Dissertations / Theses on the topic 'Remote sounding from satellites'

Measurements of the refractive bending of solar radiation passing through the limb of the Earth's atmosphere can be utilized to recover vertical profiles of density and temperature. These parameters obtained using the technique of solar refractive sounding could be used to improve satellite solar occultation trace species retrievals and to monitor potential trends in upper atmospheric temperatures. The solar refractive sounding method is described in detail and applied to data available from the Stratospheric Aerosol and Gas Experiment (SAGE II). The meteorological profiles derived from the SAGE II data are not consistently accurate enough for general use due to poor vertical sampling and measurement uncertainties. However, the qualitatively decent results provide optimism for future development and implementation of solar occultation refractive sounders. Better techniques for measuring solar refraction and the potential improvements in the retrievals are also discussed.

Global Navigation Satellite Systems Reflectometry (GNSS-R) is a multi-static radar using navigation signals as signals of opportunity. It provides wide-swath and improved spatio-temporal sampling over current space-borne missions. The lack of experimental datasets from space covering signals from multiple constellations (GPS, GLONASS, Galileo, Beidou) at dual-band (L1 and L2) and dual-polarization (Right Hand Left Hand Circular Polarization: RHCP and LHCP), over the ocean, land and cryosphere remains a bottleneck to further develop these techniques. 3Cat-2 is a 6 units (3 x 2 elementary blocks of 10 x 10 x 10 cm3) CubeSat mission ayming to explore fundamentals issues towards an improvement in the understanding of the bistatic scattering properties of different targets. Since geolocalization of specific reflections points is determined by the geometry only, a moderate pointing accuracy is still required to correct for the antena pattern in scatterometry measurements. 3Cat-2 launch is foreseen for the first quarter 2016 into a Sun-Synchronous orbit of 510 km height using a Long March II D rocket. This Ph.D. Thesis represents the main contributions to the development of the 3Cat-2 GNSS-R Earth observation mission (6U CubeSat) including a novel type of GNSS-R technique: the reconstructed one. The desing, development of the platform, and a number of ground-based, airborne and stratospheric balloon experiments to validate the technique and to optimize the instrument. In particular, the main contributions of this Ph.D. thesis are: 1) A novel dual-band Global Navigation Satellite Systems Reflectometer that uses the P(Y) and C/A signals scattered over the sea surface to perform highly precise altimetric measurements (PYCARO). 2) The first proof-of-concept of PYCARO was performed during two different ground-based field experiments over a dam and over the sea under different surface roughness conditions. 3) The scattering of GNSS signals over a water surface has been studied when the receiver is at low height, as for GNSS-R coastal altimetry applications. The precise determination of the local sea level and wave state from the coast can provide useful altimetry and wave information as "dry" tide and wave gauges. In order to test this concept an experiment has been conducted at the Canal d'Investigació i Experimentació Marítima (CIEM) wave channel for two synthetic "sea" states. 4) Two ESA-sponsored airborne experiments were perfomed to test the precision and the relative accuracy of the conventional GNSS-R. 5) The empirical results of a GNSS-R experiment on-board the ESA-sponsored BAXUS 17 stratospheric balloon campaign performed North of Sweden over boreal forests showed that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time. 6) An improved version of the PYCARO payload was tested in Octover 2014 for the second time during the ESA-sposored BEXUS-19,. This work achieved the first ever dual-frequency, multi-constellation GNSS-R observations over boreal forests and lakes using GPS, GLONASS and Galileo signals. 7) The first-ever dual-frequency multi-constellation GNSS-R dual-polarization measurements over boreal forests and lakes were obtained from the stratosphere during the BEXUS 19 using the PYCARO reflectometer operated in closed-loop mode.
