Factors influencing people’s knowledge, attitude, and practice in land use dynamics: A case study in Ca Mau province in the Mekong delta, Vietnam

2018 ◽  
Vol 72 ◽  
pp. 227-238 ◽  
Author(s):  
Hanh Tran ◽  
Quoc Nguyen ◽  
Matthieu Kervyn
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juan Pablo Sarmiento ◽  
Catalina Sarmiento ◽  
Gabriela Hoberman ◽  
Meenakshi Chabba

PurposeThis study aims to assess knowledge retention of the graduates of the online graduate certificate on local development planning, land use management and disaster risk management (PDLOTGR, the abbreviation of the certificate's Spanish title). The certificate was offered to practitioners and faculty members of Latin American countries since 2016.Design/methodology/approachThe authors reviewed the knowledge, attitude and practice (KAP) method to develop a specific approach, which included the preparation of a KAP survey, a composite KAP index and three sub-indices. The survey targeted two groups: (1) experimental group, composed of the certificate's 76 graduates, and (2) control group, comprised of 25 certificate's candidates, who had not yet undergone the training/intervention. The statistical analysis included a one-way multivariate analysis of variance to compare the mean scores on the KAP index and sub-indices for individuals in the experimental and control groups.FindingsThe study results showed significant differences in the knowledge sub-index between those who had completed the PDLOTGR training and those who had not, while the attitudes and practices sub-indices did not show significant differences. When using the KAP index, a statistically significant difference was also observed between the two groups.Originality/valuePerceived knowledge assessment offers an acceptable and non-intimidating option for evaluating continuing education and professional development programs associated to disaster risk. It is particularly helpful in determining whether an intervention or program has a lasting impact. It is not, however, a substitute for direct knowledge assessment, and the use of other methods to evaluate the performance of a capacity building program's graduates.


2018 ◽  
Vol 73 ◽  
pp. 269-280 ◽  
Author(s):  
Thuy Ngan Le ◽  
Arnold K. Bregt ◽  
Gerardo E. van Halsema ◽  
Petra J.G.J. Hellegers ◽  
Lam-Dao Nguyen

2017 ◽  
Vol 25 (1) ◽  
pp. 34-45 ◽  
Author(s):  
Martina Slámová ◽  
Jana Krčmářová ◽  
Pavel Hronček ◽  
Mariana Kaštierová

Abstract The cadastral district of Horný Tisovník represents a traditionally managed Carpathian mountain agricultural landscape with extensive terraces. It was historically governed by two counties with different feudal economic systems - agricultural and industrial. This paper aims to enrich traditional methods in environmental history. We applied geospatial statistics and multivariate data analysis for the assessment of environmental factors influencing the distribution of agricultural terraces. Using linear models, the hypothesis was tested that the terrace distribution is functionally related to selected factors (affiliation to the historic counties; average altitude and slope; distance from water, buildings and settlements; units of natural potential vegetation; and current land use). Significantly greater amounts of terraces were located in the agricultural county compared to the industrial county. A principal component analysis showed the coincidence between the current agricultural land use and higher concentrations of terraces occurring in lower altitudes, closer to settlements and buildings, and within the unit of Carpathian oak-hornbeam forests. These findings regarding the most significant factors influencing the distribution of terraces are used in proposals for incentives to improve the management of the traditional agricultural landscape.


Cities ◽  
2016 ◽  
Vol 58 ◽  
pp. 39-49 ◽  
Author(s):  
Bo Mu ◽  
Audrey L. Mayer ◽  
Ruizhen He ◽  
Guohang Tian

Author(s):  
Rosazlin Abdullah ◽  
Anis Farhana Hanif ◽  
Sahrianisa Toufik ◽  
Rozainah Mohd Zakaria ◽  
Wan Rasidah Kadir ◽  
...  

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