Remotely sensed images are very useful for land-cover monitoring and land-use-change detection. Before these images can be interpreted or superimposed onto other maps, they have to be geometrically corrected and registered to the consistent datum. Current approaches for geometric correction rely on manually measurements of huge amount of control points, which is one of bottlenecks of the procedure. This paper proposed an ad-hoc Least-squares Model-image Fitting (LSMIF) algorithm to semi-automatically determine the orientation parameters of the remotely sensed images. The images are therefore geometrically corrected by 3D building models instead of control points. Since the operator only has to identify each 3D building model and their approximately position on the image, the efficiency of the manual process can be improved. A proto-type system is developed to verify the proposed algorithm and the semi-automated strategy. Several FORMOSAT-II satellite images taken over the coastal area in Tainan are selected as the experimental data. The 3D building models are generated from the existing 3D topographic map. The corrected images are evaluated by two means. First, the coordinates of the check points on the geometrically corrected image are compared to their coordinates on the topographic map. Second, the geometrically corrected images are compared to the level 3 and level 4 images corrected by current approaches. The experiment shows the proposed semi-automated approach does not only improve the efficiency but also achieve the required accuracy. It also shows the potential of applying to the upcoming FORMOSAT-V satellite images
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A Study on Integrating Web Mapping Services with Drupal – A Case Study on NLSC Map Service 劉婕昕 王聖鐸 摘要隨著導航裝置與智慧型手機的風行,電子地圖已深入一般大眾的日常生活,舉凡景點查詢、門牌查詢、路徑導航、轉乘分析、景點分享等都可以透過電子地圖進行。臺灣的消費者多半習慣使用Google Map,其地圖內容是由Google公司向衛星影像公司、航測公司、地圖公司等採購原始圖資後匯整編輯而成。而歐洲則是以Web2.0的概念發展出開放街圖(OpenStreetMap, OSM),以協同製圖(Collaborative Mapping)的方式,由各地的使用者自行產生圖資。然而專業精確的地圖通常必須由政府投資測製,作為空間資訊的基礎建設(Spatial Data Infrastructure, SDI),提供土地管理、空間規劃、大地工程等應用。為達此目的,內政部國土測繪中心整合所轄:通用版電子地圖、國土利用調查成果、航測正射影像等圖資,提供一套「國土測繪圖資網路地圖服務系統」作為便民服務。該系統採用OSGeo(Open Source Geospatial Foundation)所提供的OpenLayers程式庫開發而成,為建立地圖及地理空間資訊的開放源碼(Open Source)程式語言。然而使用者仍須學習OpenLayers程式庫,才能順利將該網路地圖服務加入網站。本研究採用內容管理系統(Content Management System):Drupal來降低使用者在網站中嵌入地圖服務的門檻,利用其OpenLayers模組可整合網路地圖服務(Web Mapping Service, WMS)發布之圖層並能從多重來源呈現圖磚(Map Tiles)和標記(Markers)的特性,整合常用的消費級電子地圖及國土測繪中心圖資,提供使用者一個簡易架站系統。
Routes Analysis for Household Garbage Collecting and Transporting in Taipei 黃傳楷 王聖鐸 摘要臺北市政府為了解決長久以來的垃圾問題,自1997年起陸續實施「垃圾不落地」、「垃圾費隨袋徵收」等環保政策。其中垃圾不落地政策中的「垃圾收運」模式,從原先的定點設置垃圾子車讓市民隨時可放置垃圾待運,改為由固定發車時間的垃圾車行駛固定路徑,並於固定時間暫停於固定的收運點,市民只有在垃圾車短暫停留時間才能拋棄以專用垃圾袋包裝之垃圾。目前垃圾車的收運路徑規劃是以12個行政區的界線作為畫分依據,本研究將探討現行路線是否能迎合絕大部分市民需求,以及是否能同時兼顧收運效率及節能減碳目標。首先透過地理資訊系統(Geographic Information System, GIS)建立現行臺北市中山區、松山區及大安區三區邊界垃圾車之路徑模型,接著參考最小統計區人口數、土地使用現況調查及現地統計垃圾量等資訊,以收運點間路徑長度、單一收運點之清運量、單位時間清運量、每人垃圾量、每人單位時間垃圾量、單一路徑總清運量等作為指標,分析現有收運路徑之適宜性。最後嘗試建立跨行政區的路徑模型,將現地統計得到之垃圾清運量,分別帶入現行路徑及跨行政區路徑模型,比較兩者之收運效能。由上述指標綜合分析可知,由於人口結構之改變,部分清運點確有可調整空間,單一清運點停留收運時間亦應隨之調整,以求更加符合居民需求,並提升整體清運效率。
ABSTRACTThe 3D photo-realistic building model does not only present the building in the three-dimensional perspective but also reveals its real appearance. There have been a number of approaches for reconstructing the geometric model from photogrammetric images, from LiDAR point cloud, or from both of them. However, the façade texture generation and mapping require massive labor works, therefore, are still the bottle neck in the photo-realistic building modeling process. A semi-automated approach to modeling 3D photo-realistic buildings using smartphones or tablet PCs is proposed in this paper. The built-in GPS
Integrating Sensors on a Smartphone to Generate Texture Images of 3D Photo-realistic Building Models5/18/2012 ABSTRACTA 3D photo-realistic building model which can represent the real appearance of the building should be composed by precise geometric model and realistic façade images. There are a number of approaches to reconstructing the geometric model from photogrammetric images and LiDAR points cloud. However, the façade texture generation still relies on massive labor works, therefore, are still the bottle neck in the photo-realistic building modeling process. The emphasis of this paper will be put on the integration of sensors on a smartphone. While the camera is collecting the realistic photo of the building façade, the
ABSTRACT Reconstructing the 3D geometric model of buildings from photogrammetric images, from LiDAR point cloud, or from both of them has raised extensive researches in the past decade. However, the façade mapping is still the bottle neck in the photo-realistic building modeling process. With the rapid development of personal mobile computing devices, such as smartphones and tablet PCs, it has become easier to directly geo-referencing the taken picture. The concept of a semi-automated approach to modeling photo-realistic 3D buildings using a personal mobile computing device is proposed in this paper. The built-in GPS receiver
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