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Dear Label_Name,

Greetings! I hope you are well.

I am writing on behalf of an international publishing house, Science and Education Publishing, USA (http://www.sciepub.com).

Science and Education Publishing (SciEP) is a multidisciplinary open access publisher of Journals covering the fields of Science, Technology and Medicine. All SciEP publications are subject to high-quality peer review, editorial and production processes and are freely available online.

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American Journal of Public Health Research
DOI: 10.12691/ajphr-1-1-3

The Implementation of a Tele-Homecare System with Service Oriented Architecture and HL7 Message Transmission Standard
Ching-Sung Wang

American Journal of Medical and Biological Research
DOI: 10.12691/ajmbr-1-1-2

The Influence of Ethanol on Pyruvate Kinases Activity in Vivo, in Vitro, in Silico
Lelevich Sergey Vladimirovich, Khrustalev Vladislav Victorovich, Barkovsky Eugene Victorovich, Shedogubova Tatyana Aleksandrovna

American Journal of Medical Sciences and Medicine
DOI: 10.12691/ajmsm-1-1-1

Clinical and Histological Features in Wegener Granulomatosis
Li Cavoli Gioacchino, Passantino Rita, Bono Luisa, Tortorici Calogera, Ferrantelli Angelo, Giammarresi Carlo, Rotolo Ugo

American Journal of Infectious Diseases and Microbiology
DOI: 10.12691/ajidm-1-1-2

The Curse of Lymphatic Filariasis: Would the Continual Use of Diethylcarbamazine Eliminate this Scourge in Papua New Guinea?
Anne Lanham, Lillian Mwanri

We have released issues of some journals on February 2013.
American Journal of Public Health Research
American Journal of Medical Sciences and Medicine
American Journal of Medical and Biological Research
American Journal of Pharmacological Sciences
American Journal of Clinical Medicine Research
American Journal of Nursing Research
American Journal of Cancer Prevention
American Journal of Medicine Studies
American Journal of Infectious Diseases and Microbiology
American Journal of Cardiovascular Disease Research
American Journal of Biomedical Research
American Journal of Mechanical Engineering
American Journal of Microbiological Research
Journal of Preventive Medicine
American Journal of Food and Nutrition
American Journal of Hypertension Research
American Journal of Sports Science and Medicine
Journal of Cancer Research and Treatment
American Journal of Zoological Research
Journal of Biomedical Engineering and Technology
American Journal of Microbiological Research
Biomedical Science and Engineering

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Label_Title

Dear Label_Name,

Greetings! I hope you are well.

I am writing on behalf of an international publishing house, Science and Education Publishing, USA (http://www.sciepub.com).

Science and Education Publishing (SciEP) is a multidisciplinary open access publisher of Journals covering the fields of Science, Technology and Medicine. All SciEP publications are subject to high-quality peer review, editorial and production processes and are freely available online.

Welcome to the April, 2013 edition of SciEP newsletter, providing monthly summaries of articles on science & education related topics of interest to scientist and professionals. The mission of our journals is to provide an open access forum for publishing new findings on issues pertinent to scientific and academic field. We also invite you to submit original research papers, review articles, short reports, or case studies are considered for publication in our Multidisciplinary Journals.

American Journal of Public Health Research
DOI: 10.12691/ajphr-1-1-3

The Implementation of a Tele-Homecare System with Service Oriented Architecture and HL7 Message Transmission Standard
Ching-Sung Wang

American Journal of Medical and Biological Research
DOI: 10.12691/ajmbr-1-1-2

The Influence of Ethanol on Pyruvate Kinases Activity in Vivo, in Vitro, in Silico
Lelevich Sergey Vladimirovich, Khrustalev Vladislav Victorovich, Barkovsky Eugene Victorovich, Shedogubova Tatyana Aleksandrovna

