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This paper is situated within the discussion of mega-urbanization, a particular urbanization process that entails a large-scale agglomeration. In this paper, our focus is on urbanization in Java, Indonesia’s most dynamic region. We add to the literature by investigating the change and prediction of the land use/land cover (LULC) of mega-urbanization in Java. This research uses a vector machine approach to support the classification of land cover change dynamics, cellular automata-Markov (CA Markov), and the Klassen typology technique. This paper indicates that major metropolitan areas are still expanding in terms of built-up areas, generating a larger urban agglomeration. However, attention should be also given to the urbanization process outside existing metropolis’ boundaries given that more than half of the built-up land coverage in Java is located in non-metropolitan areas. In terms of future direction, the projection results for 2032 show that the Conservative scenario can reduce and slow down the increase in built-up land on the island of Java. On the other hand, the Spatial Plan (RTRW) scenario facilitates a rapid increase in the LULC of built-up land from 2019. The urban spatial dynamics in Java raises challenges for urban and regional planning as the process is taking place across multiple administrative authorities.

The development policies implemented in Jambi Province, Indonesia, since the New Order era, have encouraged transformations in demography, regional paradigms, growth base sectors, and growth actors. This study aims to understand how the central government’s demographic policies and plantation development program have impacted regional land cover change, rural development transformation, and economic development in Sumatra Island’s biodiversity-rich rainforest region (Jambi Province). This study explores the shifts in village typology that have occurred. Descriptive analysis and cluster analysis were applied to collect data at the provincial level that included population, poverty rate, levels of education, HDI, GRDP, Gini index, and land cover. Village Potential Data at the village level was then used to build an infrastructure index and a diversity of activities index. The results of this study indicated that macro development indicators are in a positive trend: HDI, educational levels, GRDP per capita, and the proportion of the tertiary sector in GRDP have all increased. The growth of the tertiary sector was largely driven by the trade and motorized-vehicle repair sectors. The provincial landscape has changed significantly due to the expansion of oil palm plantations. At the village level, the infrastructure index and diversity index show an increase in the number of facilities and variations in economic activity in most villages. Some shifts in rural typology are highlighted: the increase in urban villages and in villages that specialize in oil palm plantation or other industrial plantation crops.