scholarly journals Orthorectification of WorldView-3 Satellite Image Using Airborne Laser Scanning Data

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Biswajeet Pradhan ◽  
Ahmed A. Ahmed ◽  
Subrata Chakraborty ◽  
Abdullah Alamri ◽  
Chang-Wook Lee

Satellite images have been widely used to produce land use and land cover maps and to generate other thematic layers through image processing. However, images acquired by sensors onboard various satellite platforms are affected by a systematic sensor and platform-induced geometry errors, which introduce terrain distortions, especially when the sensor does not point directly at the nadir location of the sensor. To this extent, an automated processing chain of WorldView-3 image orthorectification is presented using rational polynomial coefficient (RPC) model and laser scanning data. The research is aimed at analyzing the effects of varying resolution of the digital surface model (DSM) derived from high-resolution laser scanning data, with a novel orthorectification model. The proposed method is validated on actual data in an urban environment with complex structures. This research suggests that a DSM of 0.31 m spatial resolution is optimum to achieve practical results (root-mean-square error = 0.69   m ) and decreasing the spatial resolution to 20 m leads to poor results (root-mean-square error = 7.17 ). Moreover, orthorectifying WorldView-3 images with freely available digital elevation models from Shuttle Radar Topography Mission (SRTM) (30 m) can result in an RMSE of 7.94 m without correcting the distortions in the building. This research can improve the understanding of appropriate image processing and improve the classification for feature extraction in urban areas.

Author(s):  
Man Sing Wong ◽  
Xiaolin Zhu ◽  
Sawaid Abbas ◽  
Coco Yin Tung Kwok ◽  
Meilian Wang

AbstractApplications of Earth-observational remote sensing are rapidly increasing over urban areas. The latest regime shift from conventional urban development to smart-city development has triggered a rise in smart innovative technologies to complement spatial and temporal information in new urban design models. Remote sensing-based Earth-observations provide critical information to close the gaps between real and virtual models of urban developments. Remote sensing, itself, has rapidly evolved since the launch of the first Earth-observation satellite, Landsat, in 1972. Technological advancements over the years have gradually improved the ground resolution of satellite images, from 80 m in the 1970s to 0.3 m in the 2020s. Apart from the ground resolution, improvements have been made in many other aspects of satellite remote sensing. Also, the method and techniques of information extraction have advanced. However, to understand the latest developments and scope of information extraction, it is important to understand background information and major techniques of image processing. This chapter briefly describes the history of optical remote sensing, the basic operation of satellite image processing, advanced methods of object extraction for modern urban designs, various applications of remote sensing in urban or peri-urban settings, and future satellite missions and directions of urban remote sensing.


2018 ◽  
Vol 48 (6) ◽  
pp. 642-649 ◽  
Author(s):  
Ronald E. McRoberts ◽  
Erik Næsset ◽  
Terje Gobakken ◽  
Gherardo Chirici ◽  
Sonia Condés ◽  
...  

Model-based inference is an alternative to probability-based inference for small areas or remote areas for which probability sampling is difficult. Model-based mean square error estimators incorporate three components: prediction covariance, residual variance, and residual covariance. The latter two components are often considered negligible, particularly for large areas, but no thresholds that justify ignoring them have been reported. The objectives of the study were threefold: (i) to compare analytical and bootstrap estimators of model parameter covariances as the primary factors affecting prediction covariance; (ii) to estimate the contribution of residual variance to overall variance; and (iii) to estimate thresholds for residual spatial correlation that justify ignoring this component. Five datasets were used, three from Europe, one from Africa, and one from North America. The dependent variable was either forest volume or biomass and the independent variables were either Landsat satellite image bands or airborne laser scanning metrics. Three conclusions were noteworthy: (i) analytical estimators of the model parameter covariances tended to be biased; (ii) the effects of residual variance were mostly negligible; and (iii) the effects of spatial correlation on residual covariance vary by multiple factors but decrease with increasing study area size. For study areas greater than 75 km2 in size, residual covariance could generally be ignored.


Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7234
Author(s):  
Manuel A. Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando J. Aguilar

Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05).


2014 ◽  
Vol 889-890 ◽  
pp. 1069-1072
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Hai Yan Wang

Edge detection is the basic problem in the field of image processing. Various image edge detection techniques are introduced. Using various edge detection techniques different images are analyzed and compared by MATLAB7.0. In order to evaluate the effect of edge segmentation, the root mean square error is used. The experimental results show that no an edge detection technique works well for all types of images.


