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Impacts of Mau Forest Catchment on the Great Rift Valley Lakes in Kenya

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Journal of Geoscience and Environment Protection 2016年第5期4卷 137-145页

作者： mark Kipkurwa boitt Department of Geomatic Engineering and GIS Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Remote sensing and GIS applications are being widely used for various projects relating to natural resource management. Forests are very important national assets for economic, environmental protection, social and cultural values and should be conserved in order to realize all these benefits. Kenya’s forests are rapidly declining due to pressure from increased population, technological innovation, urbanization human development and other land uses. Mau forest is one of the major forests in Kenya that is a catchment area for many Great Rift Valley lakes within the country and faces a lot of destruction. Continued destruction of the Mau forest will cause catastrophic environmental damage, resulting in massive food crises and compromising the livelihoods of millions of Kenyans, and the possible collapse of the tourism industry. The purpose of this research was to investigate the relationship between the increasing rate of deforestation and the reduction of the volumes of water in the neighboring lakes between the years 1989 to 2010. Satellite images from Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper (ETM+) were used for the detection of changes in the Mau forest and the dynamics of the neighboring water bodies that included lakes: Naivasha, Baringo, Nakuru, Elementaita and Bogoria. The research showed that from a period of 1989 to 2010 Mau forest has been decreasing due to deforestation and the water bodies have irregular dynamics in that, from 1989 to 2000, there was rise in the volume of water, this is attributed to the El Nino rains experienced in the country during the year 1997 and 1998. But between 2000 and 2010 the volume decreased as the forest is also decreasing. It is recommended that the government creates awareness to sensitize the public on the importance of such forests as catchment areas in Kenya.

关键词： Environmental Protection Natural Resource Management Land Use Forest Cover Water Reduction Normalized Difference Vegetation Index Classification

Geo-Hazard Susceptibility Assessment and Its Impacts on Livelihoods in Kerio Valley, Kenya

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International Journal of Geosciences 2022年第3期13卷 199-243页

作者： mark boitt John Gathoni Institute of Geomatics GIS and Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya Department of Research and Development GIS and Remote Sensing Section-Mapinfotek Nairobi Kenya

Geohazards are a recurrent issue in the Kerio River catchment of Kenya, which usually results in life and property loss. This research focuses on mapping geo-hazard risk zones of the region. The risk zones were developed from a combination of land use land cover maps, agroecological zones maps and soil erosion maps using the Analytical Hierarchy Process method of multi-criteria analysis. The final results depict the geohazard risk maps which show the susceptibility of different areas in the catchment (classified as risk zones) to hazards. The zones range from no risk zones to very high-risk zones. The results showed that the lowlands are most susceptible to hazards as they were classified as high-risk zones. These risk zone areas have impacts on the socio-economic development hence negatively impacting livelihoods in the area.

关键词： Kerio Valley Basin Land Use Land Cover Moisture Zones Agroecological Zones Soil Erosion RUSLE Model Geohazard Risk Zones Multivariate Clustering Analytical Hierarchy Process

Morphometric and Change Detection Analysis for Prioritization of Sub Basin Conservation, Case Study of Taita Hills

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International Journal of Geosciences 2020年第10期11卷 591-612页

作者： mark boitt Nyamwamu Bebeto Department of Geomatic Engineering and Geospatial Information Systems Jomo Kenyattta University of Agriculture and Technology Juja Kenya

The study is aimed at analyzing the risk of Taita Hills region of harmful runoff and soil erosion by employing morphometric analysis and change detection in a GIS environment to prioritize the Taita Hills in Taita Taveta County. The objective of the study was to characterize and give hierarchy in which the region should be conserved. The methodology adopted hydrological modeling, morphometric computation, Weighted Sum Analysis (WSA) and change detection. Hydrological modeling was vital in delineating the sub-watersheds and stream network. Morphometric computation and WSA was applicable in coming up with parameters and weighting the parameters for each sub-watershed’s prioritization. Change detection is related to how human activity is important for conservation as the effect of land forms and dimensions are compounded. Twenty-one fourth order streamed sub-watersheds were generated and prioritized using morphometry and change detection. Every sub-watershed is given a hierarchy based on the calculated compound parameter from the WSA equation developed and shows the risk of runoff and soil erosion. The morphometric prioritization shows 47% of the watersheds are in the high and very highly susceptible areas and there are two sub-watersheds with the highest land cover change. As well six sub-watersheds are risky with both land cover change and morphometry.

