Landscape transformations in rapidly urbanizing Guangdong, Hong Kong, and Macao (GHKM) regions of South China represent the most complex and dynamic processes altering the local ecology and ...environment. In this study, Land Change Modeler (LCM) is applied to land use land cover (LULC) maps for the years 2005, 2010, and 2017, derived from Landsat images, with the aim of understanding land use land cover change patterns during 2005–2017 and, further, to predict the future scenario of the years 2024 and 2031. Furthermore, the changes in spatial structural patterns are quantified and analyzed using selected landscape morphological metrics. The results show that the urban area has increased at an annual rate of 4.72% during 2005–2017 and will continue to rise from 10.31% (20,228.95 km2) in 2017 to 16.30% (31,994.55 km2) in 2031. This increase in urban area will encroach further into farmland and fishponds. However, forest cover will continue to increase from 45.02% (88,391.98 km2) in 2017 to 46.88% (92,049.62 km2) in 2031. This implies a decrease in the mean Euclidian nearest neighbor distance (ENN_MN) of forest patches (from 217.57 m to 206.46 m) and urban clusters (from 285.55 m to 245.06 m) during 2017–2031, indicating an accelerated landscape transformation if the current patterns of the change continues over the next decade. Thus, knowledge of the current and predicted LULC changes will help policy and decision makers to reconsider and develop new policies for the sustainable development and protection of natural resources.
A growing population has led to extensive farming at the expense of a natural environment. Changes in land use and cover have caused land degradation, and problematic groundwater recharge. The ...objective of this study was to evaluate the historical trend, simulations, and predictions of land use land cover change in the Upper Wabe-Shebele River Basin. The study accounted for 1992, 2007 and 2022 as well as it will predict the change for 2037 and 2052. Landsat TM for 1992, ETM + for 2007, and Landsat-8 OLI for 2022 were used. In QGIS 3.16, the maximum likelihood method was utilized for supervised image classification. Using CA-Markov and the Land Change Modeler land use and land cover change for 2037 and 2052 were predicted. Validity and accuracy of the model was evaluated using actual and predicted land use and land cover changes of 2022. Topography, proximity to a town, stream, roads, and population density were used as input for the model. The results showed that between 1992 and 2007, cultivated land increased by 17.07% on average at a rate of 1.05%, while settlement increased by 17.51% at a rate of 1.08% per year. Agricultural and settlement land increased by 22.97% and 30.12%, respectively. Between 1992 and 2022, the transition area matrix showed 2,330.25 and 1,145.77 km2 of forest and grazing land were changed to settlement and cultivated land, respectively. Meanwhile, from 2022 to 2037, the quantity of land used for cultivated, grazing, and settlement is predicted to increase by 0.19, 3.66, and 23.8% in order. For 2037 and 2052, settlement and cultivated land were increased by 1.3 and 7.32% respectively. Finally, since natural ecosystem had been significantly disturbed by change in the study area, comprehensive rehabilitation and management is demanded.
•Process intensification of green DME synthesis via membrane reactor.•Green DME synthesis over hybrid catalysts of Cu/ZnO/Al2O3/HZSM-5 with varying compositions.•The evaluation of membrane reactor's ...performance based on parametric and structural process parameters.•Technical and environmental assessment of direct dimethyl ether synthesis at the flowsheet level.
