Impact Of Land Cover Change Research Articles

Effects of land use/land cover change on soil physicochemical properties and soil carbon stock in Kochore district, southern Ethiopia

Land use changes from year to year due to natural and human-made factors are a serious cause of the degradation of soil properties. Therefore, this study aimed to investigate the impact of land use land cover changes on selected soil physicochemical properties and soil organic carbon stocks in Kochore district, Southern Ethiopia. Satellite images (2000, 2010, and 2020) were used as sources of information for land use and land cover analysis using ArcGIS 10.3 and ERDAS Imagine 2014 software. Three land use types (cultivated, agroforestry, and grazing land) were identified through field surveys and satellite image analysis. Soil samples were collected at different depths (0–20 cm and 20–40 cm), and selected soil properties were analyzed. The results indicate that geospatial data of the land cover of agroforestry continuously increased and a decrease in grazing and cultivated in the given periods of 2000, 2010, and 2020, and soil properties revealed such as sand, bulk density, organic carbon, total nitrogen, pH, cation exchange capacity, and exchangeable bases were significantly (P < 0.001) affected by land use and soil depth. The highest content of OC (2.37), Av.P. (3.36), and TN (0.13) was observed on agroforestry land, and the lowest 1.43 and 0.08 was OC and TN respectively. The highest value of soil organic carbon stock (60.2 mg ha−1) was observed in AFL. The study suggests the deterioration of soil properties under cultivated and grazing land, emphasizing the importance of sustainable integrated soil fertility management to optimize and maintain favorable soil physicochemical properties.

Research on the impact of land use and land cover changes on local meteorological conditions and surface ozone in the north China plain from 2001 to 2020

Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model. It simulates and analyzes the direct impact of LULCC on meteorological parameters and the indirect impact on surface ozone (O3) concentration through physical and chemical processes in the North China Plain during July in the summer. Six rapidly urbanizing cities were selected to represent the North China Plain. The results show that LULCC significantly increased sensible heat flux and 2-m temperature in rapidly urbanizing areas throughout the diurnal cycle, with more pronounced effects during the daytime, ranging from 6.49 to 23.46 W/m2 and 0.20–0.59 °C, respectively. The 10-m wind speed decreased at night and increased during the day, with changes ranging from − 0.43 to 0.27 m/s at night and − 0.16 to 0.15 m/s during the day. The planetary boundary layer height generally increased, with a larger rise during the daytime, ranging from 23.63 to 84.74 m. Simultaneously, surface O3 concentrations increased during both daytime and nighttime. The daytime increase ranged from 2.89 to 9.82 μg/m3, while the nighttime increase ranged from 1.76 to 7.77 μg/m3. LULCC enhanced meteorological and chemical processes as well as vertical transport, leading to an increase in O3. At the same time, it reduced the increase in O3 through horizontal transport and dry deposition processes. These changes are related to the meteorological variations. The impact on O3 concentrations was not limited to the surface but extended to the top of the planetary boundary layer (approximately 1500 m). Below 500 m, vertical transport increased O3 concentrations, while horizontal transport decreased O3 concentrations. Additionally, the meteorological and chemical processes induced by LULCC showed enhanced effects above the surface, whereas the dry deposition process had a smaller impact on O3 concentrations above the surface. This study reveals the significant impact of urban expansion on regional meteorological parameters and air quality. It optimizes the model’s simulation of regional air quality and provides new insights into understanding the effects of urbanization on meteorological conditions and air quality.

The impact of land cover change on runoff coefficient at Upper Garang Watershed, Jawa Tengah Province, Indonesia

Abstract The Upper Garang Watershed serves as a vital water catchment area and supplier for the surrounding regions. Changes in land cover particularly the conversion of vegetated areas to built-up spaces or the reduction of high-density vegetation to low-density coverage can increase the runoff coefficient and disrupt the water supply. This research aims to analyze the impact of land cover change on the runoff coefficient in the Upper Garang Watershed. The data in this research was the topographic map of Indonesia (RBI), the Upper Garang Watershed map, the soil map, the river flow map, and Landsat imagery. The land cover changes in 2013-2023 were analyzed from Landsat imagery. The runoff was analyzed by calculating using Cook method based on mapping slope, soil infiltration, vegetation density, and river flow density. The results showed that in 2013-2023, vegetated areas of forest and agriculture decreased, however, plantation and settlement increased. Land cover changes from vegetated areas becoming built-up areas was about 28.36% of the Upper Garang Watershed area. Land cover changes affected the runoff coefficient. The runoff coefficient changes about 2%.

