False-color composite, Valley and Ridge, south-central PA

Latest publications:

Gaertner, B., N. Zegre, T.A. Warner, R. Fernandez; Y. He, and E. Merriam, 2019. Contribution of Growing Season Length to Water Cycle Intensification: Implications for Long Term Forest Evapotranspiration in the central Appalachian Mountains, USA. Science of the Total Environment 650: 1371-1381. DOI: 10.1016/j.scitotenv.2018.09.129

Li, J., T.A. Warner, Y. Wang; J. Bai; and A. Bao, 2019. Mapping Glacial Lakes Partially Obscured by Mountain Shadow for Time Series and Regional Mapping Applications. International Journal of Remote Sensing, DOI: 10.1080/01431161.2018.1433343

Maxwell, A.E., M.P. Strager, T.A. Warner, C.A. Ramezan, A.N. Morgan, and C.E. Pauley, 2019. Large-Area, High Spatial Resolution Land Cover Mapping using Random Forests, GEOBIA, and NAIP Orthophotography: Findings and Recommendations. Remote Sensing 11, 1409. DOI: 10.3390/rs11121409

Maxwell, A., and T.A. Warner, 2019. Is high spatial resolution DEM data necessary for mapping palustrine wetlands? International Journal of Remote Sensing. 40(1): 118-137. DOI: 10.1080/01431161.2018.1506184

Ramezan, C.A., T.A Warner and A.E. Maxwell, 2019. Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Classification. Remote Sensing 11, 185. DOI: 10.3390/rs11020185

Warner, T. A., 2019. How to write an effective peer-review report: an editor’s perspective. International Journal of Remote Sensing. 40(13): 4871-4875. DOI: 10.1080/01431161.2019.1596342

Remote Sensing in the Geology and Geography Department at WVU

grape juice

Remote sensing is an exciting field of study, especially with the current interest in lidar, high spatial resolution imagery, and object-oriented analysis.   In the Department of Geology and Geography at WVU, remote sensing is part of a core emphasis on Geographic Information Science (GISc).    

My research interests include the spatial properties of remotely sensed images, lidar, high spatial resolution imagery, thermal imagery, machine learning classification, wildfire mapping, and information literacy. I have a particular interest in the use of remote sensing for promoting transparency and non-proliferation 

My students are working on:

  • The role of sample selection in affecting classification;
  • Mapping shurbland in the Eastern US; and
  • Using lidar to map butterfly habitat.
  • A list of past students is available here.

    Recently the Cooperative Ecosystems Studies Units (CESU) highlighted training in remote sensing that I periodically help provide to the US Natural Resources Conservation Service (NRCS).

    I occasionally run workshops on how to write and publish remote sensing papers.