Spectral Band Selection for Ensemble Classification of Hyperspectral Images with Applications to Agriculture and Food Safety

In this dissertation, an ensemble non-uniform spectral feature selection and a kernel density decision fusion framework are proposed for the classification of hyperspectral data using a support vector machine classifier. Hyperspectral data has more number of bands and they are always highly correlated. To utilize the complete potential, a feature selection step is necessary. In an ensemble situation, there are mainly two challenges: (1) Creating diverse set of classifiers in order to achieve a higher classification accuracy when compared to a single classifier. This can either be achieved by having different classifiers or by having different subsets of features for each classifier in the ensemble. (2) Designing a robust decision fusion stage to fully utilize the decision produced by individual classifiers. This dissertation tests the efficacy of the proposed approach to classify hyperspectral data from different applications. Since these datasets have a small number of training samples with larger number of highly correlated features, conventional feature selection approaches such as random feature selection cannot utilize the variability in the correlation level between bands to achieve diverse subsets for classification. In contrast, the approach proposed in this dissertation utilizes the variability in the correlation between bands by dividing the spectrum into groups and selecting bands from each group according to its size. The intelligent decision fusion proposed in this approach uses the probability density of training classes to produce a final class label. The experimental results demonstrate the validity of the proposed framework that results in improvements in the overall, user, and producer accuracies compared to other state-of-the-art techniques. The experiments demonstrate the ability of the proposed approach to produce more diverse feature selection over conventional approaches

Mapping Cropland abandonment in the Aral Sea Basin with MODIS time series

© 2018 by the authors. Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003-2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, "stratum-specific" classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a "global" classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation

Movimentos naturais de massa na Serra do Divisor no extremo oeste da Amazônia Ocidental.

Os movimentos de massa, também conhecidos como deslizamento, escorregamentos e erosões, que causam a desagregação e transporte do solo, ocasionado por fatores naturais como precipitação, terremotos ou ventos. Estes eventos têm impactos ambientais e/ou sociais, dependendo do contexto geográfico que estão inseridos. O presente trabalho teve como objetivo analisar a dinâmica espaço-temporal do movimento natural no Complexo Fisiográfico da Serra do Divisor e sua modificação da paisagem. Para tanto fez-se um resgate de imagens Landsat e avaliou-se a extensão das alterações ao longo de 18 anos e sua correlação com precipitação e eventos tectônicos. Os resultados revelaram que houve incremento de até oito vezes na perda de solo após o ano de 2010. Este fato está associado as condições íngremes do relevo, precipitação mensal acima de 300 mm (milímetros) e eventos tectônicos de magnitude superior a 6 mb (magnitude de ondas primárias). Os movimentos naturais de massa na região norte do Complexo Fisiográfico da Serra do Divisor fazem parte da dinâmica natural de evolução da paisagem da região, entretanto quando eventos de precipitação e terremotos de alta magnitude mesmo que em altas profundidades, tiveram resultados no desencadeamento de processos movimento de massa de mais de 3.000 ha. A região de estudo, formado por rochas de arenito, solos rasos e pedogeniticamente jovens, mesmo que sob a cobertura florestal nativa, é vulnerável a processo erosivos do solo por movimentos de massa. Mass movements, also known as landslides, landslides and erosions, cause the soil to break down and transport, caused by natural factors such as precipitation, earthquakes or winds. These events have environmental and/or social impacts, depending on the geographic context in which they are inserted. The present work aimed to analyze the spatiotemporal dynamics of natural movement in the Serra do Divisor Physiographic Complex and its modification of the landscape. For this purpose, Landsat images were retrieved and the extent of changes over 18 years and their correlation with precipitation and tectonic events were evaluated. The results revealed that there was an increase of up to eight times in soil loss after the year 2010. This fact is associated with steep relief conditions, monthly precipitation above 300 mm (millimeters) and tectonic events of magnitude greater than 6 mb (magnitude of primary waves). The natural mass movements in the northern region of the Serra do Divisor Physiographic Complex are part of the natural dynamics of landscape evolution in the region, however when precipitation events and high magnitude earthquakes, even at high depths, had results in triggering movement processes of mass of more than 3,000 ha. The study region, formed by sandstone rocks, shallow and pedogenically young soils, even under native forest cover, is vulnerable to soil erosion by mass movements. Los movimientos masivos, también conocidos como deslizamientos de tierra, deslizamientos de tierra y erosiones, hacen que el suelo se rompa y se transporte, causado por factores naturales como precipitaciones, terremotos o vientos. Estos eventos tienen impactos ambientales y / o sociales, dependiendo del contexto geográfico en el que se insertan. El presente trabajo tuvo como objetivo analizar la dinámica espacio-temporal del movimiento natural en el Complejo Fisiográfico Serra do Divisor y su modificación del paisaje. Para ello, se recuperaron imágenes Landsat y se evaluó la extensión de los cambios a lo largo de 18 años y su correlación con la precipitación y los eventos tectónicos. Los resultados revelaron que hubo un aumento de hasta ocho veces en la pérdida de suelo después del año 2010. Este hecho está asociado con condiciones de relieve abrupto, precipitación mensual superior a 300 mm (milímetros) y eventos tectónicos de magnitud superior a 6 mb (magnitud de ondas primarias). Los movimientos naturales de masas en la región norte del Complejo Fisiográfico Serra do Divisor son parte de la dinámica natural de la evolución del paisaje en la región, sin embargo, cuando los eventos de precipitación y los terremotos de gran magnitud, incluso a grandes profundidades, tuvieron como resultado el desencadenamiento de procesos de movimiento de masas. de más de 3.000 ha. La región de estudio, formada por rocas areniscas, suelos poco profundos y pedogénicamente jóvenes, incluso bajo la cubierta forestal nativa, es vulnerable a la erosión del suelo por movimientos masivos