Bare Land Research Articles

Changes in salinity and vegetation growth under different land use types during the reclamation in coastal saline soil

The ecological construction in coastal saline-alkali areas urgently needs to be explored in terms of water-salt regulation management and functional irrigation. In this paper, the extremely severe saline soil in the eastern coastal area of the North China Plain was selected for vegetation rehabilitation by drip irrigation. Through two-year field experiments, the spatial and temporal soil salinity-water dynamics of three land use types (LUTS) under two irrigation strategies (IIS) were systematically studied. The results revealed: (1) The soils in the understory grassland and shrub land root zones remained stable for desalination, with the average ECe decreasing to 0.69 dS/m and 0.71 dS/m under autumn irrigation at surface, and 0.66 dS/m and 0.85 dS/m under winter irrigation. And a slight salt accumulation occurred in the bare land in stage IV. (2)The soil surface moisture increased, and the bulk density decreased significantly with drip irrigation. The final moisture of understory grassland and shrub land was 3.85 and 2.97 times that of the bare land layer at 0–10 cm, 2.55 and 1.97 times at 10–20 cm, and 1.61 times and 1.47 times at 20–40 cm, respectively. (3)Due to quick salt rinsing, Salix matsudana and Hibiscus maintained a high survival rate, and the germination of understory vegetation further increased the vegetation coverage. Meanwhile perennial understory herbs gradually became the dominant species, which positively effects on the maintenance of soil low-salt environment. (4)There were significant differences in SWC and ECe between autumn and winter irrigation treatment during stage I and stage II, indicating that irrigation strategies only impact on soil water-salt movement in the early stage. While there was no significant difference between understory grassland and shrub land, indicating that the research about the effects of vegetation cover type on water-salt transport should take a longer time scale.

Soil Water Flow Affected by Vegetation Root Water Uptake in the Semiarid Region of Mu Us Sandy Land, China

ABSTRACTVegetation plays an important role in the management of water resources and of the terrestrial vegetation degradation in semiarid regions of China. Detailed descriptions of the actual hydrological process of vegetation root water uptake (RWU) are lacking, and the dynamics of interfaces involved in the process of RWU have not received enough attention. A field in situ experiment with bare land and vegetated land was implemented to investigate soil water flow in vadose zones affected by vegetation RWU. The results revealed that, with the influence of RWU, the soil moisture content was redistributed and impacted evaporation and infiltration; therefore, even the roots were driven to utilize groundwater under intense potential evapotranspiration and water stress. Notably, the thicker vadose zones were beneficial for preserving water resources for bare land, but Salix reduced soil water storage by 1191.13 L compared with bare land, which was adverse for water resource development in semiarid regions. The results provide the basis for the protection of the vegetation environment and water resource management in arid regions.

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.

Assessing Land-Cover Change Trends, Patterns, and Transitions in Coalfield Counties of Eastern Kentucky, USA

Surface coal mining and reclamation have greatly reshaped eastern Kentucky’s landscape affecting its socioeconomic, environmental and climatic aspects. This study examined the land-cover changes, trends and patterns in Floyd, Knott, Letcher, Magoffin, Martin, Perry, and Pike counties from 2004 to 2019. Using a random forest classifier, land cover was categorized into seven major classes, i.e., water, barren land, developed land, forest, shrubland, herbaceous, and planted/cultivated, majorly based on Landsat images. The Kappa accuracy ranged from 75 to 89%. The results showed a notable increase in forest area from 5052 sq km to 5305 sq km accompanied by a substantial decrease in barren land from 179 sq km to 91 sq km from 2004 to 2019. These findings demonstrated that reclamation activities positively impacted the forest expansion and reduced the barren land of the study area. Key land-cover transitions included barren land to shrubland/herbaceous, forest to shrubland, and shrubland to forest, indicating vegetation growth from 2004 to 2019. An autocorrelation analysis indicated similar land-cover types clustered together, showing effective forest restoration efforts. As surface coal mining and reclamation significantly influenced the landscapes of the coalfield counties in eastern Kentucky, this study provides a holistic perspective for understanding the repercussions of these transformations, including their effects on humans, society, and environmental health.

