The goal of this study is to apply the extraordinarily rich set of historical cartographic and remote sensing data of Cairo, Egypt to the analysis of the problem of informal development in the twentieth century. Remote sensing of urban areas has been dominated in recent years by multispectral analysis of Landsat imagery. This restricts studies both temporally and in spatial resolution. In this study an aerial photo interpretation methodology is applied to images and maps spanning two centuries of Cairo’s history at a spatial resolution on the scale of individual buildings. From these techniques insights can be obtained of the political and social forces shaping the development of Cairo.

Land cover change detection in urban areas provides valuable data on loss of forest and agricultural land to residential and commercial development. Using Landsat 5 Thematic Mapper (1991) and Landsat 7 ETM+ (2000) imagery of Gwinnett County, GA, change images were obtained using image differencing of Normalized Difference Vegetation Index (NDVI), principal components analysis (PCA), and Tasseled Cap-transformed images. Ground truthing and accuracy assessment determined that land cover change detection using the NDVI and Tasseled Cap image transformation methods performed best in the study area, while PCA performed the worst of the three methods assessed. Analyses on vegetative and vegetation changes from 1991- 2000 revealed that these methods perform well for detecting changes in vegetation and/or vegetative characteristics but do not always correspond with changes in land use. Gwinnett County lost an estimated 13,500 hectares of vegetation cover during the study period to urban sprawl, with the majority of the loss coming from forested areas.

Certain alteration minerals are used to identify the hydrothermally altered rocks. Potassic, phyllic (sericitic), propylitic, argillic and silicification are main alteration types observed in volcanic rocks. The role of remote sensing in alteration mapping is the differentiation of the minerals that are unique for In this study, Landsat TM 5 images are used. General alteration trend in the area is mapped by conventional methods of color composite, band rationing, principal component analysis and multi-linear regression analysis. Detailed mineral mapping carried on by using the United States Geological Survey (USGS) spectral library data. Spectral reflectances of selected minerals are analyzed according to the TM band intervals and appropriate band ratios are selected. TM bands 1,2,3,4,5 and 7 are used. Outputs of mineral maps are investigated for zonal distribution. Mineral maps that are obtained by the mineral separation method reveal that the youngest volcanic complex Hasandag is poorly altered. Instead, Ke&ccedil / iboyduran, Melendiz and Tepek&ouml / y volcanic complexes are found to be highly altered with the pattern of clay dominant in the center and increasing oxidation towards flanks. Also the alteration along the previously mapped buried faults is a proof that the method can provide information about the alteration source.

Anthropogenic disturbance in a landscape can take various forms, including residential development, which has substantial impact on the world’s ecosystems. Exurban development, characterized by low density residential development outside urban areas, was and continues to be one of the fastest growing forms of residential development in North America. It has disproportionately large ecological impacts relative to its footprint, yet is mostly overlooked in scientific studies. Specifically, a lack of spatially explicit (disaggregate) data on exurban development at regional level has contributed to a very limited understanding of this interspersed low density development. The main goal of this dissertation is to provide an increased understanding of exurban development in terms of its location, locating factors, and conservation and ecological implications at regional level, especially to enable incorporation of exurban information in the decision making processes. For this I asked four specific questions in this dissertation: (i) Where exactly is exurban development? (ii) What are the most likely factors that influence exurban development location? (iii) How does current and future development conflict with conservation goals? And (iv) What is the extent of the exurban development’s ecological impacts? Using a heterogeneous landscape, the County of Peterborough (Ontario, Canada), as the case study this dissertation undertook a number of separate yet related analyses that collectively provided the improved understanding of exurban development. The investigation of traditionally used surrogates for development, like roads and census data, and a more direct remote sensing method, using moderate resolution SPOT/HRVIR imagery, provided insights and contributed to development of spatially explicit data on exurban development. The evaluation of several commonly hypothesized locating factors in relation to exurban development revealed some of the major influences on the location of this development, especially in the context of Ontario. This research contributed to our understanding of the future risks of land conversion and identification of potential conflict areas between development and conservation plans in the study area. Lastly, examining the ecological impact of exurban development including associated roads, in terms of functions such as barrier effects and landscape connectivity, highlighted the importance of these seldom included anthropogenic disturbances in land and conservation planning. The contributions of this research to the existing body of knowledge are threefold. First, this dissertation reveals the limitations associated with existing methods used to map exurban development and presents a relatively easy, effective, automated and operational method to delineate exurban built areas at regional level using GIS and remote sensing. Second, the analyses conducted in this dissertation repeatedly highlights the importance of incorporating fine level details on exurban development in land and conservation planning as well as ecological impact assessments and presents methods and tools that can systematically and scientifically integrate this information in decision making framework. Third, this study conducted one of a kind, comprehensive and spatially explicit study on exurban development in Canada, where there is near absence of such research. With the rarely available exurban built footprint data delineated for the study area, this study not only identified the potential locating factors, future conversion risk, and conflict areas between development and conservation plans, but also quantified ecological impact in terms of landscape function, namely barrier effects and landscape connectivity, using a relatively novel circuit theoretic approach that can directly inform land and conservation decision planning process.

