Development of multi-purposes procedures and service tools for GNSS data processing finalized to monitor a deep-seated earthslide in the Dolomites (Italy)

The Corvara landslide is an active, large-scale, deep-seated and slow moving earthslide of about 30 Mm3 located in the Dolomites (Italy). It is frequently damaging a national road and, occasionally, isolated buildings and recre- ational ski facilities. In this work we present the analysis performed on data acquired thank to the installation of 3 DualFrequency GPS in permanent acquisition installed in the accumulation, track and source zone of the active portion of the landslide. In particular two years (2014 and 2015) of data were processed with several approaches and goals: daily time series were produced through Precise Point Positioning and Differential Positioning using both scientific packages and automatic on line tool based on open source libraries, specifically developed in order to provide a prototypal service. The achievable results based on single frequency (L1) data processing were also investigated in order to pave the way to the deployment of lowcost GPS receiver for this kind of application. Moreover, daily and sub-daily phenomena were analyzed. Different strategies were investigated in order to de- scribe the kinematics on the basis of 0.2 Hz data collected by the 3 permanent receivers. For particular events also the variometric approach, through the recent advances of VADASE, was applied, to detect significant movements. Finally, tropospheric parameters were estimated over the whole period in order to give a contribution to the SAR interferometry techniques. Also for this specific purpose and application, the possibilities of single frequency use were assessed

EURAC SDI: A Near Real Time and Offline Automatic Metadata Generation Processing Chain. GI_Forum 2013 – Creating the GISociety|

Scientists dealing with geospatial information usually work with huge sets of heterogeneous geographic data derived from different sources. Without a well-defined and organized structure they face problems in finding and reusing existing spatial data. Due to the increasing amount of collected data, the risk of data redundancy arises, which may cause data inconsistency, space issues and search difficulties. A spatial cataloguing system can facilitate a more efficient spatial data search as well as allowing data exchange with different institutions. Our proposed solution is implementing a spatial cataloguing system along with an automatic rule-based approach metadata generator that processes remote sensing data in Near Real Time (NRT) and simultaneously derives metadata. This paper will further describe how to extract the relevant metadata from the processed data and how we converted this heterogeneous metadata information into a common standardized format. A real-world scenario applied in The European Academy (EURAC) Research Institute for Applied Remote Sensing (IARS) illustrates the procedure of data processing and metadata generation

EURAC SDI: A Near Real Time and Offline Automatic Metadata Generation Processing Chain. GI_Forum 2013 – Creating the GISociety|

Scientists dealing with geospatial information usually work with huge sets of heterogeneous geographic data derived from different sources. Without a well-defined and organized structure they face problems in finding and reusing existing spatial data. Due to the increasing amount of collected data, the risk of data redundancy arises, which may cause data inconsistency, space issues and search difficulties. A spatial cataloguing system can facilitate a more efficient spatial data search as well as allowing data exchange with different institutions. Our proposed solution is implementing a spatial cataloguing system along with an automatic rule-based approach metadata generator that processes remote sensing data in Near Real Time (NRT) and simultaneously derives metadata. This paper will further describe how to extract the relevant metadata from the processed data and how we converted this heterogeneous metadata information into a common standardized format. A real-world scenario applied in The European Academy (EURAC) Research Institute for Applied Remote Sensing (IARS) illustrates the procedure of data processing and metadata generation

Snow cover maps from MODIS images at 250 m resolution, part 1: Algorithm description

A new algorithm for snow cover monitoring at 250 m resolution based on Moderate Resolution Imaging Spectroradiometer (MODIS) images is presented. In contrast to the 500 m resolution MODIS snow products of NASA (MOD10 and MYD10), the main goal was to maintain the resolution as high as possible to allow for a more accurate detection of snow covered area (SCA). This is especially important in mountainous regions characterized by extreme landscape heterogeneity, where maps at a resolution of 500 m could not provide the desired amount of spatial details. Therefore, the algorithm exploits only the 250 m resolution bands of MODIS in the red (B1) and infrared (B2) spectrum, as well as the Normalized Difference Vegetation Index (NDVI) for snow detection, while clouds are classified using also bands at 500 m and 1 km resolution. The algorithm is tailored to process MODIS data received in real-time through the EURAC receiving station close to Bolzano, Italy, but also standard MODIS products are supported. It is divided into three steps: first the data is preprocessed, including reprojection, calculation of physical reflectance values and masking of water bodies. In a second step, the actual classification of snow, snow in forested areas, and clouds takes place based on MODIS images both from Terra and Aqua satellites. In the third step, snow cover maps derived from images of both sensors of the same day are combined to reduce cloud coverage in the final SCA product. Four different quality indices are calculated to verify the reliability of input data, snow classification, cloud detection and viewing geometry. Using the data received through their own station, EURAC can provide SCA maps of central Europe to end users in near real-time. Validation of the algorithm is outlined in a companion paper and indicates good performance with accuracies ranging from 94% to around 82% compared to in situ snow depth measurements, and around 93% compared to SCA derived from Landsat ETM+ images

