Research Papers

Estimating the land-surface temperature of pixels covered by clouds in MODIS products

[+] Author Affiliations
Wenping Yu

Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, 320 Donggang West Road, Lanzhou 730000, China

University of Chinese Academy of Science, Beijing 100049, China

Mingguo Ma

Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, 320 Donggang West Road, Lanzhou 730000, China

Xufeng Wang

Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, 320 Donggang West Road, Lanzhou 730000, China

Junlei Tan

Chinese Academy of Sciences, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, 320 Donggang West Road, Lanzhou 730000, China

J. Appl. Remote Sens. 8(1), 083525 (Nov 06, 2014). doi:10.1117/1.JRS.8.083525
History: Received July 17, 2014; Revised September 24, 2014; Accepted October 9, 2014
Text Size: A A A

Abstract.  This study implements the “neighboring-pixel” (NP) theoretical method, which uses spatially and temporally NPs to reconstruct cloud-contaminated pixels in daily Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) products. The 2012 MODIS LSTs of the Heihe River Basin (HRB) region in China are used as an example, and the ground-measured LSTs obtained at 17 sites from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project are used to validate the reconstruction results. The results show a bias of 0.25 K and RMSE of 4.122 K during the day and a bias of 0.1263K and RMSE of 2.901K at night. The error analysis reveals an uncertainty in the estimation of the cloud-contaminated pixels that can be attributed to errors in the estimation of parameters and net solar radiation retrieval and inaccuracies inherent in the NP scheme. The analysis results reveal that the time-gap effect is the main cause of uncertainty in the nighttime reconstruction, whereas the large extreme cases for the daytime reconstruction are generally caused by strong convection systems that usually occur with heavy precipitation in the cloud-contaminated pixels. Despite the uncertainty, the proposed approach is promising for the improvement of MODIS LST application in practice.

Figures in this Article
© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Wenping Yu ; Mingguo Ma ; Xufeng Wang and Junlei Tan
"Estimating the land-surface temperature of pixels covered by clouds in MODIS products", J. Appl. Remote Sens. 8(1), 083525 (Nov 06, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083525


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.