Digital terrain representation. Data Acquisition Methodology. Terrain Surface Modeling (Reconstruction). Algorithms for Triangular Irregular Network Formation. Interpolation Methods. Data Quality Control. Mathematical Models for DTM Accuracy.Multi-Scale Representation of Digital Elevation Models. DTM Data Management. Contouring from DTM. DTM-Based Terrain Analysis (DTM Interpretation). Visualization of DTM Surface. Applications. Integration with GIS. Index.

Digital Terrain Modeling: Principles and Methodology

Image and template matching is probably the most important function in digital photogrammetry and also in automated modelling and mapping. Many approaches for matching have evolved over the years, but the problem is still unsolved in general terms. This paper describes the development of image matching techniques in photogrammetry over the past 50 years, addresses the results of some empirical accuracy studies and also provides a critical account of some of the problems that remain.Although automated approaches have quite a number of advantages, the quality of the results is still not satisfactory and, in some cases, far from acceptable. Even with the most advanced techniques, it is not yet possible to achieve the quality of results that a human operator can produce. There is an urgent need for further improvements and innovations, be it through more powerful multi-sensor approaches, thereby enlarging the information spectrum, and/or through advancements in image understanding algorithms, thus coming closer to human capabilities of reading and understanding image content.

Resume

L’appariement d’images et de formes est sans doute l’operation la plus importante en photogrammetrie numerique et en modelisation et cartographie automatiques. De nombreuses approches se sont succede depuis des annees mais le probleme n’est toujours pas totalement resolu. Cet article decrit le developpement des techniques d’appariement d’images en photogrammetrie pendant les 50 dernieres annees, presente les resultats obtenus dans quelques etudes de precision empiriques, et dresse un bilan critique des problemes qui subsistent. Bien que les approches automatiques aient un grand nombre d’avantages, la qualite des resultats n’est toujours pas satisfaisante, et meme loin d’etre acceptable dans certains cas. Meme avec les techniques les plus avancees, nous sommes toujours dans l’incapacite d’atteindre la qualite des resultats obtenus par un operateur humain. Il y a un besoin urgent d’ameliorations et d’innovations, soit a travers des approches multi-capteurs plus puissantes et consistant aelargir le spectre d’information, soit a travers une amelioration des algorithmes de comprehension d’images visant a les rendre plus proches des possibilites humaines de lecture et de comprehension du contenu des images.

Zusammenfassung

Bild- und Musterkorrelation gehoren zu den wichtigsten Grundfunktionen der Digitalen Photogrammetrie und somit auch der automatischen 3D Modellierung und Kartierung. Viele Ansatze zur Korrelation wurden uber die Jahre entwickelt, aber das Problem gilt grundsatzlich noch immer als ungelost. Dieser Beitrag beschreibt die Entwicklung der Verfahren der Bildkorrelation in der Photogrammetrie uber die letzten 50 Jahre, verweist auf die Ergebnisse einiger empirischer Genauigkeitsstudien und diskutiert einige der immer noch bestehenden Probleme.Obwohl automatische Verfahren eine ganze Reihe von Vorteilen aufweisen, ist doch die Qualitat der Ergebnisse meist nicht ausreichend, teilweise ja sogar weit entfernt von jeglicher Akzeptanz. Selbst mit den hochstentwickelten Verfahren sind wir immer noch nicht in der Lage, die Qualitat der Ergebnisse eines menschlichen Operateurs zu erreichen. Wir benotigen dringend weitere Verbesserungen und Innovationen. Dazu gibt es gegenwartig zwei grundsatzlich gangbare Wege: (a) Nutzung von Multi-Sensor Informationen und somit Erweiterung der Informationsgrundlagen und/oder (b) durch Fortschritte bei den Algorithmen des Bildverstehens und somit besserer Modellierung des menschlichen Prozesses des Bildverstehens.

Resumen

La correspondencia de imagenes y muestras es, probablemente, la funcion mas importante en la fotogrametria digital, en el modelado 3D y en la cartografia automatica. Muchos metodos de correspondencia han evolucionado a lo largo de los anos pero, en terminos generales, el problema se considera aun no resuelto completamente. Este articulo describe la evolucion de las tecnicas de correspondencia de imagenes en la fotogrametria a lo largo de los ultimos 50 anos, analiza los resultados de algunos estudios empiricos de la exactitud, y ofrece una valoracion critica de los problemas aun sin resolver. Aunque los metodos automaticos poseen un gran numero de ventajas, la calidad de los resultados no es todavia satisfactoria y, en algunos casos, incluso esta lejos de ser aceptable. Incluso con las mas avanzadas tecnicas no somos capaces de lograr la calidad de los resultados que un operador humano puede conseguir. Hay una necesidad urgente de continuar las mejoras e innovaciones, ya sea mediante la utilizacion de multiples sensores que incrementen el espectro de la informacion, o por avances en los algoritmos de comprension de la imagen que permitan acercarnos mas a la capacidad humana de lectura e interpretacion de su contenido.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1477-9730.2011.00671.x

Development and Status of Image Matching in Photogrammetry

State of the art and applications in archaeological underwater 3D recording and mapping

The need for sound baseline information about community structure and composition against which changes can be detected and quantified is a well-recognised priority in Antarctica. Here, the collection of such data is challenging, especially at sea, where long-term monitoring is usually logistically feasible only in the proximity of permanent research stations. In recent years, underwater photogrammetry has emerged as a non-destructive and low-cost method for high-resolution topographic reconstruction. We decided to apply this technique to videos, recorded during standard SCUBA surveys of Antarctic benthos in Tethys Bay (Ross Sea, Antarctica) in 2006 and 2015 and originally not meant for photogrammetry. Our aim was to assess the validity and utility of the photogrammetric method to describe benthic communities from the perspective of long-term monitoring. For this purpose, two of the transects surveyed in 2015 were revisited in 2017. Videos were processed with photogrammetric procedures to obtain 3D models of the seafloor and inhabiting organisms. Overall, a total of six 20 m-long transects, corresponding to a total area of ~ 200 m2 of seafloor were analysed. Accuracy of the resulting models, expressed in terms of Length Measurement Error (LME), was 1.9 mm on average. The 2017 transects showed marked differences in some species, such as a 25–49% increase in the number of sea urchins Sterechinus neumayeri (Meissner, 1900) and the complete disappearance of some sponges Mycale (Oxymycale) acerata Kirkpatrick, 1907. Our analyses confirm the efficacy of photogrammetry for monitoring programmes, including their value for the re-analysis of legacy video footage.

/pdf/underwater-photogrammetry-in-antarctica-long-term-429uy8meuq.pdf

Underwater photogrammetry in Antarctica: long-term observations in benthic ecosystems and legacy data rescue

Picture processing: 1974

TWO PRINCIPLES FOR DIGITAL CORRELATION ARE: ONE IS BASED ON REFERRING PHOTOGRAPHIC DENSITIES TO OBJECT POINTS IN AN OBJECT COORDINATE SYSTEM AND CAN BE USED IN CHANGE DETECTION IN THE OBJECT; THE OTHER IS BASED ON SCANNING THE STEREO MODEL IN EPIPOLAR PLANES AND CAN BE USED IN MAPPING APPLICATIONS. THE PRINCIPLES SIMPLIFY THE PROBLEM OF CORRELATION. A PROTOTYPE INCORPORATES THE PRINCIPLES.

S E Masry

Papers

Digital correlation principles