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Logistic Regression A Self Learning Text

Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

Evaluation of vertical accuracy of open source Digital Elevation Model (DEM)

Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method.

The Institute of Geodesy and Photogrammetry (IGP) at ETH Zurich is participating in the Cartosat-1 evaluation programme, a common initiative of ISRO (India) and ISPRS. Within this programme various test sites with reference data have been established and Cartosat-1 images have been acquired over these sites. Here, investigations at the Rome (Italy) and Maussane-les-Alpilles (France) test sites are reported. First, radiometric problems encountered with the images and pre-processing for their improvement are reported. Examples are shown, together with pre-processing methods that can be employed in order to improve image quality, aimed especially at automatic generation of a digital surface model (DSM) with fewer blunders and more matched points. Then, georeferencing is discussed and the 3D point measurement accuracy that can be achieved is introduced, as well as problems encountered with the rational polynomial coefficients (RPCs). The georeferencing results were produced using various options regarding image pre-processing, the mathematical model used for georeferencing, the number and distribution of ground control points (GCPs) and the GCP image mensuration methods. The best results led to a planimetric and height accuracy (RMSE) of about 1·3 m. Use of an affine transformation after the RPCs, with about six well-distributed GCPs transferred with matching to the second image, is suggested. Finally, the results of automatic DSM generation using the SAT-PP program package developed at the IGP are presented. Various DSMs were generated with 10 m grid spacing. The results were checked visually and were also compared to the reference data provided. In the best case, the accuracy achieved is about 2·7 m without any manual editing, in spite of a 3-year difference between the matching and reference DSMs. Although some aspects regarding image quality and RPC generation could be improved, Cartosat-1 is a useful sensor for mapping and especially for the generation of DSMs. However, owing to its poor absolute geolocation accuracy, Cartosat-1 cannot be used for the generation of a global DSM without GCPs.

Resume

L’Institut de Geodesie et de Photogrammetrie (IGP) participe au programme d’evaluation de Cartosat-1, initiative commune de l’ISRO (Inde) et de l’ISPRS. Dans ce programme, plusieurs sites-test avec donnees de reference ont eteetablis et des images Cartosat-1 acquises sur ces sites. Nous rapportons ici nos recherches sur les sites-test de Rome (Italie) et de Maussane-les-Alpilles (B.-du-R., France). Nous signalons d’abord les problemes radiometriques rencontres dans les images et les pretraitements effectues en vue de les ameliorer. Nous montrons des exemples et aussi des methodes de pretraitement pouvant etre utilisees pour ameliorer la qualite des images, dans le but surtout de generer automatiquement un MNS avec moins d’artefacts et plus de points homologues. Ensuite, nous presentons le georeferencement et la precision sur la mesure de points 3D qui peut etre obtenue ainsi que les problemes rencontres avec les Coefficients Polynomiaux Rationnels (RPC). Les resultats du georeferencement ont ete obtenus en variant les options, concernant le pretraitement des images, les modeles mathematiques du georeferencement, le nombre et la distribution des points d’appui terrain (GCP) et les methodes de mesure des GCP dans l’image. Les meilleurs resultats ont conduit a des precisions planimetrique et altimetrique d’environ 1,3m (emq). Nous suggerons l’utilisation d’une transformation affine apres les RPC, avec appariement d’environ six GCP correctement repartis dans le couple. Finalement, nous presentons les resultats de la generation automatique de MNS en utilisant notre propre suite logicielle SAT-PP. Plusieurs MNS ont ete generes avec un echantillonnage spatial de 10m. Les resultats ont ete verifies visuellement et ont ete aussi compares aux donnees de reference fournies. Dans le meilleur des cas, la precision obtenue fut d’environ 2,7m sans aucune correction manuelle, malgre une difference de 3 ans entre le MNS obtenu par correlation et celui de reference. Meme si certains aspects concernant la qualite des images et la generation de RPC pourraient etre ameliores, Cartosat-1 est un capteur pertinent pour la cartographie, particulierement pour la generation de MNS. Neanmoins, en raison de sa faible precision de geolocalisation absolue, Cartosat-1 ne peut etre utilise pour la generation d’un MNS global sans GCP.

