Eritrea faces significant environmental and agricultural challenges due to human activities, rugged terrain, and fluctuating climates like recurrent droughts and erratic rainfall. Desertification, deforestation, and s...Eritrea faces significant environmental and agricultural challenges due to human activities, rugged terrain, and fluctuating climates like recurrent droughts and erratic rainfall. Desertification, deforestation, and soil erosion are major concerns affecting soil quality, water resources, and vegetation, especially in areas like the Alla catchment. Recent assessments reveal declining vegetation and precipitation levels over four decades, alongside rising temperatures, linked to increased desertification and land degradation driven by climate variations and prolonged droughts. The urgent need for sustainable land management practices is explained by reduced productivity, biodiversity, and ecosystem health. This study focused on modelling land degradation in Eritrea’s Alla catchment using advanced geospatial techniques. Vegetation indices and soil erosion models were used to evaluate critical factors such as rainfall Erosivity, soil erodibility, slope characteristics, and land cover management. The resulting model highlighted varying levels of susceptibility to land degradation, highlighting widespread vulnerability characterized by high and very high susceptibility hotspots. Areas with minimal degradation were found in the northern vegetation-covered regions. Soil loss in the catchment is primarily influenced by inadequate land cover, steep slopes, soil erosion susceptibility, erosive rainfall patterns, and insufficient support practices. The study underscores the urgency of addressing deforestation and unsustainable agricultural practices to mitigate soil erosion. Recommendations include enhancing community capacity for effective land management, promoting climate adaptation strategies, and aligning national efforts with the global Sustainable Development Goals to achieve Land Degradation Neutrality.展开更多
Changes in climate will affect conditions for species growth and distribution, particularly along elevation gradients, where environmental conditions change abruptly. Agroforestry tree (AGT) species on the densely inh...Changes in climate will affect conditions for species growth and distribution, particularly along elevation gradients, where environmental conditions change abruptly. Agroforestry tree (AGT) species on the densely inhabited slopes of Mount Kilimanjaro and Taita Hills will change their elevation distribution, and associated carbon storage. This study assesses the potential impacts of climate change by modelling species distribution using maximum entropy. We focus on important agroforestry tree species (Albiziagummifera, Mangiferaindica and Perseaamericana) and projected climate variables under IPCC-AR5 RCP 4.5 and 8.5 for the mid-century (2055) and late century (2085). Results show differential response: downward migration for M. indica on the slopes of Mount Kilimanjaro is contrasted with Avocado that will shift upslope on the Taita Hills under RCP 8.5. Perseaamericana will lose suitable habitat on Kilimanjaro whereas M. indica will expand habitat suitability. Potential increase in suitable areas for agroforestry species in Taita Hills will occur except for Albizia and Mango which will potentially decrease in suitable areas under RCP 4.5 for period 2055. Shift in minimum elevation range will affect species suitable areas ultimately influencing AGC on the slopes of Mount Kilimanjaro and Taita Hills. The AGC for agroforestry species will decrease on the slopes of Mount Kilimanjaro but AGC for Mango will increase under RCP 8.5 for period 2055 and 2085. In Taita Hills, AGC will remain relatively stable for A. gummifera and P. americana under RCP 8.5 for period 2055 and 2085 but decrease in AGC will occur for M. indica under projected climate change. Climate change will affect AGT species and the amount of carbon stored differently between the sites. Such insight can inform AGT species choice, and conservation and support development by improving carbon sequestration on sites and reliable food production.展开更多
A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objective...A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.展开更多
Green gram is considered as one of the legumes suitable for cultivation in the Arid and Semi-Arid Lands (ASALs) of Kenya. However, climate change may alter the areas suitable for green gram production. This study soug...Green gram is considered as one of the legumes suitable for cultivation in the Arid and Semi-Arid Lands (ASALs) of Kenya. However, climate change may alter the areas suitable for green gram production. This study sought to model green gram suitability in Kenya under present and future conditions using bias-corrected RCA4 models data. The datasets used were: maps of soil parameters extracted from Kenya Soil Survey map;present and future rainfall and temperature data from an ensemble of nine models from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM);and altitude from the Digital elevation model (DEM) of the USGS. The maps were first reclassified into four classes of suitability as Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (N). The classes represent the different levels of influence of a factor on the growth and yield of green grams. The reclassified maps were then assigned a weight generated using the Analytical Hierarchy Process (AHP). A weighted overlay of climate characteristics (past and future rainfall and temperature), soil properties (depth, pH, texture, CEC, and drainage) and altitude found most of Kenya as moderately suitable for green gram production during the March to May (MAM) and October to December (OND) seasons under the baseline, RCP 4.5 and RCP 8.5 scenarios with highly suitable areas being found in Counties like Kitui, Makueni, and West Pokot among others. During the MAM season, the area currently highly suitable for green gram production (67,842.62 km<sup>2</sup>) will increase slightly to 68,600.4 km<sup>2</sup> (1.1%) during the RCP 4.5 and reduce to 61,307.8 km<sup>2</sup> (<span style="white-space:nowrap;">−</span>9.6%) under the RCP 8.5 scenario. During the OND season, the area currently highly suitable (49,633.4 km<sup>2</sup>) will increase under both RCP 4.5 (22.2%) and RCP 8.5 (58.5%) scenarios. This increase is as a result of favourable rainfall and temperature conditions in the future.展开更多
Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We as...Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites and against environmental variables. One hectare sampling plots were randomly distributed along elevational gradients stratified by cropland type;AGC was derived from all trees with diameter ≥ 10 cm at breast height in each plot. Predictor variables were physical and edaphic variables and human population. A generalized linear model was used for predicting AGC with AIC used for ranking models. AGC was spatially upscaled in 2 km buffer and visually compared. Kilimanjaro has higher AGC in cropped and agroforestry areas than the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry in Kilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Persea americana, and in the Taita Hills Grevillea robusta and Mangifera indica. Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 = 0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the top multivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation, slope and population (R2 = 0.89, p = 0.00). Despite of the difference in land management history of Mount Kilimanjaro and the Taita Hills, mean of AGC in croplands does not differ significantly. Difference occurs on variation of AGC, type of trees contributing AGC, and environmental variables that explain AGC distribution. The research results provide reference for management of carbon sequestration on inhabited montane areas.展开更多
