Nguyen Quang Minh

Hanoi University of Mining and Geology · Department of Surveying

Bài báo đề cập đến việc cải thiện độ chính xác của mô hình số độ cao (Digital Elevation Model - DEM). Mặc dù, các thuật toán tái chia mẫu song tuyến, bicubic, Kriging và mô hình tăng độ phân giải bằng mạng nơ ron Hopfield (HNN) cho phép nâng cao độ chính xác cho mô hình số độ cao, đặc biệt là mô hình số độ cao từ các nguồn dữ liệu toàn cầu như SRTM...

In this paper, a comparison and evaluation of three resamplingmethods for gridded DEM is implemented. The evaluation was based onthe results of bilinear resampling, bi-cubic and Kriging resamplingmethods for an experiment using both degraded and sampled datasets at 20m and 60 m spatial resolutions. The evaluation of the algorithms wasaccomplished c...

UAV technology is being applied for DSM generation in open-pit mines with a well-established fact that the precision of such DSM is improved by increasing the number of ground control points (GCPs). however, DSMs are updated frequently in an open-pit mine where the surface is excavated continuously. This imposes a challenge to arrange and maintain...

A new Hopfield neural network (HNN) model for downscaling a digital elevation model in grid form (gridded DEM) is proposed. The HNN downscaling model works by minimizing the local semivariance as a goal, and by matching the original coarse spatial resolution elevation value as a constraint. The HNN model is defined such that each pixel of the origi...

The main objective of this research work was to propose and verify a new soft computing approach based on Multivariate Adaptive Regression Splines (MARS) and Particle Swarm Optimization (PSO) for spatial prediction of flash flood susceptible areas. A high frequency tropical typhoon area located on Northwest of Vietnam was selected as a case study....

Flash flood is a typ­i­cal nat­ural haz­ard that oc­curs within a short time with high flow ve­loc­i­ties and is dif­fi­cult to pre­dict. In this study, we pro­pose and val­i­date a new soft com­put­ing ap­proach that is an in­te­gra­tion of an Ex­treme Learn­ing Ma­chine (ELM) and a Par­ti­cle Swarm Op­ti­miza­tion (PSO), named as PSO-ELM, for the...

Hiện nay, mô hình số độ cao (DEM) có rất nhiều ứng dụng trong các lĩnh vực của đời sống kinh tế, xã hội, đặc biệt là trong các lĩnh vực về quản lý tài nguyên thiên nhiên và bảo vệ môi trường. Các DEM với độ phân giải không gian cao hơn sẽ mang lại kết quả chính xác hơn và mang tính thông tin hơn. Bài báo này đề xuất một thuật toán làm tăng độ phân...

Flash flood is widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash flood based on Sentinel-1 SAR imagery and a new hybrid machine learning techniqu...

One of passive sensor’s limitations is its high sensitivity to weather condition during image acquiring process. Consequently, the image is often affected by cloud cover. This phenomenon severely influences the completeness of land use/cover obtained from optical satellite imagery and make image processing more complicatedly. However, the pattern o...

Trên thế giới thành lập bản đồ bằng công nghệ đo ảnh máy bay không người lái (UAV) và máy ảnh thông thường đang ngày càng được sử dụng rộng rãi trong ngành trắc địa- bản đồ, tuy nhiên công nghệ này vẫn là tương đối mới ở Việt Nam. Mục đích chính của bài báo này là trình bày quy trình công nghệ sử dụng ảnh máy bay không người lái, xây dựng các sản p...

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regio...

Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this pap...

Using soft classification, it is possible to obtain the land cover proportions from the remotely sensed image. These land cover proportions are then used as input data for a procedure called "super-resolution mapping" to produce the predicted hard land cover layers at higher resolution than the original remotely sensed image. Superresolution mappin...

Three dimensional (3D) reconstruction has been widely applied in urban planning, digital city, and the conservation of cultural/archaeological heritage etc. to rebuild 3D object geometry. In the situation where the objects are irregular and have structure-complex, the use of conventional methods is time-consuming and mostly not practicable because...

Detailed tree attributes such as tree height, tree type, diameter at breast height, number of trees are critical for effective management and analysis of the forest. By usage of airborne LiDAR (LIght Detection And Ranging) and hyperspectral data, this paper presents individual tree extraction method to get the accurate tree information. SVM (Suppor...

Super-resolution mapping or sub-pixel mapping is a set of techniques to produce the hard land cover map at sub-pixel spatial resolution from the land cover proportion images obtained by soft-classification methods. In addition to the information from the land cover proportion images at the original spatial resolution, supplementary information at t...

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground...

Superresolution mapping is a set of techniques to increase the spatial resolution of a land cover map obtained by soft-classification methods. In addition to the information from the land cover proportion images, supplementary information at the subpixel level can be used to produce more detailed and accurate land cover maps. The proposed method in...

Superresolution mapping is a set of techniques to obtain a subpixel map from land cover proportion images produced by soft classification. Together with the information from the land cover proportion images, supplementary information at the subpixel level can be used to produce more detailed and accurate land cover maps. This research aims to use t...

Nowadays in Vietnam, although still adopting the policy that land itself is not individual property, land-use rights, such as exchange, transfer, rent, inheritance or mortgage, are considered as property in reality. This means that a trading market of land-use rights is emerging and becom-ing increasingly popular. In order to manage and develop thi...

Super-resolution techniques can be used to increase the spatial resolution of the imagery. Although widely applied in image processing, the current super-resolution approaches were hardly applicable for super-resolution of remotely sensed multispectral (MS) imagery because of the lack of a sequence of images in a scene at the same time. In this pap...