Zusammenfassung

Das Cartosat-1 Evaluierungsprogramm ist eine gemeinsame Initiative von ISRO (Indien) und der ISPRS, an dem auch das Institut fur Geodasie und Photogrammetrie (IGP) beteiligt ist. Innerhalb dieses Programms wurden verschiedene Testgebiete mit zugehorigen Referenzdaten angelegt. Es stehen fur jedes Testfeld Cartosat-1 Bilder zur Verfugung. Wir berichten hier uber unsere Untersuchungen in den zwei Testgebieten Rom (Italien) und Maussane-les-Alpilles (Frankreich). Wir behandeln zunachst radiometrische Probleme der Bilder und der Vorverarbeitung. Dann zeigen wir Beispiele und Methoden zur Vorprozessierung zur Verbesserung der Bildqualitat insbesondere mit Hinblick auf die Vermeidung von groben Fehlern bei der DOM Generierung und einer Erhohung der in den Bildern zugeordneten Punkte. Danach werden wir die Georeferenzierung und die erreichbare 3D Punktmessgenauigkeit behandeln, sowie Probleme im Zusammenhang mit den gegebenen Rational Polynomial Coefficients (RPCs). Die Ergebnisse der Georeferenzierung werden unter Berucksichtigung von verschiedenen Vorgehensweisen bei der Bildprozessierung, dem mathematischen Model fur die Georeferenzierung, der Anzahl und Verteilung von Passpunkten und der eingesetzten Bildmessmethoden diskutiert. Das beste Ergebnis liefert eine Lage- und Hohengenauigkeit (RMSE) von ca. 1·3 m. Dabei zeigte sich die Verwendung einer Affintransformation nach der Anwendung der RPCs mit ca. 6 gut verteilten Passpunkten, ubertragen in das zweite Bild mit einer automatischer Bildzuordnung, als sehr geeignet. Zum Schluss prasentieren wir die Resultate der automatischen DOM Generierung unter Verwendung unseres Softwarepaketes SAT-PP. Wir haben verschiedene DOMs mit einer Rastergrosse von 10 m generiert. Die Ergebnisse werden zunachst visuell uberpruft und danach auch mit den gegebenen Referenzdaten numerisch verglichen. Zwischen der Aufnahme der Bilder und der Erstellung der Referenzdaten liegt zwar ein Zeitraum von 3 Jahren, jedoch wird im besten Fall eine Genauigkeit von 2·7 m ohne manuelle Editierung erreicht. Obwohl einige Aspekte hinsichtlich der Bildqualitat und der Generierung der gegebenen RPCs noch verbessert werden konnten, ist Cartosat-1 ein geeigneter Sensor fur den Einsatz zur Kartierung und besonders fur die Generierung von DOMs. Aufgrund seiner schlechten Absolutgenauigkeit fur die Georeferenzierung kann Cartosat-1 jedoch nicht fur die Generierung eines globalen DOMs ohne Passpunkte eingesetzt werden.