Global Navigation Satellite Systems Reflectometry (GNSS-R) es una técnica de radar multi-estático que usa señales de radio-navegación como señales de oportunidad. Esta técnica proporciona "wide-swath" y un mejor sampleado espacio-temporal en comparación con las misiones espaciales actuales. La falta de datos desde el espacio proporcionando señales de múltiples constelaciones (GPS, GLONASS, Galileo, Beidou) en doble banda (L1 y L2) y en doble polarización (RHCP y LHCP) sobre océano, tierra y criosfera continua siendo un problema por solucionar. 3Cat-2 es un cubesat de 6 unidades con el objetivo de explorar elementos fundamentales para mejorar el conocimiento sobre el scattering bi-estático sobre diferentes medios dispersores. Dado que la geolocalización de puntos de reflexión específicos está determinada solo por geometría, es necesario un requisito moderado de apuntamiento para corregir el diagrama de antena en aplicaciones de dispersometría. El lanzamiento del 3Cat-2 será en Q2 2016 en una órbitra heliosíncrona usando un cohete Long March II D. Esta tesis representa las contribuciones principales al desarrollo del satélite 3Cat2 para realizar observación de la tierra con GNSS-R incluyendo una nueva técnica: "the reconstructed-code GNSS-R". El diseño, desarrollo de la plataforma y un número de experimentos en tierra, desde avión y desde globo estratosférico para validar la técnica y optimizar el instrumento han sido realizados. En particular, las contribuciones de esta Ph.D. son: 1) un novedoso Global Navigation Satellite Systems Reflectometer que usa las señales P(Y) y C/A después de ser dispersadas sobre la superficie del mar para realizar medidas altimétricas muy precisas. (PYCARO). 2) La primera prueba de concepto de PYCARO se hizo en dos experimentos sobre un pantano y sobre el mar bajo diferentes condiciones de rugosidad. 3) La disperión de las señales GNSS sobre una superfice de agua ha sido estudiada para bajas altitudes para aplicaciones GNSS-R altimétricas de costa. La determinación precisa del nivel local del mar y el estado de las olas desde la costa puede proporcionar información útil de altimetría e información de olas. Para hacer un test de este concepto un experimento en el Canal d'Investigació i Experimentació Marítima (CIEM) fue realizado para dos estados sintéticos de rugosidad. 4) Dos experimentos en avión con esponsor de la ESA se realizaron para estudiar la preción y la exactitud relativa de cGNSS-R. 5) Los resultados empíricos del experimento GNSS-R en BEXUS 17 con esponsor de la ESA realizado en el norte de Suecia sobre bosques boreales mostró que la potencia reflejada de las señales es independiente de la altitud de la plataforma para un tiempo de integración coherente muy alto. 6) Una versión mejorada del PYCARO fue testeada en octubre del 2014 por segunda vez durante el BEXUS 19 que también fue patrocidado por la ESA. Este trabajo proporcionó las primeras medidas GNSS-R sobre bosques boreales en doble frecuencia usando varias constelaciones GNSS. 7) Las primeras medidas polarimétricas (RHCP y LHCP) de GNSS-R sobre bosques boreales también fueron conseguidas durante el experimento BEXUS 19.

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 land surface skin temperature diurnal cycle (LSTD) is very important for the understanding of surface climate and for evaluating climate models. This variable, however, cannot be obtained globally from polar-orbiting satellites because the satellites usually pass a given area twice per day and because their infrared channels cannot observe the surface when the sky is cloudy. In order to more optimally use the satellite data, this research is designed, for the first time, to solve the above two problems by advance use of remote sensing techniques and climate modeling. Specifically, this work is divided into two parts. Part one deals with obtaining the skin temperature diurnal cycle for cloud-free cases. We have developed a "cloud-free algorithm" to combine model results with satellite and surface-based observations, thus interpolating satellite twice-daily observations to the diurnal cycle. Part two studies the cloudy cases. The "cloudy-pixel treatment" presented here is a hybrid technique of "neighboring-pixel" and "surface air temperature" approaches. The whole algorithm has been tested against field experiments and climate model CCM3/BATS in global and single column mode simulations. It shows that this proposed algorithm can obtain skin temperature diurnal cycles with an accuracy of 1-2 K at the monthly pixel level.

On se propose dans un premier temps d'étudier des jeux de données topographiques sur la lune glacée de Jupiter Ganymède et d'estimer l'impact de la topographie sur les performances du futur radar sondeur. Les principaux résultats sont présentés dans [1]. Une seconde partie est dédiée à l'expression mathématique du problème direct du sondage radar planétaire (physique et instrumentation). On rappelle ainsi comment dériver à partir des formulations de Stratton-Chu les formulations volumiques classiques et surfaciques (i.e. Huygens-Fresnel). On s'attache ensuite à détailler un algorithme performant basé sur la formulation surfacique pour simuler des échos radar à partir d'une surface planétaire maillée. Cette approche est largement inspirée par le travail de J.-F. Nouvel [2]. Une troisième partie s'intéresse à l'inversion des paramètres géophysiques de surface à partir des mesures radar. On écrit ainsi le problème dans un cadre probabiliste (c.f. [3]) et on présente trois grandes familles d'algorithmes : (i) une approche avec une linéarisation du problème, (ii) une approche itérative basée sur une méthode de gradient et (iii) une approche statistique pour estimer les densités de probabilités a posteriori. Ces algorithmes sont appliqués à des jeux de données synthétiques pour illustrer leurs performances. [1] Y. Berquin, W. Kofman, A. Herique, G. Alberti, and P. Beck. A study on ganymede's surface topography: Perspectives for radar sounding. Planetary and Space Science, (0), 2012. [2] J.-F. Nouvel, A. Herique, W. Kofman, and A. Safaeinili. Radar signal simulation: Surface modeling with the Facet Method. Radio Science, 39:RS1013, February 2004. [3] A. Tarantola. Inverse problem theory and methods for model parameter estimation. SIAM, 2005
