Spatial scale conversion approach for moderate-resolution imaging spectroradiometer leaf area index product validation

Yunping Chen; Wei Wei; Angelica E. Patterson; Ling Tong

doi:10.1117/1.JRS.7.073463

16 December 2013 Spatial scale conversion approach for moderate-resolution imaging spectroradiometer leaf area index product validation

Yunping Chen, Wei Wei, Angelica E. Patterson, Ling Tong

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 7, Issue 1, 073463 (December 2013). https://doi.org/10.1117/1.JRS.7.073463

Abstract

This paper proposes a new spatial scale conversion method, which validates moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) product when geometry information from the MODIS 1B product and classification result is combined. The in situ LAI data, Landsat Thematic Mapper (TM), and MODIS 1B product were utilized in this research. An object-oriented method was used to classify TM imaging, where each class was computed using an empirical model to achieve LAI respectively. The 30-m TM LAI image was aggregated into the MODIS 1B product based on the geometry information of MODIS 1B. The simulated MODIS 1B image was then converted into a MODIS LAI product and compared with the simulated LAI map pixel by pixel. The results showed a lower root mean square error and higher normalization of the absolute error with the new method. In addition, the field LAI was not significantly correlated with MODIS LAI, but it did show a strong correlation with TM LAI. The new method achieved a higher correlate coefficient with the MODIS product than the conventional methods. Using this validation method based on classification and image simulation can improve the accuracy of product certification.

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Yunping Chen, Wei Wei, Angelica E. Patterson, and Ling Tong "Spatial scale conversion approach for moderate-resolution imaging spectroradiometer leaf area index product validation," Journal of Applied Remote Sensing 7(1), 073463 (16 December 2013). https://doi.org/10.1117/1.JRS.7.073463

Published: 16 December 2013

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