Impact Of Land Use And Land Cover Changes Research Articles

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.

Decadal hydrological impact assessment of evolving land use and land cover in an Indian river basin: a multi-model approach

ABSTRACT All river basins have ever-evolving land use and land cover (LULC) attributes. The impact of these changes may not be significant on short time scales (i.e., monthly, seasonal, yearly), but over a decadal scale, they can substantially alter the hydrological processes of the basin. This study comprehensively quantifies the impacts of LULC changes over Cauvery basin in India using LULC maps from four decades spanning from 1980 to 2020. Simulations were performed using the Soil and Water Assessment Tool (SWAT) with various datasets. To isolate the effects of LULC changes, two sets of SWAT models were developed: A-set models for calibration and validation to establish basin parameters and B-set models to examine LULC change impacts while isolating other factors such as terrain and climate changes. Key findings include a significant increase in urban areas (0.87% in 1985 to 5.54% in 2015), a decline in vegetation cover (25.34% in 1985 to 21.32% in 2015), and an increase in the Curve Number and average annual surface runoff, highlighting the impact of LULC changes on hydrological processes. The A-set models achieved R-squared values of 0.831, 0.728, 0.715, and 0.757, while the B-set models showcased significant changes in hydrological parameters due to LULC changes.

Addressing the impact of land use land cover changes on land surface temperature using machine learning algorithms

Over the past two and a half decades, rapid urbanization has led to significant land use and land cover (LULC) changes in Kabul province, Afghanistan. To assess the impact of LULC changes on land surface temperature (LST), Kabul province was divided into four LULC classes applying the Support Vector Machine (SVM) algorithm using the Landsat satellite images from 1998 to 2022. The LST was assessed using Landsat data from the thermal band. The Cellular Automata-Logistic Regression (CA-LR) model was applied to predict the future patterns of LULC and LST for 2034 and 2046. Results showed significant changes in LULC classes, as the built-up areas increased about 9.37%, while the bare soil and vegetation cover decreased 7.20% and 2.35%, respectively, from 1998 to 2022. The analysis of annual LST revealed that built-up areas showed the highest mean LST, followed by bare soil and vegetation. The future simulation results indicate an expected increase in built-up areas to 17.08% and 23.10% by 2034 and 2046, respectively, compared to 11.23% in 2022. Similarly, the simulation results for LST indicated that the area experiencing the highest LST class (≥ 32 °C) is expected to increase to 27.01% and 43.05% by 2034 and 2046, respectively, compared to 11.21% in 2022. The results indicate that LST increases considerably as built-up areas increase and vegetation cover decreases, revealing a direct link between urbanization and rising temperatures.

Exploring Land Use/Land Cover Dynamics and Statistical Assessment of Various Indicators

Current information on urban land use and surface cover is derived from the land classification of cities, facilitating accurate future urban planning. Key insights are driven by multi-year remote sensing data. These data, when analyzed, produce high-resolution changes on the Earth’s surface. In this context, publicly accessible Urban Atlas data are employed for the high-precision and high-resolution classification and monitoring of terrestrial surfaces. These datasets, which are useful for preserving natural resources, guiding spatial developments, and mitigating pollution, are crucial for monitoring changes and managing cities. This research aims to analyze and contrast land use and land cover (LULC) changes in Gaziantep (Turkey) between 2010 and 2018 using Urban Atlas data, and to investigate correlations between the city’s statistical data and LULC changes. Gaziantep’s urban dynamics were analyzed using Urban Atlas datasets from 2010 to 2015 and 2012 to 2018, the latter part of Copernicus, the European Earth Observation Programme. To understand the impact of LULC changes on urban landscapes, people, and the environment, official environmental and demographic statistics spanning four years were sourced and studied. The findings reveal a trend of agricultural and vacant lands evolving into residential and industrial zones, with such changes likely to increase in the near future, given the growth of building zones. While some land classes have shown consistent area values annually, residential and industrial zones have expanded in response to housing and employment demands. The most significant alterations have occurred in the last three years. Shifts in urban configurations align closely with migratory patterns, reflecting notable variations in factors like population, consumption, and pollution.

