Jock A. Blackard

Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables

Jock A. Blackard, Denis J. Dean · Computers and Electronics in Agriculture · 1999 · 491 citations

Data Classification, Classification Method, Image Analysis +11

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

Jock A. Blackard, Mark Finco, Eileen H. Helmer et al. · Remote Sensing of Environment · 2007 · 446 citations

Moderate Resolution Information, Engineering, U.s. Forest Biomass +10

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

Gretchen G. Moisen, Jock A. Blackard, Tracey S. Frescino et al. · Ecological Modelling · 2006 · 274 citations

Additive Models, Basal Area, Forestry +5

Conterminous U.S. and Alaska Forest Type Mapping Using Forest Inventory and Analysis Data

Bonnie Ruefenacht, Mark Finco, Mark D. Nelson et al. · Photogrammetric Engineering & Remote Sensing · 2008 · 243 citations · Full text

Engineering, Forest Biometrics, Land Use +17

Remote sensing‐based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

Niklaus E. Zimmermann, Thomas C. Edwards, Gretchen G. Moisen et al. · Journal of Applied Ecology · 2007 · 202 citations · Full text