Assessment Of Land Use Change Research Articles

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.

Comprehensive Analysis of Land Use Change and Carbon Sequestration in Nepal from 2000 to 2050 Using Markov Chain and InVEST Models

The escalating pace of migration and urbanization in Nepal has triggered profound alterations in land use practices. This event has resulted in a considerable diminution of ecological diversity and a substantial decline in the potential for carbon sequestration and other ecosystem services, thereby impeding climate change mitigation efforts. To address this, a comprehensive assessment of land use change and carbon storage was conducted from 2000 to 2019 and forecasted to 2050 in Nepal. Employing the Markov chain and InVEST models, this study evaluated the loss and gain of carbon, elucidating its economic value and spatial distribution. The findings revealed that carbon storage in 2000 and 2019 were 1.237 and 1.271 billion tons, respectively, with a projected increase to 1.347 million tons by 2050. Carbon sequestration between 2000 and 2019 amounted to 34.141 million tons, which is anticipated to surge to 76.07 million tons from 2019 to 2050, translating to economic valuations of 110.909 and 378.645 million USD, respectively. Forests emerged as pivotal in carbon storage, exhibiting higher carbon pooling than other land use types, expanding from 37% to 42% of the total land area from 2000 to the predicted year 2050. Notably, carbon distribution was concentrated in parts of the terai and mountain regions, alongside significant portions of the hilly terrain. The findings from this study offer valuable insights for governing Nepal and REDD+ in developing and implementing forest management policies. The results emphasize the importance of providing incentives to local communities judiciously to promote effective conservation measures.

Assessment of land use change in the dryland agricultural region of Córdoba, Argentina, between 2000 and 2020 based on NDVI data

The dryland region of Córdoba province experienced a strong increase in agricultural land-use in the 21st century. Between years 2000 and 2020 the temporal variation of land-use measures derived from the seasonal variation curve of the Normalized Difference Vegetation Index (NDVI) was analyzed. In eleven departments of the region, the following NDVI measurements wereobtained for each crop cycle from September to April: minimum value (NDVIn), maximum value (NDVIx), amplitude (NDVIa=NDVIx-NDVIn) and mean value (NDVIm). The sowing percentage per department was analyzed spatially and temporally, as well as the land use indicators. Both NDVIn and NDVIx are related to the sowing area per department, determining a negative correlation (-0.36) for NDVIn and a positive one (0.596) for NDVIx. The positive correlation with NDVIa (0.569) is considered directly linked to the agricultural land use. The seasonal variation of the NDVI showed changes over time, which werecompatible with the increase in agricultural activity in the region. Although the increase in agricultural land use was noticeable through both the decrease in NDVIn and the increase in NDVIx, along with a general trend towards rising NDVIa values, the variation was more apparent in those departments where agricultural activity increased to a greater proportion.

Assessment of Land Use Changes Using Remote Sensing and Geographic Information System (GIS) in Kumbotso Local Government Area, Kano State

Assessment of Land Use Changes Using Remote Sensing and Geographic Information System (GIS) in Kumbotso Local Government Area, Kano State

Amazon Deforestation and Global Meat Consumption Trends: An Assessment of Land Use Change and Market Data from Rondônia That Shows Why We Should Consider Changing Our Diets

This paper seeks to elucidate the interrelationship between global meat consumption and deforestation in the Amazon region. To this end, empirical research is conducted to investigate land use changes in Rondônia and the expansion of pasture areas and beef production. Brazil is one of the largest beef producers in the world, with products destined for local and global markets. Based on bibliographical research, the paper analyzes maps of land use change between 1985 and 2021, using Landsat satellite imagery and the MapBiomas methodology for Landsat mosaic and classification. The research shows that beef from Rondônia is primarily purchased and consumed in Brazil, but it is also bought and sold on the international market. Landsat imagery analysis shows the predominance of forest conversion to pasture in Rondônia. The results show that deforestation in the Amazon is directly linked to the growth of cattle ranching. Land use change from native forest to pasture for beef cattle production is a reality in the Brazilian Amazon, especially in Rondônia. It suggests the urgent need for more conscious consumption and production practices as well as ethical and sustainable eating habits.

