L
Linda See
Researcher at International Institute for Applied Systems Analysis
Publications - 338
Citations - 13633
Linda See is an academic researcher from International Institute for Applied Systems Analysis. The author has contributed to research in topics: Land cover & Crowdsourcing. The author has an hindex of 55, co-authored 312 publications receiving 10755 citations. Previous affiliations of Linda See include International Institute of Minnesota & University College London.
Papers
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Journal ArticleDOI
Corrigendum to ‘Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling’ (Urban Climate (2019) 28, (S2212095519300975), (10.1016/j.uclim.2019.100459))
Jason Ching,Daniel G. Aliaga,Gerald Mills,Valéry Masson,Linda See,Marina Neophytou,Ariane Middel,Alexander Baklanov,Chao Ren,Edward Ng,Jimmy Chi Hung Fung,Michael Wong,Yuan Huang,Alberto Martilli,Oscar Brousse,Iain D. Stewart,Xiaowei Zhang,Aly Shehata,Shiguang Miao,Xuemei Wang,Weiwen Wang,Yoshiki Yamagata,Denise Helena Silva Duarte,Yuguo Li,Johan Feddema,Benjamin Bechtel,Julia Hidalgo,Yelva Roustan,Young Seob Kim,Helge Simon,Tim Kropp,Michael Bruse,Fredrik Lindberg,Sue Grimmond,Matthias Demuzure,Fei Chen,Chen Li,Jorge Gonzales-Cruz,Bob Bornstein,Qiaodong He,Tzu-Ping,Adel Hanna,Evyatar Erell,Nigel J. Tapper,R. K. Mall,Dev Niyogi +45 more
The WUDAPT Project: Status of Database and Portal Tools
TL;DR: In this article, the authors show that despite their global significance, we know very little about the spatial composition of most cities and what we do know is often too coarse or inconsistent to undertake scientific inquiry or make meaningful comparisons.
Book ChapterDOI
The Cropland Capture Game: Good Annotators Versus Vote Aggregation Methods
TL;DR: A perceptual hash and blur detection algorithm is used to improve the quality of the Cropland Capture game’s dataset and demonstrates that volunteer-image assignment is highly irregular and only good annotators are presented.
FotoQuest Go: A Citizen Science Approach to the Collection of In-Situ Land Cover and Land Use Data for Calibration and Validation
Steffen Fritz,Tobias Sturn,Mathias Karner,Inian Moorthy,Linda See,J.C. Laso Bayas,Dilek Fraisl +6 more
TL;DR: FotoQuest Go as mentioned in this paper is one of the tools that are part of the H2020-funded LandSense Citizen Observatory for land cover and land use data collection, which can be used to validate the CORINE land cover map, which is generated for EU member countries every 6 years, and it represents the only publicly available in situ dataset for the calibration and validation of products derived from Earth Observation for Europe.