Impact Of Land Use And Land Cover Change Research Articles

Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China

The Yellow River basin of China has experienced significant land use and land cover change (LUCC) due to excessive exploitation of nature resources, ecological degradation, and rapid urbanization, which plays an important role in the regional climate. It is crucial to explore the climate patterns of the basin under different future development scenarios to mitigate climate issues and achieve “carbon peaking and carbon neutrality goals”. Here we utilized land use and land cover (LULC) data and projections of future climate under two shared socioeconomic path – representative concentration path (SSP245 and SSP585) scenarios. Using the Weather Research and Forecasting (WRF) model, we simulated four future spatial variation patterns of temperature and precipitation in the basin. Results indicated that under the SSP245 and SSP585 scenarios, the temperature is projected to increase by 0.18 °C and 0.46 °C, respectively, while precipitation is expected to rise by 32.21 mm and 134.24 mm, respectively. The impact of LUCC was found to be relatively minor and mainly concentrated in the middle reaches of the basin. It resulted in a slight increase in temperature in both scenarios and an increase in precipitation in SSP245, but a decrease in precipitation in SSP585. Changes in farmland and urban area exhibited a certain warming effect in both scenarios, with urban areas having a greater influence, leading to a temperature increase by 0.25 °C and 0.28 °C, respectively. Forest, grassland, and bare areas had a lesser impact on temperature and showed different trends under two scenarios. Regarding precipitation, forests and urban areas had a greater influence in both SSP245 and SSP585 scenarios. This study identified the significant role of LUCC under different development scenarios in shaping future temperature and precipitation changes, providing valuable insights for effectively addressing climate issues in the Yellow River basin. It also highlights the need for clear policy recommendations and identifies institutions or agencies responsible for implementing such recommendations.

Assessing the Influence of Land Use and Land Cover (LULC) Changes on Hydrological Response of the Timah-Tasoh Reservoir

Changing patterns in land use and land cover (LULC) is potentially due to development pressure. Due to the increase in LULC change, it alters natural ecosystems and changing the composition of the natural ecosystem services. This study provides evidence to support the hypothesis that LULC can influence both inflow and discharge. The objectives of the study were to measure the impact of LULC change on inflow of the Timah-Tasoh reservoir. The study area land cover was reclassified into five categories which included agriculture, built-up areas, forest, vacant land, and water bodies. Based on the effect of LULC on hydrological response, it is observed that the catchment is not sensitive to changes in LULC. Two mains of LULC scenarios were used including deforestation and afforestation. With an increase in CN to 89.26 (deforestation), the inflow rate increases by 2% (342.20 m3/s) compared to the present inflow rate. Meanwhile, the inflow rate will decrease to 0.21% (334.80 m3/s) if the CN value is 80.02 (afforestation). Thus, by using this study’s results, a better method and parameters compatible with another hydrological modelling can be developed for future study.

Impact of Land Use/Cover Changes on Soil Erosion by Wind and Water from 2000 to 2018 in the Qaidam Basin

Assessing the impact of land use and land cover change (LUCC) on soil erosion by wind and water is crucial for improving regional ecosystem services and sustainable development. In this study, the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE) were used to reveal changes in the extent of soil erosion by wind and water in the Qaidam Basin from 2000 to 2018 and the impact of LUCC on them. From 2000 to 2018, with global climate change, the areas and intensities of soil erosion by wind decreased, whereas those of soil erosion by water increased. With increased human activities, approximately 12.96% of the total area underwent conversion of the type of use: the areas of cropland, woodland, grassland, and construction land increased, whereas the areas of shrubbery, desert, and other unused land decreased. Land use/cover changes are positive to the soil erosion of water but negative to the soil erosion of wind. Among them, the changes in vegetation coverage of other unused land and grassland contributed to 83.19% of the total reduction in soil erosion by water. Converting other unused land to grassland reduced the total reductions in soil erosion by wind by 94.69%. These results indicate that the increase in vegetative cover and area of grasslands in the Qaidam Basin had a positive impact on the reduction in soil erosion. It is recommended that the arrangement of grasses, shrubs, and trees be optimized to prevent compound erosion by wind and water for protecting regional ecological environments.

