Dissertations / Theses on the topic 'Digital aerial photography'

I developed a new methodology to produce an orthorectified mosaic and a vegetation database of Petersburg National Battlefield using mostly digital methods. Both the mosaic and the database meet National Map Accuracy Standards and proved considerably faster than traditional aerial photograph interpretation methods. I classified vegetation polygons to the formation level using the Nature Conservancy?s National Vegetation Classification System. Urban areas were classified using Mitchell?s Classification Scheme for Urban Forest Mapping with Small-Scale Aerial Photographs. This method reduced the production time by 2/3, compared to traditional methods. It also reduced the chance of user error because re-tracing of the linework is not required.

My method started with scanning 75 aerial color IR photos, provided by Petersburg National Battlefield, at 600 dpi. Erdas Imagine was used to rectify the images using United States Geological Service (USGS) Digital Elevation Models (DEM) and black and white USGS Digital Orthophoto Quarter Quadrangles (DOQQ) as reference. The images were then mosaiced to create a seamless color infrared orthorectified basemap of the park. The vegetation polygons were drawn onscreen using ArcMap from Environmental Systems Research Institute, Inc. (ESRI) with the color, orthorectified mosaic as a background image. Stereo pairs of the aerial photos were referenced as needed for clarification of the vegetation. I used a minimum mapping unit (mmu) of 0.2 hectares, which exceeds guidelines defined by the United States Geological Survey ? National Park Service Vegetation Mapping Program. This methodology is easily learned quickly and has already been applied to several other studies.

The production of an orthorectified mosaic, created during the process, from the aerial photographs greatly increases the value of the photographs at little additional cost to the user. The orthorectified basemap can then be used as a backdrop for existing data layers or it can be used to create new GIS data layers. I used a minimum mapping unit (mmu) of 0.2 hectare, which exceeds guidelines defined by the United States Geological Survey-National Park Service Vegetation Mapping Program

Traditionally, vegetation polygons are delineated on acetate for each photograph. The linework on the acetates is then transferred to a basemap using a zoom transfer scope or other transfer instrument. The linework is traced again to digitize it for use in a GIS program. This process is time consuming, and the linework is drawn three times. The redundant tracing increases the chance of user error. My new methodology requires that polygons be delineated only once. I wanted to avoid using the zoom transfer scope and to avoid the redundant linework.

A total of 228 polygons were delineated over 20 separate vegetation and land cover classes with an overall thematic accuracy of 87.42% and a Kappa of .8545. Positional accuracy was very good with a RMSE of 1.62 meters in the x direction and 2.81 meters in the y direction. The Kappa and RMSE values compare favorably with accuracies obtained using traditional vegetation mapping methods.

The coastal zone is a highly dynamic entity both spatially and temporally and when shoreline changes (and in particular retreat) occur on a hmnan time-scale, measurement of the rate of change becomes a pressing issue. This dynamism presents an excellent scenario for monitoring change using remote sensing techniques, and in the case of coastal sand dunes, where the requirement is to measure small scale changes such as erosion or accretion in the region of 10 or 20 m, aerial photography is the preferred source of remotely sensed data. The rapid developments in digital camera technology and real time satellite differential Global Positioning Systems have yielded new opportunities for mapping and monitoring environmental change when used with image processing and mapping software and state-of-the-art digital photogrammetric workstations. Despite the progress in digital technologies, however, there is still considerable lack of awareness on the part of potential users, and it is in response to this that the processing chain for data collection through to orthophoto production described here has been developed. This study explores the major issues that affect quality, mission logistics and cost and will demonstrate the methodology and application of digital techniques for producing georectified imagery and contoured orthophoto maps of coastal environments. This will be achieved through a series of case studies of dynamic dune environments in south-west England and France. Digital imagery was captured using a colour infrared Aerial Digital Photographic System and ground control was collected using differential Global Positioning Systems. This study seeks to assess the application of this imagery to coastal dune monitoring, putting these new techniques within the grasp of coastal dune managers, enabling them to make use of digital imagery captured to different specifications depending on the accuracy requirement of the end product. The results indicate that this type of imagery and the techniques used can provide the dune manager with information which would otherwise be too costly or time consuming to acquire. 2D rectification of the imagery provided maps of dune retreat and accretion with errors in the region of± 1.5m, and rectification to a higher order using 3D photogrammetric correction provided 1 :5000 contoured orthophotographs with mean xy errors in the region of 2. 5 m and mean elevation errors in the region of 1.5m.

Aerial photography and digital visualisation technologies are commonly used to reveal and interpret archaeological sites and landscapes. These methods afford a clarity and overview that has considerable advantages in heritage visualisation. Despite this, both technologies offer a view that is distanced from the grounded experiences that are integral to heritage sites and landscapes. This tension, between visualisation technologies and lived experience, is significant because the experiences of visiting these places are a valuable common platform - shared by specialists and general audiences alike - for communicating archaeological narratives. Beyond this, such tensions have been central to debates within landscape archaeology about how embodied perspectives on the one hand, and the conventions of visual representation on the other, might affect archaeological interpretations. This thesis investigates the hypothesis that creative practice can serve to bridge the gap between visualisation technologies and lived experience, ultimately providing more powerful and meaningful visualisations of landscape heritage. This is possible because aerial and digital visualisations can and do go beyond topographical representation and respond to the aesthetic and emotive dimensions of landscape. Aerial photographs and digital models resist the visual modes of modernity despite their technological premise. The meanings that they transmit draw not only from the visual language of aerial photography and digital media but also from the viewer's prior experience of landscape and flight. It is within this context that this study attempts to better understand the relationship between visualisation technologies, creative practice, and the lived experience of landscape. To do this the author adopts the role of research-practitioner in order to explore and demonstrate the arguments through the creative application of aerial photography and digital visualisation technologies. This practice combines methods from archaeological survey, and approaches from visual effects filmmaking, with an aesthetic inspired by artist-photographers like Marilyn Bridges, Emmet Gowin and Patricia Macdonald. These creative practitioners have adopted the aerial view to portray landscapes with intimacy, agency and dynamism. The practice aims to work from an immersed or insider's view, drawing influence from Tim Ingold's notion of the "dwelling perspective". A main case study is undertaken at the Iron Age hillfort site of the Caterthuns in Angus, Scotland, with supporting case studies at the prehistoric site of Links of Notlland in Orkney and additional hillfort sites in Strathearn. Through this hands-on experience the aim is to better understand how novel approaches to practice can improve landscape heritage visualisation in an interdisciplinary context.

