VNU-UET Repository: No conditions. Results ordered -Date Deposited. 2024-03-29T10:04:33ZEPrintshttp://eprints.uet.vnu.edu.vn/images/sitelogo.pnghttps://eprints.uet.vnu.edu.vn/eprints/2020-12-23T14:22:37Z2020-12-23T14:22:37Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4322This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/43222020-12-23T14:22:37ZAnalysis of CALIPSO satellite imagery for air pollution source identification in Hanoi, VietnamTuan Vinh TranVan Ha PhamThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2020-12-23T14:20:27Z2020-12-23T14:20:27Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4320This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/43202020-12-23T14:20:27ZParticulate Matter Concentration Mapping from Satellite ImageryThi Nhat Thanh Nguyenthanhntn@vnu.edu.vnViet Hung LuuVan Ha PhamQuang Hung Buihungbq@vnu.edu.vnThi Kim Oanh Nguyen2020-12-23T14:19:54Z2020-12-23T14:19:54Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4318This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/43182020-12-23T14:19:54ZRemote Sensing ProductsVan Ha PhamViet Hung LuuAnh PhanDominique LafflyQuang Hung Buihungbq@vnu.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2020-12-23T14:19:00Z2020-12-23T14:19:00Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4316This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/43162020-12-23T14:19:00ZRemote Sensing Case StudiesVan Ha PhamThi Nhat Thanh Nguyenthanhntn@vnu.edu.vnDominique Laffly2020-10-09T07:10:25Z2020-10-09T07:10:25Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/4071This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/40712020-10-09T07:10:25ZApplication of WRF-Chem to simulate air quality over Northern VietnamThe WRF-Chem (Weather Research and Forecasting with Chemistry) model is implemented and validated against ground-based observations for meteorological and atmospheric variables for the first time in Northern Vietnam. The WRF-Chem model was based on HTAPv2 emission inventory with MOZCART chemical-aerosol mechanism to simulate atmospheric variables for winter (January) and summer (July) of 2014. The model satisfactorily reproduces meteorological fields, such as temperature 2 m above the ground and relative humidity 2 m above the ground at 45 NCHMF meteorological stations in January, but lower agreement was found in those simulations of July. PM10 and PM2.5 concentrations in January showed good temporal and spatial agreements to observations recorded at three CEM air monitoring stations in Phutho, Quangninh, and Hanoi, with correlation coefficients of 0.36 and 0.59. However, WRF-Chem model was underestimated with MFBs from − 27.9 to − 118.7% for PM10 levels and from − 34.2 to − 115.1% for PM2.5 levels. It has difficulty in capturing day-by-day variation of PM10 and PM2.5 concentrations at each station in July, but MFBs were in the range from − 27.1 to − 40.2% which is slightly lower than those in January. It suggested that further improvements of the model and local emission data are needed to reduce uncertainties in modeling the distribution of atmospheric pollutants. Assessment of biomass burning emission on air quality in summer was analyzed to highlight the application aspect of the WRF-Chem model. The study may serve as a reference for future air quality modeling using WRF-Chem in Vietnam.Thi Nhu Ngoc Dongocdtn@fimo.edu.vnXuan Truong Ngotruongnx@fimo.edu.vnVan Ha Phamhapv@fimo.edu.vnNhu Luan Vuongluannv@cem.gov.vnHoang Anh LeChau Thuy PhamQuang Hung Buihungbq@vnu.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2020-01-04T05:40:54Z2020-01-04T05:41:44Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3799This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/37992020-01-04T05:40:54ZEvaluation of Maximum Likelihood Estimation and regression methods for fusion of multiple satellite Aerosol Optical Depth data over VietnamThis paper applied different data fusion methods including Maximum Likelihood Estimation (MLE) and Linear Regression methods on satellite images over Vietnam areas from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. In comparison with ground station Aerosol Robotic Network (AERONET), the regression method is better than Maximum Likelihood Estimator (MLE). Our results show that the fusion methods can improve both data coverage and quality of satellite aerosol optical depth (AOD). Strong correlations were observed between fused AOD and AERONET AOD (R 2 = 0.8118, 0.7511 for Terra regression and MLE method, respectively). This paper presented the evaluation of data fusion algorithm and highlighted its importance on the satellite AOD data coverage and quality methods from multiple sensors.Van Ha Phamhapv@fimo.edu.vnXuan Truong NgoDominique LafflyAstrid JourdanThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2019-06-20T22:32:58Z2019-06-20T22:32:58Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3499This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/34992019-06-20T22:32:58ZAir pollution monitoring network using low-cost sensors, a case study in Hanoi, VietnamAir pollution is a serious problem in Vietnam, especially in urban areas with high pressures of population, traffic, construction, and industrial development. Besides high accurate measurements from automatic and continuous monitoring ground stations and high-cost sensor devices, low-cost sensors have recently utilized to extent air pollution monitoring networks although their data quality is still argumentative. In this paper, we present a low-cost device, named FAirKit, which measured 6 basic air pollutants including PM2.5, PM10, CO, O3, NO2, and SO2, and temperature and relative humidity. The sensors are calibrated with standard devices to improve their data quality. FAirKits are installed and transferred data in