Results 1 to 10 of about 42,095 (293)
A spectral method for spatial downscaling. [PDF]
Biometrics, 2014 SummaryComplex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrate model output with monitoring data to adjust for model biases and ...
Reich BJ, Chang HH, Foley KM.
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Time Varying Spatial Downscaling of Satellite-Based Drought Index [PDF]
Remote Sensing, 2021 Drought monitoring is essential to detect the presence of drought, and the comprehensive change of drought conditions on a regional or global scale. This study used satellite precipitation data from the Tropical Rainfall Measuring Mission (TRMM), but ...
Hone-Jay Chu +3 more
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Spatial downscaling of multivariate disease risk. [PDF]
Int J Health GeogrAbstract Downscaling areal health data to a finer resolution is important for understanding the intricate spatial patterns of disease. It helps to identify shared risk factors and to develop targeted public health interventions. This paper introduces Area-to-Area (ATA) and Area-to-Point (ATP) Poisson cokriging for downscaling spatial disease ...
Payares-Garcia D +3 more
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Statistical Learning-Based Spatial Downscaling Models for Precipitation Distribution
Advances in Meteorology, 2022 The downscaling technique produces high spatial resolution precipitation distribution in order to analyze impacts of climate change in data-scarce regions or local scales.
Yichen Wu +3 more
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Spatial downscaling of precipitation using adaptable random forests
Water Resources Research, 2016 This paper introduces Prec-DWARF (Precipitation Downscaling With Adaptable Random Forests), a novel machine-learning based method for statistical downscaling of precipitation. Prec-DWARF sets up a nonlinear relationship between precipitation at fine resolution and covariates at coarse/fine resolution, based on the advanced binary tree method known as ...
He, Xiaogang +3 more
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Downscaling spatial interaction with socioeconomic attributes
EPJ Data ScienceA variety of complex socioeconomic phenomena, for example, migration, commuting, and trade can be abstracted by spatial interaction networks, where nodes represent geographic locations and weighted edges convey the interaction and its strength.
Chengling Tang +6 more
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Intercomparison of Downscaling Techniques for Satellite Soil Moisture Products [PDF]
Advances in Meteorology, 2018 During recent decades, various downscaling methods of satellite soil moisture (SM) products, which incorporate geophysical variables such as land surface temperature and vegetation, have been studied for improving their spatial resolution.
Daeun Kim +4 more
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Spatial‐statistical downscaling with uncertainty quantification in biodiversity modelling
Methods in Ecology and EvolutionAccurate downscaling with uncertainty quantification and its inclusion in fitting biodiversity models to data are essential for accurate, valid inferences and predictions.
Xiaotian Zheng +4 more
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Spatial Downscaling of Alien Species Presences Using Machine Learning [PDF]
Frontiers in Earth Science, 2017 Spatially explicit assessments of alien species environmental and socio-economic impacts, and subsequent management interventions for their mitigation, require large scale, high-resolution data on species presence distribution.
Ioannis N. Daliakopoulos +3 more
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Applied Sciences, 2023 This paper compared the predictive performance of different regression models for trend component estimation in the spatial downscaling of coarse resolution satellite data using area-to-point regression kriging in the context of the sensitivity to input ...
Geun-Ho Kwak +2 more
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