In recent years, mapping software utilizing scanned?or ?softcopy??aerial photographs has become widely available. Using scanned photos of Valley Forge (PA) National Historical Park, I explored some of the latest tools for image processing and computer-based vegetation mapping. My primary objective was to compare different approaches for their efficiency and accuracy. In keeping with the USGS-NPS Vegetation Mapping Program protocol, I classified the park?s vegetation according to The Nature Conservancy?s National Vegetation Classification System (NVCS).

Initially, I scanned forty-nine 1:6000 color-infrared air photos of the area at 600 dpi using an Epson desktop scanner. I orthorectified the images by two different methods. First, I did so on a single-image basis using ERDAS Imagine. In this approach, United States Geological Survey (USGS) Digital Ortho Quarter Quadrangles (DOQQ) and a 10-meter Digital Elevation Model (DEM) served as references for between seven and twelve ground control points per photo. After achieving a root mean square error (RMSE) of less than 1 meter for an image, I resampled it into an orthophoto. I then repeated the process using Imagine Orthobase. Via aerial triangulation, Orthobase generated an RMSE solution for the entire block of images, which I resampled into orthophotos using a batch process.

Positional accuracies were remarkably similar for image mosaics I created from the single-image as well as the Orthobase orthophotos. For both mosaics, planimetric x-coordinate accuracy met the U.S. National Map Accuracy Standard for Class 1 maps, while planimetric y-coordinate accuracy met the Class 2 standard. However, the Orthobase method is faster?reducing process time by 50%?and requires 20% (or less) of the ground control points necessary for the single-image method.

I delineated the park?s vegetation to the formation level of the NVCS. Using ESRI ArcMap, I digitized polygons of homogeneous areas observed from the orthophotos. This on-screen mapping approach was largely monoscopic, though I verified some areas using a scanning stereoscope and the original hard-copy photos. The minimum mapping unit (MMU) was 0.5 acres (ac), smaller than that recommended by the USGS-NPS protocol. Based on field data, thematic accuracy for this map met the National Map Accuracy Standard of 80%. Misestimation of the hydrologic period of certain polygons resulted in some classification errors, as did confusion between evergreen and deciduous vegetation.

In addition to orthophotos, Orthobase creates a stereo block viewable in ERDAS Stereo Analyst, a digital stereoscopic software package. Using Crystal Eyes? eyewear and a high-refresh-rate monitor, a user can observe imagery full screen, three-dimensionally. Features delineated on the images are stored in ESRI shapefile format. I created a preliminary vegetation map at the alliance level of the NVCS with this software. Thematic accuracy of this map will be known when assessment is completed this summer. Notably, the classification scheme has required revision to accommodate the anthropogenically altered landscape of Valley Forge.

Nevertheless, it is clear that Stereo Analyst offers advantages for vegetation and other types of mapping. Stereoscopic view and sharp zoom-in capabilities make photo interpretation straightforward. Because features are delineated directly into a GIS, Stereo Analyst cuts process time by 70% and avoids two steps that can introduce errors in conventional mapping methods (i.e., transfer to map base and digitizing). Perhaps most importantly, joint use of Orthobase and Stereo Analyst allows simultaneous orthophoto creation and GIS data collection; in contrast, the ArcMap approach requires finished orthophotos before features can be delineated. Ultimately, though, both monoscopic and stereoscopic methods have roles in vegetation mapping projects. The level of detail required for the project should determine which technique is most appropriate.

Thesis (M.S.)--West Virginia University, 2000.
Title from document title page. Document formatted into pages; contains x, 128 p. : ill. (some col.), maps (some col.) Vita. Includes abstract. Includes bibliographical references (p. 116-121).

Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Oceanografia Física, Química e Geológica, Instituto de Oceanografia, 2005.
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Este estudo apresenta um mapeamento detalhado do uso do solo da margem esquerda do Canal do Rio Grande, no município de São José do Norte, realizado através da fotointerpretação de imagens digitais, 35 mm, no modo visível, adquiridas com o sensor aerotransportado ADAR 1000 e de verificações de campo. As imagens foram inseridas no programa MegaGIS, criando um Sistema de Informações Geográficas (SIGs), denominado SIG-MECRG/SJN. A alta resolução das fotografias aéreas (0,5m por pixel) permitiu a visualização e identificação dos diferentes alvos. Através do uso de produtos de sensoriamento remoto e do uso das tecnologias de geoprocessamento, é possível mapear e identificar as feições observadas. O uso das fotografias aéreas é adequado para o mapeamento de áreas urbanas, devido à sua alta resolução espacial. Além das informações digitais, foram obtidas informações sobre as residências da área através de entrevistas com os moradores. Para a elaboração do SIG, foram utilizados programas para georreferenciar, exportar e manipular as fotografias aéreas. O emprego destas fotografias foi satisfatório para o reconhecimento e identificação das feições estudadas. As principais feições mapeadas na área de estudo foram as residências, a linha de costa, a hidrografia, as marismas, as dunas e as modificações antrópicas. Todas as informações inseridas no SIG, podem ser consultadas de acordo com o interesse do pesquisador. Estas consultas podem ser disponibilizadas na forma de gráficos para a visualização dos dados.
This study presents a detailed mapping of the land uses along the left margin of the Canal do Rio Grande, municipality of São José do Norte. The mapping was conducted using (a) interpretation of digital photographs (35 mm) acquired by airborne sensor ADAR 1000 and (b) field surveys. A Geographical Information System (GIS), denominated SIG-MECRG/SJN, was created using the MegaGIS software. To build the GIS, it was necessary the application of geoprocessing techniques, and export and enhancement of digital photos. Additionally, data about the properties identified in the photos were obtained through interviews with local residents. The high resolution of the aerial photos (0.5 m per pixel) combined with geoprocessing techniques allowed the identification of the different targets in the urban area. The main targets identified in the area are: houses, coastline, water flows, salt marshes, dunes, and man-made changes in the landscape. The GIS allows searching of information according to specific needs from which data can be displayed in tabular or graphic formats.

