Michael Schmidt

Orcid: 0000-0001-5830-7935

Affiliations:
  • Remote Sensing Centre, Brisbane, QLD, Australia
  • University of Bonn, Department of Geography, Germany (PhD 2003)


According to our database1, Michael Schmidt authored at least 11 papers between 2010 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2019
A Decision Tree Approach for Spatially Interpolating Missing Land Cover Data and Classifying Satellite Images.
Remote. Sens., 2019

2018
Detection of Forest Disturbance With Spaceborne Repeat-Pass SAR Interferometry.
IEEE Trans. Geosci. Remote. Sens., 2018

Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees.
Remote. Sens., 2018

2017
LARGE-scale fine-resolution products of forest disturbance using new approaches from spacborne sar interferometry.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

2016
Integration of Optical and X-Band Radar Data for Pasture Biomass Estimation in an Open Savannah Woodland.
Remote. Sens., 2016

Forest Disturbance Mapping Using Dense Synthetic Landsat/MODIS Time-Series and Permutation-Based Disturbance Index Detection.
Remote. Sens., 2016

2015
Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa.
Remote. Sens., 2015

Definitions and Mapping of East African Wetlands: A Review.
Remote. Sens., 2015

Enhancing the Detectability of Clouds and Their Shadows in Multitemporal Dryland Landsat Imagery: Extending Fmask.
IEEE Geosci. Remote. Sens. Lett., 2015

On the relevance of radiometric normalization of dense Landsat time series for forest monitoring.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2010
Estimation of pasture biomass and soil-moisture using dual-polarimetric X and L band SAR - accuracy assessment with field data.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010


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