The manuscript details the work performed in the course of my PhD on planetary sounding radar. The main goal of the study is to help designing and assessing the sounding radar performances. This instrument will be embarked on the ac{ESA}'s large class mission ac{JUICE} to probe Jupiter's environment and Jupiter's icy moons Callisto, Ganymede and Europa. As an introduction to the problem, a study on Ganymede's surface ac{DEM} and its implications with regard to the radar performances was performed. The results of this work put forward issues due to a hostile environment with important surface clutter which eventually lead to a decrease in the radar signal bandwidth to 8--10 MHz. A first section is then dedicated to the formulation of the direct problem of sounding radar with a focus on surface formulations. This section eventually leads to a novel algorithm for radar surface echo computation from meshed surfaces which proves to be both efficient and accurate. A second section studies the possibility to use surface formulation to recover geophysical surface parameters from sounding radar data. For that purpose, three main approaches are discussed namely (i) a linear approach, (ii) a gradient-based approach and (iii) a statistical approach. These techniques rely on a probabilistic view of the inverse problem at hand and yield good result with different setups. Although we mainly focus on surface reflectivity, we also discuss surface topography inversion. Finally, a last section discusses the work presented in the manuscript and provides perspectives for future work

This thesis presents a methodological approach to developing the capability of the Infrared Atmospheric Sounding Interferometer (IASI) instrument to inform on the atmospheric concentrations of carbon monoxide (CO), focussing on three key studies: 1) an assessment of the radiometric accuracy of the instrument; 2) the development of the University of Leicester IASI Retrieval Scheme (ULIRS) to convert measured radiances into a CO product; and 3) an investigation into the reliability and possible use of the ULIRS product. An intercomparison between the radiances as measured by the IASI and Advanced Along Track Scanning Radiometer (AATSR) instruments is performed, and absolute differences at 11 µm of less than 0:1K are observed. Given the radiometric behaviour across the IASI instrument as a whole, it is also concluded that the IASI instrument is radiometrically accurate to < 0.3K in the 12 and 4.7 µm spectral regions. A retrieval scheme, the ULIRS, is developed with explicit digital elevation and emissivity information, and a correction for solar surface reflection with a high resolution solar spectrum. Typical random errors over the African region relating to the profiles are found to be ~10% at 5 and 12 km, and on the total columns to be ~12 %. The ULIRS dataset and the operational CO products from the Measurements Of Pollution In The Troposphere (MOPITT) are inter-compared. A methodology which uses the same a priori statistics, and which reduces the smoothing bias between the two sets of data shows that there is only a small bias between the ULIRS and MOPITT V4 products. A simplified top-down approach to estimating CO emissions from fires is also presented, highlighting the need for a better understanding of the correct detection of burnt area from space-based measurements.

Satellite observations provide information on land surface processes over a large spatial extent with a frequency dependent on the satellite revisit time. These observations are not subject to the spatial limitations of the traditional point measurements and are usually collected in a global scale. With a reasonable spatial resolution and temporal frequency, the Moderate Resolution Imaging Spectroradiometer (MODIS) is one of these satellite sensors which enables the study of land-atmospheric interactions and estimation of climate variables for over a decade from remotely sensed data. This research investigated the potential of remotely sensed land surface temperature (LST) data from MODIS for air temperature (Ta) and soil moisture (SM) estimation in New Zealand and how the satellite derived parameters relate to the numerical model simulations and the in-situ ground measurements. Additionally, passive microwave SM product from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) was applied in this research. As the first step, the MODIS LST product was validated using ground measurements at two test-sites as reference. Quality of the MODIS LST product was compared with the numerical simulations from the Weather Research and Forecasting (WRF) model. Results from the first validation site, which was located in the alpine areas of the South Island, showed that the MODIS LST has less agreement with the in-situ measurements than the WRF model simulations. It turned out that the MODIS LST is subject to sources of error, such as the effects of topography and variability in atmospheric effects over alpine areas and needs a careful pre-processing for cloud effects and outliers. On the other hand, results from the second validation site, which was located on the flat lands of the Canterbury Plains, showed significantly higher agreement with the ground truth data. Therefore, ground measurements at this site were used as the main reference data for the accuracy assessment of Ta and SM estimates. Using the MODIS LST product, Ta was estimated over a period of 10 years at several sites across New Zealand. The main question in this part of the thesis was whether to use LST series from a single MODIS pixel or the series of a spatially averaged value from multiple pixels for Ta estimation. It was found that the LST series from a single pixel can be used to model Ta with an accuracy of about ±1 ºC. The modelled Ta in this way showed r ≈ 0.80 correlation with the in-situ measurements. The Ta estimation accuracy improved to about ±0.5 ºC and the correlation to r ≈ 0.85 when LST series from