Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

Impact of Northern Hemisphere snow on the Arctic Ocean in a climate model

A present day control integration performed with the Hadley Centre's coupled climate model HadGEM1.2 experiences a large salinity bias in the Arctic Ocean when compared to in situ observations. Such a large salinity bias may have implications for both Arctic and Atlantic Ocean circulation. Large differences are seen between the runoff in HadGEM and the observations from the Global Runoff Data Centre, in particular in the Lena catchment, which could account for this salinity bias. We suggest that this discrepancy in runoff is, at least in part, due to a lack of snow accumulation in the model. The model climatology is very different to those obtained by remote sensing, such as the Global Snow Water Equivalent Climatology (NSIDC) and GlobSnow (ESA).

End-to-end validation of EPS / MetOp GOME-2 trace gas data

Within the next decade, the improved version 2 of Global Ozone Monitoring Experiment (GOME-2), a ultraviolet-visible spectrometer dedicated to the observation of key atmospheric trace species from space, will be launched successively on board three EUMETSAT Polar System (EPS) MetOp satellites. Starting with the launch of MetOp-1 scheduled for summer 2006, the GOME-2 series will extend till 2020 the global monitoring of atmospheric composition pioneered with ERS-2 GOME-1 since 1995 and enhanced with Envisat SCIAMACHY since 2002 and EOS-Aura OMI since 2004. For more than a decade, an international pool of scientific teams active in ground-and space-based ultraviolet-visible remote sensing have contributed to the successful post-launch validation of trace gas data products and the associated maturation of retrieval algorithms for the latter satellites, ensuring that geophysical data products are/become reliable and accurate enough for intended research and applications. Building on this experience, this consortium plans now to develop and carry out appropriate validation of a list of GOME-2 trace gas column data of both tropospheric and stratospheric relevance: nitrogen dioxide (NO 2), ozone (O 3), bromine monoxide (BrO), chlorine dioxide (OClO), formaldehyde (HCHO), and sulphur dioxide (SO 2). The proposed investigation will combine four complementary approaches resulting in an end-to-end validation of expected column data products.

Lidar observation campaign of sugar cane fires and industrial emissions in the State of São Paulo, Brazil

Brazil has an important role in the biomass burning, with the detection of approximately 100,000 burning spots in a single year (2007). Most of these spots occur in the southern part of the Amazon basin during the dry season (from August to november) and these emissions reach the southeast of the country, a highly populated region and with serious urban air pollution problems. With the growing demand on biofuels, sugarcane is considerably expanding in the state of São Paulo, being a strong contributor to the bad air quality in this region. In the state of São Paulo, the main land use are pasture and sugarcane crop, that covers around 50% and 10% of the total area, respectively. Despite the aerosol from sugarcane burning having reduced atmospheric residence time, from a few days to some weeks, they might get together with those aerosol which spread over long distances (hundreds to thousands of kilometers). In the period of June through February 2010 a LIDAR observation campaign was carried in the state of São Paulo, Brazil, in order to observe and characterize optically the aerosols from two distinct sources, namely, sugar cane biomass burning and industrial emissions. For this purpose 2 LIDAR systems were available, one mobile and the other placed in a laboratory, both working in the visible (532 nm) and additionally the mobile system had a Raman channel available (607 nm). Also this campaign counted with a SODAR, a meteorological RADAR specially set up to detect aerosol echoes and gas-particle analyzers. To guarantee a good regional coverage 4 distinct sites were available to deploy the instruments, 2 in the near field of biomass burning activities (Rio Claro and Bauru), one for industrial emissions (Cubatão) and others from urban sources (São Paulo). The whole campaign provide the equivalent of 30 days of measurements which allowed us to get aerosol optical properties such as backscattering/extinction coefficients, scatter and LIDAR ratios, those were used to correlate with air quality and meteorological indicators and quantities. In this paper we should focus on the preliminary results of the Raman LIDAR system and its derived aerosol optical quantities. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Initial analysis from a Lidar observation campaign of sugar cane fires in the central and western portion of the S̃ao Paulo State - Brazil