A high-resolution infrared Fourier Transform Spectrometer (FTS) has been operational at the Toronto Atmospheric Observatory (TAO)since May 2002. An optimal estimation retrieval technique is used to analyse the observed spectra and provide regular total and partial column measurements of trace gases in the troposphere and stratosphere as part of the Network for the Detection of Atmospheric Composition Change. The quality of these results were assessed through two ground-based validation campaigns, comparisons with three satellite instruments, and comparison with a three-dimensional chemical transport model. The two ground-based campaigns involved two lower-resolution FTS instruments: the University of Toronto FTS and the Portable Atmospheric Research Interferometric Spectrometer for the Infrared. The first campaign took place over the course of four months and is the longest side-by-side intercomparison of ground-based FTS instruments, to date. The second campaign was more focused and involved all three instruments measuring over a two-week period. Simultaneous measurements of O3, HCl, N2O, and CH4 were recorded and average total column differences were all < 3.7% in the extended campaign, and < 4.5% in the focused campaign. Satellite-based comparisons were done with the SCanning and Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Optical Spectrograph and InfraRed Imager System (OSIRIS). Total column CO, CH4, and N2O compared with SCIAMACHY all had average differences < 10% with results from the TAO-FTS being as good as, or better, than that of other instruments. Validation with the ACE-FTS showed that average partial columns of O3, NO2, N2O, CH4, and HCl were within 10% while observations of CO and NO each had an average bias of about 25%. Comparisons of monthly average partial column O3 and NO2 with OSIRIS were highly correlated (R = 0.82-0.97) with monthly mean differences of < 3.1% for O3 and < 2.6% for NO2. Finally, comparisons with the GEOS-Chem chemical transport model revealed that the model consistently over-estimates tropospheric columns of CO and C2H6 observed at TAO. It was determined that the enhanced CO values were partially due to the North American emissions specified in the model, but more work must be done in the future if the source of this discrepancy is to be fully explained.

L’oceanografia per satèl•lit ha esdevingut una integració consolidada de les tècniques convencionals de monitorització in situ dels oceans. Un coneixement precís dels processos oceanogràfics i de la seva interacció és fonamental per tal d’entendre el sistema climàtic. En aquest context, els camps de salinitat mesurats regularment constituiran directament una ajuda per a la caracterització de les variacions de la circulació oceànica global. La salinitat s’utilitza en models oceanogràfics predictius, pero a hores d’ara no és possible mesurar-la directament i de forma global. La missió Soil Moisture and Ocean Salinity (SMOS) (en català, humitat del sòl i salinitat de l’oceà) de l’Agència Espacial Europea pretén omplir aquest buit mitjançant la implementació d’un satèl•lit capaç de proveir aquesta informació sinòpticament i regular. Un nou instrument, el Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) (en català, radiòmetre d’observació per microones per síntesi d’obertura), ha estat desenvolupat per tal d’observar la salinitat de la superfície del mar (SSS) als oceans a través de l’adquisició d’imatges de la radiació de microones emesa al voltant de la freqüència de 1.4 GHz (banda L). SMOS portarà el primer radiòmetre orbital, d’òrbita polar, interferomètric 2D i es llençarà a principis de 2009. Així com a qualsevol altra estimació de paràmetres geofísics per teledetecció, la recuperació de la salinitat és un problema invers que implica la minimització d’una funció de cost. Per tal d’assegurar una estimació fiable d’aquesta variable, la resta de paràmetres que afecten a la temperatura de brillantor mesurada s’ha de tenir en compte, filtrar o quantificar. El producte recuperat seran doncs els mapes de salinitat per a cada passada del satèl•lit sobre la Terra. El requeriment de precisió proposat per a la missió és de 0.1 ‰ després de fer el promig en finestres espaciotemporals de 10 dies i de 20x20. En aquesta tesi de doctorat, diversos estudis s’han dut a terme per a la determinació del balanç d’error de la salinitat de l’oceà en el marc de la missió SMOS. Les motivacions de la missió, les condicions de mesura i els conceptes bàsics de radiometria per microones es descriuen conjuntament amb les principals característiques de la recuperació de la salinitat. Els aspectes de la recuperació de la salinitat que tenen una influència crítica en el procés d’inversió són: • El biaix depenent de l’escena en les mesures simulades, • La sensibilitat radiomètrica (soroll termal) i la precisió radiomètrica, • La definició de la modelització directa banda L • Dades auxiliars, temperatura de la superfície del mar (SST) i velocitat del vent, incerteses, • Restriccions en la funció de cost, particularment en el terme de salinitat, i • Promig espacio-temporal adequat. Un concepte emergeix directament de l’enunciat del problema de recuperació de la salinitat: diferents ajustos de l’algoritme de