Remote-Sensing and Carbon Estimation – Arjan Wilkie

Title: Improved measurement and estimation of Biomass and Soil Carbon in diverse landscapes using high-resolution remote-sensing

Project Description

This project uses high-resolution remote-sensing data from satellite and aerial sensors to measure current biomass carbon and soil carbon levels, and to estimate future carbon sequestration potential. I am trying to answer the questions of how much carbon is actually there now, and how much more can these sites store in the future. The idea is to develop a method that can use some local on-ground measurements along with the latest remote-sensing datasets to produce a fine-scale whole-of-site measurement.  This will quantify within-paddock and within-farm variations of current carbon stocks, and will highlight the most productive areas for future carbon projects on these sites. This information will allow land managers to better understand the size of the opportunity to integrate carbon farming within their existing businesses, both as an extra revenue stream and to assist with the climate change mitigation effort.

Approach

Data fusion of remotely sensed LIDAR, radar, geophysical and multi-spectral and hyper-spectral optical datasets, integrated with field-based measurements, to produce a quantitative carbon model of both the above-ground biomass carbon and soil organic carbon, carbon pools. Local relationships between soil carbon levels in digital soil mapping soil units and remnant vegetation carbon levels will be used to infer the additional carbon sequestration potential of adjacent cleared land units.

Outcome

A general data fusion method and field sampling protocol, along with new quantitative datasets for current carbon stocks and carbon sequestration potential values highlighting prospective locations for carbon sequestration projects.

Users

Private land managers such as farmers, graziers and horticulturalists; as well as public land managers such as local, regional and state government agencies.