Resumen

El Institute of Geodesy and Photogrammetry (IGP) participa en el programa de evaluacion de Cartosat-1, una iniciativa comun de ISRO (India) y de ISPRS. En dicho programa se han definido varias zonas de estudio con datos de referencia y se han obtenido imagenes de Cartosat-1 de estas areas. En este articulo informamos sobre las investigaciones realizadas en las areas de Roma (Italia) y Maussane-les-Alpilles (Francia). En primer lugar se identifican problemas radiometricos de las imagenes y se describe el preprocesado necesario para resolverlos. Ademas, se muestran ejemplos y metodos de preprocesado para mejorar la calidad de las imagenes con el objetivo especifico de calcular automaticamente un modelo digital de superficie (MDS) con menos errores groseros y mas puntos homologos. A continuacion se describe la georreferenciacion y la exactitud que se puede conseguir en la determinacion de puntos tridimensionales, asi como los problemas relativos a los coeficientes polinomicos racionales (CPR). La georreferenciacion se realizo aplicando varias estrategias en el preprocesado de las imagenes, el modelo matematico de georreferenciacion, el numero y distribucion de los puntos de apoyo terrestres y los metodos de medida de esos puntos en la imagen. Los mejores resultados proporcionaron una exactitud RMSE planimetrica y altimetrica aproximada de 1,3 m. Se sugiere aplicar una transformacion afin despues de los CPR, con unos seis puntos bien distribuidos de apoyo terrestres transferidos mediante correlacion a la segunda imagen. Finalmente se presentan los resultados del calculo automatico de un modelo digital de superficie (MDS) usando nuestro propio programa SAT-PP. Se calcularon varios MDS con una resolucion espacial de 10 m. Los resultados se validaron visualmente y tambien se compararon con los datos de referencia disponibles. En el mejor de los casos, la exactitud obtenida es aproximadamente de 2,7 m sin edicion manual alguna, incluso con una diferencia de tres anos respecto el MDS de referencia. Aunque se podrian mejorar algunos aspectos relativos a la calidad de la imagen y el calculo de los CPR, Cartosat-1 es un sensor muy util para cartografia y especialmente para el calculo de MDS. Sin embargo dada la pobre exactitud absoluta de georreferenciacion, Cartosat-1 no se puede utilizar para el calculo de un MDS global sin puntos de apoyo terrestres.

Analysis of Cartosat‐1 images regarding image quality, 3D point measurement and DSM generation

Calibration and validation of early ALOS/PRISM images (小特集 ALOSの実データを用いた校正・検証)

The Cartographic Institute of Catalonia (ICC) has acquired a DMC digital camera and has performed some first investigations regarding radiometric performance and geometric accuracy potential. In this cooperation with the Institute of Geodesy and Photogrammetry (IGP), ETH Zurich various aspects are analysed. The investigations make use of recent test flights near Tortosa, a plane region with varying landcover. For the quantitative analysis of the DMC results, a ground control points and lidar data exist, which have been simultaneously acquired with the DMC images. The first part of the investigations focusses on geometric sensor modeling and aerial triangulation. Preliminary results of ICC have shown that when standard additional parameters, like the 12 Ebner parameters, are used in AT, significant systematic errors remain and each of the 4 subimages that form the virtual panchromatic image has a different pattern of image deformations. In these investigations, we do not perform analysis of additional parameters in order to model these deformations, as this has been done in another ICC work. The results are analysed using GCPs established in the above mentioned testfield, using two different bundle adjustment programs.. Another part of our investigations regarding AT deals with automatic point transfer using a high quality multi-image, multi-primitive matching method developed at IGP, initially for automatic DSM generation. Different aspects like number, distribution and accuracy of the tie points are analysed, as well number of rays per tie point. The second part of the paper focuses on automatic DSM generation. Although digital cameras offer characteristics, like better image quality, that could be used favourably in automated DSM generation, almost all commercial systems employ matching methods with limitations, like no support of multi-image matching. In these investigations, we briefly introduce the above mentioned IGP multi-image matching and present the matching results. Initial results with other digital cameras and images with large forward and side overlap have shown that this matching approach can produce DSMs at least as dense as those produced by airborne laser scanning and almost as accurate, preserving also very well surface discontinuities. The processing and DSM control was performed by IGP using lidar data provided by ICC, while ICC made an independent control of the aerial triangulation using the software programs at ICC.

/pdf/tests-and-performance-evaluation-of-dmc-images-and-new-cbjd2nv7d3.pdf

Sultan Kocaman

Papers

Analysis of Cartosat‐1 images regarding image quality, 3D point measurement and DSM generation

Calibration and validation of early ALOS/PRISM images (小特集 ALOSの実データを用いた校正・検証)

Tests and performance evaluation of dmc images and new methods for their processing

Flood damage assessment with Sentinel-1 and Sentinel-2 data after Sardoba dam break with GLCM features and Random Forest method.

Self-calibrating triangulation of airborne linear array CCD Cameras