American Journal of Medical Sciences and Medicine
DOI: 10.12691/ajmsm-1-1-1

Clinical and Histological Features in Wegener Granulomatosis
Li Cavoli Gioacchino, Passantino Rita, Bono Luisa, Tortorici Calogera, Ferrantelli Angelo, Giammarresi Carlo, Rotolo Ugo

American Journal of Infectious Diseases and Microbiology
DOI: 10.12691/ajidm-1-1-2

The Curse of Lymphatic Filariasis: Would the Continual Use of Diethylcarbamazine Eliminate this Scourge in Papua New Guinea?
Anne Lanham, Lillian Mwanri

We have released issues of some journals on February 2013.
American Journal of Public Health Research
American Journal of Medical Sciences and Medicine
American Journal of Medical and Biological Research
American Journal of Pharmacological Sciences
American Journal of Clinical Medicine Research
American Journal of Nursing Research
American Journal of Cancer Prevention
American Journal of Medicine Studies
American Journal of Infectious Diseases and Microbiology
American Journal of Cardiovascular Disease Research
American Journal of Biomedical Research
American Journal of Mechanical Engineering
American Journal of Microbiological Research
Journal of Preventive Medicine
American Journal of Food and Nutrition
American Journal of Hypertension Research
American Journal of Sports Science and Medicine
Journal of Cancer Research and Treatment
American Journal of Zoological Research
Journal of Biomedical Engineering and Technology
American Journal of Microbiological Research
Biomedical Science and Engineering

We are pleased to announce that submissions are now being accepted for peer review for all the journals across all our subject areas in SciEP.

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Analysis of Land Use/Land Cover Changes Using GIS and Remote Sensing Techniques in River Ruiru Watershed, Kiambu County, Kenya

Ann Waithaka

Department of Geography, Mount Kenya University, Thika, Kenya

Abstract: Watershed management and water resource planning require accurate measurements of the past and present land use and land cover data to determine hydrological and ecological processes taking place. This study aimed to establish the extent of land use and land cover changes that have occurred in River Ruiru watershed in Kiambu County from 1976 to 2017. The study integrated the use of remote sensing data and GIS techniques to collect and analyse collected data. Three multi-temporal LANDSAT imageries of 1976, 1995 and 2017 were used. Supervised classification-maximum likelihood algorithm in ArcGIS 10.4.1 was employed. Results from the study indicated that built-up areas, annual crops and perennial crops (tea and coffee) increased by 3.068%, 35.848% and 11.493% respectively between 1976 and 2017. However, it was observed that perennial crops increased gradually between 1976 and 1995 but declined by 1.94% between 1995 and 2017. During the same period, between 1976 and 2017, grassland, shrubland and forestland declined by 7.48%, 13.25% and 29.79% respectively. The findings from this study will enable the quantification of change and analysis of the direction of change between various land use/land cover types that have occurred in River Ruiru watershed from 1976 to 2017 hence enabling the assessment of watershed hydrological vulnerabilities resulting from land use/land cover change. The data from this study will provide critical input to decision making on water resources management and planning. This will aid in the management of water resources on a watershed basis thus addressing the potential impacts and deterioration of water resources.

Keywords: land use change, land cover change, GIS, remote sensing, River Ruiru watershed

Received October 01, 2023; Revised November 01, 2023; Accepted November 09, 2023

Citation: Ann Waithaka, Analysis of Land Use/Land Cover Changes Using GIS and Remote Sensing Techniques in River Ruiru Watershed, Kiambu County, Kenya. Journal of Geosciences and Geomatics, 11 (4). 97-101. January 2023. doi:10.12691/jgg-11-4-1

1. Introduction

It is estimated that land use and land cover change has affected almost a third (32%) of the global land area in six decades between 1960-2019 [1,2]. Moreover, about three quarter of the earth’s surface has been altered by humans within the last millennium [3,4]. Consequently, land use/land cover changes associated with human activities and natural factors compromise many ecosystems including watersheds of important rivers [5,6]. These changes have significant impacts on the functioning of socio-economic and environmental systems with important tradeoffs for sustainability, food security, biodiversity and socio-economic vulnerability of people and ecosystems [7-9]. However, despite its significance, understanding how land use and land cover have changed in space and time is limited by shortage of comprehensive data [10,11].Therefore an investigation of these changes provides a baseline requirement for planning and sustainable management of natural resources [12,13].

