Asia-Pacific Journal of Regional Science最新文献

This article reviews the book by Akita and Kataoka (Regional inequality and development: Measurement and applications in Indonesia, 2022). The book first provides an overview of various measurement methods of regional inequality. Next, it presents four case studies that deepen our understanding of regional inequality in the context of the development challenges of Indonesia: decentralization, premature deindustrialization, financial crisis, low labor productivity, among others. Overall, this book provides an excellent introduction and application of inequality decomposition methods in the context of regional disparities and structural change.

This study examined the impact of climate change on yield, production and cropped areas of rice, wheat, gram and maize in Himachal Pradesh (Province), India, from 1970 to 2019 using the Cobb–Douglas production function approach (CDPFA). Euler’s theorem and marginal impact analytical technique (MIAT) were applied to determine the nature and degree of homogeneity and projected values of the selected crop yields, production and cropped areas. The results revealed that climate change significantly affects the yield, production and cropped areas of Himachal Pradesh. However, the impact of climatic factors significantly varied according to the crops. Based on Euler’s theorem, the findings revealed a decreasing return to scale for these crops’ yield, production and cropped area function. The projected estimates showed that rice, wheat and gram production and yields are expected to decline significantly by the 2040s, 2060s, 2080s and 2100s. The projected cropped area of rice and wheat may increase by the 2040s, 2060s and 2080s due to climate change, but after that, the state may experience a declining trend in both crops. On the other hand, the projected cropped areas of maize have shown an upward trend over the years. In conclusion, agricultural production in the state is at an alarming stage due to climate change and requires significant policy intervention. Farmers should use appropriate agricultural technologies, mixed cropping patterns, advanced irrigation facilities and crop insurance policies to reduce the negative consequences of climate change in the agricultural sector of Himachal Pradesh.

Valuing air quality can help governments better evaluate the economic benefits of policies related to air pollution. However, many studies ignore heterogeneity and spatial effects within cities, which may render the results inaccurate. To fill these gaps, this study attempted to examine individuals’ marginal willingness to pay (MWTP) for air quality across locations and buyers in Beijing by utilizing hedonic price, spatial regression and quantile regression models. The results showed: (1) a concentration of PM2.5 is significantly negatively correlated with housing prices. Specifically, the value of the MWTP for a 1% improvement in PM2.5 is US$327, and this figure is US$177 after considering the spatial effects. (2) The MWTP for air quality is heterogeneous across locations. MWTP for air quality is lower the farther away the location is from the central business district (CBD) and the nearest employment center, the lower the MWTP for air quality. (3) Buyers of high-priced housing display a higher MWTP for air quality. These findings show that developing countries facing environmental issues should re-examine the traditional development model of “sacrificing the environment for economic growth” and develop a sustainable model. Moreover, further joining of air pollution control and a differential, location-specific scheme coupled with an individual-specific scheme for developing new communities is necessary.

Rapid satellite-based flash flood inundation mapping and the delivery of flash flood inundation maps during a flash flood event for wetland communities can provide valuable information for decision-makers to put relief measures and emergency responses in place without delay. With remote sensing techniques, flash flood mapping of large areas, basically wetlands, can be done quickly with a high level of precision through different water indices. This study developed an algorithm for rapid flash flood inundation mapping for crisis management through the demarcation of the most flash flood-inundated areas in the Haor Basin (wetlands) of Bangladesh by utilizing high-resolution Sentinel-2 remotely sensed data. The algorithm applied here involves near-infrared (NIR) spectral band-derived indices, namely, a normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) to develop a rapid flash flood water detection technique integrating three year (2017–2019) datasets before and after flash floods. A simple threshold method was created to cluster the data and identify the flash flood pixels in the imagery using a density slicing technique followed by natural break analysis. Calculations were then made to estimate the flash flood (inundated), mixed pixels and non-inundated pixels for each year and three combinations. NDVI and NDWI, as well as their combinations (NDVI-NDWI), were remarkably effective for extracting inundation, non-inundation and mixed pixels. Additionally, highly consistent results were obtained for all inundation classes in the studied areas, confirming that NIR-derived indices can effectively detect water pixels. However, a higher inundation pixel value was observed in the Tahirpur Subdistrict compared with the other two study areas (Gowainghat and Kulaura). The developed NIR band-derived water indices algorithm produced more than 80.0% accuracy to detect water-related pixels when verified with ground reference points. As shown by these results, the developed NIR band-derived water indices were capable of effectively detecting flash flood water turbidity in wetland areas. Therefore, these NIR band-derived water indices can be applied for rapid flash flood inundation mapping just after a flash flood occurrence for immediate decisions to support affected farmers.

