BRIAR: Biomass Retrieval in Ireland Using Active Remote Sensing (2014-CCRP-MS.17)

Abstract

Biomass Retrieval Using Active Remote Sensing Hedgerows are a very significant component of the Irish landscape. They perform multiple functions, acting as boundary markers, acting as stock-proof fencing, supporting bio-diversity and controlling run-off. They function as reservoirs of above-ground biomass and their potential as carbon sinks was explored in an earlier study which found that hedgerows potentially sequester 0.5–2.7tCO2 /ha/year. The earlier study used light detection and ranging (lidar) scanning to build 3D models of hedgerows to successfully estimate biomass, but at the time the cost–benefit of doing so was poor. However, this has since changed with the availability of free lidar sources and the reduced cost of commissioning/ acquiring lidar data. The purpose of the present study was to examine the use of another active remote sensing tool, imaging radar, to estimate biomass in hedgerows. The study area around Fermoy in County Cork was field surveyed using new drone technology to collect data on a sample of hedgerows from which estimates of biomass could be drawn. These field estimates were used with new high-resolution TerraSAR-X Staring Spotlight (TSX-SS) radar imagery to model hedgerows directly from radar backscatter. The study found that hedgerow biomass cannot be derived directly from radar backscatter. There were a number of reasons for this, such as the hedgerow biomass density, with an average of 10kg/m2 , being above the threshold of saturation for radar in the X-band frequency range. However, other radar sensors with lower frequencies, and thus higher saturation limits, do not have the spatial resolution to map hedgerows. An alternative method of investigating hedgerow structure, and thus inferring biomass, interferometry, is not successful as the level of coherence between the observations in our dataset was too low to build a 3D model (i.e. the backscatter from the hedgerow changed too much between observations). A new method that examines the cross-sectional response of the radar return across a hedgerow was shown to be successful at modelling the relationship between the width of the backscatter profile and the width of the hedgerow. However, this too was sensitive to the orientation of the hedgerow to the sensor. Therefore, this study shows that radar data does not seem to be an appropriate technology for estimating hedgerow properties in Ireland. In order to estimate the national stock of hedgerow, the new Prime2 spatial data storage model (OSI, 2014) was applied in conjunction with developed maps showing the probability of a field boundary being a stone wall or a hedgerow, to give a new national estimate for hedgerow length in Ireland of 689,000km. This estimate is double the frequently quoted figure of 300,000km because of a much wider definition of “hedgerow” used in this report. Net change in hedgerow length was examined using the aerial photographic records from 1995, 2005 and 2015, along with county-level survey records, showing that there has been a net removal of hedgerows between 1995 and 2015 of between 0.16% and 0.3% per annum, although the rate is much slower in the latter half of that period. As X-band radar seems to be inappropriate for hedgerow evaluation (especially for the obvious case of the identification of the complete removal of large hedgerows, for which it is much more expensive and time-consuming than the detection of hedgerow removal using aerial photography), the existing national lidar surveys from the Geological Survey of Ireland were examined for their appropriateness for hedgerow evaluation. A digital canopy model derived from these data successfully estimated heights (mean and maximum) in the trial test site, with an r 2 value of 0.79.