Scaling characteristics of remotely sensed surface net radiance over densely vegetated grassland in Northern China

Wenjiang Zhang; Zhiqiang Gao

doi:10.1117/12.675930

27 September 2006 Scaling characteristics of remotely sensed surface net radiance over densely vegetated grassland in Northern China

Wenjiang Zhang, Zhiqiang Gao

Author Affiliations +

Proceedings Volume 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III; 62981O (2006) https://doi.org/10.1117/12.675930
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

The surface heterogeneity of densely vegetated region is often ignored as its spatial variation doesn't shows so obvious as sparse region. This paper is to examine to which degree the estimation difference with scale change would be. The surface net radiation and related variables between six consecutive scales from 30 to 960 m over a dense grass covered region in Northern China are calculated with a simplified scheme based on Landsat ETM data. The estimation agreements between neighbouring scales are evaluated with the mean absolute percent difference and the index of agreement. The two indices indicated variation is not so obvious and can't determine whether the study area is homogeneous or not. Further analyses of the fraction variation of land covers with scales and the change of related mean variables for individual land cover with scales, reach a consistent result that the major covers with larger patches are more insensitive to scale change than the minor ones with smaller patches. The introduction of land cover information improves detecting the effect of patches with different covers when the surface net radiation is considered.

Citation Download Citation

Wenjiang Zhang and Zhiqiang Gao "Scaling characteristics of remotely sensed surface net radiance over densely vegetated grassland in Northern China", Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62981O (27 September 2006); https://doi.org/10.1117/12.675930

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