Songnian Li
Ryerson University
105 Papers
317 Citations
Songnian Li is an academic researcher from Ryerson University. The author has contributed to research in topics: Computer science & Geospatial analysis. The author has an hindex of 19, co-authored 92 publications. Previous affiliations of Songnian Li include China University of Mining and Technology & University of New Brunswick.
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Papers
Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes
TL;DR: An approach that combines spatiotemporal fusion and object-based image analysis, using the spatial and temporal adaptive reflectance fusion model to generate a time series of Landsat 8 OLI images on critical dates of sedge swamp and paddy rice, and the timeseries of MODIS NDVI to calculate phenological parameters for identifying wetlands with an object- based method is proposed.
Collaboration enabled GIS Tools for Emergency Operation Centre
Zheng Chang,Songnian Li +1 more
- 01 Jan 2007
TL;DR: A research project is presented, aiming at providing such collaborative GIS software tools over the Internet for the VEOC, and the prototype software adopts a semi-replicated and distributed architecture and is deployed over Internet.
Information from imagery: ISPRS scientific vision and research agenda
Jun Chen,Ian Dowman,Songnian Li,Zhilin Li,Marguerite Madden,Jon P. Mills,Nicolas Paparoditis,Franz Rottensteiner,Monika Sester,Charles K. Toth,John Trinder,Christian Heipke +11 more
TL;DR: The significant challenges currently facing ISPRS and its communities are examined, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving.
Geographic information science in the era of geospatial big data: A cyberspace perspective
Xintao Liu,Min Chen,Christophe Claramunt,Michael Batty,Mei Po Kwan,Ahmad M. Senousi,Tao Cheng,Josef Strobl,Cöltekin Arzu,John A. Wilson,Temenoujka Bandrova,Milan Konečný,Paul M. Torrens,Fen Ge Zhang,Li He,Jinfeng Wang,Carlo Ratti,Olaf Kolditz,Alexander Klippel,Songnian Li,Hui Lin,Guonian Lü +21 more
TL;DR: In this paper , Batty et al. present a brief narrative review and a framework for the cyber thinking and analysis of challenges and opportunities for GIScience with a specific focus on emerging geospatial big data.
Spectral Estimation Model Construction of Heavy Metals in Mining Reclamation Areas.
TL;DR: The study reported here examined surface soils in the Liuxin mining area of Xuzhou, and explored the heavy metal content and spectral data by establishing quantitative models with Multivariable Linear Regression (MLR), Generalized Regression Neural Network (GRNN) and Sequential Minimal Optimization for Support Vector Machine (SMO-SVM) methods.