In Kenya, various river catchments and water towers have been gradually characterized by human settlement, deforestation, wetland reclamation and unsustainable agricultural activities [14,15]. This has accelerated the unprecedented changes in the ecosystem and environmental processes in the country [16,17]. River Ruiru watershed which traverses rural, urban and peri-urban areas is characterized by high population growth, movement of people move from rural to urban environment especially in Ruiru Municipality, higher demands for food security as well as increased agricultural, industrial and quarrying activities. Moreover, the influence of the city of Nairobi has also led to tendency towards land use change from agricultural to commercial and settlement, especially within the urban centres [18]. Therefore, to ensure sustainable development in the watershed, it is necessary to monitor the ongoing process on LULC pattern over a period of time. Information about land use and land cover change is also essential for a better understanding of relationships and interactions between humans and natural environment in the watershed.

River Ruiru watershed is also an important water resource as it includes Ruiru 1 and the proposed Ruiru 2 dams important for inter-basin water transfer to Nairobi City County. This is due to the fact that the towns around the city of Nairobi that share water resources from the Aberdares are among the worst hit by water scarcity resulting from the ever increasing demand. The capacity of water resources in the headwater regions has been declining with time due to a number of factors including catchment degradation and reduced rainfall to recharge the sources [18,19]. River Ruiru is also one of the major perennial tributaries of River Athi which provides water to the population in the vast semi-arid parts of Kenya for various purposes before discharging into the Indian Ocean.

These rapid and intense changes in land use and land cover have created the need to quantify them so that we can understand and leverage this information to the best way possible. It is also critical in formulating alternative future landscape scenarios to improve environmental conditions [20,21]. Remote sensing and Geographic Information System are powerful, cost-effective tools for assessing spatial and temporal land use and land cover changes [22,23]. The use of these geospatial analysis techniques provide accurate, timely and detailed information for detecting and monitoring changes in land use and land cover [24-26]. By integrating remote sensing and GIS techniques, it is possible to analyze and classify the changing pattern of land cover for a long period and understand the changes within the area of interest. These techniques also allow for the study and manipulation of geographic information for large areas easily and effectively [27]. The potential of satellite based data as a basis for generating valuable information for land use/land cover is widely recognized as they serve a great deal in classification of different landscape components at a larger scale [27,28].

2. Materials and Methods

2.1. The Study Area

The study area was River Ruiru watershed which has an area of 484.515 km2 [29]. The area has a population of 671,646 persons [30]. It lies between longitude 36°40’E and 37°00’E and latitude 1°10’S and 0°50’S. River Ruiru originates from Kikuyu plateau and drains to the southeastern slopes of the Aberdare ranges in Kiambu County.

River Ruiru watershed is hydrologically located within the Athi Basin 3BC sub-basin. The watershed is covered by a well distributed dense lateral river network. It is located in medium rainfall potential area of Athi Basin with moderate and reliable rainfall [31]. The mean temperature is 26°C with temperature ranging from 17.1°C in the upper highlands to 34°C in the lower midlands. Ruiru River is the major river in the watershed with its main tributaries being Makuyu, Gatamaiyu and Komothai [18].

River Ruiru watershed has four dominant land cover types which include trees, settlements, grasslands and croplands [31]. The land cover has high temporal variations with the wet season exhibiting high vegetation cover (high biomass) and the dry season exhibiting very low vegetation cover (low biomass). The upper part is predominantly forested but is currently threatened by encroachments into the forest area. The area has an undulating landscape, with steep valleys where the rivers cross. The land use potential may be described according to the country’s agro-ecological zones which may be categorized as medium to high potential falling under zones UM3, UM2, UH1, UH0, UM1, UM5, UM4 and LH1 as in Figure 1 [32,33].