Carbon utilization plays a pivotal role in the circular carbon economy approach. However, CO2 conversion technologies, including thermocatalytic hydrogenation approaches, entail several challenges such as thermodynamic limits and low kinetic rates. In the pursuit of eliminating these two hurdles, this study aims to highlight the unique synergy and high potential of the combination of two emerging technologies: catalytic zeolite membrane reactor and direct dimethyl ether synthesis over hybrid catalysts of Cu/ZnO/Al2O3/HZSM-5. To this end, an equation-based pseudo homogenous model for a plug flow membrane reactor, previously developed in Aspen Custom Modeler, will be verified using experimental data in the literature and then coupled with the appropriately selected kinetic models, which describe this particular reaction system accurately. This enables us to confidently identify the impact of several membrane reactor's characteristics and process parameters on the conversion and selectivity. We also analyze a membrane-reactor-based dimethyl ether synthesis process and compare it with the conventional counterpart. According to our results, at 7.5 MPa pressure, a membrane-based process design offers 1.5%, 44.5% and 69.4% savings in power, heating and refrigerant utilities, respectively. These reductions correspond to 7.3% improvement in CO2 utilization efficiency as a metric to compare the environmental performance of emerging green fuel/chemicals.
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Abstract
As one of the largest super-saline lakes in the world, Lake Urmia in northwestern Iran has been facing severe drying in recent years. Drought and rapid expansion of agricultural activities ...are considered to be the main driving factors in the shrinking of the lake. To address this problem, an analysis of the spatiotemporal dynamics of land use/land cover (LULC) is important. This research implemented a multi-source satellite image analysis through support vector machine (SVM) for mapping LULC distributions for the years 2000, 2010, and 2020. Cellular automata (CA)–Markov was prepared for modeling the future landscape changes for 2030 and 2040. In the last step, the water requirement of agriculture in the catchment area of the Urmia Lake was simulated through the NETWAT model. Through the employed future LULC modeling, it was found that the areas covered by irrigated agriculture and gardens will grow from 1,450 and 395 km2 to 3,600 and 1,650 km2 in 2040, respectively, as deduced from the changes that occurred from 2000 to 2020. This will increase the water requirement of agriculture from 1.5 billion cubic metres in 2000 to more than 4.1 billion cubic metres in 2040.
Introduction This study delves into the spatiotemporal dynamics of land use and land cover (LULC) in a Metropolitan area over three decades (1991–2021) and extends its scope to forecast future ...scenarios from 2031 to 2051. The intent is to aid sustainable land management and urban planning by enabling precise predictions of urban growth, leveraging the integration of remote sensing, GIS data, and observations from Landsat satellites 5, 7, and 8. Methods The research employed a machine learning-based approach, specifically utilizing the random forest (RF) algorithm, for LULC classification. Advanced modeling techniques, including CA–Markov chains and the Land Change Modeler (LCM), were harnessed to project future LULC alterations, which facilitated the development of transition probability matrices among different LULC classes. Results The investigation uncovered significant shifts in LULC, influenced largely by socio-economic factors. Notably, vegetation cover decreased substantially from 49.21% to 25.81%, while forest cover saw an increase from 31.89% to 40.05%. Urban areas expanded significantly, from 7.55% to 25.59% of the total area, translating into an increase from 76.31 km 2 in 1991 to 258.61 km 2 in 2021. Forest area also expanded from 322.25 km 2 to 409.21 km 2 . Projections indicate a further decline in vegetation cover and an increase in built-up areas to 371.44 km 2 by 2051, with a decrease in forest cover compared to its 2021 levels. The predictive accuracy of the model was confirmed with an overall accuracy exceeding 90% and a kappa coefficient around 0.88. Discussion The findings underscore the model’s reliability and provide a significant theoretical framework that integrates socio-economic development with environmental conservation. The results emphasize the need for a balanced approach towards urban growth in the Islamabad metropolitan area, underlining the essential equilibrium between development and conservation for future urban planning and management. This study underscores the importance of using advanced predictive models in guiding sustainable urban development strategies.
