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Dr. Duong Nong
Faculty of Natural Resources and Environment, Vietnam National University of Agriculture

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Research Keywords & Expertise

0 Landscape Analysis
0 Land cover and land use change
0 Urban environment remote sensing
0 GIS & Remote Sensing in Environment
0 Forest and Agriculture

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Journal article
Published: 11 June 2021 in Land
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We analyzed the agricultural land-use changes in the coastal areas of Tien Hai district, Thai Binh province, in 2005, 2010, 2015, and 2020, using Landsat 5 and Landsat 8 data. We used the object-oriented classification method with the maximum likelihood algorithm to classify six types of land uses. The series of land-use maps we produced had an overall accuracy of more than 80%. We then conducted a spatial analysis of the 5-year land-use change using ArcGIS software. In addition, we surveyed 150 farm households using a structured questionnaire regarding the impacts of climate change on agricultural productivity and land uses, as well as farmers’ adaptation and responses. The results showed that from 2005 to 2020, cropland decreased, while aquaculture land and forest land increased. We observed that the most remarkable decreases were in the area of rice (485.58 ha), the area of perennial crops (109.7 ha), and the area of non-agricultural land (747.35 ha). The area of land used for aquaculture and forest increased by 566.88 ha and 772.60 ha, respectively. We found that the manifestations of climate change, such as extreme weather events, saltwater intrusion, drought, and floods, have had a profound impact on agricultural production and land uses in the district, especially for annual crops and aquaculture. The results provide useful information for state authorities to design land-management strategies and solutions that are economic and effective in adapting to climate change.

ACS Style

Duong Nong; An Ngo; Hoa Nguyen; Thuy Nguyen; Lan Nguyen; Summet Saksena. Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam. Land 2021, 10, 627 .

AMA Style

Duong Nong, An Ngo, Hoa Nguyen, Thuy Nguyen, Lan Nguyen, Summet Saksena. Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam. Land. 2021; 10 (6):627.

Chicago/Turabian Style

Duong Nong; An Ngo; Hoa Nguyen; Thuy Nguyen; Lan Nguyen; Summet Saksena. 2021. "Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam." Land 10, no. 6: 627.

Research article
Published: 30 March 2021 in Environment and Urbanization ASIA
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The process by which cities (or urban areas) expand over time has remained a key focus for geographers, ecologists and other scientists interested in urban phenomena for decades. This study investigated the use of spatial metrics and population data for defining and mapping rural-urban transition zones in Hanoi and exploring urban growth models. The analysis showed that in 2010, about 30% of communes within Hanoi could be defined as rural, 38% as peri-urban and 32% as urban. The peri-urban communes showed a greater level of landscape fragmentation and a higher pace of population growth than rural communes. The urban landscape of Hanoi in 2010 shows characteristics of both transportation corridors and dispersed sites models—the two least eco-friendly models of urbanization. This study provides an effective method for mapping such rural-urban transition and identifies forms of urbanization in places where other socio-economic data sources are limited. This is particularly useful for planners and development agencies that require reliable methods for collecting and analysing data, which can enable them to assess variables along the rural-to-urban continuum.

ACS Style

Du’O’Ng H. Nông; Jefferson M. Fox; Sumeet Saksena; Christopher A. Lepczyk. The Use of Spatial Metrics and Population Data in Mapping the Rural-Urban Transition and Exploring Models of Urban Growth in Hanoi, Vietnam. Environment and Urbanization ASIA 2021, 12, 156 -168.

AMA Style

Du’O’Ng H. Nông, Jefferson M. Fox, Sumeet Saksena, Christopher A. Lepczyk. The Use of Spatial Metrics and Population Data in Mapping the Rural-Urban Transition and Exploring Models of Urban Growth in Hanoi, Vietnam. Environment and Urbanization ASIA. 2021; 12 (1):156-168.

Chicago/Turabian Style

Du’O’Ng H. Nông; Jefferson M. Fox; Sumeet Saksena; Christopher A. Lepczyk. 2021. "The Use of Spatial Metrics and Population Data in Mapping the Rural-Urban Transition and Exploring Models of Urban Growth in Hanoi, Vietnam." Environment and Urbanization ASIA 12, no. 1: 156-168.

Journal article
Published: 11 March 2020 in VNU Journal of Science: Earth and Environmental Sciences
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This study focuses on the environmental pressure of waste generated from pig farming in Yen Dung district. Terrain analysis of the digital elevation model (DEM) was used to delineate the sub-basin map where pollutants accumulated. Then we combined this map with land use map and statistical data for determining the distribution of pollutant discharged sources. Based on the pollution load coefficient prescribed by the Vietnam Environment Administration, the loads from all sources, including pig farming, were estimated for entire sub-basins within the district. The results show that the pollutant load from pig farming accounts for a large proportion and creates a major pressure on the local environment. The pollutant from pig farming greatly influences the spatial distribution of pollutant loads across sub-basins. Therefore, special attention should be paid to the waste management at pig farms (households and farm) to ensure the effectiveness of the environmental protection for the communities. Keywords: livestock waste, pollutant load mapping, pig farming.

