Sutee Anantsuksomsri

Eastern Thailand serves as a critical case study for the escalating tension between agricultural preservation and urban expansion, a dynamic recently intensified by the COVID-19 pandemic. This study addresses a pivotal research question: To what extent do emerging socio-economic realities, such as policy shifts, labor fluctuations, and climatic extremes, alter the spatiotemporal continuity of urban expansion? Employing a mixed-methods approach, we integrated multi-stakeholder insights with quantitative spatial modeling to simulate context-specific land use futures through 2030. Qualitative findings indicate that while COVID-19 accelerated agricultural modernization, evidenced by increased mechanization and e-commerce integration, these shifts have limited long-term impact on land use patterns. Instead, regional policy, climate change, and technological innovation emerged as the primary drivers of landscape transformation. Quantitative simulations reveal that urban growth will concentrate in the western provinces bordering Bangkok and the southern coastal corridors of Chon Buri and Rayong. Crucially, across all scenarios, approximately 60% of new urban land is projected to be converted from existing croplands, followed by significant losses in natural forest cover. These results demonstrate that current growth-oriented policies may undermine regional food security and ecosystem services. This study provides a framework for balancing agricultural modernization with ecological preservation, offering essential evidence for developing the integrated, sustainability-focused land use frameworks required to meet 2030 development goals.

This study explores the method of recording memorable places and highlights the peak recollection spots of college town universities across generations--prospective, present, and past students. The chosen areas are the University of Massachusetts Amherst and Cornell University. Ninety participants produced mental maps based on memory, including landmarks, meaningful places, paths, landscapes, and anything they associated with the campus. Following Lynch's methods, elements from sketch maps were mainly landmarks (87%). Current students had a higher percentage of buildings recalled, but fewer landscapes recalled than prospective students and alumni. Adapting from Appleyard's methods, over four-fifths of student populations provided spatial dominant maps, which indicated more substantial stages of spatial knowledge. Categorizing by functional aspects, the highest recollection of all students was landscape and roads (28%), exceeding academic buildings (25%). The researcher counted an element from sketch maps that demonstrated at least one stage of spatial knowledge development and transformed it into digital maps. The collective memory-significant maps presented different patterns of recall frequency among student subgroups. The top three highest intensities were iconic buildings and adjacent landscapes at the core campus. Memory intensity did not diminish equally as distance increased from the central zone. The Hot Spot Analysis, utilizing the Getis-Ord-Gi* statistic and inverse distance weighting (IDW), revealed different patterns of hot spots among generations. A landscape landmark served as a memorable hot spot in every subpopulation. This innovative method could be an additional tool in bridging the gap between practical knowledge and theoretical knowledge to record intangible aspects of memory into databases and measurable plans. Other campuses could implement the procedure and include the memory-significant assessment to design institutional environments that meet diverse student perceptions.

Thailand is vulnerable to severe flooding; for example, the 2011 flood affected 13 million people and caused significant socioeconomic damage. Because of a possible 100-year return period and other climate change effects, in 2012, industrial estates in Ayutthaya, such as the Rojana Ayutthaya Industrial Park, developed flood protection systems by raising the flood walls to around six meters above the mean sea level (MSL); however, the surrounding areas do not have comprehensive plans. This study analyzes the physical landscapes within a radius of two kilometers around Ayutthaya's industrial estate to assess flood vulnerability, after which we develop adaptation strategies based on community input for vulnerable areas. The topography and footprint maps are analyzed to identify the flood scenarios. To compare the urban and agricultural area differences, the highest 2011 water level of 5.30 meters above MSL was applied to identify two scenarios for moderate and extreme flood areas. Alternative mitigation solutions for both scenarios were discussed in a community focus group, which decided that the engineering resistance concept would best prevent moderate flooding because of the current flood protection levee improvements around the study areas. However, while the landscape resilience concept was seen by the communities as a more sustainable solution, it was considered difficult to implement due to land ownership issues. The moderate and severe flood mitigations are conceptually a resistance to resilience shift in flood control approaches, which could be adopted by other regions or countries that suffer similar problems.

Education is a powerful tool against poverty and inequality, yet its potential is undermined by floods. While floods do not affect the population equally, previous studies have ignored the chronic impact of recurrent flooding on education across different economic strata, thereby overlooking the effect of inequality. Our study investigates this dynamic along Thailand’s Chao Phraya River, exploring a novel research topic: “How recurrent floods create inequality in livelihood improvement through education”. Using qualitative methods, we conducted in-depth household interviews lasting 1.5 to 2 h per household. These interviews revealed stark differences in educational experiences between rich and poor, whether these people were flood-affected or not. Even when exposed to the same flood conditions, wealthier households tend to maintain stability while poorer families face severe disruptions that limit their ability to support their children’s education, thereby perpetuating the poverty cycle. Non-flooded poor often exhibit optimism and focus on livelihood upward growth, whereas the flooded poor may face a daily struggle to survive, leaving little time and opportunity for future planning. Meanwhile, affluent families, regardless of flooding, continue to accumulate wealth and pass advantages to their children, further widening economic inequality. Our findings highlight how recurrent flooding not only entrenches poverty but also exacerbates disparities by disrupting education. This underscores the important, and new, notion that to elevate poverty and reduce inequality in flood-prone developing countries, education alone is insufficient.

