ALBERT

Description: One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real-time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real-time ground observations are not available. These include several international river locations in Africa: the Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (random forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measure-ment sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1km; a large floodplain area and in flooded forest, a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; leaf area index 〉 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. This work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

Description: This paper presents an automated technique which ingests orbital synthetic-aperture radar (SAR) imagery and outputs surface water maps in near real time and on a global scale. The service anticipates future open data dissemination of water extent information using the European Space Agency's Sentinel-1 data. The classification methods used are innovative and practical and automatically calibrated to local conditions per 1 × 1° tile. For each tile, a probability distribution function in the range between being covered with water or being dry is established based on a long-term SAR training dataset. These probability distributions are conditional on the backscatter and the incidence angle. In classification mode, the probability of water coverage per pixel of 1 km × 1 km is calculated with the input of the current backscatter – incidence angle combination. The overlap between the probability distributions of a pixel being wet or dry is used as a proxy for the quality of our classification. The service has multiple uses, e.g. for water body dynamics in times of drought or for urgent inundation extent determination during floods. The service generates data systematically: it is not an on-demand service activated only for emergency response, but instead is always up-to-date and available. We validate its use in flood situations using Envisat ASAR information during the 2011 Thailand floods and the Pakistan 2010 floods and perform a first merge with a NASA near real time water product based on MODIS optical satellite imagery. This merge shows good agreement between these independent satellite-based water products.

Description: This paper presents an automated technique, embedded in an online service, which ingests orbital synthetic aperture radar (SAR) imagery and outputs surface water maps in near real time and on a global scale. The service anticipates future open data dissemination of water extent information using the European Space Agency's Sentinel-1 data. The classification methods used are innovative but practical and different per 1 × 1 degree tile. For each tile, a probability distribution function of a pixel, being covered with water or being dry is established based on a long SAR training dataset. These probability distributions are conditional on the backscatter and the incidence angle. In classification mode the probability of water coverage is calculated, conditional on the current backscatter – incidence angle combination. The overlap between the probability distributions of a pixel being wet or dry is used as a proxy for the quality of our classification. The service has multiple uses, e.g. for water body dynamics in times of drought or for urgent inundation extent determination during floods. The service generates data systematically: it is not an on-demand service activated only for emergency response, but instead is always up-to-date and available. We demonstrate its use in flood situations using Envisat ASAR information during the 2011 Thailand floods. A first merge with a NASA near real time water product based on MODIS optical satellite imagery shows excellent agreement between these independent satellite-based water products.

Description: One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real time ground observations are not available. These include several international river locations in Africa: Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (Random Forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measurement sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1 km; a large floodplain area and in flooded forest; with a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; Leaf Area Index 〉 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. The work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

Description: Detailed geological mapping of portions of the Thaumasia Fossae and Aeolis Quandrangles has documented several interesting relationships between valley development and local geology. Formation of the valley development was discussed.

Description: I offer here the speculative genetic hypothesis that the flat-floored landforms represent episodically active, sediment-laden valley glaciers formed by localized geothermal melting of abundant interstitial ice (permafrost) in a fine-grained sedimentary terrain. Geothermal melting may also localize spring heads for the narrow deep, high-gradient valleys, or the collapse process itself may result in the generation of decanted, relatively sediment-poor overland water flows (some local evidence of fluid overtopping of the localized depressions exists). Whatever the generic mechanisms for the suite of valley landforms, perhaps the most interesting observation is simply their youth. In aggregate, the morphologies are similar to the ancient valley systems cited as evidence for a previously much denser atmosphere on Mars.

Description: As part of a detailed study of the geological and geomorphological evolution of Aeolis Quadrangle, I have encountered evidence suggesting that near surface ice exists at low latitudes and was formed by partial or complete freezing of an inland sea. The area of interest is centered at approximately -2 deg, 196 deg. As seen in a suite of Viking Orbiter frames obtained at a range of approximately 600 km, the plains surface at this location is very lightly cratered or uncratered, and it is thus of late Amazonian age. Extant topographic data indicate that the Amazonian plains at this location occupy a trough whose surface lies at least 1000 m below the Mars datum. A reasonable hypothesis is that quite recent surface water releases, perhaps associated with final evolution of large 'outflow chasms' to the south, but possibly from other source areas, filled this trough, that ice floes formed almost immediately, and that either grounded ice or an ice-covered sea still persists. A reasonable hypothesis is that quite recent surface water releases, perhaps associated with final evolution of large 'outflow chasms' to the south, but possibly from other source areas, filled this trough, that ice floes formed almost immediately, and that either grounded ice or an ice-covered sea still persists. In either case, the thin (a few meters at most) high albedo, low thermal inertia cover of aeolian materials was instrumental in allowing ice preservation, and at least the lower portions of this dust cover may be cemented by water ice. Detailed mapping using Viking stereopairs and quantitative comparisons to terrestrial shelf ice geometries are underway.

Description: Since the beginning of operation of the MODIS instrument on the NASA Terra satellite at the end of 1999, an exceptionally useful sensor and public data stream have been available for many applications including the rapid and precise characterization of terrestrial surface water changes. One practical application of such capability is the near-real time mapping of river flood inundation. We have developed a surface water mapping methodology based on using only bands 1 (620-672 nm) and 2 (841-890 nm). These are the two bands at 250 m, and the use of only these bands maximizes the resulting map detail. In this regard, most water bodies are strong absorbers of incoming solar radiation at the band 2 wavelength: it could be used alone, via a thresholding procedure, to separate water (dark, low radiance or reflectance pixels) from land (much brighter pixels) (1, 2). Some previous water mapping procedures have in fact used such single band data from this and other sensors that include similar wavelength channels. Adding the second channel of data (band 1), however, allows a band ratio approach which permits sediment-laden water, often relatively light at band 2 wavelengths, to still be discriminated, and, as well, provides some removal of error by reducing the number of cloud shadow pixels that would otherwise be misclassified as water.