Effects of saltwater intrusion on pinewood vegetation using satellite ASTER data: the case study of Ravenna (Italy)

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• 作者：M. Barbarella (1)
  M. De Giglio (1)
  N. Greggio (2)
  
  1. Department of Civil ; Chemical ; Environmental and Materials Engineering鈥擠ICAM ; University of Bologna ; Viale Risorgimento 2 ; 40136 ; Bologna ; Italy
  2. Interdepartmental Centre for Environmental Science Research (CIRSA) ; I.G.R.G. Lab. ; University of Bologna ; Via S. Alberto 163 ; 48123 ; Ravenna ; Italy
  
• 关键词：NDVI ; ASTER ; Saltwater intrusion in coastal aquifer ; Groundwater ; Pinewood ; Statistical evaluation
• 刊名：Environmental Monitoring and Assessment
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：187
• 期：4
• 全文大小：3,514 KB
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• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Monitoring, Environmental Analysis and Environmental Ecotoxicology
  Ecology
  Atmospheric Protection, Air Quality Control and Air Pollution
  Environmental Management
  
• 出版者：Springer Netherlands
• ISSN：1573-2959

文摘

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.