Land use/cover change using Remote Sensing and Geographic Information Systems : Pic Macaya National Park, Haiti

A post classification change detection technique based on a hybrid classification approach (unsupervised and supervised) was applied to Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Plus (ETM+), and ASTER images acquired in 1987, 2000 and 2004 respectively to map land use/cover changes in the Pic Macaya National Park in the southern region of Haiti. Each image was classified individually into six land use/cover classes: built-up, agriculture, herbaceous, open pine forest, mixed forest, and barren land using unsupervised ISODATA and maximum likelihood supervised classifiers with the aid of field collected ground truth data collected in the field. Ground truth information, collected in the field in December 2007, and including equalized stratified random points which were visual interpreted were used to assess the accuracy of the classification results. The overall accuracy of the land classification for each image was respectively: 1987 (82%), 2000 (82%), 2004 (87%). A post classification change detection technique was used to produce change images for 1987 to 2000, 1987 to 2004, and 2000 to 2004. It was found that significant changes in the land use/cover occurred over the 17- year period. The results showed increases in built up (from 10% to 17%) and herbaceous (from 5% to 14%) areas between 1987 and 2004. The increase of herbaceous was mostly caused by the abandonment of exhausted agriculture lands. At the same time, open pine forest and mixed forest areas lost (75%) and (83%) of their area to other land use/cover types. Open pine forest (from 20% to 14%) and mixed forest (from18 to 12%) were transformed into agriculture area or barren land. This study illustrated the continuing deforestation, land degradation and soil erosion in the region, which in turn is leading to decrease in vegetative cover. The study also showed the importance of Remote Sensing (RS) and Geographic Information System (GIS) technologies to estimate timely changes in the land use/cover, and to evaluate their causes in order to design an ecological based management plan for the park.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.

Change-Impact driven Agile Architecting.

Software architecture is a key factor to scale up Agile Software Development ASD in large softwareintensive systems. Currently, software architectures are more often approached through mechanisms that enable to incrementally design and evolve software architectures aka. agile architecting. Agile architecting should be a light-weight decision-making process, which could be achieved by providing knowledge to assist agile architects in reasoning about changes. This paper presents the novel solution of using change-impact knowledge as the main driver for agile architecting. The solution consists of a Change Impact Analysis technique and a set of models to assist agile architects in the change -decision-making- process by retrieving the change-impact architectural knowledge resulting from adding or changing features iteration after iteration. To validate our approach, we have put our solution into practice by running a project of a metering management system in electric power networks in an i-smart software factory.

Anomaly Detection Using Remote Sensing for the Archaeological Heritage Registration

The aim of this work is an approach using multisensor remote sensing techniques to recognize the potential remains and recreate the original landscape of three archaeological sites. We investigate the spectral characteristics of the reflectance parameter and emissivity in the pattern recognition of archaeological materials in several hyperspectral scenes of the prehispanic site in Palmar Sur (Costa Rica), the Jarama Valley site and the celtiberian city of Segeda in Spain. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of HyMAP, AHS, MASTER and ATM have been used. Several experiments on natural scenarios of Costa Rica and Spain of different complexity, have been designed. Spectral patterns and thermal anomalies have been calculated as evidences of buried remains and change detection. First results, land cover change analyses and their consequences in the digital heritage registration are discussed.

Transformada Wavelet Compleja de Doble Árbol (DT-CWT) y su aplicación en Teledetección. Nuevos modelos y aplicaciones