spatially averaged values over a window of 9x9 to 25x25 pixels were applied. It was discussed that these improvements are due to noise reduction in the spatially averaged LST series. By comparison of LST diurnal trends from MODIS with Ta diurnal trends from hourly measurements in a weather station, it was shown that the MODIS LST has a better agreement with Ta measurements at certain times of the day with changes over day and night. After estimation of Ta, the MODIS LST was applied to derive the near-surface SM using two Apparent Thermal Inertia (ATI) functions. The objective was to find out if more daily LST observations can provide a better SM derivation. It was also aimed to identify the potential of a land-atmospheric coupled model for filling the gaps in derived SM, which were due to cloud cover. The in-situ SM measurements and rainfall data from six stations were used for validation of SM derived from the two ATI functions and simulated by the WRF model. It was shown that the ATI function based on four LST observations has a better ability to derive SM temporal profiles and is better able to detect rainfall effects. Finally, the MODIS LST was applied for spatial and temporal adjustment of the near-surface SM product from AMSR-E passive microwave observations over the South Island of New Zealand. It was shown that the adjustment technique improves AMSR-E seasonal trends and leads to a better matching with rainfall events. Additionally, a clear seasonal variability was observed in the adjusted AMSR-E SM in the spatial domain. Findings of this thesis showed that the satellite observed LST has the potential for the estimation of the land surface variables, such as the near-surface Ta and SM. This potential is greatly important on remote and alpine areas where regular measurements from weather stations are not often available. According to the results from the first validation site, however, the MODIS LST needs a careful pre-processing on those areas. The concluding chapter included a discussion of the limitations of remotely sensed data due to cloud cover, dense vegetation and rugged topography. It was concluded that the satellite observed LST has the potential for SM and Ta estimations in New Zealand. It was also found that a land-atmospheric model (such as the WRF coupled with the Noah and surface model) can be applied for filling the gaps due to cloud cover in remotely sensed variables.

[ES] Las playas son espacios costeros que desarrollan numerosas funciones ambientales. Éstas proporcionan importantes beneficios a la sociedad y a las comunidades costeras, entre las que destacan la función ecológica, el suministro de protección para los territorios costeros y el hecho de que constituyen un recurso básico de la industria turística. De forma ligada al cambio climático, así como a acciones humanas que alteran el dinamismo natural de la costa, las playas están experimentando procesos erosivos cada vez más dañinos que afectan a su integridad física y al mantenimiento de sus funciones. La gestión de las playas en muchas ocasiones no se encuentra adaptada a las particularidades de los diferentes segmentos costeros. La toma de decisiones no se sustenta en información suficiente sobre las características, el dinamismo y el estado actual de las playas, dando lugar a soluciones cortoplacistas o ineficaces. Las características geomorfológicas son esenciales en el desarrollo de sus funciones al condicionar sus dimensiones físicas y su comportamiento frente a la acción del mar. Por ello, su caracterización de forma detallada y actualizada es necesaria para llevar a cabo acciones eficientes, permitiendo virar hacia una gestión costera más ecosistémica y sostenible. Las técnicas de teledetección presentan una gran capacidad para la adquisición de datos de la superficie terrestre. En concreto, los satélites Sentinel-2 y Landsat (5, 7 y 8) permiten disponer de forma gratuita imágenes de resolución media con cobertura mundial y alta frecuencia de revisitado. Los algoritmos de extracción de la línea de costa desarrollados recientemente por el Grupo de Cartografia GeoAmbiental y Teledetección (CGAT - UPV) permiten definir sobre estas imágenes la posición de la línea de costa, constituyendo datos potencialmente útiles para describir la morfología de las playas y su dinamismo. Universalizar su aplicación requiere su testeo y validación en diferentes tipos de costa. Para ello, el proceso de extracción ha sido adaptado para su explotación en entornos mareales, y las líneas de costa resultantes han sido evaluadas ante diferentes condiciones oceanográficas ofreciendo una precisión cercana a los 5 m RECM (raíz del error cuadrático medio). Teniendo en cuenta las necesidades de información para la gestión existentes, a partir de estas líneas de costa se propone derivar indicadores que permitan caracterizar la geomorfología de las playas y monitorizar sus cambios. Para ello, las metodologías propuestas aseguran una gestión eficiente de grandes volúmenes de líneas de costa, siendo así capaces de caracterizar las playas cubriendo grandes territorios y periodos de tiempo. Así se derivan el ancho de playa y el tamaño de los granos de sedimento como indicadores objetivos y fácilmente comprensibles de la geomorfología de la playa. La modelización espacio-temporal del estado y los cambios de la línea de costa y de la anchura posibilita monitorizar la respuesta de las playas a temporales y a actuaciones antrópicas, permitiendo analizar los cambios ocurridos cada pocos días hasta cubrir décadas. Su cobertura espacial junto a la integración con otras bases de datos cartográficas permite caracterizar la influencia de la geomorfología de la playa en el desempeño de sus funciones, permitiendo un análisis holístico de la costa a escala regional. Las metodologías desarrolladas en esta tesis y los indicadores derivados desde la teledetección brindan apoyo para dotar de criterios y priorizar las acciones de los gestores. Se contribuye así a llenar el espacio existente entre la disponibilidad de técnicas para obtener información remota y su aplicación en los procesos de toma de decisiones sobre la costa.