GIS-Based Land Use and Land Cover Change Assessment Around Assosa District, Upper Blue Nile Basin, Ethiopia

Land, with its intricate blend of geological, topographical, hydrological, and ecological elements, reflects the interplay of natural processes and human activities. In Ethiopia, traditional agricultural practices often lack systematic planning based on land suitability and physical characteristics, hindering agricultural productivity and economic progress. Understanding shifts in land use and cover is crucial for comprehending broader global transformations. Early studies have unveiled significant alterations in land use and cover between 2009 and 2013. Our investigation extends from 2013 to 2023, employing Landsat 8 imagery at three-year intervals (2013, 2018, and 2023) to analyze five key land cover categories: forests, farmland, built-up areas, barren land, and water bodies. Notably, farmland and built-up areas witnessed substantial expansion over these periods, juxtaposed with a significant decline in forest cover. Forests decreased by 27% from 2013 to 2018, with an additional 7% decrease from 2018 to 2023. Conversely, farmland expanded by 19% from 2013 to 2018 and by 2% from 2018 to 2023, while built-up areas saw respective increases of 4% and 10% over the same periods. These trends underscore potential environmental challenges if unaddressed. Effective land management strategies are crucial to mitigate adverse impacts on ecosystems, agricultural productivity, and overall socio-economic stability. By integrating scientific insights with sustainable practices, we can navigate the intricate dynamics of land use, paving the way for a resilient and prosperous future.

The Protection and Management of Wapiti in Desert Oases: Bare Land Poses a Limitation to Wapiti Conservation.

The Helan Mountains, situated in the heart of the desert, act as a dividing line between China's arid and semi-arid zones. Often referred to as a "desert oasis", they create an ecological island with a uniquely distinctive geographical location, making this area a focal point of contemporary research. Ungulates play a critical role in this ecosystem. The Alashan wapiti (Cervus canadensis alashanicus), an isolated population of China's smallest wapiti (Cervus canadensis) subspecies, is found exclusively within the Helan Mountains Nature Reserve. The conservation of this isolated population is fraught with challenges, particularly during winter, the harshest season for northern ungulates. Winter habitats are crucial for ensuring population stability. Therefore, we used certain methods, such as factor screening and model parameter optimization to assess habitat suitability using multi-scale species distribution models. The optimized results show that suitable habitats overlap with areas of high vegetation coverage in the Helan Mountains, covering just 588.32 km2, which is less than a quarter of the reserve's total area. The bare land area and winter NDVI are the two primary factors influencing habitat suitability, with other factors having minimal impact, underscoring the critical importance of food resources for the Alashan wapiti. The limited availability of these resources poses significant conservation challenges. Our findings provide a more precise foundation for targeted habitat protection and restoration efforts. We recommend enhancing the protection and restoration of food resources, effectively conserving vegetated areas, and preventing desertification.

Land Use Change and its Impact on Terrestrial Biodiversity of Surrounding Areas of Jim Corbett National Park

Located at the Shivalik Himalayas' foothills, near the worldwide popular hill-station of Nainital, the beautiful park is famous for being home to a huge number of Bengal tigers, the highest among any Indian national park. So many other mammals, including tigers, leopards and elephants (wild), roam in this park. On the edge of the Western Ramganga Reservoir, the Sonanadi zone is habitat to elephants and leopards, along with more than hundreds of species of fowl. Also CNP is a prime protected area of Uttarakhand forest as it provides ecological viable, profitable and sources of different income for local people. Dense forest cover is one among the most natural resources for every animal (Including human) directly and indirectly. But rapid excessive exploitations of the different vegetation, woods, shrubs species for human development here are now under the threat of biodiversity loss and uncovering forests. Present study focused on significance of terrestrial biodiversity, reason of land use changes and threats to terrestrial biodiversity (TB) because of land use change, terrestrial biodiversity of the local area is influencing by various ways. For continuous use of the forest ecosystems, it is very important to find the land use land covers changes and its negative impacts on biodiversity and surrounding environment. Forest resources are the full of vital material, base of direct and indirect human’s continuous progress and it needs to monitor the status and change of forest resources timely for logical exploitation of forests and its renewal. Present study focused on monitoring the changes in the forest areas, surrounding barren land, build-up area and natural resources.