minimització donen resultats diferents i això s’ha de tenir en compte. Basant-se en aquesta consideració, la determinació del balanç d’error s’ha aproximat progressivament tot avaluant l’extensió de l’impacte de les diferents variables, així com la parametrització en termes d’error de salinitat. S’ha estudiat l’impacte de diverses dades auxiliars provinents de fonts diferents sobre l’error SSS final. Això permet tenir una primera impressió de l’error quantitatiu que pot esperar-se en les mesures reals futures, mentre que, en un altre estudi, s’ha investigat la possibilitat d’utilitzar senyals derivats de la reflectometria per tal de corregir les incerteses de l’estat del mar en el context SMOS. El nucli d’aquest treball el constitueix el Balanç d’Error SSS total. S’han identificat de forma consistent les fonts d’error i s’han analitzat els efectes corresponents en termes de l’error SSS mig en diferents configuracions d’algoritmes. Per una altra banda, es mostren els resultats d’un estudi de la variabilitat horitzontal de la salinitat, dut a terme utilitzant dades d’entrada amb una resolució espacial variable creixent. Això hauria de permetre confirmar la capacitat de la SSS recuperada per tal reproduir característiques oceanogràfiques mesoscàliques. Els principals resultats i consideracions derivats d’aquest estudi contribuiran a la definició de les bases de l’algoritme de recuperació de la salinitat. / Satellite oceanography has become a consolidated integration of conventional in situ monitoring of the oceans. Accurate knowledge of the oceanographic processes and their interaction is crucial for the understanding of the climate system. In this framework, routinely-measured salinity fields will directly aid in characterizing the variations of the global ocean circulation. Salinity is used in predictive oceanographic models, but no capability exists to date to measure it directly and globally. The European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) mission aims at filling this gap through the implementation of a satellite that has the potential to provide synoptically and routinely this information. A novel instrument, the Microwave Imaging Radiometer by Aperture Synthesis, has been developed to observe the sea surface salinity (SSS) over the oceans by capturing images of the emitted microwave radiation around the frequency of 1.4 GHz (L-band). SMOS will carry the first-ever, polar-orbiting, space-borne, 2-D interferometric radiometer and will be launched in early 2009. Like whatsoever remotely-sensed geophysical parameter estimation, the retrieval of salinity is an inverse problem that involves the minimization of a cost function. In order to ensure a reliable estimation of this variable, all the other parameters affecting the measured brightness temperature will have to be taken into account, filtered or quantified. The overall retrieved product will thus be salinity maps in a single satellite overpass over the Earth. The proposed accuracy requirement for the mission is specified as 0.1 ‰ after averaging in a 10-day and 2ºx2º spatio-temporal boxes. In this Ph.D. Thesis several studies have been performed towards the determination of an ocean salinity error budget within the SMOS mission. The motivations of the mission, the rationale of the measurements and the basic concepts of microwave radiometry have been described along with the salinity retrieval main features. The salinity retrieval issues whose influence is critical in the inversion procedure are: • Scene-dependent bias in the simulated measurements, • Radiometric sensitivity (thermal noise) and radiometric accuracy, • L-band forward modeling definition, • Auxiliary data, sea surface temperature (SST) and wind speed, uncertainties, • Constraints in the cost function, especially on salinity term, and • Adequate spatio-temporal averaging. A straightforward concept stems from the statement of the salinity retrieval problem: different tuning and setting of the minimization algorithm lead to different results, and complete awareness of that should be assumed. Based on this consideration, the error budget determination has been progressively approached by evaluating the extent of the impact of different variables and parameterizations in terms of salinity error. The impact of several multi-sources auxiliary data on the final SSS error has been addressed. This gives a first feeling of the quantitative error that should be expected in real upcoming measurements, whilst, in another study, the potential use of reflectometry-derived signals to correct for sea state uncertainty in the SMOS context has been investigated. The core of the work concerned the overall SSS Error Budget. The error sources are consistently binned and the corresponding effects in terms of the averaged SSS error have been addressed in different algorithm configurations. Furthermore, the results of a salinity horizontal variability study, performed by using input data at increasingly variable spatial resolution, are shown. This should assess the capability of retrieved SSS to reproduce mesoscale oceanographic features. Main results and insights deriving from these studies will contribute to the definition of the salinity retrieval algorithm baseline.