Land Use and Land Cover Change Modulates Hydrological Flows and Water Supply to Gaborone Dam Catchment, Botswana

Identifying the mechanism through which changes in land use and land cover (LULC) modulate hydrological flows is vital for water resource planning and management. To examine the impact of LULC change on the hydrology of the Gaborone Dam catchment within the upper Limpopo basin, where Notwane river is the major river within the catchment, three LULC maps for the years 1997, 2008, and 2017 were established based on a mosaic of Landsat 5 for 1997 and 2008 and Landsat 8 for 2017. The 10 m-resolution Version 200 ESA World Land Cover Map for 2021 is used as a ground truth to train the random forest (RF) classifier to identify land cover classes from Landsat 8 imageries of 2021 using the Google Earth Engine (GEE) Python API. The overall accuracy/kappa coefficient of the RF classifier is 0.99/0.99 for the training and 0.73/0.68 for the validation data sets, which indicate excellent and substantial agreements with the ground truth, respectively. With this confidence in the LULC classification, the impact of LULC change on the hydrological flow within the catchment was estimated by employing the Soil and Water Assessment Tool (SWAT) and indicator of hydrological alteration (IHA). The SWAT model calibration and validation were first performed, and the ability of the model to capture the observed stream flow was found to be good. The LULC maps from Landsat images during the 1997–2017 period show a decrease in forests and shrubland in contrast to an increase in pasture land. The expansion of pasture and cropland and the reduction in forests and shrubland led to a decline in the amount of evapotranspiration and groundwater recharge. Furthermore, the LULC change also caused a reduction in low flow during dry periods and an increase in high flow during the rainy season. The findings clearly demonstrate that LULC changes can affect the water table by altering soil water recharge capacity. The study highlighted the importance of LULC for catchment water resource management through land use planning to regulate the water level in the Gaborone Dam against the impact of climate change and growing water demands by the city of Gaborone due to population growth.

Spatiotemporal variations and risk characteristics of potential non-point source pollution driven by LUCC in the Loess Plateau Region, China

With increasing human activities, regional substrate conditions have undergone significant changes. These changes have resulted in temporal and spatial variations of non-point source pollution sources, which has a significant impact on the quality of the regional soil, surface water, and groundwater environments. This study focused on the human-disturbed Loess Plateau region and used an enhanced potential non-point-source pollution index (PNPI) model to explore the dynamic changes of regional potential non-point-source pollution (PNP) and the associated risk due to land use and land cover change (LUCC) over the past 31 years. The Loess Plateau region is mainly composed of cultivated land, grassland and forest, which together account for 93.5% of the watershed area. From 1990 to 2020, extensive soil and water conservation measures were implemented throughout the Loess Plateau region, resulting in a significant reduction in the non-point source pollution risk. Using the quantile classification method, the study area’s PNP risk values were categorized into five distinct levels. The results revealed a polarization phenomenon of PNP risk in the region, with an increase in non-point source pollution risk in the human-influenced areas and a rapid expansion of the very high-risk area. However, the non-point source pollution risk in the upstream water source area of the watershed reduced over the study period. In recent years, the rapid urbanization of the Loess Plateau region has been the primary reason for the rapid expansion of the very high PNP risk area throughout the watershed. This study highlights the significant impact of LUCC on the dynamic changes in PNP risk within the Loess Plateau region, providing crucial insights into future conservation and urban planning policies aimed at enhancing the ecological health and environmental quality of the region.

Assessing Impacts of Land Use and Land Cover (LULC) Change on Stream Flow and Runoff in Rur Basin, Germany

Understanding the impact of land use/land cover (LULC) change on hydrology is the key to sustainable water resource management. In this study, we used the Soil and Water Assessment Tool (SWAT) to evaluate the impact of LULC change on the runoff in the Rur basin, Germany. The SWAT model was calibrated against the observed data of stream flow and runoff at three sites (Stah, Linnich, and Monschau) between 2000 and 2010 and validated between 2011 and 2015. The performance of the hydrological model was assessed by using statistical parameters such as the coefficient of determination (R2), p-value, r-value, and percentage bias (PBAIS). Our analysis reveals that the average R2 values for model calibration and validation were 0.68 and 0.67 (n = 3), respectively. The impacts of three change scenarios on stream runoff were assessed by replacing the partial forest with urban settlements, agricultural land, and grasslands compared to the 2006 LULC map. The SWAT model captured, overall, the spatio-temporal patterns and effects of LULC change on the stream runoffs despite the heterogeneous runoff responses related to the variable impacts of the different LULC. The results show that LULC change from deciduous forest to urban settlements, agricultural land, or grasslands increased the overall basin runoff by 43%, 14%, and 4%, respectively.

