Jia Xu

Orcid: 0000-0001-7688-5050

Affiliations:
  • Beijing Normal University, Faculty of Geographical Science, State Key Laboratory of Remote Sensing Science, China


According to our database1, Jia Xu authored at least 11 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Soil Moisture-Derived SWDI at 30 m Based on Multiple Satellite Datasets for Agricultural Drought Monitoring.
Remote. Sens., September, 2024

Satellite-Based PT-SinRH Evapotranspiration Model: Development and Validation from AmeriFlux Data.
Remote. Sens., August, 2024

A Hybrid Index for Monitoring Burned Vegetation by Combining Image Texture Features with Vegetation Indices.
Remote. Sens., May, 2024

Global Terrestrial Evapotranspiration Estimation from Visible Infrared Imaging Radiometer Suite (VIIRS) Data.
Remote. Sens., January, 2024

Using Partial Cloud-Free Images to Improve Spatiotemporal Fusion for Terrestrial Latent Heat Flux: The Multiphase Self-Adaptive (MSA) Model.
IEEE Trans. Geosci. Remote. Sens., 2024

2019
Merging the MODIS and Landsat Terrestrial Latent Heat Flux Products Using the Multiresolution Tree Method.
IEEE Trans. Geosci. Remote. Sens., 2019

Assessing the Remotely Sensed Evaporative Drought Index for Drought Monitoring over Northeast China.
Remote. Sens., 2019

Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China.
Remote. Sens., 2019

Long-Term Spatiotemporal Dynamics of Terrestrial Biophysical Variables in the Three-River Headwaters Region of China from Satellite and Meteorological Datasets.
Remote. Sens., 2019

2017
Satellite-Derived Spatiotemporal Variations in Evapotranspiration over Northeast China during 1982-2010.
Remote. Sens., 2017

MODIS-Based Estimation of Terrestrial Latent Heat Flux over North America Using Three Machine Learning Algorithms.
Remote. Sens., 2017


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