Ellen Mae C. Leonardo

An Assessment of High-Density UAV Point Clouds for the Measurement of Young Forestry Trials

Peter Massam, Grant D. Pearse, Michael S. Watt, 2020, Remote. Sens..

Use of advanced modelling methods to estimate radiata pine productivity indices

Michael S. Watt, Ellen Mae C. Leonardo, David J. Palmer, 2021 .

Application of remote sensing technologies to identify impacts of nutritional deficiencies on forests

Jonathan P. Dash, Grant D. Pearse, Ellen Mae C. Leonardo, 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

Comparison of TanDEM-X InSAR data and high-density ALS for the prediction of forest inventory attributes in plantation forests with steep terrain

Jonathan P. Dash, Grant D. Pearse, Henrik J. Persson, 2020 .

Monitoring biochemical limitations to photosynthesis in N and P-limited radiata pine using plant functional traits quantified from hyperspectral imagery

Grant D. Pearse, Ellen Mae C. Leonardo, Michael S. Watt, 2020 .

Using hyperspectral plant traits linked to photosynthetic efficiency to assess N and P partition

Ellen Mae C. Leonardo, Michael S. Watt, P. Zarco-Tejada, 2020 .

Long-term effects of water stress on hyperspectral remote sensing indicators in young radiata pine

Ellen Mae C. Leonardo, P. Zarco-Tejada, H. Buddenbaum, 2021, Forest Ecology and Management.

Prediction of the Severity of Dothistroma Needle Blight in Radiata Pine Using Plant Based Traits and Narrow Band Indices Derived from UAV Hyperspectral Imagery

Ellen Mae C. Leonardo, P. Zarco-Tejada, H. Buddenbaum, 2023, SSRN Electronic Journal.