Integration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia

The planet earth is very dynamic due to continuous interaction with human beings. Human beings overexploit the natural resources for the sake of well-being. The overexploitation of natural resources leads to environmental problems.

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Integration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia - Applied Geomatics

Rapid urbanization and population growth are the main problems faced by developing countries that lead to natural resource depletion in the periphery of the city. This research attempts to analyze the impacts of urban land use land cover (LULC) change on land surface temperature (LST) from 1991 to 2021 in Jimma city, southwestern Ethiopia. Landsat Thematic Mapper (TM) 1991, Landsat Enhanced Thematic Mapper Plus (ETM +) 2005, and Landsat-8 Operational land imagery (OLI)/Thermal Infrared Sensor (TIRS) 2021 were used in this study. Multispectral bands and thermal infrared bands of Landsat images were used to calculate LULC change, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and LST. The LULC of the study area was classified using a supervised classification method with the maximum likelihood algorithm. The results of this study clearly showed that there is a negative correlation between vegetation cover and LST. The decrease in vegetation coverage and expansion of impervious surfaces lead to elevated LST in urban areas. The loss of vegetation cover contributed to the increasing trend of LST. Moreover, the conversion of vegetation cover to impervious surfaces aggravates the problem of LST. The results revealed that the built-up area was increased at a rate of 0.4 km2/year from 1991 to 2021. The vegetation cover in the city declined due to urban expansion to the periphery of the city. Consequently, the dense vegetation and sparse vegetation were converted into built-up areas by approximately 5.2 km2 during the study period. The mean LST of the study area increased by 10.3 °C from 1991 to 2021 during the winter season in daytime. To improve the problems of climate change around urban areas, all stakeholders should work together to increase the urban green space coverage, which will contribute a significant role in mitigating LST and the urban heat island effect. More specifically, all residents could be accessible to public green spaces around big cities.

Rapid urbanization and population growth are the main problems faced by developing countries that lead to natural resource depletion in the periphery of the city. This research attempts to analyze the impacts of urban land use land cover (LULC) change on land surface temperature (LST) from 1991 to 2021 in Jimma city, southwestern Ethiopia. Landsat Thematic Mapper (TM) 1991, Landsat Enhanced Thematic Mapper Plus (ETM +) 2005, and Landsat-8 Operational land imagery (OLI)/Thermal Infrared Sensor (TIRS) 2021 were used in this study. Multispectral bands and thermal infrared bands of Landsat images were used to calculate LULC change, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and LST. The LULC of the study area was classified using a supervised classification method with the maximum likelihood algorithm. The results of this study clearly showed that there is a negative correlation between vegetation cover and LST. The decrease in vegetation coverage and expansion of impervious surfaces lead to elevated LST in urban areas. The loss of vegetation cover contributed to the increasing trend of LST. Moreover, the conversion of vegetation cover 
to impervious surfaces aggravates the problem of LST. 
The results revealed that the built-up area was increased at a rate of 0.4   km2/year from 1991 to 2021. The vegetation cover in the city declined due to urban expansion to the periphery of the city. Consequently, the dense vegetation and sparse vegetation were converted into built-up areas by approximately 5.2   km2 during the study period. The mean LST of the study area increased by 10.3 °C from 1991 to 2021during the winter season in daytime. To improve the problems of climate change around urban areas, all stakeholders should work together to increase the urban green space coverage, which will contribute a significant role in mitigating LST and the urban heat island efect. More specifcally, all residents could be accessible to public green spaces around big cities.

Introduction

The planet earth is very dynamic due to continuous interac-tion with human beings. Human beings overexploit the natu-ral resources for the sake of well-being. The overexploitation of natural resources leads to environmental problems. The declining of vegetation cover and an increasing of impervious surfaces are some of the key evidence of environmental problems like land surface temperature (LST) in many cities (Nwakaire et al. 2020; Ayanlade et al. 2021; Ejiagha et al. 2022). Because of continuous land use land cover (LULC) change, our climate system is diferent from usual which may afect sustainable development. The LULC change plays a crucial role in determining the urban heat islands in a city (Avashia et al. 2021).

Rapid urbanization and population growth are the key  driving forces for natural resource extraction and LULC change worldwide (Abebe et al. 2019; Negassa et al. 2020; Akirso 2021; Moisa and Gemeda 2021). Informal settlements and squatter settlements in urban and peri-urban areas enhance LULC change (Abebe et al. 2019; Akirso 2021). Moreover, anthropogenic-driven LULC has infuenced global and regional patterns of climate change (Ramachandra et al. 2012) as well as urban environmental problems, mainly human health issues (McDade and Adair 2001; Avashia et al. 2021). Changes in LULC are the major driving factors for the increasing trends of temperature in southwestern parts of Ethiopia (Gemeda et al. 2021, 2022; Moisa et al. 2022c). Rapid population growth and increas-ing prices of the house are some of the main driving forces for the rapid conversion of LULC around big cities. Akirso (2021) and Abebe et al. (2019) identifed that the scarcity of residential housing that is suitable for urban residents, resulting in a high rent price and the desire to own a large plot of land to create an open space around the residential neighborhood or sell it later for a large proft, is the major driver of squatter settlement in Jimma city.

