Land Use Land Cover Change Patterns Research Articles

Integrating forest cover change and carbon storage dynamics: Leveraging Google Earth Engine and InVEST model to inform conservation in hilly regions

Forests are vital in combating climate change by storing and sequestrating CO2 from the atmosphere. Measuring the influence of land use/land cover (LULC) changes on the capacity of carbon storage (CS) within forest ecosystems presents a significant challenge. This study employs remote sensing techniques to examine the changes in spatiotemporal patterns of CS in the Chittagong Hill Tracts (CHT), resulting from LULC alterations between 1996 and 2021. LULC change patterns were identified for six different years utilizing the Google Earth Engine (GEE). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was combined with GEE to evaluate the changing patterns of CS. The study discovered that the CHT region experienced a loss of 21.65 × 106 Mg of CS, owing to a 21% reduction in vegetation cover (2862.85 km^2) during the study period. The central city area (Chittagong) accounted for the most significant loss of CS (7.99 × 106 Mg), while the suburban areas of Khagrachari (0.92 × 106 Mg) and Rangamati (3.53 × 106 Mg) contributed the least. The multiple regression model revealed that elevation and vegetation characteristics significantly influenced CS. The findings underscore the importance of developing policies and strategies that mitigate the adverse effects of land cover change on CS, and advocate for sustainable forest management practices that strike a balance between ecological, social, and economic concerns.

Open Habitats under Threat in Mountainous, Mediterranean Landscapes: Land Abandonment Consequences in the Vegetation Cover of the Thessalian Part of Mt Agrafa (Central Greece)

Land abandonment is one of the main drivers of land use/land cover (LULC) change across Europe, which has already led to a significant loss of open habitats, threatening species hosted in them. We investigated LULC changes for a period of 70 years in a mountainous area of central Greece (Mt Agrafa) by mapping its land cover for the years 1945, 1996 and 2015, calculating transition matrices of land cover classes and performing intensity analysis at different levels. Subareas of the study area, with different population trends, were compared in regard to their LULC change trends. Possible drivers of LULC changes were explored by means of Random Forest modeling, and landscape metrics were calculated to assess their trends. Our results showed great changes in LULC class cover, significant shrinkage of open habitats, accelerated rates of change in the recent period and no differences in LULC change patterns in relation to different population trends. Variables expressing favorability of ecological conditions for forest establishment or probability of farmland abandonment were found as more important drivers of the spatiotemporal distribution of LULC classes, while landscape metrics revealed certain trends. Our main conclusion is that land abandonment and the subsequent vegetation succession are going through a semifinal stage, before their completeness and the almost absolute dominance of the forest, and repopulation of the countryside cannot unconditionally ensure any halting effect on the land abandonment process.

Impact of mining on vegetation cover: A case study of Prestea Huni-Valley municipality

Land Use Land Cover (LULC) changes are the direct and indirect consequences of human actions to secure essential resources for a successful livelihood. Therefore, it has become essential to analyze such changes for effective management of natural resources and protection of our environment. Anthropogenic factors such as urbanization, mining, and population increase in the Prestea Huni-Valley municipality are causing rapid changes to the land cover. These factors among others are putting a lot of pressure on the vegetation and this has dire consequences on the availability and protection of the vegetative cover. Given this, the study focused on assessing the impact of mining on vegetation cover with a particular focus on Prestea Huni-Valley municipality. Multi-spectral satellite images of the study area from 1986 to 2016 were spatially analyzed to identify the LULC change patterns. Modeling and analysis of these images were performed using IDRISI and R software. Six land cover classes were identified including forest, open vegetation, cultivated areas, bare lands, built-up, and mine sites. The result showed that the forest, open vegetation, and bare areas decreased by 14.59 %, 3.86 %, and 8.36 % respectively whereas cultivated, built up and mines increased by 6.31 %, 3.14 %, and 7.36 % respectively.

Land Use/Land Cover Change and Their Driving Factors in the Yellow River Basin of Shandong Province Based on Google Earth Engine from 2000 to 2020

As the convenient outlet to the Bo Sea and the major region of economic development in the Yellow River Basin, Shandong Province in China has undergone large changes in land use/land cover (LULC) in the past two decades with rapid urbanization and population growth. The analysis of the LULC change patterns and its driving factors in the Shandong section of the Yellow River Basin can provide a scientific basis for rational planning and ecological protection of land resources in the Shandong section of the Yellow River Basin. In this manuscript, we analyzed the spatial pattern of LULC and its spatial and temporal changes in the Shandong section of the Yellow River Basin in 2000, 2010, and 2020 by using the random forest classification algorithm with the Google Earth Engine platform and multi-temporal Landsat TM/OLI data. The driving factors of LULC changes were also quantified by the factor detector and interaction detector in the geodetector. Results show that in the past two decades, the LULC types in the study area are mainly farmland and construction land, among which the proportion of farmland area has decreased and the proportion of construction land area has increased from 19.4% to 29.7%. Based on the results of factor detector, it can be concluded that elevation, slope, and soil type are the key factors affecting LULC change in the study area. The interaction between elevation and slope, slope and soil type, and temperature and precipitation has strong explanatory power for the spatial variation of LULC change in the study area. The research results can provide data support for ecological environmental protection, sustainable, and high-quality development of the Shandong section of the Yellow River Basin, and help local governments take corresponding measures to achieve coordinated and sustainable socioeconomic and environmental development.