The impact of COVID-19 on urban workplaces has led to an increasing demand for coworking spaces (CWSs) in Bangkok and has expanded CWSs into suburban areas. This study examines the impacts of COVID-19 on CWSs and focuses on the spatial pattern of CWSs in Bangkok. It seeks to answer the following question: Does the business operation of CWSs in Bangkok have a clustered pattern? Moran's I statistic was employed to investigate the spatial autocorrelation of CWSs in Bangkok before and during COVID-19. The locations and the business operational statuses of CWSs are the main variables.The results of spatial autocorrelation analysis of the CWSs in Bangkok show that before COVID-19, the overall CWSs in Bangkok were spatially clustered patterns with nearby CWSs. Surviving CWSs may not have been spatially related during the pandemic, while closed CWSs were spatially clustered patterns. Key findings show that the operational status of the overall CWSs and closed CWSs influenced nearby CWSs. However, the operational status of surviving CWSs may not have influenced nearby CWSs.The discussion of CWS spatial patterns and the impact of COVID-19 suggests that the spatial patterns of CWSs challenge the location theory. They blur the traditional workplace usage boundaries, particularly redefining the concept of third places, as people can now work from anywhere with flexibility. Furthermore, these patterns could influence future strategies for the development of urban workspace, infrastructure, and transportation network.

Urban migration the expansion of informal settlements are pressing issues in fast-growing cities like Bangkok The Klong Toei community a significant informal settlement faces challenges related to relocation driven by urban development land reclamation initiatives from the Port Authority of Thailand This study examines how job location influences residents' willingness to relocate addressing a critical gap in urban planning literature concerning the socioeconomic factors impacting slum dwellers This research aims to explore the relationship between the proximity nature of employment the willingness of Klong Toei residents to relocate It seeks to inform more humane effective resettlement strategies that reflect the community's real needs preferences Employing a mixed-methods design this study integrates quantitative data from structured surveys with qualitative insights from interviews conducted in three distinct sub-communities of Klong Toei Analytical techniques including spatial autocorrelation cluster analysis are utilized to investigate the patterns influencing relocation decisions The findings indicate that job locations are randomly distributed not clustered with a statistically significant correlation between job location willingness to relocate Key factors affecting this willingness include job type distance from employment generational differences among residents The results emphasize the need for urban policymakers to consider employment factors in the planning of resettlement programs By aligning urban development strategies with the employment realities of slum dwellers policymakers can enhance the acceptance success of relocation efforts ensuring they meet the diverse needs of affected communities This study provides valuable insights for future policy-making urban planning processes

Household debt in Thailand has become a serious problem, particularly for the elderly, because they have less ability to pay debts compared to the working population. Therefore, better understanding of the elderly’s debt and delinquency is crucial in policy formulation for the aged society. Previous works have focused on the elderly’s debt, either at the macro or individual levels. Little is known about geographic differences at the regional level. Knowing where the elderly debt and delinquency tend to cluster could guide area-specific policies to tackle the elderly financial stability. This research aims to examine the spatio-temporal distribution of the debt and delinquency of the near-elderly population (age 50–59) and the elderly (age 60 and above) using data from the National Credit Bureau of Thailand from 2008 to 2019. The analysis focuses on various types of loans. Spatial clusters are identified by Moran’s I and Local Geary statistics. The results show that the pattern of elderly debt and delinquency generally follows the life cycle hypothesis, except for credit card and business-related loans. There exist spatial clusters and spatial differences in different types of loans, suggesting regional heterogeneities that require area-specific policy responses.

This study aims to understand the spatiotemporal changes in patterns of tropical crop cultivation in Eastern Thailand, encompassing the periods before, during, and after the COVID-19 pandemic. Our approach involved assessing the efficacy of high-resolution (10 m) Sentinel-2 dense image time series for mapping smallholder farmlands. We integrated harmonic regression and random forest to map a diverse array of tropical crop types between summer 2017 and summer 2023, including durian, rice, rubber, eucalyptus, oil palm, pineapple, sugarcane, cassava, mangosteen, coconut, and other crops. The results revealed an overall mapping accuracy of 85.6%, with several crop types exceeding 90%. High-resolution imagery demonstrated particular effectiveness in situations involving intercropping, a popular practice of simultaneously growing two or more plant species in the same patch of land. However, we observed overestimation in the majority of the studied cash crops, primarily those located in young plantations with open tree canopies and grass-covered ground surfaces. The adverse effects of the COVID-19 pandemic were observed in specific labor-intensive crops, including rubber and durian, but were limited to the short term. No discernible impact was noted across the entirety of the study timeframe. In comparison, financial gain and climate change appeared to be more pivotal in influencing farmers’ decisions regarding crop cultivation. Traditionally dominant crops such as rice and oil palm have witnessed a discernible decline in cultivation, reflecting a decade-long trend of price drops preceding the pandemic. Conversely, Thai durian has seen a significant upswing even over the pandemic, which ironically served as a catalyst prompting Thai farmers to adopt e-commerce to meet the surging demand, particularly from China.