In most cases estimates of emissions and removals associated with REDD+ activities will be made using a combination of remotely-sensed and ground based data.

Landsat satellites provide a time series of remotely sensed digital images spanning 40 years and are being used widely in monitoring activities such as deforestation, forest degradation and natural disturbances, and for estimating changes in biomass and carbon stocks.

Other types of remotely sensed data, such as SAR, LIDAR and high resolution optical data are increasingly available and helpful especially in extending the range of REDD+ activities for which operational methods are available.

Pre-processed data sets can be used as a basis for REDD+ estimation in conjunction with reference and auxiliary data to capture national circumstances.

Remotely sensed and auxiliary ground-based data in combination are likely to be useful for stratification in order to increase sampling efficiency.

If sufficient NFI data are available over space and time and at sufficient spatial resolution, NFIs can be used to estimate directly from repeated inventories stock changes associated with REDD+ activities. It will often be best to use NFIs in combination with remotely-sensed data.

Data from NFIs are also a potentially valuable source of information for REDD+ estimation using gain-loss methods, and for developing modelling approaches at Tier 3.

Detailed information generated at a fine scale at intensive monitoring sites can help address the difficulty of estimating stocks and stock changes for litter, dead wood and soil, by supporting development of model parameters, including emissions and removals factors.