Asim Banskota

Monsanto (United States) — United States

Environmental Science · Physical Sciences

9h-index825citations14works0.02yr avg
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Research Topics

Remote Sensing in Agriculture(8), Remote Sensing and LiDAR Applications(7), Fire effects on ecosystems(4), Peatlands and Wetlands Ecology(3), Land Use and Ecosystem Services(2)

Publications14 total

Continuous Wavelet Analysis for Spectroscopic Determination of Subsurface Moisture and Water-Table Height in Northern Peatland Ecosystems
IEEE Transactions on Geoscience and Remote Sensing·2016· 20 cited
An LUT-Based Inversion of DART Model to Estimate Forest LAI from Hyperspectral Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing·2015· 55 cited
The Utility of Fire Radiative Energy for Understanding Fuel Consumption due to Wildfire in Boreal Peatlands
2014
Forest Monitoring Using Landsat Time Series Data: A Review
Canadian Journal of Remote Sensing·2014· 397 citedOpen Access
A Review of Methods for Mapping and Prediction of Inventory Attributes for Operational Forest Management
Forest Science·2014· 141 citedOpen Access
Forest monitoring using Landsat time-series data- A
2014
Characterizing wildfire in boreal peatlands using MODIS fire products
AGUFM·2013
Utility of the Wavelet Transform for LAI Estimation Using Hyperspectral Data
Photogrammetric Engineering & Remote Sensing·2013· 11 citedOpen Access
Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
Remote Sensing·2013· 45 citedOpen Access
Monitoring Wetland Change Using Inter-Annual Landsat Time-Series Data
Wetlands·2012· 92 cited
The discrete wavelet transform as a precursor to leaf area index estimation and species classification using airborne hyperspectral data
VTechWorks (Virginia Tech)·2011
Improving within-genus tree species discrimination using the discrete wavelet transform applied to airborne hyperspectral data
International Journal of Remote Sensing·2011· 39 cited
Synergistic use of very high-frequency radar and discrete-return lidar for estimating biomass in temperate hardwood and mixed forests
Annals of Forest Science·2011· 25 citedOpen Access
Predicting Biomass in Temperate Hardwood and Mixed Forests Using VHF Radar, Interferometric SAR and Discrete-Return Lidar Data
AGU Fall Meeting Abstracts·2008

Frequent Co-authors

Nilam Kayastha(8), Randolph H. Wynne(6), Michael J. Falkowski(5), Valerie A. Thomas(5), Robert E. Froese(3), Shawn Serbin(3), Philip A. Townsend(3), Evan S. Kane(3), Michael A. Wulder(2), Joanne C. White(2), Jean‐Philippe Gastellu‐Etchegorry(2), Karl M. Meingast(2), Laura Bourgeau‐Chavez(2), Mary Ellen Miller(2), Nancy H. F. French(2), M. J. Falkowski(2), Andrew Smith(2), Kimberley D. Brosofske(1), John M. Galbraith(1), Patrick D. Johnson(1)