pp. 112-122

Author(s):

Gadona Enoch Alhamdu ◽

Gamaniel Japheth ◽

Elisha Tizhe Faive

Keyword(s):

Land Use ◽

Local Government ◽

Land Cover ◽

Land Use Land Cover

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Use of GIS and Remote Sensing Data to Understand the Impacts of Land Use/Land Cover Changes (LULCC) on Snow Leopard (Panthera uncia) Habitat in Pakistan

Sustainability ◽

10.3390/su13073590 ◽

2021 ◽

Vol 13 (7) ◽

pp. 3590

Author(s):

Tauheed Ullah Khan ◽

Abdul Mannan ◽

Charlotte E. Hacker ◽

Shahid Ahmad ◽

Muhammad Amir Siddique ◽

...

Keyword(s):

Remote Sensing ◽

At Risk ◽

Land Use ◽

Land Cover ◽

Human Population ◽

Land Cover Changes ◽

Snow Leopard ◽

Land Use Land Cover ◽

Gis And Remote Sensing ◽

Panthera Uncia

Habitat degradation and species range contraction due to land use/land cover changes (LULCC) is a major threat to global biodiversity. The ever-growing human population has trespassed deep into the natural habitat of many species via the expansion of agricultural lands and infrastructural development. Carnivore species are particularly at risk, as they demand conserved and well-connected habitat with minimum to no anthropogenic disturbance. In Pakistan, the snow leopard (Panthera uncia) is found in three mountain ranges—the Himalayas, Hindukush, and Karakoram. Despite this being one of the harshest environments on the planet, a large population of humans reside here and exploit surrounding natural resources to meet their needs. Keeping in view this exponentially growing population and its potential impacts on at-risk species like the snow leopard, we used geographic information systems (GIS) and remote sensing with the aim of identifying and quantifying LULCC across snow leopard range in Pakistan for the years 2000, 2010, and 2020. A massive expansion of 1804.13 km2 (163%) was observed in the built-up area during the study period. Similarly, an increase of 3177.74 km2 (153%) was observed in agricultural land. Barren mountain land increased by 12,368.39 km2 (28%) while forest land decreased by 2478.43 km2 (28%) and area with snow cover decreased by 14,799.83 km2 (52%). Drivers of these large-scale changes are likely the expanding human population and climate change. The overall quality and quantity of snow leopard habitat in Pakistan has drastically changed in the last 20 years and could be compromised. Swift and direct conservation actions to monitor LULCC are recommended to reduce any associated negative impacts on species preservation efforts. In the future, a series of extensive field surveys and studies should be carried out to monitor key drivers of LULCC across the observed area.

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Effects of Land Use and Land Cover Change on Tse Gavar Forest Reserve, Vandeikya Local Government Area, Benue State, Nigeria

East African Journal of Forestry and Agroforestry ◽

10.37284/eajfa.2.1.127 ◽

2020 ◽

Vol 2 (1) ◽

pp. 34-46

Author(s):

Emmanuel Tertsea Ikyaagba ◽

Joseph Asen Jande ◽

Mercy Kpadoo Abiem

Keyword(s):

Land Use ◽

Local Government ◽

Land Cover ◽

Land Cover Change ◽

Local Government Area ◽

Forest Area ◽

Community Forest ◽

Remotely Sensed Data ◽

Forest Reserve ◽

Bare Land

Forests are considered to be the very basis for human existence as they touch virtually every aspect of human endeavour. Despite the numerous benefits of forests, the world is experiencing unprecedented degradation of forest and its resources; this is mainly attributed to land use and land cover (LULC) change. Therefore, monitoring of these changes has become a necessity. Hence, the use of remotely sensed data in conjunction with GIS for land use and land cover analysis of Tse Gavar community forest in Vandeikya Local Government Area would definitely enhance the available data for sustainable management and promotion of community forest in the State. This study made use of mostly secondary data from pre-existing satellites imageries. The Landsat TM for 1986, Landsat ETM+ for 2001 and 2012 as well as OLI for 2018 images were sourced from the Earthexplorer platform from United States Geological Surveys (USGS), Global Land Cover Facility (GLCF) and GloVis. Images were subjected to various image processing techniques and supervised classification was carried out on the various images. The classification resulted in classes of farmland, other vegetation, forest area and bare land. The percentage of LULC in Tse Gavar Forest Reserve indicated that farmland increased from 5.78% in 1986 to 18.25% in 2018. Shrubland also increased from 3.06% in 1986 to 21.08% in 2018. Forested area decreased from 84.17% in 1986 to 59.38% in 2018. The magnitude of land use/land cover change within the 32 years period showed that 9.36 Ha of the forest area was lost to other forms of land use, the bare land area lost within the period was 0.09 Ha to other land uses. Farmland area increased by 4.32 Ha within the period, shrubland increased by 5078.88 km2. It was established that just like other protected areas, land use and land cover changes are going on in the Tse Gavar community forest reserve. Enrichment planting of the reserve was recommended.

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GIS and Remote Sensing for Malaria Risk Mapping, Ethiopia

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-155-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 155-161 ◽

Cited By ~ 8

Author(s):

A. Ahmed

Keyword(s):

At Risk ◽

Land Use ◽

Land Cover ◽

Malaria Risk ◽

Hazard Map ◽

Land Use Land Cover ◽

Risk Map ◽

Risk Area ◽

Element At Risk ◽

Very High

Integrating malaria data into a decision support system (DSS) using Geographic Information System (GIS) and remote sensing tool can provide timely information and decision makers get prepared to make better and faster decisions which can reduce the damage and minimize the loss caused. This paper attempted to asses and produce maps of malaria prone areas including the most important natural factors. The input data were based on the geospatial factors including climatic, social and Topographic aspects from secondary data. The objective of study is to prepare malaria hazard, Vulnerability, and element at risk map which give the final output, malaria risk map. The malaria hazard analyses were computed using multi criteria evaluation (MCE) using environmental factors such as topographic factors (elevation, slope and flow distance to stream), land use/ land cover and Breeding site were developed and weighted, then weighted overlay technique were computed in ArcGIS software to generate malaria hazard map. The resulting malaria hazard map depicts that 19.2 %, 30.8 %, 25.1 %, 16.6 % and 8.3 % of the District were subjected to very high, high, moderate, low and very low malaria hazard areas respectively. For vulnerability analysis, health station location and speed constant in Spatial Analyst module were used to generate factor maps. For element at risk, land use land cover map were used to generate element at risk map. Finally malaria risk map of the District was generated. Land use land cover map which is the element at risk in the District, the vulnerability map and the hazard map were overlaid. The final output based on this approach is a malaria risk map, which is classified into 5 classes which is Very High-risk area, High-risk area, Moderate risk area, Low risk area and Very low risk area. The risk map produced from the overlay analysis showed that 20.5 %, 11.6 %, 23.8 %, 34.1 % and 26.4 % of the District were subjected to very high, high, moderate, low and very low malaria risk respectively. This help to plan valuable measures to be taken in early warning, monitor, control and prevent malaria epidemics.

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