A Simulated Assessment of Land Use and Carbon Storage Changes in the Yanqi Basin under Different Development Scenarios

A Simulated Assessment of Land Use and Carbon Storage Changes in the Yanqi Basin under Different Development Scenarios

Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during the summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation (R2 = 0.879) compared to Landsat (R2 = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects.

Assessment of land use changes in Hung Yen province from 2010 to 2020, forecast to 2030 and proposed solutions for sustainable land use of the province

Hung Yen is a province in the Red River Delta, located in the center of the Northern Delta and the Northern Economic Zone (Hanoi - Hung Yen - Hai Duong - Hai Phong - Quang Ninh). Due to that favorable geographical location, in recent years, infrastructure and industrial parks in the province have developed strongly. The results of the assessment of land use changes in the period 2010-2020 in Hung Yen province show that the period 2015-2020 had more significant changes than the period 2010-2015. For industrial land, the period 2015-2020 saw an increase of 137.70%, while the period 2010-2015 saw an increase of 84.25%. Residential land, office buildings, transportation, and other non-agricultural land increased by 8.3% in the period 2015-2020, while it increased by 6.81% in the period 2010-2015. On the other hand, the agricultural land fund also saw a faster decline in the period 2015-2020 than in the period 2010-2015. For example, the area of land for perennial crops decreased by 18.71% in the period 2015-2020, while it decreased by 7.75% in the period 2010-2015. The results of the forecast of land use status to 2030 show that the area of non-agricultural land has surpassed that of agricultural land. In particular, the area of land for annual crops has decreased significantly, with a decrease of 8.88%, much higher than the 4.60% in the period 2010-2020. This type of land was used for growing rice and other vegetables to ensure food security for the province and the country. In addition, due to the shrinking agricultural land area, it is necessary to switch the crop structure to be suitable for climatic conditions as well as for each type of soil and terrain conditions. In addition, it is necessary to apply scientific and technical methods to agriculture to increase productivity and achieve high economic efficiency.

Ecological Risk Assessment of Land Use Change in the Tarim River Basin, Xinjiang, China

In recent years, global climate change and human alterations to land use have led to a decrease in ecosystem services, making ecosystems more vulnerable. However, unlike the well-established risk assessment frameworks used in natural disaster research, the concept of ecological risks arising from changes in land use is still in its early stages, with its nuances and assessment methodologies yet to be clearly defined. This study proposes a new framework for assessing ecological risks resulting from changes in land use in the Tarim River Basin. The framework employs a coupled PLUS and Invest model to evaluate the ecological risks of land use change under three development scenarios projected for the Tarim River Basin in Xinjiang by 2035. The findings indicate that: (1) Between 2000 and 2020, the predominant land use types in the Tarim River Basin in Xinjiang were primarily unused land, followed by grassland and cropland. Conversely, grassland, water, and construction land were relatively less prevalent. During this period, the area of unused land and cultivated land increased, while grassland, forest land, and water exhibited a declining trend. Moving forward, under the three scenarios from 2020 to 2035, land use changes in the study area are characterized by the expansion of cropland and unused land, coupled with a significant decrease in grassland area, while other land categories demonstrate minor fluctuations. (2) From 2020 to 2035, across various scenarios, the total ecosystem service within the study area demonstrates an overall increasing trend in both the northern and southern marginal zones. Specifically, under the baseline scenario, the total amount of ecosystem services in the study area decreased by 15.247% compared to 2020. Similarly, under the economic development scenario, this decrease amounted to 13.358% compared to 2020. Conversely, under the ecological protection scenario, the decrease reached 19.852% compared to 2020. (3) The structure of ecological risk levels from 2020 to 2035, across multiple scenarios, demonstrates a consistent pattern, characterized by a predominant proportion of moderate risk. Conversely, other risk levels occupy relatively smaller proportions of the area.

