Machine learning applications on air temperature prediction in the urban canopy layer: A critical review of 2011–2022
Air temperature within the urban canopy layer is one of the most critical variables that impact
the environmental sustainability of cities. With advantages in computational speed, machine …
the environmental sustainability of cities. With advantages in computational speed, machine …
Regional thermal environment changes: Integration of satellite data and land use/land cover
Land surface temperature (LST) is subject to location and environmental influences, which
makes quantification difficult in terms of timeliness. Based on 10-d geostationary satellite …
makes quantification difficult in terms of timeliness. Based on 10-d geostationary satellite …
Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data
By characterizing high-frequency surface thermal dynamics at a medium spatial scale,
hourly land surface temperatures (LST), retrieved from geostationary satellite thermal …
hourly land surface temperatures (LST), retrieved from geostationary satellite thermal …
A global dataset of daily near-surface air temperature at 1-km resolution (2003–2020)
Near-surface air temperature (Ta) is a key variable in global climate studies. A global
gridded dataset of daily maximum and minimum Ta (Tmax and Tmin) is particularly valuable …
gridded dataset of daily maximum and minimum Ta (Tmax and Tmin) is particularly valuable …
[HTML][HTML] Air temperature estimation over winter wheat fields by integrating machine learning and remote sensing techniques
C Xu, M Lin, Q Fang, J Chen, Q Yue, J Xia - International Journal of Applied …, 2023 - Elsevier
Air temperature (Ta) is significant to numerous Earth's surface and agricultural processes.
For agricultural fields (eg, winter wheat), Ta plays an important role in crop growth …
For agricultural fields (eg, winter wheat), Ta plays an important role in crop growth …
[HTML][HTML] Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data
Land surface temperature (LST) plays a dominant role in the surface energy budget (SEB)
and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of …
and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of …
Exploring diurnal cycles of surface urban heat island intensity in Boston with land surface temperature data derived from GOES-R geostationary satellites
The surface urban heat island (SUHI) is one of the most significant human-induced
alterations to the Earth's surface climate and can aggravate health risks for city dwellers …
alterations to the Earth's surface climate and can aggravate health risks for city dwellers …
Combining GOES-R and ECOSTRESS land surface temperature data to investigate diurnal variations of surface urban heat island
The surface urban heat island (SUHI) phenomenon is characterized by both high spatial and
temporal variability, while its diurnal (ie, diel) variations have rarely been investigated …
temporal variability, while its diurnal (ie, diel) variations have rarely been investigated …
An evaluation of ECOSTRESS products of a temperate montane humid forest in a complex terrain environment
Plant water use is difficult to monitor and predict in complex terrain. NASA's ECOsystem
Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides …
Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides …
Estimating half-hourly solar radiation over the Continental United States using GOES-16 data with iterative random forest
J Chen, W Zhu, Q Yu - Renewable Energy, 2021 - Elsevier
To reduce carbon emissions, using more solar energy is a feasible solution. Many
meteorological-based models can estimate global downward solar radiation (DSR), but they …
meteorological-based models can estimate global downward solar radiation (DSR), but they …