With the drone industry's recent explosive advancement, aerial photography is becoming increasingly important for an array of applications ranging from construction to agriculture. A drone flyover can give a better overview of regions that are difficult to navigate, and is often significantly faster, cheaper and more accurate than man-made sketches and other alternatives. With this increased use comes a growing need for image processing methods to help in analyzing captured photographs. This thesis presents a method for automatic location detection in aerial photographs using databases of aerial photographs and satellite images. The proposed pipeline is based on an initial round of tests, performed by using existing feature detection, description and matching algorithms on aerial photographs with a high degree of similarity. After which further modifications and improvements were implemented to make the method functional also for handling aerial photographs with a high level of inherent differences, e.g., viewpoint changes, different camera- and lens parameters, temporary objects and weather effects. The method is shown to yield highly accurate results in geographical regions containing features with a low level of ambiguity, and where factors like viewpoint difference are not too extreme. In particular, the method has been most successful in cities and some types of farmland, producing very good results compared to methods based on camera parameters and GPS-location, which have been common in automatic location detection previously. Knowledge of these parameters is not necessary when applying the method, making it applicable more generally and also independently of the precision of the instruments used to determine said parameters.  Furthermore, the approach is extended for automatic processing of video streams. With lack of available ground truth data, no definite conclusions about absolute accuracy of the method can be drawn for this use case. But it is nevertheless clear that processing speeds can be greatly improved by making use of the fact that subsequent video snapshots have a large graphical overlap. And it can indeed also be said that, for the tested video stream, using a type of extrapolation can greatly reduce the risk of graphical noise making location detection impossible for any given snapshot.
Då drönarindustrin växer så det knakar, har flygfoton blivit allt viktigare för en rad applikationer i vårt samhälle. Att flyga över ett svårnavigerat område med en drönare kan ge bättre översikt och är ofta snabbare, billigare och mer precist än skisser eller andra alternativa översiktsmetoder. Med denna ökade användning kommer också ett ökat behov av automatisk bildprocessering för att hjälpa till i analysen av dessa fotografier. Denna avhandling presenterar en metod för automatisk positionsbedömning av flygfoton, med hjälp av databaser med flygfoton och satellitfoton. Den presenterade metoden är baserad på inledande tester av existerande feature detection, feature description och feature matching algoritmer på ett något förenklat problem, där givna foton är väldigt grafiskt lika. Efter detta implementerades ytterligare modifikationer och förbättringar för att göra metoden mer robust även för bilder med en hög nivå av grafisk diskrepans, exempelvis skillnad i synvinkel, kamera- och linsparametrar, temporära objekt och vädereffekter. Den föreslagna metoden ger nöjaktiga resultat i geografiska regioner med en proportionellt stor mängd grafiska särdrag som enkelt kan särskiljas från varandra och där den grafiska diskrepansen inte är allt för stor. Särskilt goda resultat ses i bland annat städer och vissa typer av jordbruksområden, där metoden kan ge betydligt bättre resultat än metoder baserade på kända kameraparametrar och fotografens GPS-positionering, vilket har varit ett vanligt sätt att utföra denna typ av automatisk positionsbestämning tidigare. Dessutom är den presenterade metoden ofta enklare att applicera, då precisionen för diverse mätinstrument som annars måste användas när fotot tas inte spelar in alls i metodens beräkningar. Dessutom har metoden utökats för automatisk processering av videoströmmar. På grund av bristfälligt referensdata kan inga definitiva slutsatser dras angående metodens precision för detta användningsområde. Men det är ändå tydligt att beräkningstiden kan minskas drastiskt genom att använda faktumet att två påföljande ögonblicksbilder har ett stort grafiskt överlapp. Genom att använda en sorts extrapolering kan inverkan från grafiskt brus också minskas, brus som kan göra positionsbestämning omöjligt för en given ögonblicksbild.

This study demonstrates the value of historical aerial photographs as a source for monitoring long-term landslide evolution, which can be unlocked by using appropriate photogrammetric methods. The understanding of landslide mechanisms requires extensive data records; a literature review identified quantitative data on surface movements as a key element for their analysis. It is generally acknowledged that, owing to the flexibility and high degree of automation of modern digital photogrammetric techniques, it is possible to derive detailed quantitative data from aerial photographs. In spite of the relative ease of such techniques, there is only scarce research available on data quality that can be achieved using commonly available material, hence the motivation of this study. In two landslide case-studies (the Mam Tor and East Pentwyn landslides) the different types of products were explored, that can be derived from historical aerial photographs. These products comprised geomorphological maps, automatically derived elevation models (DEMs) and displacement vectors. They proved to be useful and sufficiently accurate for monitoring landslide evolution. Comparison with independent survey data showed good consistency, hence validating the techniques used. A wide range of imagery was used in terms of quality, media and format. Analysis of the combined datasets resulted in improvements to the stochastic model and establishment of a relationship between image ground resolution and data accuracy. Undetected systematic effects provided a limiting constraint to the accuracy of the derived data, but the datasets proved insufficient to quantify each factor individually. An important advancement in digital photogrammetry is image matching, which allows automation of various stages of the working chain. However, it appeared that the radiometric quality of historical images may not always assure good results, both for extracting DEMs and vectors using automatic methods. It can be concluded that the photographic archive can provide invaluable data for landslide studies, when modern photogrammetric techniques are being used. As ever, independent and appropriate checks should always be included in any photogrammetric design.