Impact of Land Use Changes on Ecosystem Services Supply: A Meta Analysis of the Italian Context

Changes in land use and land cover (LULC) are caused by several factors, including climate change, socio-demographic dynamics, human pressures and urban sprawl. These factors alter the structure and functionality of ecosystems and their capacity to provide ecosystem goods and services to society. The study of LULC changes is important for understanding the dynamics of relationships between environmental, social and economic components and for analyzing the factors affecting natural capital. Including ecosystem services (ES) in spatial planning tools and sectoral policies is useful for improving governance. In this paper, the impact of LULC changes on ES provision has been estimated. To this end, we carried out a literature review (Step 1) to select the biophysical and economic coefficients of ES supply by land cover classes and collect them in a database (Step 2). We subsequently aggregated the economic and biophysical coefficients by macro classes (Step 3) and, using the benefit transfer approach, we estimated the change in the supply of ESs concerning permanence and transition phenomena in Italy from 1990 to 2018 (Step 4). The transition phenomena analysis also allowed us to evaluate the consequences of urbanization and urban green space governance on ES supply. Indeed, these urban green spaces can help reduce risks to people’s health and safety and mitigate the effects induced by climate change. In total, approximately 800 coefficients (biophysical and economic) of ESs supplied by Corine Land Cover classes were acquired. The results show a reduction in the annual supply of ecosystem services of EUR 927 million (2022) caused by LULC changes between 1990 and 2018. This research proposes a methodology to improve knowledge of ESs concerning anthropogenic impacts and to support land-use planning policies regarding Agenda 2030 for Sustainable Development Goals.

Impact of land use and land cover change on land surface temperature over Lake Tana Basin

Isolation of climate and Land Use and Land Cover (LULC) changes and their compounded effect is complicated since the two influence each other through forcing-feedback cycles. This study investigates the changes in LULC and its contribution to the change in surface and air temperature in the Lake Tana Basin using data obtained from MODIS remote sensing satellites, ground observation and reanalysis model. Observation minus reanalysis (OMR) method and various analysis tools are used to estimate the impact of LULC changes on temperature. The analysis of LULC change indicates that an increase of Savanna and other type of forest cover by about 519 km2 from year 2001 to year 2020. Wetland increased by about 83.7 km2 during the said period. During the period 2001–2020, about 56.5% baren-land areas are being converted into wetland. The conversion of water bodies and baren land to wetland is likely due to the increase of water hyacinth on both the water body and nearby baren-land whereas the increase in Savanna is linked to an on-going eucalyptus tree plantation. The negative correlation between LST and NDVI (reaching a value of −0.60) is noticed over the Basin throughout the year on inter-annual time scale. An increase in vegetation cover such as Savanna and broad leaf forest coincides with the decreasing LST with an average rate of 0.08%/decade. Also, a reduction in temperature, derived from OMR, at an average cooling rate of about 0.87%/decade is observed in the study period. However, an increase in the LST change rate over built-up and grassland is about 0.03%/decade. Therefore, we conclude that the consistent associations of the increase in areal coverage of the some LULC types with lowest LSTs, 2m-temperature and temperature trend derived from NDVI-LST and LULC-LST associations as well as OMR temperature and LST are unambiguous signatures of the effect of LULC change on temperature over Lake Tana Basin, distinct from that arising due to climate change.

