Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

baltsavias, emmanuel p.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: TECHNICAL SESSION 4 FUSION OF SENSOR-DERIVED PRODUCTS

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: STRATEGIES AND METHODS FOR THE FUSION OF DIGITAL ELEVATION MODELS FROM OPTICAL AND SAR DATA. M. Honikel

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 5.2. Data processing The DEMs have been processed with commercial software packages. The SPOT DEMs are part of the DEM of the full scene, which has been generated by the Leica Helava DPW 770 digital photogrammetric workstation, which uses cross correlation for point matching. The correlation coefficient of each DEM is not output directly, but is hidden behind a figure of merit (FOM). This FOM is scaled in a range from 0 to 100 and is directly proportional to the correlation coefficient (Leica Helava, 1997). Height values below a FOM threshold of 33 are generally considered unreliable. Although the images were taken in a four-day interval, the SPOT data had to be enhanced by filtering. Further details of the SPOT pre-processing and the accuracy of the full scene DEM are given in (Patias, 1998). The InSAR DEM has been generated with the PCI IFSAR package. IFSAR offers both the LS and tree algorithms for phase unwrapping, but as the tree algorithm failed for test site 2 and delivered the same RMS in site 1, LS has been applied to both regions, to keep the results comparable. Due to lack of ground control points (GCPs) in both areas, 5 GCPs had to be derived from the reference DEM for geocoding and baseline fitting. Baseline fitting has been performed by a technique proposed by Werner (1992). The amount of GCPs reduced remarkably the systematic error in the InSAR DEMs in comparison to earlier results with less GCPs (Honikel, 1998). 6. RESULTS The SPOT and ERS DEMs have been compared to ground truth by bilinear interpolation of each height value in the reference DEM. All referred errors are absolute errors, unless something different is stated. Detailed investigations of the influence of the crop height on the measurements have not been carried out. Still, the fact that the signed average is larger in site 2 and negative indicates a bias between the tree canopies, measured in the DEMs, and the reference data derived from contour lines (see 5.1). The InSAR and stereo DEMs are very typical in both test sites. While InSAR performs well in test site 1, where it reaches a very good RMS error of 4.8m, while the RMS error drops in the presence of steeper slopes of test site 2 to 14.9m (Tab. 2). This behaviour proves the strong InSAR dependence on the coherence in general and especially on terrain slopes, as coherence in test site 2 is lower than in test site 1. In contrast to SPOT DEMs, where outliers of more than 90m occur in both sites, such extreme errors do not occur in the InSAR DEMs, where maximum errors of 24m and 63m arise. The reasons for this performance are the smooth terrain solution of LS unwrapping and the height interpolation during the ground range conversion process. Although outliers are avoided in InSAR DEMs, the amount of errors greater than 20m is significantly higher in test site 2, where InSAR performs worse, than in the SPOT case of test site 1. This is due to the fact, that LS unwrapping is capable to bridge only limited areas, but fails to recover large decorrelated areas. The SPOT stereo DEM performs robustly in both test sites. The RMS in both types of terrain differs only by 1.4m. Also, the correlation coefficient of test site 1 is with 0.7 a little higher than that of site 2 (0.66), proving that accuracy follows the correlation value also in the optical case. The robust performance is also underlined by the amount of height deviations greater than 20m. In test site 1, only 1.9% of all values showed such an error, in test site 2, 4.3%. In both cases almost all height errors (more than 99%) are below 40m. As a conclusion, stereo DEM errors are in part extremely high, but appear very localised and affect only their direct neighbours (Fig. 4). As expected, the correlation coefficient shows the same behaviour (Fig. 3). Due to the relatively short repeat pass interval of both sensors and the applied pre-processing, the mean correlation coefficient is relatively high with values between 0.54 and 0.7 for both sites and sensors. The cross-correlation shows distinct patterns for both sensors. While it follows closely the shape of the terrain in the SAR case, decreasing at the flanks of the hills and thus varying regionally, it shows extreme local variations in the optical case, where the correlation is corrupted at various spots. As the low correlation values appear in different locations in both InSAR and stereo-optical DEMs, the DEMs can be used complementarily by the proposed fusion process, which is demonstrated in the results of the fused DEMs. DEM Test site 1 Test site 2 InSAR (ERS-1) Signed average: 1.0m Average: 3.7m RMS: 4.7m Correlation: 0.61 Signed average: -2.9m Average: 11.3m RMS: 14.9 Correlation: 0.54 Stereo-optical (SPOT) Signed average: 1.9m Average: 6.0m RMS: 7.9m Correlation: 0.7 Signed average: -2.3m Average: 6.8m RMS: 9.3 Correlation: 0.66 Fused Signed average: 1,4m Average: 3.2m RMS: 4.0m Signed average: -2.2m Average: 4.9m RMS: 6.5m Table 2. Single sensor and fused DEM errors (reference DEM - generated DEM). The RMS decreased after the data fusion in both test sites. In test site 1, the RMS dropped to 4.0m after the fusion, a decrease of 16% compared to the ERS and of 49% compared to the SPOT DEM. In test site 2, the RMS dropped to 6.5m, a decrease of 30% compared to the SPOT case and 56 % to the ERS case (Tab. 2). The fact that no error greater than 20m occurs in test site 1 proves the error sensitivity of the fusion procedure (Tab. 3). The partially extreme outliers of the SPOT DEM are completely rejected (Fig. 5) and only less erroneous values are fused with the very accurate InSAR DEM of test site 1.

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