Automatic Open Water Flood Detection from Sentinel-1 Multi-Temporal Imagery

Many technical infrastructure operators manage facilities distributed over large areas. They face the problem of finding out if a flood hit a specific facility located in the open countryside. Physical inspection after every heavy rain is time and personnel consuming, and equipping all facilities with flood detection is expensive. Therefore, methods are being sought to ensure that these facilities are monitored at a minimum cost. One of the possibilities is using remote sensing, especially radar data regularly scanned by satellites. A significant challenge in this area was the launch of Sentinel-1 providing free-of-charge data with adequate spatial resolution and relatively high revisit time. This paper presents a developed automatic processing chain for flood detection in the open landscape from Sentinel-1 data. Flood detection can be started on-demand; however, it mainly focuses on autonomous near real-time monitoring. It is based on a combination of algorithms for multi-temporal change detection and histogram thresholding open-water detection. The solution was validated on five flood events in four European countries by comparing its results with flood delineation derived from reference datasets. Long-term tests were also performed to evaluate the potential for a false positive occurrence. In the statistical classification assessments, the mean value of user accuracy (producer accuracy) for open-water class reached 83% (65%). The developed solution typically provided flooded polygons in the same areas as the reference dataset, but of a smaller size. This fact is mainly attributed to the use of universal sensitivity parameters, independent of the specific location, which ensure almost complete successful suppression of false alarms

UTILIZATION OF LARGE SCALE SURFACE MODELS FOR DETAILED VISIBILITY ANALYSES

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses

Tracking Hurricanes using GPS atmospheric precipitable water vapor field

Tropical cyclones are one of the most powerful severe weather events that produce devastating socioeconomic and environmental impacts in the areas they strike. Therefore, monitoring and tracking of the arrival times and path of the tropical cyclones are extremely valuable in providing early warning to the public and governments. Hurricane Florence struck the East cost of USA in 2018 and offers an outstanding case study. We employed Global Positioning System (GPS) derived precipitable water vapor (PWV) data to track and investigate the characteristics of storm occurrences in their spatial and temporal distribution using a dense ground network of permanent GPS stations. Our findings indicate that a rise in GPS-derived PWV occurred several hours before Florence’s manifestation. Also, we compared the temporal distribution of the GPS-derived PWV content with the precipitation value for days when the storm appeared in the area under influence. The study will contribute to quantitative assessment of the complementary GPS tropospheric products in hurricane monitoring and tracking using GPS-derived water vapor evolution from a dense network of permanent GPS station

The First PPP-Based GPS Water Vapor Real-Time Monitoring System in Pearl-River-Delta Region, China

China Satellite Navigation Conference (CSNC) 2013, Wuhan, China, 15-17 May 2013The first Precipitable Water Vapor Real-Time Monitoring System (PWVRMS) based on Global Positioning System Precise Point Positioning (PPP) technique has been developed for the Pearl-River-Delta region. This PWVRMS system estimates GPS satellite clock error data in real-time while using International GNSS Service (IGS) predicted precise satellite orbit directly. Currently it processes GPS data every 10 min on a daily basis from three networks in Pearl-River-Delta region: Hong Kong SatRef GPS network, Macao MoSRef GPS network and Guangdong CORS network. Compared to traditional double-differencing technique, the advantage of using PPP technique is that (1) the PWV estimation at each station is completely independent and is not affected by data quality at other stations; (2) the computation is much faster and simpler. This PWVRMS system is evaluated using radiosonde water vapor data. The GPS PWV accuracy is about 2.20 mm though the GPS station is 4.1 km away from the radiosonde. It is expected the actual GPS PWV accuracy should be higher if the GPS station is collocated with the radiosonde station. The real-time PWV products can be widely used in weather forecasts, climate researches, and water vapor correction for remote sensing images such as SAR applications. Currently the PWVRMS supplies real-time water vapor data to several meteorological agencies in Pearl-River-Delta region including Hong Kong Observatory, Macao Meteorological and Geophysical Bureau, Shenzhen Meteorological Bureau and Guangdong Meteorological Bureau for their weather forecasting service and research.Department of Land Surveying and Geo-Informatic

advanced gnss processing techniques working group 1

Over the last decade, near real-time analysis of GPS data has become a well-established atmospheric observing tool, primarily coordinated by the EIG EUMETNET GPS Water Vapour Programme (E-GVAP) in Europe. In the near future, four operational GNSS will be available for commercial and scientific applications with atmospheric science benefiting from new signals from up to 60 satellites observed at any one place and time, however, many challenges remain regarding their optimal combined utilization. Besides raw data streaming, recent availability of precise real-time orbit and clock corrections enable wide utilization of autonomous Precise Point Positioning (PPP), which is particularly efficient for high-rate, real-time and multi-GNSS analyses