Anthropogenic Impacts on Land Use and Land Cover Change in Ombeyi wetland, Kisumu County, Kenya

Osoro, Odhiambo Nicodemus; Obade, Paul; Gathuru, Gathuru

doi:10.5296/ijrd.v6i1.15292

Cited by 6 publications

(3 citation statements)

References 33 publications

(43 reference statements)

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“…Using Landsat imageries, a combination of NDVI and NDWI indices were applied in land cover change detection of Tanguar Haor wetland, a Ramsar site in Bangladesh, in which it was established that about 40% of wetland cover had been converted to residential and agricultural land over 30 years period . In Kenya, remote sensing techniques have been used to assess land use/cover change detection in Rumuruti (Mwita, 2016), Nyando Wetland (Okotto-Okotto et al, 2018, and Ombeyi Wetland (Nicodemus et al, 2019) among other large wetlands. These studies cumulatively indicated that the landscape of Kenya's wetlands is actively transforming due to human-induced factors.…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Changes of Limoto Wetland Land Use/Cover Before, During and After Restoration Activities in Eastern Uganda

Ochoko,

Barasa,

Luyiga

et al. 2023

AJES

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Purpose: Limoto Wetland is an arm of the Mpologoma wetland system in the Kyoga basin and is a vital ecosystem that supports rural livelihoods through the provision of various ecological goods and services. However, this ecosystem has been undergoing rapid degradation arising from competing land uses particularly paddy rice growing. In turn, this led to reduced capacity of the wetland to provide ecosystem services, thereby reducing the resilience of both the ecosystem and the livelihoods of adjacent communities. Interventions through a restoration program that introduced alternative livelihood options were instituted. It’s important to document these changes to obtain insights that can aid decision-making for effective restoration and conservation. This study, therefore, sought to examine the spatial-temporal changes in Limoto wetland land use/cover transitions for the years 2015, 2020, and 2022. Methodology: To quantify the wetland changes, remotely sensed imageries for 2015, 2020, and 2022 were utilized in classifying land use and land cover dynamics on Limoto Wetland through the Maximum Likelihood algorithm. A total of 500 points were collected from different land use/cover types and used as reference points to develop the image error matrices. Overall accuracy, producer’s and user’s accuracies as well as Kappa statistics were generated from the error matrices. A Kappa test was carried out to measure the extent of classification accuracy; the Kappa coefficient, K, being a coefficient of agreement. It reflects the difference between the actual agreement of classification with reference data and the agreement expected by chance. Findings: Results generally showed that five years after the restoration program (2020), Limoto wetlands regained over 50% of previously converted wetlands to farming. Papyrus coverage also more than doubled from 3.4% to 11.35% of the total wetland coverage. Farms degraded over the past years (1986-2019). However, in 2022, wetland coverage declined drastically as farming took up more than half of the coverage (55%) land, and built-up areas also increased. These changes between 2015-2020 were majorly driven by the introduction of alternative livelihood options which vacated communities from the wetland. Recommendation: The changes after 2020 were due to the unsustainability of the livelihood options and the effects of the Covid-19 lockdown which rendered only farming as the socio-economic activity, coupled with movement restrictions that curtailed monitoring and control of activities in wetlands by enforcers. The study recommends community-tailored, tenable, and sustainable alternative livelihood options to influence community-led wetland restoration and conservation to curb the continuous loss of this wetland.

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Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Changes of Limoto Wetland Land Use/Cover Before, During and After Restoration Activities in Eastern Uganda

Ochoko,

Barasa,

Luyiga

et al. 2023

AJES

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“…According to their findings, alterations in vegetation and water body extents had exacerbated the Isimangaliso Wetland Park's dramatic decrease in recent years. In Kenya, remote sensing techniques have been used to assess land use and land cover change detection in Rumuruti [14], Nyando Wetland [15], Tana River Basin [16], and Ombeyi Wetland [17] among other large wetlands. These studies cumulatively indicated that the landscape of Kenya's wetlands is actively transforming due to human-induced factors.…”