Lake Nakuru is one of Kenya’s Rift Valley Lakes and lies within the Lake Nakuru National Park. As a key habitat for flamingos and other water birds, the lake is a major tourist attraction. Lake Nakuru National Park c...Lake Nakuru is one of Kenya’s Rift Valley Lakes and lies within the Lake Nakuru National Park. As a key habitat for flamingos and other water birds, the lake is a major tourist attraction. Lake Nakuru National Park covers an area of approximately 188 km<sup>2</sup> and is fully enclosed with a perimeter fence. The park is home to about 56 different species of mammals, 550 plant species, and 450 species of terrestrial birds as well as flamingos and other water birds. In the last decade, the lake has experienced continuous flooding, increasing the lake area from 35 km<sup>2</sup> in 2009 to 54 km<sup>2</sup> in 2018. This impacted negatively on the available space for wildlife. The main objective of this study was to investigate the effects of this flooding on the wildlife and their habitats in Lake Nakuru National Park. The methodology used Land use Land cover (LULC) interpretation of Landsat Satellite imagery from two epochs, 2009 and 2018, and integration of the results with relevant wildlife data provided by Kenya Wildlife Service. The results, which include LULC change maps and wildlife distribution maps, have shown that the flooding impacted negatively on the available space for wildlife. In addition, the floods also compromised key park infrastructures such as roads and the main gate making it very difficult to maintain the normal park operations, and hence adversely affecting the local and national economies. The information provided by this study is useful for planning mitigation measures in respect of the current and potential future flooding.展开更多
According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food con...According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food consumed there;their farming activities are therefore critical to the economies of their countries and to the global food security. However, these farmers face the challenges of limited access to credit, often due to the fact that many of them farm on unregistered land that cannot be offered as collateral to lending institutions;but even when they are on registered land, the fear of losing such land that they should default on loan payments often prevents them from applying for farm credit;and even if they apply, they still get disadvantaged by low credit scores (a measure of creditworthiness). The result is that they are often unable to use optimal farm inputs such as fertilizer and good seeds among others. This depresses their yields, and in turn, has negative implications for the food security in their communities, and in the world, hence making it difficult for the UN to achieve its sustainable goal no.2 (no hunger). This study aimed to demonstrate how geospatial technology can be used to leverage farm credit scoring for the benefit of smallholder farmers. A survey was conducted within the study area to identify the smallholder farms and farmers. A sample of surveyed farmers was then subjected to credit scoring by machine learning. In the first instance, the traditional financial data approach was used and the results showed that over 40% of the farmers could not qualify for credit. When non-financial geospatial data, i.e. Normalized Difference Vegetation Index (NDVI) was introduced into the scoring model, the number of farmers not qualifying for credit reduced significantly to 24%. It is concluded that the introduction of the NDVI variable into the traditional scoring model could improve significantly the smallholder farmers’ chances of accessing credit, thus enabling such a farmer to be better evaluated for credit on the basis of the health of their crop, rather than on a traditional form of collateral.展开更多
The crowdsourced OpenStreetMap mapping platform is utilized by countless stakeholders worldwide for various purposes and applications.Individuals,researchers,governments,commercial,and humanitarian organizations,in ad...The crowdsourced OpenStreetMap mapping platform is utilized by countless stakeholders worldwide for various purposes and applications.Individuals,researchers,governments,commercial,and humanitarian organizations,in addition to the engineers,professionals,and technical developers,use OpenStreetMap both as data contributors and consumers.The storage,usage,and integration of volunteered geographical data in software applications often create complex ethical dilemmas and values regarding the relationships between different categories of stakeholders.It is therefore common for moral preferences of stakeholders to be neglected.This paper investigates the integration of ethical values in OpenStreetMap using the value sensitive design methodology that examines technical,empirical,and conceptual aspects at each design stage.We use the Humanitarian OpenStreetMap Team,an existing volunteered geographic information initiative,as a case study.Our investigation shows that although OpenStreetMap does integrate ethical values in its organizational structure,a deeper understanding of its direct and indirect stakeholders’perspectives is still required.This study is expected to assist organizations that contribute to or use OpenStreetMap in recognizing and preserving existing and important ethical values.To the best of our knowledge,this is the first attempt to evaluate ethical values methodically and comprehensively in the design process of the OpenStreetMap platform.展开更多
The East African Community is a regional block that brings together Kenya, Uganda, Tanzania, Rwanda, Burundi and South Sudan into various forms of economic partnership, the eventual dream being to achieve political fe...The East African Community is a regional block that brings together Kenya, Uganda, Tanzania, Rwanda, Burundi and South Sudan into various forms of economic partnership, the eventual dream being to achieve political federation. The current activities within this community, plus the block’s further development, require the generation and sharing of much geo-information to support the attendant decision-making. Such geo-information can be best served through a harmonized cartographic service with common standards. Such a harmonized service is not only lacking, but even the status of the current national services is also largely unknown. This paper reports on a study undertaken to establish this status, as represented by twelve elements of a cartographic service that the authors are able to establish. Results of the study have shown that the present national services are characterized by inadequate basic datasets that remain largely analogue. In addition, there are non-uniform spatial reference systems, inadequate cartographic human resources and lack of common mapping standards;further, funding for mapping activities remains low in national budgets. Given that over 80% of decisions are influenced by geo-spatial data, these findings point to an urgent need to improve, harmonize and digitize these services as the way forward, if the East African Community is to remain globally competitive.展开更多