Assessment of Land Use/Land Cover Change and Morphometric Parameters in the Keta Lagoon Complex Ramsar Site, Ghana

The rapid urbanization, industrialization, agricultural activities, and increasing trend of some natural hazards, such as climate change, particularly in coastal areas, necessitate the continual assessment of critical but fragile ecosystems like that of the Keta Lagoon Complex Ramsar Site (KLCRS). This productive ecosystem in Ghana faces serious threats from intensive exploitation, physical modification, changes in water regime, and water pollution. The current study employed geospatial and intensity analysis to assess the pattern of land use/land cover (LULC) change for almost the past three decades and morphometric parameters of the KLCRS landscape. Landsat Satellite images for 1991, 2007, and 2020 were acquired to uncover the pattern of LULC change, while morphometric changes were assessed using global Advance Space Thermal Emission and Radiometer (ASTER) digital elevation model (DEM) data and the spatial analyst tools in GIS software. The result established that the acceleration of land transformation was intensive between 2007 and 2020, which could be linked to population growth and increased socio-economic activities. There was a net gross gain of built-up that originated largely from the conversion of marsh, dense vegetation, and cultivated land. Prior to this period, cultivated land recorded net gain (125.51 km2) between 1991 and 2007, whereas dense vegetation and marshland showed a net loss of 151.37 km2 and 2.44 km2, respectively. The gain of cultivated land largely targeted marshland in both time intervals. The construction of saltpans contributed largely to the small increase in water extent. The morphometric analysis revealed the groundwater potential of the KLCRS. The low-lying nature of the landscape makes the area susceptible to coastal flooding. The trend of the observed changes could invariably affect the ecological integrity of the landscape, hence suggesting the need for immediate preparation and implementation of marine and coastal spatial plans by relevant stakeholders.

Effects of urbanisation in a shallow coastal aquifer: An integrated GIS-based case study in Cochin, India

Urbanisation impacts the availability and quality of renewable natural resources, particularly water resources. In coastal regions, the magnitude of urbanisation and its consequences is more prevalent. However, there are limited quantitative assessments on how urbanisation affects the groundwater system, especially the groundwater potential. Therefore, in the present study, we analysed the variability in groundwater potential zones due to the temporal changes in land use land cover (LULC) for Cochin, Kerala, India. For this, a GIS-based weighted overlay analysis method was performed with six geo-environmental factors to delineate groundwater potential zones (GWPZ). GWPZ at three different decadal time points from 1992 to 2019 was derived using the representative LULC maps. Our analysis showed a significant reduction in the high potential zone, decreasing from 75.34 % to 17.53 %. Contrastingly, the low potential zone rose from 0 to 11.8 % from 1992 to 2019. The temporal change in the spatial pattern in GWPZ named Groundwater Potential Change Index (GWPCI) was derived through pixel-level change detection. We performed a long-term (1985–2017) trend analysis on groundwater levels obtained for a network of twenty-three observation wells from the study area to validate the results. The trend analysis showed that 47 % of the wells display a statistically significant declining water level trend. Subsequently, twelve wells were selected to perform a bivariate statistical analysis between the long-term trend in water level and GWPCI. Ten wells showed a reasonable agreement to the negative change in GWPCI, while two displayed no relation to GWPCI. The study illustrates the effect of LULC change patterns in the groundwater system since significant alterations were observed on GWPZ. The systematic approach adopted in the present study can contribute to sustainable land and water resource management aimed at reducing the urbanisation impact on the groundwater system in the future.