2005 ◽  
Vol 5 ◽  
pp. 65-73 ◽  
Author(s):  
D. Haase ◽  
K. Frotscher

Abstract. Only a few studies have attempted to quantify topography-depending water fluxes, to evaluate retention and reservoir capacities and surface run-off paths within large river basins because data availability and data quality are critical issues to face this objective. It becomes most relevant if water balance has to be calculated in large or transboundary river basins. The advance of space based earth observation data offers a solution to this information problem. Therefore, this paper mainly focuses on weaknesses and strengths analyzing topography with SRTM (Shuttle Radar Topography Mission) digital height data and thus provides techniques for their improved application in river network derivation, floodplain analysis, watershed hydrology in large as well as in large river basins (>1000 km2). In the analysis different types of digital elevation models (DEM), terrain models (DTM) and land cover classification data (biotope map, Corine Land Cover 1994) have been used. The DHMs are generated from Airborne Laser Scanning (0.5 m), topographic maps (10.0/50.0 m) and SRTM at 30.0 m and 90.0 m spatial resolution. SRTM digital height models are generated by Synthetic Aperture Radar (SAR) and show a high spatial variance in urban areas, regions of dense vegetation canopy, floodplains and water bodies. As study area serve the Elbe basin (Czech Republic, Germany) with its sub-basins and the Saale river basin (Germany, different federal countries Saxony-Anhalt, Saxony and Thuringia).


Author(s):  
H. Amini Amirkolaee ◽  
H. Arefi

Abstract. In this paper, a novel approach is proposed for 3D change detection in urban areas using only a single satellite images. To this purpose, a dense convolutional neural network (DCNN) is utilized in order to estimate a digital surface model (DSM) from a single image. In this regard, a densely connected convolutional network is employed for feature extraction and an upsampling method based on dilated convolution is employed for estimating the height values. The proposed DCNN is trained using satellite and Light Detection and Ranging (LiDAR) data which are provided in 2012 from Isfahan, Iran. Subsequently, the trained network is utilized in order to estimate DSM of a single satellite image that is provided in 2006. Finally, the changed areas are detected by subtracting the estimated DSMs. Evaluating the accuracy of the detected changed areas indicates 66.59, 72.90 and 67.90 for correctness, completeness, and kappa, respectively.


Author(s):  
K. Jacobsen

The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height more as by 2-dimensional orientation. The 3-dimensional orientation showed advantages for orientation based on a limited number of GCPs, but in case of poor GCP distribution it may cause also negative effects. For some of the used satellites the bias correction by affinity transformation showed advantages, but for some other the bias correction by shift was leading to a better levelling of the generated height models, even if the root mean square (RMS) differences at the GCPs were larger as for bias correction by affinity transformation. <br><br> The generated height models can be analyzed and corrected with reference height models. For the used data sets accurate reference height models are available, but an analysis and correction with the free of charge available SRTM digital surface model (DSM) or ALOS World 3D (AW3D30) is also possible and leads to similar results. The comparison of the generated height models with the reference DSM shows some height undulations, but the major accuracy influence is caused by tilts of the height models. Some height model undulations reach up to 50&amp;thinsp;% of the ground sampling distance (GSD), this is not negligible but it cannot be seen not so much at the standard deviations of the height. In any case an improvement of the generated height models is possible with reference height models. If such corrections are applied it compensates possible negative effects of the type of bias correction or 2-dimensional orientations against 3-dimensional handling.


2017 ◽  
Vol 66 (1) ◽  
pp. 137-148 ◽  
Author(s):  
Małgorzata Woroszkiewicz ◽  
Ireneusz Ewiak ◽  
Paulina Lulkowska

Abstract The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.


2020 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Moh. Dede ◽  
Millary Agung Widiawaty

Cloud-Based GIS development has been increasing rapidly since the need for big computing for online spatial data. Besides Google Earth Engine, there is actually another Cloud-Based GIS with similar features namely EOS Platform. This study aims to determine the EOS Platform utilization as a Cloud-Based GIS to Analyze Vegetation Greenness in Cirebon Regency, Indonesia. The selection of research location based on the various phenomenon of development in the Cirebon Regency. Vegetation greenness analysis using the NDVI algorithm which available on EOS Processing and Landsat series images are obtained from Land Viewer. Changes in vegetation greenness were analyzed descriptively from NDVI values in two periods at each pixel in the same location. The results of the analysis with the EOS Platform show a decreasing vegetation greenness in the western and peri-urban areas caused by LULC changes. From this analysis, it is proven that EOS Platform can be used for effective and efficient satellite image processing. Even so, some EOS Platform products with BETA version status still show some obstacles related to integration between products.


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