Crop insurance, though clearly needed, has not taken root in Kenyan agriculture, and what little exists is indemnity based, meaning that a farmer is compensated only based on assessed crop damage or harvest shortfall....Crop insurance, though clearly needed, has not taken root in Kenyan agriculture, and what little exists is indemnity based, meaning that a farmer is compensated only based on assessed crop damage or harvest shortfall. This is often cumbersome and expensive for the average subsistence farmer. A better approach is to use index based insurance, whereby an agreed index is computed and the farmer is compensated or not compensated depending on its value. Remote sensing technology, which is now widely available globally, provides such an index, the Normalized Difference Vegetation Index (NDVI), which is an acknowledged indicator of crop health at different stages of crop growth. This paper reports on a study carried out in mid-2019 to investigate the possibility of applying remote sensing in this way to enable crop insurance for maize farmers in Migori County, Kenya. Sentinel 2 imagery from May 2017 (taken as the insurance year) was acquired, classified and NDVI generated over the study area. An 8 Km × 8 Km grid was overlaid and average NDVI computed per such grid cell. Similar imagery for May 2016 was acquired and similarly processed to provide reference NDVI averages. For any grid cell then, if Ap be the insurance year NDVI and Ar the reference NDVI, the insurance index was computed as (Ap - Ar), and farmer compensation would be triggered if this value was negative. Results show that out of about 85 small holder farms in the study area, 30 would have qualified for such compensations. These results are recommended for further refining and pilot testing in the study area and similar maize growing areas.展开更多
Solid waste dumping is a hectic problem in urban and developing areas due to shortage of land for the purpose. The main objective of this study was to select potential areas for suitable solid waste dumping for Kajiad...Solid waste dumping is a hectic problem in urban and developing areas due to shortage of land for the purpose. The main objective of this study was to select potential areas for suitable solid waste dumping for Kajiado County, Kenya. Eight input map layers including DEM （digital elevation model）, topography, urban settlement, roads, wetlands, rivers, forests and protected areas were prepared and MCDA （Multi Criteria Decision Analysis Methods） were implemented in a GIS （geographic information systems） environment. GIS, RS （remote sensing） and MDCA are powerful tools which can effectively be applied during the planning phase of solid waste management in order to avoid adverse catastrophes in future. The final suitability map was prepared by weighted overlay analyses and leveled as the most suitable, moderate suitable, less suitable and unsuitable areas. The area of each suitability level was calculated using spatial statistics. Polygons representing the most suitable sites were further analyzed in terms of area perimeter ratio in order to investigate the most suitable areas in terms of shape regularity. The leading four polygons considered were marked A, B, C, D respectively in the final map. This study showed that suitable areas for solid waste landfills were limited and scattered in the study area.展开更多
Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledg...Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledge about their groundwater potential has been leading to the drilling of numerous dry boreholes. In this study, we explored the use of Geographic Information System as a pre-analysis tool to identify zones with groundwater potential for Garissa Country. Factors that contributed to groundwater occurrence were identified as landcover, soil type and rock formation. The groundwater potential zones were generated by analysing thematic data of the three factors and integrating the musing Weighted Index Overlay Analysis (WIOA) method. The groundwater potential zones were validated by comparing the predicted potentials with actual yields of existing boreholes drilled within those areas. Results indicate that, whereas the model correctly predicted areas with low or no groundwater potential, it performed sparingly well when predicting areas with good groundwater potential. The study conclusively identified areas where groundwater prospecting should not be attempted and other alternative methods of surface water provision should be explored.展开更多
GIS certification has been a contentious issue amongst geo-technology professionals for years. Many arguments have been advanced for it, the chief one being that certification is the only way through which a true GIS ...GIS certification has been a contentious issue amongst geo-technology professionals for years. Many arguments have been advanced for it, the chief one being that certification is the only way through which a true GIS professional can be defined for the consumer public. There have been counter arguments, for example that certification will limit the widespread adoption of GIS technology, which is just a tool that anybody should be free to apply, or that it will only add another layer of regulation in a global political environment that favours increased de-regulation. The objective of this paper is to create greater awareness about GIS certification, which doesn’t exist yet in many countries, including some developed ones. Such increased awareness may encourage the standardization of GIS personnel qualifications, which could underpin a better, more dependable growth of the GIS industry, especially in the developing countries. Through analysis of key existing literature on the subject, plus the author’s own professional experiences, the paper explores the issues around GIS certification, looks at global trends on the issue and discusses the situation in the Kenyan GIS industry in respect of certification. The paper finds that there is a global move towards certification, and the relevant work of ISO has given the issue international attention. However, the paper also finds that the presence of a strong GIS professional association greatly assists in the development of a program for such certification, and that the lack of such an association makes it difficult to succeed.展开更多
<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data ...<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data used comprised station-based monthly gridded rainfall data sourced from the Climate Research </span><span style="font-family:Verdana;">Unit (CRU) and monthly model outputs from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM), which has scaled-down </span><span style="font-family:Verdana;">nine GCMs for Africa. Although the 9 Global Climate Models (GCMs) downscaled by the RCA4 model was not very good at simulating rainfall in Kenya, the ensemble of the 9 models performed better and could be used for further studies. The ensemble of the models was thus bias-corrected using the scaling method to reduce the error;lower values of bias and Normalized Root Mean Square Error (NRMSE) w</span></span><span style="font-family:Verdana;">ere</span><span style="font-family:'Minion Pro Capt','serif';"><span style="font-family:Verdana;"> recorded when compared to the uncorrected models. The bias-corrected ensemble was used to study the spatial and temporal behaviour of rainfall under baseline (1971 to 2000) and future RCP 4.5 and 8.5 scenarios (2021 to 2050). An insignificant trend was noted under the </span><span style="font-family:Verdana;">baseline condition during the March-May (MAM) and October-December</span> <span style="font-family:Verdana;">(OND) rainfall seasons. A positive significant trend at 5% level was noted</span><span style="font-family:Verdana;"> under RCP 4.5 and 8.5 scenarios in some stations during both MAM and OND seasons. The increase in rainfall was attributed to global warming due to increased anthropogenic emissions of greenhouse gases. Results on the spatial variability of rainfall indicate the spatial extent of rainfall will increase under both RCP 4.5 and RCP 8.5 scenario when compared to the baseline;the increase is higher under the RCP 8.5 scenario. Overall rainfall was found to be highly variable in space and time, there is a need to invest in the early dissemination of weather forecasts to help farmers adequately prepare in case of unfavorable weather. Concerning the expected increase in rainfall in the future, policymakers need to consider the results of this study while preparing mitigation strategies against the effects of changing rainfall patterns.</span></span> </p>展开更多
Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, res...Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, resulting in reduced harvests and sometimes losses for farmers. Better availability of information such as weather patterns, suitable crops, nutrient requirements based on soil types and conditions would greatly alleviate these challenges. While geospatial information is being developed and improved continuously by researchers, its accessibility and use by the counties has not been established and cannot be identified as contributing to better crop production outcomes. The aim of this study, therefore, was to assess the awareness and status of geospatial data availability and use for crop production, and the level of the relevant capacities, both human and infrastructural, in selected Counties of Kenya. A survey was conducted in the four counties of Vihiga, Kilifi, Wajir and Nyeri and key informant interviews were conducted with both management and technical County Agricultural Officers, as well as sub-county agricultural extension officers. From the results of the survey, out of the four counties, only one has adequate infrastructure in terms of hard-ware, software and connectivity to conduct useful geospatial data acquisition and processing. While most indicated awareness of the existence of geospatial data, limited resources, low skills and knowledge have restricted any meaningful sourcing of and access to data, with only 38% moderately or highly skilled in acquisition, 48% in processing and 57% in interpretation and use of geospatial data. The study concludes that moderate skills and capacities available within the counties have considerable potential to make use the available geospatial data to inform farmers accordingly and improve their farming outcomes.展开更多
The advancement of Global Navigation Satellite System(GNSS)technology has enhanced navigation and positioning accuracy,reliability,and availabil-ity.In Kenya,private organizations have installed CORS to support positi...The advancement of Global Navigation Satellite System(GNSS)technology has enhanced navigation and positioning accuracy,reliability,and availabil-ity.In Kenya,private organizations have installed CORS to support position ing and navigation services,allowing users to access GNSS RTK corrections for survey and mapping projects.However,the accuracy and consistency of GNSS RTK measurements from private CORS remain unverified,which this study aimed to address.A study in Nairobi,Kenya,examined the accuracy and consistency of private CORS by comparing GNSS RTK measurements over stable Survey of Kenya(SoK)control points using published coordinates as a reference.Large vertical coordinate value discrepancies(8.5 m-11 m)and relatively smaller horizontal coordinate value discrepancies(0.3 m-2.4 m)were observed.The discrepancies arise because the private CORS operate on an independent datum,not integrated with the Survey of Kenya(SoK)geo detic control network.The proximity of control points to CORS(less than 30 km)had minimal impact on measurement accuracy.To ensure accuracy and consistency,it is recommended that private CORS be integrated into the national grid,enhancing the reliability of GNSS RTK measurements for di verse survey and mapping applications.Alternatively,users relying on private CORS must localize or perform a site calibration of their rover receivers using at least three known control points to align their measurements with the Na-tional Grid.展开更多
There are estimated to be approximately 600 million small scale farmers globally, and they produce most of the food consumed, especially in the developing countries. The farmers, however, are often unable to obtain op...There are estimated to be approximately 600 million small scale farmers globally, and they produce most of the food consumed, especially in the developing countries. The farmers, however, are often unable to obtain optimal crop yields due to their exclusion from the financial systems in their countries, which deem them too high risk to lend to. This results in the farmers being unable to afford optimal inputs into their farms, hence depressing their yields and the level of food security. This study aimed to statistically determine whether the small scale farmers of Migori County in Kenya are financially excluded or not, and to what extent. Data were collected from the farmers through a questionnaire survey, and subsequent statistical analysis has shown that indeed the small scale farmers of Migori are financially excluded to a large extent. Consideration of non-financial data in the farmers’ credit rating has been recommended as a way forward towards their financial inclusivity. This study provides scientific proof of smallholder farmer financial exclusion, which proof is generally difficult to find, especially in the developing countries.展开更多
Noise is any sound that causes physiological uneasiness to the ear. People in many environments today, especially urban ones, are exposed to such noise without realizing its potential danger to their healthy hearing. ...Noise is any sound that causes physiological uneasiness to the ear. People in many environments today, especially urban ones, are exposed to such noise without realizing its potential danger to their healthy hearing. This situation is largely contributed to by the little attention that most governments, especially in the developing countries, pay to noise as a pollution issue. This paper describes a study that aimed at measuring the noise levels at selected points in Nairobi’s CBD with a view to generate a noise map over the study area in addition to identifying areas of high noise intensity or noise hot spots. The study found that noise levels, on average, varied from 61 db to 78 db, increasing from the west to the east of the CBD, and emanated mainly from vehicular traffic;several noise hotspots were also identified, and they are located mainly to the east of the CBD. The paper concludes that although the study was not city-wide, the noise levels observed are high enough to warrant further research and action by the environmental authorities.展开更多
GIS plays an important role in an organization by ensuring efficiency, effectiveness and better spatial data management. It is used by a wide range of organizations that leverage location data for informed decision ma...GIS plays an important role in an organization by ensuring efficiency, effectiveness and better spatial data management. It is used by a wide range of organizations that leverage location data for informed decision making. The extent to which GIS is utilized in an organization should be audited to ensure monitoring and evaluation. This provides information that allows the organization to access and improve overall GIS performance. Existing applications like Slim GIM, URISA GIS CMM and PSD GMI are used to assess GIS maturity capability in an organization. While auditing is centered on a complete monitoring and evaluation of entire GIS system establishment, maturity capability applications are designed to assess organization’s ability to carry out specific GIS operations. These tools can however be time consuming and need to be calibrated for meaningful result and customized for different domains in order to meet user’s need. The focus of this paper is to develop a conceptual model for GIS audit. Through review of literature, four main categories of parameters that can be used for GIS audit were identified namely: Data quality, Software utilization, GIS competencies and Procedures. The parameters generally relate to the basic GIS components. For each of the category, a number of minor parameters have been identified. The conceptual framework will be a good basis for developing a GIS audit checklist.展开更多
