GEO Objects Research Articles

Multi-frame temporal dense nested attention method for detecting GEO objects

The geostationary orbit is a special and important spatial orbital resource. However, space resident objects in this orbit pose potential threats to space security, characterized as dim and small targets in imaging features. To solve the problem of detecting dim and small targets in geostationary orbit, we propose a multi-frame temporal dense nested attention method, which consists of a uniform linear motion constraint module and a dense nested attention module. The dense nested attention module adopts a multi-layer U-shaped structure and channel spatial attention mechanism, which can preserve the deep features of small targets, extract and fuse features from different scales of feature maps, and finally obtain the preliminary detection results of single-frame images. The uniform linear motion constraint module uses the prior information of the target motion in the image sequence, removes false positives and supplements false negatives, and improves the detection performance. Experiments were conducted on the SpotGEO dataset publicly released by the European Space Agency. The results of our experiments indicate that our method outperforms the state-of-the-art approach, showing a 12.83% reduction in Mean Squared Error compared to the current leading method. Our method, characterized by its minimal parameter requirement and independence from extensive dataset pre-training, is ideally suited for integration into small satellite devices, enabling efficient monitoring and mitigation of resident space objects.

Методика инвентаризации объектов геологического наследия как инструмент управления геопарками

Using the example of the UNESCO Global Geopark "Yangan-Tau", the article presents a methodology for inventorying geological heritage objects as part of the natural heritage. The mechanism for assessing their scientific, educational and tourist significance is disclosed, the geoconservation is substantiated. The objects of geological heritage are ranked according to the value of the international, national, regional and local level. The application of the developed methodology will allow regional geoparks to approach the criteria indicators of UNESCO global geoparks. Introduction. UNESCO Global Geoparks demonstrate a model of effective management of the territory on which they are located. The status of the geopark is confirmed by seven criteria established by the UNESCO International Program on Geoparks and Geosciences. The first two of them are implemented, among other things, by conducting a detailed inventory of geological objects. The aim of research is to develop a methodology for the inventory of geological heritage objects (geo objects) of regional geoparks based on the assessment of their scientific, educational, tourist, environmental significance and the geoconservation in order to approach the criteria indicators of UNESCO Global Geoparks. Methodology. The inventory methodology involves an expert assessment of the scientific, educational and tourist value of objects, the geoconservation, the allocation of criteria for evaluating scientific, educational, tourist significance and the geoconservation, the development of indicators to determine the level of value. Results. The methodology was tested on the basis of geological heritage objects presented in the nomination dossier of the Yangan-Tau UNESCO global geopark in the Republic of Bashkortostan. The methodology revealed that over 60% of geological heritage sites have high scientific and educational significance. More than 30% of geosites have tourist significance. 12.5% of geosites require protection and preservation measures. The results of the application of the methodology demonstrated that international and national geosites have high scientific and educational significance. They are characterized by a better level of security, which guarantees the absence of significant threats. Objects of regional and local importance have medium and low scientific value, although their educational significance is quite high, and for tourists it varies between high and medium levels. Conclusion. The possibility of a regional geopark joining the UNESCO network of global geoparks is conditioned by compliance with the criteria approved by the UNESCO International Program on Geoparks and Geosciences, including various aspects of sustainable development of the territory. The methodology of inventory of geological heritage sites will allow regional geoparks to identify their strengths and weaknesses in order to approach the criteria indicators of UNESCO Global Geoparks.

Информативность геоинформационной вычислительной визуализации процессов формирования природных объектов

The paper discusses informative possibilities and prospects of application of digital nature-like methodology for computational visualization of natural processes of natural system formation based on the proposed order parameter—intensity of integral geophysical field created by host structure-forming outer space. Since the designated order parameter defines the structure and properties of natural systems and processes, the gradient of the parameter defining the structure of the natural object is a measure of its order parameter and, therefore, can serve as a predictor of forecasting the change in its properties and structure. The declared approach is tested using an example of forecasting the process of flood formation and processes of visualization of tectonic stress fields. The authors have developed a method of point prediction of the onset time and flood level based on a three-level neural network model and a method of vector space-time visualization of a hierarchy of tectonic stress fields on the territory of an unlimited area. The research shows that computational operations with the parameter of the regional temperature gradient along with intelligent forecasting methods illustrate the prospects of point medium-, long-term forecasting of hydrometeorological processes provided with long rows of instrumental observation data. Computational visualization of general, background and local fields of tectonic stresses in the territories of unlimited area serves as a source of parametric data for geoinformation-mathematical modeling of tectonic stress field restructuring in processes of tectonosphere self-organization, calculation of position of geodynamic instability loci—epicenters of possible earthquakes, visualization of tectonic currents in the Earth’s crust. Monitoring geophysical data at geodynamic instability loci opens up prospects for point prediction of earthquakes. Calculation of order parameters of natural objects and processes opens up prospects of their computational modeling, derivation of numerical laws of their conjugate development and a scale series of interaction, as well as prediction of the state of geo objects and geo processes at a given geo space point in conditions of increasing global natural variability.

