Estimating aboveground carbon stock in forests: Remote sensing

Following on from the last few blog posts, a third technique for estimating aboveground carbon stocks is through remote sensing. Remote sensing has relevance for my project since we are using it to identify cocoa farm typologies at a large (national) scale and I will indirectly use it to classify the carbon stock of those typologies.

Remote sensing and satellite imagery techniques can cover large ages and can be used for landscape classification when combined with secondary spatial information. Broad forest types at the landscape level and even tree dimensions at the plot level can be estimated which can then be converted into biomass using statistical relationships (Brown, 1997; Chave et al., 2005; Saatchi et al., 2011). Remote sensing techniques can broadly be grouped into categories of optical sensing, high-resolution satellite imagery, microwave or radar, and LiDAR. Continue reading “Estimating aboveground carbon stock in forests: Remote sensing”

Estimating aboveground carbon stock in forests: Biome approach

The aim of this post is to introduce the various methods that have evolved to measure forest carbon stocks and focus on one of the most commonly used high level methods. Subsequent posts will focus on other methods.

Importance of measurement

Forests are of global importance because of their biodiversity and the carbon they sequester. A reservoir or system which has the capacity to accumulate or release carbon is known as a “pool” (FAO, 2016). In the context of forests it refers to the amount of carbon stored in the world’s forest ecosystem, mainly in living biomass and soil, but to a lesser extent also in dead wood and litter. Continue reading “Estimating aboveground carbon stock in forests: Biome approach”