[CAT] Les platges són espais costaners que desenvolupen nombroses funcions ambientals. Aquestes proporcionen importants beneficis a la societat i comunitats costaneres, entre les quals destaquen la funció ecològica, el subministrament de protecció per als territoris costaners i el fet que constitueixen un recurs bàsic de la indústria turística. De forma lligada al canvi climàtic, així com a accions humanes que alteren el dinamisme natural de la costa, les platges estan experimentant processos erosius cada vegada més nocius que afecten la seua integritat física i al manteniment de les seues funcions. La gestió de les platges en moltes ocasions no es troba adaptada a les particularitats dels diferents segments costaners. La presa de decisions no es sustenta en informació suficient sobre les característiques, el dinamisme i l'estat actual de les platges, donant lloc a solucions curtterministes o ineficaces. Les característiques geomorfològiques són essencials en el desenvolupament de les seues funcions en condicionar les seues dimensions físiques i el seu comportament enfront de l'acció de la mar. Per això, la seua caracterització de manera detallada i actualitzada és necessària per a dur a terme accions eficients, permetent virar cap a una gestió costanera més ecosistèmica i sostenible. Les tècniques de teledetecció presenten una gran capacitat per a l'adquisició de dades de la superfície terrestre. En concret, els satèl·lits Sentinel-2 i Landsat (5, 7 i 8) permeten disposar de manera gratuïta d'imatges de resolució mitjana amb cobertura mundial i alta freqüència de captura d'informació a un mateix punt. Els algorismes d'extracció de la línia de costa desenvolupats recentment pel Grup de Cartografia Geo-Ambiental i Teledetecció (CGAT - UPV) permeten definir sobre aquestes imatges la posició de la línia de costa, constituint dades potencialment útils per descriure la morfologia de les platges i el seu dinamisme. Universalitzar la seua aplicació requereix el seu testatge i validació en diferents tipus de costa. Per a això, el procés d'extracció ha sigut adaptat per a la seua explotació en entorns mareals, i les línies de costa resultants han sigut avaluades davant diferents condicions oceanogràfiques oferint una precisió pròxima als 5 m RMSE (arrel de l'error quadràtic mitjà). Tenint en compte les necessitats d'informació per a la gestió existents, a partir d'aquestes línies de costa es proposa derivar indicadors que permeten caracteritzar la geomorfologia de les platges i monitorar els seus canvis. Per a això, les metodologies proposades asseguren una gestió eficient de grans volums de línies de costa, sent així capaces de caracteritzar les platges cobrint grans territoris i períodes de temps. Així es deriven l'ample de platja i la grandària dels grans de sediment com a indicadors objectius i fàcilment comprensibles de la geomorfologia de la platja. La modelització espai-temporal de l'estat i els canvis de la línia de costa i de l'amplària possibilita monitorar la resposta de les platges a temporals i a actuacions antròpiques, permetent analitzar els canvis ocorreguts cada pocs dies fins a cobrir dècades. La seua cobertura espacial al costat de la integració amb altres bases de dades cartogràfiques permet caracteritzar la influència de la geomorfologia de la platja en l'acompliment de les seues funcions, permetent una anàlisi holística de la costa a escala regional. Les metodologies desenvolupades en aquesta tesi i els indicadors derivats des de la teledetecció brinden suport per a dotar de criteris i prioritzar les accions dels gestors. Es contribueix així a omplir l'espai existent entre la disponibilitat de tècniques per a obtenir informació remota i la seua aplicació en els processos de presa de decisions sobre la costa.
