978 resultados para Digital Surface Model (DSM)


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La utilización de una cámara fotogramétrica digital redunda en el aumento demostrable de calidad radiométrica debido a la mejor relación señal/ruido y a los 12 bits de resolución radiométrica por cada pixel de la imagen. Simultáneamente se consigue un notable ahorro de tiempo y coste gracias a la eliminación de las fases de revelado y escaneado de la película y al aumento de las horas de vuelo por día. De otra parte, el sistema láser aerotransportado (LIDAR - Light Detection and Ranging) es un sistema con un elevado rendimiento y rentabilidad para la captura de datos de elevaciones para generar un modelo digital del terreno (MDT) y también de los objetos sobre el terreno, permitiendo así alcanzar alta precisión y densidad de información. Tanto el sistema LIDAR como el sistema de cámara fotogramétrica digital se combinan con otras técnicas bien conocidas: el sistema de posicionamiento global (GPS - Global Positioning System) y la orientación de la unidad de medida inercial (IMU - Inertial Measure Units), que permiten reducir o eliminar el apoyo de campo y realizar la orientación directa de los sensores utilizando datos de efemérides precisas de los satélites. Combinando estas tecnologías, se va a proponer y poner en práctica una metodología para generación automática de ortofotos en países de América del Sur. Analizando la precisión de dichas ortofotos comparándolas con fuente de mayor exactitud y con las especificaciones técnicas del Plan Nacional de Ortofotografía Aérea (PNOA) se determinará la viabilidad de que dicha metodología se pueda aplicar a zonas rurales. ABSTRACT Using a digital photogrammetric camera results in a demonstrable increase of the radiometric quality due to a better improved signal/noise ratio and the radiometric resolution of 12 bits per pixel of the image. Simultaneously a significant saving of time and money is achieved thanks to the elimination of the developing and film scanning stages, as well as to the increase of flying hours per day. On the other hand, airborne laser system Light Detection and Ranging (LIDAR) is a system with high performance and yield for the acquisition of elevation data in order to generate a digital terrain model (DTM), as well as objects on the ground which allows to achieve high accuracy and data density. Both the LIDAR and the digital photogrammetric camera system are combined with other well known techniques: global positioning system (GPS) and inertial measurement unit (IMU) orientation, which are currently in a mature evolutionary stage, which allow to reduce and/or remove field support and perform a direct guidance of sensors using specific historic data from the satellites. By combining these technologies, a methodology for automatic generation of orthophotos in South American countries will be proposed and implemented. Analyzing the accuracy of these orthophotos comparing them with more accurate sources and technical specifications of the National Aerial Orthophoto (PNOA), the viability of whether this methodology should be applied to rural areas, will be determined.

