Rising temperature, rainfall, and wind regime changes, increasing of frequency and intensity of extreme events are only some of the effects of climate change affecting the agro-forestry sector. Earth Observation data from satellite missions (often available for free) can certainly support analysis of climate change effects on vegetation, making possible to improve land management in space and time. Within this context, the present work aims at investigating natural and agricultural vegetation, as mapped by Corine Land Cover (CLC) dataset, focusing on phenological metrics trends that can be possibly conditioned by the ongoing climate-change. The study area consists of the entire Piemonte region (NW-Italy). MOD13Q1-v6 dataset from TERRA MODIS mission was used to describe pluri-annual (2001-2019) phenological behavior of vegetation focusing on the following CLC classes: Non-irrigated arable land, Vineyards, Pastures, and Forests. After computing and mapping some phenological metrics as derivable from the interpretation of at-pixel level NDVI (Normalized Difference Vegetation Index) temporal profile, we found that the most significant one was the maximum annual NDVI (MaxNDVI). Consequently, its trend was analyzed at CLC class level for the whole Piemonte region. Natural and semi-natural vegetation classes (Pastures and Forests) were furtherly investigated testing significance of the Percent Total Variation (TV%) of MaxNDVI in the period 2001-2019 for different altitude classes. Results proved that Non-irrigated arable land showed a not significant trend of MaxNDVI; differently, vineyards and forests showed a significant increasing one. Concerning TV%, it was found that it increases with altitude for the Forests CLC class, while it decreases with altitude for the pastures class.

Exploring Climate Change Effects on Vegetation Phenology by MOD13Q1 Data: The Piemonte Region Case Study in the Period 2001-2019

Sarvia F.;De Petris S.;Borgogno-Mondino E.
2021-01-01

Abstract

Rising temperature, rainfall, and wind regime changes, increasing of frequency and intensity of extreme events are only some of the effects of climate change affecting the agro-forestry sector. Earth Observation data from satellite missions (often available for free) can certainly support analysis of climate change effects on vegetation, making possible to improve land management in space and time. Within this context, the present work aims at investigating natural and agricultural vegetation, as mapped by Corine Land Cover (CLC) dataset, focusing on phenological metrics trends that can be possibly conditioned by the ongoing climate-change. The study area consists of the entire Piemonte region (NW-Italy). MOD13Q1-v6 dataset from TERRA MODIS mission was used to describe pluri-annual (2001-2019) phenological behavior of vegetation focusing on the following CLC classes: Non-irrigated arable land, Vineyards, Pastures, and Forests. After computing and mapping some phenological metrics as derivable from the interpretation of at-pixel level NDVI (Normalized Difference Vegetation Index) temporal profile, we found that the most significant one was the maximum annual NDVI (MaxNDVI). Consequently, its trend was analyzed at CLC class level for the whole Piemonte region. Natural and semi-natural vegetation classes (Pastures and Forests) were furtherly investigated testing significance of the Percent Total Variation (TV%) of MaxNDVI in the period 2001-2019 for different altitude classes. Results proved that Non-irrigated arable land showed a not significant trend of MaxNDVI; differently, vineyards and forests showed a significant increasing one. Concerning TV%, it was found that it increases with altitude for the Forests CLC class, while it decreases with altitude for the pastures class.
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https://www.mdpi.com/2073-4395/11/3/555/pdf
Altitudinal gradient; Climate change effects; Mod13q1; Ndvi; Vegetation phenology; Vegetation trend analysis
Sarvia F.; De Petris S.; Borgogno-Mondino E.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1794545
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