Mapping deforestation with remote sensing – a case study from Indonesia

Remote sensing utilises satellites to scan the earth and produce maps that are of value to researchers1. The use of remote sensing to quantify environmental change is at the core of the research of Dr Mark Broich from UNSW, which was discussed in his seminar at UNSW. Dr Broich’s discussion focussed on tropical forest loss in Indonesia and Malaysia, and the use of remote sensing data to determine tree cover change2.

Mapping Global Forest Change

There has been rapid progression in the monitoring of humid tropical forests globally2. One example mentioned by Dr Broich is the “Global Forest Change” website produced by Hansen et al. (2013). This website allows the user to zoom into a particular area of the world and determine forest loss and gain from 2000-2012. Hansen et al. (2013) mention that Indonesia had a significant increase in annual forest lost from 2000-01 to 2011-12 (Figure 1). An example location on the website is Riau, Indonesia, which was described by Dr Broich as a deforestation hotspot.

Indonesia deforestation increase Figure 1: Annual forest loss in Indonesia from 2000 – 2012. Source: Hansen et al. (2013 p. 852)

 

Deforestation in Indonesia

Tropical forests are of high value as they provide many ecosystem goods and services1. Furthermore, deforestation and forest degradation is a large source of carbon dioxide emissions1 – putting stored carbon back into the atmosphere, which can have large implications for climate change. Dr Broich stated that 6.5% of forest cover loss in Indonesia is illegal, with approximately 14% occurring in clearing constricted regions. With such rapid forest lost occurring1, it is evident that monitoring deforestation is vital for not only reducing carbon dioxide emissions, but also reducing biodiversity loss.

  • Mapping deforestation

The use of high spatial resolution optical imagery for deforestation mapping in Indonesia has been a challenge in the past due to the persistent cloud cover over Indonesia1,2. However, as mentioned by Dr Broich, these challenges have been overcome. Remote sensing imagery was successfully used to determine the loss of tree cover from both sides of the Indonesian and Malaysian border1,2 (Figure 2). According to Broich et al. (2013), this allows cross border differences to be identified, which may be due to social, economic and political disparities between the two countries.

The study by Broich et al. (2013) found that Intact Forest Landscapes (IFL) was 27% of the study area on the Malaysian side compared to 55% on the Indonesian side. Broich et al. (2013) also found that Malaysian forest closest to the border was more intensively cleared than on the Indonesian side. They suggest that the remoteness of the Indonesian study area may be why it is not as extensively logged as Malaysia – that is, it is less likely to be cleared2. They further suggest that spatial data should be utilised to compare forest accessibility and deforestation to determine how likely an area will be utilised for logging2.

 malaysia indonesian border

Figure 2: Remote sensing data showing tree cover loss (in red) on the Malaysian/Indonesian border. Source: Broich et al. (2013, p. 5750).

 

Concluding thoughts

It may be unlikely that Indonesia will prioritise the conservation of lowland tropical landscapes due to economic demands and social pressures, even though conservation of tropical forests in Indonesia is greatly required3. Nonetheless, remote sensing is a useful technique in monitoring changes in tree cover in the highly diverse forests of Indonesia. This may assist in monitoring areas of high carbon output as well as determining future conservation actions.

References

  1. Broich, M. (2014, March 28). Remove sensing of vegetation cover change and dynamics. School of Biological, Earth and Environmental Science Seminar Series. Conducted from UNSW, Kensington, NSW.
  1. Broich, M., Hansen, M., Potapov, P., & Wimberly, M. (2013). Patterns of tree-cover loss along the Indonesia–Malaysia border on Borneo. International Journal of Remote Sensing, 34(16), 5748-5760. doi: 10.1080/01431161.2013.796099
  1. Gaveau, D. L., Kshatriya, M., Sheil, D., Sloan, S., Molidena, E., Wijaya, A., … & Meijaard, E. (2013). Reconciling forest conservation and logging in Indonesian Borneo. PloS one, 8(8), e69887. doi: 10.1371/journal.pone.0069887
  1. Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., … & Townshend, J. R. G. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), 850-853. doi:10.1126/science.1244693

 

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