Impact of Rapid and Intensive Land Use/Land Cover Change on Soil Properties in Arid Regions: A Case Study of Lanzhou New Area, China

Land use/land cover (LULC) change widely occurs during urbanization and can affect the functionality of soil ecosystems by altering soil physicochemical properties. However, few studies have evaluated the impacts of LULC change on soils in arid regions. This study investigates LULC change patterns during 2010–2017 in Lanzhou New Area, China based on remotely sensed data (Chinese GaoFen-1 and Advanced Land Observing Satellite). We identified five main land use change types and reference native grassland and farmland to determine soil properties at different depths. Principal component analysis and scatter matrix were employed to evaluate the effect of LULC change on soil properties. The results showed that LULC changes that occurred in Lanzhou New Area were characterized by the rapid growth of construction and bare land (increased by 13.06% and 5.97%, respectively) at the expense of farmland (decreased by 25.38%). The conversion of native grassland to artificial grassland and bare land, and farmland to bare land had similar effects on soil properties; i.e., a significant decline and a lower level in total nitrogen and soil organic carbon. The farmland to construction land transition deteriorated soil nutrients and increased soil compaction by both increasing bulk density (BD, mean = 1.63 g cm−3) and enhancing sand content by 69.21%. All land use change types increased BD and decreased soil water content and saturated soil water content when compared to the reference areas. These results indicate that changes in LULC have significant impacts on soil physicochemical properties. Thus, it is essential to optimize land planning and improve soil quality in arid ecosystems to ensure sustainable resource management and ecosystem conservation.

Monitoring land use land cover changes in the Eastern Himalayan landscape of Nagaland, Northeast India.

The escalating demand for anthropic needs and urban development has highlighted the importance of monitoring and change detection of land use land cover (LULC). With an increase in agricultural expansion and infrastructural development, every land surface on earth calls for a long-term investigation of land modification patterns and their underlying contributory factors. The present investigation monitors the LULC changes and assesses the process controls in Kohima and Dimapur districts of Nagaland, India. Currently, these two districts encompassing the main urban cities of the hilly state are experiencing rapid urbanization and unplanned developmental activities. Alike any other LULC changes observed in unplanned and developing cities, these districts are likely to face environmental degradation, and particularly, the occurrence of frequent landslides and flash floods. The study has three objectives-(i) LULC mapping of Kohima and Dimapur districts for three periods (1998, 2008, and 2018), (ii) comparative analysis of LULC change patterns in the two districts during the three epochs (1998-2008, 2008-2018, and 1998-2018), and (iii) assessment of the contributory factors. For the study, remotely sensed LANDSAT images (TM and OLI) in Geographical Information System (GIS) platform were utilized along with field surveys. Supervised classification technique was employed and four major LULC classes were identified using Landsat level-1 classification system. The overall accuracy of the classification varied between 91 and 98%. Results showed that Built Up areas have increased significantly in both the districts at the rate of 322.6ha/year in Kohima and 301.9ha/year in Dimapur during 1998-2018. On the other hand, Agricultural Land and Forest Land declined in both districts. Changes in LULC were mainly due to marginalization of shifting cultivation, deforestation, infrastructural development, urban migration, and flourishing of aquaculture farming. This study furnishes baseline information on LULC in the data-scarce region of Northeast India and is an insinuation to the policy-makers to ensure sustainable land use planning in the face of rapid urbanization.

Impacts of spatial heterogeneity patterns on long-term trends of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature time series

Land surface temperature (LST) is a crucial parameter for global climate change studies. LST changes are also directly associated with the large-scale changes in land cover. Previous studies carried out a comparative analysis of satellite-derived LST response between periods before and after homogenous land cover changes. We present an alternative approach that quantifies long-term LST variability in response to various land use/land cover change (LULCC) patterns over Phuket Island, Thailand, from 2003 to 2017. First, four Moderate Resolution Imaging Spectroradiometer (MODIS) overpass times of LST time series were adjusted for seasonal effects using a cubic spline function to preserve the number of original data and enable estimates of LST dynamics and trends using the generalized least squared models. Second, LULCC patterns were classified according to land cover type conversion and spatial pattern transformations between the years 2000 and 2016. Spatial homogeneity and heterogeneity were quantified by the coverage percentage for each land use and land cover (LULC) type within a given location. Finally, the influence of LULCC patterns on the long-term spatiotemporal behavior of LST was assessed using the generalized estimating equation model. Results showed that different land cover transitions influence the dynamics of daytime LST but not the nighttime LST. The proportion of different land cover types within an LST pixel and transition amounts contributed to the quantity of increasing surface temperature, especially over impervious surface types. Diverse LULCC patterns with considerations of spatial heterogeneity improved our insight about a relatively strong effect of combined LULC types on LST responses. The climatic effect through the gradual conversion of heterogeneous land cover is necessary to be considered in climate research studies.