Guandu River Sediment Plume Space-Time Variability Characterization on Sepetiba Bay – Rio de Janeiro, SE Brazil

The Sepetiba Bay (Rio de Janeiro, SE Brazil) is an important coastal environment due to its ecological characteristics, extensive biodiversity, vast green area and connection to the sea, and vast socio-economic impact due to its importance to the surrounding communities and for the country. The bay receives a considerable amount of sediments through several small rivers and artificial channels along its coast, creating a “river plume” dynamic that influences its biogeochemical processes within the bay. This study analyzes a 20-year remote sensing temporal series from MODIS-Terra, combined with a semi-analytical algorithm based on wellestablished literature, to retrieve surface sediment concentration. The results reveal an inhomogeneous spatio-temporal pattern of the plume, which varies with climatological seasons. Summer and Spring present higher sediment concentrations and range, compared to Autumn and Winter. The observed patterns in the plume suggests a heterogeneous specialization that depends on the riverine inflow, which agrees with previous literature studies. Future studies should tackle both, the increase of remote sensing algorithms’ accuracy to retrieve sediment concentration and focus on plume change detection events to better understand the impact of land cover changes within the drainage basins surrounding Sepetiba Bay.

Assessing the impact of land use and cover change on above-ground carbon storage in subtropical forests: a case study of Zhejiang Province, China

ABSTRACT Land Use and Cover Change (LUCC) has emerged as a primary driver of terrestrial carbon storage changes. However, the contributions of LUCC to Above-Ground Carbon (AGC) storage in subtropical forests remain unclear due to the complex and diverse LUCC trajectory. Quantitative assessment of the impact of different LUCC trajectories on carbon storage is essential for regional carbon cycle mechanisms. Therefore, this study focuses on Zhejiang Province, a representative subtropical forest region in China, to accurately assess the contribution of LUCC to AGC storage changes from 1984 to 2019. We first mapped the land cover patterns using the random forest and spatiotemporal filtering algorithm and then applied these patterns to drive an optimized BIOME-BGC model to simulate the spatiotemporal distribution of AGC density. Finally, the LUCC trajectories were classified into three categories: afforestation, deforestation, and forest type transformations. Their contributions to AGC changes were isolated and analyzed through the trajectory analysis. The results demonstrated that the forest area of Zhejiang Province increased from 5.35 × 106 ha to 6.83 × 106 ha (+27.66%) and the total forest AGC storage increased from 80.52 Tg C to 124.16 Tg C (+54.19%) between 1984 and 2019. The increase in forest AGC due to LUCC amounted to 31.26 Tg C, contributing 71.63% to the total. Specifically, the afforestation, deforestation, and forest type transformations contributed 82.37%, −17.27%, and 6.53% to the change in AGC, respectively. Overall, the afforestation within the LUCC trajectories was the primary contributing factor to the growth of forest AGC in Zhejiang Province from 1984 to 2019. This study obtained accurate LUCC and AGC data, clarifying the contribution of different LUCC trajectories and providing a better understanding of the responses of the forest carbon storage to LUCC dynamics.

Evaluating and predicting the impact of land use and land cover change on land surface temperature in Lac Duong district, Lam Dong province, Vietnam

Land use and land cover (LULC) change is a key factor influencing land surface temperature (LST) dynamics. This change reflects partly global warming and climate change at local and regional scales. This study aimed to evaluate the effect of LULC on LST change in Lac Duong mountainous district, Lam Dong province in the past 10 years (2013 - 2023), and predict the LST change in 2030. The study used satellite image data from Landsat 8 and 9 OLI to build LULC and LST maps and used the CA-ANN model to predict the LST map. The results showed that the forest land had the LST below 25°C, with the below 20°C LST area correlated negatively with the forest land area, while 20 - 25°C LST correlated positively, especially at the temperature of 22 - 25°C (R2 = 0.97). The 22 - 25°C and 30 - 35°C temperature levels (R2 = 0.76 and R2 = 0.86) correlated sharply with the crop land area. The LST levels between 30 - 40°C reflected the built-up land and bare land with the highest correlation of R2 = 0.68 and 0.88, respectively. The LST level 20 - 22°C represented the water body area (R2 = 0.87). The LULC changes had an impact on the LST change in the past 10 years in Lac Duong district. While the forest land area decreased slightly by 0.5%, the cool LST area fell considerably by 10.5% compared to 10 years ago. An almost doubling of the cropland area also led to a doubling in the 25 - 35°C LST areas. In addition, the 35 - 40°C LST level started to happen in several regions. The LST change was predicted to keep increasing in 2030. The temperature was predicted to increase by 2 - 3°C with a maximum temperature of 42°C.

