Geometric calibration and radiometric correction of the maia multispectral camera

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper

GEOMETRIC CALIBRATION AND RADIOMETRIC CORRECTION OF THE MAIA MULTISPECTRAL CAMERA

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper

Multispectral Imaging for the Analysis of Materials and Pathologies in Civil Engineering, Constructions and Natural Spaces

Tesis por compendio de publicaciones[EN] Multispectral imaging is a non-destructive technique that combines imaging and spectroscopy to analyse the spectral behaviour of materials and land covers through the use of geospatial sensors. These sensors collect both spatial and spectral information for a given scenario and a spectral range, so that, their graphical representation elements (pixels or points) store the spectral properties of the radiation reflected by the material sample or land cover. The term multispectral imaging is commonly associated with satellite imaging, but the application range extends to other scales as close-range photogrammetry through the use of sensors on board of airborne systems (gliders, trikes, drones, etc.) or through their use at ground level. Its usefulness has been proved in a variety of disciplines from topography, geology, atmospheric science to forestry or agriculture. The present thesis is framed within close-range remote sensing applied to the civil engineering, cultural heritage and natural resources fields via multispectral image analysis. Specifically, the main goal of this research work is to study and analyse the radiometric behaviour of different natural and artificial covers by combining several sensors recording data in the visible and infrared ranges of the spectrum. The research lines have not been limited to the 2D data analysis, but in some cases 3D intensity data have been integrated with 2D data from active (terrestrial laser scanners) and passive (multispectral digital cameras) sensors in order to analyse different materials and possible associated pathologies, getting more comprehensive products due to the metric that 3D brings to 2D data. Works began with the radiometric calibration of the active and passive sensors used by the vicarious calibration method. The calibrations were carried out through MULRACS, a multispectral radiometric calibration software developed for this purpose (see Appendix B). After the calibration process, active and passive sensors were used together for the discretization of sedimentary rocks and detecting pathologies, as moisture, in façades and in civil structures. Finally, the Doctoral Thesis concludes with a theoretical book chapter in which all the know-how and expertise arising during this research stage have been compiled.[ES]Las imágenes multiespectrales se constituyen como técnica no destructiva que combina imagen y espectroscopía para analizar el comportamiento espectral de distintos materiales y superficies terrestres a través del uso de sensores geoespaciales. Estos sensores adquieren tanto información espacial como espectral para un escenario y un rango espectral dados de tal forma sus unidades de representación gráfica (ya sean píxeles o puntos) registran las propiedades de la radiación reflejada para cada material o cobertura a estudiar y longitud de onda. Las imágenes multiespectrales no solo se limitan a las observaciones satelitales a las que tradicionalmente se vinculan, sino que tienen un campo de aplicación más amplio gracias a los estudios de rango cercano realizados a través del uso de sensores tanto embarcados en sistemas aéreos (planeadores, paramotores, drones, etc.) como a nivel terreno. Su utilidad ha sido demostrada en multitud de disciplinas; desde la topografía, geología, aerología, hasta la ingeniería forestal o la agricultura entre otros. La presente tesis se enmarca dentro de la teledetección de rango cercano aplicada a la ingeniería civil, el patrimonio cultural y los recursos naturales a través del análisis multiespectral de imágenes. Concretamente, el principal objetivo de este trabajo de investigación consiste en el estudio y análisis del comportamiento radiométrico de distintas coberturas naturales y artificiales mediante el uso combinado de distintos sensores que registran información espectral en los rangos visible e infrarrojo del espectro electromagnético. Las líneas de investigación no se han limitado al análisis de datos bidimensionales (imágenes) sino que en algunos casos se han integrado datos de intensidad registrados en 3D a través de sensores activos (láser escáner terrestres) con datos 2D capturados con sensores pasivos (cámaras digitales convencionales y multiespectrales) con el objetivo de analizar diferentes materiales y posibles patologías asociadas a los mismos ofreciendo resultados más completos gracias a la métrica que los datos 3D aportan a los datos 2D. Los trabajos comenzaron con la calibración radiométrica de los sensores por el método de calibración vicario. Las calibraciones fueron resueltas gracias al uso del software MULRACS, un software para la calibración radiométrica multiespectral desarrollado durante este periodo para tal fin (ver Apéndice B). Tras el proceso de calibración, se combinó el uso de sensores activos y pasivos para la diferenciación de distintos tipos de rocas sedimentarias y la detección de patologías, como humedades, en fachadas de edificios históricos y en estructuras de ingeniería civil. Finalmente, la Tesis Doctoral concluye con un capítulo teórico de libro en el cual se recopilan todos los conocimientos y experiencias adquiridos durante este periodo de investigación