Assessment of Ecological Flow in Hulan River Basin Utilizing SWAT Model and Diverse Hydrological Approaches

Human activities have significantly altered the hydrological processes of rivers. In recent years, the increased focus on global water resource exploitation and land use changes has heightened the significance of related ecological and environmental issues. To investigate the land use changes in Hulan River Basin between 1980 and 2020, and the corresponding flow under various ecological standards, a quantitative assessment of land use changes in Hulan River Basin was conducted by analyzing the Land Use Dynamic Degree (LUD) index and the land use change matrix. Two types of models, namely natural runoff models and status quo runoff models, were developed to evaluate alterations in basin runoff. Various hydrological techniques were utilized to calculate the ecological water deficit in Hulan River Basin. The results suggest the following: (1) human consumption comprises approximately 40% of surface water resources, with Hulan River Basin exhibiting a moderate consumption level; (2) when determining the minimum ecological flow, the Distribution Flow Method (DFM) method yielded slightly higher outcomes compared to alternative methodologies; both the variable Q90 method and DFM (Q2) method satisfy 10% of the natural river flow, however, in terms of capturing the hydrological pattern, DFM exhibits a slightly lower fitting degree compared to the variable Q90 (monthly average flow with 90% guarantee rate) method; (3) DFM is identified as scientifically reasonable for determining the most suitable ecological flow in comparison to other hydrological methods; (4) despite the widespread water scarcity in Hulan River Basin, the variance between most periods and the ideal ecological flow remains minimal, indicating that severe water shortages are uncommon.

The large-scale expansion of rubber plantations in southern India: major impacts and the changing nature of drivers

This study investigates the major environmental and socio-economic impacts of an increase in the area of rubber plantations and the changing patterns of drivers of land use changes. Using a combination of geospatial techniques and socio-economic methods, we mainly analyzed the rate of increase in area under rubber plantations, the major impacts of land use changes, and the changing drivers of land use changes. Our results show that the area under rubber plantations has increased significantly within the study area, with the area under rubber plantations increasing from 30 to 74% of the total area within five decades. Impact assessment of land use changes based on household surveys showed significant improvement in the socio-economic conditions of the farmers, however, at the expense of severe environmental degradation. Our results also indicate that while areas under rubber plantations continue to increase, the drivers of land use changes have changed over time. Furthermore, it has been observed that in the past, many interventions prioritized social and economic development and placed less emphasis on the ecological stability of the region. Perceptions of farmers revealed that the effects of ecological fragility already affected the economic robustness of the whole area. Therefore, we conclude that government interventions to support additional rubber cultivation should also focus on ecosystem stabilization in order to minimize the risk of an ecological catastrophe that would significantly affect the economic prosperity of the region.

Integrated assessment of future climate and land use changes on urban floods: A Markov chain and PCSWMM-based approach for Hyderabad case study.

This research examines the impact of climate change and urban expansion on urban drainage systems in Hyderabad (Zone-XII, Zone-IV&V), India. It employs a Markov chain-based framework to simulate future climate and land changes. Integrated 1D-2D PCSWMM model is used to assess the hazards posed by these changes. Present and future extreme rainfall event(s) (1-10 days) are simulated to determine maximum flooding hours, valuable for resilience studies. Future rainfall events are simulated under four SSP scenarios using CMIP6 Global Climate Models (GCMs): EC-Earth3-Veg, MPI-ESM-1-2-HR, and MPI-ESM-1-2-LR. The Markov Chain Precipitation Generator (MCPG) model downscales grid-scale precipitation data to station-scale. Future urban land expansion is simulated using the Markov Chain-Cellular Automata (MC-CA) model with Terrset. MCPG model is validated using performance measures, and it showed most increased rainfall events under EC-Earth3-Veg. The MC-CA model obtained a Kappa coefficient of 0.89, indicating an increase in imperviousness in future LULC; 6.1% of vegetation and 29.06% of barren land in 2022 will be urbanized by 2075. A significant increase in extreme flood hazard areas for the 1-day and above 7-day events in the both zones is observed from the PCSWMM results. The study highlighted the importance of Markov chains and event duration in flood hazard assessments.

Assessment of land use change of ecological green wedge and cooling island effect: A case study of Wuhan, China.