[EN] Beaches are coastal spaces that perform numerous environmental functions. They provide important benefits to society and coastal communities, including the ecological function, the provision of protection for coastal territories, and constitute a basic resource for the tourism industry. Due to climate change and human actions that alter the natural dynamism of the coast, beaches are experiencing increasingly harmful erosive processes that affect their physical integrity and the maintenance of their ecological functions. Beach management is often not adapted to the particularities of the different coastal segments. Decision-making is not based on sufficient information about characteristics, dynamism, and current state of beaches, resulting in short or ineffective solutions. Geomorphological characteristics are essential in the development of beach functions as they condition their physical dimensions and their behavior in response to the action of the sea. Therefore, their detailed and updated characterization is necessary to carry out efficient actions, allowing a more ecosystemic and sustainable coastal management. Remote sensing techniques have a great capacity for acquiring data from the land surface. In particular, Sentinel-2 and Landsat (5, 7, and 8) satellites freely provide medium resolution images with global coverage and high-revisit frequency. The algorithms for extracting the water/land interface recently developed by the Geo-Environmental Cartography and Remote Sensing Group (CGAT - UPV) allow defining the position of the shoreline on these images, constituting potentially useful data to describe beach morphology and dynamics. Universalizing their application requires testing and validation at different coastal types. For this purpose, the extraction process has been adapted for exploitation in tidal environments, and the resulting shorelines have been assessed under different oceanographic conditions offering an accuracy close to 5 m RMSE (Root-Mean-Square Error). From these shorelines, and taking into account the existing information needs for management, it is proposed to derive indicators to characterize the geomorphology of the beaches and to monitor their changes. To this end, the proposed methodologies ensure the efficient management of large volumes of shorelines, being able to characterize the beaches along broad coastal segments and periods. Thus, beach width and sediment grain size are derived as objective and easily understandable indicators of the beach geomorphology. Spatial-temporal modeling of the state and changes of shoreline position and beach width makes it possible to monitor the response to storms and anthropogenic actions, allowing to analyze changes that occur every few days or over decades. The large spatial coverage together with the integration with other cartographic databases allows characterizing the influence of beach geomorphology in the performance of its functions, offering a holistic view of the coast from a regional scale. The methodologies developed in this thesis and the indicators derived from remote sensing provide support and criteria for prioritizing the actions of managers. This contributes to fill the gap between the availability of techniques to obtain remote information and its application in the coastal decision-making process.
This research integrates findings and results obtained within the framework of the contract FPU15/04501 granted to the author by the Spanish Ministry of Education, Culture, and Sports, which has allowed this doctoral thesis to become a reality. The research has been supported by the funds of the project RESETOCOAST, by the Ministry of Economy, Industry, and Competitiveness (chapters 2 to 5), and the project MONOBESAT PID2019-111435RB-I00 by the Ministry of Science, Innovation, and Universities (chapter 6). About my stay in Portugal, it was possible with the funds of the Erasmus+ program. The contribution of Ó. Ferreira was funded by EW-COAST (PTDC/CTA-OHR/28657/2017) and by FCT and Univ. Algarve through the grant UID/MAR/00350/2013, while S. Costas’ was funded by IF/01047/2014. The following institutions have provided free access to essential data for the development of the publications that constitute this thesis: ESA and USGS for the satellite imagery; Puertos del Estado, and the Portuguese Hydrographic Institute in collaboration with CIMA for supplying oceanographic data; Ministry MITECO and DGSCM for data regarding beach sedimentology and nourishments.
Cabezas Rabadán, C. (2021). Beach Morphology and its Dynamism from Remote Sensing for Coastal Management Support [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165076
TESIS

This study compared two remote sensing water indices: the Normalized Difference Water Index (NDWI) and the Modified NDWI (MNDWI). Both indices were calculated using publically-available data from the Landsat 8 Operational Land Imager (OLI). The research goal was to determine whether the indices are effective in locating open water and measuring surface soil moisture. To demonstrate the application of water indices, analysis was conducted for freshwater wetlands in the Tualatin River Basin in northwestern Oregon to estimate hydrologic connectivity and hydrological permanence between these wetlands and nearby water bodies. Remote sensing techniques have been used to study wetlands in recent decades; however, scientific studies have rarely addressed hydrologic connectivity and hydrologic permanence, in spite of the documented importance of these properties. Research steps were designed to be straightforward for easy repeatability: 1) locate sample sites, 2) predict wetness with water indices, 3) estimate wetness with soil samples from the field, 4) validate the index predictions against the soil samples from the field, and 5) in the demonstration step, estimate hydrologic connectivity and hydrological permanence. Results indicate that both indices predicted the presence of large, open water features with clarity; that dry conditions were predicted by MNDWI with more subtle differentiation; and that NDWI results seem more sensitive to sites with vegetation. Use of this low-cost method to discover patterns of surface moisture in the landscape could directly improve the ability to manage wetland environments.