Ground based forest inventory surveys can provide highly accurate measurements of tree and stand characteristics, but are time-consuming and costly, and therefore typically limited to number of sample plots.  Estimating tree and stand characteristics from digitised aerial photographs can provide measurements from the whole stand, but is less accurate.  The goal of this study was to evaluate the application of scanned, stereo aerial photography and digital photogrammetry in combination with tree crown delineation techniques to measure tree and stand characteristics in two sites in Scotland, Rosarie and Leanachan forests.  Existing medium-resolution scanned images of true colour aerial photographs (1:10,000) were used to derive Digital Elevation Models (DEMs) of the forest canopy and digital orthophotographs.  Tree crown delineation techniques were used on the derived digital orthophotographs and tree crown measurements including crown area and coordinates of each crown were derived.  The DEMs in combination with Digital Terrain Models (DTMs) derived from digital contour maps, were used for the estimation of tree and stand heights.  Equations derived from regression analysis of individual tree measurements on the ground, and the orthophotographs from Rosarie forest, were used for the estimation of tree and stand characteristics of both sites. For Rosarie forest the estimations of stand top height, basal area, stand volume stand biomass and stand density (~23.7%) were similar with the ground measured stand characteristics (±10%), where as for Leanachan forest the estimations were less accurate due to the non-optimum illumination conditions during the acquisition of the aerial photographs. The level of accuracy achieved in this study is adequate for measuring tree and stand characteristics, if the acquisition conditions of aerial photographs are optimal.  Higher level of accuracy may be possible, but requires more accurate DTMs, possibly derived using active airborne remote sensing sensors.

This research assesses the accuracy of SRTM and AIRSAR DEMs acquired over the mountainous-hillands of Cameron Highlands with DEMs generated from Digital Aerial Photograph (DAP) with a fine (2 m) spatial resolution and height resolution of about 0.5 m. The ground control points used for generating stereo models from the DAP were acquired during field work using GPS which achieved accuracy better than 2 cm in most cases. To overcome the difficulty of overlaying the DEMs with the DAP DEM as no features can be easily identified on both the images, therefore a technique of using transects and contours generated from the DEMs were used to correct the horizontal displacement. For AIRSAR DEM, comparing the accompanying AIRSAR composite images was also employed. These then allowed an analysis of the height accuracy to be undertaken. The height of both the AIRSAR and SRTM DEMs were also corrected by applying Linear Regression Models. These models were produced by comparing pixels obtained from points, profiles and an area. Once again the corrected DEMs were assessed. Finally the extracted profiles and contours from the corrected SRTM and AIRSAR were compared with the reference DEM. From the comparisons, the horizontal errors were found to be about one and the half pixels (138.72 m: for SRTM) to the east and 1 pixel (10 m: for AIRSAR) to the south. The SD of height differences of the SRTM and AIRSAR DEMs using 90% data were 9.2 m and 5.2 m with profiles comparison; 10.4 m and 5.4 m with area comparison; 10.8 m and 2.4 m with GPS GCPs comparison respectively. From the three comparisons, the means of height differences are 5.2 m, 6.1 m and 15.2 m for SRTM and 8.1 m, 8.3 m and 7.9 m for AIRSAR DEM. The results suggest there is height offset in the AIRSAR DEM. When both heights of DEMs were corrected, the generated contours are close to each other and to reference contours. Using contour colours images and height modelling, the corrected DEM was found to have the potential to detect areas that prone to flash floods and mudslides.

Forests have been proposed as a means of reducing atmospheric carbon dioxide levels due to their ability to store carbon as biomass. To quantify the amount of atmospheric carbon sequestered by forests, biomass and density estimates are often needed. This study develops, implements, and tests an individual tree-based algorithm for obtaining forest density and biomass using orthophotographs and small footprint LiDAR imagery. It was designed to work with a range of forests and image types without modification, which is accomplished by using generic properties of trees found in many types of images. Multiple parameters are employed to determine how these generic properties are used. To set these parameters, training data is used in conjunction with an optimization algorithm (a modified Nelder-Mead simplex algorithm or a genetic algorithm). The training data consist of small images in which density and biomass are known. A first test of this technique was performed using 25 circular plots (radius = 15 m) placed in young pine plantations in central Virginia, together with false color othophotograph (spatial resolution = 0.5 m) or small footprint LiDAR (interpolated to 0.5 m) imagery. The highest density prediction accuracies (r2 up to 0.88, RMSE as low as 83 trees / ha) were found for runs where photointerpreted densities were used for training and testing. For tests run using density measurements made on the ground, accuracies were consistency higher for orthophotograph-based results than for LiDAR-based results, and were higher for trees with DBH ≥10cm than for trees with DBH ≥7 cm. Biomass estimates obtained by the algorithm using LiDAR imagery had a lower RMSE (as low as 15.6 t / ha) than most comparable studies. The correlations between the actual and predicted values (r2 up to 0.64) were lower than comparable studies, but were generally highly significant (p ≤ 0.05 or 0.01). In all runs there was no obvious relationship between accuracy and the amount of training data used, but the algorithm was sensitive to which training and testing data were selected. Methods were evaluated for combining predictions made using different parameter sets obtained after training using identical data. It was found that averaging the predictions produced improved results. After training using density estimates from the human photointerpreter, 89% of the trees located by the algorithm corresponded to trees found by the human photointerpreter. A comparison of the two optimization techniques found them to be comparable in speed and effectiveness.
Ph. D.

