This diploma thesis covers questions of remote sensing in relation to land adjustment. On water area is showm usage of the vegetation index NDVI and the Tasseled Cap transformation. Satellite images were processed in computer software ERDAS IMAGINE.

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The Appalachian National Scenic Trail is a unit of the National Park System created by the National Trails Act of 1968. Commonly referred to as the Appalachian Trail, or the AT, this National Park has some of the longest boundaries of any park. The AT is routed more than 2000 miles along the mountains of the eastern United States. The land purchased for the protection of the AT creates a separate boundary on each side of the trail. Monitoring these boundaries for intrusions or encroachments is a difficult and time-consuming task when done totally by field methods. This thesis presents a more efficient and consistent monitoring process using remote sensing data and change detection algorithms. Using Landsat TM images, Normalized Difference Vegetation Index (NDVI), and image difference change detection, this research shows that major boundary encroachments can be detected. Detection of sub-pixel vegetation index decreases identifies specific locations for field inspection. Assuming low cost multispectral Landsat imagery is available, simple NDVI difference calculation allows this technique to be applied to the entire AT one or more times per year. This procedure would improve the response time for encroachment mediation. The producer's accuracy for finding possible encroachments was 100 percent and the consumer's accuracy for possible encroachments indicated was 78.3 percent. Due to limited image availability, this study only examines change between one pair of Landsat images. Further refinement of these techniques should investigate other Landsat images at other times. Use of other remote sensing systems and change detection algorithms could be the focus of further research. / Master of Science

Northern bobwhite (<I>Colinus virginianus</I>) are important game birds associated with early successional habitats across the southeastern United States. In the past 30+ years there has been an almost universal decline in bobwhite population numbers despite a long history of management. The Virginia Bobwhite Quail Management Plan was implemented in 1996 to slow and stop the current population declines in Virginia. Virginia Department of Game and Inland Fisheries (VDGIF) personnel identified a lack of knowledge about the broad-scale, landscape level habitats in eastern Virginia. A large scale land cover map along with a detailed understanding of the spatial arrangements of bobwhite habitats will not only aid Virginia's management plan, but also allow focused efforts by our wildlife managers. I explored the possibilities of using remote sensing to map various habitats important to bobwhite. I compared several classification algorithms applied to Landsat TM imagery prior to selecting the classification method that best delineated early successional habitats. After method selection, a classified land cover map for the Coastal Plain and Piedmont of Virginia was generated. Using the classified images available from the first part of the study and 4 years of bobwhite call count data, I studied the landscape level habitat associations of bobwhite. A number of landscape metrics were calculated for the landscapes surrounding bobwhite call count routes and were used in two modeling exercises to differentiate between high and low bobwhite populations. Both pattern recognition (PATREC) and logistic regression models predicted levels of bobwhite abundance satisfactorily for the modeled (84.0% and 96.0% respectively) and independent (64.3% and 57.1%, respectively) data sets. The models were applied to remotely-sensed habitat maps to develop prediction maps expressing the quality of a landscape for supporting a high population of bobwhite based on existing land cover. Finally, I explored the possibility of eliminating the time consuming and very costly step of classifying a remotely-sensed image prior to examining its quality for a particular species. Using raw Landsat TM imagery and bobwhite call count data, I developed predictive logistic regression models expressing the quality of a landscape surrounding a pixel. The first model predicted the probability of the landscape supporting a high bobwhite population. Due to a number of stops with an average of zero, I was also able to generate a model that expressed the probability of the landscape supporting any number of bobwhite. This method also satisfactorily predicted high/low population and presence/absence for the modeled data (65.7% and 83.1%, respectively) and independent data (65.3% and 83.7%, respectively). The method described will allow for rapid assessment of our wildlife resources without having to classify remotely-sensed images into habitat classes prior to analyses. / Master of Science

