The Study on Environmental Evolved Characteristic of Sandy Coast

2012 ◽  
Vol 226-228 ◽  
pp. 1170-1173
Author(s):  
Qi Peng Zhang ◽  
Xiao Qing Han ◽  
Jing Li ◽  
Jing Jing Zhao ◽  
Wei Biao Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Bohai Sea ◽  
Hebei Province ◽  
Coastal Current ◽  
Remote Sensing Images ◽  
Remote Sensing Technology ◽  
The North ◽  
Sensing Technology ◽  
Sandy Coast

In order to study the evolved characteristic of sandy coast in Hebei Province, the paper analyzed costal information by Remote Sensing technology from landform maps and remote sensing images from 1956 to 2007. It studied the evolvement characteristics and the reasons of sandy coast deeply. And it also analyzed the evolvement infections to the nearby coast of the sandy engineering. The results showed that the characteristic was erosion condition in sandy coast. There were several different evolved processing in different area from 1959 to 2007. In the region between Daihe River and Tazigou, the highest erosion speed was 3.45 m/a by the coastal current and wave between Daihe River and Yanghe River. The section was deposited into the ocean with the speed of 1.29 m/a by the cultivation ponds building in Bohai Sea farmland between the Yanghe River and Dapuhe River. In the region between Tazigou and Langwokou River, the beach had been eroded about 373 m with the speed of 13.32 m/a by 2007. And the section was eroded offshore more serious with the distance of 610 m and the speed of 21.79 m/a from the north of Luanhe River.In the region between Langwokou River and Daqinghe River, the average erosion distance was about 370 m with the speed of 13.21 m/a in Shegang sandbar. And it was eroded back to mainland about 164 m with the speed of 8.20 m/a. And it was about 504m with the speed of 18.00 m/a.

Remote sensing image quality evaluation based on deep learning

2021 ◽  
pp. 1-9
Author(s):  
Tong Wang ◽  
Hemeng Yang ◽  
Ling Zhu ◽  
Yazhou Fan ◽  
Xue Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Quality ◽  
Quality Evaluation ◽  
Remote Sensing Image ◽  
Human Vision ◽  
Remote Sensing Images ◽  
Image Quality Evaluation ◽  
Remote Sensing Technology ◽  
Sensing Technology

Remote sensing technology is an effective tool for sensing the earth’s surface. With the continuous improvement of remote sensing technology, remote sensing detectors can obtain more spectral and spatial information, including clear feature contours, complex texture features and spatial layout rules. This information was detected in mineral resources. Surface substance identification, water pollution information monitoring and many other aspects have played an important role. The coding algorithm and defects, storage algorithm and interference from atmospheric cloud radiation information during the imaging process lead to varying degrees of distortion and deterioration of remote sensing images during imaging, transmission and storage. This makes it difficult to process, analyze and apply remote sensing images. Therefore, the design of a reasonable remote sensing image quality evaluation method is not only conducive to the remote sensing image quality evaluation in the real-time processing system of remote sensing image, but also conducive to the optimization of remote sensing image system and image processing algorithm. The application is worthwhile. In this paper, the deteriorating features of remote sensing images will change the statistical distribution. We propose a method for evaluating the quality of remote sensing images in depth learning. Feature learning and blurring as well as noise intensity classification for image remote sensing using convolutional neural network are carried out. The evaluation model is modified by masking effect and perceptual weighting factor, and the quality evaluation results of remote sensing images are obtained according to human vision. The research shows that this method can effectively solve the problem of removing and evaluating the noise of remote sensing image, and can effectively and accurately evaluate the quality of remote sensing image. It is also consistent with subjective assessment and human perception.

scholarly journals Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology

2021 ◽  
Vol 25 (1) ◽  
pp. 57-64
Author(s):  
Maolin Li
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Atmospheric Correction ◽  
Least Square Method ◽  
Least Square ◽  
Dynamic Monitoring ◽  
Remote Sensing Images ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Monitoring Algorithm

A dynamic monitoring algorithm of natural resources in scenic spots based on MODIS remote sensing technology is proposed to improve natural resources monitoring accuracy in scenic spots. The remote sensing images of scenic spots obtained by MODIS were preprocessed by TM image processing, atmospheric correction, and other technologies to get high-precision remote sensing images. The remote sensing images of scenic spots were segmented by the multi-scale segmentation method, and then the hierarchical supervision classification method was used. The change points of natural resources were extracted. The resource changes and independent variables of scenic spots were analyzed based on the least square method to realize the dynamic monitoring of natural resources in scenic locations. The experimental results show that the technique can accurately monitor the dynamic changes of forest resources and water resources in scenic spots, and the monitoring results have high accuracy.

