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This paper aims to inform the readers an overview of expected impacts of sea level rise (SLR) and climate change on rice crops area, yield and the urgent need to build climate responsive infrastructures to a coastal district, Alappuzha – a high-risk area which is already under mean sea level (MSL). This research carried out to understand the realities and impacts with respect to the exposures of rise in SLR and possible inundation extent of crop land. The extreme precipitation events have caused crop loss and damage, numerous casualties and enormous economic loss in this district during the recent past and project the likely impacts under anticipated climate change.

Global sea levels have already been risen noticeably as a result of climate change, and this trend is anticipated to continue. To reflect on the research objectives, the paper projects a climate change scenario analysis and impact assessment on the major crop grown, i.e. rice, using a crop simulation model, DSSAT 4.7 as the first part of the study. QGIS 3.28 version and Erdas Imagine software were used for land use land cover analysis and to delineate possible inundation in the major land use land cover, especially in agriculture area under SLR scenario. It points out the need to equip the district urgently with climate responsive agriculture strategies as majority of the area comes under 10 mts of elevation as per the Sentinel 2 data. For better adapting to the current and future climate change impacts in the aspects of built environment such as early warnings in farm sector in particular and forests, urban water management, transportation systems, building construction and operation and land use planning in general. Climate change is no longer a policy issue alone; now it is a common man’s nightmare. For a coastal state like Kerala, extreme climate events during 2018 and 2019 and 2021 have posed substantial impacts and damages on the environment and society. The impacts hit the vulnerable communities in multiple ways.

From the analysis, it was revealed that there is an increasing trend in rainfall observed over the past three decades in Alappuzha district. It is projected that day and night time temperatures may increase in Alappuzha by 2.5°C and 2.6°C by 2100, respectively, under RCP 4.5. With unchecked pollution or emission reduction actions, warming may further rise and hence the median projection when SLR reaches 2.4 meters (8 ft) at Alappuzha to Cochin coast is 2130s. The possible inundation analysis shows that around 53.48% of the coastal agriculture land may be likely inundated if SLR is only with mitigation measures such as extreme carbon cuts, SLR rise can be delayed till 2200. Alappuzha is known as the rice bowl of Kerala; however, it is highly exposed to climate vulnerability in terms of its unique environmental geographical settings like coastal wetlands, lagoons and sand beaches. DSSAT simulations shows that Uma rice, a major ruling variety in the region, may have yield reductions of up to 13% in the near century for Alappuzha.

This paper in general explains the projected climate change perspectives for Alappuzha, a climate change hotspot of Kerala with respect to SLR and coastal agriculture. and a review of the progression of DRR in the built environment and mainstreaming CCA and DRR by government and other agencies in the state.

This study underscores the urgent need for climate-responsive agricultural strategies in Alappuzha, Kerala, due to anticipated sea level rise, climate change, and land use changes. Equipping farmers with the knowledge and tools to adapt is essential for ensuring food security and sustainable livelihoods. Implementing climate-resilient practices and technologies will help mitigate adverse effects on rice crops, promoting economic stability and resilience in the region. Involving local stakeholders in the adaptation process is crucial, as their participation can enhance collaboration, increase awareness, and accelerate the adoption of sustainable agricultural practices, making the transition smoother and more effective.

It is the responsibility of the scientific community to inform the knowledge gained for the benefit of the society, especially on criticality of altering the existing land use pattern and building climate resilient coastal infrastructures. Studies such as this can stand as basis for implementing planned adaption actions. This is to conclude that instead of working in silos, mainstreaming climate change adaptation holistically across sectors is very necessary at this crucial hour. Participatory action plans and policies involving all local stakeholders can strengthen awareness and fasten the learning processes for adaptation including managed retreats.

At present, there are no specific studies, on the impacts of climate change and SLR on rice cropping systems in the district which specifically inform how to mainstream adaptation in the agriculture strategies in low lying coastal zones of Alappuzha.

