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Remote sensing is a potentially powerful technology with which to extrapolate eddy covariance-based gross primary production (GPP) to continental scales. In support of this concept, we used meteorological and flux data from the AmeriFlux network and Support Vector Machine (SVM), an inductive machine learning technique, to develop and apply a predictive GPP(More)
Application of remote sensing data to extrapolate evapotranspiration (ET) measured at eddy covariance flux towers is a potentially powerful method to estimate continental-scale ET. In support of this concept, we used meteorological and flux data from the AmeriFlux network and an inductive machine learning technique called support vector machine (SVM) to(More)
When clusters with different densities and noise lie in a spatial point set, the major obstacle to classifying these data is the determination of the thresholds for classification, which may form a series of bins for allocating each point to different clusters. Much of the previous work has adopted a model-based approach, but is either incapable of(More)
a r t i c l e i n f o Keywords: Multi-scale digital terrain analysis Feature selection Spatial data mining Digital soil mapping ANOVA Principal components analysis Random subsets Decision trees Terrain attributes are the most widely used predictors in digital soil mapping. Nevertheless, discussion of techniques for addressing scale issues and feature(More)
Running head: Adaptive approach to selecting flow partition exponent for multiple flow direction determination 3 Acknowledgements: the University of Wisconsin-Madison is also appreciated. Abstract Most Multiple Flow Direction algorithms (MFD) use a flow partition coefficient (exponent) to determine the fractions draining to all downslope neighbors. The(More)
When two spatial point processes are overlaid, the one with the higher rate is shown as clustered points, and the other one with the lower rate is often perceived to be background. Usually, we consider the clustered points as feature and the background as noise. Revealing these point clusters allows us to further examine and understand the spatial point(More)
Terrain attributes derived from digital elevation models have been used widely for mapping soil organic matter (SOM). Among these attributes, the topographic wetness index (TWI), an index for quantitatively indicating the balance between water accumulation and drainage conditions at the local scale, has been shown to correlate with SOM. However, TWIs used(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o Transition between slope positions (e.g., ridge,(More)
Input/output (I/O) of geospatial raster data often becomes the bottleneck of parallel geospatial processing due to the large data size and diverse formats of raster data. The open-source Geospatial Data Abstraction Library (GDAL), which has been widely used to access diverse formats of geospatial raster data, has been applied recently to parallel geospatial(More)