Improving Remote Species Identification through Efficient Training Data Collection

article

Improving Remote Species Identification through Efficient Training Data Collection is …
instance of (P31):
scholarly articleQ13442814

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P8978DBLP publication IDjournals/remotesensing/BaldeckA14
P356DOI10.3390/RS6042682

P50authorGreg AsnerQ23670497
P2093author name stringClaire Baldeck
P2860cites workLandscape-scale variation in plant community composition of an African savanna from airborne species mappingQ35123444
Canopy phylogenetic, chemical and spectral assembly in a lowland Amazonian forestQ38882130
Variability in leaf optical properties of Mesoamerican trees and the potential for species classification.Q38934694
The Divergence and Bhattacharyya Distance Measures in Signal SelectionQ56432487
Identification of Specific Tree Species in Ancient Semi-Natural Woodland from Digital Aerial Sensor ImageryQ56785409
Seasonal Variation in Spectral Signatures of Five Genera of Rainforest TreesQ56934144
Tree Species Discrimination in Tropical Forests Using Airborne Imaging SpectroscopyQ56934173
Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environmentQ56934218
Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR DataQ56934253
Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR systemQ56934258
Carnegie Airborne Observatory: in-flight fusion of hyperspectral imaging and waveform light detection and ranging for three-dimensional studies of ecosystemsQ56934687
Biophysical and Biochemical Sources of Variability in Canopy ReflectanceQ56935105
Tree Species Classification in Boreal Forests With Hyperspectral DataQ58395761
Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR dataQ58395766
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue4
P921main subjectdata collectionQ4929239
P304page(s)2682-2698
P577publication date2014-03-25
P1433published inRemote SensingQ16800644
P1476titleImproving Remote Species Identification through Efficient Training Data Collection
P478volume6

Reverse relations

cites work (P2860)
Q58471333Classification of Tree Species in a Diverse African Agroforestry Landscape Using Imaging Spectroscopy and Laser Scanning
Q39309903Drivers of woody canopy water content responses to drought in a Mediterranean-type ecosystem
Q56941313Forecasting climate change impacts on plant populations over large spatial extents
Q56962861Mapping an invasive bryophyte species using hyperspectral remote sensing data
Q39344851Multiscale mapping of species diversity under changed land use using imaging spectroscopy
Q35685743Operational Tree Species Mapping in a Diverse Tropical Forest with Airborne Imaging Spectroscopy.
Q58064249Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data