Remote sensing has become a major tool for applications to forest ecology and management. Forests cover nearly one third of the Earth’s land area and play a key role in carbon sequestration and climate control. Therefore, it is important to map the status of forests and monitor any changes that may take place.

Remotely sensed images provide continuous information, are available almost everywhere often with different pixel sizes and at different moments in time, can be easily integrated with other spatial datasets, are inexpensive and are often available as image data and derived data products (Lechner et al. 2020). Remote-sensing systems are available at a wide range of sensors and platforms. The most common sensor used is a passive optical imaging system which collect reflected sunlight or emitted thermal energy. They can be multispectral (some broader bands) and hyperspectral (hundreds of narrow bands). Sentinel-2 is a multispectral system consisting of two satellites launched in 2015 and 2017 each hosting the MSI sensor (Multi-Spectral Instrument) with 10-60 m pixels size. CHIME (Copernicus Hyperspectral Imaging Mission) is a concept for a hyperspectral instrument with 30 m pixel size and will eventually be launched in 2028. Other passive optical systems comprise Landsat 8/9, SPOT 7, PROBA-V, DEIMOS-2 (0.75-3.0 m pixels), EnMAP (30 m pixels, 230 bands, launch 2022), and many more. A sensor that will be able to measure photosynthetic activity from space will be FLEX carrying the FLORIS sensor (Fluorescence Imaging Spectrometer, launch 2023).

Active systems are synthetic aperture radar (SAR) and light detecting and ranging (LiDAR); they emit a pulse and measure the backscatter reflected back to the sensor. SAR sensors can differentiate surface roughness, canopy structure, and water content. LIDARs can measure the canopy height and can be used to create 3D surface models. Important SAR systems are Sentinel-1 (two satellites launched in 2014 and 2016 carrying C-Band instruments, 5 m pixel site) and BIOMASS (P-Band, 200 m pixels size, launch 2022).

Key forest domains (and variables) that can be mapped using remote sensing systems are (Lechner et al. 2020): forest cover (tree species, tree age class, tree density, vegetation health), vegetation structure (leaf area index, above-ground biomass, tree height, basal area), vegetation chemistry (foliar chemistry, fraction of absorbed photosynthetically active radiation, moisture content), biodiversity, disturbance and soil. In forest management, remote sensing is an invaluable tool for producing inventories and for estimating timber volume. Further applications are related to management of watersheds, wildlife, biodiversity, recreation, etc. (Jones and Vaughan 2010).

Further reading:

Lechner, A.M., Foody, G.M., Boyd, D.S.: Applications in Remote Sensing of Forest Ecology and Management, One Earth 2, May 22, 2020.

Jones, H.G. and Vaughan, R.H. 2010, Remote sensing of vegetation. Oxford University Press.