Detecção de áreas degradadas na sub-bacia hidrográfica do rio taperoá/pb, utilizando parâmetros físicos dos sensores modis/terra e tm/landsat

This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation

Desenvolvimento e avaliação de pulverizador florestal com detecção eletrônica de plantas daninhas e aplicação em doses variáveis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção de mudança e sedimentação no estuário do Rio Coreaú

O uso de novas técnicas para estudar a evolução e preenchimento de vales incisos tem fornecido, ao longo dos anos, importantes resultados para entendermos como foi a evolução costeira brasileira. Neste contexto, esta tese teve como objetivo estudar a evolução do estuário do rio Coreaú, localizado no estado do Ceará, em diferentes escalas temporais, seja “Eventual” (meses, anos), “Engenharia” anos, decádas) e Geológica” (centenas, séculos, milênios), proposta por Cowell et al. (2003), com intuíto de avaliar se as transformações/alterações ao longo dos anos foram significativas ou não. Como resultados, obteve-se no primeiro objetivo, utilizando técnicas de sensoriamento remoto, a partir de imagens dos sensores TM, ETM⁺ e OLI do satélite Landsat 5,7 e 8 e LISS-3 do satélite ResourceSat-1 de 1985 a 2013, uma alteração mínima em relação a transformações morfológicas ao longo do estuário nos últimos 28 anos (entre as escalas Eventual e de Engenharia), houve neste período um acréscimo de 0,236 km² (3%) de área, não trazendo sigificativas mudanças para o estuário. Em relação a taxa de sedimentação, correspondente ao segundo bjetivo, a partir da coleta de 9 testemunhos, de até 1 m de profundidade e utilizando o radionuclídeo ²¹⁰Pb, ao longo do estuário, obteve-se uma taxa que variou de 0,33 cm/ano a 1 cm/ano (escalas entre Engenharia e Geológica) próximo a foz do estuário, e com uma rápida sedimentação percebida na margem leste do rio, onde encontram-se sedimentos mais recentes em relação a margem oeste. Em relação ao preenchimento, terceiro e último objetivo, a partir da amostragem de testemunhos de até 18 m de profundidade, utilzando o amostrador Rammkernsonden (RKS), foram gerados perfis e seções estratigráficas que ajudaram a entender o preenchimento do vale inciso do estuário do rio Coreaú e entender que trata-se de um estuário fluvio-marinho, preenchendo os vales formados no Grupo Barreiras nos últimos 10.000 anos antes do presente. Estas análises e resultados servirão como base para comparação com outros estuários, sejam fluviais, fluvio-marinhos ou marinhos, para entendermos melhor quais os possíveis eventos que dominaram a sedimentação ao longo da costa brasileira em diferentes escalas.

Plenoptic camera : theory and experimental results

The purpose of this research was to develop a working physical model of the focused plenoptic camera and develop software that can process the measured image intensity, reconstruct this into a full resolution image, and to develop a depth map from its corresponding rendered image. The plenoptic camera is a specialized imaging system designed to acquire spatial, angular, and depth information in a single intensity measurement. This camera can also computationally refocus an image by adjusting the patch size used to reconstruct the image. The published methods have been vague and conflicting, so the motivation behind this research is to decipher the work that has been done in order to develop a working proof-of-concept model. This thesis outlines the theory behind the plenoptic camera operation and shows how the measured intensity from the image sensor can be turned into a full resolution rendered image with its corresponding depth map. The depth map can be created by a cross-correlation of adjacent sub-images created by the microlenslet array (MLA.) The full resolution image reconstruction can be done by taking a patch from each MLA sub-image and piecing them together like a puzzle. The patch size determines what object plane will be in-focus. This thesis also goes through a very rigorous explanation of the design constraints involved with building a plenoptic camera. Plenoptic camera data from Adobe © was used to help with the development of the algorithms written to create a rendered image and its depth map. Finally, using the algorithms developed from these tests and the knowledge for developing the plenoptic camera, a working experimental system was built, which successfully generated a rendered image and its corresponding depth map.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

MULTI-OBJECTIVE GENETIC ALGORITHM FOR EFFICIENT POINT MATCHING IN MULTI-SENSOR SATELLITE IMAGE

This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient.

A power-scalable RF CMOS receiver for 2.4 GHz Wireless Sensor Network applications

A power scalable receiver architecture is presented for low data rate Wireless Sensor Network (WSN) applications in 130nm RF-CMOS technology. Power scalable receiver is motivated by the ability to leverage lower run-time performance requirement to save power. The proposed receiver is able to switch power settings based on available signal and interference levels while maintaining requisite BER. The Low-IF receiver consists of Variable Noise and Linearity LNA, IQ Mixers, VGA, Variable Order Complex Bandpass Filter and Variable Gain and Bandwidth Amplifier (VGBWA) capable of driving variable sampling rate ADC. Various blocks have independent power scaling controls depending on their noise, gain and interference rejection (IR) requirements. The receiver is designed for constant envelope QPSK-type modulation with 2.4GHz RF input, 3MHz IF and 2MHz bandwidth. The chip operates at 1V Vdd with current scalable from 4.5mA to 1.3mA and chip area of 0.65mm2.

Smart chemical sensor application of ZnO nanowires grown on CMOS compatible SOI microheater platform

Smart chemical sensor based on CMOS(complementary metal-oxide- semiconductor) compatible SOI(silicon on insulator) microheater platform was realized by facilitating ZnO nanowires growth on the small membrane at the relatively low temperature. Our SOI microheater platform can be operated at the very low power consumption with novel metal oxide sensing materials, like ZnO or SnO2 nanostructured materials which demand relatively high sensing temperature. In addition, our sol-gel growth method of ZnO nanowires on the SOI membrane was found to be very effective compared with ink-jetting or CVD growth techniques. These combined techniques give us the possibility of smart chemical sensor technology easily merged into the conventional semiconductor IC application. The physical properties of ZnO nanowire network grown by the solution-based method and its chemical sensing property also were reported in this paper.

Zinc oxide nanowire based hydrogen sensor on SOI CMOS platform

Here we report on the successful low-temperature growth of zinc oxide nanowires (ZnONWs) on silicon-on-insulator (SOI) CMOS micro-hotplates and their response, at different operating temperatures, to hydrogen in air. The SOI micro-hotplates were fabricated in a commercial CMOS foundry followed by a deep reactive ion etch (DRIE) in a MEMS foundry to form ultra-low power membranes. The micro-hotplates comprise p+ silicon micro-heaters and interdigitated metal electrodes (measuring the change in resistance of the gas sensitive nanomaterial). The ZnONWs were grown as a post-CMOS process onto the hotplates using a CMOS friendly hydrothermal method. The ZnONWs showed a good response to 500 to 5000 ppm of hydrogen in air. We believe that the integration of ZnONWs with a MEMS platform results in a low power, low cost, hydrogen sensor that would be suitable for handheld battery-operated gas sensors. © 2011 Published by Elsevier Ltd.