This document describes an algorithm to classify tillage changes at ~100m resolution by using Sentinel-1 and Sentinel-2 data. Binary maps of surface roughness changes are derived as a complementary product of the Surface Soil Moisture Prototype (SMOSAR) code. The algorithm implements an incoherent temporal change detection using S1 VH backscatter coefficient. A two scale thresholding approach is adopted in order to single out VH changes due to tillage practices only. The method is applied to bare or scarcely vegetated fields, which are identified by using the Normalized Difference Vegetation Index (NDVI), extracted from Sentinel-2 data or, in case of cloud cover, the Sentinel-1 VH/VV feature.
Proof-of-concept of tillage change product v3 (D6.13)
Giuseppe Satalino;Francesco Mattia;Anna Balenzano;Francesco Lovergine;Annarita D'Addabbo
2019
Abstract
This document describes an algorithm to classify tillage changes at ~100m resolution by using Sentinel-1 and Sentinel-2 data. Binary maps of surface roughness changes are derived as a complementary product of the Surface Soil Moisture Prototype (SMOSAR) code. The algorithm implements an incoherent temporal change detection using S1 VH backscatter coefficient. A two scale thresholding approach is adopted in order to single out VH changes due to tillage practices only. The method is applied to bare or scarcely vegetated fields, which are identified by using the Normalized Difference Vegetation Index (NDVI), extracted from Sentinel-2 data or, in case of cloud cover, the Sentinel-1 VH/VV feature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