The construction of urban ecological green wedges, which can mitigate the heat island effect through cooling and ventilation effects, is an important way to enhance the adaptation of cities to climate change. Dynamic monitoring and periodic assessment of both the conservation status and cooling effect of ecological green wedges is a key to ensure the heat mitigation benefits. Based on multi-source remote sensing data, we systematically analyzed the land use changes of six ecological green wedges in Wuhan in 2013 and 2020 using the methods of Markov transfer matrix, land use dynamics, and comprehensive index of land use degree, and evaluated the changes in surface temperature of the ecological green wedges and their cooling island effect. Results showed that the ecological green wedges in Wuhan generally had a large amount of construction land encroaching on ecological land from 2013 to 2020, with the water decreased the most. With the continuous deterioration of ecological green wedges, their land surface temperatures showed rising trends, together with significant weakening trends in cooling island effects. Among all the six wedges, the Dadonghu, Tangxun, and Wuhu exhibited relatively better ecological conservation, slighter land use change and lower overall development degree. Qinglinghu and Houguanhu demonstrated average levels of conservation. Fuhe experienced the most severe change under the significant influence of the westward policy of Wuhan City, with the proportion of water decreasing by 7.1%, warming up by 3.00 ℃, and the largest reduction in cooling distance for the cooling island effect, amounting to about 210 m. The results provided scientific evidence for the urban heat island mitigation-oriented planning and management of ecological green wedges for Wuhan City.

Assessment of land use change and carbon emission: A Log Mean Divisa (LMDI) approach

Changes in land use have a notable influence on carbon emissions since they can affect the levels of carbon stored in both soil and vegetation. To effectively analyze the factors influencing carbon emissions from land use change, the Log Mean Divisa (LMDI) method is commonly employed. The LMDI method is a decomposition analysis that dissects changes in carbon emissions into different factors, including shifts in land use patterns, population growth, economic activity, and energy intensity. This approach enables the identification of specific drivers of carbon emission changes and the development of targeted policy interventions to address them. To explore the relationship between land use change, carbon emissions, and the LMDI method, a case study analysis can be conducted. This involves selecting a particular region or country experiencing land use change and examining the factors driving these transformations. Subsequently, the LMDI method can be applied to decompose the changes in carbon emissions within the selected region or country, thereby pinpointing the major contributors to these changes. In our study, we observed the necessity of regulating energy consumption and greenhouse gas emissions in urban communities through sustainable practices and technologies. The research highlighted variations in energy consumption, emissions, renewable energy utilization, and public transportation usage among selected cities in China. Moreover, the study demonstrated land use patterns and their associated carbon emissions, alongside the findings of the LMDI analysis, which explored carbon emissions based on different land use patterns. The study illuminates the importance of understanding the relationship between land use change and carbon emissions, employing the LMDI method as a valuable analytical tool. It underscores the significance of sustainable practices and technologies in mitigating carbon emissions in urban areas and provides insights into the role of land use patterns in shaping carbon emission outcomes.

Monitoring Net Land Take in a Metropolitan Region—Portugal

This study seeks to contribute to the definition of a “no net land take” policy by 2050 for Portugal’s second-largest metropolitan region (AMP, Porto Metropolitan Area) while sensitising those involved in regional and local planning to the European target. Based on an assessment of land use changes in AMP and its municipalities during 2007–2018, soil sealing levels in 2018 and population evolution, the study quantifies the processes that may impart achievement of the 2050 objective and identifies the regional drivers of net land take, to support the definition of both interventions to decrease land take and soil sealing and related targets. The main contribution of the research is the exploration of new indicators in terms of soil sealing and population data to identify the potential for implementing interventions proposed by the EU Soil Strategy that do not jeopardise the maintenance of biodiversity in urban areas. The land take rate in the AMP was the highest among mainland Portugal regions. Its main drivers were the development of transport networks, industrial and commercial units and dispersed housing. The reuse and re-naturalisation of artificial land have seen little use in the region. Accordingly, the daily net land taken in the AMP (0.59 ha/day) still needs to decrease until 2050. While artificial land increased across the AMP, most of its municipalities lost population. To reverse this trend, the AMP should implement tighter control mechanisms that ensure that infrastructure and housing needs are fully met through the reuse of urban areas that are already sealed. However, given that the share of impermeable soil in most urban areas is already significantly high, there will have to be a careful choice of locations where intensifying land use will cause less environmental damage. It is concluded that the degree of soil sealing within urban areas is fundamental for deciding on the interventions to be carried out to reduce net land take and for defining a policy towards meeting the 2050 target.

