Ragweed Pollen Source Inventory for France - the Second Largest Centre of Ambrosia in Europe

France, in particular the Rhône-Alpes region, is one of the three main centres of ragweed (Ambrosia) in Europe. The aim of this study is to develop a gridded ragweed pollen source inventory for all of France that can be used in assessments, eradication plans and by atmospheric models for describing concentrations of airborne ragweed pollen. The inventory combines information about spatial variations in annual Ambrosia pollen counts, knowledge of ragweed ecology, detailed land cover information and a Digital Elevation Model. The ragweed inventory consists of a local infection level on a scale of 0–100% (where 100% is the highest plant abundance per area in the studied region) and a European infection level between 0% and 100% (where 100% relates to the highest identified plant abundance in Europe using the same methodology) that has been distributed onto the EMEP grid with 5 km × 5 km resolution. The results of this analysis showed that some of the highest mean annual ragweed pollen concentrations were recorded at Roussillon in the Rhône-Valley. This is reflected by the inventory, where the European infection level has been estimated to reach 67.70% of the most infected areas in Europe i.e. Kecskemét in central Hungary. The inventory shows that the Rhône Valley is the most heavily infected part of France. Central France is also infected, but northern and western parts of France are much less infected. The inventory can be entered into atmospheric transport models, in combination with other components such as a phenological model and a model for daily pollen release, in order to simulate the dispersion of ragweed pollen within France as well as potential long-distance transport from France to other European countries.

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, Digital Surface Models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub-metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. The paper describes the development of a LiDAR post-processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post-processing produces a Digital Terrain Model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially-distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR-derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ~1m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a 2D finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features such as buildings and roads as well as taller vegetation features such as trees and hedges. This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features.

The Namib Sand Sea digital database of aeolian dunes and key forcing variables

A new digital atlas of the geomorphology of the Namib Sand Sea in southern Africa has been developed. This atlas incorporates a number of databases including a digital elevation model (ASTER and SRTM) and other remote sensing databases that cover climate (ERA-40) and vegetation (PAL and GIMMS). A map of dune types in the Namib Sand Sea has been derived from Landsat and CNES/SPOT imagery. The atlas also includes a collation of geochronometric dates, largely derived from luminescence techniques, and a bibliographic survey of the research literature on the geomorphology of the Namib dune system. Together these databases provide valuable information that can be used as a starting point for tackling important questions about the development of the Namib and other sand seas in the past, present and future.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

NDVI With Artificial Neural Networks For SRTM Elevation Model Improvement – Hydrological Model Application

Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Monitoramento geoambiental do estuário do Rio Paraíba do Norte - PB por meio da cartografia temática digital e de produtos de sensoriamento remoto

The North Paraíba River Estuary, located in the eastern portion of the Paraíba State, Northeast Brazil, on coordinates 34º50 00 -34º57 30 S and 6º55 00 -7º7 30 W, constitutes a fluvio-marine plain formed by the North Paraíba River and its tributaries Sanhauá, Paroeira, Mandacaru, Tiriri, Tambiá, Ribeira and Guia. This estuary comprises an area of about 260 km2. Increasing human demands on the estuary area and inadequate environment managing have generated conflicts. The present work main purpose is to evaluate the geodynamic evolution of the North Paraíba River Estuary in the period from 1969 to 2001, using digital image processing techniques, thematic digital cartography and multitemporal data integration, combined to geological-geophysical field surveys. The SUDENE cartographic database, converted to digital format were, used to obtain occupation and topographic maps from 1969 and to generate a Digital Elevation Model (DEM). Digital Landsat 7 ETM+ and Spot HRVIR-PAN satellite images interpretation allowed the environmental characterization of the estuary. The most important digital processing results were achieved color composites RGB 5-4-3, 5-3-1, 5-2-NDWI and band ratio 7/4-5/3-4/2, 5/7-3/1-5/4). In addition the fusion image technique RGBI was used by the inclusion of the Spot HRVRI and Landsat 7 ETM+ panchromatic band on I layer with RGB triplets 5-4-3, 5-3-1 and 5/7-3/1-5/4. The DEM and digital images integration allowed the identification of seven geomorphological units: coastal tableland, flowing tray, tide plain, fluvial terrace, submerged dune, beach plain and beach). Both Side Scan Sonar and Echosound were used to analyse underwater surface and bedforms of the estuarine channel, sand predominance (fine to very fine) and 2D dune features 5 m wide and 0.5 m height. This investigation characterized the estuary as an environment dominated by regimen of average flow. The channel depth varies between 1 m and 11 m, being this last quota reached in the area of Porto de Cabedelo. The chanel estuary is relatively shallow, with erosion evidences mainly on its superior portion, attested by sand banks exposed during the low tide. Multitemporal digital maps from 1969 and 2001 integration were obtained through geoprocessing techniques, resulting the geodynamic evolution of the estuary based on landuse, DEM geomorphology and bathymetric maps