Understanding trends in regional house prices and whether they converge to a single steady state or form clusters are important issues. These trends have been studied at length in respect to advanced and emerging market economies (EMEs). However, the trends are not understood well in the context of a major and populous EME such as India, which can offer vital policy insights for other countries. Using residential house price data for fifty cities, this study showed that house prices do not converge to a single steady state in India. Rather these prices form three clusters wherein they converged to their respective steady-state paths and displayed conditional convergence. Higher initial house price, home loan, rent, population density and literacy were associated with an increased probability of higher house price club. City inflation, on the contrary, increased the chances of association with lower-price clubs. Similar dynamics of housing clusters can enable policymakers to probe the common driving factors and accordingly devise cluster-specific policy measures. There is no study, so far, on club convergence of house prices for India; so this study contributes to this gap in the literature.

Jamuna, a dynamic and unstable braided river system in Bangladesh, is approximately 240 km long and becomes extremely unstable during the rainy season resulting in serious bank erosion. Therefore, this study aimed to assess the erosion-prone areas adjacent to the Jamuna River system. Change detection analysis was carried out using Landsat 8 (OLI) images captured in 2020 by multi-criteria analysis using a geospatial fuzzy expert system and state-of-the-art remote sensing technology. Normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference water index (NDWI), distance from the river, land use and land cover (LULC), and slope and elevation were selected as criteria for this analysis. All criteria maps were standardized using fuzzy membership functions and reclassification of each criteria performed. Furthermore, expert judgments were included to rank the criteria influencing vulnerable areas based on an analytical hierarchy process (AHP) approach. Finally, a weighted overlay map was prepared for erosion vulnerability assessment from the reclassified maps. From these analyses, we found that water bodies covered 1003 km² (10.94%), high-to-moderate erosion-prone areas were 7401.21 km² (77.39%), marginal erosion-prone areas 1065 km² (11.61%) and nonerosion-prone areas only 5.9 km² (0.06%), respectively. To verify the vulnerable areas, 150 reference points of water bodies from the mainstream of the Jamuna River were taken using Google Earth Pro images captured in 2020. These points were plotted on the NDWI maps of 2020 and 1990 to verify the detection of changes in the riverbank shifts for 30-year intervals. This confirmed the bank shifted from 3 to 4 km in more than 20 points during this span of time. Our analysis also confirmed that high-to-moderately erosion-vulnerable areas fall between 3 and 7 km. Therefore, we recommend the adoption of new agricultural land use planning, considering erosion venerable areas to ensure agricultural production and livelihood security.

Three border provinces in southern Thailand commonly known as the Deep South have a long history of conflicts and insurgency. These chronic conflicts in the Deep South may forcibly hinder educational attainment and its effectiveness in the aggregate economy. This study aimed to analyze the comparative effects of education on the aggregate economy between the Deep South (a region with conflict) and other provinces of the South (a region of harmony) in Thailand. The Thai Labor Force Survey from 1995 to 2015, a large-scale national survey conducted by the National Statistical Office, and data from the Office of National Economic and Social Development Council (NESDC) of Thailand were used for the analysis. Employing a Random Effect Model and pooled regression, this study revealed that if average schooling increases by one percent, overall economic output will increase by 2.62%. However, the effects of educational attainment are significantly lower in the Deep South economy compared to other southern provinces. Therefore, this study provides an analysis of the comparative effects of schooling on the economy between areas of conflict and harmony because this issue has not been properly addressed in the existing literature.

