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SEMI AUTOMATED LAND COVER LAYER UPDATING PROCESS UTILIZING SPECTRAL ANALYSIS AND GIS DATA FUSION
NTDB (National Topographic Data Base), Segmentation, Classification, nDSM, data fusion
2018/5/11
Technological improvements made in recent years of mass data gathering and analyzing, influenced the traditional methods of updating and forming of the national topographic database. It has brought a ...
GRASSLAND NPP MONITORING BASED ON MULTI-SOURCE REMOTE SENSING DATA FUSION
Multi-source remote sensing Data fusion Net primary productivity Carnegie-Ames-Stanford Approach model
2018/5/11
Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycl...
MAPPING LAND COVER IN THE TAITA HILLS, SE KENYA, USING AIRBORNE LASER SCANNING AND IMAGING SPECTROSCOPY DATA FUSION
GEOBIA LCCS Hyperspectral data
2015/5/7
The Taita Hills, located in south-eastern Kenya, is one of the world’s biodiversity hotspots. Despite the recognized ecological importance of this region, the landscape has been heavily fragmented d...
Model–data fusion across ecosystems: from multisite optimizations to global simulations
Model–data fusion across ecosystems global simulations
2014/12/19
This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (...
Generalized Canonical Correlation Analysis for Disparate Data Fusion
Manifold matching canonical correlation analysis reduced rank regression efficiency,classification
2012/11/22
Manifold matching works to identify embeddings of multiple disparate data spaces into the same low-dimensional space, where joint inference can be pursued. It is an enabling methodology for fusion and...
Ensemble modelling of nitrogen fluxes: data fusion for a Swedish meso-scale catchment
Ensemble modelling nitrogen fluxes data fusion
2010/12/22
Model predictions of biogeochemical fluxes at the landscape scale are highly uncertain, both with respect to stochastic (parameter) and structural uncertainty. In this study 5 different models (LASCAM...
The combination of data obtained with different sensors (data fusion) is a powerful technique that can provide target products of the best quality in terms of precision and accuracy, as well as spatia...
Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments
data fusion fuzzy logic neural network hydrological modelling
2009/3/17
This paper evaluates six published data fusion strategies for hydrological forecasting based on two contrasting catchments: the River Ouse and the Upper River Wye. The input level and discharge estima...