La humedad del suelo es la variable que regula los intercambios de agua, energía, y carbono entre la tierra y la atmósfera. Mediciones precisas de humedad son necesarias para una gestión sostenible de los recursos hídricos, para mejorar las predicciones meteorológicas y climáticas, y para la detección y monitorización de sequías e inundaciones. Esta tesis se centra en la medición de la humedad superficial de la Tierra desde el espacio, a escalas global y regional. Estudios teóricos y experimentales han demostrado que la teledetección pasiva de microondas en banda L es optima para la medición de humedad del suelo, debido a que la atmósfera es transparente a estas frecuencias, y a la relación directa de la emisividad del suelo con su contenido de agua. Sin embargo, el uso de la teledetección pasiva en banda L ha sido cuestionado en las últimas décadas, pues para conseguir la resolución temporal y espacial requeridas, un radiómetro convencional necesitaría una gran antena rotatoria, difícil de implementar en un satélite. Actualmente, hay tres principales propuestas para abordar este problema: (i) el uso de un radiómetro de apertura sintética, que es la solución implementada en la misión Soil Moisture and Ocean Salinity (SMOS) de la ESA, en órbita desde noviembre del 2009; (ii) el uso de un radiómetro ligero de grandes dimensiones y un rádar operando en banda L, que es la solución que ha adoptado la misión Soil Moisture Active Passive (SMAP) de la NASA, con lanzamiento previsto en 2014; (iii) el desarrollo de técnicas de desagregación de píxel que permitan mejorar la resolución espacial de las observaciones. La primera parte de la tesis se centra en el estudio del algoritmo de recuperación de humedad del suelo a partir de datos SMOS, que es esencial para obtener estimaciones de humedad con alta precisión. Se analizan diferentes configuraciones con datos simulados, considerando (i) la opción de añadir información a priori de los parámetros que dominan la emisión del suelo en banda L —humedad, rugosidad, temperatura del suelo, albedo y opacidad de la vegetación— con diferentes incertidumbres asociadas, y (ii) el uso de la polarización vertical y horizontal por separado, o del primer parámetro de Stokes. Se propone una configuración de recuperación de humedad óptima para SMOS. La resolución espacial de los radiómetros de SMOS y SMAP (40-50 km) es adecuada para aplicaciones globales, pero limita la aplicación de los datos en estudios regionales, donde se requiere una resolución de 1-10 km. La segunda parte de esta tesis contiene tres novedosas propuestas de mejora de resolución espacial de estos datos: • Se ha desarrollado un algoritmo basado en la deconvolución de los datos SMOS que permite mejorar la resolución espacial de las medidas. Los resultados de su aplicación a datos simulados y a datos obtenidos con un radiómetro aerotransportado muestran que es posible mejorar el producto de resolución espacial y resolución radiométrica de los datos. • Se presenta un algoritmo para mejorar la resolución espacial de las estimaciones de humedad de SMOS utilizando datos MODIS en el visible/infrarrojo. Los resultados de su aplicación a algunas de las primeras imágenes de SMOS indican que la variabilidad espacial de la humedad del suelo se puede capturar a 32, 16 y 8 km. • Un algoritmo basado en detección de cambios para combinar los datos del radiómetro y el rádar de SMAP en un producto de humedad a 10 km ha sido desarrollado y validado utilizando datos simulados y datos experimentales aerotransportados. Este trabajo se ha desarrollado en el marco de las actividades preparatorias de SMOS y SMAP, los dos primeros satélites dedicados a la monitorización de la variación temporal y espacial de la humedad de la Tierra. Los resultados presentados contribuyen a la obtención de estimaciones de humedad del suelo con la precisión y la resolución espacial necesarias para un mejor conocimiento del ciclo del agua y una mejor gestión de los recursos hídricos. / Soil moisture is a key state variable of the Earth's system; it is the main variable that links the Earth's water, energy and carbon cycles. Accurate observations of the Earth's changing soil moisture are needed to achieve sustainable land and water management, and to enhance weather and climate forecasting skill, flood prediction and drought monitoring. This Thesis focuses on measuring the Earth's surface soil moisture from space at global and regional scales. Theoretical and experimental studies have proven that L-band passive remote sensing is optimal for soil moisture sensing due to its all-weather capabilities and the direct relationship between soil emissivity and soil water content under most vegetation covers. However, achieving a temporal and spatial resolution that could satisfy land applications has been a challenge to passive microwave remote sensing in the last decades, since real aperture radiometers would need a large rotating antenna, which is difficult to implement on a spacecraft. Currently, there are three main approaches to solving this problem: (i) the use of an L-band