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This paper aims to assess the rate and land category contributing to the changes in seven land-uses in the Kintampo North Municipality of Ghana and the effect of the decisions of land users on future landscapes.

LANDSAT images were classified to generate land use/cover maps to detect changes that had occurred between 1986 and 2014. In total, 120 farmers were also interviewed to determine their perceptions on land use changes. Interval, category and transition levels of changes were determined. Savanna woodland, settlement and forest were mostly converted to farmland in both intervals (1986-2001 and 2001-2014).

Results showed that rock outcrop, plantation, cropland and savanna woodland increased at an annual rate of 13.86, 1.57, 0.82 and 0.33 per cent, respectively, whilst forest, settlement and water body decreased at 4.90, 1.84 and 1.17 per cent annual rate of change, respectively. Approximately, 74 per cent of farmers will not change land use in the future, while 84.2 per cent plan to increase farm sizes.

The study shows that more land cover will be targeted for conversion as farmers expand their farmlands. There is the need for strict implementation of appropriate land use/cover policies to sustain food production in the region in this era of changing climate and population increase.

This research assessed the land use changes in the Kintampo North Municipality and its impacts on agriculture and carbon stocks release via land use changes. It identified how the decisions of the local farmers on land management will affect future landscape.

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai.

Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions.

Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD.

In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.

The purpose of this paper is to provide the extensive review on dynamic monitoring of forestry area in China.

Countermeasure and suggestions were proposed for three aspects including the establishment of data sets with unified standards, top-level design of monitoring and assessment and analysis models, and establishment of the decision support platform with multiple scenario simulation.

Finally, the authors proposed key research area in this field, i.e., improving the systematic and optimal forest management through integrating and improving the data, models and simulation platforms and coupling the data integration system, assessment system and decision support system.

The authors explored the limitation of dynamic monitoring and state of the art research on data accumulation, professional model development and the analytical platform.

This study aims to present the climate change effect on soil moisture regimes in Mexico in a global 1.5°C warming scenario.

The soil moisture regimes were determined using the Newhall simulation model with the database of mean monthly precipitation and temperature at a scale of 1: 250,000 for the current scenario and with the climate change scenarios associated with a mean global temperature increase of 1.5°C, considering two Representative Concentration Pathways, 4.5 and 8.5 W/m² and three general models of atmospheric circulation, namely, GFDL, HADGEM and MPI. The different vegetation types of the country were related to the soil moisture regimes for current conditions and for climate change.

According to the HADGEM and MPI models, almost the entire country is predicted to undergo a considerable increase in soil moisture deficit, and part of the areas of each moisture regime will shift to the next drier regime. The GFDL model also predicts this trend but at smaller proportions.

The changes in soil moisture at the regional scale that reveal the impacts of climate change and indicate where these changes will occur are important elements of the knowledge concerning the vulnerability of soils to climate change. New cartography is available in Mexico.

The purpose of the study is to analyze changes in land use, specifically residential area expansion, in South Tangerang City and identify the factors that influence land use change.

The study used remote sensing methods in ArcGIS 10.8 for data analysis and processing, including spatial analysis and identification of land use changes. The study analyzed satellite images from 2010 and 2020 to identify changes in land use in South Tangerang City over the ten-year period.

The study found that the most significant land use changes in South Tangerang City between 2010 and 2020 were the reduction of mixed plantation area and the expansion of residential areas. The study identified the development of small townships by private developers as the main factor that influenced land use change in South Tangerang City.

The study has several limitations, including a focus on only one aspect of land use change (i.e. residential area expansion), limited scope of the study area (South Tangerang City) and a reliance on remote sensing methods for data analysis.

The findings of the study can be used by policymakers and city planners to develop sustainable land use planning strategies that balance the need for urban development with environmental and social concerns. By understanding the factors that drive land use changes in South Tangerang City, policymakers can develop policies that encourage sustainable urban growth and development while preserving natural resources and protecting the environment.

The study has social implications as the expansion of residential areas in South Tangerang City indicates a growing demand for housing in the area. The study highlights the importance of developing affordable and sustainable housing solutions to meet the needs of the growing population in South Tangerang City. Additionally, the study emphasizes the importance of understanding the social and economic factors that drive land use change and their implications for the well-being of local communities.