The central and western portion of the S̃ao Paulo State has large areas of sugar cane plantations, and due to the growing demand for biofuels, the production is increasing every year. During the harvest period some plantation areas are burnt a few hours before the manual cutting, causing significant quantities of biomass burning aerosol to be injected into the atmosphere. During August 2010, a field campaign has been carried out in Ourinhos, situated in the south-western region of S̃ao Paulo State. A 2-channel Raman Lidar system and two meteorological S-Band Doppler Radars are used to indentify and quantify the biomass burning plumes. In addiction, CALIPSO Satellite observations were used to compare the aerosol optical properties detected in that region with those retrieved by Raman Lidar system. Although the campaign yielded 30 days of measurements, this paper will be focusing only one case study, when aerosols released from nearby sugar cane fires were detected by the Lidar system during a CALIPSO overpass. The meteorological radar, installed in Bauru, approximately 110 km northeast from the experimental site, had recorded echoes (dense smoke comprising aerosols) from several fires occurring close to the Raman Lidar system, which also detected an intense load of aerosol in the atmosphere. HYSPLIT model forward trajectories presented a strong indication that both instruments have measured the same air masss parcels, corroborated with the Lidar Ratio values from the 532 nm elastic and 607 nm Raman N2 channel analyses and data retrieved from CALIPSO have indicated the predominance of aerosol from biomass burning sources. © 2011 SPIE.

Fototriangulação em bloco de imagens orbitais com modelos rigorosos baseados em pontos e retas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Topografia convencional na aferição de áreas obtidas por georreferenciamento e Google Earth

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Investigations into the degassing and eruption mechanisms of Nyamuragira volcano, Democratic Republic of the Congo (Africa)

One of two active volcanoes in the western branch of the East African Rift, Nyamuragira (1.408ºS, 29.20ºE; 3058 m) is located in the D.R. Congo. Nyamuragira emits large amounts of SO2 (up to ~1 Mt/day) and erupts low-silica, alkalic lavas, which achieve flow rates of up to ~20 km/hr. The source of the large SO2 emissions and pre-eruptive magma conditions were unknown prior to this study, and 1994-2010 lava volumes were only recently mapped via satellite imagery, mainly due to the region’s political instability. In this study, new olivine-hosted melt inclusion volatile (H2O, CO2, S, Cl, F) and major element data from five historic Nyamuragira eruptions (1912, 1938, 1948, 1986, 2006) are presented. Melt compositions derived from the 1986 and 2006 tephra samples best represent pre-eruptive volatile compositions because these samples contain naturally glassy inclusions that underwent less post-entrapment modification than crystallized inclusions. The total amount of SO2 released from the 1986 (0.04 Mt) and 2006 (0.06 Mt) eruptions are derived using the petrologic method, whereby S contents in melt inclusions are scaled to erupted lava volumes. These amounts are significantly less than satellite-based SO2 emissions for the same eruptions (1986 = ~1 Mt; 2006 = ~2 Mt). Potential explanations for this observation are: 1) accumulation of a vapor phase within the magmatic system that is only released during eruptions, and/or 2) syn-eruptive gas release from unerupted magma. Post-1994 Nyamuragira lava volumes were not available at the beginning of this study. These flows (along with others since 1967) are mapped with Landsat MSS, TM, and ETM+, Hyperion, and ALI satellite data and combined with published flow thicknesses to derive volumes. Satellite remote sensing data was also used to evaluate Nyamuragira SO2 emissions. These results show that the most recent Nyamuragira eruptions injected SO2 into the atmosphere between 15 km (2006 eruption) and 5 km (2010 eruption). This suggests that past effusive basaltic eruptions (e.g., Laki 1783) are capable of similar plume heights that reached the upper troposphere or tropopause, allowing SO2 and resultant aerosols to remain longer in the atmosphere, travel farther around the globe, and affect global climates.

