Guido Lemoine, European Commission's Joint Research Centre

The European Copernicus program has launched 4 Earth Observation platforms since April 2014. Operational data streams from the Sentinel-1A, a C-band SAR, and Sentinel-2A, an optical and infrared sensor are provided under a full, free and open license since October 2014 (S1A) and August 2015 (S2A). These streams will soon be complemented with those from Sentinel 3A (a medium resolution sensor launched in February 2016) and Sentinel-1B, the twin of S-1A (launched April 2016). In the last year, the Earth Engine team has started with the ingestion of S1A and S2A data streams into the Engine, exposing it as 2 hosted data catalogues to the growing community of Earth Engine users. The unique combination of frequent, all-weather SAR S1 acquisitions and 10 multispectral band S2 at 10-20m resolution, and their combination with existing Landsat data sets and lower resolution MODIS time series provides exciting new opportunities for applications in crop monitoring. In the presentation, we discuss some dedicated processing methods for S1 data (e.g. speckle filtering, time series analysis) and S2 (e.g. red-edge analysis) and their combined use in large classification and validation experiments. On the basis of our results, and the further expansion of the Sentinel fleet in 2017 with Sentinel-2B and -3B, we propose some directions for future development (constrained segmentation, multi-annual change analysis, integration of crop rotation knowledge, links to ‘deep learning’ issues, etc.).

About the speaker: Guido Lemoine is a Principal Scientist in the Monitoring Agricultural ReSources (MARS) Unit of the European Commission’s Joint Research Centre (JRC). He is an agricultural engineer by training (1987, Soil Science, Wageningen University, The Netherlands). His main expertise is in applied remote sensing, first developed as a research topic (microwave backscattering of soils) and later as a commercial activity in a co-founded remote sensing and GIS consultancy. After he joined the JRC, in 1997, he has further developed his remote sensing and informatics expertise in agricultural statistics and subsidy control applications, in fisheries monitoring, and in civil security applications (Copernicus emergency services). In 2014, he returned to the MARS unit to help develop the uptake of the European Copernicus Sentinel in global agricultural monitoring applications.

Dr. Brady Allred, University of Montana

About the speaker: Dr. Brady Allred is an assistant professor of rangeland ecology at the University of Montana. His research interests include rangeland dynamics, processes, and structure at broad scales. He uses earth observation data to advance the science and practice of rangeland conservation.

About the speaker: Beth Tellman is a PhD student in geographical sciences at Arizona State University. Her research focuses understanding how environmental change shapes flood vulnerability and how illicit human activity drives land use change. She employs tools and methods from land system science, hydrology, and the social sciences to model social and natural systems across time and space using satellite, cadastral, and ancillary socioeconomic data. Current projects include examining political drivers of urbanization and water infrastructure in irregular settlements, and the historical pathway of adaptation to flood risk (in Mexico City with NSF project- MEGADAPT), estimating the return on investment of watershed conservation for flood mitigation in Latin American cities with SNAP, quantifying the effect of the cocaine commodity chain on deforestation patterns in Central America, and modeling global biophysical and social flood vulnerability using Google Earth Engine with a company she co-founded, Cloud to Street. Beth received her M.S. from Yale School of Forestry in Environmental Science and B.S in Sustainable Globalization from Santa Clara University.

Surface water detection using multi-spectral satellite imagery is a relatively trivial process. However, a very accurate estimation of water mask is still a challenge and fully automated methods are very scarce. A fast-growing satellite industry necessitates such generic automated methods. Main sources of noise in multispectral imagery include clouds and cloud shadows, systematic sensor or data processing errors, but also, varying climate and topographic conditions across the globe. At research institute Deltares, we have started using Google Earth Engine platform (EE) very intensively for many applications, including but not limited to the estimation of flood extent, surface water mask detection, and hydrological analysis. This presentation demonstrates some of these projects as well several new datasets being developed actively using EE (such as global height above the nearest drainage: http://global-hand.appspot.com) and a new web tool to analyze surface water changes globally at 30m resolution (http://aqua-monitor.appspot.com). 

About the speaker: Gennadii Donchyts is a senior consultant at Deltares. He has many years of expertise in multidisciplinary software development and research related to the numerical simulation of surface and subsurface water flow processes. He obtained an MSc in radio physics, electronics and computer systems from the Kyiv National Taras Shevchenko University and is currently pursuing a Ph.D. in at the Delft University of Technology focusing on the development of new methods and datasets for the automated surface water extraction and change detection using Earth Observation datasets.