关键词： Watershed Prioritization Morphometric Analysis GIS Change Detection

Modeling the Spatial Distribution of Soil Heavy Metals Using Random Forest Model—A Case Study of Nairobi and Thirirka Rivers’ Confluence

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Journal of Geographic Information System 2020年第6期12卷 597-619页

作者： Evans Omondi mark boitt Department of Geomatic Engineering and Geospatial Information Systems Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Modeling the spatial distribution of soil heavy metals is important in determining the safety of contaminated soils for agricultural use. This study utilized 60 topsoil samples (0 - 30 cm), multispectral images (Sentinel-2), spectral indices, and ancillary data to model the spatial distribution of heavy metals in the soils along the Nairobi River. The model was generated using the Random Forest package in R. Using R2 to assess the prediction accuracy, the Random Forest model generated satisfactory results for all the elements. It also ranked the variables in order of their importance in the overall prediction. Spectral indices were the most important variables within the rankings. From the predicted topsoil maps, there were high concentrations of Cadmium on the easterly end of the river. Cadmium is an impurity in detergents, and this section is in close proximity to the Nairobi water sewerage plant, which could be a direct source of Cadmium. Some farms had Zinc levels which were above the World Health Organization recommended limit. The Random Forest model performed satisfactorily. However, the predictions can be improved further if the spatial resolutions of the various variables are increased and through the addition of more predictor variables.

关键词： Random Forest Sentinel 2 Heavy Metals Spectral Indices Spatial Modeling

Application of Remote Sensing in Coral Reef Mapping and Assessment of Climatic and Environmental Conditions

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Journal of Geoscience and Environment Protection 2024年第11期12卷 284-306页

作者： Amina Said mark boitt Michael Hahn Faculty of Geomatics Computer Science and Mathematics Hochschule fuer Technik Stuttgart Stuttgart Germany Institute of Geomatics GIS and Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya

Coral reefs have tremendous benefits to both humans and marine biodiversity but are globally endangered. Traditionally, data collection of coral reefs was fieldwork based, which is time-consuming, costly and lacking in full coverage. This study shows that optical imageries can be utilised to map coral reefs, by fusing visible bands and depth invariant index (DII) to classify benthic features. Overall accuracy of at least 68 percent is achieved. However, to overcome the challenge of cloud cover, which is common in coastal areas, microwave imagery is used to map the emergent coral reefs. Again, remote sensing proves to be reliable in estimation of sea surface temperature (SST) and extraction of water quality parameters through Case-2 Region CoastColour (C2RCC) processor. Thereafter, regression analysis is performed to evaluate the correlation of SST and water quality. It is concluded that higher spatial resolution can improve coral mapping and that there is a need for more research on correlation to its environment.

关键词： Coral Reef DII SST C2RCC Water Quality

Assessment of Groundwater Potential and Prediction of the Potential Trend up to 2042 Using GIS-Based Model and Remote Sensing Techniques for Kiambu County

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International Journal of Geosciences 2023年第10期14卷 1036-1063页

作者： mark boitt Patricia Khayasi Catherine Wambua Institute of Geomatics GIS and Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya Department of Research and Development GIS and Remote Sensing Section-Mapinfotek Nairobi Kenya

Groundwater is one of the important necessary renewable resources of the world. It forms part of the natural water cycle that is present in the underground strata with the principal sources being precipitation and streamflow. Traditionally, information on the potential occurrence of groundwater was obtained using techniques such as drilling, geophysical, geological, hydro-geological and geo-electrical which are time-consuming, costly and lacked full coverage. This study shows that remote sensing and GIS techniques can be utilized to map groundwater potential using a GIS-based model, the Modified DRASTIC Model, which incorporates factors that influence groundwater occurrence. These factors are the surface attributes that infer groundwater potentials and they include geology, soil texture, land use, lithology, landforms, slope steepness, lineaments and drainage systems. A prediction of the groundwater prediction was done by utilizing the MOLUSCE tool, a plugin in Qgis that utilizes ANN, multicriteria evaluation, weights of evidence and LRs algorithms in predicting land changes. The kappa value for prediction was 0.83. The results showed areas in the Southwest region had low to very low potential and the central region had high to very high potential for all the years and there were little changes between the years. The prediction showed that by 2042, the eastern region of Kiambu County will have a decline in groundwater potential.

关键词： Groundwater DRASTIC MOLUSCE Remote Sensing ANN LR

Mapping of Freshwater Snails’ Habitat—A Source of Transmitting Bilharzia in Mwea Sub-County, Kenya

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Journal of Geoscience and Environment Protection 2021年第10期9卷 130-150页

作者： mark Kipkurwa boitt Mungai Kaara Suleiman Institute of Geomatics GIS and Remote Sensing Dedan Kimathi University of Technology Nyeri Kenya Department of Geomatic Engineering and GIS Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Bilharzia is vector-borne disease carried by a parasite that is hosted by fresh water snails. The distribution of the disease is concurrent with the existence of the freshwater snails and is dependent on certain suitable environmental conditions. It is difficult to identify the specific habitats of the snails as they are often inaccessible on the ground, the snails also migrate by means of flowing water, making it difficult to keep a track of the freshwater snails’ habitat. This paper aimed at using GIS, Remote Sensing and Species Distribution Modelling techniques to model the suitable habitats for the freshwater snails and to prove that the snails migrate when there are sudden changes in water levels whilst showing the population at risk of bilharzia. The SDM used is the Maximum Entropy (MAXENT) for its ability to make right predictions even with small presence sites. The AUC value of the model was 0.951. The research results showed that the environmental variables;brightness Index, elevation, temperatures were negatively correlated with the snails’ presence while the wetness index, MSAVI, greenness index and soil pH were positively correlated. The snails are observed to favor clay soils of the montmorillonite type and the crop-lands land cover. Areas consistently submerged by water especially after flooding are shown to be the most suitable areas where snails migrate by means of river or canal water. The research proves that Mwea is not the source habitat of the freshwater snails. The neighboring sub-counties within Kirinyaga County should be investigated using such models as a likely source-habitat of the freshwater snails. Destroying the source habitats will lead to complete eradication of the freshwater snails within Mwe