Virtual Cilicia Project. How to use Google Earth as a visualization environment in an archaeological context

Over the past few years, archaeology has experienced a rapid development in geophysical prospection and remote sensing techniques. At the same time, the focus of archaeological research has shifted to landscape evelopment and human interaction. To impart the results, new methods and techniques are necessary. Virtual globes such as Google Earth offer fascinating methods of giving interested amateurs the possibility to interactively explore ancient cities and landscapes. Thanks to the increasing usage of GIS in cultural heritage, the implementation of interactive three dimensional learning opportunities becomes less and less tedious, but the non-linear narrative story telling medium demands for a special adaption of the content. This paper summarizes the experience gained during the realization of the “Virtual Cilicia Project” and outlines the future potential of virtual globes in the field of cultural heritage.

Terrestrial Radar Interferometric Measurement of Hillslope Deformation and Atmospheric Disturbances in the Illgraben Debris-Flow Catchment, Switzerland

We describe a method for rapid identification and precise quantification of slope deformation using a portable radar interferometer. A rockslide with creep-like behavior was identified in the rugged and inaccessible headwaters of the Illgraben debris-flow catchment, located in the Central Swiss Alps. The estimated volume of the moving rock mass was approximately 0.5 x 10(6) m(3) with a maximum daily (3-D) displacement rate of 3 mm. Fast scene acquisition in the order of 6 s/scene led to uniquely precise mapping of spatial and temporal variability of atmospheric phase delay. Observations led to a simple qualitative model for prediction of atmospheric disturbances using a simple model for solar radiation, which can be used for advanced campaign planning for short observation periods (hours to days).

Discription of coastal shape at Bykovsky Peninsula

This article presents a comparison of sediment input by rivers and by coastal erosion into both the Laptev Sea and the Canadian Beaufort Sea (CBS). New data on coastal erosion in the Laptev Sea, which are based on field measurements and remote sensing information, and existing data on coastal erosion in the CBS as well as riverine sediment discharge into both the Laptev Sea and the CBS are included. Strong regional differences in the percentages of coastal erosion and riverine sediment supply are observed. The CBS is dominated by the riverine sediment discharge (64.45210**6 t/a) mainly of the Mackenzie River, which is the largest single source of sediments in the Arctic. Riverine sediment discharge into the Laptev Sea amounts to 24.10210**6 t/a, more than 70% of which are related to the Lena River. In comparison with the CBS, the Laptev Sea coast on average delivers approximately twice as much sediment mass per kilometer, a result of higher erosion rates due to higher cliffs and seasonal ice melting. In the Laptev Sea sediment input by coastal erosion (58.4210**6 t/a) is therefore more important than in the CBS and the ratio between riverine and coastal sediment input amounts to 0.4. Coastal erosion supplying 5.6210**6 t/a is less significant for the sediment budget of the CBS where riverine sediment discharge exceeds coastal sediment input by a factor of ca. 10.

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

(Table 1) Mean temperatures in january and july, and total annual snowfall at Great Bear Lake and Great Slave Lake, Canada

The sensitivity of brightness temperature (T(B)) at 6.9, 10.7, and 18.7 GHz from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) observations is investigated over five winter seasons (2002-2007) on Great Bear Lake and Great Slave Lake, Northwest Territories, Canada. The T(B) measurements are compared to ice thicknesses obtained with a previously validated thermodynamic lake ice model. Lake ice thickness is found to explain much of the increase of T(B) at 10.7 and 18.7 GHz. T(B) acquired at 18.7 GHz (V-pol) and 10.7 GHz (H-pol) shows the strongest relation with simulated lake ice thickness over the period of study (R**2 > 0.90). A comparison of the seasonal evolution of T(B) for a cold winter (2003-2004) and a warm winter (2005-2006) reveals that the relationship between T(B) and ice growth is stronger in the cold winter (2003-2004). Overall, this letter shows the high sensitivity of T(B) to ice growth and, thus, the potential of AMSR-E mid-frequency channels to estimate ice thickness on large northern lakes.