This article explores the impacts of the changing land-use on urban heat island (UHI) in an urban transformation zone in Ankara (Türkiye). Identifying a characteristic rural landscape until the 1950s, the study area experienced a drastic land-use change by razing the fertile landscape of the city and replacing it with a sealed surface. Development of the squatter houses after the 1960s and, subsequently, the implementation of a new housing morphology have introduced new sceneries, scales and surface conditions that make the study area a noteworthy case to analyze.

Regarding the drastic spatio-temporal change of the study area, this research assesses the impacts of the changing land-use on UHI based on three periods. Using 1957, 1991 and 2021 aerial imaginaries and maps, it analyzes the temperature alteration caused by the changing land-use. To do so, different surface types, green patterns and built-up areas have been modeled using Ankara climatic data and transferred to ENVI-Met to calculate the Universal Thermal Climate Index (UTCI) values.

The calculation has been developed over a transect covering an area of 40 m × 170 m, which includes diversity in terms of architecture, landscape and open space elements. To encourage future design strategies, the research findings deliberate into three extents that discuss the lacking climate knowledge in the ongoing urban transformation projects: impervious surface ratio and regional albedo variation, changing aspect ratio and temperature variation at the pedestrian level.

Urban transformation projects, being countrywide operations in Türkiye, need to cover climate-informed design strategies. Herein, the article underlines the critical position of design decisions in forming a climate-informed urban environment. Dwelling on a typical model of housing transformation in Türkiye, the research could trigger climate-informed urban development strategies in the country.

This study aims to understand how climatic drivers of change will affect rural communities living in the hot semiarid region of Bhokardan Taluka of Jalna district in the Indian state of Maharashtra. In the context of the economic and social change they are experiencing, the concern is to evolve ways that enable them to cope with, adapt to and benefit from these challenges.

The focus of most of the climate change studies is on the short- to long-term trends of weather parameters such as rainfall, temperature and extreme weather events. The impact of climate variability and changing patterns on the local communities, the local economy, livelihoods and social life in specific geographies is less explored.

As the impacts of climatic and nonclimatic drivers of change are cross-sectoral, diverse, multidimensional, interlinked and dynamic, this study has adopted a transdisciplinary “research-in-use” approach involving multidisciplinary teams covering the aspects such as changes in land use and land cover, surface and groundwater status, edaphic conditions, crops and livestock, climate analysis including projected changes, socioeconomic analysis, people’s experience of climate variability and their current coping strategies and resilience (vulnerability) analysis of communities and various livelihood groups.

The study was based on the peoples’ perspective and recommendation based on the local communities ability to cope up with climate change. However, a statistical analysis perspective is missing in the present study.

Based on these findings, a set of implementation-focused recommendations are made that are aimed at conserving and enhancing the resilience of the foundations that uphold and sustain the social and economic well-being of the rural communities in Bhokardan taluka, namely, land, water, agriculture, livestock, food and nutrition security, livelihoods, market access and social capital.

This paper aims to assess the current and future dynamics of land cover transitions and analyze the vegetation conditions in Abuja city since its establishment as the capital of Nigeria in 1991.

A random forest classifier embedded in the Google Earth Engine platform was used to classify Landsat imagery for the years 1990, 2001, 2014 and 2020. A post-classification comparison was used to detect the dynamics of land cover transitions. A hybrid simulation model that comprised cellular automata and Markovian was used to model the probable scenario of land cover changes for 2050. The trend of Normalized Difference Vegetation Index was examined using Mann–Kendall and Theil Sen’s from 2014 to 2022. Nighttime band data from the National Oceanic and Atmospheric Administration were obtained to analyze the trend of urbanization from 2014 to 2022.

The findings show that built-up areas increased by 40%, while vegetation, bare land and agricultural land decreased by 27%, 7% and 8%, respectively. Vegetation had the highest declining rate at 3.15% per annum. Built-up areas are expected to increase by 17.1% between 2020 and 2050 in contrast with other land cover. The proportion of areas with moderate vegetation improvement is estimated to be 15.10%, while the proportion of areas with no significant change was 38.10%. The overall proportion of degraded areas stands at 46.8% due to urbanization.