Prediction of Land Surface Temperature Considering Future Land Use Change Effects under Climate Change Scenarios in Nanjing City, China

Land use and land cover (LULC) changes resulting from rapid urbanization are the foremost causes of increases in land surface temperature (LST) in urban areas. Exploring the impact of LULC changes on the spatiotemporal patterns of LST under future climate change scenarios is critical for sustainable urban development. This study aimed to project the LST of Nanjing for 2025 and 2030 under different climate change scenarios using simulated LULC and land coverage indicators. Thermal infrared data from Landsat images were used to derive spatiotemporal patterns of LST in Nanjing from 1990 to 2020. The patch-generating land use simulation (PLUS) model was applied to simulate the LULC of Nanjing for 2025 and 2030 using historical LULC data and spatial driving factors. We simulated the corresponding land coverage indicators using simulated LULC data. We then generated LSTs for 2025 and 2030 under different climate change scenarios by applying regression relationships between LST and land coverage indicators. The results show that the LST of Nanjing has been increasing since 1990, with the mean LST increased from 23.44 °C in 1990 to 25.40 °C in 2020, and the mean LST estimated to reach 26.73 °C in 2030 (SSP585 scenario, integrated scenario of SSP5 and RCP5.8). There were significant differences in the LST under different climate scenarios, with increases in LST gradually decreasing under the SSP126 scenario (integrated scenario of SSP1 and RCP2.6). LST growth was similar to the historical trend under the SSP245 scenario (integrated scenario of SSP2 and RCP4.5), and an extreme increase in LST was observed under the SSP585 scenario. Our results suggest that the increase in impervious surface area is the main reason for the LST increase and urban heat island (UHI) effect. Overall, we proposed a method to project future LST considering land use change effects and provide reasonable LST scenarios for Nanjing, which may be useful for mitigating the UHI effect.

Satellite Based Approach for Assessing Land Cover Changes of Modhupur Sal Forest Regions in Bangladesh: Its Dynamics and Impacts on Surface Temperature

Land Use and Land Cover (LULC) changes have a significant impact on climate changes in the local to global scales. In this paper, we studied the impact of LULC changes of Modhupur Sal forest and its adjoining areas in Bangladesh on LST using multi temporal satellite data. Seasonal and temporal values of LST were determined for three decades from 1989 to 2019. It was seen from the LULC study that the Sal forest area has changed a lot over the time period. Through the long-term time series data, it is found that with the change of LULC, LST of the area has increased. An inverse correlation between the NDVI and LST has been observed from 1989 to 2009 in winter and 1993 to 2011 in summer. But in 2019, both in winter and summer, with the increase of NDVI value of the area, LST was seen to increase.

Land use changes impact on selected chemical denudation element and components of water cycle in small mountain catchment using SWAT model

Land use changes are extremely important in the context of land and water management. This study examines impact of land use and land cover (LULC) changes on nitrate nitrogen, outflow and surface runoff in the agriculture catchment in the Polish Carpathians using the Soil and Water Assessment Tool (SWAT). The study covers 25-year (1995–2019) and was divided into three periods relating to different LULC patterns (1995–2004, 2005–2012, 2013–2019). The LULC maps used were based on aerial photos from 1997, 2009, and 2016. The SWAT was calibrated and applied to periods with variable LULC (in simulation 1) and by keeping the LULC constant during the period 1995–2019 (simulation 2; the LULC from 1997) to determine the impact of LULC changes on the analysed variables. The ongoing LULC changes were found to have resulted in a reduction of cultivated land area (by 72 %) and an increase of grassland (by 45 %), forest (by 2 %) and urbanised areas (by 17 %). The SWAT model achieved reasonable accuracy. The model results tend to overestimate the load of nitrate nitrogen and underestimate outflow and surface runoff. The LULC changes resulted in a decrease in outflow between 1995 and 2004 of 24 % in comparison to 2013–2019, and a decrease in surface runoff of 12 %. At the same time, there was a significant decrease in nitrate nitrogen load of 68 % (from 13.0 kg ha−1 in 1995–2004 to 4.2 kg ha−1 in 2013–2019). If the LULC of 2013–2019 was restored to 1997 conditions (as in simulation 2), the outflow and load of NO3-N would be higher by 16 % (12 % in simulation 1) and 67 % (55 % in simulation 1) in relation to the observed values. The impact of LULC on the analysed parameters was spatially differentiated between subbasins depending on the scale of the land use changes. The research conducted here indicates that planning and managing the effects of LULC changes is of key importance for sustainable development in terms of the quantity and quality of water.

