地形复杂山区常用植被指数的地形校正对比

植被指数能反映地表植被生长、覆盖等情况,常作为反演植物生物物理参量的有效参数。然而,在地形复杂的山区,由于地形效应的影响,导致一些植被指数适用性受限。基于以上现状,本文以贵州省江口县为研究区,采用4种地形校正模型（Teillet-回归模型、Minnaert模型、C模型、SCS+C模型）对常用植被指数（SR、MSR、NDVI、SAVI、MSAVI、EVI）进行地形校正,以评价不同坡度条件下植被指数地形校正效果。结果表明：地形校正对缓解波段比形式的植被指数（SR、MSR、NDVI）地形效应的作用有限,而对非波段比形式的植被指数（SAVI、MSAVI、EVI）效果较好。另外,随着坡度增加,地形效应显著,地形校正效果也更明显：坡度较小时,波段比形式的植被指数无需进行地形校正,而建议非波段比形式的植被指数进行地形校正;坡度较大时,建议2类植被指数都进行地形校正,但非波段比形式的植被指数可能会发生过度校正现象。此外,地形校正后非波段比形式的植被指数与森林地上生物量线性回归模型的精度明显提高。因此,建议在地形复杂山区利用非波段比形式的植被指数进行定量反演时,先进行地形校正。

Comparison of Topographic Correction on Commonly Used Vegetation Indices in Rugged Terrain Area

In the field of remote sensing applications, vegetation indices have been used as an effective parameter for monitoring surface vegetation biophysical features such as the growth status and vegetation coverage. However, in the mountainous area, the influence of terrain causes the applicability of some vegetation indices being limited. It is conductive to improving the accuracy of vegetation indices by using topographic correction model in rugged terrain area. In this paper, 4 topographic correction models (Teillet-regression model, Minnaert model, C model and SCS + C model) were employed to correct several commonly used vegetation indices (SR, MSR, NDVI, SAVI, MSAVI and EVI) derived from the Landsat-5 TM data. This paper aimed at assessing the topographic correction results of these vegetation indices on different slope gradients, by taking Fanjing Mountain as the research area. The results indicated that topographic correction had different influences with respect to different vegetation indices. Topographic correction was more effective on non-band-ratio vegetation indices (SAVI, MSAVI and EVI) than band-ratio vegetation index (SR, MSR and NDVI), because the band ratio could reduce the effect of topography to some extent. Furthermore, the effects of topographic correction on the vegetation index were also different with respect to different slopes. While the slope increases, the topographic effects became more significant and topographic correction acted more effectively. On the gentler slopes, the non-band-ratio vegetation indices, rather than the band-ratio vegetation indices, need to be corrected using topographic correction models. On the steep slopes, we recommended that both of the indices should be corrected, while the non-band-ratio vegetation indices may be overcorrected. In addition, the precision of the linear regression equation of the non-band-ratio vegetation indices and forest aboveground biomass was improved after the application of topographic correction. Above all, before using the non-band-ratio vegetation indices for quantitatively retrieving the vegetation parameters in rugged terrain area, topographic correction is recommended to be conducted.