Biodiversity hotspot assessment in the Altai Mountains transboundary region based on Mammals and Aves.

Most of the world's mountains are distributed across national boundaries. However, due to the sovereignty of national boundaries, conservation plans between neighboring countries are often uncoordinated. Against the backdrop of impending environmental changes, transboundary mountain ecosystems and biodiversity face significant threats. This study employs the MaxEnt model, leveraging data on climate, topography, landscape, and human activities to predict potential distribution areas for mammals and birds, aiming to identify biodiversity hotspots (BHs) and analyze their distribution mechanisms in the Altai Mountains transboundary region (AMTR). Results indicate that BHs are primarily located near the Russian-Mongolian border, significantly influenced by climate variables, elevation, and human activities. The study also highlights changes in key habitat types (KHTs), particularly transitions between grassland and bareland, and the impact of climate-driven land cover change on the distribution of BHs. Furthermore, the research evaluates the coverage of protected areas and emphasizes the importance of identifying key biodiversity areas (KBAs) and establishing transboundary corridors for enhanced species protection and future environmental change adaptation. The findings underscore the necessity of transboundary cooperation and focused strategies for biodiversity conservation to mitigate the adverse effects of climate change and human activities.

Impacts of land use land cover change on Leopard ( Panthera pardus ) habitat suitability and its effects on human wildlife conflict in Hirkiso forest, Sibu Sire District, Western Ethiopia

Impacts of land use land cover change on Leopard ( <i>Panthera pardus</i> ) habitat suitability and its effects on human wildlife conflict in Hirkiso forest, Sibu Sire District, Western Ethiopia

Impact of Land Use and Land Cover Change on Soil Erosion in Dondor Watershed, Blue Nile Basin, Northwestern Ethiopia

Understanding how land use and land cover (LULC) changes affect soil erosion is essential for effective management of watershed areas. This study used Geographic Information Systems (GISs) and the Revised Universal Soil Loss Equation (RUSLE) model to analyze the impact of LULC changes on soil erosion in the Dondor Watershed. Remote sensing data, including Landsat and Sentinel-2 satellite images, alongside field surveys, topographic data, rainfall, and soil data were used. The results showed agricultural land as the primary LULC type, increasing from 43.49% in 2002 to 59.10% in 2023. Forest and built-up areas also expanded, while grassland decreased. Soil erosion estimates revealed that more than 85% of the watershed experienced very slight erosion though the average annual soil loss increased from 4.98 t ha⁻1 year⁻1 in 2002 to 7.96 t ha⁻1 year⁻1 in 2023. Agriculture and built-up areas were identified as the primary contributors to erosion. This study underscores the importance of monitoring LULC dynamics for responsible land management and conservation efforts in the watershed.

Investigating the impact of land use land cover change on groundwater level dynamics in the Koraiyar watershed, Coimbatore District, Tamil Nadu, India

Investigating the impact of land use land cover change on groundwater level dynamics in the Koraiyar watershed, Coimbatore District, Tamil Nadu, India

Impact of Land Use and Land Cover Changes on Soil Physico-Chemical Properties in Southern Tigray, Northern Ethiopia

