0000000000759093
AUTHOR
L. Guanter
Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt
Forecasting crop yields is becoming increasingly important under the current context in which food security needs to be ensured despite the challenges brought by climate change, an expanding world population accompanied by rising incomes, increasing soil erosion, and decreasing water resources. Temperature, radiation, water availability and other environmental conditions influence crop growth, development, and final grain yield in a complex non-linear manner. Machine learning (ML) techniques, and deep learning (DL) methods in particular, can account for such non-linear relations between yield and its covariates. However, they typically lack transparency and interpretability, since the way t…
Gridding artifacts on ENVISAT/MERIS temporal series
Earth observation satellites are a valuable source of data that can be used to better understand the Earth system dynamics. However, analysis of satellite image time series requires an accurate spatial co-registration so that the multi-temporal pixel entities offer a true temporal view of the study area. This implies that all the observations must be mapped to a common system of grid cells (gridding). Two common grids can be defined as a reference: (1) a grid defined by an external dataset in a given coordinate system or (2) a grid defined by one of the images of the time series. The aim of this paper is to study the impact that gridding has on the quality of ENVISAT/MERIS image time series…
Cloud screening and multitemporal unmixing of MERIS FR data
The operational use of MERIS images can be hampered by the presence of clouds. This work presents a cloud screening algorithm that takes advantage of the high spectral and radiometric resolutions of MERIS and the specific location of some of its bands to increase the cloud detection accuracy. Moreover, the proposed algorithm provides a per-pixel probabilistic map of cloud abundance rather than a binary cloud presence flag. In order to test the proposed algorithm we propose a cloud screening validation method based on temporal series. In addition, we evaluate the impact of the cloud screening in a multitemporal unmixing application, where a temporal series of MERIS FR images acquired over Th…