The findings provide a comprehensive insight into the dynamics of land cover transitions and vegetation variability induced by rapid urbanization in Abuja city, Nigeria. In addition, the findings provide valuable insights for policymakers and urban planners to develop a sustainable land use policy that promotes inclusivity, safety and resilience.

Studies on land acquisition (LA) and recovery simulations have garnered considerable attention amidst climate change. Previous literature has reported that LA and relocation contribute to reducing repetitive disaster losses or downzoning (limiting development). However, studies on decision-making about resettlement or relocation for landowners or decision-makers for disaster-impacted lands are limited. This study aims to qualitatively illustrate LA program schemes for recovery, and identify the underlying concepts of LA in Italy, the United States and Japan. By doing so, this study contributes to construction of future agent-based recovery simulations.

This study seeks to identify a variety of LA models in different contexts to provide input for future works. This study employed multiple case studies to explore common and contrasting results, and identify varied LA concepts. The methodology involved a literature review, including official reports, to examine the timeframes of LA projects qualitatively, complemented using aerial photos to confirm related land use changes pre- and post-LA.

The results indicate that buyout programs in the United States enhance renaturalization in flood-prone areas as a downzoning approach. In contrast, LA in Japan focuses on the continuation of communities or neighborhoods through the recovery and relocation process. In Italy, LA is used to contribute to supporting the tradition/legacy of historic housing and facilities for post-disaster temporary dwellings, reflecting an underlying concept of “tradition and legacy.”

This comparative study fills a research gap by focusing on LA concepts, and its novelty lies in finding the underlying concepts of LA in three countries. Through international comparison, it suggests that LA in Japan could incorporate conservation of the historical town center or the opportunity for downzoning.

Despite the enormous need to succeed in the urban model, scientists and policymakers should work consistently to create blueprints to regulate urbanization. The absence of coordination between the crucial requirements and the regional strategies of the local authorities leads to a lack of conformance in urban development. The purpose of this paper is to address this issue.

This study intends to manage future urban growth patterns using integrated methods and then employ the results in the genetic algorithm (GA) model to considerably improve growth behavior. Multi-temporal land-use datasets have been derived from remotely sensed images for the years 1990, 2000, 2010 and 2020. Urban growth patterns and processes were then analyzed with land-use-and-land-cover dynamics. Results were examined for simulation and utilization of the GA.

Model parameters were derived and evaluated, and a preliminary assessment of the effective coefficient in the formation of urbanization is analyzed, showing the city's urbanization pattern has followed along with the transportation infrastructure and outward growth, and the scattering rates are high, with an increase of 5.64% in building area associated with a decrease in agricultural lands and rangelands.

The research achieved a considerable improvement over the growth behavior. The conducted research design was the first of its type in that field to be executed to any specific growth pattern parameters in terms of regulating and policymaking. The method has integrated various artificial intelligence models to monitor, measure and optimize the projected growth by applying this design. Other research on the area was limited to projecting the future of Amman as it is an urbanized distressed city.

This study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).

Using the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.

The study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.

The novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

This study aims to develop a modelling framework of housing supply dynamics within the context of urban microsimulation systems. Housing markets have witnessed substantial investigation over recent decades, predominantly concerning residential demand. However, comparatively limited attention has been directed towards comprehending the housing supply dynamics. Housing policy disconnects with the developers’ market behaviours, which leads to significant mismatch between the housing construction and affordable housing needs of the population. Research attention should be made in comprehending the residential construction market activities. To address this gap, this study developed an autoregressive distributed lag (ARDL) model and analyzed the temporal evolution of housing construction.

An ARDL model was developed to address the issue of temporal modelling of the housing supply. An empirical study was conducted in the Greater Toronto and Hamilton Area (GTHA) based on a longitudinal housing starts data set from 1998 to 2020. The model integrates diverse variables, including macroeconomic conditions, property development costs, dwelling prices and opportunity costs. Notably, the model captures both the path-dependent effects stemming from supply market fluctuations and the temporal lag effect of influential factors.