Impact of Land Use/Land Cover Change on Hydrological Components in Chongwe River Catchment

Chongwe River Catchment, a sub-catchment of the Zambezi River Basin, has been experiencing changes in land use/land cover (LULC) and in its hydrology. This study aims to assess the impact of LULC changes on the catchment’s hydrological components such as streamflow, evapotranspiration and water abstractions. LULC change data, detected from the 1984, 1994, 2014 and 2017 USGS Landsat imagery using a maximum likelihood supervised classifier, were integrated into the WEAP Model along with soil, slope and hydro–climate data. The results showed that between 1984 and 2017 built-up area increased by 382.77% at 6.97 km2/year, irrigated agriculture increased by 745.62% at 1.70 km2/year, rainfed farms/ranch/grassland increased by 14.67% at 14.53 km2/year, forest land decreased by 41.11% at 22.33 km2/year and waterbodies decreased by 73.95% at 0.87 km2/year. Streamflow increased at a rate of 0.13 Mm3 per annum in the wet seasons and showed a high variation with flow volume of 79.68 Mm3 in February and 1.01 Mm3 in September. Annual actual evapotranspiration decreased from 840.6 mm to 796.3 mm while annual water abstraction increased from 8.94 mm to 23.2 mm from the year 1984 to 2017. The pattern of LULC change between 1984 and 2017 has negatively impacted the hydrology of the Chongwe River Catchment. From these findings, an integrated catchment management and protection approach is proposed to mitigate the negative impacts of LULC dynamics on hydrological components in the Chongwe River Catchment.

PREDICTION OF FUTURE LAND USE LAND COVER CHANGES OF KELANTAN, MALAYSIA

Abstract. Land use land cover change (LULC) is a dynamic process, which is largely influenced by anthropogenic effect. In less urbanized area, human activities such as agricultural expansion, timber extraction and infrastructure development, has caused LULC transformation at alarming rate. Understanding of the potential future LULC changes is necessary for town planners and local authorities to formulate and design town planning. Besides that, the projected LULC patterns could also be incorporated into other models to further evaluate the impact of LULC changes on environment, agricultural, ecosystem, water resources and health. This study projected a future LULC scenario of Kelantan, Malaysia, using an integrated GIS CA-Markov model. The model achieved an accuracy of 78.57% when compared with the LULC map of 2008. Built-up area has increased by 111 km2, while forest area has decreased 1532 km2 in the past 15 years. Results showed that the built-up area, oil palm, and rubber plantation are expected to increase to 181.69 km2, 2142.48 km2, and 3076.24 km2, respectively, in 2025. By contrast, forest and paddy area are projected to decrease to 8548.20 km2, and 693.44 km2 respectively. Urban expansion is mainly found in the northern part of the state, while oil palm expansion in the southern part of the state. It was predicted that this pattern will continue in the next thirty years where built-up and agriculture area continued to expand at the stake of forest area. The findings provide useful information for planners in planning for future development and safeguarding the environment.

Assessment of Climate Trends and Land Cover/Use Dynamics within the Somone River Basin, Senegal

This study was undertaken mainly to 1) investigate temporal trends in annual rainfall and temperature; 2) identify discontinuities in the time series; and 3) assess the Land Use/Land Cover Change (LULC) in the Somone coastal lagoon, within the river basin. The study examined temporal trends in rainfall (1931-2016) and temperature (1961-2016) datasets of Somone river basin, and breaks in time series using Mann-Kendall non-parametric test and other suitable statistical tools. Temporal evolution in LULC was assessed for the years 1954, 1978, 2003 and 2016. Analysis indicates a significant decreasing trend in precipitation over the basin. These trends are much more pronounced for minimum and average rainfall than for maximum and annual amplitudes. Contrary to precipitation, surface air temperature shows a significant increasing trend for its minimum and averages, and a decreasing trend for its maximum and amplitudes. A significant break in precipitation was observed in 1958, while surface air temperature presents much longer breaks within the years 1975 and 1977, and 1991 and 1993. A more direct implication of climate change on LULC patterns is increased in unproductive salt pans (Sabkhas). Increase in Sabkhas gave rise to conversion of forest lands to agricultural lands of local farmers in search for fertile soils to cater for the food needs of a growing population. Otherwise, the development of the settlements, favored by the tourism activity and agriculture crisis, is another cause of croplands decreasing. The findings of the present research clearly indicate that the impacts of climate change are exacerbated by rapid urbanization in the basin.

A big data urban growth simulation at a national scale

The Land Transformation Model (LTM) is a Land Use Land Cover Change (LUCC) model which was originally developed to simulate local scale LUCC patterns. The model uses a commercial windows-based GIS ...

A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment

The Land Transformation Model (LTM) is a Land Use Land Cover Change (LUCC) model which was originally developed to simulate local scale LUCC patterns. The model uses a commercial windows-based GIS program to process and manage spatial data and an artificial neural network (ANN) program within a series of batch routines to learn about spatial patterns in data. In this paper, we provide an overview of a redesigned LTM capable of running at continental scales and at a fine (30m) resolution using a new architecture that employs a windows-based High Performance Computing (HPC) cluster. This paper provides an overview of the new architecture which we discuss within the context of modeling LUCC that requires: (1) using an HPC to run a modified version of our LTM; (2) managing large datasets in terms of size and quantity of files; (3) integration of tools that are executed using different scripting languages; and (4) a large number of steps necessitating several aspects of job management.