A rede de drenagem se constitui em importante indicador de alterações ocorridas na composição da paisagem de bacias hidrográficas, seja por mudanças na sua estruturação, forma ou então por ganho ou perda de canais. O objetivo deste trabalho é apresentar e aplicar uma proposta metodológica, com base em análise morfométrica temporal das redes de drenagem de microbacias, visando a avaliação das alterações e o zoneamento regional de uma bacia hidrográfica. A metodologia envolve o uso de imagens de sensoriamento remoto e técnicas de geoprocessamento para a caracterização das atividades antrópicas e levantamento das variáveis morfométricas em duas datas, com um intervalo de 23 anos. A avaliação das alterações e a consequente classificação das microbacias são efetuadas com base em análise estatística multivariada. A proposta foi aplicada na bacia hidrográfica do rio Capivari e os resultados comprovam que ocorreram alterações significativas na composição da rede de drenagem no período de análise. As variáveis morfométricas que mais contribuíram para a avaliação das alterações foram a Densidade de Drenagem e Densidade Hidrográfica. Dentre as microbacias que mais se alteraram estão as urbanas ou em processo de urbanização e, dentre aquelas onde as alterações foram menos pronunciadas estão as microbacias rurais, com predomínio de pastagens e/ou cana de açúcar. / The drainage system is an important indicator of the alterations occurred in the composition of the hydrographic basin environment, either due to changes in their structure and shape or due to channel loss and gain. The objective of this project is to present and apply a methodological proposal, based on time morphometric analysis of the microbasin drainage systems, aiming at the alteration evaluation and the regional zoning of a hydrographic basin. The methodology involves the use of remote images and geoprocessing techniques for the characterization of the anthropic activities and the determination of the morphometric variables on two dates, with a 23-year interval. The evaluation of the alterations and the consequent microbasin classification are carried out based on multivariate statistical analysis. The proposal was applied on Capivari river hydrographic basin, and the results prove that there were significative alterations in the drainage system composition in the analyzed period. The morphometric variables which most contributed to the alteration evaluation were the Drainage Density and the Hydrographic Density. Among the microbasins which were most altered there are the urban and under urbanization ones, and among those which had less significative alterations there are the rural microbasins, prevailing the pasture lands and sugar-cane raising.

Em um exame mamográfico, quando os fótons de raios-X incidem sobre a mama, uma parte destes fótons é transmitida sem ser desviada da trajetória inicial (radiação transmitida primária), permitindo a formação da imagem mamográfica, e outra é dispersa de sua trajetória inicial pelo tecido (radiação espalhada), atuando de forma deletéria na imagem mamográfica. Entretanto, recentes investigações têm demonstrado que a radiação espalhada pode ser útil na caracterização de tecidos. O objetivo deste trabalho é desenvolver um modelo de diagnóstico de alterações no tecido mamário utilizando as informações presentes na distribuição angular da radiação espalhada (perfil de espalhamento). Os perfis de espalhamento de 40 amostras de tecidos mamários foram obtidos utilizando um difractômetro comercial SIEMENS D5005, operando em modo reflexão na energia de 8,04 keV e variando o detector da posição angular de 5º a 150º, correspondendo a um intervalo de x de 0,03Å-1 a 0,62 Å-1. As amostras de tecido foram previamente classificadas histopatologicamente como tecidos normais, fibroadenomas (neoplasias benignas) e diferentes tipos de carcinomas (neoplasias malignas). Neste trabalho, três modelos de diagnóstico baseados na análise estatística dos perfis de espalhamento foram desenvolvidos. O primeiro, analisa seis parâmetros extraídos dos perfis de espalhamento, já o segundo e o terceiro utilizam análise multivariada (análise de componentes principais e análise de discriminante, respectivamente) para reconhecimento de padrões. Para cada modelo, valores de sensibilidade, especificidade e índice de concordância entre o diagnóstico baseado no modelo utilizado e o diagnóstico histopatológico foram obtidos. Dentre os modelos desenvolvidos, aquele que utiliza análise de discriminante proporciona o melhor diagnóstico das alterações encontradas no tecido, permitindo diferenciar tecidos normais e neoplasias benignas e malignas. Com base nos resultados obtidos conclui-se que modelos baseados na análise estatística dos perfis de espalhamento permitem classificar histologicamente tecidos mamários. / In mammography, when x-ray photons reach the breast, a fraction of these photons is transmitted without interaction with any tissues (primary transmitted radiation), allowing the formation of the mammographic image, and another fraction of them is deviated by the tissue from its initial trajectories (scattered radiation), reducing the image contrast. However, recent investigations have demonstrated that scattered radiation can be a useful diagnostic tool. The purpose of this work is to develop a diagnostic model for breast tissue characterization using the angular distribution of the scattered radiation (scattering profile). The scattering