The potential of drones and sensors to enhance detection of archaeological cropmarks: a comparative study between multi-spectral and thermal imagery

Abstract This paper presents experimentation carried out at the Roman Republican city of La Caridad (Teruel, Spain), where different tools have been applied to obtain multispectral and thermal aerial images to enhance detection of archaeological cropmarks. Two different drone systems were used: a Mikrokopter designed by Tecnitop SA (Zaragoza, Spain) and an eBee produced by SenseFly Company (Cheseaux-sur-Lausanne, Switzerland). Thus, in this study, we have combined in-house manufacturing with commercial products. Six drone sensors were tested and compared in terms of their ability to identify buried remains in archaeological settlements by means of visual recognition. The sensors have different spectral ranges and spatial resolutions. This paper compares the images captured with different spectral range sensors to test the potential of this technology for archaeological benefits. The method used for the comparison of the tools has been based on direct visual inspection, as in traditional aerial archaeology. Through interpretation of the resulting data, our aim has been to determine which drones and sensors obtained the best results in the visualization of archaeological cropmarks. The experiment in La Caridad therefore demonstrates the benefit of using drones with different sensors to monitor archaeological cropmarks for a more cost-effective assessment, best spatial resolution and digital recording of buried archaeological remains

SENSORIAMENTO REMOTO POR MEIO DE UMA AERONAVE REMOTAMENTE PILOTADA PARA ESTUDO DO MANGUEZAL DA BAÍA DE VITÓRIA (ES)

O ecossistema manguezal fornece vários serviços ecológicos e econômicos, mas estão entre os ecossistemas mais ameaçados e vulneráveis do mundo. Eles se tornaram foco da atenção no contexto das atuais mudanças climáticas e discussões dos serviços fornecidos por esse ecossistema, como o sequestro de carbono. Neste contexto, o sensoriamento remoto é uma importante ferramenta para detectar, identificar, mapear e monitorar o ecossistema manguezal. É possível obter informações como a densidade e altura das árvores, a dominância de espécies, avaliar processos erosivos, estudar a dinâmica populacional da vegetação, cálculo de biomassa, entre outros estudos. Tais estudos podem ser baseados em diferentes sensores, como fotografia aérea, imagens ópticas de alta e média resolução, dados hiperespectrais e dados de microondas ativos (SAR). A aquisição de dados por meio de sensores orbitais possui algumas lacunas como tempo de revisita e resolução espacial. Já os sensores ópticos multiespectrais de alta resolução espacial embarcados em uma Aeronave Remotamente Pilotada (RPA) é uma tecnologia promissora para o mapeamento detalhado de ecossistemas costeiros embora o processo de calibração radiométrica ainda seja desafiador. Nesta pesquisa utilizou-se ortomosaicos obtidos por uma RPA para análise multiespectral do manguezal da Baía de Vitória e realizou-se análise hiperespectral foliar de três espécies de mangue; R. mangle, L. racemosa e A. schaueriana por meio de espectrorradiometria em laboratório

Calibration and validation of satellite data (images) over inland water bodies and the effect caused by the adjacency towards them