A produção de mosaicos fotográficos é uma atividade de apoio bastante importante em diversas áreas tais como a geração de mapas, o monitoramento ambiental e o gerenciamento agrícola. A fotogrametria, e em especial a aerofotogrametria, é a ciência que trata, entre outros tópicos, da geração de mosaicos através de procedimentos trabalhosos, o que torna sua manutenção uma tarefa difícil e de alto custo. O Projeto ARARA (Aeronaves de Reconhecimento Assistidas por Rádio e Autônomas) representa uma alternativa de baixo custo para a aquisição de fotografias aéreas. Câmeras digitais de pequeno formato a bordo das aeronaves permitem a obtenção automática das fotografias necessárias para a geração de mosaicos. Este trabalho propõe uma metodologia para a geração e a atualização de mosaicos compostos por fotografias aéreas oblíquas digitais e de pequeno formato, adquiridas com o auxílio das aeronaves do Projeto ARARA. As fotografias podem ser submetidas a procedimentos que associam técnicas de ortoretificação e processamento digital de imagens para corrigir suas distorções geométricas e radiométricas. A metodologia apresentada neste trabalho procura evitar a necessidade de pontos de controle no solo e focaliza a geração automática ou semi-automática dos mosaicos. Procedimentos automáticos têm o potencial de permitir a utilização de uma grande quantidade de fotografias de pequeno formato em substituição às fotografias normalmente utilizadas pela aerofotogrametria convencional.
The generation of photographic mosaics is an important activity in many areas such as map production, environment monitoring and agricultural management. Photogrammetry, and specially aero-photogrammetry, are the sciences that deal, among other subjects, with mosaic generation using time consuming procedures, making the maintenance and updating of photographic mosaics a difficult and high-cost task. The ARARA Project (Autonomous and Radio Assisted Reconaissance Aircrafts), presents a low cost alternative to acquire aerial photographs. An onboard, small format digital camera can take automatically the photographs used for the mosaic generation. This work proposes a methodology for mosaic generation and updating using oblique, digital, small format aerial photographs taken by ARARA aircraft. Photographs can be corrected both geometrically and radiometrically by orthorectification and digital image processing procedures. The methodology presented in this work avoids the use of ground control points, focusing on the automatic and semi-automatic mosaic generation. An automatic procedure make possible the use of a large number of small format photographs to replace the photographs normally used in conventional aerophotogrammetry.

Nesta dissertação é apresentado o desenvolvimento de uma ferramenta computacional para o processamento de pares de imagens estereoscópicas obtidos por câmeras aéreas métricas e não métricas. O programa foi desenvolvido na linguagem C++ e foi utilizado a biblioteca OpenGL. O resultado obtido é uma imagem tridimensional de onde pode ser extraídas cotas de altura e formas de terreno. Estas imagens poderão ser usadas no estudo de áreas de risco em encostas.
In this dissertation is presented the development of a computational tool for the processing of pairs of images estereoscópicas obtained by metric and not metric aerial cameras. The program was developed in the program language C++ and the library was used OpenGL. The result of the program is a three-dimensional image from where it can be extracted height quotas and land forms. These images can be used in the study of risk areas on slopes.

碩士
國立政治大學
地政學系
89
It needs the information of land use intensity to control the growth of cities, such as building coverage ratio and building bulk ratio. It spends much manpower and time to get the information. The improving technology of digital photogrammetry and geographic information systems can assist investigate and collect the information. The objective of this research has been to analyze the land use intensity with assistance of geographic information systems and digital photogrammetry. Digital aerial photographs have been used to collect 3-D spatial information of research area. This information has been imported into a geographic information system. Building coverage ratio and building bulk ratio of whole research area could be established thereafter. The information collected by digital photogrammetry has also been investigated and checked in situ. The results have indicated that: 1.The ratios of both building coverage ratio and building bulk ratio to the original planned record have been of 1.1~1.2. 2.The most suitable height of each floor is 3.3m when calculating the floor number of building in the research area. 3.Digital aerial photographs could be very useful when the information of land use intensity was required.

Seagrasses are core components of the nearshore environment and there is sustained interest in developing mapping and monitoring techniques of their extent and condition for management purposes. An identified gap in mapping methods is the capacity to monitor at landscape scales, that is, areas that are larger than the 1 m2 quadrat and smaller than those covered by broad area mapping (approximately 5km2 or greater). Monitoring at the landscape scale is required to investigate the dynamic patterning and patchiness present in seagrass beds, as well as providing inputs and validation for predictive modelling. However, the acquisition and use of remote sensing images for these purposes provides many challenges to the practitioner. The primary aim of this thesis is to develop effective optical remote sensing techniques for mapping and monitoring seagrass habitats in shallow temperate marine waters, over depth ranges of approximately 0-10 m and spatial scales of hundreds of square metres. Image capture is often compromised because of environmental conditions, such as sun glitter, water clarity, cloudiness and wind. Small format digital aerial photography was selected as the remote sensing platform for its flexibility and responsiveness regarding deployment when environmental conditions are favourable and its low cost, rapid access to imagery. To address the problem of sun glitter, a simplified algorithm was developed that allows the precise prediction of the extent of sun glitter on vertical, downward-looking imagery with the readily available inputs of sun elevation angle, wind speed and sensor field of view (FOV). Subsurface illumination was also investigated via the modelling of reflection and refraction at the water surface. These improvements and investigations enable more efficient and accurate image capture. Problems are also typically encountered during image interpretation, in part due to the characteristics of the seagrass habitats, including the common occurrence of uncertain boundaries and the high variability of vegetation density. Limitations on the detectability of the maximum depth limit (MDL) of seagrass were examined, with the discovery that if imagery is captured when water clarity is higher than the annual average, the limiting factor is the contrast between the seagrass and the surrounding substrate or submerged aquatic vegetation (SAV). A simple and inexpensive measurement of water clarity, Secchi depth (Zsd), was found to be suitable when applying this monitoring method. These findings have substantially increased the feasibility of monitoring seagrass condition and extent via the MDL, as well as the water quality parameter of average annual water clarity (Kz). A major challenge for image interpretation is presented by the high attenuation of light in water, which often means that spectral methods of image analysis, such as image classification, produce poor results. In response, an improved depth correction approach was developed that uses digital bathymetry (DEM) to assist in removing the spectral attenuation of light by the water column. The method lifted the accuracy of mapping seagrass epiphyte abundance (i.e. the amount of associated algae including epiphytic and drift algae present, related to biomass) by an average 25% to an overall average accuracy of 75%, though it made no difference to the accuracy of SAV density mapping (Note: SAV density relates to the proximity and length of the SAV blades such that high density SAV obscures the substrate and creates high levels of shadowing while lower densities have less shadowing and allow the substrate to be observed.). The improved depth correction method also enabled, for the first time from aerial photography, the production of a spatially explicit map of epiphytic biomass in the form of a continuous prediction surface with values ranging from 4 to 58 g dried weight m-2. In response to the shortcomings of the existing field observation measurements of seagrass density and cover for image interpretation purposes, a new measurement was created, called SAV structural density or SSD, which is designed to improve thematic coherence between aerial photography and field observations, such as downward-looking benthic videography or dive quadrats. This new measurement enabled the consistent discrimination of high and low density SAV with average overall accuracies of 77%, which supports the assessment of seagrass condition, particularly when complemented by the new maps of epiphyte abundance. This thesis presents methods that improve the quality of remote sensing of shallow marine habitats and provides a more reliable basis for further investigation of habitat change detection via spatial metrics and predictive modelling at landscape scales.