ACS Style

Ngo The An; Ngo Phuong Lan; Vo Huu Cong; Nong Huu Duong; Nguyen Thi Huong Giang. Environmental Pressure from Pig Farming to Surface Water Quality Management in Yen Dung District Bac Giang Province. VNU Journal of Science: Earth and Environmental Sciences 2020, 36, 1 .

AMA Style

Ngo The An, Ngo Phuong Lan, Vo Huu Cong, Nong Huu Duong, Nguyen Thi Huong Giang. Environmental Pressure from Pig Farming to Surface Water Quality Management in Yen Dung District Bac Giang Province. VNU Journal of Science: Earth and Environmental Sciences. 2020; 36 (1):1.

Chicago/Turabian Style

Ngo The An; Ngo Phuong Lan; Vo Huu Cong; Nong Huu Duong; Nguyen Thi Huong Giang. 2020. "Environmental Pressure from Pig Farming to Surface Water Quality Management in Yen Dung District Bac Giang Province." VNU Journal of Science: Earth and Environmental Sciences 36, no. 1: 1.

Research article
Published: 07 May 2018 in PLoS ONE
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Urbanization has been driven by various social, economic, and political factors around the world for centuries. Because urbanization continues unabated in many places, it is crucial to understand patterns of urbanization and their potential ecological and environmental impacts. Given this need, the objectives of our study were to quantify urban growth rates, growth modes, and resultant changes in the landscape pattern of urbanization in Hanoi, Vietnam from 1993 to 2010 and to evaluate the extent to which the process of urban growth in Hanoi conformed to the diffusion-coalescence theory. We analyzed the spatiotemporal patterns and dynamics of the built-up land in Hanoi using landscape expansion modes, spatial metrics, and a gradient approach. Urbanization was most pronounced in the periods of 2001–2006 and 2006–2010 at a distance of 10 to 35 km around the urban center. Over the 17 year period urban expansion in Hanoi was dominated by infilling and edge expansion growth modes. Our findings support the diffusion-coalescence theory of urbanization. The shift of the urban growth areas over time and the dynamic nature of the spatial metrics revealed important information about our understanding of the urban growth process and cycle. Furthermore, our findings can be used to evaluate urban planning policies and aid in urbanization issues in rapidly urbanizing countries.

ACS Style

Duong H. Nong; Christopher A. Lepczyk; Tomoaki Miura; Jefferson M. Fox. Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics. PLoS ONE 2018, 13, e0196940 .

AMA Style

Duong H. Nong, Christopher A. Lepczyk, Tomoaki Miura, Jefferson M. Fox. Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics. PLoS ONE. 2018; 13 (5):e0196940.

Chicago/Turabian Style

Duong H. Nong; Christopher A. Lepczyk; Tomoaki Miura; Jefferson M. Fox. 2018. "Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics." PLoS ONE 13, no. 5: e0196940.

Journal article
Published: 29 March 2017 in Remote Sensing
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We performed a multi-date composite change detection technique using a dense-time stack of Landsat data to map land-use and land-cover change (LCLUC) in Mainland Southeast Asia (MSEA) with a focus on the expansion of boom crops, primarily tree crops. The supervised classification was performed using Support Vector Machines (SVM), which are supervised non-parametric statistical learning techniques. To select the most suitable SMV classifier and the related parameter settings, we used the training data and performed a two-dimensional grid search with a three-fold internal cross-validation. We worked in seven Landsat footprints and found the linear kernel to be the most suitable for all footprints, but the most suitable regularization parameter C varied across the footprints. We distinguished a total of 41 LCLUCs (13 to 31 classes per footprint) in very dynamic and heterogeneous landscapes. The approach proved useful for distinguishing subtle changes over time and to map a variety of land covers, tree crops, and transformations as long as sufficient training points could be collected for each class. While to date, this approach has only been applied to mapping urban extent and expansion, this study shows that it is also useful for mapping change in rural settings, especially when images from phenologically relevant acquisition dates are included.

ACS Style

Kaspar Hurni; Annemarie Schneider; Andreas Heinimann; Duong H. Nong; Jefferson Fox. Mapping the Expansion of Boom Crops in Mainland Southeast Asia Using Dense Time Stacks of Landsat Data. Remote Sensing 2017, 9, 320 .