profiles of 40 breast tissue samples were obtained in a SIEMENS D5005 diffractometer, operating in reflection mode at 8,04keV, and varying the angular position of the detector from 5º to 150º, corresponding to an x interval from 0,03 Å-1 to 0,62 Å-1. All tissue samples were previously classified histopathologically as normal tissues, fibroadenomas (benign alteration) and several types of carcinomas (malignant alteration). Three models of diagnostic based on the statistical analysis of the scattering profiles were developed. The first one was constructed using six parameters extracted from the scattering profiles and the second and third models used the whole information from the scattering profiles. The latter two used multivariate analysis (principal component analysis and discriminant analysis, respectively) for pattern recognition. For each model, values of sensitivity, specificity and rate of agreement between the model diagnostic and histopathological results were obtained. Among the developed models, the discriminant analysis provides the best diagnostic of the lesions present in the tissues (normal tissues, benign and malignant alterations). From the results, it is possible to conclude that models based on the statistical analysis of the scattering profiles allow the histological classification of breast tissues.

A metabolômica vem se tornando uma abordagem eficaz para a avaliação abrangente de plantas medicinais, classificação de matérias-primas, além de estudos quimiotaxonômicos. Este trabalho demonstra a aplicabilidade da metabolômica, utilizando a subfamília Barnadesioideae (Asteraceae) como modelo de estudo, na avaliação da qualidade e classificação de espécies medicinais (espécies de Chuquiraga) e no estudo quimiotaxonômico dos principais gêneros de Barnadesioideae (Arnaldoa, Barnadesia, Chuquiraga, Dasyphyllum, Fulcaldea e Schlechtendalia). Em primeiro lugar, a análise dos perfis metabólicos por LC-MS dos membros de Barnadesioideae demonstrou que esta subfamília constitui um grupo quimicamente não explorado com uma diversidade complexa de substancias fenólicas, fenilpropanoides, alquilglicósidos e glicosídeos triterpenoides. As relações intergenéricas dentro da subfamília Barnadesioideae, baseadas na comparação dos seus perfis metabólicos por análises estatísticas multivariadas, mostraram semelhanças com as relações intergenéricas propostas pelo mais recente estudo filogenético com base em marcadores morfológicos e moleculares. Em segundo lugar, a aquisição dos perfis metabólicos de espécies de Chuquiraga (C. jussieui, C. spinosa e C. weberbaueri) por analises de LC-MS, levaram à identificação de uma variedade significativa de compostos fenólicos, fenilpropanoides, alquilglicosídeos e glicosídeos triterpenoides, assim como o estabelecimento de modelos de classificação geográfica e de espécies, além da identificação de metabólitos discriminantes por meio de análises estatísticas multivariadas exploratórias e supervisionadas. Terceiro, uma abordagem clássica foi realizada através da aquisição dos perfis cromatográficos por HPLC de espécies de Chuquiraga para o perfilhamento de compostos fenólicos e a classificação das espécies por meio de análises estatísticas multivariadas exploratórias e supervisionadas. Logo, os resultados revelam a metabolômica como uma valiosa ferramenta auxiliar no controle de qualidade e classificação de plantas medicinais, bem como em estudos de quimiotaxonômia / Metabolomics is emerging as an effective approach for the comprehensive evaluation of medicinal plants, classification of raw material, as well as chemotaxonomic studies. This work demonstrates the applicability of metabolomics, using the subfamily Barnadesioideae (Asteraceae) as a study model, for quality assessment and classification purposes of medicinal species (Chuquiraga genus) and a chemotaxonomy study of six Barnadesioideae genera (Arnaldoa, Barnadesia, Chuquiraga, Dasyphyllum, Fulcaldea and Schlechtendalia). First, the LC-MS metabolic profiles of Barnadesioideae demonstrated that this subfamily constitutes a chemically underinvestigated taxa with a complex diversity of phenolic compounds, phenylpropanoid derivatives, alkyl glycosides, and triterpenoid glycosides. The intergeneric relationships within Barnadesioideae genera, based on the comparison of their LC-MS metabolic profiles by exploratory and supervised analyses, displayed similarities to those of the intergeneric relationships obtained by the most recent phylogenetic study based on morphological and molecular markers. Second, the LC-MS metabolic profiles of three Chuquiraga species (C. jussieui, C. spinosa and C. weberbaueri) lead to the identification of a significant variety of phenolic compounds, phenylpropanoid derivatives, alkyl glycosides, and triterpenoid glycosides, as well as the establishment of prediction models for geographical origin and species classification, as well as the identification of discriminating metabolites by exploratory and supervised multivariate statistical analysis. Third, a classical approach was carried out by acquiring HPLC chromatographic profiles of three Chuquiraga species (C. jussieui, C. spinosa and C. weberbaueri) for profiling phenolic compounds and comparison by exploratory and supervised multivariate statistical analysis. Therefore, our results support metabolomics as a valuable tool in the quality control and classification of medicinal plants as well as in chemotaxonomy studies.