Agriculture continues to be the bedrock of Kenya’s economy at 24% of the GDP with 80% of the population living in the rural areas. Horticulture one of the sub-sectors in agriculture generates US$1 billion annually. T...Agriculture continues to be the bedrock of Kenya’s economy at 24% of the GDP with 80% of the population living in the rural areas. Horticulture one of the sub-sectors in agriculture generates US$1 billion annually. The favorable weather provides an environment for the flower industry to thrive. However, flowers are a very delicate commodity and require appropriate management to minimize losses due to decay. A GIS based system is thus desirable to manage the flower chain from the supplier that is the farms, to distributors and eventually to the florists/consumers. The goal of this study therefore was to leverage the use of GIS in managing the supply chain for floriculture application using Nairobi County as a case study. One of the objectives addressed involved identification of optimal or alternative routes for efficient delivery of flowers from the source to the consumer using Network analysis. Ensuring that customers receive the right flowers in terms of quality and quantity was also addressed using Business Intelligence analysis. Trace analysis was done to provide information to the consumers on the source of the flowers and the growing conditions. From the case study, City Market acted as the link between the flower farms and the florists/consumers. The results obtained were presented using maps, graphs, pie charts and tables. The Central Business District (CBD) was found to be the largest purchaser compared to other regions and the months considered. Karen and CBD were the highest purchasers of Lilies whereas Ferns were preferred in Westlands. The CBD registered high level of satisfaction followed by Karen. Greenhouses and hydroponic methods were used for growing flowers resulting in variations in terms of vase life and stem length. GIS in SCM for floriculture application is useful in understanding the floriculture business environment.展开更多
文摘Eritrea faces significant environmental and agricultural challenges due to human activities, rugged terrain, and fluctuating climates like recurrent droughts and erratic rainfall. Desertification, deforestation, and soil erosion are major concerns affecting soil quality, water resources, and vegetation, especially in areas like the Alla catchment. Recent assessments reveal declining vegetation and precipitation levels over four decades, alongside rising temperatures, linked to increased desertification and land degradation driven by climate variations and prolonged droughts. The urgent need for sustainable land management practices is explained by reduced productivity, biodiversity, and ecosystem health. This study focused on modelling land degradation in Eritrea’s Alla catchment using advanced geospatial techniques. Vegetation indices and soil erosion models were used to evaluate critical factors such as rainfall Erosivity, soil erodibility, slope characteristics, and land cover management. The resulting model highlighted varying levels of susceptibility to land degradation, highlighting widespread vulnerability characterized by high and very high susceptibility hotspots. Areas with minimal degradation were found in the northern vegetation-covered regions. Soil loss in the catchment is primarily influenced by inadequate land cover, steep slopes, soil erosion susceptibility, erosive rainfall patterns, and insufficient support practices. The study underscores the urgency of addressing deforestation and unsustainable agricultural practices to mitigate soil erosion. Recommendations include enhancing community capacity for effective land management, promoting climate adaptation strategies, and aligning national efforts with the global Sustainable Development Goals to achieve Land Degradation Neutrality.
文摘Changes in climate will affect conditions for species growth and distribution, particularly along elevation gradients, where environmental conditions change abruptly. Agroforestry tree (AGT) species on the densely inhabited slopes of Mount Kilimanjaro and Taita Hills will change their elevation distribution, and associated carbon storage. This study assesses the potential impacts of climate change by modelling species distribution using maximum entropy. We focus on important agroforestry tree species (Albiziagummifera, Mangiferaindica and Perseaamericana) and projected climate variables under IPCC-AR5 RCP 4.5 and 8.5 for the mid-century (2055) and late century (2085). Results show differential response: downward migration for M. indica on the slopes of Mount Kilimanjaro is contrasted with Avocado that will shift upslope on the Taita Hills under RCP 8.5. Perseaamericana will lose suitable habitat on Kilimanjaro whereas M. indica will expand habitat suitability. Potential increase in suitable areas for agroforestry species in Taita Hills will occur except for Albizia and Mango which will potentially decrease in suitable areas under RCP 4.5 for period 2055. Shift in minimum elevation range will affect species suitable areas ultimately influencing AGC on the slopes of Mount Kilimanjaro and Taita Hills. The AGC for agroforestry species will decrease on the slopes of Mount Kilimanjaro but AGC for Mango will increase under RCP 8.5 for period 2055 and 2085. In Taita Hills, AGC will remain relatively stable for A. gummifera and P. americana under RCP 8.5 for period 2055 and 2085 but decrease in AGC will occur for M. indica under projected climate change. Climate change will affect AGT species and the amount of carbon stored differently between the sites. Such insight can inform AGT species choice, and conservation and support development by improving carbon sequestration on sites and reliable food production.
文摘A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.
文摘Green gram is considered as one of the legumes suitable for cultivation in the Arid and Semi-Arid Lands (ASALs) of Kenya. However, climate change may alter the areas suitable for green gram production. This study sought to model green gram suitability in Kenya under present and future conditions using bias-corrected RCA4 models data. The datasets used were: maps of soil parameters extracted from Kenya Soil Survey map;present and future rainfall and temperature data from an ensemble of nine models from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM);and altitude from the Digital elevation model (DEM) of the USGS. The maps were first reclassified into four classes of suitability as Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (N). The classes represent the different levels of influence of a factor on the growth and yield of green grams. The reclassified maps were then assigned a weight generated using the Analytical Hierarchy Process (AHP). A weighted overlay of climate characteristics (past and future rainfall and temperature), soil properties (depth, pH, texture, CEC, and drainage) and altitude found most of Kenya as moderately suitable for green gram production during the March to May (MAM) and October to December (OND) seasons under the baseline, RCP 4.5 and RCP 8.5 scenarios with highly suitable areas being found in Counties like Kitui, Makueni, and West Pokot among others. During the MAM season, the area currently highly suitable for green gram production (67,842.62 km<sup>2</sup>) will increase slightly to 68,600.4 km<sup>2</sup> (1.1%) during the RCP 4.5 and reduce to 61,307.8 km<sup>2</sup> (<span style="white-space:nowrap;">−</span>9.6%) under the RCP 8.5 scenario. During the OND season, the area currently highly suitable (49,633.4 km<sup>2</sup>) will increase under both RCP 4.5 (22.2%) and RCP 8.5 (58.5%) scenarios. This increase is as a result of favourable rainfall and temperature conditions in the future.