Mining Subsidence Monitoring around Longgu Coal Mine Based on Remote Sensing

2014 ◽  
Vol 1010-1012 ◽  
pp. 489-495 ◽  
Author(s):  
Hai Qing Wang
Keyword(s):  
Remote Sensing ◽  
Coal Mine ◽  
Mining Subsidence ◽  
Remote Sensing Images ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Short Period ◽  
Subsidence Monitoring

There are serious mining subsidence around Longgu coal mine, local people's livelihood has been affected seriously. Remote sensing technology was used to survey the mining subsidence, because it is macroscopic, rapid, economic, effective and objective. There were 6 period remote sensing images were collected in total. Those remote sensing images were compared, and the history about those mining subsidence was known. Filed investigation were applied in this articles to survey these mining subsidence, also. The area of these mining subsidence destroyed were: 0.35km2 in December 2010, 0.56km2 in August 2011, 1.01km2 in September 2012, 1.26 km2 in May 2013, 1.53km2 in November 2013. There were a rapidly develop in the four years. The mining subsidence in this area belong to the young type, developed rapidly, trend to destroy great deal farmland during a short period. The mining subsidence should be monitored persistent use remote sensing. The regular about mining subsidence should be further study. And some prediction works should be done based on the regular study.

A CBIR System for Hyperspectral Remote Sensing Images Using Endmember Extraction

2017 ◽  
Vol 31 (04) ◽  
pp. 1752001 ◽  
Author(s):  
Jing Zhang ◽  
Qianlan Zhou ◽  
Li Zhuo ◽  
Wenhao Geng ◽  
Suyu Wang
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Image ◽  
Hyperspectral Remote Sensing ◽  
Superior Performance ◽  
Endmember Extraction ◽  
Remote Sensing Images ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Hyperspectral Remote Sensing Images ◽  
Hyperspectral Remote Sensing Image

With the rapid development of remote sensing technology, searching the similar image is a challenge for hyperspectral remote sensing image processing. Meanwhile, the dramatic growth in the amount of hyperspectral remote sensing data has stimulated considerable research on content-based image retrieval (CBIR) in the field of remote sensing technology. Although many CBIR systems have been developed, few studies focused on the hyperspectral remote sensing images. A CBIR system for hyperspectral remote sensing image using endmember extraction is proposed in this paper. The main contributions of our method are that: (1) the endmembers as the spectral features are extracted from hyperspectral remote sensing image by improved automatic pixel purity index (APPI) algorithm; (2) the spectral information divergence and spectral angle match (SID–SAM) mixed measure method is utilized as a similarity measurement between hyperspectral remote sensing images. At last, the images are ranked with descending and the top-[Formula: see text] retrieved images are returned. The experimental results on NASA datasets show that our system can yield a superior performance.

The Research of Ortho-Rectification to QuickBird Image with more Mountains Based on ERDAS10.0

2014 ◽  
Vol 571-572 ◽  
pp. 772-776 ◽  
Author(s):  
Cong Li ◽  
Qiang Wang ◽  
Meng Wang ◽  
Jia Jie Cui
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Orthogonal Projection ◽  
Satellite Image ◽  
Remote Sensing Image ◽  
Remote Sensing Images ◽  
Positioning Accuracy ◽  
Remote Sensing Technology ◽  
Sensor Model ◽  
Sensing Technology

In recent years, the application of high resolution remote sensing images has become more and more widely with the development of Remote Sensing technology. QuickBird satellite image is the more commercial used high resolution remote sensing image, but due to its technical confidentiality, high-resolution satellite generally does not provide rigorous sensor model. This paper uses ERDAS10.0 to orthographic check the QuickBird image by the method of orthorectification, introduces the method and procedure of the orthogonal projection like drawing, analysis the positioning accuracy.

Land Utilization and Classification Method Based on Remote Sensing Technology

2012 ◽  
Vol 239-240 ◽  
pp. 501-506 ◽  
Author(s):  
Tong He Sun ◽  
Guo Qing Yan
Keyword(s):  
Remote Sensing ◽  
Supervised Classification ◽  
Reference Value ◽  
Classification Methods ◽  
Remote Sensing Images ◽  
Land Utilization ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Erdas Imagine ◽  
Supervised Classification Methods

This paper discusses land utilization classification based on remote sensing technology. Taking the Xinjiang Kulja county bureau department area remote sensing images as the basic information, and using ERDAS IMAGINE, this paper discusses non-supervised classification and supervised classification methods. The results show that remote sensing technology applies to land utilization situation and land classification, which has reference value.

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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