关键词： Area Under Operating Curve (AUC) Species Distribution Models Maximum Entropy (MaxEnt) Land Surface Temperatures Geographic Information Systems Remote Sensing Land Use Land Cover

Identification and Mapping of Essential Fish Habitats Using Remote Sensing and GIS on Lake Victoria, Kenya

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Journal of Geoscience and Environment Protection 2021年第10期9卷 91-109页

作者： mark Kipkurwa boitt Erick Otieno Aete Institute of Geomatics GIS and Remote Sensing (IGGReS) Dedan Kimathi University of Technology Nyeri Kenya Department of Geomatic Engineering and GIS (GEGIS) Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Fisheries in Lake Victoria have been threatened by declining fish stocks and diversity, environmental degradation due to increased input of pollutants, industrial and municipal waste, overfishing and use of unapproved fishing methods, infestation by aquatic weeds especially water hyacinth, de-oxygenation and a reduction in the quantity and quality of water. Remote sensing and GIS are essential tools in detection of fishing grounds which is important in providing fish sustainability for human beings and allows fishing grounds detection at minimal cost and optimizes effort. This research tends to identify the most favorable both environmentally and ecologically satisfactory factors which favor fish breeding and growth. The main aim of the study was to identify habitat variables that promote fish breeding and growth to maturity including the extraction of environmental variables from Landsat 8 images for the study period and using suitability index derived from fishery data. The study concentrated on establishing suitability ratings in different parts of Lake Victoria using lake surface temperature and chlorophyll-a levels. The study was conducted for months;January, May and December 2019 on Lake Victoria (limited by the availability of recent data). The factors were analysed and the favorable regions mapped satisfying the conditions for fish breeding. The output obtained illustrated the availability of suitable and habitable zones within the lake using satellite imagery and the suitability index. The fish catch data and satellite derived variables were used to determine habitat suitability indices for fish during January, May and December 2019. More than 90% of the total catch was found to come from the areas with sea surface temperature of 23.0˚C - 28.3˚C and chlorophyll-a concentration between 0.72 -

关键词： Catch Per Unit Effort Potential Fishing Zones Geographic Information Systems High Resolution Satellite Image Habitat Suitability Index

Geospatial Assessment for Sustainable Management of Mangroves in Kilifi Creek, Kenya

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Journal of Geoscience and Environment Protection 2019年第7期7卷 1-13页

作者： mark Kipkurwa boitt Amina Omar Said Department of Geomatic Engineering and GIS Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya

Mangroves are salt-tolerable trees that grow on zones parallel to the coastline along the creeks. They follow the mud flat accretions which are unvegetated areas consisting of sand or gravel that are either exposed or flooded by tides. They provide 70% of the wood requirement along the Kenyan Coast. Currently, there are no harvest plans of the mangroves and there is selective removal of suitable poles and most of the quality poles have been wiped out. This not only leaves the inferior species unsuitable for the market but also affects the quality of the forest. Moreover, areas that are suitable for mangroves growth have been occupied by human settlement and infrastructure, hence, there is a need of sustainable use of the mangroves so as to protect them from degradating and eventually extinction. To achieve this, geospatial techniques need to be employed in order to determine the spatial extent of the vegetation and devise methods and plans of managing them. The Kilifi Mangrove Forest creek is home to major six species: Avicennia marina, Ceriops tagal, Sonneratia alba J., Rhizophora mucronata, Lumnitzera racemosa and Bruguiera gymnorrhiza. This study showed that the most dominant species in the forest is Avicenna Marina which had a percentage stand of 25.6%. The less dominant species Lumnitzera racemosa and Heritiera littoralis had a stand of 0.10% which were restricted for harvesting in the analysis, they need to be protected so as to prevent its extinction in the forest which will affect the biodiversity and richness of the forest. Density and heights of the mangroves were considered so as to decide on which areas to do reforestation in order to protect the forest and help in preventing soil erosion. The final suitable area for harvesting after carrying out conditional and majority filter was 394 acres which are 9% of the total forest area. The total area most suitable for reforestation is 1151 acres which are 27% of the total Kilifi Mangrove Forest. A recommendati

关键词： Environmental Protection Natural Resource Management Mangroves Suitability Analysis