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La observación de la Tierra es una herramienta de gran utilidad en la actualidad para el estudio de los fenómenos que se dan en la misma. La observación se puede realizar a distintas escalas y por distintos métodos dependiendo del propósito. El actual Trabajo Final de Grado persigue exponer la observación del territorio mediante técnicas de Teledetección, o Detección Remota, y su aplicación en la exploración de hidrocarburos. Desde la Segunda Guerra Mundial el capturar imágenes aéreas de regiones de la Tierra estaba restringido a usos cartográficos en el sentido estricto. Desde aquellos tiempos, hasta ahora, ha acontecido una serie de avances científicos que permiten deducir características intrínsecas de la Tierra mediante mecanismos complejos que no apreciamos a simple vista, pero que, están configurados mediante determinados parámetros geométricos y electrónicos, que permiten generar series temporales de fenómenos físicos que se dan en la Tierra. Hoy en día se puede afirmar que el aprovechamiento del espectro electromagnético está en un punto máximo. Se ha pasado del análisis de la región del espectro visible al análisis del espectro en su totalidad. Esto supone el desarrollo de nuevos algoritmos, técnicas y procesos para extraer la mayor cantidad de información acerca de la interacción de la materia con la radiación electromagnética. La información que generan los sistemas de captura va a servir para la aplicación directa e indirecta de métodos de prospección de hidrocarburos. Las técnicas utilizadas en detección por sensores remotos, aplicadas en campañas geofísicas, son utilizadas para minimizar costes y maximizar resultados en investigaciones de campo. La predicción de anomalías en la zona de estudio depende del analista, quien diseña, calcula y evalúa las variaciones de la energía electromagnética reflejada o emitida por la superficie terrestre. Para dicha predicción se revisarán distintos programas espaciales, se evaluará la bondad de registro y diferenciación espectral mediante el uso de distintas clasificaciones (supervisadas y no supervisadas). Por su influencia directa sobre las observaciones realizadas, se realiza un estudio de la corrección atmosférica; se programan distintos modelos de corrección atmosférica para imágenes multiespectrales y se evalúan los métodos de corrección atmosférica en datos hiperespectrales. Se obtendrá temperatura de la zona de interés utilizando los sensores TM-4, ASTER y OLI, así como un Modelo Digital del Terreno generado por el par estereoscópico capturado por el sensor ASTER. Una vez aplicados estos procedimientos se aplicarán los métodos directos e indirectos, para la localización de zonas probablemente afectadas por la influencia de hidrocarburos y localización directa de hidrocarburos mediante teledetección hiperespectral. Para el método indirecto se utilizan imágenes capturadas por los sensores ETM+ y ASTER. Para el método directo se usan las imágenes capturadas por el sensor Hyperion. ABSTRACT The observation of the Earth is a wonderful tool for studying the different kind of phenomena that occur on its surface. The observation could be done by different scales and by different techniques depending on the information of interest. This Graduate Thesis is intended to expose the territory observation by remote sensing acquiring data systems and the analysis that can be developed to get information of interest. Since Second World War taking aerials photographs of scene was restricted only to a cartographic sense. From these days to nowadays, it have been developed many scientific advances that make capable the interpretation of the surface behavior trough complex systems that are configure by specific geometric and electronic parameters that make possible acquiring time series of the phenomena that manifest on the earth’s surface. Today it is possible to affirm that the exploitation of the electromagnetic spectrum is on a maxim value. In the past, analysis of the electromagnetic spectrum was carry in a narrow part of it, today it is possible to study entire. This implicates the development of new algorithms, process and techniques for the extraction of information about the interaction of matter with electromagnetic radiation. The information that has been acquired by remote sensing sensors is going to be a helpful tool for the exploration of hydrocarbon through direct and vicarious methods. The techniques applied in remote sensing, especially in geophysical campaigns, are employed to minimize costs and maximize results of ground-based geologic investigations. Forecasting of anomalies in the region of interest depends directly on the expertise data analyst who designs, computes and evaluates variations in the electromagnetic energy reflected or emanated from the earth’s surface. For an optimal prediction a review of the capture system take place; assess of the goodness in data acquisition and spectral separability, is carried out by mean of supervised and unsupervised classifications. Due to the direct influence of the atmosphere in the register data, a study of the minimization of its influence has been done; a script has been programed for the atmospheric correction in multispectral data; also, a review of hyperspectral atmospheric correction is conducted. Temperature of the region of interest is computed using the images captured by TM-4, ASTER and OLI, in addition to a Digital Terrain Model generated by a pair of stereo images taken by ASTER sensor. Once these procedures have finished, direct and vicarious methods are applied in order to find altered zones influenced by hydrocarbons, as well as pinpoint directly hydrocarbon presence by mean of hyperspectral remote sensing. For this purpose ETM+ and ASTER sensors are used to apply the vicarious method and Hyperion images are used to apply the direct method.

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LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

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This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).

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The ocean plays an important role in modulating the mass balance of the polar ice sheets by interacting with the ice shelves in Antarctica and with the marine-terminating outlet glaciers in Greenland. Given that the flux of warm water onto the continental shelf and into the sub-ice cavities is steered by complex bathymetry, a detailed topography data set is an essential ingredient for models that address ice-ocean interaction. We followed the spirit of the global RTopo-1 data set and compiled consistent maps of global ocean bathymetry, upper and lower ice surface topographies and global surface height on a spherical grid with now 30-arc seconds resolution. We used the General Bathymetric Chart of the Oceans (GEBCO, 2014) as the backbone and added the International Bathymetric Chart of the Arctic Ocean version 3 (IBCAOv3) and the Interna- tional Bathymetric Chart of the Southern Ocean (IBCSO) version 1. While RTopo-1 primarily aimed at a good and consistent representation of the Antarctic ice sheet, ice shelves and sub-ice cavities, RTopo-2 now also contains ice topographies of the Greenland ice sheet and outlet glaciers. In particular, we aimed at a good representation of the fjord and shelf bathymetry sur- rounding the Greenland continent. We corrected data from earlier gridded products in the areas of Petermann Glacier, Hagen Bræ and Sermilik Fjord assuming that sub-ice and fjord bathymetries roughly follow plausible Last Glacial Maximum ice flow patterns. For the continental shelf off northeast Greenland and the floating ice tongue of Nioghalvfjerdsfjorden Glacier at about 79°N, we incorporated a high-resolution digital bathymetry model considering original multibeam survey data for the region. Radar data for surface topographies of the floating ice tongues of Nioghalvfjerdsfjorden Glacier and Zachariæ Isstrøm have been obtained from the data centers of Technical University of Denmark (DTU), Operation Icebridge (NASA/NSF) and Alfred Wegener Institute (AWI). For the Antarctic ice sheet/ice shelves, RTopo-2 largely relies on the Bedmap-2 product but applies corrections for the geometry of Getz, Abbot and Fimbul ice shelf cavities.