Impacts of land use and land cover changes on local meteorology and PM2.5 concentrations in Changchun, Northeast China

Land use and land cover (LULC) changes have a considerable influence on the surface energy balance, altering regional meteorology and air quality. However, this impact is not quantified in Changchun, an important city in the old industrial base of Northeast China. In this study, based on the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model, the LULC2017 (LULC data in 2017) and LULC2001 (LULC data in 2001) scenarios were simulated for January and July 2017, respectively, to assess the impact of LULC changes on meteorology and fine particulate matter (PM2.5) concentrations in Changchun. The results show that the sensible heat flux in the urban expansion area (UEA) increased during the daytime, reaching a maximum value of 154 W/m2 and 162 W/m2, respectively, while the latent heat flux decreased during the daytime, reaching a maximum value of 22.84 W/m2 and 180.75 W/m2, respectively. Consequently, 2 m temperature (T2) increased by 4 °C and 3 °C, respectively; 10 m wind speed (WS10) increased by 1.05 m/s and 1.60 m/s, respectively; and planetary boundary layer height (PBLH) increased by 100 m and 117 m, respectively. These variations in meteorological factors can substantially impact the spatial distribution of air pollutants. In the UEA, PM2.5 concentrations decreased by 34 μg/m3 and 20 μg/m3 in January and July, respectively. The change in SO42− accounted for approximately 25% of the total concentration change of PM2.5, with a decrease of approximately 5–6 μg/m3 during the nighttime in January. Secondary organic aerosol (SOA) formed from biogenic volatile organic compounds (BVOC) precursors (BSOA) slightly decreased owing to the reduction in croplands dominated by green vegetation. Meanwhile, PM2.5 concentrations in the surrounding areas of the UEA increased significantly in January. The results of the process analysis based on the CMAQ model indicate that the main reason for the spatial variation of PM2.5 concentrations is the enhancement of transport and diffusion in the horizontal and vertical directions in the UEA. In January, the negative contribution of vertical advection (ZADV) and horizontal advection (HADV) processes to PM2.5 in the UEA increased by 25 μg/m3 and 40 μg/m3, respectively. Vertical diffusion (VDIF) process caused an increase in PM2.5 diffusion by 40 μg/m3 and 16 μg/m3 during the daytime and nighttime in the UEA, respectively. In July, the negative contribution of VDIF and HADV processes to PM2.5 increased by 40 μg/m3 and 32 μg/m3 during the nighttime in the UEA, respectively.

Assessing the Impact of Land Use and Land Cover Changes on Aflaj Systems over a 36-Year Period

The aflaj systems represent unique irrigation technologies that have been implemented in the Sultanate of Oman. This innovative system, referred to as “falaj” in the singular form, is composed of a sophisticated network of underground tunnels and open-air channels designed to access shallow subterranean water tables, thereby providing water for residential and agricultural use. The aflaj systems have played a significant role in supporting sustainable water resource management in arid and semiarid regions, making a notable contribution to the socioeconomic development of the country. The alteration of land use and land cover (LULC) in arid and semiarid regions can have significant consequences for hydrological systems, affecting the ability of local ecosystems to manage fresh surface and groundwater resources. These changes are often caused by both natural and anthropogenic factors. To investigate the impact of LULC changes on aflaj systems in the northern part of Oman, we utilized satellite imagery, aflaj data, and spatial analytical and image processing techniques within the framework of geographic information systems (GIS) and remote sensing. In the first part of the study, we quantified the changes in LULC and their impact on aflaj systems in seven cities in Oman due to urban expansion. In the second part, we evaluated the effect of LULC on groundwater for four major aflaj between 1985 and 2021. The study area was divided into four primary LULC classifications: vegetation, bodies of water, metropolitan areas, and bare soil. The classification maps demonstrated a high overall accuracy of 90% to 95%, indicating satisfactory performance. Our results revealed a significant reduction in vegetation areas between 1985 and 2021, primarily shifting from bare soil (BS) to urban areas (UAs) and from vegetation cover (VC) to BS, due to the reduction of groundwater resources. Over the four study periods (1985–1990, 1990–2000, 2000–2013, and 2013–2021), the percentages of the total area of Falaj Al-Muyasser, Falaj Daris, Falaj Al-Maliki, and Falaj Al-Khatmeen that transformed from agricultural lands to UAs were 40%, 39%, 32%, and 8%, respectively. Our study highlights the need for appropriate land management and planning to ensure the most effective solutions are utilized to meet social and economic sustainability requirements. In conclusion, our study presents a comprehensive analysis of LULC changes and their impact on aflaj systems over a 36-year period, providing new insights into the potential effects of LULC changes on groundwater resources and offering a basis for informed decision making on land management in arid and semiarid areas.