Seagrasses are core components of the nearshore environment and there is sustained interest in developing mapping and monitoring techniques of their extent and condition for management purposes. An identified gap in mapping methods is the capacity to monitor at landscape scales, that is, areas that are larger than the 1 m2 quadrat and smaller than those covered by broad area mapping (approximately 5km2 or greater). Monitoring at the landscape scale is required to investigate the dynamic patterning and patchiness present in seagrass beds, as well as providing inputs and validation for predictive modelling. However, the acquisition and use of remote sensing images for these purposes provides many challenges to the practitioner. The primary aim of this thesis is to develop effective optical remote sensing techniques for mapping and monitoring seagrass habitats in shallow temperate marine waters, over depth ranges of approximately 0-10 m and spatial scales of hundreds of square metres. Image capture is often compromised because of environmental conditions, such as sun glitter, water clarity, cloudiness and wind. Small format digital aerial photography was selected as the remote sensing platform for its flexibility and responsiveness regarding deployment when environmental conditions are favourable and its low cost, rapid access to imagery. To address the problem of sun glitter, a simplified algorithm was developed that allows the precise prediction of the extent of sun glitter on vertical, downward-looking imagery with the readily available inputs of sun elevation angle, wind speed and sensor field of view (FOV). Subsurface illumination was also investigated via the modelling of reflection and refraction at the water surface. These improvements and investigations enable more efficient and accurate image capture. Problems are also typically encountered during image interpretation, in part due to the characteristics of the seagrass habitats, including the common occurrence of uncertain boundaries and the high variability of vegetation density. Limitations on the detectability of the maximum depth limit (MDL) of seagrass were examined, with the discovery that if imagery is captured when water clarity is higher than the annual average, the limiting factor is the contrast between the seagrass and the surrounding substrate or submerged aquatic vegetation (SAV). A simple and inexpensive measurement of water clarity, Secchi depth (Zsd), was found to be suitable when applying this monitoring method. These findings have substantially increased the feasibility of monitoring seagrass condition and extent via the MDL, as well as the water quality parameter of average annual water clarity (Kz). A major challenge for image interpretation is presented by the high attenuation of light in water, which often means that spectral methods of image analysis, such as image classification, produce poor results. In response, an improved depth correction approach was developed that uses digital bathymetry (DEM) to assist in removing the spectral attenuation of light by the water column. The method lifted the accuracy of mapping seagrass epiphyte abundance (i.e. the amount of associated algae including epiphytic and drift algae present, related to biomass) by an average 25% to an overall average accuracy of 75%, though it made no difference to the accuracy of SAV density mapping (Note: SAV density relates to the proximity and length of the SAV blades such that high density SAV obscures the substrate and creates high levels of shadowing while lower densities have less shadowing and allow the substrate to be observed.). The improved depth correction method also enabled, for the first time from aerial photography, the production of a spatially explicit map of epiphytic biomass in the form of a continuous prediction surface with values ranging from 4 to 58 g dried weight m-2. In response to the shortcomings of the existing field observation measurements of seagrass density and cover for image interpretation purposes, a new measurement was created, called SAV structural density or SSD, which is designed to improve thematic coherence between aerial photography and field observations, such as downward-looking benthic videography or dive quadrats. This new measurement enabled the consistent discrimination of high and low density SAV with average overall accuracies of 77%, which supports the assessment of seagrass condition, particularly when complemented by the new maps of epiphyte abundance. This thesis presents methods that improve the quality of remote sensing of shallow marine habitats and provides a more reliable basis for further investigation of habitat change detection via spatial metrics and predictive modelling at landscape scales.

Thesis (M.S.)--University of Wisconsin--Madison, 2006.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 48-50).

碩士
國立臺北科技大學
土木與防災研究所
100
A sequence of earthquakes, from October 22 to December 5 in 1951, occurred from Hualien to Taitung of Longitudinal Valley. There was a serials of surface rupture caused by the earthquakes around Ruei-Suie area. Chung(2003) demonstrate that 1951 rupture may separate to three segments, Ruei-Suie,Yuli and Chihshang segment. The maximum displacement of Ruei-Suie segment about 2 meters. Most of the studies are focus on the description in 1951 earthquake, to characteristics of near-fault activity and deformation, however the surface rupture of 1951 earthquake did not discuss in details. By the advancing technology in recent years, the serials of the remote-sensing images taken in different periods have been wildly applied for multi-displine, especially for surface and environmental change analysis. The earliest aerial photographs were taken by the U.S. Air force during the 1940s in Taiwan. Nevertheless, because of absent of aerial information, difficult to acquire and image damages, it’s difficult to achieve and for application. In this study, the aerial images were taken by the U.S. Air force and TW Air force during 1940-1960. The Real Time Kinematic GPS equipment has been used accordingly to measure the ground reference points to calculating the exterior orientation parameters of each image. The photos is thus been orthorectified by means of the Airborne LiDAR data. Finally, the 1951 Ruei-Suie earthquake deformation is analyzed by means of Particle Image Velocimetry (PIV) sub-pixel matching technique and feature point measurements base on the orthorectified images. The results shows 2008’s DTM is better than 5M_DEM official data. The most important of DTM construction based on historical aerial photography is the definition of image. It’s difficult to calculate the coseismic displacement by PIV sub-pixel matching technique, because of the topography has been change a lot. By the feature points, it indicates Ruei-Suie fault show a left-lateral reverse fault, and the average displacement is 3.66 m , the maximum displacement is 5.77 m.