La teledetección o percepción remota (remote sensing) es la ciencia que abarca la obtención de información (espectral, espacial, temporal) sobre un objeto, área o fenómeno a través del análisis de datos adquiridos por un dispositivo que no está en contacto con el elemento estudiado. Los datos obtenidos a partir de la teledetección para la observación de la superficie terrestre comúnmente son imágenes, que se caracterizan por contar con un sinnúmero de aplicaciones que están en continua evolución, por lo cual para solventar los constantes requerimientos de nuevas aplicaciones a menudo se proponen nuevos algoritmos que mejoran o facilitan algún proceso en particular. Para el desarrollo de dichos algoritmos, es preciso hacer uso de métodos matemáticos que permitan la manipulación de la información con algún fin específico. Dentro de estos métodos, el análisis multi-resolución se caracteriza por permitir analizar una señal en diferentes escalas, lo que facilita trabajar con datos que puedan tener resoluciones diferentes, tal es el caso de las imágenes obtenidas mediante teledetección. Una de las alternativas para la implementación de análisis multi-resolución es la Transformada Wavelet Compleja de Doble Árbol (DT-CWT). Esta transformada se implementa a partir de dos filtros reales y se caracteriza por presentar invariancia a traslaciones, precio a pagar por su característica de no ser críticamente muestreada. A partir de las características de la DT-CWT se propone su uso en el diseño de algoritmos de procesamiento de imagen, particularmente imágenes de teledetección. Estos nuevos algoritmos de procesamiento digital de imágenes de teledetección corresponden particularmente a fusión y detección de cambios. En este contexto esta tesis presenta tres algoritmos principales aplicados a fusión, evaluación de fusión y detección de cambios en imágenes. Para el caso de fusión de imágenes, se presenta un esquema general que puede ser utilizado con cualquier algoritmo de análisis multi-resolución; este algoritmo parte de la implementación mediante DT-CWT para luego extenderlo a un método alternativo, el filtro bilateral. En cualquiera de los dos casos la metodología implica que la inyección de componentes pueda realizarse mediante diferentes alternativas. En el caso del algoritmo de evaluación de fusión se presenta un nuevo esquema que hace uso de procesos de clasificación, lo que permite evaluar los resultados del proceso de fusión de forma individual para cada tipo de cobertura de uso de suelo que se defina en el proceso de evaluación. Esta metodología permite complementar los procesos de evaluación tradicionales y puede facilitar el análisis del impacto de la fusión sobre determinadas clases de suelo. Finalmente, los algoritmos de detección de cambios propuestos abarcan dos enfoques. El primero está orientado a la obtención de mapas de sequía en datos multi-temporales a partir de índices espectrales. El segundo enfoque propone la utilización de un índice global de calidad espectral como filtro espacial. La utilización de dicho filtro facilita la comparación espectral global entre dos imágenes, esto unido a la utilización de umbrales, conlleva a la obtención de imágenes diferencia que contienen la información de cambio. ABSTRACT Remote sensing is a science relates to information gathering (spectral, spatial, temporal) about an object, area or phenomenon, through the analysis of data acquired by a device that is not in contact with the studied item. In general, data obtained from remote sensing to observe the earth’s surface are images, which are characterized by having a number of applications that are constantly evolving. Therefore, to solve the constant requirements of applications, new algorithms are proposed to improve or facilitate a particular process. With the purpose of developing these algorithms, each application needs mathematical methods, such as the multiresolution analysis which allows to analyze a signal at different scales. One of the options is the Dual Tree Complex Wavelet Transform (DT-CWT) which is implemented from two real filters and is characterized by invariance to translations. Among the advantages of this transform is its successful application in image fusion and change detection areas. In this regard, this thesis presents three algorithms applied to image fusion, assessment for image fusion and change detection in multitemporal images. For image fusion, it is presented a general outline that can be used with any multiresolution analysis technique; this algorithm is proposed at first with DT-CWT and then extends to an alternative method, the bilateral filter. In either case the method involves injection of components by various means. For fusion assessment, the proposal is focused on a scheme that uses classification processes, which allows evaluating merger results individually for each type of land use coverage that is defined in evaluation process. This methodology allows complementing traditional assessment processes and can facilitate impact analysis of the merger on certain kinds of soil. Finally, two approaches of change detection algorithms are included. The first is aimed at obtaining drought maps in multitemporal data from spectral indices. The second one takes a global index of spectral quality as a spatial filter. The use of this filter facilitates global spectral comparison between two images and by means of thresholding, allows imaging containing change information.

Signal detection theory in applied tasks: The case of hazard perception in driving

Fuzzy signal detection analysis can be a useful complementary technique to traditional signal detection theory analysis methods, particularly in applied settings. For example, traffic situations are better conceived as being on a continuum from no potential for hazard to high potential, rather than either having potential or not having potential. This study examined the relative contribution of sensitivity and response bias to explaining differences in the hazard perception performance of novices and experienced drivers, and the effect of a training manipulation. Novice drivers and experienced drivers were compared (N = 64). Half the novices received training, while the experienced drivers and half the novices remained untrained. Participants completed a hazard perception test and rated potential for hazard in occluded scenes. The response latency of participants to the hazard perception test replicated previous findings of experienced/novice differences and trained/untrained differences. Fuzzy signal detection analysis of both the hazard perception task and the occluded rating task suggested that response bias may be more central to hazard perception test performance than sensitivity, with trained and experienced drivers responding faster and with a more liberal bias than untrained novices. Implications for driver training and the hazard perception test are discussed.