Η παρούσα μελέτη παρουσιάζει τρία μεθοδολογικά σχήματα τα οποία μπορούν να εφαρμοστούν στην χωρική και χρονική ανάλυση δεδομένων για την διαχείριση των υδατικών πόρων. Αποτελείται από τρία ανεξάρτητα μεταξύ τους τμήματα τα οποία είναι : α)Χρήση Γεωγραφικών Συστημάτων Πληροφοριών και Πολυδιάστατης Στατιστικής Ανάλυσης για την διερεύνηση των σχέσεων μεταξύ υπόγειων υδάτων και χρήσεων γης β)Μελέτη χρονικών υδροχημικών δεδομένων από ένα μεγάλης διάρκειας πρόγραμμα παρακολούθησης σε μιά ρηχή λίμνη με χρήση Πολυδιάστατης Στατιστικής Ανάλυσης και γ)Εφαρμογή της Clean φασματικής ανάλυσης σε υδροχημικά δεδομένα : Παραδείγματα από δύο λίμνες της Ελλάδας. / The present study intoduces three methodologies which can be applied in water resource management. It consist of three independed projects : a)Indentifing relationships between groundwater quality and landuse using GIS and Multivariate Statistical Analysis b)A long-term study of temporal hydrochemical data in a shallow lake using multivariate statistical techniques and c)Application of Clean Spectral Analysis to hydrochemical data : Case studies from two lakes, Greece.

Em um exame mamográfico, quando os fótons de raios-X incidem sobre a mama, uma parte destes fótons é transmitida sem ser desviada da trajetória inicial (radiação transmitida primária), permitindo a formação da imagem mamográfica, e outra é dispersa de sua trajetória inicial pelo tecido (radiação espalhada), atuando de forma deletéria na imagem mamográfica. Entretanto, recentes investigações têm demonstrado que a radiação espalhada pode ser útil na caracterização de tecidos. O objetivo deste trabalho é desenvolver um modelo de diagnóstico de alterações no tecido mamário utilizando as informações presentes na distribuição angular da radiação espalhada (perfil de espalhamento). Os perfis de espalhamento de 40 amostras de tecidos mamários foram obtidos utilizando um difractômetro comercial SIEMENS D5005, operando em modo reflexão na energia de 8,04 keV e variando o detector da posição angular de 5º a 150º, correspondendo a um intervalo de x de 0,03Å-1 a 0,62 Å-1. As amostras de tecido foram previamente classificadas histopatologicamente como tecidos normais, fibroadenomas (neoplasias benignas) e diferentes tipos de carcinomas (neoplasias malignas). Neste trabalho, três modelos de diagnóstico baseados na análise estatística dos perfis de espalhamento foram desenvolvidos. O primeiro, analisa seis parâmetros extraídos dos perfis de espalhamento, já o segundo e o terceiro utilizam análise multivariada (análise de componentes principais e análise de discriminante, respectivamente) para reconhecimento de padrões. Para cada modelo, valores de sensibilidade, especificidade e índice de concordância entre o diagnóstico baseado no modelo utilizado e o diagnóstico histopatológico foram obtidos. Dentre os modelos desenvolvidos, aquele que utiliza análise de discriminante proporciona o melhor diagnóstico das alterações encontradas no tecido, permitindo diferenciar tecidos normais e neoplasias benignas e malignas. Com base nos resultados obtidos conclui-se que modelos baseados na análise estatística dos perfis de espalhamento permitem classificar histologicamente tecidos mamários. / In mammography, when x-ray photons reach the breast, a fraction of these photons is transmitted without interaction with any tissues (primary transmitted radiation), allowing the formation of the mammographic image, and another fraction of them is deviated by the tissue from its initial trajectories (scattered radiation), reducing the image contrast. However, recent investigations have demonstrated that scattered radiation can be a useful diagnostic tool. The purpose of this work is to develop a diagnostic model for breast tissue characterization using the angular distribution of the scattered radiation (scattering profile). The scattering profiles of 40 breast tissue samples were obtained in a SIEMENS D5005 diffractometer, operating in reflection mode at 8,04keV, and varying the angular position of the detector from 5º to 150º, corresponding