Valuation of Land-Use/Land-Cover-Based Ecosystem Services in Afghanistan—An Assessment of the Past and Future

Being one of the weakest economies in the world, livelihoods in Afghanistan remain highly dependent on local ecosystem services. However, the risk of ecosystem services degradation in Afghanistan over the past two decades has significantly increased, mainly due to rapid changes in land-use and land-cover (LULC). As such, policy makers must be able to estimate the impact of LULC changes on various ecosystem services. By utilizing GlobeLand30 land cover products for 2000, 2010 and 2020, and by adopting the value transfer method, this study assessed the ecosystem services value (ESV) changes in response to the changes of LULC in Afghanistan. Additionally, the dynamics of the land system (DLS) model was innovatively coupled with linear programming to predict likely scenarios of ESV changes by 2030. The predicted results were also validated against actual land cover and achieved a Kappa value of 0.78. The results showed that over the 20-year period, ecologically important LULC categories such as forest, water bodies and grassland were severely unstable and rapidly decreasing in scope. These LULC types were being threatened by agricultural, built-up and unused lands. During this period, we estimated a decrease in the total ESV from 161 billion USD in 2000 to 152.27 billion USD in 2020. About 92% of this decrease was shared by supporting and provisioning services. The simulated scenarios also showed that ESV will likely further decrease under Business-As-Usual (BAU), and Rapid Economic Development (RED) scenarios. Positively, an Environmental Protection (ENP) scenario is predicted, with a 4.5% increase in ESV by 2030. However, achieving this scenario requires the enforcement of strict environmental protection measures.

The impact of land use and land cover changes on the landscape pattern and ecosystem service value in Sanjiangyuan region of the Qinghai-Tibet Plateau

Decades of intensifying human activities have caused dramatic changes in land use and land cover (LULC) in the ecologically fragile areas of the Qinghai-Tibet Plateau, which have led to significant changes in ecosystem service value (ESV). Taking the ecologically fragile Sanjiangyuan region of the Qinghai-Tibet Plateau as the research object, we focused on understanding the impact of LULC changes on the Sanjiangyuan's landscape pattern and its corresponding ESV, which was combined with a Markov-Plus model to predict LULC changes in 2030. The results showed: (1) from 2000 to 2020, the LULC of Sanjiangyuan has changed to varying degrees, respectively. In the central and southern regions where animal husbandry is the mainstay activity, the area of grass land converted to bareland had expanded; (2) from 2000 to 2010, the total regional ESV increased sharply. However, the total amount of ESV decreased from 2010 to 2020; (3) the overall ESV in the study area was observed to be trending down and is expected to decrease by approximately 4.25 billion CNY by 2030; (4) the fragmentation and complexity of regional landscape patterns will negatively affect local ecosystem stability and biodiversity. Overall, there is a strong temporal and spatial correlation between LULC and ESV. This study will provide a reference for the local government to provide targeted and sustainable land management policies, thereby promoting the improvement of the Qinghai-Tibet Plateau regional ecology value.