AMA Style

Kaspar Hurni, Annemarie Schneider, Andreas Heinimann, Duong H. Nong, Jefferson Fox. Mapping the Expansion of Boom Crops in Mainland Southeast Asia Using Dense Time Stacks of Landsat Data. Remote Sensing. 2017; 9 (4):320.

Chicago/Turabian Style

Kaspar Hurni; Annemarie Schneider; Andreas Heinimann; Duong H. Nong; Jefferson Fox. 2017. "Mapping the Expansion of Boom Crops in Mainland Southeast Asia Using Dense Time Stacks of Landsat Data." Remote Sensing 9, no. 4: 320.

Journal article
Published: 17 December 2015 in Land
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In 1986, the Government of Vietnam implemented free market reforms known as Doi Moi (renovation) that provided private ownership of farms and companies, and encouraged deregulation and foreign investment. Since then, the economy of Vietnam has achieved rapid growth in agricultural and industrial production, construction and housing, and exports and foreign investments, each of which have resulted in momentous landscape transformations. One of the most evident changes is urbanization and an accompanying loss of agricultural lands and open spaces. These rapid changes pose enormous challenges for local populations as well as planning authorities. Accurate and timely data on changes in built-up urban environments are essential for supporting sound urban development. In this study, we applied the Support Vector Machine classification (SVM) to multi-temporal stacks of Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images from 1993 to 2010 to quantify changes in built-up areas. The SVM classification algorithm produced a highly accurate map of land cover change with an overall accuracy of 95%. The study showed that most urban expansion occurred in the periods 2001–2006 and 2006–2010. The analysis was strengthened by the incorporation of population and other socio-economic data. This study provides state authorities a means to examine correlations between urban growth, spatial expansion, and other socio-economic factors in order to not only assess patterns of urban growth but also become aware of potential environmental, social, and economic problems.

ACS Style

Duong H. Nong; Jefferson Fox; Tomoaki Miura; Sumeet Saksena. Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data. Land 2015, 4, 1213 -1231.

AMA Style

Duong H. Nong, Jefferson Fox, Tomoaki Miura, Sumeet Saksena. Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data. Land. 2015; 4 (4):1213-1231.

Chicago/Turabian Style

Duong H. Nong; Jefferson Fox; Tomoaki Miura; Sumeet Saksena. 2015. "Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data." Land 4, no. 4: 1213-1231.

Research article
Published: 23 September 2015 in PLoS ONE
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Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the ‘convergence model’ was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model’s predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.

ACS Style

Sumeet Saksena; Jefferson Fox; Michael Epprecht; Chinh C. Tran; Duong Nong; James H. Spencer; Lam Nguyen; Melissa L. Finucane; Vien D. Tran; Bruce A. Wilcox. Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam. PLoS ONE 2015, 10, e0138138 .

AMA Style

Sumeet Saksena, Jefferson Fox, Michael Epprecht, Chinh C. Tran, Duong Nong, James H. Spencer, Lam Nguyen, Melissa L. Finucane, Vien D. Tran, Bruce A. Wilcox. Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam. PLoS ONE. 2015; 10 (9):e0138138.

Chicago/Turabian Style

Sumeet Saksena; Jefferson Fox; Michael Epprecht; Chinh C. Tran; Duong Nong; James H. Spencer; Lam Nguyen; Melissa L. Finucane; Vien D. Tran; Bruce A. Wilcox. 2015. "Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam." PLoS ONE 10, no. 9: e0138138.

Journal article
Published: 12 February 2014 in Land
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The urban transition that has emerged over the past quarter century poses new challenges for mapping land cover/land use change (LCLUC). The growing archives of imagery from various earth-observing satellites have stimulated the development of innovative methods for change detection in long-term time series. We tested two different multi-temporal remote sensing datasets and techniques for mapping the urban transition. Using the Red River Delta of Vietnam as a case study, we compared supervised classification of dense time stacks of Landsat data with trend analyses of an annual series of night-time lights (NTL) data from the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS). The results of each method were corroborated through qualitative and quantitative GIS analyses. We found that these two approaches can be used synergistically, combining the advantages of each to provide a fuller understanding of the urban transition at different spatial scales.

ACS Style

Miguel Castrence; Duong H. Nong; Chinh C. Tran; Luisa Young; Jefferson Fox. Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam. Land 2014, 3, 148 -166.

AMA Style

Miguel Castrence, Duong H. Nong, Chinh C. Tran, Luisa Young, Jefferson Fox. Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam. Land. 2014; 3 (1):148-166.

Chicago/Turabian Style

Miguel Castrence; Duong H. Nong; Chinh C. Tran; Luisa Young; Jefferson Fox. 2014. "Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam." Land 3, no. 1: 148-166.