Spatial and Temporal Characteristics of Land Use Changes in the Yellow River Basin from 1990 to 2021 and Future Predictions

Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. Based on the China Land Cover Dataset (CLCD) of the Yellow River Basin from 1990 to 2021, this study employs various methods such as the Mann–Kendall test and sliding t-test, land use dynamics, the land use transfer matrix, the standard deviation ellipse, the center of gravity migration model, and a geographic detector to explore the spatial and temporal characteristics of land use changes and driving forces in the Yellow River Basin over the past 30 years. Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. The results show the following: (1) From 1990 to 2021, the area of forest, grassland, water, and impervious surfaces increased significantly, while the area of cropland, shrub, barren land, and wetlands decreased significantly. The most actively changing land use types are cropland, grassland, barren land, and impervious surfaces. (2) The center of gravity for shrub and impervious surfaces shifted westward, while wetlands showed a trend of obvious concentrated distribution, and the remaining land use types exhibited stable directional distributions. (3) Economic factors had a stronger driving effect on land use changes than topographic and climatic factors. The land use changes in the Yellow River Basin are influenced by the coordinated driving forces of multiple factors. (4) In 2030, the main land use types in the Yellow River Basin are still expected to be cropland, grassland, and forest. However, there will be a significant expansion of impervious surfaces and forest land, with substantial encroachment on cropland and grassland.

Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development

The pivotal aspects of enhancing regional ecosystem services and augmenting socioeconomic growth lie in optimizing the land-space development and protection strategies, coupled with the establishment of a robust ecological network (EN). This article examines the Poyang Lake area and employs the MOP model, NSGA-II, and PLUS model to determine the best sustainable land use strategy. Subsequently, the MSPA, InVEST model, circuit theory, complex network, and others are employed to construct and analyze the land-space EN across three time periods. Ultimately, the EN is optimized based on spatial protection priority, ecological obstacle areas, and ecological nodes. The results show the following: (1) From 2005 to 2035, more construction land will be developed around the Greater Nanchang area and other urban centers. In the BAU scenario, construction land will expand faster, while cultivated land, forest, grassland, and bare land will continue to decline. In the SD scenario, the alteration to comparable land is minimal, the growth rate of construction land will slow, cultivated land, forest, grassland, and bare land will all decline little, and the water area will increase slightly; (2) While the area of ecological sources is decreased and ecological corridors become longer and narrower in the BAU scenario, the spatial distribution of ENs in different periods is small, and the quantitative structure and spatial distribution of ecological sources and corridors are essentially unchanged in the SD scenario; (3) Based on the topological structure of ENs, it is found that the clustering of nodes in the SD scenario is more obvious, the importance of ecological sources is enhanced, the efficiency of information transmission is improved, and the radiation range is wider and more stable; (4) The greatest priority ecological sources in each period are concentrated around Poyang Lake. In the SD scenario, the priority of ecological sources improves, and 7025 km2 of ecological obstacle restoration area is identified, with 41, 31, and 36 ecological breakpoints in the first, second, and third levels. The study’s findings can assist and shape theoretical and practical approaches to land governance and sustainable development in great lake areas.

A Cost–Benefit Analysis for the Economic Evaluation of Ecosystem Services Lost Due to Erosion in a Mediterranean River Basin

Soil degradation in Europe is mostly represented by soil erosion that, as a sediment production mechanism, is the main environmental threat to many watersheds, including the Bovilla watershed (Tirana), useful for the supply of drinking water to the city, and therefore, the care of water quality is of particular interest. The soil erosion of the Bovilla watershed was monitored in a work set up in June 2017. Following this work, this research updates the previous data on soil loss at the Bovilla watershed in t/ha/year to September 2019 and focuses on the identification and monetary evaluation of the ecosystem services (ESs) linked to soil erosion (loss of carbon, loss of mineral elements, habitat quality, crop productivity, and sustainable tourism suitability). Then, we applied the replacement cost analysis to test the economic convenience and suggest the adoption of sustainable land management practices (e.g., reforestation) able to improve the quality water in this watershed. The study carried out demonstrates that the values of soil lost due to erosion vary depending on the type of land use (ranging from average values of 120.32 t/ha for bare land to values of 8.16 t/ha for wooded areas). Furthermore, from the application of monetary methods for the evaluation of some ecosystem services linked to erosion (loss of carbonaceous and mineral elements, habitat quality, productivity, suitability for sustainable tourism), it clearly emerges that the value of the productivity of agricultural crops varies from EUR 0 to 35,320.50/ha and that the service represents a more incisive service than the previous ones, so much so as to make the conversion of some agricultural land with high productivity values into wooded areas economically disadvantageous. The data from this study may help to develop Bovilla watershed management strategies for erosion and pollution control and sediment remediation mainly in agricultural lands. A program of measures can be effective for controlling soil erosion, but it must be implemented over long time frames, and it requires relevant investments from the public and private sectors, also with a view to increase the allocation of economic values of monetary compensation aimed at those who decide to start forestation projects on highly productive soils.

