Vegetation Monitoring for Mountainous Regions Using a New Integrated Topographic Correction (ITC) of the SCS plus C Correction and the Shadow-Eliminated Vegetation Index
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abstract
The mountainous vegetation is important to regional sustainable development. However, the topographic effect is the main obstacle to the monitoring of mountainous vegetation using remote sensing. Aiming to retrieve the reflectance of frequently-used redgreenblue and near-infrared (NIR) wavebands of rugged mountains for vegetation mapping, we developed a new integrated topographic correction (ITC) using the SCS + C correction and the shadow-eliminated vegetation index. The ITC procedure consists of image processing, data training, and shadow correction and uses a random forest machine learning algorithm. Our study using the Landsat 8 Operational Land Imager (OLI) multi-spectral images in Fujian province, China, showed that the ITC achieved high performance in topographic correction of regional mountains and in transferability from the sunny area of a scene to the shadow area of three scenes. The ITC-corrected multi-spectral image with an NIRredgreen composite exhibited flat features with impressions of relief and topographic shadow removed. The linear regression of corrected waveband reflectance vs. the cosine of the solar incidence angle showed an inclination that nearly reached the horizontal, and the coefficient of determination decreased to 0.00~0.01. The absolute relative errors of the cast shadow and the self-shadow all dramatically decreased to the range of 0.30~6.37%. In addition, the achieved detection rate of regional vegetation coverage for the three cities of Fuzhou, Putian, and Xiamen using the ITC-corrected images was 0.92~6.14% higher than that using the surface reflectance images and showed a positive relationship with the regional topographic factors, e.g., the elevation and slope. The ITC-corrected multi-spectral images are beneficial for monitoring regional mountainous vegetation. Future improvements can focus on the use of the ITC in higher-resolution imaging.
