Land tessellation effects in mapping agricultural areas by remote sensing at field level

While mapping agricultural areas by remote sensing, it is quite common to operate at cadastral parcel level. Unfortunately, this land tessellation is merely administrative: a single parcel can, in fact, be made of differently managed parts whose spectral properties can be significantly different, being often different their content. In this situation, approaches that aggregate spectral signals of pixels belonging to the same parcel to investigate their average behaviour can generate misleading results. In this work, we evaluated how different field tessellation schemes can condition the interpretation of the spectral behaviour of crops with special concern on time series of NDVI (normalized difference vegetation index) and NDWI (normalized difference water index) spectral indices, which are assumed as proxies of plant vigour and crop/soil water content, respectively. The study relies on Sentinel 2 and Landsat 8 data imaging a rice-cultivated area sited in Piemonte (NW Italy). Two reference land tessellation geometries were taken into account: (a) the local cadastral map (purely administrative land division criterion) and (b) a map obtained by image segmentation of the NDVI time series (purely spectral land division criterion). After signal aggregation, some statistics were therefore computed to test differences both in time (within the same parcel along its temporal profile) and in space (within the same image at different positions at the same time). Results obtained exploring the rice growing season 2016 showed that (a) in 23% (70% at 1 sigma) and 27% (70% at 1 sigma) of segments (respectively for NDVI and NDWI) spectral differences, averagely along the year, are significant, possibly leading to wrong interpretation of occurring dynamics in the area; (b) in rice-cultivated fields, spectral differences suffer from seasonality with a higher incidence in Spring, when rice agronomic phases are more dynamic and, in the meantime, critical for management.