Se recopiló una base de datos geográfica, con cartografía básica y temática, sobre la provincia de Napo (Ecuador), en la que se destacan los mapas de cobertura del suelo de los años 2002 y 2008. Como primer producto se elaboró un mapa de cobertura del suelo del año 1990 a partir de imágenes del sensor TM, (Landsat 4 y 5). Posteriormente se realizó un modelo de probabilidad de presencia de coberturas de tipo antrópico, usando la técnica de regresión logística multivariada; se evaluó el modelo con la curva ROC (Relative Operating Characteristic) y se determinó un alto poder de predicción en el modelo (AUC 0.89), distinguiendo además, que la distancia a centros poblados y a vías de comunicación son las variables más influyentes para la presencia de coberturas antrópicas. Se utilizó el mapa resultante del modelo de probabilidad como entrada en un modelo de transición de coberturas que combina Autómatas Celulares y Cadenas de Markov, entre otros aspectos, simulando un mapa de tipo de coberturas (natural o antrópico) para el año 2008. Se evaluó este mapa simulado, comparándolo con uno de referencia, a partir de índices kappa, y se obtuvo un porcentaje de concordancia general de 93%, lo cual es un buen indicador. Una vez que se ha contado con un modelo que permitía hacer simulaciones con el grado de confianza necesario, se realizaron simulaciones para los años 2015 y 2020. En estos escenarios de tipo de cobertura, se puede ver una clara presión hacia los bosques de la rivera del Rio Napo en un futuro, y también en aquellos cercanos a los principales centros poblados como Tena especialmente. Sin embargo, las áreas protegidas muestran un estado de conservación “natural” en las simulaciones, y esto se debe a sus condiciones de inaccesibilidad, en cuanto a falta de infraestructura vial, y a sus condiciones ambientales especiales. Por último, se verificó que la tasa de deforestación (cambio de natural hacia antrópico) en el período 1990-2008 fue de 4661 ha/año y en el período 2008-2020 sería de 3550 ha/año, indicando que la tendencia en el tiempo muestra en el mejor de los casos una disminución o por lo menos una estabilización de los procesos de deforestación.

This dissertation is a treatise on spatially-explicit resource selection on two very different vertebrate species. The North Atlantic right whale (Eubalaena glacialis) is the most endangered large whales in the world. Ship strikes and fishing gear entanglement are impediments to recovery. The gopher tortoise (Gopherus polyphemus) is an imperiled species whose upland habitats are shrinking from urban and agricultural development. Determining spatial distribution of important resources is important for conservation strategies. Historical and modern thinking of habitat selection theory and analytical techniques are reviewed and applied to these species. Fine-scale resource selection of sea surface temperature (SST), derived from AVHRR imagery, is evaluated for right whales in the southeastern U. S. calving grounds. Aerial survey data (December-March, 1991-1998) including survey tracklines and right whale locations were entered into a Geographic Information Systems (GIS) for comparing whale use of SST to availability based on search effort. Using Monte Carlo techniques, mean and standard deviation for SSTs and latitudes of whale-sightings were compared to sampling distributions derived from available SSTs and latitudes. From these data, it was concluded that the North Atlantic right whale uses SSTs and latitudes non-randomly. Broad-scale habitat selection for gopher tortoises was evaluated from the 2003 Land Cover/Land Use map (Florida Fish and Wildlife Conservation Commission). Based on land cover and ancillary data, potential gopher tortoise habitat was developed for northeast Florida.

