Characterizing landscape fragmentation of Koitobos river sub-basin, Trans-Nzoia, Kenya

Murunga, Kennedy Wekesa; Nyadawa, Maurice; Sang, Joseph; Cheruiyot, Charles

doi:10.1016/j.heliyon.2024.e29237

Cited by 2 publications

(1 citation statement)

References 77 publications

(133 reference statements)

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“…Zhang et al, found that the patch density and shape complexity, landscape diversity, and fragmentation of the landscape continued to increase while landscape connectivity declined in the process of urbanization [31]. Kennedy et al extracted the landscape index by Fragstats 4.2 and found that unprecedented landscape fragmentation occurred in Koitobos river sub-basin, Trans-Nzoia, Kenya [33]. Traditional landscape metrics, however, are often constrained to singular indices that address specific landscape issues in isolation, with prevailing research predominantly focusing on the sequential analysis of individual characteristics before qualitatively integrating these observations to depict the overall landscape [29,34,35].…”

Section: Introductionmentioning

confidence: 99%

Analyzing Spatial–Temporal Characteristics and Influencing Mechanisms of Landscape Changes in the Context of Comprehensive Urban Expansion Using Remote Sensing

Li,

Zhen,

Luo

et al. 2024

Remote Sensing

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The phenomena of global climate change and comprehensive urban expansion have precipitated significant and unprecedented transformations in landscape patterns. To enhance the assessment of these spatio−temporal changes and their driving forces at a regional level, we developed a comprehensive landscape index (CLI) to quantify these patterns and conducted a detailed analysis of the spatio−temporal variations in Minnesota over the last two decades. Our analysis of the CLI was conducted by examining both its quantitative relationships and spatial distribution patterns. The findings indicate a consistent increase in Minnesota’s CLI over this period, marked by an escalation in landscape fragmentation and diversity, alongside a decline in landscape connectivity. Temporally, the CLI experienced a notable shift in 2010. Spatially, the clustering characteristics of landscape patterns have largely remained stable. Our analysis reveals that the CLI is most sensitive to total population (POP) and gross domestic product (GDP) factors, underscoring the significant impact of human activity on landscape patterns. Notably, the explanatory capacity of interactions between factors is substantially greater than that of individual factors, with the GDP and vegetation structure (VS) interaction demonstrating the greatest influence on the spatial distribution of landscape patterns. This highlights the critical role of the interplay between human socio−economic activity and vegetation coverage in shaping landscape configurations.

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Section: Introductionmentioning

confidence: 99%

Analyzing Spatial–Temporal Characteristics and Influencing Mechanisms of Landscape Changes in the Context of Comprehensive Urban Expansion Using Remote Sensing

Li,

Zhen,

Luo

et al. 2024

Remote Sensing

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Monitoring urban growth and landscape fragmentation in Kaduna, Nigeria, using remote sensing approach

Musa,

Abubakar

2024

J. Degrade. Min. Land Manage.

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This study assessed urban growth in Kaduna using remote sensing indices, landscape metrics, and Landsat images (2003, 2013, and 2023). Land use/land cover was carried out using the decision tree algorithm, while the transition matrix was computed using ArcGIS 10.8. Landscape fragmentation was assessed using Fragstat 4.3. The results revealed that between 2003 and 2023, bare land, built-up areas, and water bodies increased by 596 km2, 121.04 km2, and 0.22 km2, respectively, while cultivated land and tree cover decreased by 525.54 km2 and 191.91 km2, respectively. For the rate of change, bare lands, built-up areas, and water bodies increased by 29.81 km2, 6.05 km2, and 0.01 km2 annually, respectively, while cultivated lands and water bodies decreased by 26.28 km2 and 9.60 km2, respectively. For the land-use transition, 112.71 km2 of the built-up areas remained persistent. Cultivated lands, tree cover, and water bodies transitioned to built-up areas, losing 85.43 km2, 13.91 km2, and 0.91 km2, respectively. Landscape fragmentation analysis revealed that the number of patches increased from 405 in 2003 to 614 in 2023. Patch density, largest patch index, total edge, edge density, area-weighted mean shape index, and fractal dimension index decreased between 2003 and 2013 but increased between 2013 and 2023, indicating urban sprawl. However, the area-weighted mean contiguity index consistently increased between 2003 and 2023. The study concluded that urbanization is the leading driver of landscape fragmentation. This study recommends that development should be controlled to reduce encroachment on agricultural lands and habitats, thereby reducing landscape fragmentation and land degradation.

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Characterizing landscape fragmentation of Koitobos river sub-basin, Trans-Nzoia, Kenya

Cited by 2 publications

References 77 publications

Analyzing Spatial–Temporal Characteristics and Influencing Mechanisms of Landscape Changes in the Context of Comprehensive Urban Expansion Using Remote Sensing

Analyzing Spatial–Temporal Characteristics and Influencing Mechanisms of Landscape Changes in the Context of Comprehensive Urban Expansion Using Remote Sensing

Monitoring urban growth and landscape fragmentation in Kaduna, Nigeria, using remote sensing approach

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