1 December 27, 2022
Articles
1. Thi Nam Phuong Doan, Van Trung Nguyen, Thi Thanh Hoa Pham, Thanh Ha Tran, Thi Thu Ha Le
Forest Fire Risk Assessment and Mapping Using Support Vector Machine Algorithm, A Case Study in Nghe An Province, Vietnam
European Geographical Studies. 2022. 9(1): 3-11.
Number of views: 70 Download in PDF
2. Kim Dung Le, Thi Lan PhamEuropean Geographical Studies. 2022. 9(1): 3-11.
Abstract:
In recent years, forest fires have occurred frequently in Vietnam due to the influence of climate change and human activities. This paper presents the results of modeling the risk of forest fires in the west of Nghe An province (north-central Vietnam) from remote sensing and GIS data. 09 factors affect the risk of forest fire, including vegetation cover (NDVI index), soil moisture (NMDI index), elevation, slope, aspect, wind speed, land surface temperature, average monthly precipitation and population density are used to build a model for mapping forest fire risk based on Suppor Vector Machine (SVM) algorithm. The past forest fire data is collected from the database of the Forest Protection Department (Vietnam Ministry of Agriculture and Rural Development) to evaluate the accuracy of the model. Different values of cost parameter (C) are tested to select the value with the highest accuracy in predicting forest fire risk. The results obtained in the study can be used effectively for monitoring and early warning of forest fire risk in the localities, helping to reduce damage caused by forest fires.
In recent years, forest fires have occurred frequently in Vietnam due to the influence of climate change and human activities. This paper presents the results of modeling the risk of forest fires in the west of Nghe An province (north-central Vietnam) from remote sensing and GIS data. 09 factors affect the risk of forest fire, including vegetation cover (NDVI index), soil moisture (NMDI index), elevation, slope, aspect, wind speed, land surface temperature, average monthly precipitation and population density are used to build a model for mapping forest fire risk based on Suppor Vector Machine (SVM) algorithm. The past forest fire data is collected from the database of the Forest Protection Department (Vietnam Ministry of Agriculture and Rural Development) to evaluate the accuracy of the model. Different values of cost parameter (C) are tested to select the value with the highest accuracy in predicting forest fire risk. The results obtained in the study can be used effectively for monitoring and early warning of forest fire risk in the localities, helping to reduce damage caused by forest fires.
Number of views: 70 Download in PDF
Shoreline Changes and Their Impacts on Tourism: A Case Study of Sam Son City, Thanh Hoa Province, Vietnam
European Geographical Studies. 2022. 9(1): 12-20.
Number of views: 77 Download in PDF
3. European Geographical Studies. 2022. 9(1): 12-20.
Abstract:
Sam Son has over 17 kilometers of coastline, making it advantageous for marine tourism and resort tourism. However, various types of research have confirmed that climate change has impacted on tourism activities. The change in shoreline can have a significant impact on tourism infrastructure, as it can alter the accessibility, safety, and attractiveness of coastal destinations. The aim of the paper is to analyze the shoreline change rate over 33 years (1989−2022) and its impacts on tourism in Sam Son. Multi-temporal satellite images were used to extract shorelines, and Digital Shoreline Analysis Systems (DSAS) was used to detect the rate of shoreline change. The results indicated that the shoreline change of Sam Son can be divided two parts, including the Hoi estuary zone and the Do River estuary area. In the Hoi estuary, the erosion rates range from -2.22 m/yr to -40.32 m/yr. Buiding FLC Sam Son for tourism is one of the causes of loss of sedimentation in this area. Additionally, in the Do River estuary, the rate of accretion has significantly increased, reaching to 9.7 m/yr. This phenomenon of sediment accumulation is the foundation for building resorts to serve tourism in Sam Son.
Sam Son has over 17 kilometers of coastline, making it advantageous for marine tourism and resort tourism. However, various types of research have confirmed that climate change has impacted on tourism activities. The change in shoreline can have a significant impact on tourism infrastructure, as it can alter the accessibility, safety, and attractiveness of coastal destinations. The aim of the paper is to analyze the shoreline change rate over 33 years (1989−2022) and its impacts on tourism in Sam Son. Multi-temporal satellite images were used to extract shorelines, and Digital Shoreline Analysis Systems (DSAS) was used to detect the rate of shoreline change. The results indicated that the shoreline change of Sam Son can be divided two parts, including the Hoi estuary zone and the Do River estuary area. In the Hoi estuary, the erosion rates range from -2.22 m/yr to -40.32 m/yr. Buiding FLC Sam Son for tourism is one of the causes of loss of sedimentation in this area. Additionally, in the Do River estuary, the rate of accretion has significantly increased, reaching to 9.7 m/yr. This phenomenon of sediment accumulation is the foundation for building resorts to serve tourism in Sam Son.
Number of views: 77 Download in PDF