Drivers of Deforestation in Indonesia

Updated 2026-11-02 · 4 min read · By the akar.earth specialist team

Drivers of deforestation in Indonesia explained: plantations, smallholder farming, logging, mining, fire and infrastructure, and how projects analyse drivers.

Deforestation in Indonesia has been driven mainly by industrial oil palm and pulpwood plantations, smallholder agriculture, logging that opens forests to later conversion, mining, fires on drained peat, and new roads and settlements, with the mix varying by province and over time. Understanding the local drivers is the foundation for any REDD+ baseline, intervention plan, leakage analysis or EUDR risk assessment.

The main drivers

The relative weight of these drivers has shifted. Industrial plantation expansion dominated earlier decades; more recent analyses point to a growing role for smallholders, mining (including nickel for batteries in Sulawesi and Maluku) and new frontiers in Papua. Use current data for your area rather than national averages.

Underlying causes

Direct drivers sit on top of deeper causes:

• Commodity demand and prices, domestic and export.
• Land tenure and spatial planning: overlapping claims, unclear boundaries between forest estate and other land.
• Governance: permits, enforcement, local politics.
• Peat drainage, which makes land flammable.
• Livelihood needs where farm incomes are low.

Policy responses

Indonesia has introduced a permanent moratorium on new permits in primary natural forest and peatland, peat restoration programmes after the 2015 fires, social forestry programmes, and stricter fire controls. See primary forest moratorium and peat restoration rules. Market measures, such as zero-deforestation company commitments, certification and the EUDR, also act on commodity-driven loss. See EUDR and palm oil.

How to analyse drivers for a project

1. Map historical loss in and around the project with Landsat-based loss data and recent alerts. See deforestation alerts.
2. Attribute loss to drivers using plantation and concession maps, mining permits, road data and high-resolution imagery.
3. Talk to people. Village interviews reveal who clears, why and where.
4. Identify agents and pressure points: companies, smallholders, migrants, local elites.
5. Project future pressure, considering new roads, permits and prices.
6. Design interventions that address each driver: livelihoods, tenure security, patrols, fire prevention, agreements with companies.
7. Assess leakage: where would displaced activity go?

The driver analysis feeds baseline setting and leakage accounting.

Drivers differ by island

National patterns hide strong regional contrasts. In Sumatra, much lowland forest has already been converted, and remaining pressures sit at forest edges, on peat and in protected areas. In Kalimantan, plantations, coal mining and fire on peat remain important. In Sulawesi and Maluku, nickel mining and smallholder cocoa and clove expansion stand out in recent years. In Papua, large plantation and food estate permits, logging and new roads put pressure on some of Indonesia’s largest intact forests. Java and Bali have little natural forest left, and pressures there are about land-use change in remaining fragments and agroforestry. Province pages, such as Riau, give local context.

Common mistakes

• Citing national driver statistics instead of local evidence.
• Assuming “smallholders” are one group; migrant and local farmers behave differently.
• Ignoring legal clearing within permits, which projects cannot always stop.
• Interventions that do not match the drivers, for example patrols where the driver is a permitted plantation.
• Forgetting fire as a driver of loss and reversals.

What good evidence looks like

A VVB and buyer will expect: loss maps with sources and dates; a driver attribution method and results; concession and permit overlays; interview records; a clear link from drivers to interventions and monitoring indicators; and a leakage analysis. Under jurisdictional approaches, show consistency with provincial data.

Relevance beyond carbon

Driver analysis is also the core of EUDR risk assessment for palm oil, rubber, cocoa, coffee and wood sourced from Indonesia. The same maps and field knowledge help both. See one dataset for carbon and EUDR.

Peat and fire deserve their own analysis; see peatland REDD+. Our feasibility and eligibility service includes driver analysis. More on the REDD+ hub.