Identification of visual field progression

The study developed statistical techniques to evaluate visual field progression for use with the Humphrey Field Analyzer (HFA). The long-term fluctuation (LF) was evaluated in stable glaucoma. The magnitude of both LF components showed little relationship with MD, CPSD and SF. An algorithm was proposed for determining the clinical necessity for a confirmatory follow-up examination. The between-examination variability was determined for the HFA Standard and FASTPAC algorithms in glaucoma. FASTPAC exhibited greater between-examination variability than the Standard algorithm across the range of sensitivities and with increasing eccentricity. The difference in variability between the algorithms had minimal clinical significance. The effect of repositioning the baseline in the Glaucoma Change Probability Analysis (GCPA) was evaluated. The global baseline of the GCPA limited the detection of progressive change at a single stimulus location. A new technique, pointwise univariate linear regressions (ULR), of absolute sensitivity and, of pattern deviation, against time to follow-up was developed. In each case, pointwise ULR was more sensitive to localised progressive changes in sensitivity than ULR of MD, alone. Small changes in sensitivity were more readily determined by the pointwise ULR than by the GCPA. A comparison between the outcome of pointwise ULR for all fields and for the last six fields manifested linear and curvilinear declines in the absolute sensitivity and the pattern deviation. A method for delineating progressive loss in glaucoma, based upon the error in the forecasted sensitivity of a multivariate model, was developed. Multivariate forecasting exhibited little agreement with GCPA in glaucoma but showed promise for monitoring visual field progression in OHT patients. The recovery of sensitivity in optic neuritis over time was modelled with a Cumulative Gaussian function. The rate and level of recovery was greater in the peripheral than the central field. Probability models to forecast the field of recovery were proposed.

Intelligent Model of User Behavior in Distributed Systems

We present a complex neural network model of user behavior in distributed systems. The model reflects both dynamical and statistical features of user behavior and consists of three components: on-line and off-line models and change detection module. On-line model reflects dynamical features by predicting user actions on the basis of previous ones. Off-line model is based on the analysis of statistical parameters of user behavior. In both cases neural networks are used to reveal uncharacteristic activity of users. Change detection module is intended for trends analysis in user behavior. The efficiency of complex model is verified on real data of users of Space Research Institute of NASU-NSAU.

Anomaly detection from time-changing environmental sensor data streams

This thesis stems from the project with real-time environmental monitoring company EMSAT Corporation. They were looking for methods to automatically ag spikes and other anomalies in their environmental sensor data streams. The problem presents several challenges: near real-time anomaly detection, absence of labeled data and time-changing data streams. Here, we address this problem using both a statistical parametric approach as well as a non-parametric approach like Kernel Density Estimation (KDE). The main contribution of this thesis is extending the KDE to work more effectively for evolving data streams, particularly in presence of concept drift. To address that, we have developed a framework for integrating Adaptive Windowing (ADWIN) change detection algorithm with KDE. We have tested this approach on several real world data sets and received positive feedback from our industry collaborator. Some results appearing in this thesis have been presented at ECML PKDD 2015 Doctoral Consortium.

Building a Rockfall Database Using Remote Sensing: Techniques for Hazard Management in Canadian Rail Corridors

