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FOSS4G 2016 Proceedings: Academic Program - selected papers and posters
This Conference Proceedings is a collection of selected papers and posters submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G 2016), 24th to 26th August 2016 in Bonn, Germany.
Like in previous FOSS4G conferences on national and international level the academic papers and posters cover an extensive wide range of topics reflecting the contribution of the academia to this field by the development of open source software components, in the design of open standards, in the proliferation of web-based solutions, in the dissemination of the open principles important in science and education, or in the collection and the hosting of freely available geo-data
Applications of ISES for vegetation and land use
Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management
InSAR-Informed In-Situ Monitoring for Deep-Seated Landslides
This work focuses on assessing the fidelity of Interferometric Synthetic
Aperture Radar (InSAR) as it relates to subsurface ground motion monitoring, as
well as understanding uncertainty in modeling active landslide scarp
displacement for the case study of the in situ monitored El Forn deep seated
landslide in Canillo, Andorra. We used the available Sentinel 1 data on the
Alaska Satellite Facility (ASF) Vertex platform to create deformation velocity
maps and time series of the El Forn landslide scarp. We compared the
performances of InSAR data from the recently launched European Ground Motion
Service (EGMS) platform and the ASF Vertex Platform in a time series comparison
of displacement in the direction of landslide motion with in situ borehole
based measurements from 2019 to 2021, suggesting that ground motion detected
through InSAR can be used in tandem with field monitoring to provide optimal
information with minimum in situ deployment. While identification of active
landslide scarps may be possible via the use of EGMS platform, the intents and
purposes of this work are in assessment of InSAR as a monitoring tool. Based on
that, geospatial interpolation with statistical analysis was conducted to
better understand the necessary number of in situ observations needed to lower
error on a remote sensing recreation of ground motion over the entirety of a
landslide scarp, suggesting between 20 to 25 total observations provides the
optimal normalized root mean squared error for an ordinarily kriged model of
the El Forn landslide scarp
ALOS-2 L-band SAR backscatter data improves the estimation and temporal transferability of wildfire effects on soil properties under different post-fire vegetation responses
Remote sensing techniques are of particular interest for monitoring wildfire effects on soil properties, which may be highly context-dependent in large and heterogeneous burned landscapes. Despite the physical sense of synthetic aperture radar (SAR) backscatter data for characterizing soil spatial variability in burned areas, this approach remains completely unexplored. This study aimed to evaluate the performance of SAR backscatter data in C-band (Sentinel-1) and L-band (ALOS-2) for monitoring fire effects on soil organic carbon and nutrients (total nitrogen and available phosphorous) at short term in a heterogeneous Mediterranean landscape mosaic made of shrublands and forests that was affected by a large wildfire. The ability of SAR backscatter coefficients and several band transformations of both sensors for retrieving soil properties measured in the field in immediate post-fire situation (one month after fire) was tested through a model averaging approach. The temporal transferability of SAR-based models from one month to one year after wildfire was also evaluated, which allowed to assess short-term changes in soil properties at large scale as a function of pre-fire plant community type. The retrieval of soil properties in immediate post-fire conditions featured a higher overall fit and predictive capacity from ALOS-2 L-band SAR backscatter data than from Sentinel-1 C-band SAR data, with the absence of noticeable under and overestimation effects. The transferability of the ALOS-2 based model to one year after wildfire exhibited similar performance to that of the model calibration scenario (immediate post-fire conditions). Soil organic carbon and available phosphorous content was significantly higher one year after wildfire than immediately after the fire disturbance. Conversely, the short-term change in soil total nitrogen was ecosystem-dependent. Our results support the applicability of L-band SAR backscatter data for monitoring short-term variability of fire effects on soil properties, reducing data gathering costs within large and heterogeneous burned landscapesS
Εκτίμηση Εδαφικής Υγρασίας από Πολυφασματικά και Ραντάρ Δορυφορικά Δεδομένα με χρήση του Google Earth Engine και Τεχνικών Μηχανικής Μάθησης
Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική
Radar and multispectral remote sensing data accurately estimate vegetation vertical structure diversity as a fire resilience indicator
The structural complexity of plant communities contributes to maintaining the
ecosystem functioning in fire-prone landscapes and plays a crucial role in driving
ecological resilience to fire. The objective of this study was to evaluate the
resilience to fire off several plant communities with reference to the temporal
evolution of their vertical structural diversity (VSD) estimated from the data
fusion of C-band synthetic aperture radar (SAR) backscatter (Sentinel-1) and
multispectral remote sensing reflectance (Sentinel-2) in a burned landscape of
the western Mediterranean Basin. We estimated VSD in the field 1 and 2 years
after fire using Shannon’s index as a measure of vertical heterogeneity in vegetation
structure from the vegetation cover in several strata, both in burned and
unburned control plots. Random forest (RF) was used to model VSD in the
control (analogous to prefire scenario) and burned plots (1 year after fire)
using as predictors (i) Sentinel-1 VV and VH backscatter coefficients and (ii)
surface reflectance of Sentinel-2 bands. The transferability of the RF model
from 1 to 2 years after wildfire was also evaluated. We generated VSD prediction
maps across the study site for the prefire scenario and 1 to 4 years postfire.
