With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 1,000,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

This study analyzed data from satellite altimeter measurements, satellite-tracked surface drifters and global typhoons from 1993 to 2015 to investigate mesoscale cyclonic eddies induced by slow-moving super typhoons, defined as that the translation speed of typhoon is less than the phase speed of first baroclinic mode in that ocean. Our results show that among 22 slow-moving super typhoons found globally in this period, only seven typhoons produced or strengthened cyclonic eddies (3 in Northern Hemisphere, and 4 in Southern Hemisphere). Comparing to the averaged characteristics of eddies in open oceans, these typhoon-induced eddies had stronger intensity and longer lifespan, especially for the Northwestern Pacific and South Pacific Oceans. Take TC-Nida-eddy for instance, maximum current speeds of over 2 m/s, lifespan of 8 month, temperature drop of 4.5 ˚C and formation of upwelling were observed. A negative correlation is also found between eddy’s EKE and TC’s translation speed.

Nowadays the rising of temperature making global warming and climate change becomes very popular topics. Previous studies pointed out that human activity is one of the causes of the heat island effect. In Taiwan, more and more seasonal tourism activities are held in recent years along with the improvement of life quality. However, such activities attract a lot of crowds and traffic flow, and change the heat island intensity. In order to monitor this effect, this study uses thermal infrared channels of Landsat series imagery and retrieves the land surface temperature based on the methodology proposed by Jiménez-Muñoz et al. (2014) and Rozenstein et al. (2014). Xinshe flowery field in Taichung City is chosen to monitor the change of heat island effect during different periods. With supervised maximum likelihood classification, land features are divided into four categories: water, soil, impervious surface and vegetation; and then the emissivity values are assigned to each category. The results show that the land surface temperature of the flowery field has indeed risen during the seasonal activities. Besides, the land surface temperature in the flowery field is as high as other heat areas in Taichung, such as Tali Industrial District and Taichung Thermal Power Plant. This confirms that impacts of changes in land use/cover and human activities may influence the land surface temperature.

Normalized Digital Surface Model (nDSM) represents the elevation of the object with respect to the ground surface, which can be obtained by subtracting Digital Elevation Model (DEM) from Digital Surface Model (DSM). The DEM can be obtained by interpolating the elevations of the first returns from the airborne laser scanner (ALS) data. However, in forest area, the laser can penetrate through the openings of the canopy, where the first returns of ALS point clouds are not necessary on top of the canopy. As a result, the DSM interpolated based on the first returns may show lowered elevation values. In turn, the nDSM obtained from such DSM may show similar phenomenon. In DSM and nDSM data, the raster with lowered elevation value is called pit, which need to be removed for the purpose of data integrity. This study compares the performance of four pit removal algorithms, i.e., median filter, Gaussian smoothing filter, pit filling algorithm with morphological crown control, and pit-free algorithm, in vegetated and non-vegetated areas with the focus on pit removal in vegetated area while keeping the surface integrity. The results show that pit filling algorithm with morphological crown control and pit-free algorithm can effectively reduce the number of pits in forest area while avoid creating overly smoothed results. For single tree, building, and electrical tower, only pit-free algorithm can reasonably mitigate the pits in DSM and nDSM.

Open data is an important trend in different domains. In order to integrate and understand semantic information from different domains, ontology is a good way to descript the concepts in different domains. OpenStreetMap (OSM) project is the most significant example among Volunteered geographic information (VGI). The aim of this study is to develop an ontology-based framework for the building in OSM. OSMonto organized the tags from OSMwiki and Taginfo into an ontology framework in 2011. However, many useful keys and tags are proposed for OSM recently. For example, three-dimensional building information tags (e.g. building＝*). OSM’s information becomes richer that is from two-dimensional development to three-dimensional. In order to improve the structure of OSM tags, it is necessary to revise an up-to-date ontology-based framework for OSM. We used an open-source ontology editor, i.e. protégé, to build up the OWL for the building in OSM. This study expected to achieve a hierarchy’s rationalization and definition of tag’s attributes. Furthermore, this ontology can be used in querying via Jena API. This study discussion about the data sources, attribute definition methods, and the hierarchy of key value that the OSM can be used to exchange with other domain ontology easier.