THE INFLUENCE OF SNOW COVER ON THE SEASONAL VARIATION OF GLOBAL CLUMPING INDEX PRODUCTS

被引：0

作者：

Dong, Yadong ^{[1
,2
,3
]}

Jiao, Ziti ^{[1
,2
]}

Cui, Lei ^{[1
,2
]}

Yin, Siyang ^{[1
,2
]}

Chang, Yaxuan ^{[1
,2
]}

Zhang, Xiaoning ^{[1
,2
]}

He, Dandan ^{[1
,2
]}

Ding, Anxing ^{[1
,2
]}

机构：

[1] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[2] Beijing Normal Univ, Fac Geog Sci, Coll Remote Sensing & Engn, Beijing 100875, Peoples R China

[3] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China

来源：

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年

基金：

国家重点研发计划;

关键词：

kernel-driven model; clumping index; snow cover; seasonal variation; MODIS; MODEL; VERSION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The foliage Clumping Index (CI) quantifies the level of foliage grouping within a distinct canopy structure relative to a random distribution. It is a key structure parameter for the ecological, hydrological, and land surface models. In this study, we investigate the influence of snow cover on the seasonal variation of global CI products derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) parameter products using the improved RTCLSR kernel-driven model. Results indicated that the cover of snow can lead to a much larger CI and thus considerably decrease the quality of the CI product. Statistics in 2006 indicates that more than 85% low quality pixels are covered by the snow. The average CI for evergreen needleleaf forests in winter will decrease about 0.1 after deducing the influence of snow covered pixels. The influence of snow cover should be carefully considered and corrected when analyzing the seasonal variation of the global CI product.

引用

页码：5406 / 5409

页数：4

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