For winter crop seasonality and phenology, we derived (1) the NDVI peak value
for agricultural winter crop season (April mean value) and (2) the NDVI loading as
an accumulated value of NDVI greater than 0.5 during winter season, as a proxy of
crop productivity (Fig. 3).
For features related to temporal land cover evolution, the multi-temporal evolution of five main land cover classes was taken into account—urban dense, urban
sparse, agricultural medium intensity, agricultural high intensity, and natural vegetation—for each year from 2000 to 2013.
In addition to the environmental features derived from satellite data described
above, in situ datasets were collected to characterize the environmental dynamics of
Fig. 2 Areal extent derived from monthly satellite time series for 2002 algal blooming features
Fig. 3 NDVI peak as derived from monthly satellite time series for 2002 winter crop conditions
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
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for agricultural winter crop season (April mean value) and (2) the NDVI loading as
an accumulated value of NDVI greater than 0.5 during winter season, as a proxy of
crop productivity (Fig. 3).
For features related to temporal land cover evolution, the multi-temporal evolution of five main land cover classes was taken into account—urban dense, urban
sparse, agricultural medium intensity, agricultural high intensity, and natural vegetation—for each year from 2000 to 2013.
In addition to the environmental features derived from satellite data described
above, in situ datasets were collected to characterize the environmental dynamics of
Fig. 2 Areal extent derived from monthly satellite time series for 2002 algal blooming features
Fig. 3 NDVI peak as derived from monthly satellite time series for 2002 winter crop conditions
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
91