H. Topan

Information content of optical satellite images for topographic mapping

Geometric high‐resolution satellite imagery (HRSI) is being used increasingly for generating large‐scale topographic maps. The detection of object shapes has become easier and more accurate with improved geometric resolution. The grey value range and spectral resolution are also important for the identification and classification of objects. The nominal ground sampling distance (GSD) must not be the same as the effective GSD corresponding to the information content. In addition, the topographic conditions, object contrast, sun elevation and azimuth and atmospheric conditions influence the object identification. The information content of panchromatic and multispectral satellite images (Landsat 7 ETM+, ASTER, TK‐350, KVR‐1000, SPOT‐5, IRS‐1C, IKONOS, QuickBird and OrbView‐3) available for the Zonguldak test field were investigated with respect to the generation of large‐scale topographic maps. The rule of thumb for topographic mapping of at least 0.1 mm GSD in the map scale with the limit of a maximum of 5 m GSD also for smaller map scales has been confirmed.

Georeferencing Accuracy Assessment of High-Resolution Satellite Images Using Figure Condition Method

In the case of sensor-independent georeferencing, accuracy of the used model is commonly assessed by misfits separately obtained from ground control points and independent check points. However, applying only this approach has some disadvantages. This paper proposes using the figure condition method to support the common approach. Applying the figure condition process, a more rigorous analysis of accuracy for the used models can be conducted, and one can decide whether the used model is proper or not. In this contribution, a case study is carried out using affine and extended affine models for high-resolution IKONOS Geo, OrbView-3 Basic, and QuickBird OrthoReady Standard images. The results obtained are subjected to the analysis of figure condition.

First Experience with Figure Condition Analysis Aided Bias Compensated Rational Function Model for Georeferencing of High Resolution Satellite Images

Georeferencing of high resolution satellite images using sensor-dependent Rational Function Model (RFM) is a common approach in the remote sensing community since the turn of the millennium. In the case of mono image evaluation, the georeferencing is performed using the ground control points (GCPs), and the image-wide georeferencing accuracy is estimated at the independent check points (ICPs). Nevertheless, such an accuracy assessment approach has some disadvantages and must be overcomed by a proper method as suggested by the figure condition analysis (FCA). Considering various bias compensation methods, the FCA is adopted to RFM and a case study is performed on three high resolution satellite images (HRSIs), IKONOS Geo, QuickBird OrthoReady Standard and OrbView-3 Basic, covering undulating and mountainous Zonguldak test site. The results demonstrate that a bias compensation is required for all images, and IKONOS has the highest accuracy both at GCPs and figure condition points (FCPs) where OrbView-3 has the lowest accuracy. The innovative characteristics of FCA and further research issues are also discussed.

Combined Efficiency of RPC and DEM Accuracy on Georeferencing Accuracy of Orthoimage: Case Study With Pléiades Panchromatic Mono Image

Generation of orthoimages in remote sensing and photogrammetry is a common and sometimes mandatory issue. The desired georeferencing accuracy of the orthoimage depends on two main factors: accuracy of transformation parameters and density and accuracy of height information. The objective of this letter is to estimate the combined efficiency of accuracies of refined rational polynomial coefficients and digital elevation models on georeferencing accuracy of the orthoimage utilizing the figure condition method (FCM). In this letter, details of the method, the characteristics of the evaluated Pléiades panchromatic mono image and auxiliary data, and also the test site are presented. The findings were compared with other results from high-resolution satellite images such as those from IKONOS, QuickBird, and OrbView-3. It is observed that the FCM might be preferred to estimate the overall georeferencing accuracy of an orthoimage, reaching ± 0.3-2.7-pixel accuracy range. The Pléiades panchromatic mono image presents almost equal accuracy as the compared images. The research was carried out on the Zonguldak (Turkey) test site which has mountainous and extremely undulating topography.

GeoEtrim: Geospatial evaluation and training of images

GeoEtrim is a computation package written in Matlab platform having the purpose of geospatial evaluation and training of images. The current version of the software consists of GeoSpot-1.0 and GeoFigcon-1.0 sub-packages. GeoSpot-1.0 performs georeferencing of two SPOT HRG level 1A stereoimages with bundle adjustment, and analyses the efficiency of orientation parameters on the georeferenced coordinates. Mathematical model is a parametric model which considers interior and exterior orientation parameters. The achieved accuracy is ±1 m at GCPs and ±5 m at ICPs, and the interior orientation parameters are more effective than exteriors. GeoFigcon-1.0, the other sub-package, assesses sensor-independent georeferencing accuracy using figure condition method, a more rigorous analysis of accuracy. Current version is available for the mono images of IKONOS Geo, OrbView-3 Basic, and QuickBird OrthoReady Standard via affine projection. The results show the accuracy varies growing from center to edges of images accommodating height of topographic surface. GeoEtrim will be developed by the contribution of researches worldwide.

