scholarly journals Detection and Tracking Method of Maritime Moving Targets Based on Geosynchronous Orbit Satellite Optical Images

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1092
Author(s):  
Fengqi Xiao ◽  
Fei Yuan ◽  
En Cheng
Keyword(s):  
Satellite Image ◽  
Image Sequence ◽  
Geosynchronous Orbit ◽  
Optical Remote Sensing ◽  
Large Area ◽  
Tracking Method ◽  
Detection And Tracking ◽  
Orbit Satellite ◽  
Optical Images ◽  
Long Time

The GF-4 geosynchronous orbit satellite can observe a large area for a long time, but the unique characteristics of its optical remote sensing image restrict the detection of maritime targets. This paper proposes a maritime target detection and tracking method for the GF-4 satellite image sequence based on the differences in information between frames in the image sequence. First, a preprocessing method is proposed for the unique characteristics of the image. Then, the ViBe (Visual Background Extractor) algorithm is used to extract the targets in the image sequence. After detection, the DCF-CSR (discriminative correlation filters with channel and spatial reliability) is used as a tracker to track and correlate the detected target to complete the task of predicting and monitoring the targets’ movements. Finally, through the comparative analysis of experiments with several classic methods, the feasibility and effectiveness of this method are verified.

scholarly journals Detection and Tracking Method of Moving Ships through Navigational Image Sequence

2005 ◽  
Vol 113 (0) ◽  
pp. 115-126 ◽  
Author(s):  
Masatoshi SHIMPO ◽  
Masato HIRASAWA ◽  
Masaki OSHIMA
Keyword(s):  
Image Sequence ◽  
Tracking Method ◽  
Detection And Tracking

scholarly journals Real-time Detection and Tracking Method of Landmark Based on UAV Visual Navigation

2018 ◽  
Vol 36 (2) ◽  
pp. 294-301 ◽  
Author(s):  
Jing Li ◽  
Xiaodong Ma ◽  
Huaimin Chen ◽  
Xiaojun Duan ◽  
Yanlong Zhang
Keyword(s):  
Real Time ◽  
Search Algorithm ◽  
Visual Navigation ◽  
Motion Blur ◽  
Tracking Method ◽  
Detection And Tracking ◽  
Illumination Changes ◽  
Long Time ◽  
Real Time Detection ◽  
Principle Of Similarity

A real-time detection and tracking method of landmark based for UAV visual navigation and fixed landing was proposed. This method used the SVM classification algorithm to train the offline classifier based on SURF-BoW features extracted from samples, which can recognize the landing landmark accurately and complete the initialization of the tracker. Afterwards, tracked the landmark via the improved median flow algorithm to ensure the reliability and integrity of the tracking target. Finally, based on the classifier and the principle of similarity between two adjacent frames' target, this paper designed a target re-search algorithm to ensure that the target can be retrieved quickly even if the target is lost or the target tracking fails, which makes the entire set of algorithm track the target accurately for a long time. The experimental results show that the proposed algorithm has good tracking performance under the conditions of the change of target scale, illumination changes and motion blur.

Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping

2020 ◽  
Vol 38 (4A) ◽  
pp. 510-514
Author(s):  
Tay H. Shihab ◽  
Amjed N. Al-Hameedawi ◽  
Ammar M. Hamza
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Artificial Neural Network ◽  
Random Forest ◽  
Satellite Image ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Data Set ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

In this paper to make use of complementary potential in the mapping of LULC spatial data is acquired from LandSat 8 OLI sensor images are taken in 2019.  They have been rectified, enhanced and then classified according to Random forest (RF) and artificial neural network (ANN) methods. Optical remote sensing images have been used to get information on the status of LULC classification, and extraction details. The classification of both satellite image types is used to extract features and to analyse LULC of the study area. The results of the classification showed that the artificial neural network method outperforms the random forest method. The required image processing has been made for Optical Remote Sensing Data to be used in LULC mapping, include the geometric correction, Image Enhancements, The overall accuracy when using the ANN methods 0.91 and the kappa accuracy was found 0.89 for the training data set. While the overall accuracy and the kappa accuracy of the test dataset were found 0.89 and 0.87 respectively.

scholarly journals Morphology and distribution of the freshwater mussel Diplodon granosus, a rare and poorly understood species

2020 ◽  
Vol 50 (1) ◽  
pp. 44-53 ◽  
Author(s):  
Igor Christo MIYAHIRA ◽  
Maria Cristina Dreher MANSUR ◽  
Daniel Mansur PIMPÃO ◽  
Sheyla Regina Marques COUCEIRO ◽  
Sonia Barbosa dos SANTOS
Keyword(s):  
South America ◽  
Freshwater Mussels ◽  
Freshwater Mussel ◽  
Wide Distribution ◽  
Large Area ◽  
The North ◽  
Coastal Rivers ◽  
The Status ◽  
Long Time

