I have been at GIS Centre, INES as a PhD student since Novermber 2015 with a topic "Integration and linkage of heterogeneous geospatial data" under the supervisions of Prof. dr. Lars Harrie and Dr. Ali Mansourian. Within my PhD topic, I am mainly instereted in expoliting the knowledge representation techniques (including ontology, semantic web, linked data, descriptive logic, etc.) for facilitating geospatial data integration, with a peticular perspective of geovisualisation.
I have accomplished my first sub-study, which pertains the utilisation of linked data for the integration and synchronisation of thematic data and base maps in web maps nowadays. The starting point of this study is twofold: the web maps nowadays are usually presented in the form of map mashups, namely the thematic information is overlaid on various base maps, whereas the thematic data and the base maps are generally not linked, and this often raises much geometric inconsistencies in the web maps; the second starting point is that the European spatial data infrastructure initiative INSPIRE as well as Swedish national mapping agency (Lantmäteriet) are investigating of postential of linked data, and the linked data perfectly fits to alleviate the aforementioned long-standing visualisation flaw, thus we used linked data paradigm to enable (potential) genuine self-adapting web maps. To this end, we have addressed the research motivation and the methodology in a paper published by International Journal of Geographical Information Science, see the article. In addition to this, we have developed a prototype system as a proof of concept, all the codes (but not the data) are available in GitHub at here under the GPL 3.0 license.
My next studies will concentrate on the exploitation of knowledge represenatation techniques for another aspect of geovisualisation, e.g. rule-based multi-scale symbolisation, mapping for disaster management.
Furthermore, I am keen on exploring the geospatial applications of information technologeis in some other aspects, e.g. machine learning for remote sensing change detection, in which I have cooprated with some of my colleagues at China Agricultural University and Wuhan University. You are more than welcome to discuss any potential scientific collaboration with me.
And a few words about myself, I am from China, and was born in Jinan. I have had my studies in Jinan, Wuhan and Beijing before I came to Lund. I like Chinese calligraphy, music, football, and computer technology.
Displaying of publications. Sorted by year, then title.
- RECONCILING CITY MODELS with BIM in KNOWLEDGE GRAPHS : A FEASIBILITY STUDY of DATA INTEGRATION for SOLAR ENERGY SIMULATIONW. Huang, P. O. Olsson, J. Kanters, L. Harrie
(2020) ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 6 p.93-99
- Towards Knowledge-Based Geospatial Data Integration and Visualization : A Case of Visualizing Urban Bicycling SuitabilityWeiming Huang, Khashayar Kazemzadeh, Ali Mansourian, Lars Harrie
(2020) IEEE Access, 8 p.85473-85489
- Geospatial data and knowledge on the Web : Knowledge-based geospatial data integration and visualisation with Semantic Web technologiesWeiming Huang
- Towards knowledge-based geovisualisation using Semantic Web technologies : a knowledge representation approach coupling ontologies and rulesWeiming Huang, Lars Harrie
(2020) International Journal of Digital Earth, 13 p.976-997
- Building extraction from VHR remote sensing imagery by combining an improved deep convolutional encoder-decoder architecture and historical land use vector mapWenqing Feng, Haigang Sui, Li Hua, Chuan Xu, Guorui Ma, et al.
(2020) International Journal of Remote Sensing, 41 p.6595-6617
- Assessment and benchmarking of spatially enabled RDF stores for the next generation of spatial data infrastructureWeiming Huang, Syed Amir Raza, Oleg Mirzov, Lars Harrie
(2019) ISPRS International Journal of Geo-Information, 8
(2019) CEUR Workshop Proceedings, 2548 p.37-45
- Water Body Extraction From Very High-Resolution Remote Sensing Imagery Using Deep U-Net and a Superpixel-Based Conditional Random Field ModelWenqing Feng, Haigang Sui, Weiming Huang, Chuan Xu, Kaiqiang An
(2019) IEEE Geoscience and Remote Sensing Letters, 16 p.618-622
- A novel change detection approach based on visual saliency and random forest from multi-temporal high-resolution remote-sensing imagesWenqing Feng, Haigang Sui, Jihui Tu, Weiming Huang, Kaimin Sun
(2018) International Journal of Remote Sensing, 39 p.7998-8021
- A novel change detection approach for multi-temporal high-resolution remote sensing images based on rotation forest and coarse-to-fine uncertainty analysesWenqing Feng, Haigang Sui, Jihui Tu, Weiming Huang, Chuan Xu, et al.
(2018) Remote Sensing, 10
(2018) International Journal of Geographical Information Science, 32 p.1117-1137
(2018) Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden
- Towards knowledge-based integration and visualization of geospatial data using semantic web technologies*Weiming Huang
(2018) CEUR Workshop Proceedings, 2204
(2017) Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 46 p.1880-1890
(2017) CEUR Workshop Proceedings, 2088