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Satellite and Airborne Remote Sensing for Earth Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (20 November 2018) | Viewed by 20330

Special Issue Editor

Department of Geography, University of Victoria, BC V8P 5C2, Canada
Interests: mutisensor payloads; high spatial and spectral resolution imaging; UAV; airborne; hyperspectral; LiDAR

Special Issue Information

Dear Colleagues,

Earth observation, through the use of airborne and satellite derived data, has undergone an unprecedented evolution over the past few years. We have experienced a growth in the number and sophistication of missions involving space-borne platforms through the national (NASA, DLR, CSA for example) and super-national (ESA) space agency programmes, and their overarching Earth observing initiatives (NASA- Decadal Survey, ESA-Copernicus, to name two). In concert with these initiatives, we have experienced a technological revolution in sensor design that has led to deploying a large array of instruments that sense and record multiple facets of the Earth surface and near-surface processes. This sensor revolution has allowed us to acquire high spatial and spectral resolution data throughout the VIS-NIR-SWIR, Thermal, and Microwave portions of the spectrum from space-borne to smaller airborne platforms culminating in UAV-based sensor payloads. Smaller instrument packages also allow us to introduce multiple sensors to collect contemporaneous, complimentary data.

The range of spatial resolutions offered by the spectrum of airborne to space-borne platforms offer unique challenges for analysts. Issues such as high accuracy absolute positioning for multi-temporal and multi-sensor data, pixel/spectrum mixing, and the influence of leaf angle on spectral reflectance are, for example, just a few of the factors that need to be considered when comparing data from the different platforms.

This Special Issue is aimed exploring some of the experiences that researchers have encountered in acquiring, pre-processing and data preparation, and information/feature extraction. We welcome manuscripts that describe work related to the application of a full range of sensors as applied to Earth observation and monitoring.

Prof. Dr. Olaf Niemann
Guest Editor

Manuscript Submission Information

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Keywords

  • Mutisensor payloads
  • high spatial and spectral resolution
  • UAV
  • Airborne
  • Spaceborne
  • Earth observation

Published Papers (5 papers)