Figure 1. River Ruiru watershed

2.2. Data Collection Techniques

Land use data of four landsat MSS, TM and OLI/TIRS images for 1976, 1984, 1995 and 2017 were obtained from USGS-Earth explorer (http://www.earthexplorer.usgs.gov/) website in Geotiff format as shown in Table 1. Multi-temporal analysis of satellite images is effective for change analysis because of high correlation between imagery spectral variation and land use change [34,35]. To avoid uncertainties, clouds and possible errors emanating from seasonal differences between time points, the selected images were acquired within the dry seasons of the year (December-January-February-March). It has been recommended that by using dry season images, there will be reduced confusion at forest edges between dense forest vegetation and small-scale agricultural plots [36,37]. Landsat imagery was used due to its longest history of service with a relatively high spatial resolution and its wide application for land cover classification across the world [38]. The use of these new data with higher spatial resolutions have the potential of more accurate analysis [39,40].

Table 1. Satellite image metadata and date of acquisition

2.3 Land Use Change Analysis

Spatial extent of Ruiru watershed was done through ArcGIS 10.4.1 functions based on 1976, 1995 and 2017 landsat images. Three bands B2, B3 and B4 representing the RGB colours were imported into the ArcMap. A composite of the three bands was formed using the image analysis tool. The study area was extracted through masking in the arctool box then projected into UTM WGS 1984 southern hemisphere zone 37S. Training samples were then created based on different colours of the study area, landsat images and the signature file. Land use classification was done using image classification tool -maximum likelihood classification method. False colour composites (Bands 432) were used for the visual examination and interpretation of the images. Maximum likelihood classification method was used as it is the most widely used per-pixel method which takes into account spectral information of land cover classes [41]. The maximum likelihood decision rule is based on the probability that a given pixel belongs to a specific class [42] and that the statistics for each individual class in each band is evenly distributed.

To prepare land use and land cover maps from satellite images, a classification scheme that defines the land use and land cover was considered. The number of LULC classes are based on the requirement of a specific project for a particular application [43,44]. The images were classified into seven land use types using supervised classification based on land use/land cover classification system [45]. These land use types include built-up areas, annual crops, plantation (tea and coffee), grassland, shrubland, forestland and waterbody.

3. Results and Discussion

Figure 2 indicate that River Ruiru watershed experienced land use/land cover change from 1976 to 2017. Built-up areas increased by 3.07% from 0.69%, 2.16% and 3.76% from 1976, 1995 and 2017 respectively. In the same period, annual crops increased by 35.85% from 10.79%, 38.12% and 46.63%. Perennial crops (Tea and coffee) increased by 11.49% from 4.67% and 18.10% between 1976 and 1995 but declined to 16.16 % between 1995 and 2017. Areas under water bodies slightly increased in the area by 0.1% from 0.21%, 0.29% and 0.31%. In the same period, forestland declined by 29.79% from 56.42% in 1976, to 30.0% in 1995 and to 26.63% in 2017. Similarly, grasslands and shrublands declined by 7.48% and 13.25% respectively from 12.55%, 6.03% to 5.07% and from 14.68%, 5.3% to1.43% between 1976, 1995 and 2017.

The increase in built-up areas, perennial and annual crop farming could be due to population increase in the area and expansion of agricultural land. The observed decline in perennial crops between 1995 and 2017 could have been contributed by the conversion of coffee estates into residential and commercial lands and conversion into annual crops. This conversion was attributed to low coffee prices in the international market. The decline in forestland, shrubland and grassland could be due to increased demand for residential, commercial and agricultural land.