Effect of Pit and Soil Types on Growth and Development, Nutrient Content and Fruit Quality of Pomegranate in the Central Deccan Plateau Region, India

To enhance pomegranate production on marginal gravelly lands, standardized planting techniques were evaluated in an 8-year-old orchard. Trenching, wider pit excavation, pit digging, and auger digs with dimensions of 1 and 2 m were employed. Utilizing native soil from barren land, with or without spent wash, and mixing it with black soil up to 1 m deep, growth parameters, leaf nutrients, fruit production, and fruit quality were assessed. The trench and wider pit methods outperformed others, yielding greater above-ground biomass (>70.3 kg tree−1), root biomass (>24.5 kg, tree−1), and cross-sectional area (>3.30 m2 tree−1). These methods also produced longer roots (>4.0 m tree−1) and higher leaf phosphorus (>0.28%) and potassium (>1.81%) levels, fruit juice content (>48.50%), and total soluble solids (>16.05°) compared to other planting methods. This resulted in higher and more sustainable fruit yield production under the trench and wider pit planting methods (>7.21 t ha−1). Similarly, the native and black soil mixture produced healthy fruit trees, improved fruit quality, and sustainably higher fruit yield over the native soil alone. In summary, the trench and wider pit methods (2–3 m3), combined with a soil mixture, are recommended for sustainable, high-quality fruit production in shallow gravelly terrains, thereby improving food security and the livelihoods of farmers in arid regions.

Investigating the Relationship between Urbanization and Air Pollution Using Google Earth Engine Platform: A Case Study of Istanbul

Rapid population growth in megacities such as Istanbul has led to various effects, such as industrialization, urbanization, loss of green areas, increasing vehicle traffic, and higher consumption of fossil fuels. These reasons, along with many other environmental factors, contribute to the rise of air pollution in urban life. This study aimed to examine the relationship between urbanization and air pollution in Istanbul. For this purpose, land cover maps covering Istanbul province were produced using Landsat-5 (TM), Landsat-8 (OLI), and Sentinel-2 (MSI) images for the years 1996 to 2021 at three-year intervals on the Google Earth Engine platform. Land cover for classification purposes was divided into five different classes: forest, water surface, urban area, and bare land, and classified using a random forest machine learning algorithm. To examine the impact of this urban area growth on air pollution, in the second step of the study, the column number density values of Sentinel 5P (TROPOMI) data for SO2, NO2, CO, and O3 gases for 2019, 2020, and 2021 were analyzed. The averages of the data from 39 air pollution monitoring stations across Istanbul were also examined. According to this classification, the urban area expanded from 491 km2 in 1996 to 1222 km2 by 2021. Considering the total surface area of Istanbul province, the urban area, which was 9% in 1996, reached 23% by 2021. The TROPOMI values were calculated as follows: the average column number density values for SO2, NO2, CO, and O3 were 0.0003538 mol/m², 0.0339514 mol/m², 0.0000984 mol/m², and 0.1453515 mol/m², respectively. Similarly, the gas concentrations of SO2, NO2, CO, and O3 measured from the ground stations were calculated as 6.603 µ/m3, 786,815 µ/m3, 43.763 µ/m3 and 45.773 µ/m3, respectively. Correlations between urbanization and TROPOMI values revealed a positive correlation of 0.39, 0.02, and 0.80 for SO2, NO2, and CO gases, while a negative correlation of 0.25 was found for O3 gas. The study also examined correlations between TROPOMI and ground station measurements, resulting in positive correlations of 0.55, 0.66, and 0.16 for SO2, NO2, and CO gases, respectively, while a negative correlation of 0.05 was found for O3 gas. Based on these findings, among the air pollutants studied both through TROPOMI and ground station data, the highest correlation was observed for CO gas.