Quantitative assessment of land surface temperature and vegetation indices on a kilometer grid scale.

Due to expanding populations and thriving economies, studies into the built environment's thermal characteristics have increased. This research tracks and predicts how land use and land cover (LULC) changes may affect ground temperatures, urban heat islands, and city thermal fields (UTFVI). The current study examines land surface temperature (LST), urban thermal field variance index (UTFVI), normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), and land use land cover (LULC) on a kilometer scale. According to the comparative study, the mean LST decreases by 3°C and the NDVI increases considerably. Correlation analysis showed that LST and NDVI are inversely connected, while LST and NDBI are positively correlated. NDVI and NDBI have a strong negative association, while LST and UTFVI have a positive correlation. Urban planners and environmentalists can study the LST's effects on land surface parameters in different environmental contexts during the lockout period. The urban heat island (UHI) phenomenon, in which the land surface qualities of an urban region cause a change in the urban thermal environment, forms and intensifies over an urban area. The minimum and maximum LST in grid number 1 in 2009 was 20.30°C and 29.91°C, respectively, with a mean LST of 25.1°C. There was a decline in the minimum and maximum LST in grid number 1 in 2020 with a minimum and maximum LST of 17.31°C and 25.35°C, respectively, with a mean LST of 21.33°C. There was a 3.8°C drop in the LST of this grid. The minimum and maximum NDVI were also - 0.16 and 0.59, respectively, with an average NDVI value of 0.21. Therefore, it is essential to evaluate and foresee the impact of LULC change on the thermal environment and examines the connection between LULC shifts with subsequent changes in land surface temperature (LST) along with the UHI phenomenon. Maps of the UTFVI reveal positive UHI phenomena, with the highest UTFVI zones occurring over the developed area and none over the adjacent rural territory. During the summer months, the urban area with the strongest UTFVI zone grows noticeably larger than it does during the winter months during the forecasted years. Future policymakers and city planners can mitigate the effects of heat stress and create more sustainable urban environments by evaluating the expected distribution maps of LULC, LST, UHI, and UTFVI.

Terrain gradient response of landscape ecological environment to land use and land cover change in the hilly watershed in South China

There are abundant resources like climate, water, biological and tourism in the middle and upper reaches of the Ganjiang River (MU-GJR), which is an important ecological protection area in hilly areas of South China. The four periods of land use and land cover (LULC) data from 1980 to 2018 and DEM data are the main data support. The LULC change were analyzed with the area proportion, transfers chord diagram and change characteristics map, the response of ecological environment from LULC change was analyzed by using the landscape ecological environment quality (LEEQ) and contribution index. Then the terrain gradient was used to analyze the impact of LULC transfer on ecological environment under different terrain conditions. (1) The LULC characteristics in the study area show that was dominated by forest land and cultivated land (more than 90 %), various types of land transfer significantly from 2010 to 2018, especially the cultivated land, forest land and grassland. The stable type of LULC change was the most widely distributed, followed by the later change type (2010–2018) and mainly distributed in the flat valley, with the largest change range of cultivated land, forest land and grassland. (2) The LEEQ was generally well, but gradually deteriorates. The obvious change of LEEQ was found after 2010. The deterioration type of quality mostly occurs around the city, while the getting better type occurs in the transition area between the city and the mountains. (3) There are more deterioration categories than improvement categories of LULC transfer from 1980 to 2018. The improvement categories were mainly contributed by the transfer to other land to forest land and build-up land to other land. The deterioration categories were mainly contributed by the transfer of forest land to other land. (4) The impact of LULC change on the ecological environment decreases with the increase of elevation, slope and terrain position. There are differences in the impacts of various types of transfer on the ecological environment under the three gradients. In the elevation gradient, the improvement effect were dominant at −105–100 m and 200–500 m, and the deterioration effect were dominant at 100–200 m, 500–1000 m and 1000–2128 m. In the slope gradient, the improvement effect were dominant at 0–2°, 15–25° and 25–69.7°, and the deterioration effect were dominant at 2–6° and 6–15°. In terrain position gradient, improvement effect were dominant at 0–0.32, 0.32–0.51, 0.7–0.9 and 0.9–1.58, and deterioration effect were dominant at 0.51–0.7. Therefore, the specific conditions of different terrain gradients should be considered for land resource development in the middle and upper reaches of Ganjiang River region.

