scholarly journals Orthorectification of KOMPSAT Optical Images Using Various Ground Reference Data and Accuracy Assessment

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Kwangjae Lee ◽  
Eunseon Kim ◽  
Younsoo Kim
Keyword(s):  
High Resolution ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Open Data ◽  
Shuttle Radar Topography Mission ◽  
Image Correction ◽  
Optical Images ◽  
Common Location ◽  
Rational Polynomial ◽  
High Resolution Satellite Images

Along with the appearance of high resolution satellite images, image correction using Rational Polynomial Coefficients (RPCs) has become common. Location accuracy of Korea Multipurpose Satellite (KOMPSAT) standard images is still not adequate, so, in order to leverage the KOMPSAT images for applications such as mapping and change detection, it is necessary to orthorectify the images. In this study, using updated RPCs, we performed orthorectification of KOMPSAT-2, KOMPSAT-3, and KOMPSAT-3A images using various data. Through this study, we discovered that the orthorectification result using precise Ground Control Points (GCPs) and Digital Elevation Model (DEM) is the best, but it was found that the correction results through image matching are also excellent. In particular, it was confirmed that orthoimages with a planimetric accuracy around 3 m (Root Mean Square Error (RMSE)) can be generated by using well-known matching algorithms with open data such as OpenStreetMap (OSM) and Shuttle Radar Topography Mission (SRTM) DEM, which can be acquired by anyone. Although the accuracy was low in some mountainous terrain, it was confirmed that it could be used for generating KOMPSAT orthoimages using open data. This paper describes the results for orthorectifying high resolution KOMPSAT optical images using various reference data.

scholarly journals Geomorpho90m - Global high-resolution geomorphometry layers: empirical evaluation and accuracy assessment

2019 ◽  
Author(s):  
Giuseppe Amatulli ◽  
Daniel McInerney ◽  
Tushar Sethi ◽  
Peter Strobl ◽  
Sami Domisch
Keyword(s):  
High Resolution ◽  
Accuracy Assessment ◽  
Empirical Evaluation ◽  
Shuttle Radar Topography Mission ◽  
The United States ◽  
Rate Of Change ◽  
Environmental Models ◽  
Digital Elevation ◽  
The Difference ◽  
Elevation Model

Topographical relief is composed of the vertical and horizontal variations of the Earth's terrain and drives processes in geography, climatology, hydrology, and ecology. Its assessment and characterisation is fundamental for various types of modelling and simulation analyses. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) is the best global, high-resolution DEM currently available at a 3 arc-seconds (90 m) resolution. This is an improved product as multiple error components have been corrected from the underlying Shuttle Radar Topography Mission (SRTM3) and ALOS World 3D - 30 m (AW3D30) DEMs. To depict topographical variations worldwide, we developed the Geomorpho90m dataset comprising of different geomorphometry features derived from the MERIT-DEM. The fully standardised geomorphometry variables consist of layers that describe (i) the rate of change using the first and second order derivatives, (ii) the ruggedness, and (iii) the geomorphology landform. To assess how remaining artefacts in the MERIT-DEM could affect the derived topographic variables, we compared our results with the same variables generated using the 3D Elevation Program (3DEP) DEM, which is the highest quality DEM for the United States of America. We compared the two data sources by calculating the first order derivative (i.e., the rate of change through space measured in degrees) of the difference between a MERIT-derived vs. a 3DEP-derived topographic variable. All newly-created topographic variables are readily available at resolutions of 3 and 7.5 arc-seconds under the WGS84 geographic system, and at a spatial resolution of 100 m under the Equi7 projection. The newly-developed Geomorpho90m dataset provides a globally standardised dataset for environmental models and analyses in the field of geography, geology, hydrology, ecology and biogeography.

scholarly journals PHOTOGRAMMETRIC PROCESSING USING ZY-3 SATELLITE IMAGERY

2015 ◽  
Vol XL-3/W2 ◽  
pp. 109-113 ◽  
Author(s):  
W. Kornus ◽  
A. Magariños ◽  
M. Pla ◽  
E. Soler ◽  
F. Perez
Keyword(s):  
High Resolution ◽  
Level Of Detail ◽  
Multispectral Image ◽  
Stereoscopic Vision ◽  
Surface Model ◽  
Pixel Size ◽  
Image Correction ◽  
North West ◽  
Polynomial Coefficients ◽  
Rational Polynomial