La conservation du couvert forestier tropical est essentielle pour assurer la fourniture durable de services écosystémiques. Dans les paysages anthropisés, la conservation des forêts doit également être conciliée avec la productivité agricole. Toutefois, l'accroissement de la démographie, la demande de produits agricoles et les changements dans l'utilisation des terres affectent la durabilité des forêts. Une première étape pour adapter la gestion efficace des forêts par les décideurs locaux consiste à identifier les forêts les plus vulnérables et à caractériser ce qui la génère. L'objectif de cette thèse est de développer une approche multidimensionnelle utilisant la télédétection pour évaluer la dégradation des forêts et les relations avec la dynamique de l'utilisation des terres afin d’estimer la vulnérabilité écologique des forêts. La thèse a été appliquée à Paragominas (Brésil) et Di Linh (Vietnam), où la déforestation à grande échelle due à l'agriculture commerciale a façonné le paysage en mosaïques d'utilisation des terres. A Paragominas, la dégradation est liée à l'accumulation de l’exploitation sélective du bois et au feu impliquant des changements dans la structure forestière. Nous avons estimé le potentiel de la télédétection multisource pour cartographier la biomasse forestière aérienne (AGB) à partir de données de stock de carbone. Nous avons amélioré la précision de la cartographie de l'AGB par rapport aux données pantropicales et révélé que 87 % des forêts étaient dégradées. À une plus petite échelle, nous avons étudié les conséquences de 33 ans de dégradation sur les structures forestières à l'aide de drone. Nous avons constaté que les textures de la canopée capturaient le grain, l'hétérogénéité et les gradients d'ouverture de la canopée, corrélés à la variabilité de la structure forestière et pouvaient être utilisés comme indicateurs pour caractériser les forêts dégradées. Nous avons également évalué le potentiel des images satellites à très haute résolution pour cartographier les structures des forêts dégradées à l'échelle de la municipalité. En nous basant sur des facteurs environnementaux, géographiques et de structure du paysage dérivés de la classification de l'utilisation des terres, nous avons démontré que 80 % de la dégradation des forêts était principalement due à l'accessibilité, la géomorphologie, la fréquence des incendies et à la fragmentation. Les facteurs de dégradation sont interconnectés et agissent en séquence au sein de différentes cascades d'effets. L'évolution de la structure du paysage a permis de reconstituer des trajectoires informant sur la dynamique des frontières agricoles. La combinaison de l'état actuel des forêts, de la dynamique du paysage et de la distribution des facteurs de dégradation permettra d’évaluation la vulnérabilité. A Di Linh, la dégradation concerne principalement les lisières forestières et est due à l'empiètement de l'agriculture (café). L'inventaire sur le terrain des différents types de forêts et d'autres éléments, combiné aux images Sentinel-2, a permis de cartographier avec une grande précision la couverture terrestre actuelle. Nous avons cartographié l'évolution de la couverture terrestre sur 45 ans à l'aide de séries chronologiques Landsat. Nous avons construit des trajectoires de dynamique paysagère afin de caractériser l'expansion de la frontière agricole et mis en évidence l'empiétement agricole sur les zones forestières. Nous avons également identifié des trajectoires de dégradation et de fragmentation qui affectent le couvert forestier à différentes intensités. Ensemble, ces indicateurs ont mis en évidence des points chauds de vulnérabilité. Grâce aux approches et aux indicateurs élaborés à multiples échelles, nous avons fourni un diagnostic holistique des forêts dans les paysages anthropisés, englobant l'état des forêts et des dynamiques à plus larges échelles. Cette thèse vise à orienter une gestion adaptée des forêts dégradées à l'échelle du paysage
The conservation of tropical forest cover is a key to ensuring sustainable provision of multiple ecosystem services. In human-modified landscapes, forest conservation must also be reconciled with agricultural productivity. However, increasing demography, demand for agricultural products and changes in land uses are affecting forest sustainability through degradation processes. A first step to tailor effective forest management by local decision makers is to identify most vulnerable forests and to characterize what is driving this vulnerability. The objective of this thesis is to develop a multidimensional approach using remote sensing to assess forest degradation and the relations with the broader dynamics of land use/cover towards the evaluation of forest ecological vulnerability. The thesis was applied in old-deforestation fronts of Paragominas (Brazil) and Di Linh (Vietnam) where large-scale deforestation driven by commercial agriculture shaped the landscape into land use mosaics with increasing degradation pressures. In Paragominas, degradation is linked with long-term accumulation of selective logging and fire implying changes in forest structure. We estimated the potential of multisource remote sensing to map forest aboveground biomass (AGB) from large-scale field assessment of carbon stock. We improved the accuracy of AGB mapping compared to pantropical datasets and revealed that 87% of forest was degraded. At a lower scale, we investigated the consequences of 33 years of degradation history from Landsat on forest structures using Unmanned Aerial Vehicle. We found that canopy textures captured canopy grain, heterogeneity and openness gradients, correlated with forest structure variability and could be used as proxies to characterize degraded forests. We also assessed the potential of very high resolution satellite images and derived canopy textures to upscale texture-structure relations at the municipality scale. Based on environmental, geographical factors and landscape structure metrics derived from land use/cover classification, we demonstrated