Assessment of Land Use changes and its impact on environment in the least populous district of Haryana through Remote Sensing methods (2001-2021)

In today’s world, almost every accessible piece of land today is being utilized for some or the other purpose directly affecting human needs. Not only is the land being used intensively, but is also evolving and changing with time. The rapid and intensive changes in land use and land cover (LULC) have created the need to quantify these changes in numbers and maps, so that we can understand this information to the best use possible. Thus, this paper aims to examine Panchkula district focusing upon the relationship of land use land cover (LULC) and the consequent changes in environment. Three annual LULC maps (2001, 2011 and 2021) were prepared with the help of satellite images. The change detection showed that built-up area has increased by approximately 268% in two decades with a total area of 10261.9 ha area in 2021, thus indicating that water bodies and barren land were converted into settlement for managing the population across the district and introducing infrastructure for the same. However, the forest and river bed area has increased by 19 % and 78.02 % respectively, while agricultural land was noticed to be increased by 55.62 % with a significant increase during 2001-11 and a slight decrease after 2011. The open scrub land has increased by 56 %. Thus, the present study can help with identifying areas experiencing significant changes in ecosystems and natural resources in the district. It can also provide valuable insights into the expansion of urban areas, changes in infrastructure and the encroachment on natural and agricultural lands, thereby contributing to urban planners to understand urban growth patterns, assess the impacts and make informed decisions regarding land zoning, infrastructure development and resource allocations.

Analysis of Land Use Based on Carrying Capacity of Agricultural Land in Bantul Regency

Population growth requires expansion of land as a place to grow and develop. If development is not controlled, land conversion can occur for activities that are not in accordance with its function, so that it has an impact on decreasing the carrying capacity of the environment. The environmental carrying capacity of an area is an important factor that must be considered so that the development process carried out can be sustainable. This study aims to determine changes in agricultural land and land carrying capacity in Bantul Regency. The method used is to analyze land change, evaluate land use based on land class and subclass and analyze the carrying capacity of land in Bantul Regency. In formulating these recommendations, several stages were carried out in this research. Geographic analysis is carried out by optimizing Geographic Information System (GIS) applications to map land conditions including an assessment of land use changes over several years.

Impact assessment of land use and land cover change on soil erosion at Laonung watershed in Taiwan

Impact assessment of land use and land cover change on soil erosion at Laonung watershed in Taiwan

Impact Assessment of Land Use and Land Cover Change on the Runoff Changes on the Historical Flood Events in the Laigiang River Basin of the South Central Coast Vietnam

Impact Assessment of Land Use and Land Cover Change on the Runoff Changes on the Historical Flood Events in the Laigiang River Basin of the South Central Coast Vietnam

Monitoring and multi-scenario simulation of agricultural land changes using Landsat imageries and FLUS model on coastal Alanya

Anthropogenic activities have adverse impacts on productive lands around coastal zones due to rapid developments. Assessment of land use and land cover (LULC) changes provides better understanding of the process for conservation of such vulnerable ecosystems. Alanya is one of the most popular tourism hotspots in Mediterranean coast of Turkey, and even though the city faced with severe LULC changes after mid-80s due to tourism-related investments, limited number of studies has conducted in the area The study aimed to determine short-term and long-term LULC changes and effects of residential development process on agricultural lands using six Landsat imageries acquired between 1984 and 2017, and presented the first attempt of future simulation in the area. Average annual conversions (AAC) (ha) calculated to assess magnitudes of annual changes in six different periods. AACs used to calculate area demands for LULC2030 and LULC2050, whereby annual conversions from different periods were multiplied by number of years between 2017, 2030 and 2050 for each scenario. Finally, optimistic and pessimistic scenarios for agricultural lands are simulated using FLUS model. Accordingly, agricultural lands decreased from 53.9% to 31.4% by 22.5% in 33 years, and predicted to change between 19.50% and 24.63% for 2030, 1.07% and 14.10% for 2050, based on pessimistic and optimistic scenarios, respectively.