Effects of Phosphorus Application Levels on Its Uptake and Utilization in Foxtail Millet

Foxtail millet is a traditional minor crop in China, known for its strong resistance to stress, tolerance to barren lands, and wide adaptation. Phosphorus is an essential element for crop growth and development, and the appropriate application of phosphorus can enhance crop yield and quality. However, the optimal phosphorus fertilization levels for the growth of foxtail millet have yet to be determined. This study aims to explore the effects of different phosphorus application levels (T1, T2, T3, and T4), on phosphorus accumulation and use efficiency and crop yield and quality in the foxtail millet cultivars ‘B376’ and ‘B27’, which have different phosphorus efficiencies. Additionally, we investigated the effects of phosphorus accumulation and use efficiency on the heading and filling stages of these cultivars. The results show that the total phosphorus content and accumulation levels in the ‘B376’ and ‘B27’ cultivars vary at different developmental stages and in different plant parts. Furthermore, crop yield and quality in both cultivars vary in response to the different phosphorus application levels. In terms of yield, the phosphorus-tolerant variety ‘B376’ reaches its highest at T2, while the phosphorus-sensitive variety ‘B27’ achieves its maximum yield at T3. For quality, ‘B376’ exhibits the highest moisture and crude fat content under T4, and the highest protein and the lowest amylose content under T3. On the other hand, ‘B27’ achieves its highest moisture content under T4, its highest crude fat and protein levels under T3, and its lowest amylose content under T2. Therefore, the response to different phosphorus application levels differs between the two cultivars with different phosphorus use efficiencies. Moreover, under different phosphorus fertilization levels, the average crop yield, moisture, fat, and amylose content averages of the phosphorus-tolerant ‘B376’ cultivar are 16.1%, 1.2%, 7.0%, and 4.1% higher than those of the phosphorus-sensitive ‘B27’ cultivar. Additionally, phosphorus use efficiency is positively correlated with the moisture and crude fat contents of foxtail millet. In conclusion, the phosphorus-tolerant cultivar demonstrates superior phosphorus accumulation, absorption, and utilization capacities compared to the phosphorus-sensitive cultivar. These results suggest that in the phosphorus-tolerant ‘B376’, optimal phosphorus fertilization levels enhance the development of roots, stems, and leaves at the T2 (P45) level, and promote the accumulation of moisture and crude fat in foxtail millet grains, thereby improving their taste and quality. Our findings provide a theoretical basis for phosphorus fertilizer utilization in foxtail millet cultivation and will help determine the optimal fertilization levels for foxtail millet growth.

Assessing the impacts of vegetation loss and land surface temperature on Surface Urban Heat Island (SUHI) in Gazipur District, Bangladesh

Rapid replacement of vegetated land with impermeable land (built-up areas) is a major factor in the increase in Land Surface Temperature (LST), while increased LST worsens the temperature in cities and creates the Surface Urban Heat Island (SUHI) effect. The study aims to measure vegetation loss and Land Surface Temperature of the Gazipur district between 2000 and 2020 and explore the relationship among Normalized Difference Vegetation Index (NDVI), LST, and Urban Thermal Field Variance Index (UTFVI). The Landsat TM/OLI images with minimum cloud coverage have been used to derive different indices. The mean NDVI values are 0.21, 0.16, and 0.22 in 2000, 2010, and 2020 respectively which indicates a general improvement in the health of the vegetation. Besides, the highest LST values throughout 20 years, represent a general increasing trend. As a consequence, different land covers have experienced fluctuations in mean temperature. The result shows that the mean temperature of bare land, buildup, vegetation, and waterbody has increased by 4.77, 2.01, 2.25, and 2.23 °C respectively from 2000 to 2020. The strongest SUHI zone’s area grew by about 28% between 2000 and 2020. Additionally, the highest index value of UTFVI was 0.39 in 2000 and grew to 0.43 in 2010. It changed to 0.49 in 2020, or ten years later. Thus, the SUHI effect’s increasing intensity is visible. Also, regression analysis has been used to explore the correlation between the derived indices. Stakeholders from different sectors like urban planners and policymakers may take insights from this study to work to promote greenery for a healthy urban environment.