This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. <br><br> All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are detected covering an area of 4691ha, corresponding to less than 2% of the imaged area. Most of the artifacts are caused by clouds (4614ha). A minor part (77ha) is affected by colour patch, stripping or blooming effects. <br><br> For the final qualitative analysis on the usability of the ZY-3 imagery for stereo plotting purposes stereo combinations of the nadir and an oblique image are discarded, mainly due to the different pixel size, which produces difficulties in the stereoscopic vision and poor accuracy in positioning and measuring. With the two oblique images a level of detail equivalent to 1:25.000 scale is achieved for transport network, hydrography, vegetation and elements to model the terrain as break lines. For settlement, including buildings and other constructions a lower level of detail is achieved equivalent to 1:50.000 scale.

scholarly journals Sensor-Level Mosaic of Multistrip KOMPSAT-3 Level 1R Products

2021 ◽  
Vol 11 (15) ◽  
pp. 6796
Author(s):  
Changno Lee ◽  
Jaehong Oh
Keyword(s):  
High Resolution ◽  
Focal Length ◽  
Image Data ◽  
Shuttle Radar Topography Mission ◽  
Reference Image ◽  
Geospatial Information ◽  
Sensor Model ◽  
High Resolution Satellite Images ◽  
Inaccessible Area ◽  
Sensor Modeling

High-resolution satellite images such as KOMPSAT-3 data provide detailed geospatial information over interest areas that are evenly located in an inaccessible area. The high-resolution satellite cameras are designed with a long focal length and a narrow field of view to increase spatial resolution. Thus, images show relatively narrow swath widths (10–15 km) compared to dozens or hundreds of kilometers in mid-/low-resolution satellite data. Therefore, users often face obstacles to orthorectify and mosaic a bundle of delivered images to create a complete image map. With a single mosaicked image at the sensor level delivered only with radiometric correction, users can process and manage simplified data more efficiently. Thus, we propose sensor-level mosaicking to generate a seamless image product with geometric accuracy to meet mapping requirements. Among adjacent image data with some overlaps, one image is the reference, whereas the others are projected using the sensor model information with shuttle radar topography mission. In the overlapped area, the geometric discrepancy between the data is modeled in spline along the image line based on image matching with outlier removals. The new sensor model information for the mosaicked image is generated by extending that of the reference image. Three strips of KOMPSAT-3 data were tested for the experiment. The data showed that irregular image discrepancies between the adjacent data were observed along the image line. This indicated that the proposed method successfully identified and removed these discrepancies. Additionally, sensor modeling information of the resulted mosaic could be improved by using the averaging effects of input data.

scholarly journals Satellite remote sensing approaches and field measurements to tracking coastline changes of the Sambia peninsula

2018 ◽  
Vol 14 (3) ◽  
pp. 15-24
Author(s):  
Natalia A. Bryksina ◽  
Dzhuraboy T. Fidaev ◽  
Vitaliy M. Bryksin
Keyword(s):  
High Resolution ◽  
Coastal Zone ◽  
Satellite Images ◽  
Field Measurements ◽  
Remote Measurement ◽  
Short Term ◽  
Optical Images ◽  
High Resolution Satellite Images ◽  
Spatio Temporal ◽  
Coastal Boundary

The purpose of this work is to assess the accuracy of measuring the coastal boundary of the sea on optical images for the study of the short-term dynamics of the coastal zone of the Sambian Peninsula and its development trends using high-resolution and ultra-high resolution satellite images. The methodological issues of studying the dynamics of the coastal zone of the Sambian Peninsula using ground data and optical images of high and ultra-high resolution are considered. The estimation of the measurement error of the coastline on satellite images by comparison with the data of ground-based measurements of the coordinates of the coastline was carried out. It has been established that remote measurement of the coastal boundary of the sea using optical images is possible with an error not exceeding a few meters. It is shown that Change Detection is used to detect spatio-temporal changes in the coastal zone in multi-time images. Analysis of the quantitative assessment of changes in the area of erosion and accumulative sites on the coast of the Sambian Peninsula over the study period 2010-2017. Showed the prevalence of abrasion processes over accumulative, which is also confirmed by ground-based observations in the survey of the coastal zone after the storm in the period 2012-2017. It has been established that in most of the peninsula, over 5 years, the tendency for the coastline to recede towards the coast from 6 to 36 m on average prevails.

