New publication on peat dome surface modelling based on ICESat-2 data in Remote Sensing
April 27, 2021
Satellitenbasiertes System quantifiziert Ökosystemleistungen des Waldes
August 9, 2021
The UN assembly recently declared 2021 – 2030 the decade for Ecosystem Restoration with the overall objective of removing up 26 gigatons of greenhouse gases from the atmosphere (UN Environment Programme, 2019). On the islands of Mindanao in the Philippines, Kennemer Eco Solutions (KenEco) is restoring and protecting forest formations comprising ~220,000 ha, with funds from USAID Green Invest Asia. Remote Sensing Solutions (RSS) provides technical support to implement a new Verified Carbon Standard (VCS) project in a community forest project area in eastern Mindanao. RSS was assessing past deforestation and associated drivers and predicts future deforestation locations until 2030. The project combines KenEco’s socio-ecological and forest carbon knowledge in the Philippines with RSS’s expertise on REDD+ Monitoring, Reporting and Verfication (MRV).
The partnership with USAID Green Invest Asia comes with technical assistance to set up the carbon credit scheme to attract private capital with the aim to reduce millions of tons of CO2 emission expected this decade. The project was carried out in accordance to the VM0007 REDD+ methodological framework of the Verified Carbon Standard (VCS). Specifically, a reliable and transparent proof of concept for accrediting certain sites under the VCS is required. These will help to credibly qualify carbon pools where deforestation is avoided, while also forest systems’ conservation is considered. REDD+ projects mainly aim at reducing carbon emissions from avoided deforestation and forest degradation, but multiple co-benefits can be achieved such as reducing biodiversity loss and increasing quality of life for local communities. After finishing the first project phase in April, which also included capacity development in the domain of Earth Observation and VCS-conformant data processing, KenEco is starting to implement the forest restoration project, based on the data-driven evidence of benefits such project can achieve.
