Barbarella M, De Giglio M, Greggio N
Department of Civil, Chemical, Environmental and Materials Engineering-DICAM, University of Bologna, Viale Risorgimento 2, 40136, Bologna, Italy,
Environ Monit Assess. 2015 Apr;187(4):166. doi: 10.1007/s10661-015-4375-z. Epub 2015 Mar 7.
The San Vitale pinewood (Ravenna, Italy) is part of the remaining wooded areas within the southeastern Po Valley. Several studies demonstrated a widespread saltwater intrusion in the phreatic aquifer caused by natural and human factors in this area as the whole complex coastal system. Groundwater salinization affects soils and vegetation, which takes up water from the shallow aquifer. Changes in groundwater salinity induce variations of the leaf properties and vegetation cover, recognizable by satellite sensors as a response to different spectral bands. A procedure to identify stressed areas from satellite remote sensing data, reducing the expensive and time-consuming ground monitoring campaign, was developed. Multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired between May 2005 and August 2005, were used to calculate Normalized Difference Vegetation Index (NDVI). Within the same vegetation type (thermophilic deciduous forest), the areas with the higher vegetation index were taken as reference to identify the most stressed areas using a statistical approach. To confirm the findings, a comparison was conducted using contemporary groundwater salinity data. The results were coherent in the areas with highest and lowest average NDVI values. Instead, to better understand the behavior of the intermediate areas, other parameters influencing vegetation (meteorological data, water table depth, and tree density) were added for the interpretation of the results.
圣维塔莱松林（意大利拉文纳）是波河河谷东南部剩余林地的一部分。多项研究表明，作为整个复杂的沿海系统，该地区的潜水含水层受到自然和人为因素导致的广泛海水入侵。地下水盐碱化影响土壤和植被，植被从浅层含水层获取水分。地下水盐度的变化会引起叶片特性和植被覆盖的变化，卫星传感器可通过对不同光谱波段的响应识别这些变化。开发了一种从卫星遥感数据中识别受胁迫区域的程序，以减少昂贵且耗时的地面监测活动。利用2005年5月至2005年8月期间获取的多光谱先进星载热发射和反射辐射计（ASTER）数据来计算归一化植被指数（NDVI）。在同一植被类型（嗜热落叶林）内，以植被指数较高的区域为参考，采用统计方法识别受胁迫最严重的区域。为了证实研究结果，使用同期的地下水盐度数据进行了比较。在平均NDVI值最高和最低的区域，结果是一致的。相反，为了更好地理解中间区域的情况，添加了其他影响植被的参数（气象数据、地下水位深度和树木密度）来解释结果。