Significant Differences in Microbial Soil Properties, Stoichiometry and Tree Growth Occurred within 15 Years after Afforestation on Different Parent Material.

The mineralogical composition of the parent material, together with plant species and soil microorganisms, constitutes the foundational components of an ecosystem's energy cycle. Afforestation in arid-semi arid regions plays a crucial role in preventing erosion and enhancing soil quality, offering significant economic and ecological benefits. This study evaluated the effects of afforestation and different parent materials on the physicochemical and microbiological properties of soils, including microbial basal respiration (MR), as well as how these changes in soil properties after 15 years influence plant growth. For this purpose, various soil physicochemical parameters, MR, soil microbial biomass carbon (Cmic), stoichiometry (microbial quotient = Cmic/Corg = qMic and metabolic quotient = MR/Cmic = qCO2), and tree growth metrics such as height and diameter were measured. The results indicated that when the physicochemical and microbiological properties of soils from different bedrock types, along with the average values of tree growth parameters, were analyzed, afforestation areas with limestone bedrock performed better than those with andesite bedrock. Notably, sensitive microbial properties, such as Cmic, MR, and qMic, were positively influenced by afforestation. The highest values of Cmic (323 μg C g-1) and MR (1.3 CO2-C g-1 h-1) were recorded in soils derived from limestone. In contrast, the highest qCO2 was observed in the control plots of soils with andesite parent material (7.14). Considering all the measured soil properties, the samples can be ranked in the following order: limestone sample (LS) > andesite sample (AS) > limestone control (LC) > andesite control (AC). Similarly, considering measured plant growth parameters were ranked as LS > AS. As a result, the higher plant growth capacity and carbon retention of limestone soil indicate that it has high microbial biomass and microbial activity. This study emphasizes the importance of selecting suitable parent material and understanding soil properties to optimize future afforestation efforts on bare lands.

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.

Geo-environmental monitoring of coastal and land resources for Coatzacoalcos coastal region

Coatzacoalcos is one of the notable Mexico coastal areas regarding location, activities, and resources. The purpose of the current study is to use geographic techniques to assess the spatial and temporal changes in Land Use/Cover (LULC), Land Surface Temperature (LST), and Shoreline as a result of anthropogenic and natural factors. Four calibrated multi-temporal Landsat images, dated 1993, 2003, 2013, and 2023, were combined and processed to accomplish this goal. The six primary LULC classes forest, built-up land, mining, water bodies, and agriculture were mapped using RF Machine learning algorithms. The last period (2003–2023) shows the highest rate of built-up land expansion, while the years 1993–2013 show the lowest rate of agricultural land reduction. Forest cover in the southeast decreased steadily from 339.25, 308.49, 287.43, and 211.83 km2 in 1993, 2003, 2013, and 2023. There is a slight difference in mean LST between built-up areas that recorded 26, 29, 32, and 33 °C in 1993, 2003, 2013, and 2023, respectively. The following is an order of LULC from lowest to highest LST during 2023 water body 12 °C, Forest 19 °C, Agriculture Land 22 °C, Mining 26 °C, Barren Land 34 °C and Built-up Land 33 °C. In Zone B near Coatzacoalcos showed particularly high accretion as a result of building artificial structures. Maximum rates of accretion and erosion were recorded at 2.0 m/year and −9.63 m/year, respectively. Fortunately, Zone C has minimal urban development and is home to forests and agricultural areas, so the potential negative effects are reduced. This study aids in understanding spatial and temporal LULC changes, LST variations, and shoreline dynamics, crucial for the sustainable management of Coatzacoalcos coastal resources in Mexico.

Temporal Dynamics of Global Barren Areas between 2001 and 2022 Derived from MODIS Land Cover Products