to an x interval from 0,03 Å-1 to 0,62 Å-1. All tissue samples were previously classified histopathologically as normal tissues, fibroadenomas (benign alteration) and several types of carcinomas (malignant alteration). Three models of diagnostic based on the statistical analysis of the scattering profiles were developed. The first one was constructed using six parameters extracted from the scattering profiles and the second and third models used the whole information from the scattering profiles. The latter two used multivariate analysis (principal component analysis and discriminant analysis, respectively) for pattern recognition. For each model, values of sensitivity, specificity and rate of agreement between the model diagnostic and histopathological results were obtained. Among the developed models, the discriminant analysis provides the best diagnostic of the lesions present in the tissues (normal tissues, benign and malignant alterations). From the results, it is possible to conclude that models based on the statistical analysis of the scattering profiles allow the histological classification of breast tissues.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Os aqÃÃferos aluviais presentes na regiÃo semi-Ãrida do Nordeste brasileiro hospedam importantes recursos hÃdricos naturais para as populaÃÃes que vivem nessa regiÃo, devido a sua excelente qualidade, quando comparado aos aqÃÃferos localizados nas Ãreas de embasamento cristalino. No entanto, constituem recursos frÃgeis, sendo susceptÃveis a processos de degradaÃÃo da sua qualidade por aÃÃes antrÃpicas, variaÃÃes climÃticas ou modificaÃÃes hidrogeolÃgicas. Com o objetivo de identificar e quantificar os principais processos responsÃveis pelo aumento da salinidade observada no aqÃÃfero aluvial durante o perÃodo nÃo chuvoso usou-se, alÃm de estudos hidroquÃmicos (diagramas e estudo de razÃes iÃnicas), a anÃlise estatÃstica multivariada (agrupamento hierÃrquico e discriminante) e a modelagem geoquÃmica inversa. Os diagramas de Piper e Stiff mostraram a classificaÃÃo das Ãguas quanto à presenÃa dos Ãons dominantes, onde as Ãguas aluviais apresentaram caracterÃsticas intermediÃrias entre as Ãguas do aqÃÃfero fissural e Ãgua dos reservatÃrios. Com o diagrama de RAS obteve-se a mesma interpretaÃÃo. As relaÃÃes iÃnicas revelaram forte relaÃÃo das Ãguas aluviais com a litologia da regiÃo e a provÃvel dissoluÃÃo de aerossÃis contendo compostos de MgCl2 nos aqÃÃferos do embasamento cristalino. A anÃlise de agrupamento mostrou as similaridades entre os poÃos, enquanto a anÃlise discriminante ajudou a compreender o processo de salinizaÃÃo no aqÃÃfero aluvial. As modelagens geoquÃmicas inversas realizadas com o PHREEQC identificaram trocas catiÃnicas de CaX2, MgX2, NaX e KX, alÃm de precipitaÃÃes de K-mica e albita e dissoluÃÃes de anortita e K-feldspato, evidenciando a aÃÃo intempÃrica das Ãguas sobre as rochas. A grande dissoluÃÃo de CO2 nas Ãguas aluviais justifica a caracterÃstica bicarbonatada dessas Ãguas. A contribuiÃÃo volumÃtrica de Ãguas do aqÃÃfero fissural, como forma de justificar o aumento da salinidade nos poÃos aluviais, foi estimada entre 1,53% e 27,99% para diferentes pontos, na mÃdia foi de 15,8%. No entanto, esta contribuiÃÃo representa quase 64% da salinidade no aluviÃo. / The alluvial aquifers in the semi-arid region of Brazilâs Northeast host an important natural water resource for the populations that live in that region, owing to its excellent quality, when compared to the crystalline basement rock aquifers. However, they are fragile resources and are susceptible to processes of degradation of quality by anthropic action, climatic changes or hydrogeological modifications. The objective of this research is to identify and quantify the primary processes responsible for the increase in salinity observed in the alluvial aquifers during the dry season. Besides hydrochemical analysis (Piper and Stiff diagrams and ionic relations), multivariate statistical analysis (hierarchical clustering and discriminant analyses) and inverse