Accurate and up-to-date information about forest resources is crucial to effective forest management. Remote sensing technologies are increasingly being applied to forest resource assessment, with airborne laser scanning (ALS) now employed for operational forest management in many countries. Statistical relationship between ALS point cloud data and forest structural data collected in the field are exploited to arrive at spatially explicit estimates of forest inventory attributes. Digital aerial photography (DAP) has recently emerged as a potential alternative to ALS that may provide advantages such as lower deployment and data collection costs and easier access to a greater variety of sensors and platforms. However, the robustness and reliability of DAP methods need to be well understood and proven prior to operationalisation of a photogrammetric approach to point cloud measurement of forest structure. Pinus radiata is the dominant plantation tree species in Australia and New Zealand. Using a P. radiata study site located in north east Tasmania, Australia, this thesis characterises DAP-based point clouds and evaluates the potential to apply DAP point cloud data to forest inventory. The thesis investigates the capability of DAP-based point cloud to characterise forest structure, including the influences of photogrammetric processing strategies, terrain slope, canopy occlusion, canopy cover, photo-overlap and camera location. Canopy metrics commonly used in statistical models to estimate forest inventory attributes are examined for three different point cloud generation strategies and are shown to be robust to the choice of strategy. Point cloud data from small- and medium-format DAP is utilised to estimate area-based forest inventory variables (top height, basal area, stocking and total stem volume). Accuracy as well as precision of the statistically modelled inventory variables are compared with those derived from ALS and with field data at both plot- and stand-level. It is concluded that forest inventory attributes can be estimated using DAP-based point cloud data sourced from cameras with different technical specifications (i.e. small- and medium-format cameras) and that accuracy levels are similar to those derived from ALS. The suitability of DAP-based point cloud for individual tree detection (ITD) is evaluated. Two point cloud based ITD algorithms are applied to point cloud data sourced from small- and medium-format photography and from ALS. Using each of the ITD algorithms, the accuracy of tree-detection is reported for each of the data types. The influence of canopy structure and the relationship of canopy structural metrics with tree detection are investigated. This thesis contributes to the understanding of the robustness of DAP-based point cloud data, the capability of DAP-based point cloud data to characterise forest canopy and to be used to derive estimates of forest inventory attributes. The thesis demonstrates the robustness of DAP-based point clouds for area-based forest inventory. The findings will assist forest managers to optimally choose from a variety of sensors and platforms that best suit their operational needs and to optimise flight planning and photo-acquisition for forest inventory applications.

碩士
國立屏東科技大學
森林系所
100
Traditional forest inventory have to put in a lot of manpower and material resources to address weaknesses at the lowest cost, and new forest inventory methods based on remote sensing that have been an important issue. ADS40 airborne multispectral images are high-resolution aerial photographs that have been widely applied in forest inventory. In this study, we used the ADS40 airborne multispectral images to classify the land-use types of the Fourth Survey Forest Resource project. The use of High-Resolution Remote-Sensing (HRRS) imagery of classification is liable to cause heavy Salt-and-Pepper Noises; therefore, I chose object-oriented classification methods for ADS40 images to reduce material quantity of imageodesy. The results showed that the image segmentation scale 400 type was better than other image segmentation scales; hence image classification results of accuracy were used to compare pixel-base and object-base image classifications. The analysis determined that object-base image classification was better than pixel-base image classification. Each image information type was collected and used as the image of the superimposed images, and Maximum Likelihood Classification was used to compare different superimposed images of overall classification accuracy. The image group was elected of using Duncan statistical analysis that the result has 54.82% of overall classification accuracy, 0.4997 of overall kappa, and Kappa values were used to compare the two classification methods of Maximum Likelihood and the Knowledge-Based Classification to applicability of ADS40 images. In conclusion, Knowledge-Based Classification showed that the result had 78.20% of overall classification accuracy and 0.7597 of overall kappa statistics better than results of maximum likelihood classification.

碩士
國立高雄大學
土木與環境工程學系碩士班
103
Unmanned aerial vehicle (UAV) can be used to take aerial photographs, and it has drawn widely attraction in recent years. This study will use aerial photographs and digital image correlation method (DIC) to establish three-dimensional terrain models. In this study, instead of manual selection, digital image correlation method is used to obtain the image coordinates of control points. A series of experiments are carried out to confirm the results that DIC can improve the accuracy of the control point positioning. The experiments are divided into indoor and outdoor experiments. The indoor experiments used flat specimen, three-dimensional ladder test specimen and oval model to discuss the influence of the amount of control points on analysis error. According to the indoor experiments, the high variability of control point elevation can improve accuracy of camera calibration, and using seven control points to the analysis is better than using five or six control points. At last, the result of reconstructing spatial coordinates of the oval model shows that the standard error of elevation is 0.1mm, and the ratio of this error to the object distance corresponds to 2.4 / 10000. In outdoor experiments, the aerial photographs of NUK are taken, and these images are used to calibrate the camera and reconstruct three-dimensional coordinates. According to the results, the standard error of elevation coordinate is about 0.136m, and its ratio to the 3 object distance is about 14/10000. This ratio is larger than that obtained by Airborne LiDAR and ImageStation Automatic Elevations.