文摘Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites and against environmental variables. One hectare sampling plots were randomly distributed along elevational gradients stratified by cropland type;AGC was derived from all trees with diameter ≥ 10 cm at breast height in each plot. Predictor variables were physical and edaphic variables and human population. A generalized linear model was used for predicting AGC with AIC used for ranking models. AGC was spatially upscaled in 2 km buffer and visually compared. Kilimanjaro has higher AGC in cropped and agroforestry areas than the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry in Kilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Persea americana, and in the Taita Hills Grevillea robusta and Mangifera indica. Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 = 0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the top multivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation, slope and population (R2 = 0.89, p = 0.00). Despite of the difference in land management history of Mount Kilimanjaro and the Taita Hills, mean of AGC in croplands does not differ significantly. Difference occurs on variation of AGC, type of trees contributing AGC, and environmental variables that explain AGC distribution. The research results provide reference for management of carbon sequestration on inhabited montane areas.
文摘Lake Nakuru is one of Kenya’s Rift Valley Lakes and lies within the Lake Nakuru National Park. As a key habitat for flamingos and other water birds, the lake is a major tourist attraction. Lake Nakuru National Park covers an area of approximately 188 km<sup>2</sup> and is fully enclosed with a perimeter fence. The park is home to about 56 different species of mammals, 550 plant species, and 450 species of terrestrial birds as well as flamingos and other water birds. In the last decade, the lake has experienced continuous flooding, increasing the lake area from 35 km<sup>2</sup> in 2009 to 54 km<sup>2</sup> in 2018. This impacted negatively on the available space for wildlife. The main objective of this study was to investigate the effects of this flooding on the wildlife and their habitats in Lake Nakuru National Park. The methodology used Land use Land cover (LULC) interpretation of Landsat Satellite imagery from two epochs, 2009 and 2018, and integration of the results with relevant wildlife data provided by Kenya Wildlife Service. The results, which include LULC change maps and wildlife distribution maps, have shown that the flooding impacted negatively on the available space for wildlife. In addition, the floods also compromised key park infrastructures such as roads and the main gate making it very difficult to maintain the normal park operations, and hence adversely affecting the local and national economies. The information provided by this study is useful for planning mitigation measures in respect of the current and potential future flooding.
文摘According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food consumed there;their farming activities are therefore critical to the economies of their countries and to the global food security. However, these farmers face the challenges of limited access to credit, often due to the fact that many of them farm on unregistered land that cannot be offered as collateral to lending institutions;but even when they are on registered land, the fear of losing such land that they should default on loan payments often prevents them from applying for farm credit;and even if they apply, they still get disadvantaged by low credit scores (a measure of creditworthiness). The result is that they are often unable to use optimal farm inputs such as fertilizer and good seeds among others. This depresses their yields, and in turn, has negative implications for the food security in their communities, and in the world, hence making it difficult for the UN to achieve its sustainable goal no.2 (no hunger). This study aimed to demonstrate how geospatial technology can be used to leverage farm credit scoring for the benefit of smallholder farmers. A survey was conducted within the study area to identify the smallholder farms and farmers. A sample of surveyed farmers was then subjected to credit scoring by machine learning. In the first instance, the traditional financial data approach was used and the results showed that over 40% of the farmers could not qualify for credit. When non-financial geospatial data, i.e. Normalized Difference Vegetation Index (NDVI) was introduced into the scoring model, the number of farmers not qualifying for credit reduced significantly to 24%. It is concluded that the introduction of the NDVI variable into the traditional scoring model could improve significantly the smallholder farmers’ chances of accessing credit, thus enabling such a farmer to be better evaluated for credit on the basis of the health of their crop, rather than on a traditional form of collateral.
文摘The crowdsourced OpenStreetMap mapping platform is utilized by countless stakeholders worldwide for various purposes and applications.Individuals,researchers,governments,commercial,and humanitarian organizations,in addition to the engineers,professionals,and technical developers,use OpenStreetMap both as data contributors and consumers.The storage,usage,and integration of volunteered geographical data in software applications often create complex ethical dilemmas and values regarding the relationships between different categories of stakeholders.It is therefore common for moral preferences of stakeholders to be neglected.This paper investigates the integration of ethical values in OpenStreetMap using the value sensitive design methodology that examines technical,empirical,and conceptual aspects at each design stage.We use the Humanitarian OpenStreetMap Team,an existing volunteered geographic information initiative,as a case study.Our investigation shows that although OpenStreetMap does integrate ethical values in its organizational structure,a deeper understanding of its direct and indirect stakeholders’perspectives is still required.This study is expected to assist organizations that contribute to or use OpenStreetMap in recognizing and preserving existing and important ethical values.To the best of our knowledge,this is the first attempt to evaluate ethical values methodically and comprehensively in the design process of the OpenStreetMap platform.
文摘The East African Community is a regional block that brings together Kenya, Uganda, Tanzania, Rwanda, Burundi and South Sudan into various forms of economic partnership, the eventual dream being to achieve political federation. The current activities within this community, plus the block’s further development, require the generation and sharing of much geo-information to support the attendant decision-making. Such geo-information can be best served through a harmonized cartographic service with common standards. Such a harmonized service is not only lacking, but even the status of the current national services is also largely unknown. This paper reports on a study undertaken to establish this status, as represented by twelve elements of a cartographic service that the authors are able to establish. Results of the study have shown that the present national services are characterized by inadequate basic datasets that remain largely analogue. In addition, there are non-uniform spatial reference systems, inadequate cartographic human resources and lack of common mapping standards;further, funding for mapping activities remains low in national budgets. Given that over 80% of decisions are influenced by geo-spatial data, these findings point to an urgent need to improve, harmonize and digitize these services as the way forward, if the East African Community is to remain globally competitive.
