Flood Disaster Monitoring and Evaluation System Based on GIS and Remote Sensing: Case Study in Hejiang River

2012 ◽  
Vol 239-240 ◽  
pp. 560-564
Author(s):  
Tao Sun ◽  
Rong Li ◽  
Hai Ying Deng ◽  
Xiao Tao Li
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation System ◽  
Flood Control ◽  
Monitoring And Evaluation ◽  
Flood Disaster ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Observation Area ◽  
Seamless Connection

Flood disaster occurs frequently in Hejiang watershed, Guangxi province which causes huge economic and social losses. Remote sensing technique (RS) has the advantage of quickness, economy, objectiveness and large observation area. As is known to all, geographic information system (GIS) is good at analyzing and dealing with spatial data. Based on GIS, RS and hydrological and hydraulic models, flood disaster evaluation system of Hejiang river is developed which realizes the seamless connection of GIS platform with Xinanjiang model and Muskingum model. GIS system combined with necessary information obtained from remote sensing images could extract useful thematic information of flood disaster, which is meaningful to flood control and disaster relief of local authorities.

Remote Sensing Technology in Flood Monitoring and Assessment Application

2013 ◽  
Vol 411-414 ◽  
pp. 1495-1500
Author(s):  
Xiao Tao Li ◽  
Shi Feng Huang ◽  
Gai Le ◽  
Ya Yong Sun
Keyword(s):  
Remote Sensing ◽  
Evaluation System ◽  
Monitoring And Evaluation ◽  
Development Trend ◽  
Flood Disaster ◽  
Remote Sensing Monitoring ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Disaster Monitoring ◽  
Research Situation

This paper expounds the research situation of remote sensing technology in the flood disaster monitoring and evaluation. And some of the application of domestic and foreign better remote sensing monitoring and evaluation system of flood disaster are introduced in this paper. Some current problems of remote sensing monitoring and evaluation of flood disaster and the future development trend are also presented in this paper.

scholarly journals A Precision Evaluation Method for Remote Sensing Data Sampling Based on Hexagon Discrete Grid

2020 ◽  
Author(s):  
Yue Ma ◽  
Guoqing Li ◽  
Xiaochuang Yao ◽  
Jin Ben ◽  
Qianqian Cao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation System ◽  
Evaluation Method ◽  
Remote Sensing Data ◽  
Accuracy Evaluation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Hexagonal Grids ◽  
Discrete Grid

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

Use of GIS and Remote Sensing for Landslide Susceptibility Mapping

2019 ◽  
pp. 384-398 ◽  
Author(s):  
Arzu Erener ◽  
Gulcan Sarp ◽  
Sebnem H. Duzgun
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Geographical Information Systems ◽  
Vegetation Index ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Gis And Remote Sensing ◽  
Data Layers

In recent years, geographical information systems (GISs) and remote sensing (RS) have proven to be common tools adopted for different studies in different scientific disciplines. GIS is defined as a set of tools for the input, storage, retrieval, manipulation, management, modeling, analysis, and output of spatial data. RS, on the other hand, can play a role in the production of a data and in the generation of thematic maps related to spatial studies. This study focuses on use of GIS and RS data for landslide susceptibility mapping. Five factors including normalized difference vegetation index (NDVI) and topographic wetness index (TWI), slope, lineament density, and distance to roads were used for the grid-based approach for landslide susceptibility mappings. Results of this study suggest that geographic information systems can effectively be used to obtain susceptibility maps by compiling and overlaying several data layers relevant to landslide hazards.

scholarly journals Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 12 ◽  
Author(s):  
Mohd Khairul Amri Kamarudin ◽  
Kabir Abdulkadir Gidado ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Roslan Umar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Geographical Information ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Multi Temporal ◽  
Vegetation Water

Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC found to be 100%, 88.83%, 86.15%, 81.91% in 1976, 1989, 2001 and 2016 respectively. While water body accounts for 0%, 11.17%, 12.36% and 13.62% in the years 1976, 1989, 2001 and 2016 respectively and built-up area 1.49% and 4.47 in 2001 and 2016 respectively. The predominant LC changes in the study are the water body and vegetation, the earlier increasing rapidly at the expense of the later. Therefore, proper monitoring, policies that integrate conservation of the environment are strongly recommended. 

scholarly journals Geo Information Systems &Remote Sensing: Applications in Environmental Systems & Management

2020 ◽  
pp. 11-18
Author(s):  
P.K. Paul ◽  
P. S. Aithal ◽  
A. Bhuimali ◽  
K.S. Tiwary ◽  
R. Saavedra ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Information Science ◽  
Spatial Information ◽  
Physical Content ◽  
Gis And Remote Sensing ◽  
Interdisciplinary Field ◽  
Sensing Applications ◽  
Database Technology ◽  
Remote Sensing Applications

Geo Informatics is an interdisciplinary field responsible for spatial information related activities. Geo Informatics is close to the Geo Information Science, Geo Information System, Remote Sensing, etc. Geo Informatics is a combination of Geo Science and Information Science and here different kinds of IT and Computing tools are being used such as Database Technology, Network Technology, Web Technology, Multimedia Technology, etc in the spatial data management. Remote Sensing is considered as a component of Geo Information Science dedicated in gathering of information on the different types of objects without physical content and applicable in different areas of the geography, survey of land and different type of geo related areas viz. Hydrology, Ecology, Meteorology, Oceanography and Geology, etc. The term remote sensing is also called as GIS & RS due to their relationship and their importance. The applications of the IT in Geography and allied areas are called as Geo Informatics or Geo Information Science. Similarly, the applications and utilization of IT, Information Science and Computing in Environment and allied areas are known as Environmental Informatics or Environmental Information Science. The GIS and Remote Sensing applications in the environment and ecological areas are increasing rapidly and it includes various existing and emerging applications. This paper talks about the applications of the GIS and RS in Environmental Applications and Management.

scholarly journals Planform Dynamics of Kankai River using GIS and Remote Sensing

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Md Shahnawaz Alam ◽  
Ajai Singh
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
West Bengal ◽  
Water Levels ◽  
Erosion And Deposition ◽  
Gis And Remote Sensing ◽  
Migration Rates ◽  
River Training ◽  
Erosion And Accretion ◽  
Large Quantum

The Kankai river is a rainfed perennial river of eastern Nepal and carries a large quantum of silt, and enters in Kishanganj of West Bengal, India. Recently, a bridge collapsed in a village in the Kishanganj district due to a rise in the water levels of the Kankai river. This paper presents a study of the dynamics of changes in channel planform and measurement of the erosion and accretion of the Kankai river in Bihar, India from 2000 to 2018. Spatial data were processed in GIS to determine the changes in sinuosity, centreline migration rates, and extent of erosion, and deposition of sediment. The maximum river shift was obtained as 800 to 1600 m and the minimum river shift varied from 6 to 70 m. With a sinuosity ratio for the whole reach of the river of 1.45, the Kankai river is considered a sinuous river and needs river training works at the erosion sites.

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