Results 11 to 20 of about 41,752 (176)

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, Zhihua Zhang, M. James C. Crabbe, Lipon Chandra Das   +3 more
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Downscaling spatial interaction with socioeconomic attributes

EPJ Data Science
A 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, Lei Dong, Hao Guo, Xuechen Wang, Xiao-Jian Chen, Quanhua Dong, Yu Liu   +6 more
doaj   +2 more sources

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.
europepmc   +4 more sources

Spatial‐statistical downscaling with uncertainty quantification in biodiversity modelling

Methods in Ecology and Evolution
Accurate downscaling with uncertainty quantification and its inclusion in fitting biodiversity models to data are essential for accurate, valid inferences and predictions.
Xiaotian Zheng, Noel Cressie, David A. Clarke, Melodie A. McGeoch, Andrew Zammit‐Mangion   +4 more
doaj   +2 more sources

Spatial downscaling of multivariate disease risk. [PDF]

Int J Health Geogr
Abstract 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, Osei F, Mateu J, Stein A.   +3 more
europepmc   +2 more sources

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, Ioannis N. Daliakopoulos, Stelios Katsanevakis, Aristides Moustakas   +3 more
doaj   +2 more sources

Blocks-removed spatial unmixing for downscaling MODIS images [PDF]

Remote Sensing of Environment, 2021
Abstract The Terra/Aqua MODerate resolution Imaging Spectroradiometer (MODIS) data have been used widely for global monitoring of the Earth's surface due to their daily fine temporal resolution. The spatial resolution of MODIS time-series (i.e., 500 m), however, is too coarse for local monitoring.
Wang, Q., Peng, K., Tang, Y., Tong, X., Atkinson, P.M.   +4 more
openaire   +2 more sources

Downscaling species occupancy from coarse spatial scales [PDF]

Ecological Applications, 2012
The measurement and prediction of species' populations at different spatial scales is crucial to spatial ecology as well as conservation biology. An efficient yet challenging goal to achieve such population estimates consists of recording empirical species' presence and absence at a specific regional scale and then trying to predict occupancies at ...
Azaele, Sandro, Cornell, Stephen J., Kunin, William E.   +2 more
openaire   +4 more sources

Residential electricity demand projections for Italy: A spatial downscaling approach [PDF]

Energy Policy, 2022
This work projects future residential electricity demand in Italy at the local (1 km grid) level based on population, land use, socio-economic and climate scenarios for the year 2050. A two-step approach is employed. In the first step, a grid-level model is estimated to explain land use as a function of socio-economic and demographic variables.
Massimiliano Rizzati, Enrica De Cian, Gianni Guastella, Malcolm N. Mistry, Stefano Pareglio   +4 more
openaire   +3 more sources

Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example [PDF]

Hydrology and Earth System Sciences, 2015
Soil moisture retrieved from satellite microwave remote sensing normally has spatial resolution on the order of tens of kilometers, which are too coarse for many regional hydrological applications such as agriculture monitoring and drought prediction ...
J. Peng, J. Niesel, A. Loew
doaj   +1 more source