The Role of a Part of Speech in the System of Toponym Formation

Each place name has its own history. The name of a mountain or any other object of the environment, whether it is a small spring, a piece of land, a water area or even a desert, is of great importance and contains an unsolved mystery.The article is devoted to the issue of the formation of toponyms as a valuable cultural heritage, which, being a kind of" language of the earth", often provide more for solving the problems of historical phenomena than the monuments of material culture, the evidence of ancient and medieval authors. The study of the historical, geographical and linguistic meaning of a placename allows you to get acquainted with the life of the people living in this area.Each geographical name is historical, and its meaning is extensive. They deal with different information depending on the phenomena and changes of time: different wars, folk customs, traditions, relations between peoples and a rich historical past. The appellatives that are part of toponyms determine the natural features of the object (terrain, plants, soil, etc.), and there are also names made up of ethnonyms and antrotoponyms. The names in this group fully convey theethnogenesis of the region. Geo objects on earth are also named for their distinctive features, qualitative, and quantitative properties. What matters to us is what parts of speech are used when creating these names. The article discusses the most common toponyms, which are created using nouns, and also provides their structural models. Nouns and adjectives play a more active role intoponymy than other parts of speech.Nouns actively participate in the formation of toponyms, forming new words. In this regard, the composition of toponyms is also diverse. Toponymic names contain word-forming suffixes, all types of words in various ways. Derived suffixes in the formation of toponymic names and their activity are also considered.

The Role of a Part of Speech in the System of Toponym Formation

Each place name has its own history. The name of a mountain or any other object of the environment, whether it is a small spring, a piece of land, a water area or even a desert, is of great importance and contains an unsolved mystery. The article is devoted to the issue of the formation of toponyms as a valuable cultural heritage, which, being a kind of" language of the earth", often provide more for solving the problems of historical phenomena than the monuments of material culture, the evidence of ancient and medieval authors. The study of the historical, geographical and linguistic meaning of a place name allows you to get acquainted with the life of the people living in this area. Each geographical name is historical, and its meaning is extensive. They deal with different information depending on the phenomena and changes of time: different wars, folk customs, traditions, relations between peoples and a rich historical past. The appellatives that are part of toponyms determine the natural features of the object (terrain, plants, soil, etc.), and there are also names made up of ethnonyms and antrotoponyms. The names in this group fully convey the ethnogenesis of the region. Geo objects on earth are also named for their distinctive features, qualitative, and quantitative properties. What matters to us is what parts of speech are used when creating these names. The article discusses the most common toponyms, which are created using nouns, and also provides their structural models. Nouns and adjectives play a more active role in toponymy than other parts of speech. Nouns actively participate in the formation of toponyms, forming new words. In this regard, the composition of toponyms is also diverse. Toponymic names contain word-forming suffixes, all types of words in various ways. Derived suffixes in the formation of toponymic names and their activity are also considered.

Strengthen the Feature Distinguishability of Geo-Object Details in the Semantic Segmentation of High-Resolution Remote Sensing Images

Semantic segmentation is one of the hot topics in the field of remote sensing image intelligent analysis. Deep convolutional neural network (DCNN) has become a mainstream technology in semantic segmentation due to its powerful semantic feature representation. The emergence of high-resolution remote sensing imagery has provided massive detail information, but difficulties and challenges remain in the “feature representation of fine geo objects” and “feature distinction of easily confusing geo objects.” To this end, this article focuses on the distinguishing features of geo-object details and proposes a novel DCNN-based semantic segmentation. First, the cascaded relation attention module is adopted to determine the relationship among different channels or positions. Then, information connection and error correction are used to capture and fuse the features of geo-object details. The output feature representations are provided by the multiscale feature module. Besides, the proposed model uses the boundary affinity loss to gain accurate and clear geo-object boundary. The experimental results on the Potsdam and Vaihingen datasets demonstrate that the proposed model can achieve excellent segmentation performance on overall accuracy and mean intersection over union. Furthermore, the results of ablation and visualization analyses also verify the feasibility and effectiveness of the proposed method.

Understanding the Effects of Optimal Combination of Spectral Bands on Deep Learning Model Predictions: A Case Study Based on Permafrost Tundra Landform Mapping Using High Resolution Multispectral Satellite Imagery.