Land surface temperature and human thermal comfort responses to land use dynamics in Chittagong city of Bangladesh

Intense urbanization alters the microclimate and ecology of cities by converting naturally vegetated and permeable surfaces into impervious built-up surfaces. These artificial impermeable surfaces re-balance the surface energy budget by storing solar heat due to their higher thermal conductivity, and consequently, increase the Land Surface Temperature (LST). The higher LST affects the city dwellers' Human Thermal Comfort (HTC). To address these issues, unlike most prior research, we assess not only the influence of Land Use and Land Cover (LULC) alterations on summer LST but also on winter LST in Chittagong City of Bangladesh between 1993 and 2020 by using Remote Sensing (RS) and Geographic Information Systems (GIS). Additionally, the study evaluates the impact of LULC changes on the HTC during summer as LST substantially affects HTC in summer. The LULC analysis shows an increase in built-up area by 204% from bare lands, vegetated lands, lowlands, and water bodies between 1993 and 2020. In contrast, bare lands were converted from naturally vegetated surfaces, followed by lowlands and water bodies because of anthropogenic activities. The LSTs of Chittagong city, derived from remote sensing data, show a strong upward trend, with summer (winter) ranges of 20.62–34.07 °C (7.50–27.52 °C), 22.82–37.62 °C (14.92–29.32 °C), and 22.32–43.52 °C (17.08–31.83 °C) for 1993, 2007, and 2020, respectively. Between 1993 and 2020, the spatial mean winter and summer LSTs increased by 4.04 °C and 6.45 °C, respectively, or 0.15 °C and 0.24 °C per year. Chittagong had the highest mean LST in built-up areas for all the years. In addition, the study area's HTC gradually shifted to intense heat stress. The summer LST strongly correlated with normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI) while winter LST exhibited poor correlation with these indices.

Effect of the Belt and Road Initiatives on Trade and Its Related LUCC and Ecosystem Services of Central Asian Nations

Economic development and trade activities are some of the main driving forces leading to land use and land cover changes (LUCC) with impacts on ecosystem services (ESs) functions. As the origin of the Belt and Road Initiative (BRI) initiated by China, Central Asia nations (CANs) provide a prism to examine the impact of LUCC and ESs changes brought by the BRI. The impacts of LUCC and ecological influences were evaluated. The land use transfer matrix and dynamic index, the Vector Autoregressive (VAR) model, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), the Carnegie Ames–Stanford Approach (CASA) model, and the Revised Wind Erosion Equation (RWEQ) model were used to evaluate the impact of export trade from the CANs to China (ETCC) on LUCC and ESs in the CANs before and after the BRI. Results showed that before and after BRI (2001–2020), agricultural land and construction land increased by 59,120 km2 and 7617 km2, respectively, while ecological land decreased by 66,737 km2. The annual growth rate of agricultural land and the annual reduction rate of ecological land after the BRI were higher than that before the BRI, while the annual growth rate of construction slowed down. Among the ecological land, the forestland increased by 5828 km2 continuously, while the grassland increased by 12,719 km2 and then decreased of 13,132 km2. The trends for LUCC spatial variation were similar. The development of ETCC positively affected the changes in agricultural and construction land in the CANs and negatively affected the changes in ecological land. The average contribution rates of the ETCC to changes in agriculture, construction, and ecological lands after the BRI were higher than those before the BRI. They increased by 5.01%, 3.33% and 5.01%, respectively. The ESs after the BRI improved compared with those before the BRI, indicating that, during short-term implementation of the BRI, ETCC growth also ensures the ecological protection of CANs. This study provides a reference for dealing with trade, land management and environmental protection relations between member countries of international economic alliances worldwide.