Section: Introductionmentioning

confidence: 99%

Land Use Land Cover Changes and Encroachment Issues in Kapkatet Wetland, Kenya

Kibet¹,

Olatubara²,

Ikporukpo³

et al. 2021

OJE

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Kapkatet Wetland is a vital ecosystem in Kenya that supports rural livelihoods through the provision of various ecological goods and services. However, this ecosystem has been undergoing rapid degradation arising from competing land uses. It's important to document these changes to obtain insights that can aid decision-making for effective restoration and conservation. This study, therefore, sought to assess the extent and patterns of land use and land cover changes in Kapkatet Wetland between 1986 and 2019, and their driving forces. The study followed a mixed-method research approach involving a combination of remote sensing and descriptive surveys. To quantify the wetland changes, remotely sensed imageries for 1986, 2000, and 2019 were utilized in classifying land use and land cover maps through the Maximum Likelihood algorithm. Household questionnaires and focus group discussions were used to obtain information about peoples' perceptions of the driving forces of landscape change within the wetland. Results generally showed that Kapkatet wetland declined by 24.77% over the past years . Wetland vegetation declined drastically as open grounds increased while tree cover and disturbed reeds showed a fluctuating trend. These changes were majorly driven by land conversion activities within the wetland. The study recommends a community-based enforcement approach to existing laws and policies by both National and Local governments to curb the continuous loss of this wetland.

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“…These images were processed using the producer company's Impact Observatory Deep-learning AI, trained using human-labeled image pixels developed by the United States National Geographic Society (Kontgis, 2022). As for the time frame the maps would be taken from, it would be annually for two (2) years before and after the implementation of the taxation policy of interest (Osoro, 2020;Redo et al, 2012). This means that the images that are to be considered in the study are within the years 2018 to 2021.…”

Section: Data Collection and Preprocessingmentioning

confidence: 99%

The relationship between the land and buildings Tax Act, B.E. 2562 (A.D. 2019), and the land use and land cover (LULC) of Bangkok, Thailand

Orina

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The Land and Buildings Tax Act, B.E. 2562 (A.D. 2019), was enacted in Thailand with the aim of wealth distribution, revenue increase, and discouraging unproductive land use. However, since its implementation in 2020, in Bangkok, a notable increase in land use and land cover (LULC) changes, specifically vacant lands being converted to agricultural lands, has been observed. These changes are hypothesized to be related to tax avoidance activities. This study aims to investigate the phenomenon of vacant-to-agricultural land conversions in Bangkok and employ spatial analysis techniques to identify and locate these LULC changes. By employing a statistical t-test and conducting key informant interviews, this research shows that the implementation of the new property tax policy is likely contributing to these land use changes. Additionally, remote sensing and geospatial analyses are performed on ESRI LULC maps and Google platform images from 2018, 2019, 2020, and 2021, reveal that: (1) the majority of LULC changes and suspected tax avoidance activities occur in the urban fringes, (2) there is a clustering of suspected tax avoidance activities, particularly in the eastern fringe of the city, while the urban core exhibits minimal such activities, and (3) the clusters of high or low suspected tax avoidance activities demonstrate interrelatedness. The employed research techniques and the results have implications for the administration of the new property tax policy, as well as for wealth redistribution, urban service provision, and peri-urban dynamics in the city. In addition, the study suggests the improvement of property tax management by providing specific guidelines accompanying the law and fostering the co-creation of urban services and infrastructure.

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Anthropogenic Impacts on Land Use and Land Cover Change in Ombeyi wetland, Kisumu County, Kenya

Cited by 6 publications

References 33 publications

Spatial-Temporal Changes of Limoto Wetland Land Use/Cover Before, During and After Restoration Activities in Eastern Uganda

Spatial-Temporal Changes of Limoto Wetland Land Use/Cover Before, During and After Restoration Activities in Eastern Uganda

Land Use Land Cover Changes and Encroachment Issues in Kapkatet Wetland, Kenya

The relationship between the land and buildings Tax Act, B.E. 2562 (A.D. 2019), and the land use and land cover (LULC) of Bangkok, Thailand

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