Impact Of Land Use Change Research Articles

Assessing the Sustainability Impact of Land-Use Changes and Carbon Emission Intensity in the Loess Plateau

Assessing the Sustainability Impact of Land-Use Changes and Carbon Emission Intensity in the Loess Plateau

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

The impact of land use change on food security under the background of rapid urbanization - a case study of Xiamen city

Abstract China has undergone a long period of rapid urbanization from 2000 to 2020, resulted in huge conversion of arable land into built-up areas. This situation has raised concerns regarding food security, including issues like reduced food supply and challenges to achieving food self-sufficiency, particularly in certain regions and during special period. To address these issues, this study focuses on Xiamen, a rapidly urbanizing coastal city in China, and examined both the food supply and demand. On hand of the supply, this study mainly analyzed the attributes of the food availability, indicators like the food production (FP) of the ecosystem service value (ESV), per capita grain production, imports and exports along with food price were calculated. The findings revealed a significant expansion of built-up areas in Xiamen, mostly at the expense of arable land. The declining arable land coupled with population growth due to rapid urbanization contributed to a decrease in per capita grain production, drop to 6 kg in 2018, which is merely 1% of China’s average. A comparison of per capita grain production across various regions, as well as changes in China’s grain import and export, highlighted a notable discrepancy between urbanization rates and food security in Xiamen. It has become challenging for Xiamen to rely on outside for sustained food import. Therefore, it is imperative for Xiamen to implement a range of measures and policy interventions to ensure a certain level of food self-sufficiency and protect basic arable land.

Assessing the impact of Land Use/Land Cover Change on Land Surface Temperatures and SUHI: Case of Pune, India

The emergence of urban heat islands and rising land surface temperatures in developing countries like India is becoming a crucial concern for urban planners and policymakers. This study attempts to assess the impact of Land use and land cover (LULC) change on the Land Surface Temperature (LST) and Surface Urban Heat Islands (SUHI) in Pune, India, using remote sensing and Geographic information systems (GIS). A spatiotemporal analysis of the Landsat satellite imagery from 2000 – 2023 has been used to trace the LULC trends and compute LST variations across the years in land cover types. The thermal band, 10 of the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), is used for computing LST. Spatial indicators such as normalized difference vegetation index (NDVI) and normalized differentiated built index (NDBI) are also calculated. Results indicate that there has been a 30% decline in vegetation across the city over the years, alongside an increase of 16.64°C in LST due to urbanization-induced LULC changes. Furthermore, this study attempts to identify the thermal hotspots in the city. The results of this study can enable the assessment of urbanization and the formulation of informed climate-sensitive urban planning strategies. Keywords: Land Surface Temperature, Pune, Remote Sensing, GIS, Local Climate Zone, SUHI

An integrated simulation-optimization modeling approach for coupled risk management of blue water and green water under changing environmental conditions

Due to the impact of global climate change and land use changes, the spatiotemporal distribution and water cycle processes of watershed water resources are affected. In order to sustainably manage watershed water resources, it is necessary to accurately assess the available water volume to meet the coordinated management of the watershed's socio-economic subsystem and eco-environment subsystem. The amount of Bluewater resources (BW) is closely related to the amount of Greenwater resources (GW). BW is directly related to human consumption in the socio-economic subsystem, while GW is used to maintain the health of the ecosystem. A method called the integrated simulation-optimization modeling system (ISOMS) was developed to evaluate adaptive strategies for dealing with the combined effects of climate change and land-use changes. ISOMS not only predicts future hydrological trends under varying environmental conditions but also generates comprehensive risk management plans that incorporate different types of uncertainties, including random and fuzzy factors. The Copula function is introduced to handle the interaction between available BW and available GW. The results showed that: (i) uncertainties in the hydrologic system could result in alterations to the distribution of water resources; (ii) system benefits are, to some extent, affected by land use change and climate change; (iii) the shortage of BW is affected by the level of risk, and the joint risk increases, resulting in an increase in water scarcity; (iv) the planned annual agricultural water consumption is the highest, followed by domestic water consumption, and industrial water consumption is the lowest. Through the results of the model operation, the joint risk assessment and adaptive management of BW and GW in the East River Basin (ERB) under changing environments, as well as the BW allocation plan, are obtained to provide support for scientific and reasonable resource collaborative decision-making and promote the synchronized advancement of the socio-economic subsystem and eco-environment subsystem in the ERB.