geochemical modeling were also used. The Piper and Stiff diagrams presented water classification according to dominant ions, where the alluvial water showed intermediate characteristics between the hard-rock basement aquifer water and that from the reservoirs. With the SAR diagram, the same result was observed. The ionic relations revealed a strong relation of the alluvial water with the lithology of the region and the probable dissolution of aerosols containing composites of the MgCl2 type in the aquifers of the crystalline rock shield. Cluster analysis showed the similarities between the wells, whereas discriminant analysis helped to understand the process of salinization in the alluvial aquifer. The inverse geochemical modeling carried out with PHREEQC identified cationic exchanges of CaX2, MgX2, NaX and KX, as well as precipitation of K-mica and albite and dissolutions of anorthite and K-feldspar, evidencing the intemperic action of the water on the rocks. Strong dissolution of CO2 in the alluvial water justifies the bicarbonated characteristics of that water. The volume contribution from crystalline rock aquifer water was estimated as between 1.53% and 27.99% at different points with a mean value of 15.8%. However, this contribution represents nearly 64% of the salinity of the water in the alluvium.

A rede de drenagem se constitui em importante indicador de alterações ocorridas na composição da paisagem de bacias hidrográficas, seja por mudanças na sua estruturação, forma ou então por ganho ou perda de canais. O objetivo deste trabalho é apresentar e aplicar uma proposta metodológica, com base em análise morfométrica temporal das redes de drenagem de microbacias, visando a avaliação das alterações e o zoneamento regional de uma bacia hidrográfica. A metodologia envolve o uso de imagens de sensoriamento remoto e técnicas de geoprocessamento para a caracterização das atividades antrópicas e levantamento das variáveis morfométricas em duas datas, com um intervalo de 23 anos. A avaliação das alterações e a consequente classificação das microbacias são efetuadas com base em análise estatística multivariada. A proposta foi aplicada na bacia hidrográfica do rio Capivari e os resultados comprovam que ocorreram alterações significativas na composição da rede de drenagem no período de análise. As variáveis morfométricas que mais contribuíram para a avaliação das alterações foram a Densidade de Drenagem e Densidade Hidrográfica. Dentre as microbacias que mais se alteraram estão as urbanas ou em processo de urbanização e, dentre aquelas onde as alterações foram menos pronunciadas estão as microbacias rurais, com predomínio de pastagens e/ou cana de açúcar. / The drainage system is an important indicator of the alterations occurred in the composition of the hydrographic basin environment, either due to changes in their structure and shape or due to channel loss and gain. The objective of this project is to present and apply a methodological proposal, based on time morphometric analysis of the microbasin drainage systems, aiming at the alteration evaluation and the regional zoning of a hydrographic basin. The methodology involves the use of remote images and geoprocessing techniques for the characterization of the anthropic activities and the determination of the morphometric variables on two dates, with a 23-year interval. The evaluation of the alterations and the consequent microbasin classification are carried out based on multivariate statistical analysis. The proposal was applied on Capivari river hydrographic basin, and the results prove that there were significative alterations in the drainage system composition in the analyzed period. The morphometric variables which most contributed to the alteration evaluation were the Drainage Density and the Hydrographic Density. Among the microbasins which were most altered there are the urban and under urbanization ones, and among those which had less significative alterations there are the rural microbasins, prevailing the pasture lands and sugar-cane raising.