ABSTRACT Diplodon granosus was one of the first freshwater mussels to be described for South America. However, the status of the species was confusing for a long time, receiving different taxonomic treatments. In this paper, we redescribe the shell, with new data on the soft parts and information on the distribution and conservation of D. granosus, a rarely recorded species. The shell is thin, not inflated; the macrosculpture is composed only by granules that cover the whole shell, not forming bars; the microsculpture comprises short spikes. In the soft parts we highlight the few, weak and irregularly distributed lamellar connections of the outer demibranch and some features of the stomach, such as the distally enlarged minor typhlosole. There are records of D. granosus over a large area of South America, from Guiana to Argentina. However, most of these records are related to other species and the distribution of D. granosus is restricted to the north of South America in the basins of the Amazonas and Orinoco rivers, and coastal rivers in between. Despite this wide distribution, the species occurs in specific habitats, mainly streams (igarapés), resulting in an extremely fragmented occurrence. Thus, any disturbance to these habitats can threat this freshwater mussel.

scholarly journals Optical Remote Sensing

2021 ◽  
pp. 315-344
Author(s):  
Man Sing Wong ◽  
Xiaolin Zhu ◽  
Sawaid Abbas ◽  
Coco Yin Tung Kwok ◽  
Meilian Wang
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Information Extraction ◽  
Urban Areas ◽  
Satellite Image ◽  
Background Information ◽  
Optical Remote Sensing ◽  
Basic Operation ◽  
City Development ◽  
Satellite Image Processing

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.

scholarly journals Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram

2015 ◽  
Vol 9 (2) ◽  
pp. 2597-2623 ◽  
Author(s):  
F. Paul
Keyword(s):  
Satellite Images ◽  
Satellite Image ◽  
Time Lapse ◽  
Image Sequences ◽  
Flow Dynamics ◽  
Mountain Range ◽  
Time Period ◽  
Climatic Control ◽  
Long Time ◽  
Glacier Flow

Abstract. Although animated images are very popular on the Internet, they have so far found only limited use for glaciological applications. With long time-series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable for a wide public. For this study animated image sequences were created from freely available image quick-looks of orthorectified Landsat scenes for four regions in the central Karakoram mountain range. The animations play automatically in a web-browser and might help to demonstrate glacier flow dynamics for educational purposes. The animations revealed highly complex patterns of glacier flow and surge dynamics over a 15-year time period (1998–2013). In contrast to other regions, surging glaciers in the Karakoram are often small (around 10 km2), steep, debris free, and advance for several years at comparably low annual rates (a few hundred m a−1). The advance periods of individual glaciers are generally out of phase, indicating a limited climatic control on their dynamics. On the other hand, nearly all other glaciers in the region are either stable or slightly advancing, indicating balanced or even positive mass budgets over the past few years to decades.

Review on critical technology development of avian radar system

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Weishi Chen ◽  
Yifeng Huang ◽  
Xianfeng Lu ◽  
Jie Zhang
Keyword(s):  
Technology Development ◽  
Time Integration ◽  
Radar System ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Detection And Tracking ◽  
Critical Technology ◽  
Long Time ◽  
Long Time Integration ◽  
Target Characteristics

Purpose This paper aims to review the critical technology development of avian radar system at airports. Design/methodology/approach After the origin of avian radar technology is discussed, the target characteristics of flying birds are analyzed, including the target echo amplitude, flight speed, flight height, trajectory and micro-Doppler. Four typical airport avian radar systems of Merlin, Accipiter, Robin and CAST are introduced. The performance of different modules such as antenna, target detection and tracking, target recognition and classification, analysis of bird information together determines the detection ability of avian radar. The performances and key technologies of the ubiquitous avian radar are summarized and compared with other systems, and their applications, deployment modes, as well as their advantages and disadvantages are introduced and analyzed. Findings The ubiquitous avian radar achieves the long-time integration of target echoes, which greatly improves detection and classification ability of the targets of birds or drones, even under strong background clutter at airport. In addition, based on the big data of bird situation accumulated by avian radar, the rules of bird activity around the airport can be mined to guide the bird avoidance work. Originality/value This paper presented a novel avian radar system based on ubiquitous digital radar technology. The authors’ experience has confirmed that this system can be effective for airport bird strike prevention and management. In the future, the avian radar system will see continued improvement in both software and hardware, as the system is designed to be easily extensible.

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