Examining the impact of land use and land cover changes on land surface temperature in Herat city using machine learning algorithms

Examining the impact of land use and land cover changes on land surface temperature in Herat city using machine learning algorithms

The Impact of Land Use and Land Cover Changes on Ecosystem Services Value in Laos between 2000 and 2020

The Impact of Land Use and Land Cover Changes on Ecosystem Services Value in Laos between 2000 and 2020

Redefining the modified water benefit-based ecological index to evaluate the impact of cropland expansion on the ecological environment in an arid area

Global land-use changes have a significant impact on the environment and food security, and escalating human activity and uncontrolled agricultural land expansion pose a grave threat to regional ecosystems. This study aims to assess the challenges faced by the environment and food security, with a particular focus on the impact of land use change on ecosystems. The study selected the Ebinur Lake Basin, a typical arid region in China, as the object and analyzed the land type changes from 2013 to 2021 using the Google Earth Engine platform and the China Land Cover Dataset. We created an Improved Water-Benefit-Based Ecological Index (IWBEI) based on the poor air quality environment in the watershed, and then calculated the ecological index of the watershed. The results indicate that the grassland and bare land areas in the Ebinur Lake Basin have fluctuated and shown an overall downward trend. The trend of farmland expansion is to expand to surrounding areas on the basis of existing farmland. The overall center of gravity of cultivated land in the watershed is moving from northwest to southeast, mainly towards the water source area. The IWBEI index is more prominent in identifying cultivated land and wetlands in arid regions. According to IWBEI's calculations, the priority order of land types is: forest > cultivated land > wetland > water > snow > grassland > impermeable surface > bare land. The overall ecological environment quality of the watershed is showing a deteriorating trend. Therefore, relevant departments should pay attention to the impact of farmland expansion on the local ecological environment to avoid the continuous deterioration of the ecological environment.

Assessing the impact of land use and land cover change on the Densu Delta wetland using Markov chain modeling and artificial neural networks

This study investigates the dynamics of land use and land cover (LULC) changes in the Densu Delta wetlands, a critical ecosystem in Ghana. Here, satellite images spanning from 1998 to 2023 were used to analyse the spatio-temporal patterns of LULC changes and their implications for water bodies, wetlands, vegetations, bare lands and urban areas in the Densu Delta wetland. Employing advanced techniques such as Markov chain modelling and artificial neural networks (ANNs), the research assesses and predicts LULC alterations. Significantly, the largest loss of LULC is observed in the Densu Delta wetland, where wetlands transition to waterbody cover type (14.02 km²). Model validation for 2023 attests to the accuracy of the model, boasting a correctness percentage of 70% and a kappa value of 0.74. In-depth analyses explore regional variations in the Densu Delta wetlands, revealing distinct patterns in the rates of LULC change before and after 2013. Notably, urbanization emerges as a prominent factor post-2013, with urban areas experiencing remarkable rates of change in the wetland. Transition matrices underscore the intricate interplay of different land cover classes over the years. Simulated LULC predictions for 2033 and 2043 highlight the urban land cover type as having the highest positive change, recording approximately 0.39% for the Densu Delta wetland. The wetland land cover in the Densu Delta wetland exhibit negative changes of about −0.52%. The synthesis of LULC data enhances our understanding of the complex interactions shaping these critical ecosystems. This research offers valuable insights for sustainable environmental conservation, emphasizing the pivotal role of informed urban planning policies. It also unveils potential challenges posed by climate change, advocating for a holistic approach to preserve these vital wetland ecosystems.

The Impact of land use change on peatland degradation: A case Nathong and Saming Village, Champhone district, Champasack Province, Lao PDR

The major impact on land use change and peatland degradation was directly from human activities and inappropriate management. Changing of land use and land cover (LULC) influence directly on peat land drained and degraded. Nathong and Saming Village, Champhone district, Champasack Province, Lao PDR is one of proposed peatland area and rapid LULC changes from 2016 due to a social-economic growth. Therefore, the assessment of land use change is required for sustainable peatland management. The main objectives of this study were to assess LULC and its change between 2011 to 2016 and 2016 to 2021. In this study, remote sensing data has been used for LULC classification using random forest classifier in Google Earth Engine (GEE). Then, the post-comparison change detection algorithm was applied for detected LULC changes. The result revealed that mixed deciduous area was continually decrees 523.44 ha and 607.05 ha from 2011 to 2016 and 2016 to 2021. Additionally, cassava and dry dipterocarp were increase from 138.24 ha in 2011 to 2016 to 386.1 ha in 2016 to 2021 and 93.15 ha in 2011 to 2016 to 156.42 ha in 2016 to 2021 respectively. Additionally, the derived overall accuracy and Kappa hat coefficients of the land use and land cover map in 2011,2016 and 2021 were higher than 85%. The average producer’s accuracy and user’s accuracy for all land use and land cover types were also more than 83%. The derived information of land use and land cover data of this study can be used as information to support decision-makers and land use planners for to awareness and sustainable peatland management.

