Discussion of “Interfacing the geographic information system, remote sensing, and the soil conservation service-curve number method to estimate curve number and runoff volume in the ASIR region of Saudi Arabia” by Fawzi S. Mohammad, Jan Adamowski

2017 ◽  
Vol 10 (9) ◽  
Author(s):  
Ayman G. Awadallah ◽  
Mahmoud S. Farahat ◽  
Mohammed Haggag
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Saudi Arabia ◽  
Geographic Information System ◽  
Soil Conservation ◽  
Curve Number ◽  
Geographic Information ◽  
Soil Conservation Service ◽  
Asir Region ◽  
Service Curve

scholarly journals ASSESSING THE IMPACT OF URBANIZATION ON DIRECT RUNOFF IN DISTRICT 8, HO CHI MINH CITY

2021 ◽  
Vol 11 (3) ◽  
pp. 145-156
Author(s):  
Van Minh NGUYEN ◽  
Elena Yurievna ZAYKOVA
Keyword(s):  
Remote Sensing ◽  
Surface Runoff ◽  
Soil Conservation ◽  
Curve Number ◽  
Ho Chi Minh City ◽  
Soil Conservation Service ◽  
Impact Of Urbanization ◽  
Service Curve ◽  
The Impact ◽  
Scs Cn

Ho Chi Minh City (HCMC) is among the cities that are most at risk of fl ooding worldwide. Urbanization processes have led to a change in land use, which in turn has resulted in an increase in impervious surfaces and runoff , thus again leading to the risk of fl ooding in the city. The aim of the article is to study the impact of urban development (on the example of District 8 of HCMC) on surface runoff using a combination of the interpretation of remote sensing images of the earth (ERS) Google Earth and the SCS-CN model (the Soil Conservation Service curve number). Theoretical models are used to analyze the relationship between the typology of buildings and areas of open and impervious surfaces. The interpretation of remote sensing images was carried out in the ArcGIS program. The method used to calculate surface runoff is the Soil Conservation Service Curve Number (SCS-CN) method developed by the US Soil Conservation Service and is suitable for assessing the eff ects of land-use/land cover change due to urbanization. The results of the study show the volume of surface runoff in areas with diff erent levels of urbanization in district 8 of HCMC, assessing the impact of urbanization processes on surface runoff and revealing new opportunities for managing this process. The combination of remote sensing interpretation and SCS-CN model makes it possible to assess the impact of urban development on surface runoff . Urbanization and an increase in built-up area strongly aff ect fl ooding, reducing the soil retention.

scholarly journals A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods

2021 ◽  
Vol 13 (9) ◽  
pp. 1818
Author(s):  
Lisha Ding ◽  
Lei Ma ◽  
Longguo Li ◽  
Chao Liu ◽  
Naiwen Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Flash Flood ◽  
Flash Floods ◽  
Geographic Information ◽  
Flood Disaster ◽  
Future Research ◽  
Time Zone ◽  
Gis Technologies

Flash floods are among the most dangerous natural disasters. As climate change and urbanization advance, an increasing number of people are at risk of flash floods. The application of remote sensing and geographic information system (GIS) technologies in the study of flash floods has increased significantly over the last 20 years. In this paper, more than 200 articles published in the last 20 years are summarized and analyzed. First, a visualization analysis of the literature is performed, including a keyword co-occurrence analysis, time zone chart analysis, keyword burst analysis, and literature co-citation analysis. Then, the application of remote sensing and GIS technologies to flash flood disasters is analyzed in terms of aspects such as flash flood forecasting, flash flood disaster impact assessments, flash flood susceptibility analyses, flash flood risk assessments, and the identification of flash flood disaster risk areas. Finally, the current research status is summarized, and the orientation of future research is also discussed.

scholarly journals Quantitative Analysis of Catchment Using Remote Sensing and Geographic Information System

2015 ◽  
Vol 4 ◽  
pp. 1421-1428 ◽  
Author(s):  
D. Sindhu ◽  
Sadashivappa ◽  
A.S. Ravikumar ◽  
B.L. Shivakumar
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Quantitative Analysis ◽  
Geographic Information System ◽  
Geographic Information
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