Hydrological Response of the Wami–Ruvu Basin to Land-Use and Land-Cover Changes and Its Impacts for the Future

The evaluation of the hydrological responses of river basins to land-use and land-cover (LULC) changes is crucial for sustaining water resources. We assessed the impact of LULC changes (1990–2018) on three hydrological components (water yield (WYLD), evapotranspiration (ET), and sediment yield (SYLD)) of the Wami–Ruvu Basin (WRB) in Tanzania, using the Soil and Water Assessment Tool (SWAT). The 1990 LULC imagery was used for SWAT simulation, and imagery from 2000, 2010, and 2018 was used for comparison with modelled hydrological parameters. The model was calibrated (1993–2008) and validated (2009–2018) in the SWAT-CUP after allowing three years (1990–1992) for the warm-up period. The results showed a decrease in WYLD (3.11 mm) and an increase in ET (29.71 mm) and SYLD (from 0.12 t/h to 1.5 t/h). The impact of LULC changes on WYLD, ET, and SYLD showed that the increase in agriculture and built-up areas and bushland, and the contraction of forest led to the hydrological instability of the WRB. These results were further assessed with climatic factors, which revealed a decrease in precipitation and an increase in temperature by 1 °C. This situation seems to look more adverse in the future, based on the LULC of the year 2036 as predicted by the CA–Markov model. Our study calls for urgent intervention by re-planning LULC and re-assessing hydrological changes timely.

Have land use and land cover change affected soil thickness and weathering degree in a subtropical region in Southern Brazil? Insights from applied mid-infrared spectroscopy

Land use and land cover changes (LUCC) can drastically alter various components of the critical zone, including soil thickness and soil chemical weathering processes. Often these studies, however, tend to focus on extreme cases, not representing what actually happens on average at larger, regional scales. Here, we evaluate the impact of LUCC on soil thickness and soil weathering degree at the regional scale, where we use soil spectroscopy to derive weathering indices. In a subtropical region in Southern Brazil, we collected calibration/validation soil samples (n = 49) from 4 different locations for which we measured the mid-infrared (MIR) spectral reflectance and 3 soil chemical weathering indices: chemical index of alteration (CIA), the total reserve in bases (TRB), and the iron ratio (Fed/Fet). We used partial least square regressions on this calibration/validation dataset to relate the MIR spectra of the soil samples to these weathering indices, resulting in good calibration relationships with R2 values of 0.97, 0.91 and 0.84 for CIA, TRB and Fed/Fet, respectively. Applying these relations to MIR spectra of regionally collected soil samples allowed us to calculate soil weathering degrees for a large number of soil samples (n = 229), without requiring costly and time-consuming chemical analyses. We collected these soil samples at 100 mid-slope positions: 50 under forest and 50 under agricultural land use. Land use explained only a minor part of the variation in soil thickness and weathering degree. Thus, while local water and tillage erosion rates might be considerable after deforestation, this has not led to significant reductions in average soil thickness and has not affected soil weathering degree. Slope gradient is the main factor influencing the spatial variability in soil thickness and weathering degree on mid-slope sections in our study area. Human activities over the last century did not fundamentally alter these patterns.

Global and regional impacts of land cover changes on isoprene emissions derived from spaceborne data and the MEGAN model

