Date: Wednesday 28/06 - 14h00
Organisation: Hydrology and Remote Sensing Laboratory, Agricultural Research Service, U.S. Department of Agriculture
Title: Daily monitoring of vegetation conditions and evapotranspiration at field scale by fusing multi-satellite images
Description: Vegetation monitoring requires frequent remote sensing observations. While imagery from coarse resolution sensors can provide daily observations, they lack spatial detail to capture surface features for vegetation monitoring. The medium spatial resolution (10-100m) sensors are suited to capturing surface details at field scale, but a long revisit cycle has limited its use in describing daily surface changes. In this presentation, data fusion approaches will be examined. The systems for building daily vegetation index and evapotranspiration at field scale using multi-satellite images will be introduced. Recent applications including vegetation phenology mapping, drought monitoring and crop yield estimation will be demonstrated.
Biography: Dr. Feng Gao is a Research Physical Scientist with the Hydrology and Remote Sensing Laboratory, Agricultural Research Service, U.S. Department of Agriculture. He was a Research Associate Professor at the Department of Geography, Boston University and a Research Scientist with the NASA Goddard Space Flight Center and Earth Resources Technology, Inc. His current research interests include vegetation phenology mapping, vegetation condition and water use monitoring, and crop yield estimation at field scale using multi-satellite data fusion approach. He has authored or co-authored over 100 publications in peer-reviewed journals. He is a member of the Landsat and MODIS Science Team.
Thuy Le Toan
Date: Thursday 29/06 - 14h00
Organisation: Centre d'Etudes Spatiales de la Biosphère (CESBIO), Toulouse, France
Title: SAR time series for vegetation monitoring
Description: In studying the Earth’s processes from space, the information we seek is very often carried by patterns of change. This is particularly true for SAR data, for which many of the applications rely explicitly on the use of multitemporal data. However, the issues in exploiting multitemporal SAR are not to do with missing data, atmospheric correction or varying sun conditions as for optical data, but arise from the physics of microwave interactions with the surface and the impacts this has on the information content, interpretation and handling of the data. This paper presents approach to monitor changes in vegetation cover and to retrieve vegetation parameters with a temporal sequence of SAR data, taking into account the perturbations caused by environment effects and by the SAR speckle noise. The illustrations will be provided on the use of time series SAR data for forest monitoring and for paddy rice monitoring.
Biography: Thuy Le Toan is leading the biomass research group at the Centre d’Etudes Spatiales de la Biosphère,Toulouse. Her research activity has been in the area of remote sensing for land applications, and her specialisation is on radar remote sensing for agriculture and forest monitoring. She is proposer and co-leader of the next ESA Earth Explorer satellite mission BIOMASS, selected for launch in 2021. She has been a Project Coordinator and PI of several satellite research projects. She has also been member of science teams and review panels for E.U., ESA, NASA, JAXA and national organisations on the use of SAR in monitoring land surfaces.
Date: Tuesday 27/06 - Opening Session (09h45 - 12h00)
Organisation: Vienna University of Technology (TU Wien) and Earth Observation Data Centre for Water Resources Monitoring (EODC)
Title: Monitoring of soil moisture and vegetation dynamics with ASCAT and Sentinel-1
Description: Active microwave measurements of the land surface as acquired by Synthetic Aperture Radars (SARs) or scatterometers are very sensitive to the water content in the soil and vegetation. Given that both variables are highly variable in time, it is important to observe the surface frequently in order to understand and disentangle the effects of soil moisture and vegetation on the backscattered signal. Unfortunately, past SAR missions have only been able to acquire a few measurements per month or year over one particular region. The new constellation of Sentinel-1 satellites represents a significant advance as the identical SAR instruments onboard the two satellites will cover the land surface every three to six day (over Europe and other hotspot regions) and six to twelve days over the remaining land surface areas. While this is sufficient to characterize vegetation dynamics, this is still not enough to capture the temporal variability of soil moisture. Therefore, only when Sentinel-1 are used in combination with scatterometer data (such as provided by the Advanced Scatterometer ASCAT) it becomes possible to capture the full spatio-temporal dynamics of soil moisture and vegetation. In presentation, I will discuss the complementary nature of Sentinel-1 SAR and ASCAT observations, highlighting the significant benefits of using the two sensors systems in a synergistic way to derive soil moisture and vegetation.