Soil quality declines due to the conversion of natural vegetation into farmland and grazing areas. The response of soil properties to land use and land cover changes (LULC) exhibits both spatial and temporal variations. This study aimed to assess the effects of LULC changes on the physico-chemical properties of soil in the Wojic watershed. Soil samples were collected from natural forests, bushland, shrubland, and cultivated lands across three landforms of the watershed (upper, middle, and lower) to evaluate the physical and chemical properties of the soil associated with different LULC types. The LULC categories were compared using mean values and critical thresholds for selected physicochemical soil properties. Soil analysis was conducted using R software, employing one-way analysis of variance (ANOVA). A normality test was performed before the post hoc analysis, and Tukey’s honest significance difference (HSD) test was utilized for mean separation among the LULC types. Additionally, a normalized difference vegetation index (NDVI) was calculated for the years 1997 and 2017. A simple linear regression model was developed to estimate soil physico-chemical properties over the past 20 years, using laboratory soil parameters and the NDVI for 2017. The pH values showed a slight decrease in cultivated land (from 5.7 to 5.4), bushland (from 7 to 6.6), and shrubland (from 6.5 to 6.2) over the study period. The analysis indicated a declining trend in physico-chemical properties, attributed to changes in vegetation cover and management practices. Consequently, the government needs to enforce policies and regulations that promote effective land resource management and utilization, with particular emphasis on the proper management and conservation of forests, bushlands, and shrublands, as well as measures to prevent increased land resettlement.

Understanding the relationship between land use/land cover changes and air quality: A GIS-based fuzzy inference system approach.

Air pollution is a global issue that demands urgent attention due to its detrimental effects on human health and the environment. Land Use and Land Cover (LULC) change is an essential factor that significantly impacts ambient air quality through alterations in emission sources, vegetation cover, natural processes, and urban design. This study investigates the spatio-temporal variation of key air pollutants resulting from urban LULC changes in the Delhi region. Findings reveal a notable increase in pollutant concentrations, particularly particulate matter, in 2019 (PM10: 318.65 ± 45.80 µg/m3) and 2023 (PM10: 383.70 ± 61.49 µg/m3), compared to 2008 (PM10: 246.76 ± 30.66). LULC change analysis demonstrates a rise in built-up areas 24.59%(2008 to 2019), 33.62% (2008 to 2023) and a decline in vegetation cover 27.49% (2008 to 2019),32.37% (2008 to 2023). Correlation analysis indicates a positive correlation between PM10 and urban indices (+ 0.63) and a negative correlation between PM10 and vegetation indices (- 0.61), highlighting the impact of LULC on air quality deterioration. Subsequently, a fuzzy inference system model integrates LULC information to develop an air quality index (AQI). Incorporating LULC changes in AQI assessment offers a realistic approach to address the complexity arising from combined air pollutant effects, surpassing conventional AQI calculation methods. The findings underscore the significance of understanding the impact of Land Use and Land Cover (LULC) change on ambient air quality in formulating effective air quality management programs and policies. Integrating this knowledge into policymaking is crucial for the successful abatement of air pollution in urbanized areas.

Dam Siltation in the Mediterranean Region Under Climate Change: A Case Study of Ahmed El Hansali Dam, Morocco

Dams are vital for irrigation, power generation, and domestic water needs, but siltation poses a significant challenge, especially in areas prone to water erosion, potentially shortening a dam’s lifespan. The Ahmed El Hansali Dam in Morocco faces heightened siltation due to its upstream region being susceptible to erosion-prone rocks and high runoff. This study estimates the siltation at the dam from its construction up to 2014 using bathymetric data and the Brown model, which is a widely-used empirical model that calculates reservoir trap efficiency. Additionally, the study evaluates the impact of Land Use and Land Cover (LULC) changes and projected future rainfall until around 2076 based on siltation rates. The results indicate that changes in LULC, particularly temporal variations in precipitation, have a significant impact on the siltation of the Ahmed El Hansali dam. Notably, rainfall is strongly correlated with the siltation rate, with an R2 of 0.92. The efficiency of sediment trapping (TE) is 97.64%, meaning that 97.64% of the sediment in the catchment area is trapped or deposited at the bottom of the dam. The estimated annual specific sediment yield is about 32,345.79 tons/km2/yr, and the sediment accumulation rate is approximately 4.75 Mm3/yr. The dam’s half-life is estimated to be around 2076, but future precipitation projections may extend this timeframe due to the strong correlation between siltation and precipitation. Additionally, soil erosion driven by land management practices plays a crucial role in future siltation dynamics. Hence, this study offers a comprehensive assessment of the siltation dynamics at the Ahmed El Hansali dam, providing essential information on the long-term effects of erosion, land use changes, and climate projections. These findings may assist decision makers in managing dam reservoir sedimentation more effectively, ensuring the durability of the dam and extending the reservoir life.