The Analysis of NPP Changes under Different Climatic Zones and under Different Land Use Types in Henan Province, 2001–2020

Net Primary Productivity (NPP) is a crucial indicator of ecological environment quality. To better understand the carbon absorption and carbon cycling capabilities of Henan Province, this study investigates the trends and driving factors of NPP across different climatic zones and land use types. The Theil–Sen Median trend analysis method and the Mann–Kendall trend test are employed to monitor NPP changes from 2001 to 2020. The average annual NPP in Henan Province during this period was 414.61 gC·m−2·year−1, showing a significant increasing trend with a growth rate of 3.73 gC·m−2·year−1. Spatially, both the annual average NPP and its increase rate were higher in the western part of Henan compared to the eastern part, and NPP variability was more stable in the southern region than in the northern region. By classifying climatic zones and using the Geodetector method to assess NPP sensitivity to natural factors, the results show that climate and vegetation factors jointly influence NPP variations, with annual precipitation being the primary natural factor affecting NPP trends in Henan Province from 2001 to 2020. By analyzing the NPP gain and loss matrix, the impact of land use changes on NPP was evaluated. Forests had the highest average annual NPP at 483.52 gC·m−2·year−1, and the conversion of arable land to urban areas was identified as the primary land change type leading to NPP reductions. In the subtropical zone of Henan, forests, croplands, and grasslands exhibited higher NPP values and increase rates compared to those in the warm belt. This study provides new insights into the spatial variation of NPP caused by changes in climatic zones and land use types.

Simulation of the Potential Impact of Land Use Change on Ecological Networks in the Context of Rapid Urbanization

Simulation of the Potential Impact of Land Use Change on Ecological Networks in the Context of Rapid Urbanization

Impacts of Land Use Changes on Landscape Patterns and Ecosystem Service Values in Counties (Villages) in Ethnic Regions of China: A Case Study of Jianghua Yao Autonomous County, Hunan Province

This study, using Jianghua Yao Autonomous County in Hunan Province as a case, systematically analyzes the response of ecosystem service value (ESV) to land use and landscape pattern changes by employing landscape-level indices and landscape-type-level indices. The findings provide a reliable basis for scientifically formulating land use planning and ecological protection policies in ethnic regions, thereby promoting regional ecological security and sustainable development. This study reveals that (1) the land use structure in the county underwent significant changes between 2000 and 2020, with grassland and shrubland areas decreasing substantially by 71.66% and 78.41%, respectively, while urban and arable land areas increased significantly by 228.30% and 15.84%, respectively. Particularly under the scenario of prioritizing economic development, these changes led to increased landscape fragmentation and a decline in ecosystem service value (from CNY 296.571 billion in 2020 to CNY 287.959 billion in 2030). (2) In contrast, the scenarios of ecological protection and sustainable development significantly enhanced the region’s ecosystem service value by increasing forest and water area, effectively maintaining the stability of the landscape pattern. These findings provide important evidence for the formulation of scientifically sound land use planning and ecological protection policies, contributing to the dual goals of economic development, tourism growth and ecological protection in Jianghua Yao Autonomous County and similar regions.

Addressing soil data needs and data gaps in catchment-scale environmental modelling: the European perspective

Abstract. To effectively guide agricultural management planning strategies and policy, it is important to simulate water quantity and quality patterns and to quantify the impact of land use and climate change on soil functions, soil health, and hydrological and other underlying processes. Environmental models that depict alterations in surface and groundwater quality and quantity at the catchment scale require substantial input, particularly concerning movement and retention in the unsaturated zone. Over the past few decades, numerous soil information sources, containing structured data on diverse basic and advanced soil parameters, alongside innovative solutions to estimate missing soil data, have become increasingly available. This study aims to (i) catalogue open-source soil datasets and pedotransfer functions (PTFs) applicable in simulation studies across European catchments; (ii) evaluate the performance of selected PTFs; and (iii) present compiled R scripts proposing estimation solutions to address soil physical, hydraulic, and chemical data needs and gaps in catchment-scale environmental modelling in Europe. Our focus encompassed basic soil properties, bulk density, porosity, albedo, soil erodibility factor, field capacity, wilting point, available water capacity, saturated hydraulic conductivity, and phosphorus content. We aim to recommend widely supported data sources and pioneering prediction methods that maintain physical consistency and present them through streamlined workflows.

