Nakmuenwai P.,Geo Informatics and Space Technology Development Agency |
Nakmuenwai P.,Chiba University |
Yamazaki F.,Chiba University |
Liu W.,Chiba University
Remote Sensing | Year: 2017
This study examines a novel extraction method for SAR imagery data of widespread flooding, particularly in the Chao Phraya river basin of central Thailand, where flooding occurs almost every year. Because the 2011 flood was among the largest events and of a long duration, a large number of satellites observed it, and imagery data are available. At that time, RADARSAT-2 data were mainly used to extract the affected areas by the Thai government, whereas ThaiChote-1 imagery data were also used as optical supporting data. In this study, the same data were also employed in a somewhat different and more detailed manner. Multi-temporal dual-polarized RADARSAT-2 images were used to classify water areas using a clustering-based thresholding technique, neighboring valley-emphasis, to establish an automated extraction system. The novel technique has been proposed to improve classification speed and efficiency. This technique selects specific water references throughout the study area to estimate local threshold values and then averages them by an area weight to obtain the threshold value for the entire area. The extracted results were validated using high-resolution optical images from the GeoEye-1 and ThaiChote-1 satellites and water elevation data from gaging stations. © 2017, by the authors; licensee MDPI, Basel, Switzerland.
Rakwatin P.,Geo Informatics and Space Technology Development Agency |
Sansena T.,Geo Informatics and Space Technology Development Agency |
Marjang N.,Kasetsart University |
Rungsipanich A.,Geo Informatics and Space Technology Development Agency
Remote Sensing Letters | Year: 2013
In 2011, when Thailand faced its most severe flood disaster in 50 years, the Geo-Informatics and Space Technology Development Agency provided flood affected data to support government agencies during the crisis, specifically synthetic aperture radar (SAR) imagery, optical satellite imagery and a digital elevation model (DEM). These data were combined with water level data from gauge stations to map the area flooded and to estimate water volume in near real time to support decision-making for flood relief operations. However, difficulties were encountered when dealing with different kinds of spatial data and different application techniques. Problems included inconsistent acquisition schedules for different satellites, different image resolutions and different data acquisition modes, i.e. ScanSAR Wide and Wide modes. DEM accuracy also proved to be an issue. Current work is underway to improve the satellite image acquisition planning andDEMaccuracy and increase the number of gauge stations in the flood affected area so as to improve the accuracy, reliability and usefulness of geoinformatics data for future disaster management. © 2012 Taylor & Francis.
Tulsuk P.,Kasetsart University |
Srestasathiern P.,Geo Informatics and Space Technology Development Agency |
Ruchanurucks M.,Kasetsart University |
Phatrapornnant T.,National Science and Technology Development Agency |
Nagahashi H.,Tokyo Institute of Technology
IEEE Intelligent Vehicles Symposium, Proceedings | Year: 2014
This paper presents a novel method for extrinsic parameters estimation of a single line scan LiDAR and a camera. Using a checkerboard, the calibration setup is simple and practical. Particularly, the proposed calibration method is based on resolving geometry of the checkerboard that visible to the camera and the LiDAR. The calibration setup geometry is described by planes, lines and points. Our novelty is a new hypothesis of the geometry which is the orthogonal distances between LiDAR points and the line from the intersection between the checkerboard and LiDAR scan plane. To evaluate the performance of the proposed method, we compared our proposed method with the state of the art method i.e. Zhang and Pless . The experimental results showed that the proposed method yielded better results. © 2014 IEEE.
Auynirundronkool K.,Wuhan University |
Chen N.,Wuhan University |
Peng C.,Wuhan University |
Yang C.,Wuhan University |
And 2 more authors.
International Journal of Applied Earth Observation and Geoinformation | Year: 2012
Flooding in general is insignificant event worldwide and also in Thailand. The Central plain, the Northern plain and the northeast of Thailand are frequently flooded areas, caused by yearly monsoons. The Thai government has extra expenditure to provide disaster relief and for the restoration of flood affected structures, persons, livestock, etc. Current flood detection in real time or near real time has become a challenge in the flood emergency response. In this paper, an automatic instant time flood detection approach consisting of a data retrieval service, flood sensor observation service (SOS), flood detection web processing service (WPS) under a sensor web environment, is presented to generate dynamically real-time flood maps. A scenario of a RADARSAT and MODIS sensor web data service for flood detection cover of the Thailand Central plain is used to test the feasibility of the proposed framework. MODIS data are used to overview the wide area, while RADARSAT data are used to classify the flood area. The proposed framework using the transactional web coverage service (WCS-T) for instant flood detection processes dynamic real-time remote sensing observations and generates instant flood maps. The results show that the proposed approach is feasible for automatic instant flood detection. © 2011 Elsevier B.V.