Deep learning (DL) convolutional neural networks (CNNs) have been rapidly adapted in very high spatial resolution (VHSR) satellite image analysis. DLCNN-based computer visions (CV) applications primarily aim for everyday object detection from standard red, green, blue (RGB) imagery, while earth science remote sensing applications focus on geo object detection and classification from multispectral (MS) imagery. MS imagery includes RGB and narrow spectral channels from near- and/or middle-infrared regions of reflectance spectra. The central objective of this exploratory study is to understand to what degree MS band statistics govern DLCNN model predictions. We scaffold our analysis on a case study that uses Arctic tundra permafrost landform features called ice-wedge polygons (IWPs) as candidate geo objects. We choose Mask RCNN as the DLCNN architecture to detect IWPs from eight-band Worldview-02 VHSR satellite imagery. A systematic experiment was designed to understand the impact on choosing the optimal three-band combination in model prediction. We tasked five cohorts of three-band combinations coupled with statistical measures to gauge the spectral variability of input MS bands. The candidate scenes produced high model detection accuracies for the F1 score, ranging between 0.89 to 0.95, for two different band combinations (coastal blue, blue, green (1,2,3) and green, yellow, red (3,4,5)). The mapping workflow discerned the IWPs by exhibiting low random and systematic error in the order of 0.17–0.19 and 0.20–0.21, respectively, for band combinations (1,2,3). Results suggest that the prediction accuracy of the Mask-RCNN model is significantly influenced by the input MS bands. Overall, our findings accentuate the importance of considering the image statistics of input MS bands and careful selection of optimal bands for DLCNN predictions when DLCNN architectures are restricted to three spectral channels.

基于改进Phong模型的天基光学观测GEO目标姿态估计方法

基于改进Phong模型的天基光学观测GEO目标姿态估计方法

Image processing for GEO object with 3D rotation based on ground-based InISAL with orthogonal baselines.

While imaging geosynchronously orbiting objects with ground-based inverse synthetic aperture LADAR (ISAL), target rotation and vibration will introduce phase errors into the echo and cause the two-dimensional imaging result to be defocused. To solve this problem, one layout of the ISAL receiving channels is designed, combining the orthogonal short baselines in the inner field with the orthogonal long baselines in the external field. On this basis, an imaging method based on orthogonal interferometry processing is proposed. The proposed method estimates and compensates for the phase errors introduced by the rotation and vibration of the target such that the focus of the two-dimensional image is improved, and three-dimensional imaging results with high accuracy are obtained. The effectiveness of the proposed method is verified by simulation data.

Algorithms for space-based anomaly detection of GEO objects

Beyond catalog maintenance, a sun-synchronous sensor can provide valuable information about GEO objects’ characteristics. Algorithms were designed for attitude anomaly detection of GEO satellites and spin axis determination for tumbling objects using space-based non-resolved optical data. The spin axis orientation of a tumbling GEO object can be estimated by analyzing its observed tumble rate variations with an orbiting sensor. Simulated space-based observations using a GEO satellite model, with variable spin rates and axial tilt angles, have suggested that the algorithms are effective at estimating a GEO satellite’s spin rates and orientation.

地球同步轨道暗弱目标地基光学成像技术综述

地球同步轨道暗弱目标地基光学成像技术综述

国外地球同步轨道目标天基光学监视策略

国外地球同步轨道目标天基光学监视策略

Attitude optimization of optical space surveillance satellite to observe specific geostationary orbit object

Due to the restriction of field of view (FOV) of GEO camera, the optical space-based space surveillance satellite may be not able to observe some specific important GEO objects in time. The satellite attitude could be pre-adjusted based on the relative position between satellite and object. The available attitude adjusting angle is obtained through analysis of the azimuth and elevation of object to satellite. The attitude adjusting angle is optimized by the Powell method with the accessible duration as index, and the method for determining the initial value is provided. The results show that the optimization of attitude both in three-axis stabilized attitude mode and quasi-inertial attitude mode can improve the accessible duration to 300s or longer. This method can determine the adjusting angle conveniently and improve the capability of satellite.

Associating optical measurements of MEO and GEO objects using Population-Based Meta-Heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). The MTT problem quickly becomes an NP-hard combinatorial optimization problem. This means that the effort required to solve the MTT problem increases exponentially with the number of tracked objects. In an attempt to find an approximate solution of sufficient quality, several Population-Based Meta-Heuristic (PBMH) algorithms are implemented and tested on simulated optical measurements. These first results show that one of the tested algorithms, namely the Elitist Genetic Algorithm (EGA), consistently displays the desired behavior of finding good approximate solutions before reaching the optimum. The results further suggest that the algorithm possesses a polynomial time complexity, as the computation times are consistent with a polynomial model. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the association and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

ACQUISITION OF HIGH RESOLUTION GEO OBJECTS USING IMAGE MOSAICKING TECHNIQUES

Remote sensing onboardsatellite techniques have been demonstrated to be powerful tools for monitoring the earth’s surface. Image mosaicking aligns multiple overlapping images of a same scene into a larger image of high resolution. In this paper, the feature extraction is based on SIFT and SURF technique. These techniques produce an efficient mosaicked image output as compared with other methods. From these algorithms the efficiency of PSNR and MSE value is 40%. It has been active research in finding disaster areas, computer vision and computer graphics, military target purposes.

