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Special Issue "Satellite Mapping Technology and Application"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (28 February 2014)

Special Issue Editor

Guest Editor
Prof. Dr. Xinming Tang

Satellite Surveying and Mapping Application Center (SASMAC), National Administration of Surveying, Mapping and Geoinformation(NASG), National Geographic Information Technology Industrial Park, Airport East Road, Shunyi, Beijing, China
E-Mail
Fax: +86 10 88187800
Interests: new theory, method and application of remote sensing and geographical information science; Fuzzy Spatial Factor Model; Spatio-Temporal Analysis; key technology of satellite surveying and mapping

Special Issue Information

Dear Colleagues,

Satellite mapping is an important component of modern mapping technology. As one of the representatives of high-precision remote sensing satellites, high-resolution mapping satellites serve as the main driven force for promoting the geo-information industry. Great achievements have been made recently in the construction of earth-observation satellite system, in the post-launch calibration of satellite sensors and in the development of the corresponding data processing techniques, leading to tremendous progress in satellite mapping, resources management, disaster monitoring, and many other application areas. Nowadays, international cooperation becomes more and more frequent, to promote joint construction and sharing of satellite data, products and related technologies, and to explore the international market for satellite data products application and services.
The International Symposium on Satellite Mapping Technology and Application (ISSMTA 2013) will be held in Nanjing, China on 6-8 November 2013. The symposium is hosted by the Secretariat of the United Nations Global Geospatial Information Management (UN-GGIM), International Society for Photogrammetry and Remote Sensing (ISPRS), and National Administration of Surveying, Mapping and Geoinformation (NASG) of China.
The symposium and the proposed special issue aim to focus on satellite mapping technology and application at a number of scales, and will provide a set of papers that will be of great reference for people engaged in the development of satellite mapping technology and application service level. We invite you to submit articles on the following topics:

• Tendency of Satellite Mapping Technology
• System Construction of Earth Observation Satellites
• Application of BeiDou Navigation Satellite System
• Geometric Calibration & Radiometric Correction of Optical Imaging Satellites
• Data Processing Technology of ZY-3 (as well as other Mapping Satellites)
• Application of High-resolution Optical Satellite Imagery
• Strategic Cooperation Mechanism of Satellite Mapping Technology

Dr. Xinming Tang
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs).

Published Papers (7 papers)