real-time to servers where an information system based on Sensor Web Enablement (SWE) standard of Open Geospatial Consortium (OGC) has been developed to store, process, and visualize real-time air pollution information. Currently, the low-cost sensors network has been deploying in Hanoi, Vietnam to enhance public awareness and alert local people to air pollution.Thi Nhat Thanh Nguyenthanhntn@vnu.edu.vnDuc Van Havanhd@fimo.edu.vnThi Nhu Ngoc Dongocdtn@fimo.edu.vnVan Hai Nguyenhainv@fimo.edu.vnXuan Truong Ngotruongnx@fimo.edu.vnVan Ha Phamhapv@fimo.edu.vnNgoc Duc Nguyenducnn@fimo.edu.vnQuang Hung Buihungbq@vnu.edu.vn2019-06-20T22:32:26Z2019-06-20T22:32:26Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3498This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/34982019-06-20T22:32:26ZAnalyzing the impacts of urban expansion on air pollution in Vietnam using the SEAP platformThe relationship between urbanization and air pollution was discovered in many studies. In this study, we analyzed the impacts of urban expansion on air pollution in Vietnam using remotely-sensed data from 2004 to 2015. In this period of time, Vietnam urban square was increased from 4623 km2 in 2004 to 5094 km2 in 2015. Besides, there is a clear difference between the average PM2.5 concentration value of urban areas and non-urban areas in Vietnam, urban PM2.5 values are generally higher than in rural areas for years. In this study, we use the SEAP (big Spatial data Exploration and Analysis Platform) platform to analyze and store data.Tuan Dung Phamdungpt@fimo.edu.vnVan Ha Phamhapv@fimo.edu.vnQuang Thang Luuthanglq@fimo.edu.vnXuan Truong Ngotruongnx@fimo.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vnQuang Hung Buihungbq@vnu.edu.vn2018-10-29T04:28:31Z2018-10-29T04:28:31Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3129This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/31292018-10-29T04:28:31ZCurrent Status of PM2.5 Pollution and its Mitigation in VietnamVietnam is experiencing serious fine particulate matter (PM2.5) pollution as a result of local activities and long-range transport (LRT) pollutants. In this article, we summarize and analyze PM2.5 data from ground stations and manual measurements showing PM2.5 status, characteristics and emission sources in the period from 1996 to 2017 in Vietnam. In addition, we provide a brief impact assessment of PM2.5 pollution on public health regarding diseases and deaths. Conscious of PM2.5's harmful effects, Vietnam has been taking steps to mitigate PM2.5 pollution in various forms through efforts by the government, non-governmental organizations, media, communities and individuals, and has obtained initial results. This article presents a comprehensive review of current PM2.5 pollution and its mitigation in Vietnam.Thi Nhat Thanh Nguyenthanhntn@vnu.edu.vnHoang Anh LeThi Minh Tra MacThi Trang Nhung NguyenVan Ha PhamQuang Hung Buihungbq@vnu.edu.vn2018-10-29T04:24:41Z2018-10-29T04:24:41Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3132This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/31322018-10-29T04:24:41ZAssessment of georeferencing methods on MODIS Terra/Aqua and VIIRS NPP satellite images in VietnamIn this study, several georeferencing methods such as Polynomial, Thin Plate Spline (TPS) and geolocation transformations are applied on satellite images over Vietnam areas from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard Terra/Aqua satellites and Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi National Polar-orbiting Partnership (NPP) satellite. In comparison with global administrative areas data, the georeferenced images of TPS function have a better fitting than Polynomial function. In addition, the experimental results highlighted the effect of georeferencing methods on satellite aerosol optical depth (AOD) data in which TPS function produce a higher quality than Polynomial function on both MODIS Terra/Aqua and VIIRS AOD images. Validation results indicated strong correlation between AERONET AOD and TPS georeferenced images (R2 = 0.739, 0.537 and 0.596 for MODIS Terra, MODIS Aqua and VIIRS AOD, respectively) meanwhile these correlations of Polynomial are lower (R2 = 0.596, 0.443 and 0.475 for MODIS Terra, MODIS Aqua and VIIRS AOD, respectively). The
correlations between MODIS AOD and VIIRS AOD images are also affected by georeferencing methods. The average of these correlations on TPS georeferenced images is 0.72 meanwhile mean correlation of Polynomial is 0.51. This study focused on the assessment of georeferencing methods and highlighted the effect of these methods on the quality and correlation of satellite AOD images.Van Ha Phamhapv@fimo.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vnQuang Hung Buihungbq@vnu.edu.vnPascal KleinJourdan AstridLaffly Dominique2017-12-12T07:47:56Z2017-12-12T07:47:56Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2767This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/27672017-12-12T07:47:56ZSatellite Aerosol Optical Depth over Vietnam, an analysis from VIIRS and CALIOP aerosol products.Tuan Vinh Tranvinhtt@fimo.edu.vnVan Ha Phamhapv@fimo.edu.vnXuan Thanh PhamXuan Anh NguyenQuang Hung Buihungbq@vnu.edu.vnThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vnThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2016-05-23T03:04:06Z2016-05-23T03:04:47Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1547This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/15472016-05-23T03:04:06ZMô hình hóa nồng độ bụi sử dụng ảnh vệ tinhViệc sử dụng dữ liệu ảnh sol khí trong giám sát ô nhiễm bụi là một hướng tiếp cận mới và hứa hẹn [1, 3, 5 - 8]. Các ảnh sol khí có thể được tích hợp với dữ liệu quan trắc bụi trong các mô hình ước tính mức độ ô nhiễm nhằm tăng chất lượng tính toán và dự đoán của các mô hình này.
