Research Papers

Use of MODIS and Landsat time series data to generate high-resolution temporal synthetic Landsat data using a spatial and temporal reflectance fusion model

[+] Author Affiliations
Mingquan Wu, Zheng Niu, Changyao Wang, Li Wang

Institute of Remote Sensing Applications, Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Datun Street, Chaoyang District, P. O. Box 9718, Beijing 100101, China

Chaoyang Wu

Institute of Remote Sensing Applications, Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Datun Street, Chaoyang District, P. O. Box 9718, Beijing 100101, China

University of Toronto, Department of Geography, 100 St. George Street, Room 5047, Toronto, Ontario, Canada M5S 3G3

J. Appl. Remote Sens. 6(1), 063507 (Mar 07, 2012). doi:10.1117/1.JRS.6.063507
History: Received March 21, 2011; Revised January 1, 2012; Accepted January 5, 2012
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Abstract.  Due to cloud coverage and obstruction, it is difficult to obtain useful images during the critical periods of monitoring vegetation using medium-resolution spatial satellites such as Landsat and Satellite Pour l’Observation de la Terre (SPOT), especially in pluvial regions. Although high temporal resolution sensors, such as the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS), can provide high-frequency data, the coarse ground resolutions of these sensors make them unsuitable to quantify the vegetation growth processes at fine scales. This paper introduces a new data fusion model for blending observations of high temporal resolution sensors (e.g., MODIS) and moderate spatial resolution satellites (e.g., Landsat) to produce synthetic imagery with both high-spatial and temporal resolutions. By detecting temporal change information from MODIS daily surface reflectance images, our algorithm produced high-resolution temporal synthetic Landsat data based on a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image at the beginning time (T1). The algorithm was then tested over a 185×185km2 area located in East China. The results showed that the algorithm can produce high-resolution temporal synthetic Landsat data that were similar to the actual observations with a high correlation coefficient (r) of 0.98 between synthetic imageries and the actual observations.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Topics

MODIS ; Reflectivity

Citation

Mingquan Wu ; Zheng Niu ; Changyao Wang ; Chaoyang Wu and Li Wang
"Use of MODIS and Landsat time series data to generate high-resolution temporal synthetic Landsat data using a spatial and temporal reflectance fusion model", J. Appl. Remote Sens. 6(1), 063507 (Mar 07, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063507


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