A kappa coefficient of 79 % and an overall accuracy of 82% were achieved for the 2017 land use/land cover classification indicating a high agreement between the classified image and the reference image. Kappa coefficient ranges from 0 to 1 and values higher than 0.7 are considered acceptable while those equal or lower than 0.4 identify a very low correlation between the classified image and the ground truth [46]. According to [47] a kappa value higher than 0.5 can be considered as satisfactory for modelling of land use change. Similarly [48] characterized agreement for the kappa coefficient as follows; values > 0.79 are excellent, values between 0.6 and 0.79 are substantial and values of 0.59 or less indicate moderate or poor agreement. Equally [49] affirms that a K>0.8 is usually considered as a strong agreement and good accuracy while the acceptable threshold for overall accuracy according to USGS classification is 75%. According to (50) such results can be used to study the spatial and temporal patterns of LULC change and evaluate its long-term hydrological impacts.

Figure 2. Land use/land cover in 1976, 1995 and 2017

These results are consistent with study findings by [51] in his study on the influence of geomo-hydrometric characteristics and land use/land cover change on water resources management in River Gucha-Migori catchment who observed that between 1986 to 2008 towns and large cultivated areas increased from 21.5 km² and 37.1 km² to 39.0 km2 and 56.5 km² respectively while closed forests, open grasslands, closed shrubs and open shrubs decreased from 40.7 km², 41.2km², 211.9 km² and 1313.8km² to 28.0 km², 25.0 km², 74.5 km² and 268.6 km² respectively. Correspondingly [52] in a study on land use cover change and classification in Chaohu lake catchment observed that built-up areas increased from 3.5% in 1979 to 25.1% in 2015. Similarly, the agricultural land use increased from the area coverage of 29.8% in 1979 to 45.2% in 2015 while forested/vegetated land of the catchment substantially decreased during this period, from 59.8% in 1979 to 22.9% in 2015. Further [53] in their study on the effect of rainfall variability and land use and land cover change in a small tropical river basin observed that between 2000 and 2016 forest and shrub cover increased by 5%, built up areas increased by 35%, tea increased marginally by 5% while coffee decreased by 38%.

Findings from the current study are also comparable with the findings by [54] who assessed land use/land cover change in Makueni County and found out that evergreen forests decreased the most from 39% coverage in 2000 to 17% coverage in 2016. Similarly, [55] while evaluating land use/land cover change in Bhimtal Lake catchment observed that during the last 20 years (1995-2015), the settlement area increased from 9.70% to 18.38%, agricultural area has increased from 44.32% to 47.63% while the forest area decreased from 43.58% to 31.47% in their study area. Consequently, [56] in their study on land use change mapping and analysis in Sinily watershed concluded that land use and land cover shift in the watershed was evidenced by the decline in the area of vegetation and water class by 38.2% and 74.3% respectively and augmentation of area covered by classes of settlements by 80.1%, agricultural by 163.7% and barren land by 63.3%.

4. Conclusion

The findings from the study indicated that built-up areas, perennial and annual crop farming increased by 3.07%, 11.49% and 35.85% respectively in River Ruiru watershed for the last 41 years from 1976 to 2017. However, it was observed that between 1995 and 2017 perennial crop farming declined by 1.94%. In the same period, forestland, shrubland and grassland declined by 29.79%, 13.25% and 7.48% respectively due to increased demand for residential, commercial and agricultural land. Remote sensing and GIS techniques provided powerful and effective tools for analyzing land use and land cover change. By comparing each classified map with the successive, it was possible to determine land use and land cover change in River Ruiru watershed. In conclusion, River Ruiru watershed has experienced land use/land cover changes.

Statement of Competing Interests

The author has no competing interests.