Effect of Land Use-Land Cover Change on Soil Erosion and Sediment Yield in Muger Sub-Basin, Upper Blue Nile Basin, Ethiopia

Land use and land cover (LULC) change have intense implications on soil resources, that requires research attention and global collaboration to take urgent actions. The present study attempted to analyze the impact of LULC change on soil erosion and sedimentation in Muger Sub-basin, southwestern parts of Ethiopia. Landsat TM 1986, Landsat ETM+ 2003, and Landsat OLI/TIRS 2020 are used for LULC analysis. We used rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices to calculate soil erosion and sedimentation between 1986 and 2020. In this study, the integration of revised universal soil loss equation (RUSLE) model and geographic information system (GIS) are used to analyze the impact of LULC change on soil erosion and sedimentation. The average soil loss rate is about 53.2 ton/ha/year in 1986 and increased to 63.6, and 64 ton/ha/year in 2003, 2020, respectively. Result revealed that about 2707.7 ha (33%), 3124.5 ha (38.1%) and 3197.4 ha (38.9%) were exposed to severe erosion in 1986, 2003 and 2020, respectively. The mean sediment yields of the study area is estimated to 7.8 ton/ha/year in 1986, and later increased to 10, and 10.2 ton/ha/year in 2003, and 2020, respectively. Results revealed that the steep slope areas with crop land experience considerable soil loss, with mean soil loss increasing over all study period. Thus, urgent policy on the wise use of natural resources is essential not optional to reduce the current soil loss and sedimentation in Muger Sub-basin.

Use of support vector machine and cellular automata methods to evaluate impact of irrigation project on LULC.

Land use and land cover (LULC) both define the earth's surface both anthropogenically and naturally. It helps maintain global balance but changes in land use create inequality. The LULC modification adversely affects physical parameters such as infiltration, groundwater recharge, surface runoff, ground temperature, and air quality. It is high time to monitor land use changes globally. Remote sensing and GIS techniques help to monitor these changes with a low budget and time. Various types of LULC classifiers have been invented to classify the LULC types. Maximum likelihood is a popular LULC classifier, but nowadays, support vector machine (SVM) classifier is gaining popularity because it provides a more accurate LULC than the maximum likelihood classifier. Therefore, in this study, the SVM classification technique has been applied to produce good accuracy LULC maps. Using the SVM classifier, six LULC maps are produced from 1995 to 2020 for the Shali reservoir area in India which is a medium irrigation project irrigating ~ 3211 hectares of land per year. It plays an important role in the agricultural production of the region by providing irrigation water in monsoon and post-monsoon seasons. The impact of LULC change on the environment is also studied. The LULC forecast maps are also created using the cellular automata (CA) model and MOLUSCE plugin. Kappa coefficient and validation methods are used to validate the LULC and simulated maps. Both maps produce high accuracy with a kappa coefficient of 0.9. Secondary data, collected from the governmental gazette, such as population, crop production, and water level is also used to justify the results. The simulated map shows that 4% of agricultural land and built-up area may increase from 2020 to 2030. Overall, it has been proven that the SVM and CA models can produce accurate classified results.