Tại Việt Nam, việc kiểm soát và tính toán lượng bụi và chất lượng không khí từ các tham số đo đạc trên các vùng thí điểm cũng đã được đề cập đến trong nhiều nghiên cứu. Tuy nhiên, việc sử dụng và khai thác các thông tin từ vệ tinh cho bài toán mô hình hoá hoặc ước lượng mức độ ô nhiễm không khí chưa được quan tâm và nghiên cứu rộng rãi tại Việt Nam. Đề tài “Mô hình hóa nồng độ bụi sử dụng ảnh vệ tinh” được nghiên cứu nhằm kế thừa và áp dụng phương pháp sử dụng ảnh vệ tinh cho bài toán Ô nhiễm không khí còn rất hạn chế ở Việt Nam. Đề tài tập trung vào giải quyết các nội dung chính như sau:
➢ Nội dung 1: Các kỹ thuật nâng cao chất lượng sản phẩm sol khí: Các phương pháp, kỹ thuật như Merging (SAA, MLE, WPC), Nội suy IO, Kriging, Phương pháp biến đổ 3D-Var, 4D-Var, bộ lọc Kalman được sử dụng nhằm nâng cao chất lượng sản phẩm sol khí.
➢ Nội dung 2: Xây dựng mô hình ước tính nồng độ Ô nhiễm bụi từ ảnh vệ tinh: Các mô hình ước tính như hồi quy, SVM, Neural Network… được thực nghiệm và đánh giá để tìm ra mô hình ước tính tốt nhất cho dữ liệu trên vùng nghiên cứu.
➢ Nội dung 3: Phân tích và đánh giá ảnh hưởng của Ô nhiễm bụi: Bản đồ nồng độ bụi PM được ước tính từ mô hình được sử dụng cho các bài toán đánh giá ảnh hưởng của Ô nhiễm không khí đế các lĩnh vực khác như sức khỏe cộng đồng [2, 4, 9] (Tỉ lệ tử vong, số lượng bệnh nhân tim mạch, ưng thư…), ảnh hưởng đến nông nghiệp, biến đối khí hậu.Van Ha PhamThi Nhat Thanh Nguyenthanhntn@vnu.edu.vn2015-12-16T07:44:41Z2016-03-27T08:04:30Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1420This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/14202015-12-16T07:44:41ZAir Pollution Monitoring and Warning SystemNowaday, remote sensing images have provided a large dataset with geospatial information at global scale at different resolutions, which is widely using in various domains. The usage of satellite technology for air pollution monitoring applications has been recently increasing especially to provide global-to-local distribution of aerosol and its properties for deriving Particulate Matter concentration (PM). The paper investigates aerosol retrieval for multi- resolution satellite images. After that, PM is estimated from aerosol products and meteorological parameters in order to provide dust observations at different spatial scales. A geographic information system for air pollution monitoring and warning is developed based on these research results.Thi Nhat Thanh Nguyenthanhntn@vnu.edu.vnQuang Hung Buihungbq@vnu.edu.vnChinh Ke LuongViet Hung LuuVan Ha PhamNgoc Thanh DaoHuu Bang PhamDuc Chuc ManThanh Ha Leltha@vnu.edu.vnNam Hoang Nguyenhoangnn@vnu.edu.vnHai Chau Nguyenchaunh@vnu.edu.vnThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vn2015-12-15T06:25:45Z2015-12-15T06:29:09Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1422This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/14222015-12-15T06:25:45ZNghiên cứu và phát triển hệ thống giám sát và cảnh báo mức độ ô nhiễm không khí tại Việt NamThi Nhat Thanh Nguyenthanhntn@vnu.edu.vnQuang Hung Buihungbq@vnu.edu.vnChinh Ke LuongViet Hung LuuVan Ha PhamNgoc Thanh DaoHuu Bang PhamDuc Chuc ManThanh Ha Leltha@vnu.edu.vnNam Hoang Nguyenhoangnn@vnu.edu.vnHai Chau Nguyenchaunh@vnu.edu.vnThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vn