Abstract. Among the biogenic volatile organic compounds (BVOCs) emitted by plant foliage, isoprene is by far the most important in terms of both global emission and atmospheric impact. It is highly reactive in the air, and its degradation favours the generation of ozone (in the presence of NOx) and secondary organic aerosols. A critical aspect of BVOC emission modelling is the representation of land use and land cover (LULC). The current emission inventories are usually based on land cover maps that are either modelled and dynamic or satellite-based and static. In this study, we use the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) model coupled with the canopy model MOHYCAN (Model for Hydrocarbon emissions by the CANopy) to generate and evaluate emission inventories relying on satellite-based LULC maps at annual time steps. To this purpose, we first intercompare the distribution and evolution (2001–2016) of tree coverage from three global satellite-based datasets, MODerate resolution Imaging Spectroradiometer (MODIS), ESA Climate Change Initiative Land Cover (ESA CCI-LC), and the Global Forest Watch (GFW), and from national inventories. Substantial differences are found between the datasets; e.g. the global areal coverage of trees ranges from 30 to 50×106 km2, with trends spanning from −0.26 to +0.03 % yr−1 between 2001 and 2016. At the national level, the increasing trends in forest cover reported by some national inventories (in particular for the US) are contradicted by all remotely sensed datasets. To a great extent, these discrepancies stem from the plurality of definitions of forest used. According to some local censuses, clear cut areas and seedling or young trees are classified as forest, while satellite-based mappings of trees rely on a minimum height. Three inventories of isoprene emissions are generated, differing only in their LULC datasets used as input: (i) the static distribution of the stand-alone version of MEGAN, (ii) the time-dependent MODIS land cover dataset, and (iii) the MODIS dataset modified to match the tree cover distribution from the GFW database. The mean annual isoprene emissions (350–520 Tg yr−1) span a wide range due to differences in tree distributions, especially in isoprene-rich regions. The impact of LULC changes is a mitigating effect ranging from 0.04 to 0.33 % yr−1 on the positive trends (0.94 % yr−1) mainly driven by temperature and solar radiation. This study highlights the uncertainty in spatial distributions of and temporal variability in isoprene associated with remotely sensed LULC datasets. The interannual variability in the emissions is evaluated against spaceborne observations of formaldehyde (HCHO), a major isoprene oxidation product, through simulations using the global chemistry transport model (CTM) IMAGESv2. A high correlation (R > 0.8) is found between the observed and simulated interannual variability in HCHO columns in most forested regions. The implementation of LULC change has little impact on this correlation due to the dominance of meteorology as a driver of short-term interannual variability. Nevertheless, the simulation accounting for the large tree cover declines of the GFW database over several regions, notably Indonesia and Mato Grosso in Brazil, provides the best agreement with the HCHO column trends observed by the Ozone Monitoring Instrument (OMI). Overall, our study indicates that the continuous tree cover fields at fine resolution provided by the GFW database are our preferred choice for constraining LULC (in combination with discrete LULC maps such as those of MODIS) in biogenic isoprene emission models.

Land use and land cover change and their impact on temperature over central India

This study explored the land use and land cover changes (LULCC) during 1981–2006 over central India and their impact on the surface temperature over this region. The land use maps were prepared from the Advanced Very High Resolution Radiometer (AVHRR) datasets to investigate the LULCC during 1981–2006 and the impact of LULCC was investigated from the Observation Minus Reanalysis method. The overall analysis indicated a decrease in the small vegetation lands and open forests during 1981–2006 and an increase in the dry lands, agricultural lands and dense forests during this period. As a probable consequence, the temperature trend increased by 0.076 °C per decade due to the LULCC over central India.

Future scenarios impact on land use change and habitat quality in Lithuania

Anticipating future land use and land cover (LULC) changes can improve our knowledge of the complexity of human-environment interactions that lead to transformations in the landscape. Therefore, it is key to understand these LULC changes under different scenarios and how they affect habitat quality (HQ) a key indicator for ecosystem services (ES) supply quality. This work aims to study the impacts of LULC changes under different scenarios: business as usual (A0), urbanisation (A1), land abandonment and afforestation (A2) and agriculture intensification (A3) in 2050. To simulate future LULC changes we applied the Cellular Automata (CA) method, and to assess HQ, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used. Spatial autocorrelation was assessed with a Moran's I index and the Getis Ord* hotspot analysis. The result showed that the LULC model calibration and validation were accurate (80%). Between 1990 and 2018 there was an increase in urban areas and forest and woodlands, which was reflected in the A0 scenario in 2050. Under the A1 scenario there was an increase in the urban area (4628 ha) compared to 2018, and in the most important cities (e.g., Vilnius, Kaunas, Klaipeda) in the scenario A2 there was an increase of 375,820 ha of woodland and forest. Finally, under the scenario A3, a large growth in cropland area (884,030 ha) was identified. HQ model had a better validation using three cover density data (r2 = 0.67), than with imperviousness (r2 = 0.26). A2 scenario showed the highest HQ and A3 scenario have the lowest HQ. The land uses of 1990, 2018, and A3 scenario had a clustered distribution while A0, A1 and A2 showed a random pattern. The results can support policy-makers by assessing the impact of future LULC changes in Lithuania.