scholarly journals RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 579-586 ◽  
Author(s):  
K. Gong ◽  
D. Fritsch
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Satellite Image ◽  
Relative Orientation ◽  
Ground Control ◽  
Surface Model ◽  
Control Information ◽  
Rational Polynomial ◽  
High Resolution Satellite Images ◽  
Resampling Method

High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM) generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs) provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM) method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

scholarly journals Geomorpho90m - Global high-resolution geomorphometry layers: empirical evaluation and accuracy assessment

2019 ◽  
Author(s):  
Giuseppe Amatulli ◽  
Daniel McInerney ◽  
Tushar Sethi ◽  
Peter Strobl ◽  
Sami Domisch
Keyword(s):  
High Resolution ◽  
Accuracy Assessment ◽  
Empirical Evaluation ◽  
Shuttle Radar Topography Mission ◽  
The United States ◽  
Rate Of Change ◽  
Environmental Models ◽  
Digital Elevation ◽  
The Difference ◽  
Elevation Model

Topographical relief is composed of the vertical and horizontal variations of the Earth's terrain and drives processes in geography, climatology, hydrology, and ecology. Its assessment and characterisation is fundamental for various types of modelling and simulation analyses. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) is the best global, high-resolution DEM currently available at a 3 arc-seconds (90 m) resolution. This is an improved product as multiple error components have been corrected from the underlying Shuttle Radar Topography Mission (SRTM3) and ALOS World 3D - 30 m (AW3D30) DEMs. To depict topographical variations worldwide, we developed the Geomorpho90m dataset comprising of different geomorphometry features derived from the MERIT-DEM. The fully standardised geomorphometry variables consist of layers that describe (i) the rate of change using the first and second order derivatives, (ii) the ruggedness, and (iii) the geomorphology landform. To assess how remaining artefacts in the MERIT-DEM could affect the derived topographic variables, we compared our results with the same variables generated using the 3D Elevation Program (3DEP) DEM, which is the highest quality DEM for the United States of America. We compared the two data sources by calculating the first order derivative (i.e., the rate of change through space measured in degrees) of the difference between a MERIT-derived vs. a 3DEP-derived topographic variable. All newly-created topographic variables are readily available at resolutions of 3 and 7.5 arc-seconds under the WGS84 geographic system, and at a spatial resolution of 100 m under the Equi7 projection. The newly-developed Geomorpho90m dataset provides a globally standardised dataset for environmental models and analyses in the field of geography, geology, hydrology, ecology and biogeography.

Evaluation of automated feature extraction algorithms using high-resolution satellite imagery across a rural-urban gradient in two unique cities in developing countries

2021 ◽  
Author(s):  
Andrew Griffin ◽  
Sean Griffin ◽  
Kristofer Lasko ◽  
Megan Maloney ◽  
S. Blundell ◽  
...  
Keyword(s):  
Developing Countries ◽  
Feature Extraction ◽  
High Resolution ◽  
Satellite Imagery ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Network Connectivity ◽  
Automated Feature Extraction ◽  
Before And After ◽  
High Resolution Satellite Imagery

Feature extraction algorithms are routinely leveraged to extract building footprints and road networks into vector format. When used in conjunction with high resolution remotely sensed imagery, machine learning enables the automation of such feature extraction workflows. However, many of the feature extraction algorithms currently available have not been thoroughly evaluated in a scientific manner within complex terrain such as the cities of developing countries. This report details the performance of three automated feature extraction (AFE) datasets: Ecopia, Tier 1, and Tier 2, at extracting building footprints and roads from high resolution satellite imagery as compared to manual digitization of the same areas. To avoid environmental bias, this assessment was done in two different regions of the world: Maracay, Venezuela and Niamey, Niger. High, medium, and low urban density sites are compared between regions. We quantify the accuracy of the data and time needed to correct the three AFE datasets against hand digitized reference data across ninety tiles in each city, selected by stratified random sampling. Within each tile, the reference data was compared against the three AFE datasets, both before and after analyst editing, using the accuracy assessment metrics of Intersection over Union and F1 Score for buildings and roads, as well as Average Path Length Similarity (APLS) to measure road network connectivity. It was found that of the three AFE tested, the Ecopia data most frequently outperformed the other AFE in accuracy and reduced the time needed for editing.

scholarly journals Η συμβολή των δορυφορικών πολυφασματικών εικόνων στη Γεωμορφολογία, από τη δεκαετία του 70 (δορυφόροι LANDSAT) μέχρι σήμερα (δορυφόροι IKONOS, QuickBird). Παραδείγματα από την Ελλάδα.