Landscape Impacts on Ecosystem Service Values Using the Image Fusion Approach

The landscape is a complex mosaic of physical and biological patches with infrastructures, cultivable lands, protected ecosystems, water bodies, and many other landforms. Varying land-use changes are vulnerable to the world and need the mitigation and management of landforms to achieve sustainable development, which without proper oversight, may lead to habitat destruction, degradation, and fragmentation. In this study, we quantify the land-use and land-cover (LULC) changes using downscaled satellite imagery and assess their effects on ecosystem services (ES) and economic values in Ningxia Province, China. Various landscape metrics are derived to study the pattern and spatial configuration over 15 years (2005–2020), in which the landscapes are evolving. The impact of LULC change in various ES is analyzed using ecosystem service values (ESV) and validated with a sensitivity index. Finally, the level of urban sprawl (US) due to overpopulation is established using Renyi’s entropy. Using Landsat 8′s Operational Land Imager (OLI) datasets, we downscaled the MODIS data of 2005, 2010, 2015, and 2020 to prepare the LULC map through a rotation forest algorithm. Results demonstrate that water bodies, woodlands, and built-up landscapes increased in their spatial distribution over time and that there was a decrease in farmlands. Results further suggest that the connectivity and uniformity of the landscape pattern improved in the later period due to several plans formulated by the government with a slight improvement in landscape diversity. Overall ESV get improved, while LULC classes such as farmland and water bodies have decreased and increased ESV, respectively, and a sensitivity analysis is used to test the reliability of ESV on LULC classes. The level of US is 0.91 in terms of Renyi’s entropy, which reveals the presence of a dispersion of settlements in urban fringes. The simulated US for 2025 shows urbanization is more severe over a prolonged time and finally the impacts of the US in ESV are analyzed. Using an interdisciplinary approach, several recommendations are formulated to maintain the ESV despite rapid LULC changes and to achieve sustainable development globally.

Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature.

Assessing Impact of Land Use Change on the Ecosystem Service Value in Yinchuan City from 1980 to 2018

Accurate assessment and response analysis of land use and land cover change (LUCC), and ecosystem service values (ESV), are critical to regional ecological security and economic development. There is a lack of detailed reports on the impact of LUCC on the temporal and spatial evolution of ESV in Yinchuan City, which is inconsistent with the pilot urban design policy. This paper, using the LUCC data of Yinchuan City from 1980 to 2018, calculated the ESV, analyzed the temporal and spatial patterns of LUCC and ESV, and discussed the response of ESV to LUCC. The results show that, from 1980 to 2018, the building land increased significantly in Yinchuan City, as did the cultivated land. Meanwhile, grassland and bare land decreased, while forest and the water body remained stable. The spatial connectivity of the building land showed regular improvements, while the urban landscape developed in a regular and balanced direction. During the study period, the total ESV of Yinchuan City decreased by 0.75 × 109 yuan. This was due to the decrease in grasslands and the increase in building area. The supply, regulation and support of three types of services have a high correlation with different land types. The prosperity and progress of culture reduces the ESV value of cultivated land to some extent, while the change in land use type leads to the significant loss of ESV in Yinchuan City.

Assessment of the impact of LUCC on NPP and its influencing factors in the Yangtze River basin, China

Land use and land cover change (LUCC) will directly affect the types, structures and functions of ecosystems, and then have important impact on vegetation net primary productivity (NPP). The evaluation of the spatio-temporal dynamic changes of LUCC and regional NPP, and assessing the impact of LUCC on NPP can facilitate the corresponding management of different environmental types of regions and provide scientific guidance for scientific development of ecological resources, and better restore and control the ecological environment, thus promoting rapid economic development. Using MODIS normalized difference vegetation index (NDVI) data and meteorological data from 2001 to 2018, combined with Carnegie-Ames-Stanford model (CASA), the regional NPP was estimated, and the influence of LUCC on NPP in Yangtze River basin from 2001 to 2018 and its causes were analyzed. The results showed that the area with a land cover and land use change account for 10.98% of the total study area in the past 18 years, and the most important change is the transformation from grassland to forest and grassland to crop/natural vegetation mosaic (NVM). Forests, wetlands, crop/natural vegetation mosaic, low vegetation cover (LVC) land, urban, and water bodies are growing. The forest land area increased the most and that of grassland decreased the most. Total NPP has increased by 53887.51GgC in the past 18 years, which was due to the combination effect of LUCC change and climate change.

