Predictive modeling of desertification in Jibia Local Government Area of Katsina State, Nigeria

Falaki, Mohammad Ahmad; Ahmed, Hadiza Tanimu; Akpu, Benedine

doi:10.1016/j.ejrs.2020.04.001

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…A comprehensive survey is available on the existing free Geographic Information System (GIS) [21,22], recent trends in the development of cartography [23] and new directions and perspectives in GIS [24], while this section covers the most relevant GIS applications for environmental mapping. The efficient solutions for satellite image processing are presented by Earth Resources Data Analysis System (ERDAS) Imagine with applications of environmental monitoring [25] with many existing cases due to the functionality and availability of diverse modules aimed at raster data processing. The Global Mapper GIS, developed by the USGS, includes a variety of tools including Light Detection and Ranging (LiDAR) handling, 3D rendering, and watershed delineation to process geological and environmental data.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Monitoring Seasonal Fluctuations in Saline Lakes of Tunisia Using Earth Observation Data Processed by GRASS GIS

Lemenkova

2023

Land

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This study documents the changes in the Land Use/Land Cover (LULC) in the region of saline lakes in north Tunisia, Sahara Desert. Remote sensing data are a valuable data source in monitoring LULC in lacustrine landscapes, because variations in the extent of lakes are visible from space and can be detected on the images. In this study, changes in LULC of the salt pans of Tunisia were evaluated using a series of 12 Landsat 8-9 Operational Land Imager (OLI) and Thermal Infrared (TIRS) images. The images were processed with the Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) software. The study area included four salt lakes of north Tunisia in the two regions of the Gulf of Hammamet and Gulf of Gabès: (1) Sebkhet de Sidi el Hani (Sousse Governorate), (2) Sebkha de Moknine (Mahdia Governorate), (3) Sebkhet El Rharra and (4) Sebkhet en Noual (Sfax). A quantitative estimate of the areal extent analysed in this study is 182 km × 185 km for each Landsat scene in two study areas: Gulf of Hammamet and Gulf of Gabès. The images were analysed for the period 2017–2023 on months February, April and July for each year. Spatio-temporal changes in LULC and their climate–environmental driving forces were analysed. The results were interpreted and the highest changes were detected by accuracy assessment, computing the class separability matrices, evaluating the means and standard deviation for each band and plotting the reject probability maps. Multi-temporal changes in LULC classes are reported for each image. The results demonstrated that changes in salt lakes were determined for winter/spring/summer months as detected changes in water/land/salt/sand/vegetation areas. The accuracy of the classified images was evaluated using pixel rejection probability values, which were filtered out using the ‘r.mapcalc’ module of GRASS GIS. The confidence levels were computed and visualised with a series of maps along with the error matrix and measured convergence level of classified pixels. This paper contributes to the environmental monitoring of Tunisian landscapes and analysis of climate effects on LULC in landscapes of north Africa.

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Section: Introduction 1backgroundmentioning

confidence: 99%

Monitoring Seasonal Fluctuations in Saline Lakes of Tunisia Using Earth Observation Data Processed by GRASS GIS

Lemenkova

2023

Land

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“…Several studies have carried out LULC classification extensively either as a standalone study or as a method in a study (Bawa et al, 2022;Gondwe et al, 2021;Falaki et al, 2020;Spruce et al, 2020;Kidane et al, 2019;Liping et al, 2018;Mienmany, 2018;Rwanga and Ndambuki, 2017;Hassan et al, 2016;Goodin et al, 2015). However, in the LULC classification, the LU class has frequently been generalized as built-up area, without a proper distinction of its constituents (e.g.…”

Section: Introductionmentioning

confidence: 99%

Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map

Aliyu

Akomolafe

Bala

et al. 2023

International Journal of Environment and Geoinformatics

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There are several remotely sensed images of varied resolutions available. As a result, several classification techniques exist, which are roughly classified as pixel-based and object-based classification methods. Based on the foregoing, this study provided an integrated method of deriving land use from a coarse satellite image. Location coordinates of the land uses were acquired with a handheld Global Positioning System (GPS) instrument as primary data. The study classified the image quantitatively (pixel-based) into built-up, water, riparian, cultivated, and uncultivated land cover classes with no mixed pixels, and then qualitatively into educational, commercial, health, residential, and security land use classes that were conflicting due to spectral similarity. The total accuracy and kappa coefficient of the pixel-based land cover classification were 92.5% and 94% respectively. The results showed that residential land use occupied an area of 5500.01ha, followed by educational (2800.69ha); security (411.27ha); health (133.88ha); and commercial (109.01ha) respectively. The integrated method produces a crisp-appearance like the object-based image classification method. It eliminates the "salt and pepper" appearance that a traditional pixel-based classification would have. The output can be a vector or raster model depending on the purpose for which it is created.

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“…Problems related to climate change have been aggravated in the last two decades due to global climate change and desertification processes affects this region similarly to other African countries [11][12][13]. In the north of Nigeria, desertification and land resource degradation are attributed to climatic variations, as well as to population increase that causes mismanagement of the land [14][15][16]. The scale of the vegetation cover changes indicated by research results obtained particularly through remote sensing requires actions aimed at mitigating and preventing further losses in the environment [17,18].…”

Section: Introductionmentioning

confidence: 99%

Afforestation of Transformed Savanna and Resulting Land Cover Change: A Case Study of Zaria (Nigeria)

2022

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This paper presents the effects of actions aiming at tree planting, and thus protection of the land belonging to Ahmadu Bello University (ABU) in Zaria (Nigeria) from erosion. This area is located within the northern limits of the Guinea savanna belt, which has been considerably transformed primarily for agricultural purposes. For years this area has been subjected to the destructive surface and gully erosion processes, which were documented both by field work and the analysis of high-resolution images presented by Google Earth. Land erosion leads to the silting of an impounding reservoir (Kubanni)—the primary water source for the university campus and the basis for its existence. Since 2000, the university has been actively involved in tree-planting efforts in the campus vicinity, executed mainly through the establishment of small plantations ranging in area from approximately 1 ha to 56 ha. Today, these measures have brought tangible effects such as increment of tree-planted expanses, as evidenced in the multitemporal analysis of the Landsat 7 ETM+ and Landsat 8 OLI satellite images. The increasing planted area protects both the soil and the reservoir. A marked stand increment (almost doubled) has been recorded, which is evident from the satellite imageries, and is presented on the land-use map produced with GIS technique for this project.

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Predictive modeling of desertification in Jibia Local Government Area of Katsina State, Nigeria

Cited by 4 publications

References 3 publications

Monitoring Seasonal Fluctuations in Saline Lakes of Tunisia Using Earth Observation Data Processed by GRASS GIS

Monitoring Seasonal Fluctuations in Saline Lakes of Tunisia Using Earth Observation Data Processed by GRASS GIS

Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map

Afforestation of Transformed Savanna and Resulting Land Cover Change: A Case Study of Zaria (Nigeria)

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