RESTORE+: Addressing Landscape Restoration on Degraded Land in Indonesia and Brazil

The project aims to deliver mapping technologies to help key actors in Brazil and Indonesia access high-quality data in planning, mobilizing funds, and implementing efforts to avoid deforestation and restore degraded forests and landscapes. Although crucial for many activities, the availability and accessibility of map data are often limited. This limitation hampers detailed planning of forest and landscape restoration, as well as mobilization of financial and institutional resources that require baseline setting and monitoring of results. In the context of avoiding deforestation, data limitation will also result in limited ability to participate in markets that incentivize/enforce sustainable practices. Additionally, the project will also derive insights for national policies and long-term strategies to further demonstrate the multiplier effect of high-quality map data towards increased capacity for delivering land use sustainability.

Project data

Countries: Brazil, Indonesia
IKI funding: 12,498,171.00 €
Duration: 03/2017 till 06/2028
Status: open
Implementing organisation: International Institute for Applied Systems Analysis (IIASA)
Political Partner: Brazilian Cooperation Agency (ABC)

National Research and Innovation Agency (BRIN)
Implementing Partner: SELPER Brazil

World Agroforestry Center (ICRAF)
Online: http://www.restoreplus.org/

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State of implementation/results

As the second phase of the project has only started in the last quarter of 2024, results in both Indonesia and Brazil are limited to preliminary or intermediate processes from preparatory activities.
In late November 2024, the project team in Indonesia kick-started the development of adaptive landscape mapping technology, introduced as Evolving Participatory Information System for Nature-based Climate Solutions (Epistem), through drafting functional specification document specifying potential functionality and early descriptions of archetype users.
Furthermore, the project team revisited and enhanced the semi-automatic land use land cover mapping algorithm from the first phase of the RESTORE+ project. Focus was given to mapping features to ensure scalability and replicability across different landscapes with the most updated satellite imagery.
Nine diverse target groups were identified, including (local) government agencies, local Civil Society Organizations (CSOs), and the private sectors, representing potential user archetypes. Following this, early consultation has been conducted in South Sumatra in February 2025 to inform the development of mock-ups and communication tools aimed at clearly conveying the objectives of the 2nd phase of the project to stakeholders and potential co-development partners of the landscape monitoring technology.
The above preparatory work (i.e., preliminary functional specification, pilot consultation with preliminary target groups, and mock-up development) is aimed at effective kick-off communication/engagement that will be held in April 2025.
In Brazil, development and testing have been ongoing for the software required to estimate the Rural Environmental Registry (CAR) based on the data currently available. The team is working to improve the first version of the geospatial database associated to CAR, so that it will be as complete as possible when delivered to the stakeholders in late 2025.
On the topic of deforestation mapping, current activities cover the design, development, testing, and documentation of version 1.5.2 of the open-source SITS software. Following requests from National Institute for Space Research (INPE), this version has many improvements, including the capability of merging Sentinel-1 SAR with Sentinel-2 optical satellite data for increased classification accuracy. The version has been certified by INPE to be used operationally by its team.
Another important result was the production of a report comparing the accuracy of SITS-based deforestation classification with the current Satellite Monitoring Project for Deforestation in the Legal Amazon (PRODES) baseline. SITS reached an accuracy of 95% relative to PRODES in a case study in the state of Rondonia.

Latest Update:
04/2025