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Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

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Changes in the Earth's orbit lead to changes in the seasonal and meridional distribution of insolation. We quantify the influence of orbitally induced changes on the seasonal temperature cycle in a transient simulation of the last 6000 years - from the mid-Holocene to today - using a coupled atmosphere-ocean general circulation model (ECHAM5/MPI-OM) including a land surface model (JSBACH). The seasonal temperature cycle responds directly to the insolation changes almost everywhere. In the Northern Hemisphere, its amplitude decreases according to an increase in winter insolation and a decrease in summer insolation. In the Southern Hemisphere, the opposite is true. Over the Arctic Ocean, decreasing summer insolation leads to an increase in sea-ice cover. The insulating effect of sea ice between the ocean and the atmosphere leads to decreasing heat flux and favors more "continental" conditions over the Arctic Ocean in winter, resulting in strongly decreasing temperatures. Consequently, there are two competing effects: the direct response to insolation changes and a sea-ice insulation effect. The sea-ice insulation effect is stronger, and thus an increase in the amplitude of the seasonal temperature cycle over the Arctic Ocean occurs. This increase is strongest over the Barents Shelf and influences the temperature response over northern Europe. We compare our modeled seasonal temperatures over Europe to paleo reconstructions. We find better agreements in winter temperatures than in summer temperatures and better agreements in northern Europe than in southern Europe, since the model does not reproduce the southern European Holocene summer cooling inferred from the paleo reconstructions. The temperature reconstructions for northern Europe support the notion of the influence of the sea-ice insulation effect on the evolution of the seasonal temperature cycle.

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We analysed long-term variations in grain-size distribution in sediments from Gåsfjärden, a fjord-like inlet on the south-west Baltic Sea, and explored potential drivers of the recorded changes in sediment grain-size data. Over the last 5.4 thousand years (ka), the relative sea level decreased 17 m in the study region, caused by isostatic land uplift. As a consequence, Gåsfjärden has been transformed from an open coastal setting into a semi-closed inlet surrounded on the east by numerous small islands. To quantitatively estimate the morphological changes in Gåsfjärden over the last 5.4 ka and to further link the changes to our grain-size data, a digital elevation model (DEM)-based openness index was calculated. In the period between 5.4 and 4.4 ka BP, the inlet was characterised by the largest openness index. During this interval, the highest sand contents (~0.4 %) and silt/clay ratios (~0. 3) in the sediment sequence were recorded, indicating relatively high bottom water energy. After 4.4 ka BP, the average sand content was halved to ~0.2 % and the silt/clay ratios showed a significant decreasing trend over the last 4 ka. These changes are found to be associated with the gradual embayment of Gåsfjärden as represented in the openness index. The silt/clay ratios exhibited a delayed and slower change compared with the sand contents, which further suggest that finer particles are less sensitive to changes in hydrodynamic energy. Our DEM-based coastal openness index has proved to be a useful tool for interpreting the sedimentary grain-size record.

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Glacier and ice sheet retreat exposes freshly deglaciated terrain which often contains small-scale fragile geomorphological features which could provide insight into subglacial or submarginal processes. Subaerial exposure results in potentially rapid landscape modification or even disappearance of the minor–relief landforms as wind, weather, water and vegetation impacts on the newly exposed surface. Ongoing retreat of many ice masses means there is a growing opportunity to obtain high resolution geospatial data from glacier forelands to aid in the understanding of recent subglacial and submarginal processes. Here we used an unmanned aerial vehicle to capture close-range aerial photography of the foreland of Isfallsglaciären, a small polythermal glacier situated in Swedish Lapland. An orthophoto and a digital elevation model with ~2 cm horizontal resolution were created from this photography using structure from motion software. These geospatial data was used to create a geomorphological map of the foreland, documenting moraines, fans, channels and flutes. The unprecedented resolution of the data enabled us to derive morphological metrics (length, width and relief) of the smallest flutes, which is not possible with other data products normally used for glacial landform metrics mapping. The map and flute metrics compare well with previous studies, highlighting the potential of this technique for rapidly documenting glacier foreland geomorphology at an unprecedented scale and resolution. The vast majority of flutes were found to have an associated stoss-side boulder, with the remainder having a likely explanation for boulder absence (burial or erosion). Furthermore, the size of this boulder was found to strongly correlate with the width and relief of the lee-side flute. This is consistent with the lee-side cavity infill model of flute formation. Whether this model is applicable to all flutes, or multiple mechanisms are required, awaits further study.

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This is a version of the Jisc ‘Six Elements of Digital Capabilities’ model, developed to support student-facing sta working in Careers and Employability roles and curriculum sta working to embed employability issues into the curriculum. It draws on the work of the Jisc Developing Student Employability project e.g. on the model of the ‘employable student’ produced by Peter Chatterton for that project.

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The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

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Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.

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The reconstruction of a complex scene from multiple images is a fundamental problem in the field of computer vision. Volumetric methods have proven to be a strong alternative to traditional correspondence-based methods due to their flexible visibility models. In this paper we analyse existing methods for volumetric reconstruction and identify three key properties of voxel colouring algorithms: a water-tight surface model, a monotonic carving order, and causality. We present a new Voxel Colouring algorithm which embeds all reconstructions of a scene into a single output. While modelling exact visibility for arbitrary camera locations, Embedded Voxel Colouring removes the need for a priori threshold selection present in previous work. An efficient implementation is given along with results demonstrating the advantages of posteriori threshold selection.