Long-term monitoring studies on the transition of different land cover units to barren areas are crucial to gain a better understanding of the potential challenges and threats that land surface ecosystems face. This study utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover products (MCD12C1) to conduct geospatial analysis based on the maximum extent (MaxE) concept, to assess the spatiotemporal changes in barren areas from 2001 to 2022, at global and continental scales. The MaxE area includes all the pixels across the entire period of observations where the barren land cover class was at least once present. The relative expansion or reduction of the barren areas can be directly assessed with MaxE, as any annual change observed in the barren distribution is comparable over the entire dataset. The global barren areas without any land change (UA) during this period were equivalent to 12.8% (18,875,284 km2) of the global land surface area. Interannual land cover changes to barren areas occurred in an additional area of 3,438,959 km2 (2.3% of the global area). Globally, barren areas show a gradual reduction from 2001 (91.1% of MaxE) to 2012 (86.8%), followed by annual fluctuations until 2022 (88.1%). These areas were mainly interchanging between open shrublands and grasslands. A relatively high transition between barren areas and permanent snow and ice is found in Europe and North America. The results show a 3.7% decrease in global barren areas from 2001 to 2022. Areas that are predominantly not barren account for 30.6% of the transitional areas (TAs), meaning that these areas experienced short-term or very recent transitions from other land cover classes to barren. Emerging barren areas hotspots were mainly found in the Mangystau region (Kazakhstan), Tibetan plateau, northern Greenland, and the Atlas Mountains (Morocco, Tunisia).

Assessing Tropical Cyclone Destruction Using Landsat Satellite Imagery: A Case Study in Bangladesh

Tropical cyclones are extreme natural catastrophes and are anticipated to intensify strength and recurrence under upcoming climate change consequences in our coastal regions through Bangladesh. This study has tested and developed methods for evaluating considerable damages affected in 2020 by cyclone Amphan in Satkhira district (3817.29 km2) in Bangladesh from 30m spatial-resolution satellite imageries. Iso-cluster unsupervised classification procedures are applied to prepare maps in pre- and post-cyclone Landsat 8 imagery. A difference between the pre- and post-cyclone image classification and NDVI analysis give us evidence about the significant landscape changes at the Cyclone Amphan impact on the study area. The total accuracies for pre- and post-cyclone images classification were 70% and 68% respectively. The outcomes indicate that 35.09% of the study region was remarkably influenced by cyclone Amphan. Statistical analysis indicates that water bodies have dramatically increased 17.65% in different land cover areas due to the strong water surge. On the contrary, the classified image showed that the vegetation and agricultural land decreased 4.13% and 10.82%. Thus, land covers have inundated due to heavy flash during the cyclone. Barren land also decreased 1.80%, and low land areas were also flooded 0.36% due to heavy water flashes. NDVI analysis indicated no destruction of any vegetation species, but vegetation damage is considerable. The developed method may be imposed in future to measure the impacts produced by cyclones in Bangladesh and to make policies for the commitments of cyclone disaster controlling and management.

Optimizing Jatropha curcas bioenergy plantations in Pakistan: A geospatial suitability analysis using advanced spatial modeling

Bioenergy from energy plants, an alternative fuel, is projected to increasingly meet future worldwide energy demands as well as those of a developing nation like Pakistan. Jatropha curcas (JC) has been found to possess many desirable qualities, including high oil content seeds (27–40 %), rapid growth, ease of growing, tolerance to drought, ability to grow on poor soil and wasteland, needing less nutrient input and management, and not interfering with current food crops, insects, or pest resistance. Hence, growing JC in highly appropriate barren lands could reduce the global reliance on fossil fuels. However, an evaluation of the suitability of the land would be required for tree establishment to be effective. In this study, we integrated an Analytical Hierarchy Process (AHP) with the ArcGIS tool for assessing suitable available sites to cultivate JC across Pakistan. Using geospatial technologies, this study intended to assess and map possible areas appropriate for JC bioenergy plantations with the necessary climate, soil type, and topography factors. Pakistan was classified into 3 levels of suitability for JC plantations based on the results of a spatial analysis that integrated various data sets and varied evaluation criteria: Most Suitable, Moderately Suitable, and Less Suitable. Our results showed that out of the total area of Pakistan, around 54,392,075 hectares (57 %), 22,516,700 hectares (23 %), and 19,594,100 hectares (20 %) were identified as highly suitable, moderately suitable, and less suitable, respectively, for JC bioenergy plantations. We conclude that the methods used in this study provided a considerably reliable estimate of suitable sites for JC production in Pakistan. It can assist smallholder-based initiatives to promote JC cultivation on farmer-owned to enhance their living circumstances. Multi-criteria decision analysis (MCDA) was found to be a beneficial tool in breaking down the issues of identifying and classification of the locations for afforestation in the management of forests.