To manufacture safe, effective and affordable medicines with greater efficiency, process analytical technology (PAT) has been introduced by the Food and Drug Agency to encourage the pharmaceutical industry to develop and design well-understood processes. PAT requires chemical imaging techniques to be used to collect process variables for real-time process analysis. Multivariate statistical analysis tools and process control tools are important for implementing PAT in the development and manufacture of pharmaceuticals as they enable information to be extracted from the PAT measurements. Multivariate statistical analysis methods such as principal component analysis (PCA) and independent component analysis (ICA) are applied in this thesis to extract information regarding a pharmaceutical tablet. ICA was found to outperform PCA and was able to identify the presence of five different materials and their spatial distribution around the tablet.Another important area for PAT is in improving the control of processes. In the pharmaceutical industry, many of the processes operate in a batch strategy, which introduces difficult control challenges. Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that has been used extensively to extract chemical and physical information from a product sample based on the scattering effect of light. In this thesis, NIR measurements were incorporated as feedback information into several control strategies. Although these controllers performed reasonably well, they could only regulate the NIR spectrum at a number of wavenumbers, rather than over the full spectrum.In an attempt to regulate the entire NIR spectrum, a novel control algorithm was developed. This controller was found to be superior to the only comparable controller and able to regulate the NIR similarly. The benefits of the proposed controller were demonstrated using a benchmark simulation of a batch reactor.

Characterization of post-translational modifications (PTMs) of therapeutic proteins is very important during the bioprocess development to maintain desired product quality and during the submission process to regulatory authorities for product approval. Monitoring glycosylation in pharmacokinetic studies can be useful to evaluate the dependence of clearance rates on different glycoforms. The cost and efficiency of characterization affect the speed to market of biopharmaceutical proteins. A reduction in the number of manual processing steps, cost of reagents and consumption of sample, as well as the time required for chemical analysis, is therefore necessary. The research presented in this thesis is focused on the potential of using microfluidic discs for automated, miniaturized, parallel and rapid sample preparation for PTM characterization of therapeutic monoclonal antibodies. Paper I describes the method development for N-linked glycosylation profiling. Several sample preparation steps have been performed in an integrated process in the microfluidic compact disc (CD). Paper II demonstrates the use of the method presented in paper I in combination with multivariate statistics for discrimination of glycosylation profiles of different therapeutic antibodies and simulation of a real case of quality control. Paper III is focused on a method for monitoring changes in glycosylation profiles of therapeutic antibodies in serum over time by incubation with an exoglycosidase enzyme. Paper IV describes the method for peptide mapping of therapeutic antibodies. In addition, recent work (unpublished results) assesses the potential of this method for methionine oxidation detection. The developed methods were fast, robust with low sample/reagent consumption. Generation of glycosylation profile data for one sample was established in approximately 2 h. The amount of samples and antigens loaded into the CD platform for one replicate was less than 0.3 μg and approximately 0.06 μg, respectively. Furthermore, considering the parallel function of the CD, conducting the analysis for 54 samples can be completed within a day. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>

The overall objective of this dissertation research is to understand the spatiotemporal dynamics of water quality parameters in different water bodies of South Florida. Two major approaches (multivariate statistical techniques and remote sensing) were used in this study. Multivariate statistical techniques include cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), discriminant analysis (DA), absolute principal component score-multiple linear regression (APCS-MLR) and PMF receptor modeling techniques were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, a 15-year (2000–2014) data set of 12 water quality variables, and about 35,000 observations were used. Agglomerative hierarchical CA grouped 16 monitoring sites into three groups (low pollution, moderate pollution, and high pollution) based on their similarity of water quality characteristics. DA, as an important data reduction method, was used to assess the water pollution status and analysis of its spatiotemporal variation. PCA/FA identified potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules, and causes were explained. The APCS-MLR and PMF models apportioned their contributions to each water quality variable. Also, the bio-physical parameters associated with the water quality of the two important water bodies of Lake Okeechobee and Florida Bay were investigated based on remotely sensed data. The principal objective of this part of the study is to monitor and assess the spatial and temporal changes of water quality using the application of integrated remote sensing, GIS data, and statistical techniques. The optical bands in the region from blue to near infrared and all the possible band ratios were used to explore the relation between the reflectance of a waterbody and observed data. The developed MLR models appeared to be promising for monitoring and predicting the spatiotemporal dynamics of optically active and inactive water quality characteristics in Lake Okeechobee and Florida Bay. It is believed that the results of this study could be very useful to local authorities for the control and management of pollution and better protection of water quality in the most important water bodies of South Florida.