References

[1]   | Lambin, E. F. and Meyfroidt, P., “Global land use change, economic globalization and the looming land scarcity”. Proceedings of the national academy of sciences, 108 (9)3465-3472, 2011.
[2]   | Karina, W., Fuch, R., Rounsevell, M. and Herold, M., “Global land use changes are four times greater than previously estimated” Nature communications, 2021.
[3]   | Lussaert, S., Jammet, M., Stoy, P.C., Estel, S., Pongrats, J., Ceschia, E. et al., “Land management and land-cover change have impacts of similar magnitude on surface temperature” Nat. clim. Change, 4(389-393), 2014.
[4]   | Arneth, A., Denton, F., Agus, F., Elbehri, A., Erb, H.K., Elasha, B.O. et al., “Framing and context. In climate change desertification, land degradation, sustainable land management, food security and greenhouse gas fluxes in terrestrial ecosystems” (eds. Shukla, P.R. et al., 2019), 2019.
[5]   | Burcher, C.L., Vallet, H.M. and Benfield, E.F., “The land cover cascade. Relationship coupling land and water”, Ecology, 88, 228242, 2007.
[6]   | Salajegheh, A., Razavizader, S., Khorasani, N., Hamidifar, M. and Salajegheh, S., “Land use changes and its effects on water quality (Case study: Karkheh watershed)”. Journal of Environmental studies, vol 37, No. 58, 2011.
[7]   | Liu, J. and Buheasier, Y., “Study on spatial-temporal feature of modern land use in China using remote sensing techniques”. Quarternary sciences, 20(3): 229-239, 2000.
[8]   | Liu, M.L., Tang, X.M. and Liu,J. Y., “Research on scaling effect based on 1km grid cell data”, Journal of remote sensing, 5 (3), 183-189, 2001.
[9]   | Mirkatouli, J., Hosseini, A. and Nehsat, A., “Analysis of land use and land cover spatial pattern based on Markov chains modeling, City Territ”Archtect. 2(4):1-9, 2015.
[10]   | Bayer, A.D., Lindeskog, M., Pugh, T.A.M, Anthoni, P.M., Fuch, R. and Arneth, A., “Uncertainties in the land use flux resulting from land use change reconstructions and gross land transitions”. Earth syst. Dyn., 8:91-111, 2017.
[11]   | Prestele, R., Arneth, A., Bondeau, A., Noblet-Ducoudre, N., Pugh, T.A.M., Sitch, S., Stehfest, E. and Verburg, P.H., “Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments” Earth syst. dyn.,369-356, 2017.
[12]   | Lambin, E.F., Rousevell, M.D.A. and Geist, H.J., “Are agricultural land use models able to predict changes in land use intensity?” Agric. ecosyst. Environ, 82(1-3): 321-331, 2000.
[13]   | Read, J. and Lam, N.S.N., “Spatial methods of characterizing land cover and detecting land cover changes for the tropics”, International journal of remote sensing, 23 (12): 2457-2474, 2002.
[14]   | UNEP (2009). “Kenya: Atlas of our changing environment: Division of Early Warning and Assessment” Progress press co. Ltd. Malta, London, .
[15]   | Aura, M.C., Raburu, P.C., and Herman, J., “Macro vertebrates community structure in rivers Kipkaren and Sosian, River Nzoia Basin”, Journal of Ecology and the National Environment, vol., 3(2), pp. 39–46, 2011.
[16]   | Campbell, D.J., Lusch, D.P., Smucker, T., and Wangui, E.E., “Root causes of land use change in the Loitoktok area, Kajiado district, Kenya”, LUCID working paper series no. 19, Michigan State University, pp 1-32, 2003.
[17]   | Kenya Land Alliance, “Land use in Kenya: The case for a national land-use policy” in Mwagore, D. (ed), vol. 3, 2003.
[18]   | Environmental and Social Impact Assessment (2014). Environmental and social impact assessment of Ruiru 11 dam water supply project-preliminary report by Norken International Ltd/Aquaclean services Ltd, Nairobi, Kenya, 2014.
[19]   | Government of Kenya, “The National Water Services Strategy”, Ministry of Water and Irrigation, Government Printers, Kenya, 2007.
