Correlation Analysis between Air Temperature and MODIS Land Surface Temperature and Prediction of Air Temperature Using TensorFlow Long Short-Term Memory for the Period of Occurrence of Cold and Heat Waves
The purpose of this study is to analyze the correlation between surface air temperature (SAT) and land surface temperature (LST) based on land use when heat and cold waves occur and to predict the distribution of SAT using the long short-term memory (LSTM) of TensorFlow. For the correlation analysis...
Main Authors: | Jeehun Chung, Yonggwan Lee, Wonjin Jang, Siwoon Lee, Seongjoon Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/19/3231 |
Similar Items
-
Multiplication of medium-density matrices using TensorFlow on multicore CPUs
by: Siraphob Theeracheep, et al.
Published: (2019-01-01) -
An Evaluation of TensorFlow as a Programming Framework for HPC Applications
by: Chien, Wei Der
Published: (2018) -
Prediction of training time for deep neural networks in TensorFlow
by: Adlers, Jacob, et al.
Published: (2018) -
Retrievals of All-Weather Daily Air Temperature Using MODIS and AMSR-E Data
by: Keunchang Jang, et al.
Published: (2014-09-01) -
TensorFlow-Based Automatic Personality Recognition Used in Asynchronous Video Interviews
by: Hung-Yue Suen, et al.
Published: (2019-01-01)