NAVIGATION IN INDOOR VOXEL MODELS

The paper proposes to use voxel models of building interiors to perform indoor navigation. The algorithms can be purely geometrical, not relying on semantic information about different building elements, such as floors, walls, stairways etc. Therefore, it is possible to use voxel models from different data sources, in addition to vector-to-raster conversions. The paper demonstrates this on the basis of tree different input types: hand measurements, point clouds and images of floorplans. On the basis of these models, the paper shows how to determine the navigable space in a voxel model for a pedestrian actor, and how to compute paths from arbitrary sources to specified destinationsScopu

Probabilistic segmentation of remotely sensed images

For information extraction from image data to create or update geographic information systems, objects are identified and labeled using an integration of segmentation and classification. This yields geometric and thematic information, respectively.Bayesian image classifiers calculate class posterior probabilities on the basis of estimated class probability densities and prior probabilities. This thesis presents refined probability estimates, which are local, i.e pertain to image regions, rather than to the entire image. Local class probability densities are estimated in a non-parametric way with an extended k-Nearest Neighbor method. Iterative estimation of class mixing proportions in arbitrary image regions yields local prior probabilities.The improved estimates of prior probabilities and probability densities increase the reliability of posterior probabilities and enhance subsequent decision making, such as maximum posterior probability class selection. Moreover, class areas are estimated more accurately, compared to standard Maximum Likelihood classification.Two sources of image regionalization are distinguished. Ancillary data in geographic information systems often divide the image area into regions with different class mixing proportions, in which probabilities are estimated. Otherwise, a regionalization can be obtained by image segmentation. A region based method is presented, being a generalization of connected component labeling in the quadtree domain. It recursively merges leaves in a quadtree representation of a multi-spectral image into segments with arbitrary shapes and sizes. Order dependency is avoided by applying the procedure iteratively with slowly relaxing homogeneity criteria.Region fragmentation and region merging, caused by spectral variation within objects and spectral similarity between adjacent objects, are avoided by regarding class homogeneity in addition to spectral homogeneity. As expected, most terrain objects correspond to image segments. These, however, reside at different levels in a segmentation pyramid. Therefore, class mixing proportions are estimated in all segments of such a pyramid to distinguish between pure and mixed ones. Pure segments are selected at the highest possible level, which may vary over the image. They form a non-overlapping set of labeled objects without fragmentation or merging. In image areas where classes cannot be separated, because of spatial or spectral resolution limitations, mixed segments are selected from the pyramid. They form uncertain objects, to which a mixture of classes with known proportion is assigned.Subsequently, remotely sensed data are used for taking decisions in geographical information systems. These decisions are usually based on crisp classifications and, therefore, influenced by classification errors and uncertainties. Moreover, when processing spatial data for decision making, the objectives and preferences of the decision maker are crucial to deal with. This thesis proposes to exploit mathematical decision analysis for integrating uncertainties and preferences, on the basis of carefully estimated probabilistic class information. It aims to solve complex decision problems on the basis of remotely sensed data.</p

A Study of Carbon Formation and Prevention in Hydrocarbon-Fueled SOFC

The formation and removal of the carbonaceous deposits formed by n-butane and liquid hydrocarbons, such as n-decane and proprietary light and heavy naphthas, between 973 and 1073 K on YSZ and ceria-YSZ, has been studied to determine conditions for stable operation of direct-utilization SOFC. First, it is shown that deactivation of SOFC with Cu-ceria-YSZ anodes operating on undiluted n-decane, a mixture of 80% n-decane and 20% toluene, or light naphtha at temperatures above 973 K is due to filling of the pores with polyaromatic compounds formed by gas-phase, free-radical reactions. Formation of these compounds occurs at a negligible rate below 973 K but increases rapidly above this temperature. The rate of formation also depends on the residence time of the fuel in the anode compartment. Because steam does not participate in the gas-phase reactions, carbonaceous deposits could form even at a H2O:C ratio of 1.5, a value greater than the stability threshold predicted by thermodynamic calculations. Temperature-programmed-oxidation (TPO) measurements with 20% H2O in He demonstrated that carbon deposits formed in pure YSZ were unreactive below 1073 K, while deposits formed on ceria-YSZ could be removed at temperatures as low as 923 K. Based on these results, we discuss strategies for avoiding carbon formation during the operation of direct-utilization anodes on oil-based liquid fuels

A synthesis of the effects of cheatgrass invasion on the US Great Basin carbon storage

Non‐native, invasive Bromus tectorum (cheatgrass) is pervasive in sagebrush ecosystems in the Great Basin ecoregion of the western United States, competing with native plants and promoting more frequent fires. As a result, cheatgrass invasion likely alters carbon (C) storage in the region. Many studies have measured C pools in one or more common vegetation types: native sagebrush, invaded sagebrush and cheatgrass‐dominated (often burned) sites, but these results have yet to be synthesized. We performed a literature review to identify studies assessing the consequences of invasion on C storage in above‐ground biomass (AGB), below‐ground biomass (BGB), litter, organic soil and total soil. We identified 41 articles containing 386 unique studies and estimated C storage across pools and vegetation types. We used linear mixed models to identify the main predictors of C storage. We found consistent declines in biomass C with invasion: AGB C was 55% lower in cheatgrass (40 ± 4 g C/m2) than native sagebrush (89 ± 27 g C/m2) and BGB C was 62% lower in cheatgrass (90 ± 17 g C/m2) than native sagebrush (238 ± 60 g C/m2). In contrast, litter C was \u3e4× higher in cheatgrass (154 ± 12 g C/m2) than native sagebrush (32 ± 12 g C/m2). Soil organic C (SOC) in the top 10 cm was significantly higher in cheatgrass than in native or invaded sagebrush. SOC below 20 cm was significantly related to the time since most recent fire and losses were observed in deep SOC in cheatgrass \u3e5 years after a fire. There were no significant changes in total soil C across vegetation types. Synthesis and applications. Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass carbon (C) losses that occur with sagebrush replacement. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C/m2, or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal

A COMPUTATIONALLY CHEAP TRICK TO DETERMINE SHADOW IN A VOXEL MODEL

Representation of scenes on the Earth surface by using voxels is gaining attention because of its suitability for integrating heterogeneous data sources in simulations and quantitative models. Computation of shadows in such models is needed, for example, to obtain crop suitability of agricultural fields in the presence of trees and buildings, or to analyze urban heat island causes and effects. We present an efficient algorithm to compute which of the voxels in a dataset receive direct sunlight, given the solar azimuth and elevation angles. The algorithm can work with multiple (sparse and dense) voxel storage strategies

Minhocas em sistemas de uso do solo: estudo de caso em Assistência, SP.

Resumo. 5° ELAETAO

Indicadores de qualidade do solo em sistemas de uso do solo: estudo de caso em Assistência, SP.

Resumo. 5° ELAETAO