碩士
國立臺灣大學
森林環境暨資源學研究所
94
The Aerial Survey Office of the Forestry Bureau, Council of Agriculture established in 1956 which is the only relevant agency in Taiwan. It has engaged extensive survey of forest resources for three times. Aerial photography is one of its major services which has already collected over seven hundreds thousands films of image data over the whole Taiwan areas. Since 2001, this office started scanning and digitalizing its treasures. It was estimated that this office will produce over 280,000 digital images in the end of 2004. Aerial photograph is alternative of comprehensive on-site survey which can collect more data on land use and engage further analysis of transition with less manpower. However, due to the vast amount of information of aerial photography, there is a need to develop a holistic database management system for digital imagines derived from aerial photographs. Metadata can play a key role within this management system which will enhance management effectiveness, circulating and exchange of information. Integrating with large memory equipments and an internet framework, this study tried to adopt metadata as the basis of searching service and to apply computer and internet techniques in order to develop a management system of digital aerial images. The result shows that the management system can shorten the management processes, reduce labor cost, and improve searching efficiency. This has made considerable contributions to distribution and sharing of aerial information.

碩士
國立屏東科技大學
熱帶農業暨國際合作系所
100
Remote sensing image is usually used for the detection of landslide locations in disaster monitoring. However, the presence of shadows often disturbs image information, easily affecting classification of the results. Therefore, the objective of this study are to analyze landslide areas on shaded and non-shaded conditions, extracted by ADS-40 airborne multispectral image, and to design an effective and fast method for future monitoring and management. This study used the Jhuoshuei river forest working circles as study area. We used stratified classifications, filter vegetation image, and slope thresholds to discard false positive landslides among the several image classes. Moreover, histogram matching and linear-correlation corrections were used to restore shaded images. Results showed that shaded images are also suitable for classification, but that restoration by histogram matching or linear-correlation correction didn’t affect significantly classification results. Because non-shaded images don’t have shadow interference, non-shaded areas demonstrated good classification ability. In this study, slopes of 25° and 15°demonstrated higher accuracy for landslide detection on shaded and non-shaded areas, respectively. At these slopes, Kappa values of classification were 0.6204 and 0.8859, and overall accuracy were 83.07% and 94.42%, respectively. Finally, after subsuming the mean of textures into analysis of the non-shaded area, the Kappa value and overall classification accuracy increased to 0.9162 and 95.92%, respectively.

Dissertação de mestrado em Geociências (área de especialização em Dinâmica Externa e Mudanças Globais)
O litoral constitui um ambiente muito dinâmico e muito sensível a impactes naturais e antrópicos. Nas últimas décadas, no litoral do NW de Portugal tem ocorrido uma erosão generalizada, manifestada essencialmente por migração das praias para o interior, perda de sedimentos e recuo das arribas. Embora natural, este processo tem sido agravado pela ação humana, sobretudo como consequência da implementação de obras de defesa costeira. É neste contexto que existe a necessidade de monitorizar e criar uma base de informação precisa de modo a suportar o planeamento e a gestão adequada destas áreas. A obtenção de dados úteis, fiáveis e de grande precisão permite conhecer e prever a evolução costeira, assim como prevenir potenciais consequências de planeamento e gestão deficientes. Neste trabalho aplicaram-se métodos de monitorização costeira de baixo custo nas praias de Ofir e Bonança, no concelho de Esposende. A fotografia aérea foi obtida através de VANT, procedendo-se a técnicas de fotogrametria e de modelação 3D recorrendo a mapeamento móvel com GPS e tecnologias SIG para: (i) demonstrar a utilidade, eficiência e qualidade de modelos tridimensionais para trabalhos de monitorização da orla costeira, (ii) avaliar tendências evolutivas da morfodinâmica costeira com recurso a modelos tridimensionais, (iii) efetuar medições de volumes para estudo de balanços sedimentares recorrendo a modelos tridimensionais e (iv) complementar, criar e prover dados para futuros estudos de monitorização. A análise dos resultados comprova uma intensa dinâmica do sistema praia-duna, com transporte sedimentar predominantemente no sentido NW-SE, devido ao vento marinho e à perda de areia na zona de contato berma da praia-duna por toda a área de estudo, mas principalmente na praia de Ofir.
The coastal zone is characterized by its intense morphodynamics and by the sensitivity to natural and anthropic impacts. In the last decades, the NW Portugal coastal zone has suffered generalized erosion, mainly expressed by inland beaches migration, sediment loss e cliffs retreat. Despite being a natural occurrence, this erosion is being enhanced by human activities largely as a consequence of the construction of coastal defence structures. Therefore the survey and development of a precise database is need to support an accurate planning and management in these areas. The acquisition of useful, reliable and exact data is essential to better knowledge and prediction in coastal evolution as to prevent wrong planning and management decisions. In this work low cost coastal survey methods were applied in Ofir and Bonança beaches, in the municipality of Esposende (northwest Portugal). Aerial photography obtained by UAV, photogrammetry techniques and 3D models using specific software, GPS mobile mapping and GIS technologies were developed in order to: (i) show the utility, efficiency and quality of 3D models in coastal survey and analysis; (ii) assess the coastal morphodynamics and evolution; (iii) define sediment growths or losses through volume measurements using these tools; (iv) compile and provide data for future research and survey. The results show an intense dynamics in the beach-dune system with sedimentary transport occurring mainly from NW to SE. This is due to the predominant sea winds and to the sand loss in the contact between the beach and the dune. It occurs in all the studied area but mainly in the Ofir beach.

碩士
國立政治大學
地政學系
88
The objective of this thesis has been to investigate the feasibility of digital aerotriangulation using small format photos. A focal length of 9mm camera mounted on a helicopter with format of 11.5cm by 11.5cm color positives have been used for taking pictures of the research area. The premarked ground control points were surveyed by GPS. Photo control was executed using a Leica BC3 analytical plotter and an Intergraph ImageStation respectively. The coordinates measurements of photo points using the two instruments have been evaluated. Both of interior and exterior parameters computed from digital triangulation and digitized photos have been used to produce the orthoimage. The resultant orthoimage was then superimposed and compared with the existing 1/1000 digital map. The results have indicated that: 1. The RMSE of digital method were X = 0.097m, Y = 0.090m, Z = 0.161m; the RMSE of analytical method were X = 0.132m, Y = 0.120m, Z = 0.144m; 2. Digital aerotriangulation could be performed using small format photos.