Phoomikiattisak D.,Geo Informatics and Space Technology Development Agency |
Bhatti S.N.,University of St. Andrews
2016 9th IFIP Wireless and Mobile Networking Conference, WMNC 2016 | Year: 2016
Seamless host mobility is vital to future network mobility, and has been an active research area for a long time. Much research focuses on the performance of the data plane. In this paper, we present comprehensive analyses on the control (signalling) plane in the IETF Mobile IPv6, and compare it with the IRTF Identifier-Locator Network Protocol (ILNP). The control plane behaviour is important in order to assess the robustness and scalability of the mobility protocol. ILNP has a different mobility model from Mobile IPv6: it is a host-based, end-To-end architecture and does not require additional network-layer entities. Hence, the control signals are exchanged only between the end systems. We provide model-based analyses for handoff signalling, and show that ILNP is more efficient than MIPv6 in terms of robustness and scalability. The analytical models we present could also be adapted for other mobility solutions, for comparative assessment. © 2016 IEEE.
Kiadtikornthaweeyot W.,Geo Informatics and Space Technology Development Agency |
Tatnall A.R.L.,University of Southampton
ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings | Year: 2015
A real scene observed from a satellite image contains a variety of features, textures and shadows and it can therefore be very complex to detect the region of interest (ROI). The ROI of a satellite image depends on the application field for Earth observation. Therefore image segmentation has been developed for extracting different features or textures inside an image. This can be performed a number of different ways using the image properties. Extraction of a feature of an image is very difficult to find the appropriate image segmentation techniques and combine different methods to detect the ROI most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI are performed automatically and focus on the ROI of coastlines, forests, urban areas and agriculture. Three different methods to detect the ROI of the satellite images have been studied, implemented and tested; these are based on edge, histogram and texture segmentation. The edge method is based on edge detection and morphology. The histogram method is based on thresholding and morphology. The texture method is based on GLCM texture feature statistics and morphology. All three of the image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts. A comparison of each technique has been performed. In this paper the combination of the proposed ROI automatic detection and image compression technique have been performed to find the percentage size reduction of the original image. Moreover the possibility to implement these techniques in cubesat onboard computer has been described. In addition the morphology structure element is used in these proposed techniques. A study on the appropriate shape and size of structure element is required and has been discussed in this paper.
Kiadtikornthaweeyot W.,Geo Informatics and Space Technology Development Agency |
Tatnall A.R.L.,University of Southampton
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2016
High resolution satellite imaging is considered as the outstanding applicant to extract the Earth's surface information. Extraction of a feature of an image is very difficult due to having to find the appropriate image segmentation techniques and combine different methods to detect the Region of Interest (ROI) most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI focus on forests, urban and agriculture areas. The proposed system is based on histograms of the image to classify objects using thresholding. The thresholding is performed by considering the behaviour of the histogram mapping to a particular region in the satellite image. The proposed model is based on histogram segmentation and morphology techniques. There are five main steps supporting each other; Histogram classification, Histogram segmentation, Morphological dilation, Morphological fill image area and holes and ROI management. The methods to detect the ROI of the satellite images based on histogram classification have been studied, implemented and tested. The algorithm is be able to detect the area of forests, urban and agriculture separately. The image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts.
Kiadtikornthaweeyot W.,Geo Informatics and Space Technology Development Agency
2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2016 | Year: 2016
The Earth observation optical image is considered as the excellent applicant to extract the Earth's surface information. Cloud cover is a spectacular problem for land surface analysis. False detection and analysis typically results from even small percentages of cloud cover. Therefore knowing the percentage of cloud in the image is constructive for the user to allow for selection of those images that contain an acceptable amount of cloud cover (and therefore error) for their application. This paper presents the algorithm for cloud cover assessment using ROI (region of interest) image classification based on histogram segmentation for THAICHOTE satellite images. The objective is to accurately determine the percentage of cloud cover in the optical satellite image, which is improved from the existing algorithm developed. In addition the morphology structure element is used in the algorithm. A study on the appropriate shape and size of structure element is required and has been discussed in this paper. © 2016 IEEE.
