After decentralization, there was massive development in Jakarta megacity’s outer suburbs (JMOS), especially in Bekasi and Tangerang regencies, marked by large-scale industrial estate/park (LSIEP) and followed by new town developments. However, this process led to the emergence of “chaotic” urban-rural land patterns. This study sought to identify the extent to which LSIEP development has affected rural-urban land transformation (RULT). The primary data were land use/cover (LUC) data from 2005, 2015, and 2020 and the LSIEP distributions. The methods applied are the Patch-generating Land Use Simulation (PLUS) model for 2025’s LUC prediction and the RULT index approach, RULT index development using the analytical hierarchy process. These combined approaches were novel in Indonesia, which usually relies on Cellular Automata (CA)-Markov, overlay (spatial), and descriptive statistics analyses to describe the RULT phenomenon. It was found that the villages located around the LSIEP close to the Jakarta megacity toll road network and those adjacent to the municipality (city) had been transformed into urban areas, while villages far from those locations were still rural. This study’s results help clarify the rural to urban transformation in Jakarta megacity’s outer suburbs and could be used as input for spatial planning policy.

Suburbanization of Bekasi Regency as a part of the Jakarta Metropolitan Area (JMA) is mainly induced by urban expansion and industrialization, in which the suburbanization process threatens food security and ultimately disrupts urban sustainability. This study aims to characterize industrial-dominated suburban formation to manage the suburbanization process using a quantitative zoning method. In assessing the characteristics of industrially dominated suburban, this research utilizes the concept of urban–rural development (URD), which consists of five aspects of development (socioeconomic, population, industrial, land-use, and environmental). Factor analysis and Rustiadi’s spatial clustering form regional clusters using all variables while referring to the URD concept. The results showed that there are three regional typologies: (i) urban, (ii) Desakota, and (iii) rural regions. Urban regions are situated in the central and western parts of Bekasi Regency, rural regions are situated in the northern part of Bekasi Regency, while the desakota region is situated between urban and rural regions. Characteristics of each typology then could be used as the basis for development policy in Bekasi Regency which is then constructed towards the protection of agricultural areas in the rural and desakota regions, serving both food security function and strengthening urban sustainability of JMA.

Although uneven regional development has long been an issue in Java, most parts of the territory experienced an increased level of development over the last two decades. Due to the variance in local background and spatial heterogeneity, the driving factors of the development level should, theoretically, vary over space. Therefore, in this study, we aim to investigate the local factors that influence the development level of Java’s regions. We used the spatiotemporal pattern analysis, ordinary least squares (OLS) regression, and geographically weighted regression (GWR), utilizing the regional development index as the predicted variable, and the social level, economy, infrastructure, land use, and environmental barriers as predictors. As per our results, it was found that the level of development in Java has improved over the past two decades. Metropolitan areas continued to lead this improvement. All the predictors that we examined significantly affected regional development. However, the spatial pattern of the local regression coefficients of Human Development Index (HDI), landslide, paddy conversion, and crime shifted due to changes in the spatial concentration of development activities.

The Jakarta metropolitan region (the Jakarta megacity), located in the fourth most populous country in the world (Indonesia), is the largest urban agglomeration in the Global South—continues to grow, especially in its outer suburbs (Bekasi Regency). The governments (Central and Local) tend to implement an urban-biased policy (UBP) to connect Bekasi Regency into global production networks and boost Bekasi Regency’s income. However, previous case studies of China and Vietnam have revealed that the UBP increases economic disparities between urban and rural areas. Therefore, this study probes urban–rural economic disparities and their characteristics at a microregional level (desa/kelurahan) in the Bekasi Regency. The methods applied in this study are geographically weighted regression (GWR), RULT index, and quantitative zoning. The results show that almost all desa/kelurahan in the high poverty (HPv) cluster are rural neighborhoods (desa/kelurahan with rural characteristics). By contrast, only 5% of desa/kelurahan with urban characteristics are HPvs, while the remainder are in the low poverty (LPv) cluster. Rural neighborhoods with HPv tend to have a high percentage of households dependent on agriculture. Thus, empirical results (with a case of a Global South megacity suburb) further support previous evidence that the UBP has caused urban–rural economic disparities.

Jakarta–Bandung Mega Urban Region (JBMUR), located in the western part of Java Island, Indonesia, is experiencing rapid regional development which can be observed from its increase in population density, massive changes of land-use from agricultural land into built-up area, rapid development of infrastructure and facilities, and advances in economic activities. Unfortunately, problems related to sustainability emerge along with this rapid regional development, primarily in decrease in environmental quality and social performance, leading to unsustainable development. This study aims: (1) to develop indicators promoting sustainable development at the subdistrict level, named the local sustainability index (LSI), utilizing factor analysis; (2) to observe local-scale spatial interdependency by employing local indicator of spatial association (LISA) statistics; and (3) to identify regional clusters based on LSI scores using K-means clustering method. Our LISA results show that spatial interdependency of local sustainability performances exists between local-scale spatial units: the LSI of a subdistrict is influenced by the sustainability state of the surrounding areas. Meanwhile, the clustering results show that most subdistricts in JBMUR are categorized as members of cluster 1 with low LSI values in economic and social dimensions but moderate in environmental dimensions.

Komering Watershed has experienced degradation in the quality of environment and ecosystems. This ecosystem and environmental degradation is due to significant deforestation and land conversion in upstream and central areas. Land conversion which led to erosion in the upstream and sedimentation in the downstream causing changes in river channel. This study aims to analyze the deformation (morphodynamics) of river channel of Komering River in 1990, 1997, 2000, 2010 and 2013. The occurred changes are identified using satellite image interpretation and calculation from sinuosity index based on changes in river channel. Satellite image data are obtained from multitemporal Landsat images to identify changes in the river channel, while sinuosity index is used as an indicator of changes in the river channel. The results of this study showed that during 26 years period (1990 - 2016), the channel of Komering River changes in eleven locations. There are five locations that indicate tendencies to be straight and six locations show tendencies to get curved. This conclusion is based on the calculation of the sinuosity index value due to changes in land cover.