Impact of Spatial Filter on Land-Use Changes Modelling Using Urban Cellular Automata

Omidipoor, Morteza; Samani, Najmeh Neysani

doi:10.5194/isprs-archives-xlii-4-w4-429-2017

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…It is among the best method and technique for quantity estimation, spatial and temporal dynamic modeling of LULC changes since GIS and remote sensing data can be well integrated to give a meaningful outcome (Kamusoko et al, 2009). In this model, the MC tool is used to produce transitional probabilities statistics, transitional area statistics and conditional transition images data which are used as inputs to predict the later state of the particular pixels over space basing on the condition, location and proximity of the neighboring pixel in CA model (Aithal et al, 2014;Arsanjaniet al, 2011;Beheraet al, 2012;Deep, 2014;Houet et al, 2007;Marko et al, 2016;Omidipoor et al, 2017;Yang et al, 2015).…”

Section: Camarkov Chain Modelmentioning

confidence: 99%

“…The collected satellite images were used to determine the change in land use/land cover of the area over time within thirty years (19862016). The classified satellite images were also used to predict the condition of land use /land cover condition in 10 years later in the MarkovCellular Automata dynamic model (MCA) (Aithal et al, 2014;Behera et al, 2012;Deep, 2014;Houet et al, 2007;Marko et al, 2016;Omidipoor et al 2017;Yang et al, 2015).…”

Section: Sources Of Data and Data Collectionmentioning

confidence: 99%

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Land use change and temporal water quality dynamics on the slopes of mount Meru

Kitalika

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This work reports on the results obtained following the study on the land use change and temporal water quality change in rivers of the slopes of Mount Meru in Northern Tanzania between 2015 and 2016. Satellite images collected from United States Geological Survey (USGS) were used to model the land use change using ArcGIS and IDRISI software. Also, 419 water samples and two (2) rocks samples were collected from various geo-referenced points and assessed for sixteen (16) water quality changes using standard methods for water and wastewater from American Public and Health Association (APHA). The stable isotope studies were done at the University of Waterloo stable isotopes laboratory using the Los Gatos Research Laser processes analyzer with Integrated Cavity Output Spectroscopy (LGRICOS™). The study showed significant land use changes in the area in every ten (10) years over a period of thirty (30) years such that, there is an increase in human settlement from 74.2 km 2 (1986) to 261.2 km 2 (2016), decrease in agricultural land from 545.8 km 2 to 531.5 km 2 (2016). Also, in similar years the bush-land decreased from 372.3 km 2 (1986) to 158.4 km 2 (2016) in favour of increase of settlement. Moreover, the mixed forest were improved from 139.7 km 2 (1986) to 116.0 km 2 (2016) whereas the water bodies decreased significantly from 14.0 km 2 (1986) to 4.2 km 2 (2016). In addition, the water quality in rivers deteriorated due to increased human activities, poor performing Wastewater Treatment Systems (WTS) which discharge its effluents in rivers, and bad agricultural practices. Few sampling points in rivers had Biochemical Oxygen Demand (BOD), NO 3  and Total Soluble Phosphate (TSP) levels higher than the World Health Organization (WHO) standards of 10 mg/L, 50 mg/L and 0.1 mg/L, respectively. Fluoride contamination in Themi, Nduruma and Tengeru Rivers were within the WHO and Tanzania Bureau of Standards (TBS) maximum acceptable limits of 1.5 mg/L and 4.0 mg/L, respectively. Maji ya Chai River showed the highest levels of fluorides and dissolved organic matter of up to 69.01 ± 0.03 mg/L and 10 ± 0.2 mg/L, respectively, which are higher than the WHO standards. The study confirmed the main source of fluorides in water is rocks containing fluoride in which its leaching is favoured in alkaline environment. Also the stable isotopes studies revealed the origin of Dissolved Organic Matter (DOM) were plant materials and soil composites whereas NO 3  originated from wastewater, urea fertilizers, and animal manures. The major sources for coloured dissolved organic matter and fluoride contents in Maji ya Chai River were discovered at Kirurumu hill (M1) and Jamera (M2), respectively.

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Section: Camarkov Chain Modelmentioning

confidence: 99%

Section: Sources Of Data and Data Collectionmentioning

confidence: 99%

Land use change and temporal water quality dynamics on the slopes of mount Meru

Kitalika

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Land-Use and Land Cover Changes on the Slopes of Mount Meru-Tanzania

Kitalika

Machunda

Komakech

et al. 2018

Curr. World Environ

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The study of spatial land use and land change is inevitable for sustainable development of land use plans. Environmental transitions analysis was done in part of the land on the slopes of the foothills of Mount Meru in thirty (30) years’ time from 1986 to 2016 using satellite-derived land use/cover maps and a Cellular Automata (CA) spatial filter under IDRISI software environment and assessed the important land use changes. Also, the future land use for 2026 which is the next ten (10) years was simulated based on Cellular-Automata Markov model. The results showed significant land use transitions whereby there is a huge land use change of bush land (BL) and agriculture land (AG) into human settlement (ST) which resulted into conversion of Arusha town into a City. In addition, the changes have caused slight changes in water bodies into mixed forest. Moreover, the future land use/land cover (LULC) simulations indicated that there will be unsustainable LULC changes in the next ten years since most of bush land and part of agriculture land will be used for building different structures thus interfering with fresh water and food availability in the City. These changes call upon the relevant planning authorities to put in place the best strategies for good urban development.

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Impact of Spatial Filter on Land-Use Changes Modelling Using Urban Cellular Automata

Cited by 2 publications

References 10 publications

Land use change and temporal water quality dynamics on the slopes of mount Meru

Land use change and temporal water quality dynamics on the slopes of mount Meru

Land-Use and Land Cover Changes on the Slopes of Mount Meru-Tanzania

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