Trustworthy remote sensing interpretation: Concepts, technologies, and applications
Geographic spaces is a vast and complex system involving multiple elements and nonlinear
interactions of these elements, and rich in geographical phenomena, processes and …
interactions of these elements, and rich in geographical phenomena, processes and …
Spatiotemporal bias adjustment of IMERG satellite precipitation data across Canada
Recently developed remote sensing data including satellite-based products show promising
performance in estimating precipitation at high spatiotemporal resolution. However, the …
performance in estimating precipitation at high spatiotemporal resolution. However, the …
Evaluation of GPM IMERG and its constellations in extreme events over the conterminous united states
Improved quantification of extreme precipitation rates using observations has far-reaching
implications for environmental sciences, especially for hydrometeorological studies. Yet …
implications for environmental sciences, especially for hydrometeorological studies. Yet …
[HTML][HTML] GPROF-NN: A neural-network-based implementation of the Goddard profiling algorithm
S Pfreundschuh, PJ Brown… - Atmospheric …, 2022 - amt.copernicus.org
Abstract The Global Precipitation Measurement (GPM) mission measures global
precipitation at a temporal resolution of a few hours to enable close monitoring of the global …
precipitation at a temporal resolution of a few hours to enable close monitoring of the global …
Customized deep learning for precipitation bias correction and downscaling
Systematic biases and coarse resolutions are major limitations of current precipitation
datasets. Many deep learning (DL)-based studies have been conducted for precipitation …
datasets. Many deep learning (DL)-based studies have been conducted for precipitation …
Ground validation and error sources identification for GPM IMERG product over the southeast coastal regions of China
The Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission
(IMERG) has been widely evaluated. However, most of these studies focus on the ultimate …
(IMERG) has been widely evaluated. However, most of these studies focus on the ultimate …
Two-decades of GPM IMERG early and final run products intercomparison: Similarity and difference in climatology, rates, and extremes
Precipitation is an essential climate and forcing variable for modeling the global water cycle.
Particularly, the recent Integrated Multi-satellite Retrievals for GPM (IMERG) product …
Particularly, the recent Integrated Multi-satellite Retrievals for GPM (IMERG) product …
Evaluation of satellite rainfall estimates in a rugged topographical basin over south gojjam basin, Ethiopia
DA Malede, TA Agumassie, JR Kosgei… - Journal of the Indian …, 2022 - Springer
Under the inaccessibility of optimum networks and lack of well-organized rain gauge data,
the provided high-resolution satellite estimates serve as a vital baseline for hydro climate …
the provided high-resolution satellite estimates serve as a vital baseline for hydro climate …
[HTML][HTML] A flood predictability study for Hurricane Harvey with the CREST-iMAP model using high-resolution quantitative precipitation forecasts and U-Net deep …
A flood is one of the most hazardous natural disasters, and it commonly causes fatalities and
socioeconomic damages. The advances of modeling techniques and observation data in …
socioeconomic damages. The advances of modeling techniques and observation data in …
Interpreting Conv-LSTM for spatio-temporal soil moisture prediction in China
Soil moisture (SM) is a key variable in Earth system science that affects various hydrological
and agricultural processes. Convolutional long short-term memory (Conv-LSTM) networks …
and agricultural processes. Convolutional long short-term memory (Conv-LSTM) networks …