Update on classification results

Time has flown and I’m into my final two weeks at the CIAT office. At the start of the week I had a discussion with the Terra-I team about the challenges and timeline for the national level cocoa classification, given my limited timeframe remaining. I’m hoping to get some cocoa probability maps from them this week.

From the trial runs carried out for the Lampung province, it has been found that the automatic classification system is working quite well at the lower probability end of the cocoa classification. However, at the other end of the scale (positive identification of cocoa), rubber and coffee plantations seem to be the most problematic confounding systems in this region. Coffee and rubber was identified as one of the four most likely confounding systems prior to starting the system training exercise. See figure below of the image interpretation key of the four confounding systems used in the supervised classification.

Continue reading “Update on classification results”

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: Allometric models

Following on from the last blog post, this post will look at another method for measuring aboveground biomass in forests is through the use of allometric models which relate tree dimensions to biomass. This is a good time to discuss this approach, since I’ve spent the past few days comparing allometric models used in two different regional carbon assessments of cocoa farms in Indonesia. Continue reading “Estimating aboveground carbon stock in forests: Allometric models”

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”