Imageamento digital de paleocavernas colapsadas com georadar

In this study, the methodological procedures involved in digital imaging of collapsed paleocaves in tufa using GPR are presented. These carbonate deposits occur in the Quixeré region, Ceará State (NE Brazil), on the western border of the Potiguar Basin. Collapsed paleocaves are exposed along a state road, which were selected to this study. We chose a portion of the called Quixeré outcrop for making a photomosaic and caring out a GPR test section to compare and parameterize the karst geometries on the geophysical line. The results were satisfactory and led to the adoption of criteria for the interpretation of others GPR sections acquired in the region of the Quixeré outcrop. Two grids of GPR lines were acquired; the first one was wider and more spaced and guided the location of the second grid, denser and located in the southern part of the outcrop. The radargrams of the second grid reveal satisfactorily the collapsed paleocaves geometries. For each grid has been developed a digital solid model of the Quixeré outcrop. The first model allows the recognition of the general distribution and location of collapsed paleocaves in tufa deposits, while the second more detailed digital model provides not only the 3D individualization of the major paleocaves, but also the estimation of their respective volumes. The digital solid models are presented here as a new frontier in the study of analog outcrops to reservoirs (for groundwater and hydrocarbon), in which the volumetric parameterization and characterization of geological bodies become essential for composing the databases, which together with petrophysical properties information, are used in more realistic computer simulations for sedimentary reservoirs.

Controle de qualidade aplicado na modelagem digital de terreno

Pós-graduação em Ciências Cartográficas - FCT

Monitoramento das perdas de solo da sub-bacia Ribeirão das Bicas - Botucatu/SP, utilizando fotogrametria digital

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Digital soil mapping: evaluation of sampling systems for soil surveys and refinement of soil maps at lower cost using legacy data

In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Interaction between GIS and hydrologic model: a preliminary approach using ArcHydro Framework Data Model

In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM) models, the Geographical Information System (GIS) is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion), situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin's dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM) is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial-temporal model.

Desenvolvimento de uma plataforma de software para a modelagem digital de terrenos baseada em TIN

Topographical surfaces can be represented with a good degree of accuracy by means of maps. However these are not always the best tools for the understanding of more complex reliefs. In this sense, the greatest contribution of this work is to specify and to implement the architecture of an opensource software system capable of representing TIN (Triangular Irregular Network) based digital terrain models. The system implementation follows the object oriented programming and generic paradigms enabling the integration of various opensource tools such as GDAL, OGR, OpenGL, OpenSceneGraph and Qt. Furthermore, the representation core of the system has the ability to work with multiple topological data structures from which can be extracted, in constant time, all the connectivity relations between the entities vertices, edges and faces existing in a planar triangulation what helps enormously the implementation for real time applications. This is an important capability, for example, in the use of laser survey data (Lidar, ALS, TLS), allowing for the generation of triangular mesh models in the order of millions of points.