Orientador: Jurandir Zullo Junior / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-13T05:57:27Z (GMT). No. of bitstreams: 1 Ramirez_GlauciaMiranda_D.pdf: 28885401 bytes, checksum: 676ec9c1c9823ae7accd5e51d3de1035 (MD5) Previous issue date: 2009 / Resumo: O café sempre foi sinônimo de progresso e contribuiu de maneira decisiva para a industrialização do Brasil sendo, ainda hoje, um dos seus produtos agrícolas mais importantes. A obtenção de informações precisas, em tempo hábil e com baixo custo, sobre a extensão e o rendimento da cultura, são instrumentos valiosos para um planejamento adequado da cultura no país. Dentre as técnicas que podem ser utilizadas, neste caso, o sensoriamento remoto é uma das que possuem um grande potencial de aplicação, principalmente considerando o aumento da disponibilidade de imagens de média resolução espacial e o advento das imagens de alta resolução espacial. Sendo assim, o objetivo geral do trabalho foi compreender as interações existentes entre os parâmetros biofísicos de cafezais e a resposta espectral registrada nas bandas de imagens dos satélites TM/LANDSAT e QUICKBIRD adquiridas em 24/01/2006 e 05/02/2006, respectivamente. Foram utilizados 30 talhões pertencentes a seis propriedades agrícolas, localizadas na região da Alta Mogiana, em São Paulo, entre os municípios de Ribeirão Corrente, Franca e Cristais Paulista. Os parâmetros biofísicos da cultura determinados a partir de dados de campo foram o espaçamento entre linhas e plantas, altura, IAF, diâmetro da copa, porcentagem de cobertura vegetal, rugosidade, variedade e biomassa. Foram utilizados valores de refletância real das bandas espectrais dos dois satélites e quatro índices de vegetação (NDVI, GVI, SAVI e RVI). Foi aplicado o teste de Tukey e realizadas análises de correlação, regressão e fatorial por componentes principais, utilizando os dados biofísicos e remotos disponíveis. Alguns parâmetros biofísicos não puderam ser estimados, mesmo com a melhoria da resolução espacial. Outros foram estimados (IAF, Biomassa e Altura) mesmo utilizando dados remotos de média resolução espacial. A análise de componentes principais permitiu separar plantios em produção, de áreas em formação, para as duas imagens, sendo que a associação dos parâmetros biofísicos "porcentagem de cobertura" e "densidade populacional" foi a principal responsável por estes resultados. Estes agrupamentos podem ser de grande utilidade na classificação automática de imagens. Apesar do avanço tecnológico proporcionado pelas imagens de alta resolução espacial, elas não se mostraram superiores a ponto de substituírem, mas complementarem as informações fornecidas pelas imagens de média resolução. / Abstract: Coffee has been synonymous of progress and has strongly contributed to the industrialization of Brazil. Nowadays, the coffee is still one of the most important Brazilian agricultural products. Precise, on time and low cost information about coffee area and yield are valuable tools for the crop planning in the country. For this purpose, remote sensing techniques show a great potential to be applied, especially considering the increased availability of medium spatial resolution images and the coming of high spatial resolution imagery. Thus, the main objective of this study was to understand the interactions between the biophysical parameters of coffee crops and the spectral response measured by the TM/LANDSAT and QUICKBIRD satellites spectral bands, acquired on 24/01/2006 and 05/02/2006, respectively. We used 30 coffee areas in six farms, located in the region of Alta Mogiana, in the State of São Paulo, between the municipalities Ribeirão Corrente, Franca e Cristais Paulista. The biophysical crop parameters determined from the field survey were the row and plants spacing, height, LAI, crown diameter, percentage of vegetation cover, roughness, variety and biomass. We used real values of reflectance from the spectral bands of both satellites and four vegetation indexes (NDVI, GVI, SAVI and RVI). Tukey test was applied and it was carried out the analysis of correlation, regression and factorial analysis through principal components by using the available remote and biophysical data. Some biophysical parameters could not be estimated, even with improved spatial resolution. Others were estimated (LAI, biomass and height), even using remote data of medium spatial resolution. The analysis of the main components allowed to separate crop lands in production and in formation in the two images. The combination of biophysical parameters "percentage of coverage" and "density" was the main responsible for these results. This technique can be very useful in the automatic classification of images. Despite the technological advances provided by the images of high spatial resolution, these images may not replace, but complement the information provided by medium-resolution images. / Doutorado / Planejamento e Desenvolvimento Rural Sustentável / Doutor em Engenharia Agrícola

Widespread mortality of quaking aspen (Populus tremuloides Michx.) has occurred over large expanses of the Western US during the 20th century. While much of this decline was due to conifer encroachment into seral aspen, significant aspen losses also occurred in areas of persistent aspen and may have been exasperated by drought conditions. Aspen decline has been especially notable at Cedar Mountain, Utah, an area of mostly private land and extensive persistent aspen coverage. The objectives of this study were to create a time series of live and dead aspen cover on the Cedar Mountain landscape, using remotely sensed imagery, and to test whether water stress correlated to the decline therein. To accomplish these objectives, a decision tree classifier was used to classify the Cedar Mountain area into live and dead aspen cover classes for the years 1985, 1990, 1995, 2001, 2005, and 2008. Thereafter, post-classification change analysis was performed to determine areas and time periods of elevated decline. Regression analyses were performed to ascertain correlations between climatic data and percent change in aspen cover. A topographic analysis using zonal statistics was also performed to determine landscape positions where aspen decline is more prevalent. The time series models indicated that aspen decline followed a step-wise pattern with an overall decrease of 23.57 % in aspen cover during a 23-year period. Considerable aspen decline occurred early in the study time frame, with decreases of 1.38 and 1.36 -1 in 1990 and 1995, respectively. The middle period between 1995 and 2001 had no net change in aspen cover. However, the end of the time series showed the greatest decline with decreases of 1.56 and 1.99 % yr-1 in 2005 and 2008, respectively. There was a correlation between percent change in aspen cover and precipitation, suggesting that drought weakens aspen, making it susceptible to future decline. The topographic zonal statistics revealed that drier landscape positions had greater frequencies of dead aspen. The most significant predictor of aspen decline was elevation, which was significantly greater in the live aspen for three of the five years.

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