Impacts of Land Use and Land Cover Change on Non-Point Source Pollution in the Nyabarongo River Catchment, Rwanda

The Nyabarongo river catchment in Rwanda has experienced significant changes in its land use and land cover (LULC) in recent decades, with profound implications for non-point source pollution. However, there are limited studies on non-point pollution caused by nutrient loss associated with land use and land cover changes in the catchment. This study investigates the spatiotemporal impacts of these changes on water quality considering nitrogen and phosphorus within the catchment from 2000 to 2020 and 2030 as a projection. The SWAT model was used in analysis of hydrological simulations, while the CA–Markov model was used for the future projection of LULC in 2030. The results revealed (1) the important changes in LULC in the study area, where a decrease in forestland was observed with a considerable increase in built-up land, grassland, and cropland; (2) that the R2 and NSE of the TN and TP in the runoff simulation in the catchment were all above 0.70, showing good applicability during calibration and validation periods; (3) that from 2000 to 2020 and looking to the projection in 2030, the simulated monthly average TN and TP levels have progressively increased from 15.36 to 145.71 kg/ha, 2.46 to 15.47 kg/ha, 67.2 to 158.8 kg/ha, and 9.3 to 17.43 kg/ha, respectively; and (4) that the most polluted land use types are agriculture and urban areas, due to increases in human activities as a consequence of population growth in the catchment. Understanding the patterns and drivers of these changes is critical for developing effective policies and practices for sustainable land management and protection of water resources.

Impact of land use land cover changes on urban temperature in Jakarta: insights from an urban boundary layer climate model

Urbanization is one of the important drivers of increasing local temperatures. As cities and urban areas evolve, extensive land use and land cover (LULC) changes alter the physical characteristics of surface materials. This modification results in reduced evapotranspiration rates, ultimately contributing to higher surface and air temperatures. This study investigated the impact of urbanization on urban temperature in Jakarta. Urban temperature was simulated for a 20-year time period (1995–2014) by the urban boundary layer climate model UrbClim, using LULC data for both 1995 and 2014. Temperature changes were analysed by assessing the temperature anomaly across different LULC change classes divided into four main classes namely no built-up changes (BB), no green spaces changes (GG), built-up to green spaces (BG), and green spaces to built-up (GB). The study revealed that the conversion of green spaces to built-up areas (GB) had the most significant impact on the increase in air temperature. This was indicated by the mean values of the temperature anomaly of GB of about 0.24°C followed by GG, BB, and BG with the mean values of the temperature anomaly of about 0.20°C, 0.19°C, 0.17°C, respectively. The different temperature anomalies of the LULC change classes indicate that green spaces have an important role in maintaining local climate. Hence, it is important for local government to effectively manage the composition, the quantity, as well as the distribution of green spaces within a city. By looking at temperature anomalies of LULC change classes, the present study provides an alternative approach to many existing methods that provide general information about temperature changes, without specifically analyzing the effects of LULC transformations.

Impacts of land use and land cover change on the landscape pattern and ecosystem services in the Poyang Lake Basin, China

ContextDecades of intensifying human activities have led to drastic changes in land use and land cover (LULC) in the Poyang Lake Basin (PLB), resulting in significant changes in landscape pattern and ecosystem service value (ESV), thereby affecting regional sustainability.ObjectivesWe focused on understanding the impact of LULC changes on the landscape pattern and ESV of the PLB and used the Patch-generating Land Use Simulation model (PLUS) to predict LULC changes in 2050.MethodsWe evaluated landscape patterns using landscape metrics and calculated ESV using the ecosystem service equivalent factor method. The Pearson correlation coefficient was used to analyze the correlation between landscape patterns and ESV from 1990 to 2020. Then, we combined the PLUS model and the ecosystem service equivalent factor method to calculate the ESV under multiple scenarios from 2020 to 2050.ResultsFrom 1990 to 2020, the LULC of the PLB changed to varying degrees. The PLB has undergone a rapid process of landscape fragmentation, and the total ESV of the PLB has decreased. The total ESV was positively correlated with the CONTAG index and negatively correlated with the SHDI index. Between 2020 and 2050, the ESV of the PLB is projected to decrease under the NDS (nature development scenario) and EDS (economic development scenario) and increase under the EPS (ecological protection scenario).ConclusionsESV responded to changes in landscape pattern. We recommend that the PLB should increase patch connectivity. Additionally, future development in the PLB should prioritize ecological protection to prevent further declines in ESV.