文摘Crop insurance, though clearly needed, has not taken root in Kenyan agriculture, and what little exists is indemnity based, meaning that a farmer is compensated only based on assessed crop damage or harvest shortfall. This is often cumbersome and expensive for the average subsistence farmer. A better approach is to use index based insurance, whereby an agreed index is computed and the farmer is compensated or not compensated depending on its value. Remote sensing technology, which is now widely available globally, provides such an index, the Normalized Difference Vegetation Index (NDVI), which is an acknowledged indicator of crop health at different stages of crop growth. This paper reports on a study carried out in mid-2019 to investigate the possibility of applying remote sensing in this way to enable crop insurance for maize farmers in Migori County, Kenya. Sentinel 2 imagery from May 2017 (taken as the insurance year) was acquired, classified and NDVI generated over the study area. An 8 Km × 8 Km grid was overlaid and average NDVI computed per such grid cell. Similar imagery for May 2016 was acquired and similarly processed to provide reference NDVI averages. For any grid cell then, if Ap be the insurance year NDVI and Ar the reference NDVI, the insurance index was computed as (Ap - Ar), and farmer compensation would be triggered if this value was negative. Results show that out of about 85 small holder farms in the study area, 30 would have qualified for such compensations. These results are recommended for further refining and pilot testing in the study area and similar maize growing areas.
文摘Solid waste dumping is a hectic problem in urban and developing areas due to shortage of land for the purpose. The main objective of this study was to select potential areas for suitable solid waste dumping for Kajiado County, Kenya. Eight input map layers including DEM （digital elevation model）, topography, urban settlement, roads, wetlands, rivers, forests and protected areas were prepared and MCDA （Multi Criteria Decision Analysis Methods） were implemented in a GIS （geographic information systems） environment. GIS, RS （remote sensing） and MDCA are powerful tools which can effectively be applied during the planning phase of solid waste management in order to avoid adverse catastrophes in future. The final suitability map was prepared by weighted overlay analyses and leveled as the most suitable, moderate suitable, less suitable and unsuitable areas. The area of each suitability level was calculated using spatial statistics. Polygons representing the most suitable sites were further analyzed in terms of area perimeter ratio in order to investigate the most suitable areas in terms of shape regularity. The leading four polygons considered were marked A, B, C, D respectively in the final map. This study showed that suitable areas for solid waste landfills were limited and scattered in the study area.
文摘Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledge about their groundwater potential has been leading to the drilling of numerous dry boreholes. In this study, we explored the use of Geographic Information System as a pre-analysis tool to identify zones with groundwater potential for Garissa Country. Factors that contributed to groundwater occurrence were identified as landcover, soil type and rock formation. The groundwater potential zones were generated by analysing thematic data of the three factors and integrating the musing Weighted Index Overlay Analysis (WIOA) method. The groundwater potential zones were validated by comparing the predicted potentials with actual yields of existing boreholes drilled within those areas. Results indicate that, whereas the model correctly predicted areas with low or no groundwater potential, it performed sparingly well when predicting areas with good groundwater potential. The study conclusively identified areas where groundwater prospecting should not be attempted and other alternative methods of surface water provision should be explored.
文摘GIS certification has been a contentious issue amongst geo-technology professionals for years. Many arguments have been advanced for it, the chief one being that certification is the only way through which a true GIS professional can be defined for the consumer public. There have been counter arguments, for example that certification will limit the widespread adoption of GIS technology, which is just a tool that anybody should be free to apply, or that it will only add another layer of regulation in a global political environment that favours increased de-regulation. The objective of this paper is to create greater awareness about GIS certification, which doesn’t exist yet in many countries, including some developed ones. Such increased awareness may encourage the standardization of GIS personnel qualifications, which could underpin a better, more dependable growth of the GIS industry, especially in the developing countries. Through analysis of key existing literature on the subject, plus the author’s own professional experiences, the paper explores the issues around GIS certification, looks at global trends on the issue and discusses the situation in the Kenyan GIS industry in respect of certification. The paper finds that there is a global move towards certification, and the relevant work of ISO has given the issue international attention. However, the paper also finds that the presence of a strong GIS professional association greatly assists in the development of a program for such certification, and that the lack of such an association makes it difficult to succeed.
文摘<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data used comprised station-based monthly gridded rainfall data sourced from the Climate Research </span><span style="font-family:Verdana;">Unit (CRU) and monthly model outputs from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM), which has scaled-down </span><span style="font-family:Verdana;">nine GCMs for Africa. Although the 9 Global Climate Models (GCMs) downscaled by the RCA4 model was not very good at simulating rainfall in Kenya, the ensemble of the 9 models performed better and could be used for further studies. The ensemble of the models was thus bias-corrected using the scaling method to reduce the error;lower values of bias and Normalized Root Mean Square Error (NRMSE) w</span></span><span style="font-family:Verdana;">ere</span><span style="font-family:'Minion Pro Capt','serif';"><span style="font-family:Verdana;"> recorded when compared to the uncorrected models. The bias-corrected ensemble was used to study the spatial and temporal behaviour of rainfall under baseline (1971 to 2000) and future RCP 4.5 and 8.5 scenarios (2021 to 2050). An insignificant trend was noted under the </span><span style="font-family:Verdana;">baseline condition during the March-May (MAM) and October-December</span> <span style="font-family:Verdana;">(OND) rainfall seasons. A positive significant trend at 5% level was noted</span><span style="font-family:Verdana;"> under RCP 4.5 and 8.5 scenarios in some stations during both MAM and OND seasons. The increase in rainfall was attributed to global warming due to increased anthropogenic emissions of greenhouse gases. Results on the spatial variability of rainfall indicate the spatial extent of rainfall will increase under both RCP 4.5 and RCP 8.5 scenario when compared to the baseline;the increase is higher under the RCP 8.5 scenario. Overall rainfall was found to be highly variable in space and time, there is a need to invest in the early dissemination of weather forecasts to help farmers adequately prepare in case of unfavorable weather. Concerning the expected increase in rainfall in the future, policymakers need to consider the results of this study while preparing mitigation strategies against the effects of changing rainfall patterns.</span></span> </p>
文摘Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, resulting in reduced harvests and sometimes losses for farmers. Better availability of information such as weather patterns, suitable crops, nutrient requirements based on soil types and conditions would greatly alleviate these challenges. While geospatial information is being developed and improved continuously by researchers, its accessibility and use by the counties has not been established and cannot be identified as contributing to better crop production outcomes. The aim of this study, therefore, was to assess the awareness and status of geospatial data availability and use for crop production, and the level of the relevant capacities, both human and infrastructural, in selected Counties of Kenya. A survey was conducted in the four counties of Vihiga, Kilifi, Wajir and Nyeri and key informant interviews were conducted with both management and technical County Agricultural Officers, as well as sub-county agricultural extension officers. From the results of the survey, out of the four counties, only one has adequate infrastructure in terms of hard-ware, software and connectivity to conduct useful geospatial data acquisition and processing. While most indicated awareness of the existence of geospatial data, limited resources, low skills and knowledge have restricted any meaningful sourcing of and access to data, with only 38% moderately or highly skilled in acquisition, 48% in processing and 57% in interpretation and use of geospatial data. The study concludes that moderate skills and capacities available within the counties have considerable potential to make use the available geospatial data to inform farmers accordingly and improve their farming outcomes.
