Mine Remote Sensing Using a Working Robot

2005 ◽  
Vol 17 (1) ◽  
pp. 101-105
Author(s):  
Nobuhiro Shimoi ◽  
◽  
Yoshihiro Takita ◽  
Keyword(s):  
Remote Sensing ◽  
Simulation Model ◽  
Real Time ◽  
Image Data ◽  
Mine Detection ◽  
Compliance Control ◽  
Ir Camera ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
End Effectors

In conducting mine detection experiments using our prototype robot COMET-1, we developed end effectors on the robot’s working legs. When detecting a mine, a robot must step safely and stably without hitting it. For this study, we created a simulation model to test the movement of a robot having an optical proximity sensor on each foot and used a walking algorithm having compliance control. We verified its efficiency in walking experiments. We also studied the use of remote sensing technology with an IR camera combined with other sensors. Tests with trial mines were used to study the detection of an IR camera and studied technologies for collecting and processing image data in real time for optimum mine detection.

scholarly journals Mangrove Distribution in Riau Islands Using Remote Sensing Technology

2017 ◽  
Vol 1 (2) ◽  
pp. 58-62 ◽  
Author(s):  
Sudra Irawan ◽  
Dwi Ely Kurniawan ◽  
Wenang Anurogo ◽  
Muhammad Zainuddin Lubis
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Image Data ◽  
Research Data ◽  
Resolution Image ◽  
Mangrove Area ◽  
High Resolution Image ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Data Application

Mangrove mapping is done with remote sensing technology using high-resolution image data. Application and information are then presented in web form. This study aims to map the mangrove distribution in Riau Islands, Indonesia. Based on the analysis, from the research data obtained the total area of mangrove in Riau Islands in 2011 and 2017 amounted to 71,504.83 Ha and 64,218.90 Ha, decreased by 7,285, 93 Ha or decreased by 10.19%. Based on the regency, the largest mangrove area in 2017 is located in Batam City of 22,964.77 Ha, then Karimun Regency (13,659,58 Ha), Lingga Regency (11,881.61 Ha), Regency of Bintan (9,701.49) Ha, Natuna Regency (2,477.16 Ha), Tanjungpinang City (1,847.65 Ha), and Anambas Regency (1,686.61 Ha). The magnitude of the widespread change (widespread reduction) occurring over the years between 2011 and 2017 by district, Natuna Regency experienced the largest reduction of 1,949.69 Ha or around 41.39%, followed by Lingga Regency of 1,947.15 Ha (14.08%), Tanjungpinang Municipality of 284.13 Ha (13.33%), Karimun Regency 1,920.93 Ha (12.33%), Anambas Regency of 195.90 Ha (10.40%), Batam City 1,094.83 Ha (4.55%) and Bintan Regency with 93.29 Ha (0, 95%). Opportunities that the pixels classified on the mangrove image are truly mangrove on the facts in the field.

scholarly journals THE TYPHOON DISASTER ANALYSIS EMERGENCY RESPONSE SYSTEM BASED ON UAV REMOTE SENSING TECHNOLOGY

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 959-965
Author(s):  
Q. J. Chen ◽  
Y. R. He ◽  
T. T. He ◽  
W. J. Fu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Visual Analysis ◽  
Satellite Image ◽  
Image Data ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Disaster Information ◽  
Satellite Image Data ◽  
Typhoon Disaster

Abstract. The satellite image data has some shortcomings such as poor timeless, incomplete disaster information and so on in the typhoon disaster analysis. Compared with the satellite image data, unmanned aerial vehicle (UAV) remote sensing technology has the characteristics of flexibility, convenience, high resolution and so on. It plays a great role in the aspect of obtaining the images and systematically analyze the disaster data. This research based on UAV technology to obtain the high resolution image data and complied the disaster thematic maps after interpretation, as well as determining the data model. Subsequently, determining the system used Html, Javascript and CSS to build the system framework. Combining with Postgre SQL database, Leaflet map module and Echarts diagram and other technologies to perform the feasibility analysis and the detailed design of the integrated system. Finally, it could accurately and comprehensively obtain the system’s disaster monitoring, the typhoon track display, the diagram statistics and visual analysis of the data processing, as well it could deeply analysis and management for the disaster information and assessment. The application shows that this system could provide the information support for future emergency rescue, which is of great significance for the monitoring and preventing the occurrence natural disasters in the future.