Snow cover maps from MODIS images at 250 m resolution, part 2: Validation

The performance of a new algorithm for binary snow cover monitoring based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images at 250 m resolution is validated using snow cover maps (SCA) based on Landsat 7 ETM+ images and in situ snow depth measurements from ground stations in selected test sites in Central Europe. The advantages of the proposed algorithm are the improved ground resolution of 250 m and the near real-time availability with respect to the 500 m standard National Aeronautics and Space Administration (NASA) MODIS snow products (MOD10 and MYD10). It allows a more accurate snow cover monitoring at a local scale, especially in mountainous areas characterized by large landscape heterogeneity. The near real-time delivery makes the product valuable as input for hydrological models, e.g., for flood forecast. A comparison to sixteen snow cover maps derived from Landsat ETM/ETM+ showed an overall accuracy of 88.1%, which increases to 93.6% in areas outside of forests. A comparison of the SCA derived from the proposed algorithm with standard MODIS products, MYD10 and MOD10, indicates an agreement of around 85.4% with major discrepancies in forested areas. The validation of MODIS snow cover maps with 148 in situ snow depth measurements shows an accuracy ranging from 94% to around 82%, where the lowest accuracies is found in very rugged terrain restricted to in situ stations along north facing slopes, which lie in shadow in winter during the early morning acquisition

An Assessment of the Solar Potential of Roofs within a Web-based Solar Cadastre. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

Solar technologies offer clean and sustainable energy production at an affordable cost. Therefore, their use is rapidly growing, and private users as well as local authorities demonstrate wide interest in identifying areas suitable for mounting solar modules. The recent improvements of remote sensing techniques such as LIDAR (Light Detection and Ranging), are very attractive and suitable for solar potential assessment; however, it is of paramount importance to transfer the knowledge to the public. The proposed solution includes the development of an interactive tool, Solar WebGIS, which can analyse and visualize solar potential characteristics. Furthermore, the article discusses the data preparation, integration, and visualization issue related to the WebGIS

OpenEO: a Common, Open Source Interface Between Earth Observation Data Infrastructures and Front-End Applications

The objective of the openEO consortium is to build a common, open source interface that facilitates standardized interchange between users and applications of Copernicus and other EO data as hosted by an increasing number of cloud providers. The openEO interface will consist of three layers of Application Programming Interfaces (APIs) that connect applications of several front office clients with various back office drivers (see Figure 1 ). This will simplify the use of cloud-based EO processing engines, allow switching between cloud-based back office providers and comparing them, and enable reproducible, open EO science. Thereby, openEO reduces the entry barriers for the adaptation of cloud computing technologies by a broad user community and paves the way for the federation of EO data infrastructure capabilities.JRC.I.3-Text and Data Minin

Integration of X-band SAR interferometry , continuous and periodic D-GPS and in-place inclinometers to characterize and monitor a deep-seated earthslide in the Dolomites ( Italy )

The Corvara landslide is an active, large-scale, deep-seated and slow moving earthslide of about 30 Mm3 located in the Dolomites (Italy). It is frequently damaging a national road and, occasionally, isolated buildings and recreational ski facilities. Since the mid ‘90s it has been mapped, dated and monitored thanks to field surveys, boreholes, radiocarbon dating, inclinometers, piezometers and periodic D-GPS measurements, carried out by the Geology and the Forestry Planning offices of the Autonomous Province of Bolzano, the Municipality of Corvara in Badia, the University of Modena and Reggio Emilia, the IRPI-CNR of Padua. In 2013, a new phase of characterization and monitoring has started which also involves the EURAC’s Institute for Applied Remote Sensing, the geodesy group of University La Sapienza, the CNR-IREA of Naples and the Leica Geosystems office in Italy. This new phase of characterization and monitoring is meant to investigate the opportunities of innovative SAR interferometry, D-GPS and in-place inclinometers techniques to provide for a high frequency monitoring of the study site in support to the analysis of the investigation of forcing factors leading unsteady, nonuniform landslide motion through different seasons of the year. Monitoring results are also expected to provide a validation of innovative interferometric techniques so to fully evaluate their conformity to be used as a long-term monitoring system in land-use planning and risk management procedures. The monitoring infrastructure now integrates: 16 Corner Reflector for satellite X-Band SAR interferometric products, 13 benchmarks for D-GPS periodic surveys, three on-site GPS receivers for continuous positioning and remote ftp data pushing, two in-place inclinometers and a pressure transducer to record pore-pressure variations. The coupling of SAR-based products with GPS records is achieved using especially designed Corner Reflectors having an appendix dedicated to hold Dual-Frequency GPS antennas. COSMO-SkyMed X-Band SAR acquisitions started on October 2013 and are ongoing with a temporal resolution of 16 days using STRIPMAP (HIMAGE) measuring mode. Discontinuous D-GPS Fast-Static surveys are scheduled with a triple frequency: annual for 24 points outside recent activation areas, monthly for 13 points in the active zone and a bi-weekly for 6 points located in the most active zone. Displacement high-frequency data are acquired thank to the installation of 3 Dual-Frequency GPS in permanent acquisition that have been located in the accumulation, track and source zone of the active portion of the landslide. High frequency data are also obtained by the two inclinometers operating in continuous acquisition located across the main slide surface at 48 m depth into a 90 m borehole drilled in the accumulation zone. A piezometer installed in the source zone and the meteorological station of Piz La Ila (3 km far away) of the Autonomous Province of Bolzano complete the system