The monitoring and modeling of changes, based on a time-series LULC approach, is fundamental for planning and managing regional environments. The current study analyzed the LULC changes as well as ...estimated future scenarios for 2027 and 2037. To achieve accuracy in predicting LULC changes, the Land Change Modeler (LCM) was used for the Latian Dam Watershed, which is located approximately in the northeast of Tehran. The LULC time-series technique was specified utilizing four atmospherically endorsed surface reflectance Landsat images for the years t
1
(1987), t
2
(1998), t
3
(2007), and t
4
(2017) to authenticate the LULC predictions, so to obtain estimates for t
5
(2027) and t
6
(2037). The LULC classes identified in the watershed were water bodies, build-up areas, vegetated areas, and bare lands. The dynamic modeling of the LULC was based on a multi-layer perceptron (MLP), the neural network in LCM, which presented good results with an average accuracy rate equivalent to 84.89 percent. The results of the LULC change analysis showed an increase in the build-up area and a decrease in bare lands and vegetated areas within the duration of the study period. The results of this research could help in the formulation of public policies designed to conserve environmental resources in the Latian Dam Watershed and, consequently, minimize the risks of the fragmentation of orchards and vegetated areas. Also, careful regional planning ensuring the preservation of natural landscapes and open spaces is critical to creating a resilient regional environment and sustainable development.
Se estudió la evolución de la dinámica espacio temporal en el Estado de Tabasco, en el Sureste de México, mediante Land Change Modeler, y se proyectaron escenarios con Cadenas de Márkov y Autómatas ...Celulares. Los resultados señalan que durante quince años (2001-2016) se perdieron 76,522 ha de humedales, 18,333 ha de selvas, y 73,591 ha de vegetación secundaría, debido al crecimiento descomunal de 148,129 ha de uso agropecuario, y la expansión de 13,375 ha de zonas urbanas. Además, mediante Cadenas de Markov y Autómatas Celulares (2016-2030), se proyectaron pérdidas de 19,152 ha de humedales, 8,324 ha de selvas, y 10,592 ha de vegetación secundaría. Este escenario demuestra que se mantendrá el incesante crecimiento agropecuario y de zonas urbanas en los próximos años. Este estudio provee información para los modelos de ordenamiento ecológico territorial, debido a que es urgente conservar y restaurar los últimos ecosistemas del sureste de México.
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•Soy Moratorium in the Legal Amazon changed the Cerrado land use.•Cerrado is responsible for 54 % of the Brazilian soybean yield.•LCM is used to model the LULC dynamics correlated ...with driver variables.•Scenario evaluation was performed based on spatial-temporal data.•Results show the possibility to meet soybean demand with vegetation conservation.
Soy Moratorium implementation in the Legal Amazon in 2006 had consequences beyond deforestation control in the region. Among these, the influence on the dynamics in land use change in the neighbor biome, the Cerrado, is evaluated. This influence becomes especially important considering that this area accounts for 54% of Brazil's soybean production, and that the country is the world's second largest producer of the grain. This work used Land Change Modeler to study the comparison of the Moratorium influence for two scenarios: a temporal analysis of change trends prior to the implementation of this policy, for 2012; and an impact analysis on the Cerrado policy extension for 2028. The main transitions observed on the evaluated period were between Vegetation, Pasture and Agriculture classes. Driver variables of the transition between these classes were used to model the scenarios. The impact of the moratorium on changing the spatial distribution of transitions was mainly noted. For future predictions, grain yield would not be significantly impacted by the extension of the Cerrado Moratorium. Conclusions include the possibility of biome's vegetation preservation, without disregarding the economic importance of soybean for Brazil and still meeting the estimated demand for 2028.
Today, in most countries, especially developing countries, economic growth is at the heart of planning. Since the place of economic activity is the environment, unfortunately, growth has had ...unfortunate consequences for the human environment. The main objective of this study is to measure the reduction of environmental pollutants and greenhouse gas emissions under policy-making scenarios compared to the reference scenario. The research method in this study is using the scenario analysis method based on Long Term Alternatives Planning Model (LEAP). The research findings show that by designing demand-side and supply-side management scenarios, meaning that replacing renewable energies and electricity in place of fossil fuels (crude oil and natural gas), reducing the amount of environmental pollutant emissions for the year 1420 (year horizon) 2014 (Year Zero Planning) is 123.5 million tonnes.
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