The main efect of urban growth on vegetation cover in urban microclimates is the rise in LST (Igun and Williams 2018). Studies showed that LST is increasing due to the replacement of natural surfaces with the impervious surface in cities (Guo et al. 2012; Igun and Williams 2018; Khan et al. 2020; Qu et al. 2020; Naima and Kafy 2021; Abulibdeh 2021; Dewan et al. 2021; Moisa et al. 2022a). Jimma city is one of the largest cities in the southwestern part of Ethiopia, experiencing rapid urbanization and population growth (Fufa et al. 2021). The key concerns of urbanization in the study area include unplanned dwelling developments, small enterprises, infrastructure development, and environmental challenges (Dibaba and Leta 2019). Furthermore, built-up areas show an increasingly positive trend over time, whereas grassland, vegetation, agriculture, and wetlands experienced a declining trend (Abebe et al. 2019; Fufa et al. 2021).Realizing a temporal relationship between LULC change and LST is useful for natural resource managers and environ-mental experts to manage natural settings in a sustainable and healthy manner. Studies by Wolteji et al. (2022) in the central Rift Valley region of Ethiopia indicate that there is an inverse relationship between LST and the level of vegetation greenness or NDVI. Several studies (Abebe et al. 2019; Dibaba and Leta 2019; Akirso 2021; Fufa et al. 2021) have concluded that urbanization has resulted in the loss of vegetation cover, agricultural land, and wetlands. A previous study by Abebe et al. (2019) reported that squatters and informal settlements are the key challenges of Jimma city. The decline in vegetation cover is another environmental challenge that gets the attention of stakeholders (Merga et al. 2022; Moisa et al. 2022b, c). All previous studies concentrated on LULC change, while little attention was given to the impact of urban LULC change on urban microclimate, particularly the LST. Moreover, less emphasis was given to integrate geospatial technologies and multiple regression model to assess the impact of LULC change on urban LST. The present study aims to address this research gap by analyzing the impacts of urban LULC change on LST using the integration of geospatial techniques and multiple regression models.

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Go to the profile of Mitiku Badasa Moisa
about 1 year ago

I I am pleased to announce my latest research article titled, "Integration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia," in the Applied Geomatics.

Article link: https://doi.org/10.1007/s12518-022-00463-x

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The main aim of this issue is to create a multi-disciplinary cross-fertilization with the scientific communities of Geomatics in response to related built environment issues, challenges and solutions by addressing potentialities and criticalities offered by Earth Observation and ground local data integration. The rapid transformation of land use in urban and natural areas, under climate change threats and anthropic pressures require to foster sustainable planning, decision-making and simulation scenarios to mitigate and reverse on course phenomena in the framework of SDGs. In today’s field of built-environmental management, effectively tracking land‐use changes at both global and local levels is becoming a crucial point for the success of climate goals on the impact of actions; particularly with respect to regenerative practices that aim to reverse degradation processes, at a global scale, i.e the LULUCF -Land Use Land Use Change and Forestry framework, within the DeCarbon objectives, – requiring a tuning at a locale scale; as well as to urban domain in better addressing soil use consumption reduction and increasing the adoption of nature based solutions (NBS). In these decades EO-based monitoring methodologies highlighting desertification trends contributed to clarify the extent of the phenomena, their distribution, main challenging areas, their global evolution on a small scale, therefore constitute an important and valuable starting point available to all users being applicable to the whole planet. Nowadays, we need entering a new phase in which, given the worldwide dimension of the phenomena including risks and consequences now tangible, the stakeholders as PAs, professionals as planners, architects, engineers, farmers, citizens communities and associations, require punctual site-specific decoding to try to reverse and slow down the phenomenon with local punctual actions, fostering methodologies supporting common knowledge based on the specificity and diversity of the places within the global analysis. Efforts and experiences have contributed to the development of a complex set of concepts, which encourage the crossing of the different experiments that take place 'in the field' to accelerate results, to bring together different experiences by finding reliable indicators. Geomatics can contribute with an added value to supporting innovation and knowledge in connections with a multifaceted multi-disciplinary contribution. Here after a proposed list of Topics but not limited to: • EO and ground data integration for urban, periurban and land use change analysis • AI, machine learning, and big data analytics in geomatics for climate resilience • GIS and remote sensing applications in urban planning and sustainability • Smart cities and digital twins for real-time monitoring and decision-making • Geospatial modeling and simulations for climate adaptation and mitigation strategies • Multi-scale-multi-temporal Land Use Change Assessment and Monitoring; • Land Use, Land Use Change and Forestry (LULUCF), Global and local Land Monitoring, platforms and applications; Innovation in Canopy management and Soil Use Classification; Increasing resolution in LULUCF domain for Decarbon and GHG related goals; • Shifting Land Degradation and Land Desertification into Restoration and Regenerative Agriculture at a G-Local scale, SOIL Health Descriptors; Precision Farming; • Urban-Periurban SOIL Challenges, monitoring and Nature Based Solutions. • Built-Environment, impact of infrastructures and NBS on renaturation and DeCarbon (as Dams, Urban de-pavements); • 3D Land(scape) surveying and analysis; • Risk management and simulation, and Indicators (as in the Mediterranean System); • Scales and specifications in the G-Local new framework; Maps Accuracies, Validation and Calibration; • Remote Sensing and Earth Observation, sensors, satellite data (as Copernicus, Landsat, Google Earth, high res data); Platforms, Tools, Application (as rGEE/GEE) EO based Multi-temporal time series and analysis; Algorithms, as Change Detection, etc., Multivariate Analysis; • Climate change threats, hydrogeological, seismic risk and resilience management in Built Environment domain; • Data analysis, informative models and systems integration: remote sensing and UAVs; on site management and monitoring, tools, APPs and devices; • MMS, GeoSLAM, multi-spectral UAV-APR drones, Geolocation, GNSS, Low-cost IOT sensors; • Digital Twins and monitoring platforms, Web-GIS data applications; eXtended Reality (VR/AR/MR) rising awareness of challenges and solutions; • Training activities, internship programmes, building capacities and value chains.

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