Abstract
The vegetation space–time variability during 1999–2010 in the North of the Apulian region (Southern Italy) was analysed using SPOT VEGETATION (VGT) sensor data. Three bands of VEGETATION (RED, NIR and SWIR) were used to implement the vegetation index named reduced simple ratio (RSR) to derive leaf area index (LAI). The monthly average LAI is an indicator of biomass and canopy cover, while the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. The space–time distribution of LAI at the catchment scale was analysed over the examined period to detect the consistency of vegetation dynamics in the study area. A diffuse increase of LAI was observed in the examined years that cannot be directly explained only in terms of increasing water availability. Thus, in order to explain such a general behaviour in terms of climatic factors, the analysis was performed upon stratification of land cover classes, focusing on the most widespread species: forest and wheat. An interesting ascending–descending behaviour was observed in the relationship between inter-annual increments of maximum LAI and rainfall, and in particular, a strong negative correlation was found when the rainfall amount in January and February exceeded a critical threshold of about 100 mm.
Highlights
The process of mapping, quantifying, and monitoring changes in the physical characteristics of vegetation cover has become essential to understand the dynamics of state variables in hydrologic, agricultural, and ecologic systems from regional to global scales (Miao et al 2013; Nemani et al 1996; Peng et al 2012; Nolè et al 2014)
The variability in space and time of such index at the catchment scale over the period 1999–2010 and its correlation with temperature and rainfall observations was analysed, in order to investigate the consistency of leaf area index (LAI) variability and to characterise the vegetation dynamics to be developed in hydrologic and climate models
Using a VGT S10 data set related to the years going from 1999 to 2011, LAI variability was analysed in both space and time finding crucial insights for the description of the hydrologic dynamics characterising large parts of Puglia (Southern Italy)
Summary
The process of mapping, quantifying, and monitoring changes in the physical characteristics of vegetation cover has become essential to understand the dynamics of state variables in hydrologic, agricultural, and ecologic systems from regional to global scales (Miao et al 2013; Nemani et al 1996; Peng et al 2012; Nolè et al 2014). A number of global LAI products are being routinely estimated using data of spatial moderate and coarse resolution from various satellite sensors such as MODIS, SPOT and MERIS, having a frequency of 1–2 weeks and timely covering a period of somewhat more than 1 decade (Chen et al 2006; Propastin and Kappas 2012). Validating these products is a difficult task because ground-based plot measurements are always limited and cannot be compared with these image data directly without considering surface heterogeneity. The variability in space and time of such index at the catchment scale over the period 1999–2010 and its correlation with temperature and rainfall observations was analysed, in order to investigate the consistency of LAI variability and to characterise the vegetation dynamics to be developed in hydrologic and climate models
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