scholarly journals IDENTIFICATION OF MANGROVE FORESTS USING MULTI-RESOLUTION SATELLITE IMAGERY

Jurnal Segara ◽  
2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Anang Dwi Purwanto
Keyword(s):  
Remote Sensing ◽  
Mangrove Forest ◽  
Image Data ◽  
Field Measurements ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Remote Sensing Technology ◽  
Red Edge ◽  
Sensing Technology ◽  
Sentinel 2A

The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015. The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites (R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but image composites from SPOT 6 image still require additional of association elements to identify mangrove objects.The development of remote sensing technology for identifying various of coastal and marine ecosystems which one of them is mangrove forest increasing rapidly. Identification of mangrove forests visually is constrained by much of combinations of RGB composite. The aims of this research is to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using Optimum Index Factor (OIF) method. The image data used represents 3 levels of intermediate to high resolution spatial resolution including Landsat 8 imagery (30 m) acquisition on 30 May 2013, Sentinel 2A image (10 m) acquisition on 18 March 2018 and SPOT 6 image (6 m) acquisition on 10 January 2015. Data of mangrove distributions used were the results of field measurements in the period 2013-2015.The results showed that the band composites of 564 (NIR+SWIR+Red) of Landsat 8 image and the band composites of 8a114 (Vegetation Red Edge+SWIR+Red) of Sentinel 2A are the best RGB composites for identifying mangrove forest, while the band composites of 341 (Red+NIR+Blue) of SPOT 6 image is  also the best colour composites(R-G-B) for identifying mangrove forest in Segara Anakan, Cilacap. The RGB composites of images developed from Landsat 8 and Sentinel 2A image are able to distinguish objects of mangrove forest from surrounding objects more clearly, but imagecomposites from SPOT 6 image still require additional of association elements to identify mangrove objects.

scholarly journals Application of UAV Remote Sensing Mapping in Map Drawing

CONVERTER ◽  
2021 ◽  
pp. 86-93
Author(s):  
Xu Chen, Kuan He, Yuntong Liu
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Low Cost ◽  
Correction Method ◽  
Field Application ◽  
Image Resolution ◽  
Technical Problems ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Surveying And Mapping

UAV aerial remote sensing system has the characteristics of strong real-time, flexible, high image resolution and low cost, which can be applied to map mapping tasks under various terrain. In this paper, the key technology of UAV Remote Sensing Surveying and mapping, the process of image processing, the research of mosaic method and the field application of remote sensing technology are studied. Aiming at the characteristics of UAV image with high resolution and small image frame, three methods of image map making are proposed, namely, single image geometric correction method, mosaic correction method and aerial triangulation method. This paper focuses on the key technical problems of the three methods, and makes a comprehensive analysis and experimental verification of each method from the aspects of mapping effect, accuracy and efficiency. The experimental results show that the UAV remote sensing technology can meet the real-time basic surveying and mapping data requirements of urban mapping. This method can meet the needs of 1:500 high-precision mapping. The system can reduce the cost and improve the usability when it is used to update the basic data of Urban Surveying and mapping.

Hyperspectral Remote Sensing Technology (HRST) program

1997 ◽  
Author(s):  
Tom Wilson ◽  
Rebecca Baugh ◽  
Ron Contillo ◽  
Tom Wilson ◽  
Rebecca Baugh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology

Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

1995 ◽  
Vol 32 (2) ◽  
pp. 77-83
Author(s):  
Y. Yüksel ◽  
D. Maktav ◽  
S. Kapdasli
Keyword(s):  
Remote Sensing ◽  
Sediment Transport ◽  
Surf Zone ◽  
Hydrodynamic Forces ◽  
Construction Site ◽  
Coastal Morphology ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

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