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ARS Home » Plains Area » College Station, Texas » Southern Plains Agricultural Research Center » Aerial Application Technology Research » Research » Publications at this Location » Publication #359559

Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research

Title: A shadow-eliminated vegetation index (SEVI) for removal of self and cast shadow effects on vegetation in rugged terrains

Author
item JIANG, HONG - FUZHOU UNIVERSITY
item WANG, SEN - FUZHOU UNIVERSITY
item CAO, XIAOJIE - FUZHOU UNIVERSITY
item Yang, Chenghai
item ZHANG, ZHAOMING - FUZHOU UNIVERSITY
item WANG, XIAOQIN - CHINESE ACADEMY OF SCIENCES

Submitted to: International Journal of Digital Earth
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/30/2018
Publication Date: 9/1/2019
Citation: Jiang, H., Wang, S., Cao, X., Yang, C., Zhang, Z., Wang, X. 2019. A shadow-eliminated vegetation index (SEVI) for removal of self and cast shadow effects on vegetation in rugged terrains. International Journal of Digital Earth. 12(9):1013-1029.

Interpretive Summary: The effect of terrain shadows on remotely sensed images in rugged terrains is a major obstacle in the accurate retrieval of vegetation parameters. This work developed a shadow-eliminated vegetation index (SEVI), which was computed from the red and near-infrared bands in images. Three methods were used to validate the SEVI accuracy in elimination of terrain shadow effects. Validation results showed that the proposed SEVI effectively eliminated terrain shadow effects, achieving similar or better results compared with conventional shadow removal methods expanding the ability to use images obtained under these conditions.

Technical Abstract: The effect of terrain shadows, including the self shadow and cast shadow, is one of the main obstacles for accurate retrieval of vegetation parameters by remote sensing in rugged terrains. A shadow- eliminated vegetation index (SEVI) was developed, which was computed from only red and near-infrared top-of-atmosphere reflectance without other heterogeneous data and topographic correction. After introduction of the conceptual model and feature analysis of conventional wavebands, the SEVI was constructed by ratio vegetation index (RVI), shadow vegetation index (SVI) and adjustment factor. Then three methods were used to validate the SEVI accuracy in elimination of terrain shadow effects, including relative error analysis for self and cast shadows, correlation analysis between the cosine of solar incidence angle and vegetation indices, and comparison analysis between SEVI and conventional vegetation indices with topographic correction. The validation results based on 532 samples showed that the SEVI relative errors for self and cast shadows were 4.32% and 1.51% respectively. The coefficient of determination between cosi and SEVI was only 0.032 and the coefficient of variation (std/mean) for SEVI in shady and sunny areas was 12.59%. The results from this study indicate that the proposed SEVI effectively eliminated the effect of terrain shadows and achieved similar or better results than conventional vegetation indices with topographic correction.