synthetic aperture radiometer, which is the solution implemented in the ESA Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009; (ii) the use of a large lightweight radiometer and a radar operating at L-band, which is the solution adopted by the NASA Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014; (iii) the development of pixel disaggregation techniques that could enhance the spatial resolution of the radiometric observations. The first part of this work focuses on the analysis of the SMOS soil moisture inversion algorithm, which is crucial to retrieve accurate soil moisture estimations from SMOS measurements. Different retrieval configurations have been examined using simulated SMOS data, considering (i) the option of adding a priori information from parameters dominating the land emission at L-band —soil moisture, roughness, and temperature, vegetation albedo and opacity— with different associated uncertainties and (ii) the use of vertical and horizontal polarizations separately, or the first Stokes parameter. An optimal retrieval configuration for SMOS is suggested. The spatial resolution of SMOS and SMAP radiometers (~ 40-50 km) is adequate for global applications, but is a limiting factor to its application in regional studies, where a resolution of 1-10 km is needed. The second part of this Thesis contains three novel downscaling approaches for SMOS and SMAP: • A deconvolution scheme for the improvement of the spatial resolution of SMOS observations has been developed, and results of its application to simulated SMOS data and airborne field experimental data show that it is feasible to improve the product of the spatial resolution and the radiometric sensitivity of the observations by 49% over land pixels and by 30% over sea pixels. • A downscaling algorithm for improving the spatial resolution of SMOS-derived soil moisture estimates using higher resolution MODIS visible/infrared data is presented. Results of its application to some of the first SMOS images show the spatial variability of SMOS-derived soil moisture observations is effectively captured at the spatial resolutions of 32, 16, and 8 km. • A change detection approach for combining SMAP radar and radiometer observations into a 10 km soil moisture product has been developed and validated using SMAP-like observations and airborne field experimental data. This work has been developed within the preparatory activities of SMOS and SMAP, the two first-ever satellites dedicated to monitoring the temporal and spatial variation on the Earth's soil moisture. The results presented contribute to get the most out of these vital observations, that will further our understanding of the Earth's water cycle, and will lead to a better water resources management.

The increasing need for range-resolved aerosol and water-vapour atmospheric observation networks worldwide has given rise to multi-spectral LIDARs (Light Detection and Ranging, a synonym of laser radar) as advanced remote sensing sensors. This Ph.D. presents the design, integration and analysis of the new 6-channel multispectral elastic/Raman LIDAR for aerosol and water-vapour content monitoring developed at the Remote Sensing Lab. (RSLAB) of the Universitat Politècnica de Catalunya (UPC). It is well known that the combination of at least three elastic and two Raman nitrogen channels are sufficient to enable retrieval of the optical and microphysical properties of aerosols with a key impact on climate change variables. The UPC lidar is part of the EARLINET (European Aerosol Research Lidar Network) -GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network), a ground-based continental network including more than 28 stations. Currently, only 8 of the 28 EARLINET stations are of such advanced type. This Ph.D. specifically focuses on: (1) Concept link-budget instrument design and overlap factor assessment. The former includes opto-atmospheric parameter modelling and assessment of backscattered power and SNR levels, and maximum system range for the different reception channels (3 elastic, and 2 aerosol and 1 water-vapour Raman channels, ultraviolet to near-infrared bands). The latter studies the laser-telescope crossover function (or overlap function) by means of a novel ray-tracing Gaussian model. The problem of overlap function computation and its near-range sensitivity for medium size aperture (f/10, f/11) bi-axial tropospheric lidar systems using both detector and fiber-optics coupling alternatives at the telescope focal-plane is analysed using this new ray-tracing approach, which provides a much simpler solution than analytical-based methods. Sensitivity to laser divergence, field-lens and detector/fiber positions, and fiber¿s numerical aperture is considered. (2) Design and opto-mechanical implementation of the 6-channel polychromator (i.e., the spectrally selective unit in reception). Design trade-offs concerning light collimation, end-to-end transmissivity, net channel responsivity, and homogeneous spatial light distribution onto the detectors¿ active area discussed. (3) System integration and