2005 ◽  
Vol 38 ◽  
pp. 157
Author(s):  
Θ. ΑΣΤΑΡΑΣ ◽  
Δ. ΟΙΚΟΝΟΜΙΔΗΣ ◽  
Α. ΜΟΥΡΑΤΙΔΗΣ
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Shuttle Radar Topography Mission ◽  
Aerial Photographs ◽  
Medium Resolution ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Multispectral Satellite Images ◽  
Geomorphological Units ◽  
Land Systems

This paper describes initially the availability of multispectral satellite images, from the launch of the first Earth Resources Satellites (Landsat series), with medium resolution capabilities (80m), to the launch of the contemporary satellites (QuickBird, 2001), with very high resolution capabilities (60cm). It reviews researches, concerning the visual and digital image analyses of the LANDSAT series, SPOT, 1RS, TERRA and QuickBird satellite images that have been carried out during the last 20 years in the Department of Physical and Environmental Geography, School of Geology, Aristotle University of Thessaloniki. These researches are of geomorphological-geological interest and involve applications in various areas of Greece. In particular, practical examples are provided, concerning the detection and delineation of landslides in Macedonia and Epirus Provinces, the detection and classification of geomorphological units (land systems) in Peloponnesos, Thrace, Macedonia and Santorini areas and the analysis of drainage network in Central Macedonia Province with emphasis in the delineation of severe erosional phenomena. Reason for this review paper, is the contemporary use of Digital Elevation Models (DEMs) with 10-30 m accuracy, from the Shuttle Radar Topography Mission (SRTM / 2000) and their contribution, along with the high resolution satellite images, (from TERRA, QuickBird, etc), in the 3-D visualization of the Earths' relief. In particular, the use of 3-D satellite images will assist geoscientists and especially geomorphologists, to study the Earths' relief and its' evolution, more quickly, with better accuracy and at lower cost, compared with aerial photographs and 2-D satellite images, which have been used during the last 20 years.

scholarly journals Accuracy Assessment of the FROM-GLC30 Land Cover Dataset Based on Watershed Sampling Units: A Continental-Scale Study

2020 ◽  
Vol 12 (20) ◽  
pp. 8435
Author(s):  
Zitian Guo ◽  
Chunmei Wang ◽  
Xin Liu ◽  
Guowei Pang ◽  
Mengyang Zhu ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Large Scale ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Visual Interpretation ◽  
Land Cover Types ◽  
Practical Applications ◽  
Land Type ◽  
Continental Scale

Land cover information plays an essential role in the study of global surface change. Multiple land cover datasets have been produced to meet various application needs. The FROM-GLC30 (Finer Resolution Observation and Monitoring of Global Land Cover) dataset is one of the latest land cover products with a resolution of 30 m, which is a relatively high resolution among global public datasets, and the accuracy of this dataset is of great concern in many related researches. The objective of this study was to calculate the accuracy of the FROM-GLC30 2017 dataset at the continental scale and to explore the spatial variation differences of each land type accuracy in different regions. In this study, the visual interpretation land cover results at 20,936 small watershed sampling units based on high-resolution remote sensing images were used as the reference data covering 65 countries in Asia, Europe, and Africa. The reference data were verified by field survey in typical watersheds. Based on that, the accuracy assessment of the FROM-GLC30 2017 dataset was carried out. The results showed (1) the area proportion of different land cover types in the FROM-GLC30 2017 dataset was generally consistent with that of the reference data. (2) The overall accuracy of the FROM-GLC30 2017 dataset was 72.78%, and was highest in West Asia–Northeast Africa, and lowest in South Asia. (3) Among all the seven land cover types, the accuracy of bareland and forest was relatively higher than that of others, and the accuracy of shrubland was the lowest. The accuracy for each land cover type differed among regions. The results of this work can provide useful information for land cover accuracy assessment researches at a large scale and promote the further practical applications of the open-source land cover datasets.

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