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The adverse impacts of oil palm plantations on socio-ecological conditions in Indonesia are a prominent issue. While farming improvement in large-scale plantations has shown good progress, accelerated expansion coupled with low productivity of smallholder plantations has raised concerns. Smallholder plantations are rarely monitored, as they are small, scattered, fragmented, often located in remote areas, with irregular shapes, susceptible to rapid change, and commonly mixed with other commodities. Accordingly, the present study aimed to (1) develop a new model for mapping smallholder oil palms, (2) describe the spatial distribution of smallholder oil palms, and (3) identify their potential impact on the environment. An object detection model based on a deep-learning approach was applied to high-resolution satellite imagery from Google Earth, Pleiades, and GeoEye to detect individual oil palm trees. The results showed that the derived model is highly accurate and can successfully map smallholder plantations. Village-level maps showed that the spatial distribution of smallholder oil palms was strongly related to local socio-ecological dynamics, whereas regency-level maps showed that smallholder oil palms have largely encroached on conservation zones and forested areas. These findings highlight the urgency of smallholder oil palm spatial data for reaching sustainable global palm oil industries. • The expansion of low-productivity smallholder oil palm has raised concerns. • Lacking spatial data hinder efforts to improve smallholder oil palm farming. • Mapping small, scattered, and fragmented smallholder plantations is complicated. • Deep learning on high-resolution satellite images offered a new mapping approach. • OPTIMAL-IPB as a QGIS plugin was developed for mapping smallholder oil palm. [ABSTRACT FROM AUTHOR]

Peri-urban agriculture (PUA) has been proposed as an important urban element to deal with the challenges of increasing poverty, food insecurity, and environmental degradation as particularly found in rapidly expanding cities of the developing world. However, farming in the peri-urban is under strong pressure from urbanization. The economic and social roles of farming need to be better understood in order to integrate peri-urban agriculture into urban planning. This study used multivariate techniques and Geographically Weighted Regression to analyze statistical data at a village and sub-district, to explore the varying relationships between agricultural activities and urban economic activities, urban poverty and informality, as well as food security. This method was applied in the Jabodetabek Metropolitan Area (JMA) with Indonesia’s capital Jakarta at its core, and it resulted in some important findings. First , PUA was more associated with the increasing low and middle class residential areas and the growing small-middle scale urban economic activities rather than development of tourism and larger traditional market facilities. Second , whereas PUA in the North of JMA was under pressure by the increasing poverty, in the Southeast of JMA it has expanded concurrently with increasing poverty. Third , PUA is strengthened by increasing informal activities in the peri-urban zone that offer alternative jobs and additional income for the farmers. Fourth , PUA in the surroundings of Jakarta as well as in the East and Northeast of JMA has contributed to increasing food affordability as well as strengthening food security policy. Based on these results, recommendations to maintain the PUA have been formulated to support its role for the peri-urban economy, reduce poverty, manage informality, and increase food security. [ABSTRACT FROM AUTHOR]