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Research

21 pages, 2358 KiB  
Article
Application of a Multi-Satellite Dynamic Mission Scheduling Model Based on Mission Priority in Emergency Response
by Jintian Cui and Xin Zhang
Sensors 2019, 19(6), 1430; https://doi.org/10.3390/s19061430 - 23 Mar 2019
Cited by 26 | Viewed by 3548
Abstract
Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem [...] Read more.
Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem of Earth observation satellites under emergency conditions, a multi-satellite dynamic mission scheduling model based on mission priority is proposed in this paper. A calculation model of mission priority is designed for emergency missions based on seven impact factors. In the satellite mission scheduling, the resource constraints of scheduling are analyzed in detail, and the optimization objective function is built to maximize the observation mission priority and mission revenues, and minimize the waiting time for missions that require urgency for execution time. Then, the hybrid genetic tabu search algorithm is used to obtain the initial satellite scheduling plan. In case of the dynamic arrival of new emergency missions before scheduling plan releases, a dynamic scheduling algorithm based on mission priority is proposed to solve the scheduling problem caused by newly arrived missions and to obtain the scheduling plan of newly arrived missions. A simulation experiment was conducted for different numbers of initial missions and newly arrived missions, and the scheduling results were evaluated with a model performance evaluation function. The results show that the execution probability of high-priority missions increased because the mission priority was taken into account in the model. In the case of more satellite resources, when new missions dynamically arrived, the satellite resources can be reasonably allocated to these missions based on the mission priority. Overall, this approach reduces the complexity of the dynamic adjustment and maintains the stability of the initial scheduling plan. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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29 pages, 7636 KiB  
Article
Optimization of Reconfigurable Satellite Constellations Using Simulated Annealing and Genetic Algorithm
by Sung Wook Paek, Sangtae Kim and Olivier de Weck
Sensors 2019, 19(4), 765; https://doi.org/10.3390/s19040765 - 13 Feb 2019
Cited by 48 | Viewed by 6390
Abstract
Agile Earth observation can be achieved with responsiveness in satellite launches, sensor pointing, or orbit reconfiguration. This study presents a framework for designing reconfigurable satellite constellations capable of both regular Earth observation and disaster monitoring. These observation modes are termed global observation mode [...] Read more.
Agile Earth observation can be achieved with responsiveness in satellite launches, sensor pointing, or orbit reconfiguration. This study presents a framework for designing reconfigurable satellite constellations capable of both regular Earth observation and disaster monitoring. These observation modes are termed global observation mode and regional observation mode, constituting a reconfigurable satellite constellation (ReCon). Systems engineering approaches are employed to formulate this multidisciplinary problem of co-optimizing satellite design and orbits. Two heuristic methods, simulated annealing (SA) and genetic algorithm (GA), are widely used for discrete combinatorial problems and therefore used in this study to benchmark against a gradient-based method. Point-based SA performed similar or slightly better than the gradient-based method, whereas population-based GA outperformed the other two. The resultant ReCon satellite design is physically feasible and offers performance-to-cost(mass) superior to static constellations. Ongoing research on observation scheduling and constellation management will extend the ReCon applications to radar imaging and radio occultation beyond visible wavelengths and nearby spectrums. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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11 pages, 2531 KiB  
Article
Space-Based Focal Plane Ambiguous Measurement Ballistic Target MeMber Tracking
by Wei Zhao, Shucai Huang and Wenhuan Cao
Sensors 2018, 18(11), 3996; https://doi.org/10.3390/s18113996 - 16 Nov 2018
Cited by 1 | Viewed by 2291
Abstract
Aimed at space-based passive detection and tracking of ballistic targets, a multi-target multi-Bernoulli (MeMber) filtering algorithm based on a focal plane ambiguous measurement model is proposed. The measurement error sources of space-based passive detection are analyzed. It is found that focal plane target [...] Read more.
Aimed at space-based passive detection and tracking of ballistic targets, a multi-target multi-Bernoulli (MeMber) filtering algorithm based on a focal plane ambiguous measurement model is proposed. The measurement error sources of space-based passive detection are analyzed. It is found that focal plane target tracking is the basis of space target tracking in the framework of the distributed data processing structure, and the main error of focal plane measurement is pixel resolution. Based on the above analysis, the focal plane ambiguous measurement model is established to replace the traditional measurement model and the generalized likelihood function is designed. Finally, the MeMber filter is modified based on ambiguous measurement and generalized likelihood function. The simulation experiment compares the tracking effect of a MeMber filter based on ambiguous measurement and traditional measurement, respectively. The filter based on ambiguous measurement achieves better results. It shows that ambiguous measurement is closer to reality and has more application value. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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27 pages, 13277 KiB  
Article
Structured Background Modeling for Hyperspectral Anomaly Detection
by Fei Li, Lei Zhang, Xiuwei Zhang, Yanjia Chen, Dongmei Jiang, Genping Zhao and Yanning Zhang
Sensors 2018, 18(9), 3137; https://doi.org/10.3390/s18093137 - 17 Sep 2018
Cited by 3 | Viewed by 2842
Abstract
Background modeling has been proven to be a promising method of hyperspectral anomaly detection. However, due to the cluttered imaging scene, modeling the background of an hyperspectral image (HSI) is often challenging. To mitigate this problem, we propose a novel structured background modeling-based [...] Read more.
Background modeling has been proven to be a promising method of hyperspectral anomaly detection. However, due to the cluttered imaging scene, modeling the background of an hyperspectral image (HSI) is often challenging. To mitigate this problem, we propose a novel structured background modeling-based hyperspectral anomaly detection method, which clearly improves the detection accuracy through exploiting the block-diagonal structure of the background. Specifically, to conveniently model the multi-mode characteristics of background, we divide the full-band patches in an HSI into different background clusters according to their spatial-spectral features. A spatial-spectral background dictionary is then learned for each cluster with a principal component analysis (PCA) learning scheme. When being represented onto those dictionaries, the background often exhibits a block-diagonal structure, while the anomalous target shows a sparse structure. In light of such an observation, we develop a low-rank representation based anomaly detection framework that can appropriately separate the sparse anomaly from the block-diagonal background. To optimize this framework effectively, we adopt the standard alternating direction method of multipliers (ADMM) algorithm. With extensive experiments on both synthetic and real-world datasets, the proposed method achieves an obvious improvement in detection accuracy, compared with several state-of-the-art hyperspectral anomaly detection methods. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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14 pages, 1439 KiB  
Article
A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images
by Libo Yao, Yong Liu and You He
Sensors 2018, 18(7), 2007; https://doi.org/10.3390/s18072007 - 22 Jun 2018
Cited by 23 | Viewed by 4167
Abstract
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In [...] Read more.
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
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