«Data management and visualization issues of the Copernicus satellite data»

Transcription

1 «Data management and visualization issues of the Copernicus satellite data» Dr. Panos Lolonis Member of the Scientific Council NATIONAL CADASTRE AND MAPPING AGENCY S.A. 288 Mesogion Ave Holaros - Athens Tel. +30 (210) plolonis@ktimatologio.gr

2 The Copernicus Programme (Sentinel satellites and contributing missions ESR-2, Envisat, CryoSat, CALYPSO, ) Sentinel-1A (and Sentinel-1B) Strip Map Mode: 80 km Swath, 5 x 5 m spatial resolution Interferometric Wide Swath: 250 km Swath, 5x20 m spatial resolution Extra-Wide Swath Mode: 400 km Swath, 25 x 100 m spatial resolution Wave-Mode: 20 km x 20 km, 5 x 20 m spatial resolution Operation: 2014 (~2016) Main application domains: Land monitoring (forests, water, soil, and agriculture) Emergency mapping (natural disasters) Marine monitoring of the maritime environment Sea ice observations and iceberg monitoring Production of high resolution ice charts Forecasting ice conditions at sea Mapping oil spills Sea vessel detection Climate change monitoring

3 The Copernicus Programme (Sentinel satellites and contributing missions ESR-2, Envisat, CryoSat, CALYPSO, ) Sentinel-1A (and Sentinel-1B) Sentinel-2A (and Sentinel-2A) Multi-spectral, 13 bands in the visible, near infrared and short wave infrared part of the spectrum Spatial resolution of 10 m, 20 m and 60 m Field view 290 Km Systematic global coverage of land surfaces from 56 S to 84 N Revisiting every 5 days at the Equator under the same viewing conditions Operation: 2015 (expected) Main application domains: «Βραβευθείσες προτάσεις Copernicus Masters», Π. Λολώνης, Συνάντηση εργασίας LDA, InnovAthens, Αθήνα, 15 Ιουλ Monitoring land cover change Agricultural crop monitoring and management Vegetation and forest monitoring Marine environmental monitoring, coastal zone mapping Inland water monitoring Glacier monitoring, ice extent mapping

4 The Copernicus Programme (Sentinel satellites and contributing missions ESR-2, Envisat, CryoSat, CALYPSO, ) Sentinel-1A (and Sentinel-1B) Sentinel-2A (and Sentinel-2A) Sentinel-3 (three satellites) Sea and land surface temperature (accuracy of global sea-surface temperatures <0.3 K) Sea and Land Surface Temperature Radiometer (SLSTR) measurements on 9 spectral channels and 2 additional bands for fire monitoring. Spatial resolution 500 m in the visible and shortwave infrared channels and 1 km in the thermal infrared channels. Revisit time<1day. Ocean and Land Color Instrument (OLCI), 21 bands, 300 m resolution, <2 days revisit SAR Altimeter measures at 300m resolution Operation: 2015/2017/2020 Main application domains: Ocean color and land reflectance Sea, land, and ice surface temperature Active fire and burnt area monitoring Sea surface topography data Glacier monitoring, ice extent mapping

5 The Copernicus Programme (Sentinel satellites and contributing missions ESR-2, Envisat, CryoSat, CALYPSO, ) Sentinel-1A (and Sentinel-1B) Sentinel-2A (and Sentinel-2A) Sentinel-3 (three satellites) Sentinels -4 / -5 / -5P Surface and atmospheric (3D) data for certain key chemical substances at various spatial resolutions (5-200 Km) and time intervals (few hours to few days). Operation: ~2020 Main application domains: monitoring of air quality stratospheric ozone and solar radiation climate monitoring

6 The Copernicus Programme (Sentinel satellites and contributing missions ESR-2, Envisat, CryoSat, CALYPSO, ) Sentinel-1A (and Sentinel-1B) Sentinel-2A (and Sentinel-2A) Sentinel-3 (three satellites) Sentinels -4 / -5 / -5P Sentinel-6 A radar altimeter to provide high-precision (centimeter precision) and timely observations of the topography of the global ocean. Operation: ~2020 Main application domains: monitoring of air quality stratospheric ozone and solar radiation climate monitoring

7 Characteristics of the Copernicus Data 2013 Sea-surface Topography Copyright ESA/CNES/CLS The Copernicus data: Are collected from a wide variety of sensors (multispectral instruments, radars, radiometers, interferometers ) Have a large variety of spatial resolutions ranging from few meters to hundreds of kilometers Have a wide variety of spectral resolutions and Depict phenomena on the Earth and its atmosphere at repeated times (satellite revisits ranging from few hours to several days). Copernicus data often need to be integrated with other types available of data (e.g. INSPIRE data, aerial photo maps, digital elevation data, crowd-sourced data etc.) in order to cover everyday user demands.

8 Integration with vector/statistical data Integration of multi-source data for flight control Courtesy: LUCIAD Integration with other types of data increases the usefulness of the Copernicus data. There is a need for data conformance and precise geo-referencing to a common reference system in order to have a sound and reliable depiction of the information. In most instances, due to the diverse source of the data and their different accuracy specifications, this requirement is not met, resulting in visual flaws and, perhaps, erroneous conclusions or decisions.