The section of CN railway between Vancouver and Kamloops runs along the base of many hazardous slopes, including the White Canyon, which is located just outside the town of Lytton, BC. The slope has a history of frequent rockfall activity, which presents a hazard to the railway below. Rockfall inventories can be used to understand the frequency-magnitude relationship of events on hazardous slopes, however it can be difficult to consistently and accurately identify rockfall source zones and volumes on large slopes with frequent activity, leaving many inventories incomplete. We have studied this slope as a part of the Canadian Railway Ground Hazard Research Program and have collected remote sensing data, including terrestrial laser scanning (TLS), photographs, and photogrammetry data since 2012, and used change detection to identify rockfalls on the slope. The objective of this thesis is to use a subset of this data to understand how rockfalls identified from TLS data could be used to understand the frequency-magnitude relationship of rockfalls on the slope. This includes incorporating both new and existing methods to develop a semi-automated workflow to extract rockfall events from the TLS data. We show that these methods can be used to identify events as small as 0.01 m3 and that the duration between scans can have an effect on the frequency-magnitude relationship of the rockfalls. We also show that by incorporating photogrammetry data into our analysis, we can create a 3D geological model of the slope and use this to classify rockfalls by lithology, to further understand the rockfall failure patterns. When relating the rockfall activity to triggering factors, we found that the amount of precipitation occurring over the winter has an effect on the overall rockfall frequency for the remainder of the year. These results can provide the railways with a more complete inventory of events compared to records created through track inspection, or rockfall monitoring systems that are installed on the slope. In addition, we can use the database to understand the spatial and temporal distribution of events. The results can also be used as an input to rockfall modelling programs.

Análise das mudanças espaciais e temporais nos padrões de paisagem na região do oeste da Bahia sobre a formação do grupo urucuia (1988-2011) e suas implicações para a conservação do Cerrado

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós Graduação em Geografia, 2015.

CLIMATE CHANGE ADAPTATION IN VULNERABLE CROP AND LIVESTOCK PRODUCTION SYSTEMS IN MGETA, TANZANIA

Increased occurrence of drought and dry spells during the growing season have resulted in increased interest in protection of tropical water catchment areas. In Mgeta, a water catchment area in the Uluguru Mountains in Tanzania, water used for vegetable and fruit production is provided through canals from the Uluguru South Forest Reserve. The clearing of forest land for cultivation in the steep slopes in the area is causing severe land degradation, which is threatening the water catchment area, livelihoods, and food security of the local communities, as well as the major population centers in the lowlands. In this paper, the economic performance of a traditional cropping-livestock system with East African (EA)-goats and pigs and extensive vegetable production is compared with a more sustainable and environmentally friendly crop-dairy goat production system. A linear programming (LP) crop-livestock model, maximizing farm income considering the environmental constraints in the area was applied for studying the economic performance of dairy goats in the production system. The model was worked out for the rainy and dry seasons and the analysis was conducted for a basic scenario representing the current situation, based on the variability in the 30 years period from 1982-2012, and in a scenario of both lower crop yields and increased crop variability due to climate change. Data obtained from a sample of 60 farmers that were interviewed using a questionnaire was used to develop and parameterize the model. The study found that in the steep slopes of the area, a crop-dairy goat system with extensive use of grass and multipurpose trees (MPTs) would do better than the traditional vegetable gardening with the EA goat production system. The crop-dairy goat system was superior both in the basic and in a climate change scenario since the yield variation of the grass and MPTs system was less affected compared to vegetable crops due to more tree cover and the use of perennial grasses. However, the goat milk production in the area was constrained by inadequate feeding and lack of an appropriate breeding program. Hence, farmers should enhance goat milk production by supplementing with more concentrate feed and by implementing goat-breeding principles. Moreover, policy measures to promote such a development are briefly discussed.

Environmental quality of life index incorporationg MCA & GIS : case study Lisbon Metropolitan Area, Portugal

The study of Quality of Life (Qol) has been conducted on various scales throughout the years with focus on assessing overall quality of living amongst citizens. The main focus in these studies have been on economic factors, with the purpose of creating a Quality of Life Index (QLI).When it comes down to narrowing the focus to the environment and factors like Urban Green Spaces (UGS) and air quality the topic gets more focused on pointing out how each alternative meets this certain criteria. With the benefits of UGS and a healthy environment in focus a new Environmental Quality of Life Index (EQLI) will be proposed by incorporating Multi Criteria Analysis (MCA) and Geographical Information Systems (GIS). Working with MCA on complex environmental problems and incorporating it with GIS is a challenging but rewarding task, and has proven to be an efficient approach among environmental scientists. Background information on three MCA methods will be shown: Analytical Hierarchy Process (AHP), Regime Analysis and PROMETHEE. A survey based on a previous study conducted on the status of UGS within European cities was sent to 18 municipalities in the study area. The survey consists of evaluating the current status of UGS as well as planning and management of UGS with in municipalities for the purpose of getting criteria material for the selected MCA method. The current situation of UGS is assessed with use of GIS software and change detection is done on a 10 year period using NDVI index for comparison purposes to one of the criteria in the MCA. To add to the criteria, interpolation of nitrogen dioxide levels was performed with ordinary kriging and the results transformed into indicator values. The final outcome is an EQLI map with indicators of environmentally attractive municipalities with ranking based on predefinedMCA criteria using PROMETHEE I pairwise comparison and PROMETHEE II complete ranking of alternatives. The proposed methodology is applied to Lisbon’s Metropolitan Area, Portugal.

