Next Article in Journal
Gradient-Based Assessment of Habitat Quality for Spectral Ecosystem Monitoring
Next Article in Special Issue
A Study of Coal Fire Propagation with Remotely Sensed Thermal Infrared Data
Previous Article in Journal
Estimating Forest Biomass Dynamics by Integrating Multi-Temporal Landsat Satellite Images with Ground and Airborne LiDAR Data in the Coal Valley Mine, Alberta, Canada
Previous Article in Special Issue
Combination of Well-Logging Temperature and Thermal Remote Sensing for Characterization of Geothermal Resources in Hokkaido, Northern Japan
Open AccessArticle

A New Global Climatology of Annual Land Surface Temperature

Institute of Geography, University of Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Academic Editors: Zhao-Liang Li, Jose A. Sobrino, Xiaoning Song, Josef Kellndorfer and Prasad S. Thenkabail
Remote Sens. 2015, 7(3), 2850-2870; https://doi.org/10.3390/rs70302850
Received: 31 December 2014 / Revised: 15 February 2015 / Accepted: 27 February 2015 / Published: 10 March 2015
(This article belongs to the Special Issue Recent Advances in Thermal Infrared Remote Sensing)
Land surface temperature (LST) is an important parameter in various fields including hydrology, climatology, and geophysics. Its derivation by thermal infrared remote sensing has long tradition but despite substantial progress there remain limited data availability and challenges like emissivity estimation, atmospheric correction, and cloud contamination. The annual temperature cycle (ATC) is a promising approach to ease some of them. The basic idea to fit a model to the ATC and derive annual cycle parameters (ACP) has been proposed before but so far not been tested on larger scale. In this study, a new global climatology of annual LST based on daily 1 km MODIS/Terra observations was processed and evaluated. The derived global parameters were robust and free of missing data due to clouds. They allow estimating LST patterns under largely cloud-free conditions at different scales for every day of year and further deliver a measure for its accuracy respectively variability. The parameters generally showed low redundancy and mostly reflected real surface conditions. Important influencing factors included climate, land cover, vegetation phenology, anthropogenic effects, and geology which enable numerous potential applications. The datasets will be available at the CliSAP Integrated Climate Data Center pending additional processing. View Full-Text
Keywords: land surface temperature; annual temperature cycle; annual cycle parameters; cloud gaps; thermal infrared; MODIS land surface temperature; annual temperature cycle; annual cycle parameters; cloud gaps; thermal infrared; MODIS
Show Figures

Figure 1

MDPI and ACS Style

Bechtel, B. A New Global Climatology of Annual Land Surface Temperature. Remote Sens. 2015, 7, 2850-2870.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Back to TopTop