Remote sensing of inland water quality is a particularly challenging satellite Earth observation (EO) application. This arises because inland water bodies are small and optically complex targets that are generally dark compared to surrounding land. Inland water bodies are source supplies of water for both living and non-living organisms, that include human beings hence they need an observation. The spatial distribution of water changes over time and that leads to issues in different sectors like agricultural sector, environmental services and ecological issues. Signal reaching the satellite is usually dominated by light scattered in the atmosphere. Aerosols are strongly variable atmospheric constituents and play a major role in generating this unwanted signal which must be quantified and removed before any conclusions about water state and condition. In order to see how the aerosols affected the water state the light scattered in the atmosphere will be observed through electromagnetic spectrum bands in the atmosphere. This study will analyse the visible and near infrared wavebands of the electromagnetic spectrum as well as where it will be easy to distinguish the atmospheric noise types. A field campaign has been executed at Roodeplaat dam near Pretoria relating to Calibration and Validation (CalVal) of the recently launched Sentinel 2 and Sentinel 3 satellites. In situ measurements were taken at Roodeplaat dam simultaneously with the satellite overpass. Atmospheric Radiative Transfer Modelling (RTM) is required to analyse the satellite surface measurement data that is in the form of radiant quantities. Aerosol models for radiative transfer have been evaluated and refined to improve retrieval accuracy of water-leaving radiance at Roodeplaat dam. A retrieval algorithm for water-leaving radiance (Lw) and remote-sensing reflectance has been developed to analyse the sensitivity of the retrieval to aerosol optical properties, sensitivities, as well as proposals for enhanced retrieval methods, are presented

Monitorización y optimización de tierras con drones y fotogrametría aérea para aplicaciones de precisión en agricultura

[ES] El proyecto consiste en aplicar una tecnología específica para la rama de agricultura de precisión. La tecnología como todos sabemos, sufre una enorme evolución y tenemos que ser capaces de demostrar que somos los mejores en usarla. En concreto, en mi profesión he decido de seguir la rama de agricultura de precisión y esto porque es un nuevo aspecto de mi carrera. El objetivo de este proyecto, es proporcionar unos resultados óptimos para la mejora de producción para los agricultores. Con manera de que ellos reducirán los fertilizantes y los usos químicos en sus productos y tendrán muchos beneficios económicos. El trabajo se desarrolló para la zona de Algemesí en la Comunidad Valenciana en 17 de Octubre en 2016. El vuelo se realizó con un Multicóptero, modelo DJI F-450 UAV (UnmannedAerialVehicle) o VANT (Vehículo Aéreo No Tripulado), con una cámara Multiespectral y RGB llamada MicraSense para poder sacar el índice de vegetación NDVI (Normalized Difference Vegetation Index). Los resultados que queremos presentar son unos modelos de MDS (Modelo Digital de Superficie), MDT (Modelo Digital de Terreno) y un Ortomosáico. Sobre ello, he tomado unos puntos de control con un GPS de Leica para poder georreferenciar el Ortomosáico. Realice con los puntos de apoyo una imagen junto con el Google Maps del área para poder mostrar que los puntos tomados en el área se diferencian. El proceso de los datos se realizó en el Departamento de Topografía y en mi casa utilizando dos diferentes ordenadores. El Software que utilice para procesar los datos fue el Pix4D Mapper Pro. Estos hechos sugieren que los instrumentos utilizados en este estudio representan una solución rápida, fiable y eficiente para la evaluación de los cultivos para aplicaciones agrícolas.[EN] The project consists of applying a specific technology for the precision agriculture branch. Technology as we all know undergoes enormous evolution and we have to be able to demonstrate that we are the best in using it. Specifically, in my profession I have decided to follow the branch of precision agriculture and this because it is a new aspect of my career. The objective of this project is to provide optimum results for improved production for agriculturists. So that they will reduce the fertilizers and the chemical uses in their products and will have many economic benefits. The work was developed for the area of Algemesí in the Valencian Community on 17 of October of 2016. The flight was realized with a Multicopter, model DJI F-450 UAV (Unmanned Aerial Vehicle) or VANT (VehículoAéreo No Tripulado), with a Multispectral and RGB camera called MicraSense to be able to extract the index of vegetation NDVI (Normalized Difference Vegetation Index). The results that we want to present are models of DSM (Digital Surface Model), DTM (Digital Terrain Model) and an Orthomosaic. On this, I have taken some control points with a Leica GPS to be able togeoreferentiate the Orthomosaic.I made with the points of control an image along with the Google Maps of the area, to be able to show that the points taken in the area they differ. The data processing was done in the Department of Surveying and in my house using two different computers. The software used to process the data was the Pix4D Mapper Pro. These facts suggest that the instruments used in this study represent a fast, reliable and efficient solution for the evaluation of crops for agricultural applications.Mitsikostas, E. (2017). Monitorización y optimización de tierras con drones y fotogrametría aérea para aplicaciones de precisión en agricultura. Universitat Politècnica de València. http://hdl.handle.net/10251/86353TFG