Impact of rapid anthropogenic land use and land cover change on basin hydrology and sediment loads

Impact of rapid anthropogenic land use and land cover change on basin hydrology and sediment loads

Land Cover Simulation and Carbon Storage Assessment in Daqing City based on FLUS-InVEST Model

Considering Daqing City as the research area, the impact of land cover change on carbon storage in the future was discussed, and the hot spots of carbon sequestration capacity were identified. The future land use simulation （FLUS） model was used to simulate the land cover pattern of a natural succession scenario, ecological protection scenario, urban development scenario, and comprehensive development scenario in 2030, and the integrated valuation of ecosystem services and trade-offs （InVEST） model was combined to estimate carbon storage in 2010, 2020, and 2030. Finally, the hot spot analysis tool was used to identify the cold hot spots of carbon sequestration capacity. The results showed the following： ① From 2010 to 2020, the area of cultivated land, water, and artificial surface increased, whereas the area of other land cover types decreased, and the total carbon storage decreased by 8.6×105 t. ② The land cover change of the natural succession scenario and urban development scenario in 2030 was similar to that of 2010-2020, with carbon storage decreasing by 1.16×106 t and 1.20×106 t, respectively. The carbon storage of the comprehensive development scenario decreased by 1.00×106 t compared with that in 2020, and carbon storage of the ecological protection scenario was 5.677 7×108 t, which increased by 2.53×106 t compared with that in 2020. ③ The conversion of grassland and wetland to cultivated land was the main cause of carbon storage loss, and the main contributor of carbon storage in the ecological protection scenarios was wetland. ④ The hot spots of carbon sequestration capacity were mainly located in the wetland area, and the cold spots were mainly distributed in the central part of Daqing City. The carbon sequestration capacity of cultivated land was not significant. According to the research results, to realize the urban transformation of Daqing City, we should insist on returning farmland to forest and grass, increase the intensity of returning moisture, improve the utilization rate of urban land, and increase green infrastructure in the main urban area.

Impacts of Land Use and Land Cover Changes on Biomass and Carbon Sequestration in Coastal Kinondoni, Tanzania

Impacts of Land Use and Land Cover Changes on Biomass and Carbon Sequestration in Coastal Kinondoni, Tanzania

Influence of urban functional zone change on land surface temperature using multi-source geospatial data: A case study in Nanjing City, China

The urban heat island effect is a prevalent urban concern, and studies on its influencing factors are essential to mitigate its negative effects and promote sustainable urban development. Although many studies have revealed the impact of land cover change on land surface temperature (LST) during urbanization, most have focused only on built-up areas without considering the relationship between urban internal functional structure and LST. To clarify the influence of changes in urban functional zones (UFZs) on LST, focusing on the downtown area of Nanjing City, China, this study proposed an effective framework using multi-source geospatial data for qualitative and quantitative analysis. Specifically, very high spatial resolution images and point of interest data were jointly used to generate UFZ maps using an advanced deep learning approach, and LST distribution maps were retrieved from Landsat 8 images using the radiative transfer equation. The UFZ and LST maps were then overlaid and analyzed to reveal the impact of UFZ change on LST. The results showed that in 2013, 2018, and 2022, the residential region constituted the largest proportion of area, comprising 23.52%, 24.52%, and 27.28%, respectively. The areas of unused region and transport region experienced the most rapid decrease and increase of 6.08% and 4.05% from 2013 to 2022, respectively. Furthermore, the area of sub-high temperature zone decreased the most, by 3.47%, whereas that of the high-temperature zone increased the most, by 6.05%. In the study area, water and green space maintained relatively low LSTs, whereas residential region and unused region exhibited higher LSTs. From 2013 to 2022, UFZ changes contributed to a 0.71°C increase in LST. Transfers from green space, water, commercial region, transport region, and industrial region mostly resulted in a higher LST, which was associated with a decrease in fractional vegetation cover (FVC). Transfers from unused region, residential region, and public service region mostly contributed to reducing LST, which was caused by the increase in FVC. The findings and the proposed framework can provide reliable references for urban managers to optimize urban spatial layout and promote sustainable urban development.