[20]   | Goldewij, K.K., “Estimating global land use change over the past 300 years: The HYDE database” Global biogeochemical cycles, vol. 15, no. 2, 417-433, 2001, http://www.rivm.nl/env/int/hyde/.
[21]   | FAO, “Global forest resources assessment 2005. Progress towards sustainable forest management” Forestry paper, 147 ISBN 92-5-10548-9, 2006.
[22]   | Yuan, F., Sawaya, F.E., Loeffelholz, B.C. and Bauer, M.E., “Land cover classification and change analysis of the Twin cities (Minnesota) Metropolitan area by multi-temporal landsat remote sensing”, Remote sens. Environ., 98, 317-328, 2005.
[23]   | Serra, P.,Pons, X. and Sauri, D., ” Land- cover and land-use change in Mediterranean landscape. A spatial analysis of driving forces integrating bio-physical and human factors”, Applied geography, 28 (3): 189-209, 2008.
[24]   | Carson, T.N. and Sanchez-Azofeifa, G.A., “Satellite remote sensing of land use change in and around San Jose, Costa Rika”, Remote sensing of environment: 70(3): 247-256, 1999.
[25]   | Guerschman, J.P.,Paruero, J.M., Bella, C.D., Giallorezi, M.C. and Pacin, F., “Land cover classification in the Argentine Pampas using multi-temporal landsat TM data”, International journal of remote sensing, 24 (17): 3381-3402, 2003.
[26]   | Rogan, J. and Chen, D., “Remote sensing technology for mapping and monitoring land-cover and land-use change”, Progress in planning, 61 (4):301-325, 2004.
[27]   | Saadat, H., Adamowski, J., Bonnell, R., Shariji, F.,Namdar, M. and Ale-Ebrahim, S., “Land use and land cover classification over a large area in Iran based on single date analysis of satellite imagery”, ISPRS J. photogrammetry R. sens., 66: 608-619, 2011.
[28]   | Ozesmi, S.L. and Bauer, M.E., “Satellite remote sensing of wetlands” Wetlands Ecol. manage, 10, 381-402, 2002.
[29]   | Thubu, J.W., “Developing a sustainable water management plan for Ruiru, Thiririka and Ndarugu sub-basins in Kenya using WEAP”, Unpublished masters thesis, Jomo Kenyatta University of Agriculture and Technology, 2012.
[30]   | Government of Kenya, “2019 Kenya Population and Housing Census”, Volume 1: Population by county and sub-county, 2019, units.www@knbs.or.ke.
[31]   | County Integrated Development Plan 2018-2022, “County government of Kiambu”, 2018.
[32]   | Jaetzold, R., and Schmidt, H., “Farm Management Handbook of Kenya.” Vol. II. East Kenya, Ministry of Agriculture, pp. 245-285, 1983.
[33]   | Jaetzold, R., Schmidt, H., Hometz, B. and Shisanya, C., ”Farm management Handbook of Kenya”, vol. II/C1, Ministry of Agriculture, 2006.
[34]   | Green, K., Kempta, D. and Lackey, L., ”Using remote sensing to detect and moitor land cover and land-use change”, Photogrammetric engineering and remote sensing, 60(3), 331-337, 1994.
[35]   | Dewan, AM. and Yamaguchi, Y., “Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005”. Environ.monit.assess.150, 237-249, 2009.
[36]   | Maingi, J.K. and Marsh, S.E., “Assessment of environmental impacts of river basin development on the riverine forest of eastern Kenya using multi-temporal satellite data”, International journal of remote sensing, 23(14):2701-2729, 2001.
[37]   | Toll, L., ”An estimate of forest cover extent and change in Jamaica using landsat MSS data” International journal of remote sensing, 23(1): 91-106, 2002.
[38]   | Kibena, J., Nhapi, I. and Gumindoga, W., “Assessing the relationship between water quality parameters and changes in land use patterns in the Upper Manyame River, Zimbabwe” Physics and Chemistry of the earth,93,153-163, 2014.