基金the support received from private CORS operators in Nairobi,Kenya,during the research period.
文摘The advancement of Global Navigation Satellite System(GNSS)technology has enhanced navigation and positioning accuracy,reliability,and availabil-ity.In Kenya,private organizations have installed CORS to support position ing and navigation services,allowing users to access GNSS RTK corrections for survey and mapping projects.However,the accuracy and consistency of GNSS RTK measurements from private CORS remain unverified,which this study aimed to address.A study in Nairobi,Kenya,examined the accuracy and consistency of private CORS by comparing GNSS RTK measurements over stable Survey of Kenya(SoK)control points using published coordinates as a reference.Large vertical coordinate value discrepancies(8.5 m-11 m)and relatively smaller horizontal coordinate value discrepancies(0.3 m-2.4 m)were observed.The discrepancies arise because the private CORS operate on an independent datum,not integrated with the Survey of Kenya(SoK)geo detic control network.The proximity of control points to CORS(less than 30 km)had minimal impact on measurement accuracy.To ensure accuracy and consistency,it is recommended that private CORS be integrated into the national grid,enhancing the reliability of GNSS RTK measurements for di verse survey and mapping applications.Alternatively,users relying on private CORS must localize or perform a site calibration of their rover receivers using at least three known control points to align their measurements with the Na-tional Grid.
文摘There are estimated to be approximately 600 million small scale farmers globally, and they produce most of the food consumed, especially in the developing countries. The farmers, however, are often unable to obtain optimal crop yields due to their exclusion from the financial systems in their countries, which deem them too high risk to lend to. This results in the farmers being unable to afford optimal inputs into their farms, hence depressing their yields and the level of food security. This study aimed to statistically determine whether the small scale farmers of Migori County in Kenya are financially excluded or not, and to what extent. Data were collected from the farmers through a questionnaire survey, and subsequent statistical analysis has shown that indeed the small scale farmers of Migori are financially excluded to a large extent. Consideration of non-financial data in the farmers’ credit rating has been recommended as a way forward towards their financial inclusivity. This study provides scientific proof of smallholder farmer financial exclusion, which proof is generally difficult to find, especially in the developing countries.
文摘Noise is any sound that causes physiological uneasiness to the ear. People in many environments today, especially urban ones, are exposed to such noise without realizing its potential danger to their healthy hearing. This situation is largely contributed to by the little attention that most governments, especially in the developing countries, pay to noise as a pollution issue. This paper describes a study that aimed at measuring the noise levels at selected points in Nairobi’s CBD with a view to generate a noise map over the study area in addition to identifying areas of high noise intensity or noise hot spots. The study found that noise levels, on average, varied from 61 db to 78 db, increasing from the west to the east of the CBD, and emanated mainly from vehicular traffic;several noise hotspots were also identified, and they are located mainly to the east of the CBD. The paper concludes that although the study was not city-wide, the noise levels observed are high enough to warrant further research and action by the environmental authorities.
文摘GIS plays an important role in an organization by ensuring efficiency, effectiveness and better spatial data management. It is used by a wide range of organizations that leverage location data for informed decision making. The extent to which GIS is utilized in an organization should be audited to ensure monitoring and evaluation. This provides information that allows the organization to access and improve overall GIS performance. Existing applications like Slim GIM, URISA GIS CMM and PSD GMI are used to assess GIS maturity capability in an organization. While auditing is centered on a complete monitoring and evaluation of entire GIS system establishment, maturity capability applications are designed to assess organization’s ability to carry out specific GIS operations. These tools can however be time consuming and need to be calibrated for meaningful result and customized for different domains in order to meet user’s need. The focus of this paper is to develop a conceptual model for GIS audit. Through review of literature, four main categories of parameters that can be used for GIS audit were identified namely: Data quality, Software utilization, GIS competencies and Procedures. The parameters generally relate to the basic GIS components. For each of the category, a number of minor parameters have been identified. The conceptual framework will be a good basis for developing a GIS audit checklist.
文摘Agriculture continues to be the bedrock of Kenya’s economy at 24% of the GDP with 80% of the population living in the rural areas. Horticulture one of the sub-sectors in agriculture generates US$1 billion annually. The favorable weather provides an environment for the flower industry to thrive. However, flowers are a very delicate commodity and require appropriate management to minimize losses due to decay. A GIS based system is thus desirable to manage the flower chain from the supplier that is the farms, to distributors and eventually to the florists/consumers. The goal of this study therefore was to leverage the use of GIS in managing the supply chain for floriculture application using Nairobi County as a case study. One of the objectives addressed involved identification of optimal or alternative routes for efficient delivery of flowers from the source to the consumer using Network analysis. Ensuring that customers receive the right flowers in terms of quality and quantity was also addressed using Business Intelligence analysis. Trace analysis was done to provide information to the consumers on the source of the flowers and the growing conditions. From the case study, City Market acted as the link between the flower farms and the florists/consumers. The results obtained were presented using maps, graphs, pie charts and tables. The Central Business District (CBD) was found to be the largest purchaser compared to other regions and the months considered. Karen and CBD were the highest purchasers of Lilies whereas Ferns were preferred in Westlands. The CBD registered high level of satisfaction followed by Karen. Greenhouses and hydroponic methods were used for growing flowers resulting in variations in terms of vase life and stem length. GIS in SCM for floriculture application is useful in understanding the floriculture business environment.
