This paper has developed a cost-efficient framework for flood vulnerability assessment at a local scale using a multi-parametric approach integrated with the Open Source Geographical Information System (GIS) and Open Remote Sensing data. The study focuses on generating a set of criteria considering three dimensions of flood vulnerability: exposure, sensitivity, and adaptive capacity (AC) on an index-based approach. These indicators were decided based on a robust analysis considering the physical and socio-economic conditions of the study area. The flood exposure was generated from the geomorphological and hydrological parameters integrated with the flood water depth, the distance to river channels, and the Modified Normalized Difference Water Index. The flood sensitivity was determined by the aggregation of local income, land use, poverty index, population density, and other parameters reflecting the socio-economic condition. The AC has been evaluated based on the Normalized Difference Vegetation Index, the density of the community service facilities, and other factors related to the coping capacity to flood. Finally, the flood vulnerability at the local scale was determined based on the integration of its contributing factors using the Analytical Hierarchical Process-based aggregated model. Results indicated that a total of 20 parameters impacted the flood vulnerability of the research area. The findings also confirmed that among the indicators of flood vulnerability of Danang City, the flood depth, land-use condition, and drainage system are the key factors affecting the vulnerability level. The empirical assessment showed that the study area is significantly affected by flood vulnerability with more than 60% of the area having the vulnerability level from moderate to very high. In addition, this paper points out that the vulnerability research should be localized and is not always based on the administrative units. This practice can make the decision-making process and adaptation plan more appropriate locally. Especially, this study attempted to evaluate the accuracy of the flood vulnerability map for the first time by using field survey data and the statistical report on flood damage that most of the previous studies have not conducted yet. This framework provides a valuable toolkit for flood management in data-scarce regions all over the world.
This study implemented an index-based approach to monitor drought in the Vu Gia – Thu Bon river basin using remote sensing data and Google Earth Engine (GEE) cloud computing services. Landsat’s time-series remote sensing data are effectively used to calculate various drought indices. In this investigation, we evaluated the performance of various remote sensing-based drought indices (RSDI) utilizing the cloud-based Google Earth Engine (GEE) computing platform. Results indicated that there was a significant correlation between RSDI and the in-situ Potential Evapotranspiration (PET) and the soil temperature. The empirical results of this study demonstrated the possible utility of remote sensing data in drought monitoring for data-scarce regions.
The study was carried out to determine the density of Vibrio sp. and Perkinsus sp. in cultured clams and evaluate the correlation between pathogenic microorganisms and disease incidence of white clams (Meretrix Lyrata) in Mekong Delta from March to May 2019. Clam samples were collected in different four regions (Ben Tre, Tra Vinh, Bac Lieu, and Tien Giang provinces) and there was mass mortality of clam in Tra Vinh province in May. In this assay, determination of the Vibrio sp. density was performed using Vibrio sp. selective Thiosulfate Citrate Bile Salt agar plates. Also, the Perkinsus sp. was cultured in Fluid thioglycollate medium to isolating the spore that effect to harmful for cultured clam. Then, T-test and one-way ANOVA analysis were used to access the impacts of those parameters on the clam health. Clams did not show specific clinical signs, and histological results showed minor injuries on their shells and gills. Correlation analysis revealed some biotic components related to clam health status; they were several Vibrio bacteria in clams were in the range of 0-2.23 x 10 5 (CFU/g). The presence of Perkinsus sp. was detected in the clam tissue with a prevalence of 53% of the ratio of infection and the infection intensity of 4.08-57.43 (spores/g). However, the density of Vibrio sp. and the ratio of infection of Perkinsus sp. on clam was no significant difference on outbreak disease and non-outbreak disease factor on clam samples (P>0.05) in the clam samples. Thus, dead clams can be caused by several other factors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.