Forestry

June 3, 2016

Forestry

Forestry is New Zealand’s third largest export market. It contributes an annual gross income of around $5 billion, 3% of New Zealand’s GDP, and directly employs around 20,000 people (MPI, 2015). Because forestry blocks are usually large and on terrain that is difficult to access, remote sensing can provide data beyond what would be available through in situ sampling methods to provide useful information to support decision-making aimed at improving the efficiency of the New Zealand forestry industry. While the Parent Organisations for CSST have not yet established operational links to the forestry sector, CSST will aim to be active in this domain.

Space-based measurements that can serve the needs of this field of operation include:

  • Timber volume, basal area, diameter at breast height (DBH), and tree height can be estimated by SAR (Mette, et al., 2004; Rahlf et al., 2014).
  • Biomass, which is a proxy for forest carbon content, can also be estimated using SAR measurements correlated with multispectral data (Lu, 2006). Furthermore, GNSS-R techniques have recently shown promise in estimating forest biomass (Ferrazzoli et al., 2011). Estimates of forest carbon content can inform New Zealand’s reporting to the United Nations Framework Convention on Climate Change (UNFCCC) and provide data required by the Emissions Trading Scheme (ETS).
  • Space-based panchromatic imagery, NDVI and SAR can provide the data needed to assess damage and loss to forestry blocks following natural or manmade disasters (Koch et al., 2008).
  • Tree health, including vigor, stress and pest infestation, can be assessed using multispectral imagery, though the need for high resolution imagery has, to date, resulted in aerial imagery being the dominant source of data (Leckie et al., 2005; Ismail et al., 2007). The combination of space- based imagery and aerial imagery in a data assimilation algorithm would provide data products that capitalize on the advantages of both measurement systems.
  • Fire risk assessments can be informed by estimates of fuel type, loading, and moisture through measurements of NDVI, and through measurements with SAR and TIR sensors (Leblon., 2005). TIR measurements can also provide early detection of fires, and areas affected by fires can be quantified using optical and infrared measurements (San-Miguel-Ayanz, 2005).
  • Maps of plant type can be generated from measurements of NDVI and measurements from multispectral sensors (Koch et al., 2008). These maps can inform forestry owners and operators to determine ideal ETS Field Measurement Approach (FMA) Forest Classes.
  • Remote sensing also supports the management of forested National Parks where it can be used to determine damage caused by wind, fire, flood, erosion and pests, as well as estimating forest biomass and conservation status for The Department of Conservation.