The public health sector of India suffers from higher inequalities despite interventions introduced from time to time. The groups suffering the most are the populations in Empowered Action Group (EAG) states, with limited access to health interventions and higher mortality and morbidity rates. Madhya Pradesh, an EAG state, is infamous for its low-level health status due to disparities in access to health care. This study aimed to understand how access to health care differs spatially in the state and identify the hotspots for urgent attention. Indicators related to health were selected from the association of Sustainable Development Goal 3 (Good Health and Wellbeing) with other SDGs, especially from 1 to 10. Principal Component Analysis was used to construct two indices, viz. Health Status Index (HSI) and Health Intervention Index (HII) out of the indicators. The results showed that the spatial distribution of HSI and HII possess a positive Moran’s I, indicating spatial clustering of these indices in the state. The bivariate association between the two indices is positive but close to zero, indicating a lower association between coverage of health indicators and health status among districts of Madhya Pradesh. These results can provide wide applications while targeting health interventions at the district level.

Drought is a complicated and slow-moving natural disaster that has severe impacts on plant greenness and yields by interrupting plant photosynthetic activity. These issues mostly happen due to water shortages and elevated temperatures. Grapes are sensitive to water stress during the summer, when high evapotranspiration is combined with very low precipitation. Therefore, the main aim of this research was to identify drought-affected vineyards on a regional scale by satellite remote sensing images with a standardized precipitation index (SPI) and standard vegetation index (SVI). The time-series standard vegetation index (SVI) was developed from the time-series normalized difference vegetation index (NDVI) for 2013–2021, and the time-series SPI was calculated from time-series CHIRPS rainfall using the Google Earth engine (GEE). Drought severity maps were classified based on thresholds from extremely dry to extremely wet. Validation was performed between drought indices and grape yield at the regional level using regression analysis. The results indicated that the years 2013, 2014, 2015, 2016, 2018 and 2021 were characterized by drought across the region within the berry formation and veraison growth phases of table grape before harvest. The most drought-affected years were 2018 and 2021. In 2018, 4785.03 ha, and in 2021, 1825.83 ha were extremely affected by drought. Moreover, the validation results indicated that the highest variability of table grape yield with SPI (r² = 0.62) was observed in June. However, table grape yield with SVI had the highest variation in July (r² = 0.60). The multiple linear regression between the average yield (ton/ha) and drought indices (SVI and SPI) showed the highest accuracy in June (r² = 0.79, MSE = 0.2) and July (r² = 0.71, MSE = 0.3). These findings suggest that SVI and SPI can be utilized for large-scale near-real-time drought monitoring and assessment to develop a regional subsidy program to support grape growers during a drought.

Partnerships between Non-Government Organizations (NGOs) and the local government are crucial to ensure optimal governance at the local level. In the last 2 decades in Bangladesh, NGOs have become essential actors in local development and governance. The present study investigated the role of NGOs for ensuring local governance in Bangladesh during the post-pandemic era. Periphery areas (two sub-districts) of the Natore District were selected for the field study. The qualitative analysis was mainly based on primary data. Four categories of respondents were targeted, namely NGOs (11), elected representatives and government officials (28), local elites (20) and general citizens (64) belonging to different genders, and educational and economic levels. In depth interviews, survey questionnaires and focus group discussions were used as the tools for collecting data from sampled respondents. Focus was placed on eleven issues including five development and administration related, five political and participation related, and management of the COVID-19 crisis. A qualitative matrix for the performance of NGOs on governance issues from the perspective of other actors in governance-local elected representatives and executive, local elites and general citizens was developed. The matrix revealed an optimistic story for NGO partnerships and social and governing issues such as women empowerment, disaster management, environment conservation, support during COVID-19 pandemic. On the other hand, indicators such as vote and election, people’s awareness, dispute resolution, local tax collection and budget making revealed that the NGOs need to work more with the local government to ensure participation in the processes of governance. The findings directly from the peripheral field were not only based on investigation of the NGOs but also included the perception of other actors of governance so these results can definitely contribute to national social policy reforms and revision of NGO strategies.