RF models accurately explained VSD in unburned control plots (R2 = 87.68;
RMSE = 0.16) and burned plots 1 year after fire (R2 = 80.48; RMSE = 0.13).
RF model transferability only involved a reduction in the VSD predictive capacity
from 0.13 to 0.20 in terms of RMSE. The VSD of each plant community
4 years after the fire disturbance was significantly lower than in the prefire scenario.
Plant communities dominated by resprouter species featured significantly
higher VSD recovery values than communities dominated by facultative or obligate
seeders. Our results support the applicability of SAR and multispectral data
fusion for monitoring VSD as a generalizable resilience indicator in fire-prone
landscapes.SIEuropean Regional Development Fund (ERDF)Spanish Ministry of Economy and CompetitivenessRegional Government of Castilla and LeónBritish Ecological Societ
Article Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing
Abstract: This paper presents a Ship Monitoring System (SIMONS) working with Synthetic Aperture Radar (SAR) images. It is able to infer ship detection and classification information, and merge the results with other input channels, such as polls from the Automatic Identification System (AIS). Two main stages can be identified, namely: SAR processing and data dissemination. The former has three independent modules, which are related to Coastline Detection (CD), Ship Detection (SD) and Ship Classification (SC). The later is solved via an advanced web interface, which is compliant with the OpenSource standards fixed by the Open Geospatial Consortium (OGC). SIMONS has been designed to be a modular, unsupervised and reliable system that meets Near-Real Time (NRT) delivery requirements. From data ingestion to product delivery, the processing chain is fully automatic accepting ERS and ENVISAT formats. SIMONS has been developed by GMV Aerospace, S.A. with three main goals, namely: 1) To limit the dependence on the ancillary information provided by systems such as AIS. 2) To achieve the maximum level of automatism and restrict human manipulation. 3) To limit the error sources and their propagation
Community Review of Southern Ocean Satellite Data Needs
This review represents the Southern Ocean community’s satellite data needs for the coming decade. Developed through widespread engagement, and incorporating perspectives from a range of stakeholders (both research and operational), it is designed as an important community-driven strategy paper that provides the rationale and information required for future planning and investment. The Southern Ocean is vast but globally connected, and the communities that require satellite-derived data in the region are diverse. This review includes many observable variables, including sea-ice properties, sea-surface temperature, sea-surface height, atmospheric parameters, marine biology (both micro and
macro) and related activities, terrestrial cryospheric connections, sea-surface salinity, and a discussion of coincident and in situ data collection. Recommendations include commitment to data continuity, increase in particular capabilities (sensor types, spatial, temporal), improvements in dissemination of data/products/uncertainties, and innovation in calibration/validation capabilities. Full recommendations are detailed by variable as well as summarized. This review provides a starting point for scientists to understand more about Southern Ocean processes and their global roles, for funders to understand the desires of the community, for commercial operators to safely conduct their activities in the Southern Ocean, and for space agencies to gain greater impact from Southern Ocean-related acquisitions and missions.The authors acknowledge the Climate at the Cryosphere program and the Southern Ocean
Observing System for initiating this community effort, WCRP, SCAR, and SCOR for endorsing the effort, and CliC, SOOS, and SCAR for supporting authors’ travel for collaboration on the review. Jamie Shutler’s time on this review was funded by the European Space Agency project OceanFlux Greenhouse Gases Evolution (Contract number 4000112091/14/I-LG)
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