Direct reflectance transformation methodology for drone-based hyperspectral imaging

Multi- and hyperspectral cameras on drones can be valuable tools in environmental monitoring. A significant shortcoming complicating their usage in quantitative remote sensing applications is insufficient robust radiometric calibration methods. In a direct reflectance transformation method, the drone is equipped with a camera and an irradiance sensor, allowing transformation of image pixel values to reflectance factors without ground reference data. This method requires the sensors to be calibrated with higher accuracy than what is usually required by the empirical line method (ELM), but consequently it offers benefits in robustness, ease of operation, and ability to be used on Beyond-Visual Line of Sight flights. The objective of this study was to develop and assess a drone-based workflow for direct reflectance transformation and implement it on our hyperspectral remote sensing system. A novel atmospheric correction method is also introduced, using two reference panels, but, unlike in the ELM, the correction is not directly affected by changes in the illumination. The sensor system consists of a hyperspectral camera (Rikola HSI, by Senop) and an onboard irradiance spectrometer (FGI AIRS), which were both given thorough radiometric calibrations. In laboratory tests and in a flight experiment, the FGI AIRS tilt-corrected irradiances had accuracy better than 1.9% at solar zenith angles up to 70◦. The system’s lowaltitude reflectance factor accuracy was assessed in a flight experiment using reflectance reference panels, where the normalized root mean square errors (NRMSE) were less than ±2% for the light panels (25% and 50%) and less than ±4% for the dark panels (5% and 10%). In the high-altitude images, taken at 100–150 m altitude, the NRMSEs without atmospheric correction were within 1.4%–8.7% for VIS bands and 2.0%–18.5% for NIR bands. Significant atmospheric effects appeared already at 50 m flight altitude. The proposed atmospheric correction was found to be practical and it decreased the high-altitude NRMSEs to 1.3%–2.6% for VIS bands and to 2.3%– 5.3% for NIR bands. Overall, the workflow was found to be efficient and to provide similar accuracies as the ELM, but providing operational advantages in such challenging scenarios as in forest monitoring, large-scale autonomous mapping tasks, and real-time applications. Tests in varying illumination conditions showed that the reflectance factors of the gravel and vegetation targets varied up to 8% between sunny and cloudy conditions due to reflectance anisotropy effects, while the direct reflectance workflow had better accuracy. This suggests that the varying illumination conditions have to be further accounted for in drone-based in quantitative remote sensing applications

Vicarious Radiometric Calibration of a Multispectral Camera on Board an Unmanned Aerial System

Combinations of unmanned aerial platforms and multispectral sensors are considered low-cost tools for detailed spatial and temporal studies addressing spectral signatures, opening a broad range of applications in remote sensing. Thus, a key step in this process is knowledge of multi-spectral sensor calibration parameters in order to identify the physical variables collected by the sensor. This paper discusses the radiometric calibration process by means of a vicarious method applied to a high-spatial resolution unmanned flight using low-cost artificial and natural covers as control and check surfaces, respectively