The residential area development in South Tangerang City is driven by private developers who make small independent cities that have all facilities in one area. These small cities attract people to reside and also drive high population growth in South Tangerang City, considering it is a buffer city of Jakarta that has good infrastructure development.

Cities are facing challenges that dramatically affect their social and physical landscapes, leading to the increase of urban segregation and polarization. One response to these challenges is adaptive reuse, yet, in heterogeneous communities, these adaptations are often a source of conflict, because local actions often lack an integrative approach, leading to further exclusion. In this paper the authors explore the potential of adaptive reuse of urban heritage as a planning tool to support inclusiveness and heterogeneity.

The city of Acre is used as a case study, where different scenarios for urban heritage are proposed and tested among stakeholders through interviews. These aim to explore how adaptive reuse processes can lead to the inclusion or exclusion of certain groups and how design interventions in historic urban landscapes challenge the way the current disconnected historic and urban layers interact.

The paper presents the commonalities and differences between the interviewees' perceptions on Acre's functioning, their idea of inclusiveness and other aspects related to urban design. Moreover, it highlights the existing conflicts of interest, value prioritization and the adequacy of the proposed scenarios, serving as a way to verify the accuracy of the scenario building process.

Testing an urban design tool related to adaptive reuse of urban heritage in a real and extreme case, based on the guidelines of the Historic Urban Landscape Recommendation; and critically analysing the sources of conflict and value systems to address inclusion in heterogenous settings.

This paper attempts to examine drivers of tourism development by affording a framework that sustains economic growth and protects the local environment. It develops evaluative and predictive models to measure city performance. Further, a strategy-based model of low carbon cities (SMLC) is used to demonstrate possible tourism development scenarios. The model was applied to the city of Surakarta to operationalize city's transformation towards sustainability.

The research methodology is constructed on three interrelated components: theoretical framework, analytical methods and SWOT. First, the authors have initiated this study by an understanding of linkages between planning and tourism. Second, the SMLC has been used to test sustainable tourism in the city of Surakarta. Third, Strength-Weakness-Opportunity-Threat (SWOT) analysis was applied to formulize the recommendations.

When evaluated by the static SMLC model, the city of Surakarta was categorized as an unsustainable touristic city. However, when the dynamic SMLC was applied, the city of Surakarta was categorized as a sustainable touristic city under a high economy scenario. By reason of the methodological and analytical frameworks and the dynamic SMLC, the city of Surakarta could be promoted to a sustainable touristic city after applying opportunity-seeking strategy and policies.

The paper concludes with policy implications to realign city plan and support sustainable tourism development in the city of Surakarta.

This paper attempts to develop a framework for sustainable tourism as it operates in the city of Surakarta by (1) introducing the sustainable touristic city concept, (2) definition and characters, (3) evaluative and predictive models using the SMLC to measure city performance of the city of Surakarta and (4) rigorous and relevant insight into the magnitude of the benefits of tourism.

This paper aims to assess agri-environment (AE) scheme options on cultivated agricultural land in England for their impact on agricultural greenhouse gas (GHG) emissions. It considers both absolute emissions reduction and reduction incorporating yield decrease and potential production displacement. Similarities with Ecological Focus Areas (EFAs) introduced in 2015 as part of the post-2014 Common Agricultural Policy reform, and their potential impact, are considered.

A life-cycle analysis approach derives GHG emissions for 18 key representative options. Meta-modelling is used to account for spatial environmental variables (annual precipitation, soil type and erosion risk), supplementing the Intergovernmental Panel on Climate Change methodology.

Most options achieve an absolute reduction in GHG emissions compared to an existing arable crop baseline but at the expense of removing land from production, risking production displacement. Soil and water protection options designed to reduce soil erosion and nitrate leaching decrease GHG emissions without loss of crop yield. Undersown spring cereals support decreased inputs and emissions per unit of crop yield. The most valuable AE options identified are included in the proposed EFAs, although lower priority is afforded to some.

Recommendations are made where applicable to modify option management prescriptions and to further reduce GHG emissions.

This research is relevant and of value to land managers and policy makers. A dichotomous key summarises AE option prioritisation and supports GHG mitigation on cultivated land in England. The results are also applicable to other European countries.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.