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Research

Open AccessArticle Inner FoV Stitching of Spaceborne TDI CCD Images Based on Sensor Geometry and Projection Plane in Object Space
Remote Sens. 2014, 6(7), 6386-6406; doi:10.3390/rs6076386
Received: 28 February 2014 / Revised: 24 June 2014 / Accepted: 25 June 2014 / Published: 8 July 2014
Cited by 3 | PDF Full-text (1280 KB) | HTML Full-text | XML Full-text
Abstract
High-quality inner FoV (Field of View) stitching is currently a prerequisite step for photogrammetric processing and application of image data acquired by spaceborne TDI CCD cameras. After reviewing the technical development in the issue, we present an inner FoV stitching method based on
[...] Read more.
High-quality inner FoV (Field of View) stitching is currently a prerequisite step for photogrammetric processing and application of image data acquired by spaceborne TDI CCD cameras. After reviewing the technical development in the issue, we present an inner FoV stitching method based on sensor geometry and projection plane in object space, in which the geometric sensor model of spaceborne TDI CCD images is used to establish image point correspondence between the stitched image and the TDI CCD images, using an object-space projection plane as the intermediary. In this study, first, the rigorous geometric sensor model of the TDI CCD images is constructed. Second, principle and implementation of the stitching method are described. Third, panchromatic high-resolution (HR) images of ZY-1 02C satellite and triple linear-array images of ZY-3 satellite are utilized to validate the correctness and feasibility of the method. Fourth, the stitching precision and geometric quality of the generated stitched images are evaluated. All the stitched images reached the sub-pixel level in precision. In addition, the geometric models of the stitched images can be constructed with zero loss in geometric precision. Experimental results demonstrate the advantages of the method for having small image distortion when on-orbit geometric calibration of satellite sensors is available. Overall, the new method provide a novel solution for inner FoV stitching of spaceborne TDI CCD images, in which all the sub-images are projected to the object space based on the sensor geometry, performing indirect image geometric rectification along and across the target trajectory. At present, this method has been successfully applied in the daily processing system for ZY-1 02C and ZY-3 satellites. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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Open AccessArticle On-Orbit Geometric Calibration Model and Its Applications for High-Resolution Optical Satellite Imagery
Remote Sens. 2014, 6(5), 4391-4408; doi:10.3390/rs6054391
Received: 13 January 2014 / Revised: 25 April 2014 / Accepted: 4 May 2014 / Published: 14 May 2014
Cited by 19 | PDF Full-text (757 KB) | HTML Full-text | XML Full-text
Abstract
On-orbit geometric calibration is a key technology to guarantee the geometric quality of high-resolution optical satellite imagery. In this paper, we present an approach for the on-orbit geometric calibration of high-resolution optical satellite imagery, focusing on two core problems: constructing an on-orbit geometric
[...] Read more.
On-orbit geometric calibration is a key technology to guarantee the geometric quality of high-resolution optical satellite imagery. In this paper, we present an approach for the on-orbit geometric calibration of high-resolution optical satellite imagery, focusing on two core problems: constructing an on-orbit geometric calibration model and proposing a robust calculation method. First, a rigorous geometric imaging model is constructed based on the analysis of the major error sources. Second, we construct an on-orbit geometric calibration model through performing reasonable optimizing and parameter selection of the rigorous geometric imaging model. On this basis, the calibration parameters are partially calculated with a stepwise iterative method by dividing them into two groups: external and internal calibration parameters. Furthermore, to verify the effectiveness of the proposed calibration model and methodology, on-orbit geometric calibration experiments for ZY1-02C panchromatic camera and ZY-3 three-line array camera are conducted using the reference data of the Songshan calibration test site located in the Henan Province, China. The experimental results demonstrate a certain deviation of the on-orbit calibration result from the initial design values of the calibration parameters. Therefore, on-orbit geometric calibration is necessary for optical satellite imagery. On the other hand, by choosing multiple images, which cover different areas and are acquired at different points in time to verify their geometric accuracy before and after calibration, we find that after on-orbit geometric calibration, the geometric accuracy of these images without ground control points is significantly improved. Additionally, due to the effective elimination of the internal distortion of the camera, greater geometric accuracy was achieved with less ground control points than before calibration. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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Open AccessArticle Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data
Remote Sens. 2014, 6(5), 4409-4429; doi:10.3390/rs6054409
Received: 14 March 2014 / Revised: 21 April 2014 / Accepted: 6 May 2014 / Published: 14 May 2014
Cited by 1 | PDF Full-text (1519 KB) | HTML Full-text | XML Full-text
Abstract
Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3
[...] Read more.
Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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Open AccessArticle Framework of Jitter Detection and Compensation for High Resolution Satellites
Remote Sens. 2014, 6(5), 3944-3964; doi:10.3390/rs6053944
Received: 4 March 2014 / Revised: 8 April 2014 / Accepted: 16 April 2014 / Published: 2 May 2014
Cited by 12 | PDF Full-text (1426 KB) | HTML Full-text | XML Full-text
Abstract
Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution
[...] Read more.
Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1) The first one is based on multispectral images using parallax between two different bands in the image; (2) The second is based on stereo images using rational polynomial coefficients (RPCs); (3) The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1) The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2) The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD) viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer), LRO (Lunar Reconnaissance Orbiter) and ZY-3 (ZiYuan-3) demonstrate the promising performance and feasibility of the proposed framework. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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Open AccessArticle Topographic Correction of ZY-3 Satellite Images and Its Effects on Estimation of Shrub Leaf Biomass in Mountainous Areas
Remote Sens. 2014, 6(4), 2745-2764; doi:10.3390/rs6042745
Received: 27 November 2013 / Revised: 10 March 2014 / Accepted: 13 March 2014 / Published: 26 March 2014
Cited by 9 | PDF Full-text (4291 KB) | HTML Full-text | XML Full-text
Abstract
The availability of ZY-3 satellite data provides additional potential for surveying, mapping, and quantitative studies. Topographic correction, which eliminates the terrain effect caused by the topographic relief, is one of the fundamental steps in data preprocessing for quantitative analysis of vegetation. In this
[...] Read more.
The availability of ZY-3 satellite data provides additional potential for surveying, mapping, and quantitative studies. Topographic correction, which eliminates the terrain effect caused by the topographic relief, is one of the fundamental steps in data preprocessing for quantitative analysis of vegetation. In this paper, we rectified ZY-3 satellite data using five commonly used topographic correction models and investigate their impact on the regression estimation of shrub forest leaf biomass obtained from sample plots in the study area. All the corrections were assessed by means of: (1) visual inspection (2) reduction of the standard deviation (SD) at different terrain slopes (3) correlation analysis of different correction results. Best results were obtained from the Minnaert+SCS correction, based on the non-Lambertian reflection assumption. Additional analysis showed that the coefficient correlation of the biomass fitting result was improved after the Minnaert+SCS correction, as well as the fitting precision. The R2 has increased by 0.113 to reach 0.869, while the SD (standard deviation) of the biomass dropped by 21.2%. Therefore, based on the facts, we conclude that in the region with large topographic relief, the topographical correction is essential to the estimation of the biomass. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
Open AccessArticle Integration of Satellite Imagery, Topography and Human Disturbance Factors Based on Canonical Correspondence Analysis Ordination for Mountain Vegetation Mapping: A Case Study in Yunnan, China
Remote Sens. 2014, 6(2), 1026-1056; doi:10.3390/rs6021026
Received: 27 November 2013 / Revised: 7 January 2014 / Accepted: 10 January 2014 / Published: 27 January 2014
Cited by 3 | PDF Full-text (1367 KB) | HTML Full-text | XML Full-text
Abstract
The integration between vegetation data, human disturbance factors, and geo-spatial data (Digital Elevation Model (DEM) and image data) is a particular challenge for vegetation mapping in mountainous areas. The present study aimed to incorporate the relationships between species distribution (or vegetation spatial distribution
[...] Read more.
The integration between vegetation data, human disturbance factors, and geo-spatial data (Digital Elevation Model (DEM) and image data) is a particular challenge for vegetation mapping in mountainous areas. The present study aimed to incorporate the relationships between species distribution (or vegetation spatial distribution pattern) and topography and human disturbance factors with remote sensing data, to improve the accuracy of mountain vegetation maps. Two different mountainous areas located in Lancang (Mekong) watershed served as study sites. An Artificial Neural Network (ANN) architecture classification was used as image classification protocol. In addition, canonical correspondence analysis (CCA) ordination was applied to address the relationships between topography and human disturbance factors with the spatial distribution of vegetation patterns. We used ordinary kriging at unobserved locations to predict the CCA scores. The CCA ordination results showed that the vegetation spatial distribution patterns are strongly affected by topography and human disturbance factors. The overall accuracy of vegetation classification was significantly improved by incorporating DEM or four CCA axes as additional channels in both the northern and southern study areas. However, there was no significant difference between using DEM or four CCA axes as extra channels in the northern steep mountainous areas because of a strong redundancy between CCA axes and DEM data. In the southern lower mountainous areas, the accuracy was significantly higher using four CCA axes as extra bands, compared to using DEM as an extra band. In the southern study area, the variance of vegetation data explained by human disturbance factors was larger than the variance explained by topographic attributes. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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Open AccessArticle Automatic Registration Method for Fusion of ZY-1-02C Satellite Images
Remote Sens. 2014, 6(1), 157-179; doi:10.3390/rs6010157
Received: 3 November 2013 / Revised: 9 December 2013 / Accepted: 10 December 2013 / Published: 20 December 2013
Cited by 6 | PDF Full-text (4504 KB) | HTML Full-text | XML Full-text
Abstract
Automatic image registration (AIR) has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size
[...] Read more.
Automatic image registration (AIR) has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system. Full article
(This article belongs to the Special Issue Satellite Mapping Technology and Application)
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