Algorithms and applications for detecting faint space debris in GEO

The GEO region is a kind of unique and precious resource, it is of great importance to prevent space debris collisions in this region. Surveying space debris in GEO and extracting the relevant information automatically are rather challenging tasks due to several factors. Here we present an image processing pipeline which detects GEO objects automatically and improves the detection ability for faint objects. In our pipeline the mathematical morphology operator is adopted to eliminate noises and perform image restoration, then the median is used to eliminate the influences of field stars and extract object positions. The pipeline is tested on a large number of raw CCD images, and the tracklets obtained are correlated and catalogued, finally the effectiveness and the efficiency are demonstrated and proved by the results.

Geostationary orbit development and evaluation for space situational awareness

Awareness of objects and events in and around the Geostationary Earth Orbit satellite belt is currently limited, and the situation is worsening as more satellites are added and the satellites trend toward smaller sizes. A potential solution is to deploy observation satellites near the geostationary altitude to improve monitoring and object characterization capabilities, but the vastness of the geostationary belt creates several unique challenges. Many of these challenges can potentially be mitigated by proper orbit and constellation designs. First, a methodology for evaluating such designs through a system simulation tool is described. Second, an analysis is performed including a variety of circular orbit, eccentric orbit, and maneuvering constellations of geostationary observer satellites. The analysis shows that non-circular orbit designs can result in improved performance for various range- and coverage-based inspection criteria. These tools are useful in mission planning and constellation design, and can be easily expanded to include additional constellation metrics or time history metrics on individual GEO objects such as illumination conditions.

A method of correlation analysis for space-based GEO object surveillance

A method of correlation analysis to determine the correlation between two too-short arcs is presented to monitor geosynchronous earth orbit objects on a space-based surveillance system. The necessary condition for a geosynchronous earth orbit object to be observed by a space-based visible sensor in two successive orbital periods is derived, and the principle for the selection of search fence parameters is proposed. The processing procedure of the correlation analysis for the two too-short arcs as well as two correlation judgment methods is given and the selection of the threshold value for the judgment is analyzed. Finally, a simulation is performed to demonstrate the applicability of the presented methods. Simulation results indicate that a surveillance system can acquire two observation arcs in two successive orbital periods by selecting the suitable search fence parameters, and that the two correlation judgment methods and the selected threshold are valid. The initial orbit of the uncorrelated objects can be determined by two observation arcs, and the accuracy of the initial orbit meets the requirements of re-acquiring the object.

Object image linking of earth orbiting objects in the presence of cosmics

In survey series of unknown Earth orbiting objects, no a priori orbital elements are available. In surveys of wide field telescopes possibly many non-resolved object images are present on the single frames of the series. Reliable methods have to be found to associate the object images stemming from the same object with each other, so-called linking. The presence of cosmic ray events, so-called Cosmics, complicates reliable linking of non-resolved images. The tracklets of object images allow to extract exact positions for a first orbit determination. A two step method is used and tested on observation frames of space debris surveys of the ESA Space Debris Telescope, located on Tenerife, Spain: in the first step a cosmic filter is applied in the single observation frames. Four different filter approaches are compared and tested in performance. In the second step, the detected object images are linked on observation series based on the assumption of a linear accelerated movement of the objects over the frame during the series, which is updated with every object image, that could be successfully linked. As results it has to be stated. Firstly, the automatic discrimination of cosmics and non-resolved object images on single frames remains difficult, especially for traces with a size of only a few pixels. Secondly, on observation series, the object image linking of GEO, GTO and MEO object images is reliable for a moderate amount of object images or cosmics on the frames if at least three object images are available per object and for four object images per object even in the presence of several hundred cosmics or images on the frames with a simple approach of an updated linear accelerated movement even over long observation series.

The Approximation of Two-Dimensional Spatial Objects by Two Bounding Rectangles

Minimal bounding rectangles are a simple and efficient tool for approximating geometries, particularly for accelerating spatial queries. If a spatial object fills a rectangular shape to a certain extent, then the minimal bounding rectangle is a reasonable approximation. Unfortunately some geo objects, such as streets or rivers, have a small area but large bounding rectangles. In this paper we suggest an approximation with two bounding rectangles instead of a single one. Since the corresponding shape provides a better approximation, we get a greater average benefit. We present an efficient algorithm that computes the two rectangles with the theoretically smallest combined area that encloses a given geometry in O(n · log n) steps. Following a detailed description of the algorithm, we present an analysis with approximately 4 million real geo objects.