Biography: Wolfgang Wagner is professor for remote sensing at the Vienna University of Technology (TU Wien), Austria, head of the Department of Geodesy and Geoinformation of TU Wien, and co-founder and head of science of the Earth Observation Data Centre for Water Resources Monitoring (EODC). His main research interests lie in geophysical parameter retrieval techniques from remote sensing data and application development. He focuses on active remote sensing techniques, in particular scatterometry, SAR and full-waveform airborne laser scanning. Before joining TU Wien, he received fellowships to carry out research at NASA Goddard Space Flight Centre, European Space Agency, and the Joint Research Centre of the European Commission. From 1999 to 2001 he was with the German Aerospace Agency (DLR). He received the ISPRS Frederick J. Doyle Award for his scientific contributions in active remote sensing in 2016. Since 2017 he has been chair of the GCOS/WCRP Terrestrial Observation Panel for Climate (TOPC).
Date: Tuesday 27/06 - Opening Session (09h45 - 12h00)
Organisation: National Physical Laboratory
Title: A framework for Establishing Confidence in Earth Observation Datasets
Description: Earth Observation satellites are increasingly used to monitor the environment, measure variability and change, inform evaluations of climate models and manage natural resources. Although EO data and products are plentiful, it is still rare for them to have reliable and fully traceable (end-to-end) information concerning their quality. Here we will expore the concepts required to develop internationally robust quality assurance procedures and gather standardised QA information on all EO data products. The key purpose being to enable more meaningul product comparisons and ensure that data users have the necessary information to make informed decisions concerning the data chosen for their climate applications.
Biography: Dr Nightingale joined the National Physical Laboratory (UK) in 2013 from NASA’s Goddard Space Flight center and has over 10 years of experience in coordinating Earth Observation System global land product validation activities. Joanne chaired the CEOS Working Group on Calibration and Validation, sub-group for Land Product Validation from 2010 - 2013. Joanne obtained her Ph.D. in Geography and Remote Sensing from the University of Queensland in Australia and completed two post-doctoral research positions at universities with in the United States. Her research interests include assessing the quality and validity of information about the terestrial biosphere from Earth observation satellites.
Date: Thursday 29/06 - Plenary Session (08h30 - 102h10)
Organisation: Wageningen University of Research (The Netherlands)
Title: Remotely Sensed Resilience of Tropical Forests
Description: Recent work suggests that episodes of drought and heat can bring forests across climate zones to a threshold for massive tree mortality. Across complex systems, the vicinity of a threshold for collapse tends to come with a loss of resilience as reflected in declining recovery rates from perturbations. Trees may be no exception, as at the verge of drought induced death, trees are found to be weakened in multiple ways affecting their ability to recover from stress. Here we use world-wide time series of satellite images to show that temporal autocorrelation, an indicator of slow recovery rates, rises steeply as mean annual precipitation declines to levels known to be critical for tropical forests. This implies independent support for the idea that such forests may have a tipping point for collapse at drying conditions. Moreover, the demonstration that slowing down may be detected from satellite data suggests a novel way to monitor resilience of tropical forests, as well as other ecosystems known to be vulnerable to collapse. With the advent of Sentinel-1 and 2 satellites new opportunities arise to derive accurate and near operational forest resilience measures.
Biography: Jan Verbesselt is associate professor in remote sensing at Wageningen University, Laboratory of Geo-information Science and Remote Sensing. He focusses at measuring and understanding ecosystem dynamics by developing novel spatio-temporal methods to detect, monitor and forecast changes using remotely sensed data from in-situ, terrestrial- and airborne LiDAR, and satellite sensors. The application of remotely sensed images for ecological modelling, and collaborative earth science for assessing vegetation, climate, and human impacts take a central place. He is the author of an open-source toolkit, BFAST, providing functionality to detect, monitor and characterise change within satellite image time series ( http://bfast.r-forge.r-project.org/).