The findings reveal that the supply-side’s responsiveness to market condition alterations may span up to 18 months. The model has reasonable and satisfying performance in fitting the observed starts. The methodological foundations laid will facilitate future modelling of housing supply dynamics.

This study innovatively separated the modelling of housing supply within the context of urban microsimulation, into two parts, the modelling of housing starts and completion. The housing starts are determined in a complex and regressive process influenced by both the micro-economic environment and the construction cost and housing market trends. Through the temporal modelling method, this study captures how long it would take for the housing supply to respond to multiple factors and provides insight for urban planners in regulating the housing market and leveraging various policies to influence the housing supply.

Agricultural land loss is a severe issue that Australia faces, along with many other countries. Myriad research studies have discussed the reasons for such land loss, including urban sprawl as the main factor and factor's repercussions. However, there is a knowledge gap in understanding the impact of dwelling type on farming land reduction. Also, there is an application gap, particularly in the local context. The purpose of this study is to discover the effect of differing dwelling types (compact and non-compact) in metropolitan areas with a growing population (such as Craigieburn) toward potentially noticeable agricultural land loss.

This paper aims to fill these research and practice gaps through a case study using a mixed methods approach. A quantitative analysis was conducted of housing types, the types' growth and agricultural land area taken up by those different housing types over 18 years. Thematic analysis of policies, strategies, schemes and codes relevant to the case study enabled a better understanding of practice gaps.

The study revealed a significant loss of agricultural land. Separate housing was found to be the main culprit due to the number of houses and the area the houses require, thus exhibiting the lack of practical guidelines to prevent the houses' overdevelopment. The findings enabled the identification of opportunities for better practice through government intervention and potential industry alterations.

Previous literature has primarily explored the issues associated with urban sprawl and the sprawl's unsustainability. This research paper offers a more targeted insight into one of the key factors leading to urban sprawl: the types of dwellings being constructed.

This study aims to analyze the short-, medium- and long-term impacts of natural-resources-seeking foreign direct investment (FDI) in the form of foreign multinational enterprise (MNE) land acquisitions on agricultural labor productivity in developing countries. The authors analyze if these land acquisitions disrupt fair and decent rural labor productivity or if the investments provide opportunities for improvement and growth. The influence of different country characteristics, such as economic development levels and governmental protection for the rural population, are acknowledged.

The study analyzes 570 land acquisitions across 90 countries between 2000 and 2015 via a generalized least squares regression. It distinguishes short- and long-term implications and the moderating role of a country’s economic development level and government effectiveness in implementing government protection.

The results suggest that natural resource-seeking FDI harms agricultural labor productivity in the short term. However, this impact turns positive in the long term as labor markets adjust to the initial disruptions that result from land acquisitions. A country’s economic development level mitigates the negative short-term impacts, indicating the possibility of finding alternative job opportunities in economically stronger countries. Government effectiveness does have no influence, presumably as the rural population in which the investment is partaking is in many developing countries, not the focus of governmental protectionism.

The findings provide interesting insights into the impact of MNEs on developing countries and particularly their rural areas that are heavily dependent on natural resources. The authors identify implications on employment opportunities in the agricultural sector in these countries, which are negative in the short term but turn positive in the long term.

Moreover, the findings also have utility for policymakers. The sale of land to foreign MNEs is not a passive process – indeed, developing country governments have an active hand in constructing purchase contracts. Local governments could organize multistakeholder partnerships between MNEs, domestic businesses and communities to promote cooperation for access to technology and innovation and capacity-building to support employment opportunities.

The authors urge MNE managers to establish new partnerships to ease transitions and mitigate the negative impacts of land acquisitions on agricultural employment opportunities in the short term. These partnerships could emphasize worker retraining and skills upgrading for MNE-owned land, developing new financing schemes and sharing of technology and market opportunities for surrounding small-holder farmers (World Bank, 2018). MNE managers could also adopt wildlife-friendly farming and agroecological intensification practices to mitigate the negative impacts on local ecosystems and biodiversity (Tscharntke et al., 2012).

The authors contribute to the debate on the positive and negative impact of FDI on developing countries, particularly considering temporality and the rural environment in which the FDI is partaking.