Results 41 to 50 of about 10,908 (283)
Representing uncertainty in continental-scale gridded precipitation fields for agrometeorological modeling [PDF]
, 2008 This work proposes a relatively simple methodology for creating ensembles of precipitation inputs that are consistent with the spatial and temporal scale necessary for regional crop modeling.
Wit, A.J.W., de +2 more
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PreciPatch: A Dictionary-based Precipitation Downscaling Method
Remote Sensing, 2020 Climate and weather data such as precipitation derived from Global Climate Models (GCMs) and satellite observations are essential for the global and local hydrological assessment.
Mengchao Xu +8 more
doaj +1 more source
Advances in Meteorology, 2017 Various downscaling approaches have been developed to overcome the limitation of the coarse spatial resolution of general circulation models (GCMs). Such techniques can be grouped into two approaches of dynamical and statistical downscaling.
Yoo-Bin Yhang, Soo-Jin Sohn, Il-Won Jung
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Sensors, 2019 Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/
Hao Sun, Baichi Zhou, Hongxing Liu
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Distance in spatial interpolation of daily rain gauge data [PDF]
, 2005 Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. The spatial density of available data sites is often changing with time.
Ahrens, B., Ahrens, Bodo
core +1 more source
Downscaling MODIS spectral bands using deep learning
GIScience & Remote Sensing, 2021 MODIS sensors are widely used in a broad range of environmental studies, many of which involve joint analysis of multiple MODIS spectral bands acquired at disparate spatial resolutions.
Rohit Mukherjee, Desheng Liu
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Remote Sensing, 2022 Remote sensing images of nighttime lights (NTL) were successfully used at global and regional scales for various applications, including studies on population, politics, economics, and environmental protection.
Shangqin Liu +7 more
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Remote Sensing, 2021 Land surface temperature (LST) is a vital physical parameter in geoscience research and plays a prominent role in surface and atmosphere interaction. Due to technical restrictions, the spatiotemporal resolution of satellite remote sensing LST data is ...
Shumin Wang +6 more
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Efficient Hybrid DCT-Domain Algorithm for Video Spatial Downscaling [PDF]
EURASIP Journal on Advances in Signal Processing, 2007 A highly efficient video downscaling algorithm for any arbitrary integer scaling factor performed in a hybrid pixel transform domain is proposed. This algorithm receives the encoded DCT coefficient blocks of the input video sequence and efficiently computes the DCT coefficients of the scaled video stream.
Nuno Roma, Leonel Sousa
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Spatial Downscaling of Vegetation Productivity in the Forest From Deep Learning
IEEE Access, 2022 Accurately estimating vegetation productivity in the forest areas is important for studying the terrestrial ecosystem and carbon cycles. Global LAnd Surface Satellite (GLASS) vegetation production datasets provide new long-term basic products of gross primary production (GPP) and net primary production (NPP) for monitoring the issues related with ...
Tao Yu +3 more
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