Analyzing Links between Spatio-Temporal Metrics of Built-Up Areas and Socio-Economic Indicators on a Semi-Global Scale

Developing Relative Spatial Poverty Index Using Integrated Remote Sensing and Geospatial Big Data Approach: A Case Study of East Java, Indonesia

Poverty data are usually collected through on-the-ground household-based socioeconomic surveys. Unfortunately, data collection with such conventional methods is expensive, laborious, and time-consuming. Additional information that can describe poverty with better granularity in scope and at lower cost, taking less time to update, is needed to address the limitations of the currently existing official poverty data. Numerous studies have suggested that the poverty proxy indicators are related to economic spatial concentration, infrastructure distribution, land cover, air pollution, and accessibility. However, the existing studies that integrate these potentials by utilizing multi-source remote sensing and geospatial big data are still limited, especially for identifying granular poverty in East Java, Indonesia. Through analysis, we found that the variables that represent the poverty of East Java in 2020 are night-time light intensity (NTL), built-up index (BUI), sulfur dioxide (SO2), point-of-interest (POI) density, and POI distance. In this study, we built a relative spatial poverty index (RSPI) to indicate the spatial poverty distribution at 1.5 km × 1.5 km grids by overlaying those variables, using a multi-scenario weighted sum model. It was found that the use of multi-source remote sensing and big data overlays has good potential to identify poverty using the geographic approach. The obtained RSPI is strongly correlated (Pearson correlation coefficient = 0.71 (p-value = 5.97×10−7) and Spearman rank correlation coefficient = 0.77 (p-value = 1.58×10−8) to the official poverty data, with the best root mean square error (RMSE) of 3.18%. The evaluation of RSPI shows that areas with high RSPI scores are geographically deprived and tend to be sparsely populated with more inadequate accessibility, and vice versa. The advantage of RSPI is that it is better at identifying poverty from a geographical perspective; hence, it can be used to overcome spatial poverty traps.

A Socio-Spatial Analysis of Land Use Dynamics and Process of Land Intervention in the Peri-Urban Areas of Bahir Dar City

The contemporary urbanization and its implication to land use dynamics especially in the peri-urban areas are emerging as a cross-cutting theme in policy debates and scientific discourse. As most cities in developing countries, including Ethiopia, are experiencing continuous expansion of built-ups and dynamic land use changes, monitoring and an in-depth analysis of the past, present and future predictions of these changes are important for a holistic understanding of the problem, its consequence, and to regulate proper land use intervention options. Thus, the main objective of this research is to assess land use dynamics and processes of land intervention in the peri-urban areas of Bahir Dar city using a socio-spatial analysis. It assesses to what extent the existing peri-urban land intervention processes and land use decisions are effective in combating and controlling unwanted land use changes. Primary socio-economic data were collected using questionnaires, focus group discussions (FGDs) and key informant interviews; in addition, spatial data including Landsat and Sentinel imageries of 1993, 2001, 2011 and 2020 were utilized. Land use/land cover (LULC) classes were computed using the integration of spectral and object-based image classification techniques. The results signal that built-ups are expanding horizontally with unpredicted patterns. This is because the existing land intervention processes are lacking effectiveness to govern the spatial patterns of built-ups. The results further depict that processes of land use intervention do not only determine horizontal urban expansion but also determine the nature of people-to-land relationships, which involve both formal and informal processes. This creates haphazard, disputed and unregulated land use systems in peri-urban areas of Bahir Dar. The socio-spatial methodology applied in this research is effective in monitoring both the spatial and social dimensions of land use changes. The spatial results effectively demonstrate the dynamics of land uses; whereas, the social analysis supports understanding of the processes of land use interventions. In conclusion, monitoring processes of land use interventions are key policy and decision making directions to regulate and manage land use dynamics in the peri-urban area.