Coastal soil erosion can be recognized as the most alarming environmental issue since, causing shoreline retreat, reduces the area available for plant habitat survival, highly influencing their health status, and, consequently, limiting their ability in beach front properties protection. A deep knowledge of vegetation changes is required to identify the proper strategy to be adopted to face soil erosion problems in coastal areas. Therefore, the current paper is aimed to quantitatively examine the spatio-temporal changes suffered by the vegetation in the coastline of Siponto in Apulia Region (Southern Italy) covering a time period of about forty years. LANDSAT images from 1975, 2006, 2011 and 2018 were collected, atmospherically corrected and, finally, processed to generate binary classification maps of vegetation by applying the Composite Vegetation Index, a novel index based on the interpolation of Red, Green and Near-Infrared bands, suitable for catching both cellular and metabolic features of vegetation. Then, the generated binary classification maps were compared using the Vegetation Index Differencing technique, a post-classification change detection technique. The results showed an increase in vegetation extension cover and density overall the entire examined period. That phenomenon appeared more and more prominent between 1975 and 2006, where an increment of vegetated areas extension of about 88% were registered. Combining of the novel vegetation index, developed ad-hoc in the current research, and Vegetation Index Differencing approach shows promising results in vegetation classification and comparison over the time. Indeed, the method allows the fast vegetation extraction, great processing time saver. Nevertheless, spatial resolution of Landsat Images limits the classification of small and low-density vegetated areas. Therefore, future work should plan to test the proposed approach at a more detailed scale.

沿海水土流失被认为是最令人担忧的环境问题，因为它导致海岸线撤退，减少了可用于植物栖息地生存的面积，严重影响了它们的健康状况，因此，限制了它们在海滩前保护方面的能力。需要对植被变化有深刻的了解，才能确定采取正确的策略来应对沿海地区的土壤侵蚀问题。因此，本文旨在定量研究普利亚地区（意大利南部）锡波托海岸线上约四十年的植被遭受的时空变化。收集了1975年，2006年，2011年和2018年的LANDSAT图像，对其进行了大气校正，最后，通过应用复合植被指数（一种基于红色，绿色和近红外波段插值的新颖指数）进行处理，以生成植被的二元分类图，该植被指数既适用于捕获植被的细胞特征，也适用于吸收新陈代谢的特征。然后，使用植被指数差异技术（一种分类后变化检测技术）对生成的二进制分类图进行比较。结果表明，在整个调查期间，植被扩展覆盖率和密度均增加了。在1975年至2006年之间，这种现象越来越明显，其中植被面积扩展的增量约为88％。结合新的植被指数，在当前研究中临时开发，植被指数差异法在一段时间内在植被分类和比较方面显示出可喜的结果。实际上，该方法允许快速的植被提取，节省大量的处理时间。但是，Landsat Images的空间分辨率限制了小而低密度植被区域的分类。因此，未来的工作应该计划更详细地测试提议的方法。