9 Depiction of spatiotemporal data (cross-section views) ortho-photomap of a rural area in Greece

10 Depiction of spatiotemporal data (cross-section views) ortho-photomap of a rural area in Greece

11 Depiction of spatiotemporal data (cross-section views) ortho-photomap of a rural area in Greece

12 Depiction of spatiotemporal data (cross-section views) ortho-photomap of a rural area in Greece

13 Depiction of spatiotemporal data (cross-section views) ortho-photomap of a rural area in Greece

14 Depiction of spatiotemporal data (multi-window views) 1945 ortho-photomap of a rural area in Greece 1971 ortho-photomap of the area 2001 ortho-photomap of the area 2008 ortho-photomap of the area

15 Depiction of spatiotemporal data (multi-window views)

16 Depiction of spatiotemporal data (Animations) Earth Arctic ice cover Courtesy: LUCIAD Animations are effective for showing large-scale trends, changes and patterns However, they fail to maintain, highlight and portray changes through time It would be desirable for analysts and users to have friendly visualization tools that help them visualize trends and changes simultaneously.

17 Depiction of spatiotemporal data Adopted from Brovelli and Zamboni, 2014, Environmental space and time web analyzer, Proc. of the 2014 Conference on Big Data from Space, Frascati, Italy, Nov Ideally, visualization software should be capable of assisting users in managing, visualizing 3D data changing through time (e.g. Sentinel 4/5/5P data). Depiction of hyperdimensionality data, however, is constrained heavily by current perceptual, methodological, and technological tools.

18 Depiction of changes through time ( delta images) Nepal earthquake deformation, Sentinel-1, 2015 Source: ESA Existing data management and visualization tools can process and depict changes between two time periods, however, they have difficulty in depicting changes in multiple time periods and depicting simultaneously the base data and changes.

19 Depiction of changes through time ( flickering ). Ortho-photomap of an area in Crete in

20 Depiction of changes through time ( flickering ). Ortho-photomap of an area in Crete in 2014

21 Depiction of changes through time ( flickering ). Ortho-photomap of an area in Crete in 1945

22 Depiction of changes through time ( swipe function ). Comparison of ortho-photo-images of the same area at two different times (Source: NCMA LSO & LSO 2014)

23 Depiction of changes through time ( swipe function ). Comparison of ortho-photo-images of the same area at two different times (Source: NCMA, CORINE LAND COVER)

24 Depiction of changes through time ( swipe function deficiencies ). Comparison of ortho-photo-images of the same area at two different times (Source: NCMA, 1945 & 2014)

25 Detecting and tracing features or objects of interest through time 1945 ortho-photomap of a rural area in Greece 1971 ortho-photomap of the area 2001 ortho-photomap of the area 2008 ortho-photomap of the area

26 Varying spatio-temporal resolution of the data Differing degrees of spatial resolution affect the outcomes of visualization and, most importantly, may have an impact on the outcomes of analyses. Copernicus data have varying degrees of spatio-temporal resolution and, therefore, it is important to have methods and tools for integrating them accurately and correctly. Integration of data with different units of spatial resolution Adopted from Mobics Innovation that works The data management and visualization tools should provide functionalities for properly integrating, analyzing and visualizing such data (e.g. interpolation tools, spatial filters etc.)

27 Visualization of error, uncertainty, and fuzziness Effective spatiotemporal visualizations should portray not only the values of a variable but also the error, uncertainty, fuzziness associated with it. An excerpt of a forest map in Greece. Red lines delineate areas that used to be forests in Green lines delineate areas that are forests in the present time. Source: NCMA S.A.

28 Human-computer interfaces Adopted from Augmented Reality Trends Visualization of spatiotemporal data becomes more challenging in mobile device environments due to the relatively small size of the display areas, the limited storage and processing power of the devices, and the constraints in the data transfer speeds. Yet, mobile devices are the future.

29 Real-time interaction with spatiotemporal data Ideally, an analyst or a user would like to be able to get into the cloud of 3D spatiotemporal data, focus on a point of interest, analyze the values of variables at that point, and be able to look around to examine what happens in the neighborhood of that point. Adopted from Brovelli and Zamboni, 2014, Environmental space and time web analyzer, Proc. of the 2014 Conference on Big Data from Space, Frascati, Italy, Nov. 2014

30 Attica, Greece. Image from satellite Sentinel-1 (Source: ESA) Summary and conclusions The Copernicus data comprise an extremely rich source of data that may be used in everyday applications. Their use, however, would benefit greatly by improvements in: Integrating Copernicus data with other types of data (e.g. INSPIRE, statistical) Enhancing current visualization tools (animations, time frames, multiple windows etc.) Improving methods for detecting, managing, and displaying changes Developing methods for detecting and tracking features or objects of interest Resolving issues that arise from multiple spatial and spectral resolutions Developing methods for visualizing error, uncertainty and fuzziness in the data Enhancing the human-computer interface functionality Developing innovative tools for interactively exploring and analyzing spatiotemporal data.

31 The NCMA Spatiotemporal Visualization Challenge in the Copernicus Masters 2015 Competition To promote the advancement of innovative ideas on visualizing spatiotemporal data, the NCMA sponsors the NCMA Spatiotemporal visualization challenge in the Copernicus Masters 2015 world-wide Competition. Submission of proposals (electronically): &anzeige=ncma.html Deadline: July 13, 2015 Information: The National Cadastre and Mapping Agency S.A. (Headquarters) Dr. Panos Lolonis Tel. +30 (210) Ε-mail: Disclaimers This work has been made within the scope of the project «Large-scale Demonstrators in Athens (LDA)», which is co-financed by the EC Enterprise and Industry Directorate General and is supported by GRNET, NOA, HAMAC and Atlantis S.A. The sole responsibility of the material of this presentation, however, lies with the author. The EC, the NCMA, and the supporting partners are not responsible for any use that may be made of the information contained therein. Acknowledgments Special thanks to my colleagues: John Kavvadas, Head of the NCMA Quality Control Division Manolis Papoutsakis, Member of the NCMA Forest and Natural Environment Directorate Liana Varela, Member of the NCMA Forest and Natural Environment Directorate for their precious help in creating part of the visual material of this presentation.