validation. This third part is two fold: On one hand, first-order backscatter-coefficient error bounds (a level-1 data product) for the two-component elastic lidar inversion algorithm are estimated for both random (observation noise) and systematic error sources (user¿s uncertainty in the backscatter-coefficient calibration, and user¿s uncertainty in the aerosol extinction-to-backscatter lidar ratio). On the other hand, the multispectral lidar so far integrated is described at both hardware and control software level. Statistical validation results for the new UPC lidar (today in routine operation) in the framework of SPALI-2010 intercomparison campaign are presented as part of EARLINET quality assurance / optimisation of instruments¿ program. The methodology developed in the first part of this Ph.D. has successfully been applied to the specification case study of the IFAE/UAB lidar system, which will be installed and operated at the Cherenkov Telescope Array (CTA) observatory. Finally, specs for automated unmanned unattended lidar operation with service times close to 365/24 are presented at the end of this Ph.D. in response to the increasing demand for larger observation times and availability periods of lidar stations.

Cities in developing countries are facing serious problems as a result of rapid urban population growth. Not the least of these problems is the creation of environmental stresses at the rural-urban fringe of these cities as they increase in area and envelop fertile surrounding agricultural lands. Because of this rapid rate of growth, sustainable urban environmental management (SUEM) policies and practices are often difficult to develop and implement proactively. This thesis argues that rapid population growth and subsequent urban expansion occurs such that urban form and function are built around the transportation network. In this context, a basic requirement for the facilitation of SUEM is the ability to be able to detect and extract indicators of urban expansion, in particular the road network, from available satellite remote sensing (RS) data. Subsequently, the indictors of growth derived from RS imagery can be integrated into a multi-source GIS database with ground-based census data to facilitate potential environmental stress analysis. The extraction of useful data from RS imagery for GIS-based analysis of urban growth is achieved through an integrated conceptual and operational framework presented in the thesis. This framework allows for environmental stress analysis at the urban periphery that can assist with the design of policies to contain urban growth.

Water quality and nonpoint source (NPS) pollution are important issues in many areas of the world, including the Greater Toronto Area where urban development is changing formerly rural watersheds into impervious surfaces. Impervious surfaces (i.e. roads, sidewalks, parking lots, strip malls, building rooftops, etc.) made out of impenetrable materials directly impact hydrological attributes of a watershed. Therefore, understanding the degree and spatial distribution of impervious surfaces in a watershed is an important component of overall watershed management. According to Environment Canada’s estimates, road salts, also considered nonpoint source pollutants, represent the largest chemical loading to Canadian surface waters. The main objective of this study is to verify the often assumed correlation between impervious surfaces and chlorides that result from the application of road salts, focusing on a case study in the selected six major watersheds within the Greater Toronto Area. In this study, Landsat-5 TM images from 1990, 1995, 2000, and 2005 were used in mapping urban impervious surface changes within the study area. Pixel-based unsupervised classification technique was utilized in estimation of percentage impervious surface coverage for each watershed. Chloride concentrations collected at Water Quality Monitoring Stations within the watersheds were then mapped against impervious surface estimates and their spatiotemporal distribution was assessed. In a GIS environment, remotely sensed impervious surface maps and chloride maps were overlaid for the investigation of their potential correlation. The main findings of this research demonstrate an average of 12.9% increase in impervious surface areas as well as a three-fold increase in chloride concentrations between 1990 and 2005. Water quality monitoring stations exhibiting the highest amounts of chloride concentrations correspond with the most impervious parts of the watersheds. The results also show a correlation (coefficient of determination of 0.82) between impervious surfaces and chloride concentrations. The findings demonstrate that the increase in imperviousness do generate higher chloride concentrations. Correspondingly, the higher levels of chloride can potentially degrade quality of surface waters in the region. Through an innovative integrated remote sensing approach, the study was successful in identifying areas most vulnerable to surface water quality degradation by road salts.