Impact of Land Use and Land Cover (LULC) Changes on Carbon Stocks and Economic Implications in Calabria Using Google Earth Engine (GEE).

Terrestrial ecosystems play a crucial role in global carbon cycling by sequestering carbon from the atmosphere and storing it primarily in living biomass and soil. Monitoring terrestrial carbon stocks is essential for understanding the impacts of changes in land use on carbon sequestration. This study investigates the potential of remote sensing techniques and the Google Earth Engine to map and monitor changes in the forests of Calabria (Italy) over the past two decades. Using satellite-sourced Corine land cover datasets and the InVEST model, changes in Land Use Land Cover (LULC), and carbon concentrations are analyzed, providing insights into the carbon dynamics of the region. Furthermore, cellular automata and Markov chain techniques are used to simulate the future spatial and temporal dynamics of LULC. The results reveal notable fluctuations in LULC; specifically, settlement and bare land have expanded at the expense of forested and grassland areas. These land use and land cover changes significantly declined the overall carbon stocks in Calabria between 2000 and 2024, resulting in notable economic impacts. The region experienced periods of both decline and growth in carbon concentration, with overall losses resulting in economic impacts up to EUR 357.57 million and carbon losses equivalent to 6,558,069.68 Mg of CO 2 emissions during periods of decline. Conversely, during periods of carbon gain, the economic benefit reached EUR 41.26 million, with sequestered carbon equivalent to 756,919.47 Mg of CO 2 emissions. This research aims to highlight the critical role of satellite data in enhancing our understanding and development of comprehensive strategies for managing carbon stocks in terrestrial ecosystems.

Impacts of land use change on carbon and nitrogen stocks in an Andosol in Michoacan, Mexico

Impacts of land use change on carbon and nitrogen stocks in an Andosol in Michoacan, Mexico

Analysis Of Land Use And Land Cover Changes In Port Harcourt Metropolis Using Geospatial Techniques

The study examined Land Use and Land Cover Changes in Port Harcourt Metropolis Using Geospatial Techniques from 1990 to 2020. The study made use of geospatial and longitudinal data sourced from the United States Geological Survey (USGS), employing Google Earth Engine to analyse Landsat and Google Earth Imagery of the area. Utilizing satellite imagery with a spatial resolution of 30 meters by 30 meters, supplemented with high-resolution Google Earth imagery, the study offers an extensive concept of the dynamic changes in land use in the four epochs of 1990, 2000, 2010 and 2020. The methodology entails processing and analysing satellite images to identify and classify different land use and land cover types as well as tracking their changes over time. This technique allows for precise mapping and assessment of the trend, extent, rate, and spatial patterns of land use changes. The study employed supervised classification, change detection, and temporal analysis, to ensure robust and accurate results. ANOVA statistics was deployed to test the stated hypothesis for the study. The findings revealed a drastic reduction in land use coverage for the various land use classes in the epochs studied. Open spaces showed a reduction from 62,262.2ha (58.92%) in 1990 to 41,832ha (39.32%) in 2020; farmland reduced from 21,172.5ha (20.04%) in 1990 to 1,474.65ha (1.4%) in 2020; built-up area increased from 9,006.03ha (8.52%) in 1990 to 41,502.8 (39.28%) in 2022; water bodies increased from 1,529.73ha (1.45%) in 1990 to 3,424.32ha (3.24%) in 2020. These changes have profound implications for environmental sustainability, urban planning, and resource management in the area. The study concludes that there has been substantial land use and land cover changes in Port Harcourt metropolis, driven primarily by urbanization. Thus, it is recommended that the government implement stricter urban planning and sustainable land management practices to mitigate the impact of rapid land use and land cover changes in Port Harcourt

Modeling the impact of long-term land use changes on deep soil hydrological processes in the Loess Plateau, China