Spatiotemporal LUCC Simulation under Different RCP Scenarios Based on the BPNN_CA_Markov Model: A Case Study of Bamboo Forest in Anji County

Simulating spatiotemporal land use and land cover change (LUCC) data precisely under future climate scenarios is an important basis for revealing the carbon cycle response of forest ecosystems to LUCC. In this paper, a coupling model consisting of a back propagation neural network (BPNN), Markov chain, and cellular automata (CA) was designed to simulate the LUCC in Anji County, Zhejiang Province, under four climate scenarios (Representative Concentration Pathway (RCP) 2.6, 4.5, 6.0, 8.5) from 2024 to 2049 and to analyze the temporal and spatial distribution of bamboo forests in Anji County. Our results provide four outcomes. (1) The transition probability matrices indicate that the area of bamboo forests shows an expansion trend, and the largest contribution to the expansion of bamboo forests is the cultivated land. The Markov chain composed of the average transition probability matrix could perform excellently, with only small errors when simulating the areas of different land-use types. (2) Based on the optimized BPNN, which had a strong generalization ability, a high prediction accuracy, and area under the curve (AUC) values above 0.9, we could obtain highly reliable land suitability probabilities. After introducing more driving factors related to bamboo forests, the prediction of bamboo forest changes will be more accurate. (3) The BPNN_CA_Markov coupling model could achieve high-precision simulation of LUCC at different times, with an overall accuracy greater than 70%, and the consistency of the LUCC simulation from one time to another also had good performance, with a figure of merit (FOM) of approximately 40%. (4) Under the future four RCP scenarios, bamboo forest evolution had similar spatial characteristics; that is, bamboo forests were projected to expand in the northeast, south, and southwest mountainous areas of Anji County, while bamboo forests were projected to decline mainly around the junction of the central and mountainous areas of Anji County. Comparing the simulation results of different scenarios demonstrates that 74% of the spatiotemporal evolution of bamboo forests will be influenced by the interactions and competition among different land-use types and other driving factors, and 26% will come from different climate scenarios, among which the RCP8.5 scenario will have the greatest impact on the bamboo forest area and spatiotemporal evolution, while the RCP2.6 scenario will have the smallest impact. In short, this study proposes effective methods and ideas for LUCC simulation in the context of climate change and provides accurate data support for analyzing the impact of LUCC on the carbon cycle of bamboo forests.

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia.

The ongoing trend toward agricultural intensification in Southern Amazonia makes it essential to explore the future impacts of this development on the extent of natural habitats and biodiversity. This type of analysis requires information on future pathways of land-use and land-cover change (LULCC) under different socio-economic conditions and policy settings. For this purpose, the spatially explicit land-use change model LandSHIFT was applied to calculate a set of high-resolution land-use change scenarios for the Brazilian states Para and Mato Grosso. The period of the analysis were the years 2010-2030. The resulting land-use maps were combined with maps depicting vertebrate species diversity in order to examine the impact of natural habitat loss on species ranges as well as the overall LULCC-induced effect on vertebrate diversity as expressed by the Biodiversity Intactness Index (BII). The results of this study indicate a general decrease in biodiversity intactness in all investigated scenarios. However, agricultural intensification combined with diversified environmental protection policies show least impact of LULCC on vertebrate species richness and conservation of natural habitats compared to scenarios with low agricultural intensification or scenarios with less effective conservation policies.

Impacts of landscape changes on local and regional climate: a systematic review

Studies have shown that land use and land cover change (LUCC) has myriad impacts on local and regional climate. Synthesizing the recent findings in this field helps advance landscape ecology and sustainability science in the face of climate change. To review and synthesize mesoscale modeling-based studies examining the impact of LUCC on climate, and to identify research gaps and future research directions. We adopted a systematic review procedure to identify and analyze relevant literature obtained from the Web of Science spanning Jan 1990–Nov 2018. The number of publications per year increased from about 5 before 2008 to as large as 25 thereafter. About 60% of the case studies were focused on China and the US. Urbanization and agricultural development exerted a stronger influence on temperature than other LUCC modifications, with temperature changes generally between 1 and 2 °C. The climate effect of forest loss and urbanization illustrated location-dependency, as similar landscape changes in different latitudes showed climate effects of opposite sign. Extensive irrigation and dam construction increased precipitation, while the impact of urbanization and forest cover change on precipitation was inconclusive (positive, neutral, and negative). Understanding landscape and climate change interactions is essential for studying the ecology and sustainability of regional landscapes. Future research needs to: (1) understand climate effects resulting from land management change, (2) investigate climate change impacts on human health as induced or mediated by landscape changes, and (3) develop sustainable landscapes that can mitigate and adapt to climate change.

Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh

Urbanization causes enormous land use and land cover (LULC) changes, which creates a significant impacts on land surface temperature (LST) in rapidly growing mega-cities. The substantial increment of the LST creates urban heat island (UHI) effects in cities. This study first identified the pattern of the LULC changes, and later, investigated their impacts on LST in Rajshahi City Corporation (RCC) areas for the years of 1999, 2009 and 2019 using Landsat TM/OLI satellite images. This study explored the impact of LULC change on LST through LST distribution in different land use categories, cross-section profile of LULC wise LST variability, and a correlation between LULC indexes (NDVI, NDBI, NDBaI & NDWI) and LST. The Multi-Layer Perceptron-Markov Chain (MLP-MC) and Artificial Neural Network (ANN) methods were utilized to simulate the LULC and LST maps, respectively, for the years of 2029 and 2039. The accuracy of LULC and LST simulation models are more than 85% and 90% , respectively, based on the validation results. Simulation results show if the current trend of urban growth continues, 70% and 88% of RCC area will experience temperature more than 38 °C in 2029 and 2039, respectively. Such impacts need to be considered and evaluated immediately for ensuring sustainable urbanization and natural resource management in the RCC area. This study will be helpful for urban planners and environmental engineers to understand the impacts of LULC change (e.g. loss of vegetation cover, agricultural land and water bodies to accommodate extensive urban growth) on LST and to propose appropriate policy measures to control it.

Spatio-temporal land use/cover dynamics and its implication for sustainable land use in Wanka watershed, northwestern highlands of Ethiopia

Long -term land use and land cover (LULC) dynamics information is essential to understand the trends and make necessary land management interventions, such as in the highlands of Ethiopia. This study analyzed six decades of LULC dynamics of Wanka watershed, Northwestern Ethiopian highlands. Two sets of aerial photographs (1957 and 2017), SPOT 5 and sentinel satellite imageries were analyzed. In addition, key informant interviews, focus group discussions and field observations were used to identify the drivers and impact of LULC change. It was found that cultivated and rural settlement land (CRSL), bare land, and urban built up area have been continuously expanded at the expenses of mainly forest and shrub lands. Over the entire study period (1957–2017) while the bare land and CRSL have increased by about 59% and 20% respectively, forest and shrub lands have declined by 59% and 57% respectively. Urban built up area has also expanded. The impact of population pressure and expansion of CRSL land were considerable. The trend of LULC dynamics in the study watershed implies adverse impact on the quality and quantity of the land resource. Hence, appropriate land use planning and strategies that reduce expansion of cultivated land need to be practiced.

Modelling the impact of land use management on water resources in a tropical inland valley catchment of central Uganda, East Africa

A combination of climate change, food demand, population growth, and other driving forces are causing land use and land cover change (LULC) in wetlands of Sub Saharan Africa (SSA). This has a profound effect on water resources, thus it is imperative that such consequences arising from these changes are predicted accurately to support land use management. For that, local scale studies are required to understand the system and to perform scenario analysis. The focus of this study was on small scale inland valleys which are common in SSA. The impact of LULC on the hydrological processes in a tropical inland valley was investigated. A hydrological response unit (HRU)-based (ArcSWAT2012) and a grid-based setup (SWATgrid) of the Soil Water Assessment Tool (SWAT) model are applied. Good model performance was achieved after calibration and validation with daily discharge (R2 and NSE > 0.7 for both model setups). Annual water balance indicates that 849.5 mm representing 65% of precipitation is lost via evapotranspiration. Surface runoff (77.9 mm) and lateral flow (86.5 mm) are the highest contributors to stream flow in the inland valley. Four land use management options are developed in addition to the current land use system, with different water resources conservation levels (Conservation, Slope conservation, Protection of headwater catchment, and Exploitation). There is a strong relationship between the first three management options with decreasing surface runoff, annual discharge and water yield while the fourth option will increase annual discharge and total water yield. This suggests that if poor management and increasing exploitation of the inland valleys persist, the availability of water resources for human consumption and plant growth will decrease. This study contributes to improving the scientific knowledge on the impact of land use change on hydrological processes in the catchment-wetland nexus to support sustainable water resources management.