Mapping Potential of Orbview-3 Panchromatic Image in Mountainous Urban Areas: Results of Zonguldak Test-Field

The objective of this study is to put forth mapping potential of Orbview-3 panchromatic image in Zonguldak test-field. Panchromatic image of Orbview-3 with 1 m GSD (Ground Sampling Distance is selected for the study since OrbView-3 is a new-generation and low-cost high resolution remote sensing satellite). Zonguldak is an important test-field for geometric and semantic analysis of geospatial applications of remote sensing imageries and it is evaluated for DEM (Digital Elevation Model) generation and validation, and information content analysis for topographic mapping. The result of this study is that the information content of OrbView-3 panchromatic imagery is not satisfactory for the generation of 1:5000 scale topographic maps. However, the available information contents are able to support the 1:10000 scale topographic maps production.

Semantic analysis of space imagery for mapping purposes

From the area around Zonguldak several space images with different ground sampling distance (GSD) from 30m down to 62cm are available. The semantic information of Landsat images is too poor for the generation of topographic maps, while QuickBird images do allow a mapping in the scale 1:5000. Not only the GSD is determining the possible map scale, also the spectral and radiometric resolution is important. The imaging conditions, especially the sun elevation with the corresponding length of shadows, do lead to quite different results especially in cities with narrow streets. The possibilities and limitations of mapping with the different space images, partially with the same image type taken in different month, has been analysed.

Pan-sharpening quality investigation of PLÉIADES-1A images

Abstract Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration.

RASAT ve GÖKTÜRK-2 Görüntülerinin Gerçek Yer Örnekleme Aralığının Belirlenmesi

Optik uydu goruntulerinin sundugu konuma bagli bilgi icerigini etkileyen en onemli etkenlerden birisi radyometrik cozunurluktur. Farkli algilayicilarla elde edilen goruntuler ayni geometrik ve spektral cozunurluge sahip olsalar bile eger radyometrik cozunurlukleri farkli ise bu goruntulerden elde edilecek bilginin niteligi farklilik gosterecektir. Hatta ayni radyometrik cozunurluge sahip olsalar dahi, bazen goruntuler geometrik cozunurlugu arttirilarak (yani yer ornekleme araligi kucultulerek) kullaniciya sunulmaktadir. Bu durumda goruntunun gercek yer ornekleme araliginin belirlenmesi uygun olacaktir. Gercek yer ornekleme araliginin belirlenebilmesi icin Matlab ortaminda epix adi verilen bir yazilim gelistirilmistir. Yazilim, goruntulerdeki duzgun bina kenarlarinin golgeleri ile cati dokusu arasindaki gri deger gecislerinin ortalamasini alarak, aralarindaki farklari belirler ve boylece kenar yayilim fonksiyonu ilkesine bagli olarak goruntulerin gercek yer ornekleme araligini hesaplar. epix yazilimi goruntu uzerinden kenar belirleme islemini Canny operatoru yardimi ile gerceklestirmektedir. Orijinal goruntu ve Canny operatoru araciligi ile uretilen kenarlar cakistirilarak kullanicinin daha kolay kenar belirlemesi saglanmistir. Uygulama, RASAT ve GOKTURK-2 uydu goruntuleri ile gerceklestirilmistir. Yapilan arastirmada goruntulerin gercek geometrik cozunurlugu yaklasik olarak 1 piksel olarak bulunmustur. Dolayisiyla bu goruntuler normal yer ornekleme araligi ile kullanilabilmektedir.

A generic point error model for TLS derived point clouds

This work aims at developing a generic and anisotropic point error model, which is capable of computing magnitude and direction of a priori random errors, described in the form of error ellipsoids for each individual point of the cloud. The direct TLS observations are the range (ρ), vertical (α) and horizontal (θ) angles, each of which is in fact associated with a priori precision value. A practical methodology was designed and performed in real-world test environments to determine these precision values. The methodology has two experimental parts. The first part is a static and repetitive measurement configuration for the determination of a priori precisions of the vertical (σα) and horizontal (σθ) angles. The second part is the measurement of a test stand which contains four plates in white, light grey, dark grey and black colors, for the determination of a priori precisions of the range observations (σρ). The test stand measurement is performed in a recursive manner so that sensor-to-object distance, incidence angle and surface reflectivity are parameterized. The experiment was conducted with three TLSs, namely Faro Focus 3D X330, Riegl VZ400 and Z+F 5010x in the same location and atmospheric conditions. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. Validation of the proposed error model was performed in real world scenarios, which revealed feasibility of the model.