Image Processing Method Based on GIS System for Better Disaster Manag Ement

2011 ◽  
Vol 403-408 ◽  
pp. 976-981
Author(s):  
Sanjivani Mahor ◽  
Nishant Shrivastava ◽  
Ashutosh K. Dubey
Keyword(s):  
Image Processing ◽  
Information System ◽  
Precision Agriculture ◽  
Earthquake Damage ◽  
Geospatial Information ◽  
Database Technology ◽  
Processing Module ◽  
Core Idea ◽  
Remote Sensing Image Processing ◽  
Gis System

A geographic information system (GIS), or geospatial information system is any system that captures, stores, analyzes, manages, and presents data that are linked to location(s). GIS is the merging of cartography, statistical analysis, and database technology, natural resource management, precision agriculture, photogrammetric, urban planning, emergency management, navigation, aerial video, and localized search engines.Today the concept of GIS is widely used in different areas of research and mankind. The disaster management systems are most based on GIS today, and the core idea of those systems is the past earthquake experiences. Remote sensing image processing can help government assess earthquake damage quickly. Taking this technology integrated with the quondam system can improve the assessment’s precision of this kind of system. In this paper, we discuss a method which quickly evaluates the earthquake damage. Firstly, we discuss different cases and quick evaluation of earthquake damage by means of GIS based system. Secondly, analyzes the result by quick assessment. Thirdly, integrating the image processing module with the old system to get the new system, in which the assessment’s precision can be improved.

scholarly journals Remote Sensing Image Dataset Expansion Based on Generative Adversarial Networks with Modified Shuffle Attention

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4867
Author(s):  
Lu Chen ◽  
Hongjun Wang ◽  
Xianghao Meng
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Image Processing ◽  
Remote Sensing Image ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Evaluation Indexes ◽  
Adversarial Network ◽  
Remote Sensing Image Processing ◽  
Data Expansion

With the development of science and technology, neural networks, as an effective tool in image processing, play an important role in gradual remote-sensing image-processing. However, the training of neural networks requires a large sample database. Therefore, expanding datasets with limited samples has gradually become a research hotspot. The emergence of the generative adversarial network (GAN) provides new ideas for data expansion. Traditional GANs either require a large number of input data, or lack detail in the pictures generated. In this paper, we modify a shuffle attention network and introduce it into GAN to generate higher quality pictures with limited inputs. In addition, we improved the existing resize method and proposed an equal stretch resize method to solve the problem of image distortion caused by different input sizes. In the experiment, we also embed the newly proposed coordinate attention (CA) module into the backbone network as a control test. Qualitative indexes and six quantitative evaluation indexes were used to evaluate the experimental results, which show that, compared with other GANs used for picture generation, the modified Shuffle Attention GAN proposed in this paper can generate more refined and high-quality diversified aircraft pictures with more detailed features of the object under limited datasets.

Geospatial information system for agricultural monitoring

2013 ◽  
Vol 49 (1) ◽  
pp. 124-132 ◽  
Author(s):  
A. Yu. Shelestov ◽  
A. N. Kravchenko ◽  
S. V. Skakun ◽  
S. V. Voloshin ◽  
N. N. Kussul
Keyword(s):  
Information System ◽  
Geospatial Information

A dynamic acceleration method for remote sensing image processing based on CUDA

2021 ◽  
Author(s):  
Xianyu Zuo ◽  
Zhe Zhang ◽  
Baojun Qiao ◽  
Junfeng Tian ◽  
Liming Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Remote Sensing Image ◽  
Acceleration Method ◽  
Remote Sensing Image Processing
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