[39]   | Boyle S.A., Kennedy C.M., Torres J., Colman K., Perez-Estigarribia, P.E. and De la Sancha, N.U., “High resolution satellite imagery is an important yet underutilized resource in conservation Biology”, PLoS ONE 9, 1-11, 2014.
[40]   | Fisher, J.R.B., Acosta, E.A., Dennedy-Frank, J., Kroeger, T. and Boucher, T.M., “Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality” Remote sensing in ecology and conservation 2018: 4(2), 137-149, 2018.
[41]   | Qian, J., Zhou, Q. and Hou, Q., “Comparison of pixel-based and object oriented classification methods for extracting built-up areas in arid zone”, In ISPRS workshop of updating geo-spatial databases with imagery and the 5th ISPRS workshop on DMGISs, 163-171, 2007.
[42]   | Manugula, S.S., Sagar, M., Nihar, K.S. and Reddy, K.A. (2017). “Digital classification of land use/land cover by using remote sensing techniques” International journal of engineering and technology, 8, 2, 2017.
[43]   | Arora, K.M. and Mathur, S., “Multi-source classification using artificial neural network in a rugged terrain” Geocarto Int., 16(3): 37-44, 2001.
[44]   | Saha, A.K., Arora, K.M., Csaplovic, E. and Gupta, R.P., “Land cover classification using IRS LISS III image and DEM in a rugged terrain. A case study of Himalayas”, Geocarto Int. 20(2): 33-40, 2005.
[45]   | Anderson, R.J., Hardy, E.E., Roach, J.T. and Witmer, R.E., “A land use and land cover classification system for use with remote sensor data”, United States Geological Survey, United States Government printing office, Washington, 1976.
[46]   | Stehman, S., “Estimating the kappa coefficient and its variance under stratified random sampling.Photagrammetric engineering and remote sensing”,401-407, 1996, https://www.asprs.org.asprs.
[47]   | Pontius, R.G., “Quantification error versus location error in comparison of categorical maps”, Photogrametric engineering and remote sensing, 66(8): 1011-1016, 2000.
[48]   | Landis, J. and Koch, G., “The measurement of observer agreement for categorical data”, Biometrics 33:159-174, 1977.
[49]   | Carletta, J., “Assessing agreement on classification tasks.The kappa statistics”, Comput. Linguist, 22, 249-254, 1996.
[50]   | Zhu, C. and Li, Y., “Long-term hydrological impacts of land use/land cover change from 1984-2010 in the Little River Watershed, Tennessee”, International soil and water conservation research, Vol. 2, No.2, pp. 11–22, 2014.
[51]   | Obiero K., “The influence of geomo-hydrometric characteristics and land use/land cover change on water resources management in River Gucha-Migori catchment, Lake Victoria Basin, Kenya”, Unpublished PhD Thesis, Kenyatta University, 2010.
[52]   | Oyedotun, T.D.T., “Land use change and classification in Chaohu lake catchment from multi-temporal remotely sensed images”, Journal of geology, ecology and landscapes, 2018.
[53]   | Kitheka, J.U., Mwangi, S. and Mwendwa, P.K., “The effects of rainfall variability and land use/land cover change in a small tropical river basin in Kenya” International journal of hydrology, 3(1), 2019.
[54]   | Cheruto, M.C., Kauti, M.K., Kisangau, P.D. and Kariuki, P. (2016). “Assessment of land use/land cover change using GIS and Remote Sensing techniques. A case study of Makueni County, Kenya”, J. remote sensing and GIS, 5: 175, 2016.
[55]   | Panwar, S. and Malik, D.S., ”Evaluating land use/land cover change dynamics in Bhimtal Lake catchment area, using remote sensing and GIS techniques” J.remote sensing and GIS, 6:199, 2017.
[56]   | Butt, A., Shabbir, R., Ahmed, S.S. and Aziz, N.,”Land use change mapping and analysis using remote sensing and GIS. A case study of Sinily watershed, Islamabad, Pakstan”, The Egyptian journal of remote sensing and space science, vol. 18, issue 2,251-259, 2015.