Sachasiri R.,Geo Informatics and Space Technology Development Agency
31st Asian Conference on Remote Sensing 2010, ACRS 2010 | Year: 2010
Thailand's activities and interest on space and space-related technologies have been increasing rapidly over the past decades. This has led to the birth of THEOS, the very first remote sensing satellite of Thailand. THEOS products assist in the development of natural resources, environmental monitoring and many others remote sensing applications. The main objective is to provide earth observation based total solution, which is applicable not only for Thailand but also for other countries. Two years of operation after its launch in 2008, GISTDA is moving forward to maximize the utilization of resources available. GISTDA aims to extend the services already available by adding further functionality such as ortho-rectification, mosaic and elevation editing to fulfill the needs of cartography applications. This has created value added service such as the use of THEOS' image data for the Rice Pricing Guarantee, one recent project in which THEOS' images has contributed greatly. THEOS products and services have also assisted Thai's Government in Agricultural Assessment and Management. In this age of high-speed information, it is obvious that web-based applications are essential. Ongoing projects aims to make all THEOS' imagery available online whereby users may browse conveniently through the online catalog, initiate and complete the process of images ordering. This can be achieved through the THEOS' online services, which will add ease of use to end-users and image distributors. In addition to existing domestic channels of distribution, GISTDA is on its way to enter the worldwide market. With the ortho-products soon to be available, GISTDA aims to be one of the key providers in the Satellite Imagery industry. This is further enhanced by the establishment of two additional Image Ground Stations for THEOS outside Thailand and the contract with polar station for additional satellite commanding. Furthermore, all three GISTDA's offices will soon be connected to the UniNet, a Government portal cum gateway that provides hi-speed information network linked to universities, institutes, and campuses with more than 200 sites across Thailand as well as overseas countries. Consequently, linking GISTDA to Thailand's educational network and the international research network, which will allow students and researchers from all over the world to be able to access to GISTDA's database and resources. Uninet will also provide a high-speed communication channel for GISTDA, which enhance the competency of the service to the greater level.
Pimnoo A.,Geo Informatics and Space Technology Development Agency
World Academy of Science, Engineering and Technology | Year: 2011
In recent years number of space objects, which are increasing continuously not only fulfil in the space of the earth atmosphere orbitally as space pollution but also have been rising probability of satellite collision between a space debris and an own satellite or a satellite and another satellite whatever are becoming more likely. Either satellite orbit determination or satellite tracking software is facility of orbit determination and accuracy satellite ephemeris prediction. So, it hardly misses a satellite visibility appointment. Nevertheless, the satellite collision avoidance is a critical event after foreseen computation occurring high probability of satellite collision. Inevitably, the collision avoidance activity has to actively manage a necessary strategy to safely avoid the risk of collision. Unfortunately, in the real action of flight dynamics engineering operators, FDS engineers can scarcely be able to know or predict either what the type of space object is coming closely or where the direction is from. THEOS is the first earth observation satellite of Thailand which is worthy of growing space technology and space education learning for Thais. So, the prevention of damaged spacecraft is necessary. The United Sates Joint Space Operations Center (JSpOC) and the Center for Space Standards & Innovation (CSSI), which are the space surveillance organization, have usually sent receipt of collision awareness, in the detail of Time of Closest Approach (TCA), to other countries. This paper is to develop a satellite collision avoidance strategy for THEOS spacecraft which is to perform procedures of satellite collision avoidance including Orbit Control Manoeuvre (OCM) plan taking into account of propellant fuel depletion. The strategy consists of 4 steps after the collision awareness monitoring. Absolutely, the first step is to deeply analyze the collision awareness notification warned by JSpOC and CSSI. This step is to analyze and determine the probability of satellite collision from the JSpOC or CSSI receipt. The second step is to perform the risk of collision avoidance manoeuvre strategy from conditional method by collaborative with expert engineers from ASTRIUM. After the second step, OCM plan will be sent to simulate the result using Satellite Simulator, meanwhile the THEOS ephemeris will be sent to JSpOC or CSSI for accuracy checking the result of collision avoidance manoeuvre. Then, the OCM plan will be sent to spacecraft on time. Finally, the status will be normally checked for efficiency calibration and will be updated new configuration. Then, FDS engineers will specially check the result of collision avoidance with own receipt by THEOS ephemeris propagated. However, these steps will be finalized by using the strong constrains and have been consistently solved with the propellant fuel depletion for saving the life-time of THEOS.