Land use change can significantly affect soil hydrology in arid and semi-arid regions, making it crucial to understand the relationship between vegetation roots and soil moisture. Current models often fail to predict root growth and its impacts on water dynamics accurately. Our work presents a novel model that seamlessly integrates the Community Land Model (CLM) with the Soil & Water Assessment Tool (SWAT). Furthermore, it enhances the root module within the CLM, enabling more accurate simulations of dynamic root depth and distribution across varying tree ages. This improvement particularly considers the crucial processes of dormancy and plant maturity. Soil moisture and root patterns under apple trees of varying ages and in wheat fields on the Loess Plateau was analyzed. Our findings indicate that our dynamic root depth model outperforms traditional static models, and can accurately reflect soil moisture levels with high precision (R2 = 0.80–0.81; Nash-Sutcliffe efficiency (NSE) = 0.65–0.75). In contrast to methods that utilize fixed root depths, dynamic root simulation can provide new insights. As apple orchards mature, the roots of 22-year-old apple trees have been found to reach a depth of 21 m in the soil. Conversely, the maximum root depth of wheat is limited to 1.9 m. This latter finding aligns more closely with the measured root depths, highlighting the accuracy of dynamic simulations. This model reveals that older apple orchards show decreased soil moisture at greater depths (>20 m), contrasting with wheat fields that affect moisture mostly within the top 2 m. Our results underscore the crucial role of dynamic modeling in comprehending root-soil water interactions. Furthermore, they imply that extended orchard cultivation practices can lead to a substantial depletion of deep soil moisture. Specifically, over a period of 1 to 22 years, a water deficit of up to 85 mm yr−1 has been observed. For a 22-year-old forest, the D-D (dynamic distributions of coarse and fine roots) method calculates a significant cumulative deep Soil Water Storage loss. Over the course of 22 years, this loss amounts to 1664 mm, which is almost three times compare to the annual rainfall recorded. Such a large loss has the potential to significant impact on groundwater recharge. This highlights the need for careful consideration in future afforestation efforts to prevent increased soil aridity.

Impacts of land use changes on the spatiotemporal evolution of groundwater quality in the Yinchuan area, China, based on long-term monitoring data

Agricultural activities and rapid urbanization have significantly impacted groundwater quality, especially in semi-arid and arid regions. This study comprehensively evaluated the quality of phreatic and confined groundwater in the Yinchuan area, China, using long-term monitoring data from 1991 to 2018. Geospatial analysis model was employed to explore the spatiotemporal evolution of groundwater hydrochemistry. The effects of land use changes on groundwater quality were assessed using correlation analysis and a multiple linear regression model (MLR). The findings indicate significant temporal variations in groundwater quality, with phreatic water consistently exhibiting high salinity and hardness. The groundwater quality indices for phreatic water were frequently more polluted than confined water. From 1991 to 2018, the hydrochemical composition of phreatic water evolved from HCO3-Mg and HCO3•SO4-Mg to more complex forms such as HCO3•SO4•Cl-Mg and HCO3•Cl-Mg. In contrast, confined water predominantly maintained its HCO3-Mg type and HCO3•Cl-Na (Na•Mg) type water. Urban land had rapidly expanded in the past three decades, increasing by 318.75% compared to 1991. The water body and urban area diminished the quality of phreatic water. High salt water in increase of TDS, Cl–, SO42–, Mn, TH, NO3–, F–, and Fe into phreatic water. NO3–, NH4+, and F− in phreatic water could be impacted by human and industrial activity in urban areas. This study provides valuable insights for local decision-makers to effectively manage groundwater resources and solve issues of groundwater scarcity and water quality problems in arid and semi-arid locations.

Impacts of climate and land-use change on flood events with different return periods in a mountainous watershed of North China

Study regionLuanhe River Basin in North China Study focusGlobal warming exacerbates hydrological cycles, leading to increased intensity and frequency of floods. Regional studies on the impacts of climate change and land cover changes on flood events in recent decades are particularly important for flood prevention and risk assessment. In this study, the Peak Over Threshold- Generalized Pareto Distribution (POT-GPD) method is used to fit extreme runoff values in the Luanhe River Basin from 1961 to 2018 to identify floods with different return periods. Six flood behavior indicators are adopted to analyze the flood characteristics and extreme climate indices are also used for breakpoint testing and trend analysis. Various scenarios are established as the input of the SWAT model to study the impacts of climate change and land-use change on the flood events. New hydrological insights for the regionThe results indicate that the 2-year and 20-year return period floods are primarily rapid-rise single-peak floods, dominated by short-duration intense precipitation. The 5-year and 10-year return period floods are mainly multi-peak floods, primarily caused by long-duration precipitation. Floods in the Luanhe River Basin are primarily influenced by climate change, however, flood events do not directly correspond to the return periods of precipitation events. Forest is the most effective land-use type for flood retention. It could reduce flood magnitudes, especially for the 20-year return period floods. However, increasing forest cover does not effectively reduce the occurrence of the 5-year or 10-year floods, i.e. multi-peak floods. With more extreme rainfall events triggered by future climate change, particular attention should be paid to long-duration precipitation events, which may result in more severe disasters and economic losses.