that 80% of forest degradation was mainly driven by accessibility, geomorphology, fire occurrence and fragmentation. The drivers of degradation acted together and in sequence and clustering analysis disentangled different cascades of effects. Changes in landscape structure allowed reconstructing trajectories informing on agricultural frontier dynamics. The combination of current forest state, landscape dynamics and distribution of degradation drivers would be at the basis of ecological vulnerability assessment. In Di Linh, degradation mostly concerns forest edges and is driven by encroachment of coffee-based agriculture. Field inventory of the different forest types and other landscape elements combined with Sentinel-2 images allowed to map with high precision the current land cover. We then mapped land cover changes over 45 years using Landsat time series. We constructed trajectories of landscape structure dynamics from which we characterized the expansion of the agricultural frontier and highlighted heterogeneous agricultural encroachment on forested areas. We also identified degradation and fragmentation trajectories that affect forest cover at different rates and intensity. Combined, these indicators pinpointed hotspots of forest ecological vulnerability. Most vulnerable forest areas were experiencing rapid and recent forest cover loss associated with landscape fragmentation, land use competition due to coffee production and degradation. Through the developed remote sensing approaches and indicators at forest and landscape scales, we provided a holistic diagnosis of forests in human-modified landscapes encompassing forest state and broader dynamics and drivers. This thesis aims to pave the way for tailored and prioritized management of degraded forests at the landscape scale

碩士
國立中山大學
海洋資源學系
85
Satellite data from Landsat Thematic Mapper (TM) were used to derive sea surface temperature (SST) in coastal waters of Hsinta that receive cooling effluent from a power plant. Ground truth temperatures measured simultaneously from a ship as Landsat passed were used to compare with the satellite results. Two methods were applied to improve the atmospheric correction process for monitoring SST. Local radiosonde measurements, used in Lowtran7 adjustments for atmospheric effects, produced corrected ocean surface radiances and atmospheric transmittances. The mean deviation between the ship-measured and satellite estimated SST is 0.94℃ if the atmospheric correction process is applied compared with over 7℃ if that process is negleted. Secondly, a scheme combining NOAA Advanced Very High Resolution Radiometer (AVHRR) and Landsat-TM was used to derive SST. The advantage of this scheme is that no atmospheric correction process is required. The mean deviation between the ground truth and satellite-derived SST from this scheme is 1.01℃ for thermal plume of Hsinta power plant and 0.62℃ for Tseng-Wen estuarine waters, respectively. With Landsat''s good resolution and proper use of the atmospheric correction process as suggested in this study, it can be used to locate power plant discharge and intake positions, to investigate the distribution of thermal plumes, and to estimate the surface temperatures of coastal waters, large rivers, lakes and estuarine waters. The combination of AVHRR and TM to estimate SST around the outfall of power plant proves to be a promising and convenient way.

The analysis and identification of texture is a key area in image processing and computer vision. One of the most prominent texture analysis algorithms is the Gabor Filter. These filters are used by convolving an image with a family of self similar filters or wavelets through the selection of a suitable number of scales and orientations, which are responsible for aiding in the identification of textures of differing coarseness and directions respectively. While extensively used in a variety of applications, including, biometrics such as iris and facial recognition, their effectiveness depend largely on the manual selection of different parameters values, i.e. the centre frequency, the number of scales and orientations, and the standard deviations. Previous studies have been conducted on how to determine optimal values. However the results are sometimes inconsistent and even contradictory. Furthermore, the selection of the mask size and tile size used in the convolution process has received little attention, presumably since they are image set dependent. This research attempts to verify specific claims made in previous studies about the influence of the number of scales and orientations, but also to investigate the variation of the filter mask size and tile size for water body extraction from satellite imagery. Optical satellite imagery may contain texture samples that are conceptually the same (belong to the same class), but are structurally different or differ due to changes in illumination, i.e. a texture may appear completely different when the intensity or position of a light source changes. A systematic testing of the effects of varying the parameter values on optical satellite imagery is conducted. Experiments are designed to verify claims made about the influence of varying the scales and orientations within predetermined ranges, but also to show the considerable changes in classification accuracy when varying the filter mask and tile size. Heuristic techniques such as Genetic Algorithms (GA) can be used to find optimum solutions in application domains where an enumeration approach is not feasible. Hence, the effectiveness of a GA to automate the process of determining optimum Gabor filter parameter values for a given image dataset is also investigated. The results of the research can be used to facilitate the selection of Gabor filter parameters for applications that involve multi-textured image segmentation or classification, and specifically to guide the selection of appropriate filter mask and tile sizes for automated analysis of satellite imagery.
Thesis (M.Sc.)-University of KwaZulu-Natal, Durban, 2012.