Results 1 to 10 of about 10,908 (283)
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 Land Surface Temperature over Heterogeneous Regions Using Random Forest Regression Considering Spatial Features [PDF]
Remote Sensing, 2021 Land surface temperature (LST) is one of the crucial parameters in the physical processes of the Earth. Acquiring LST images with high spatial and temporal resolutions is currently difficult because of the technical restriction of satellite thermal ...
Kai Tang, Hongchun Zhu, Ping Ni
doaj +4 more sources
Geographically Weighted Area-to-Point Regression Kriging for Spatial Downscaling in Remote Sensing [PDF]
Remote Sensing, 2018 Spatial downscaling of remotely sensed products is one of the main ways to obtain earth observations at fine resolution. Area-to-point (ATP) geostatistical techniques, in which regular fine grids of remote sensing products are regarded as points, have ...
Yan Jin +4 more
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An Improved Approach for Downscaling Coarse-Resolution Thermal Data by Minimizing the Spatial Averaging Biases in Random Forest [PDF]
Remote Sensing, 2020 Land surface temperature (LST) plays a fundamental role in various geophysical processes at varying spatial and temporal scales. Satellite-based observations of LST provide a viable option for monitoring the spatial-temporal evolution of these processes.
Sammy M. Njuki +2 more
doaj +5 more sources
Downscaling spatial interaction with socioeconomic attributes [PDF]
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
doaj +3 more sources
Spatial downscaling of precipitation using adaptable random forests [PDF]
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 ...
Nathaniel Chaney +2 more
exaly +6 more sources
Step-By-Step Downscaling of Land Surface Temperature Considering Urban Spatial Morphological Parameters [PDF]
Remote Sensing, 2022 Land surface temperature (LST) is one of the most important parameters in urban thermal environmental studies. Compared to natural surfaces, the surface of urban areas is more complex, and the spatial variability of LST is higher.
Xiangyu Li +3 more
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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 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 ...
Payares-Garcia D +3 more
europepmc +3 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Land surface temperature (LST) is a key parameter in numerous thermal environmental studies. Due to technical constraints, satellite thermal sensors are unable to supply thermal infrared images with simultaneous high spatial and temporal resolution.
Shumin Wang, Xiaobo Luo, Yidong Peng
doaj +3 more sources