Depression: a predictor of smoking relapse in a 6-month follow-up after hospitalization for acute coronary syndrome

Objective The objective of the study was to investigate whether depression is a predictor of postdischarge smoking relapse among patients hospitalized for myocardial infarction (MI) or unstable angina (ILIA), in a smoke-free hospital. Methods Current smokers with MI or UA were interviewed while hospitalized; patients classified with major depression (MD) or no humor disorder were reinterviewed 6 months post discharge to ascertain smoking status. Potential predictors of relapse (depression; stress; anxiety; heart disease risk perception; coffee and alcohol consumption; sociodemographic, clinical, and smoking habit characteristics) were compared between those with MD (n = 268) and no humor disorder (n = 135). Results Relapsers (40.4%) were more frequently and more severely depressed, had higher anxiety and lower self-efficacy scale scores, diagnosis of UA, shorter hospitalizations, started smoking younger, made fewer attempts to quit, had a consort less often, and were more frequently at the `precontemplation` stage of change. Multivariate analysis showed relapse-positive predictors to be MD [odds ratio (OR): 2.549; 95% confidence interval (CI): 1.519-4.275] (P<0.001); `precontemplation` stage of change (OR: 7.798; 95% CI: 2.442-24.898) (P<0.001); previous coronary bypass graft surgery (OR: 4.062; 95% CI: 1.356-12.169) (P=0.012); and previous anxiolytic use (OR: 2.365; 95% CI: 1.095-5.107) (P=0.028). Negative predictors were diagnosis of MI (OR: 0.575; 95% CI: 0.361-0.916) (P=0.019); duration of hospitalization (OR: 0.935; 95% CI: 0.898-0.973) (P=0.001); smoking onset age (OR: 0.952; 95% CI: 0.910-0.994) (P=0.028); number of attempts to quit smoking (OR: 0.808; 95% CI: 0.678-0.964) (P=0.018); and `action` stage of change (OR: 0.065; 95% CI: 0.008-0.532) (P= 0.010). Conclusion Depression, no motivation, shorter hospitalization, and severity of illness contributed to postdischarge resumption of smoking by patients with acute coronary syndrome, who underwent hospital-initiated smoking cessation.

Aprendizagem Cooperativa : um contributo para a diferenciação pedagógica inclusiva

A dissertação incidiu na diferenciação pedagógica inclusiva, especificamente, num grupo/turma com diferentes anos de escolaridade, com aprendizagens diferentes, e alunos com Necessidades Educativas Especiais (NEE) de índole comportamental e cognitivo, tendo como objectivo constituir alternativa ao problema. As professoras titulares de turma e de educação especial, em cooperação, planificaram e implementaram este estudo, cujo ponto de partida consistia em promover o desenvolvimento pessoal e social, tendo por base um livro pertencente ao Plano Nacional de Leitura (PNL). Foram desenvolvidas estruturas cooperativas de forma a melhorar comportamentos e aprendizagens em todos os alunos e em especial dos alunos com NEE. Neste processo de observação e reflexão, a experiência foi conceptualizada e analisada com o objectivo de contribuir para a mudança. A análise de dados do trabalho individual e de grupo dos alunos, onde se inferiu uma maior ajuda, autonomia, responsabilidade, envolvimento e interesse, pelas actividades, permitiu-nos verificar que os objectivos foram alcançados na sua maioria O estudo permitiu evidenciar a diminuição de conflitos comportamentais, contribuindo para um clima de entreajuda englobando todos os alunos, onde a partilha de conhecimentos coadjuvou para melhorar as aprendizagens de todos.