From 22401489de7b84711a7c29936e4856a77ae5fd7c Mon Sep 17 00:00:00 2001 From: Filip Biljecki Date: Sun, 19 May 2024 19:52:25 +0200 Subject: [PATCH] Yuhao visit and SD EBM --- content/authors/filip/_index.md | 3 +- content/post/2024-02-ceus-urban-form/index.md | 2 + content/post/2024-05-sd-ebm/featured.png | Bin 0 -> 95111 bytes content/post/2024-05-sd-ebm/index.md | 40 +++++++++++++ content/post/2024-05-visit-yuhao/1.jpg | Bin 0 -> 4945157 bytes content/post/2024-05-visit-yuhao/2.jpg | Bin 0 -> 5927735 bytes content/post/2024-05-visit-yuhao/3.jpg | Bin 0 -> 1181592 bytes content/post/2024-05-visit-yuhao/4.jpg | Bin 0 -> 1693420 bytes content/post/2024-05-visit-yuhao/5.jpg | Bin 0 -> 5038053 bytes content/post/2024-05-visit-yuhao/featured.jpg | Bin 0 -> 5197367 bytes content/post/2024-05-visit-yuhao/index.md | 56 ++++++++++++++++++ content/post/2024-05-visit-yuhao/poster.jpg | Bin 0 -> 1761585 bytes 12 files changed, 100 insertions(+), 1 deletion(-) create mode 100644 content/post/2024-05-sd-ebm/featured.png create mode 100644 content/post/2024-05-sd-ebm/index.md create mode 100644 content/post/2024-05-visit-yuhao/1.jpg create mode 100644 content/post/2024-05-visit-yuhao/2.jpg create mode 100644 content/post/2024-05-visit-yuhao/3.jpg create mode 100644 content/post/2024-05-visit-yuhao/4.jpg create mode 100644 content/post/2024-05-visit-yuhao/5.jpg create mode 100644 content/post/2024-05-visit-yuhao/featured.jpg create mode 100644 content/post/2024-05-visit-yuhao/index.md create mode 100644 content/post/2024-05-visit-yuhao/poster.jpg diff --git a/content/authors/filip/_index.md b/content/authors/filip/_index.md index 8a7de97..e0d248b 100755 --- a/content/authors/filip/_index.md +++ b/content/authors/filip/_index.md @@ -30,7 +30,7 @@ interests: education: courses: - - course: PhD in 3D GIS (highest honours) + - course: PhD in 3D GIS (cum laude) institution: Delft University of Technology, Netherlands year: - course: MSc in Geomatics @@ -113,6 +113,7 @@ The list of his publications is available [here](https://filipbiljecki.com/#publ * [NUS Sustainable and Green Finance Institute](https://sgfin.nus.edu.sg) -- Research Affiliate * [NUS Institute of Real Estate and Urban Studies](https://ireus.nus.edu.sg) -- Research Affiliate * [Landscape and Urban Planning](https://www.journals.elsevier.com/landscape-and-urban-planning) -- Editorial Board Member +* [Scientific Data](https://www.nature.com/sdata/) -- Editorial Board Member * [Transactions in GIS](https://onlinelibrary.wiley.com/journal/14679671) -- Editorial Board Member * [PLOS ONE](https://journals.plos.org/plosone/) -- Academic Editor for Geoinformatics * [International Journal of Digital Innovation in the Built Environment](https://www.igi-global.com/journal/international-journal-digital-innovation-built/224363) -- Editorial Board Member diff --git a/content/post/2024-02-ceus-urban-form/index.md b/content/post/2024-02-ceus-urban-form/index.md index 7159fc9..b5c3305 100644 --- a/content/post/2024-02-ceus-urban-form/index.md +++ b/content/post/2024-02-ceus-urban-form/index.md @@ -55,6 +55,8 @@ The abstract follows. > Most studies of urban morphology rely on morphometrics, such as building area and street length. However, these methods often fall short in capturing visual patterns that carry abundant information about the configuration of urban elements and how they interact spatially. In this study, we introduce a novel method for learning morphology features based on figure-ground maps, which leverages recent developments in computer vision. Our method facilitates discovering and comparing urban form types in a fully unsupervised manner. Specifically, we examine building fabrics by 1 km patches. A visual representation learning model (SimCLR) casts each patch into a latent embedding space where similar patches are clustered while dissimilar patches are dispelled, thus generating morphology representations that entail the layout of building groups. The learned morphology features are tested in urban form typology clustering and comparison tasks in four diverse cities: Singapore, San Francisco, Barcelona, and Amsterdam, with data sourced from OpenStreetMap. Clustering results show effective identification of typical urban morphology types corresponding to urban functions and historical developments. Further analyses based on the representations reveal inner- and cross-city morphological homogeneity relating to socio-economic drivers. We conclude that this method is a promising alternative for effectively describing urban patterns in morphology analysis. +![](2.png) + ### Paper For more information, please see the [paper](/publication/2024-ceus-urban-form-discovery/). diff --git a/content/post/2024-05-sd-ebm/featured.png b/content/post/2024-05-sd-ebm/featured.png new file mode 100644 index 0000000000000000000000000000000000000000..8b5f4afedfcea4930e5c56aa13ac2098caaa0f87 GIT binary patch literal 95111 zcmeEuby$>5+cza4NG%f5ODf%6vXrzaf*`OUB};dM61${G%MxM$f|Q6LDIHRRvUI0( z_rBM9=i_tV-~ZonJaE8X%*;7)&Y8cN3xuAI+Lg=KE@NR~UC~g7+{VJXB!Pv6i%*CT zlyKcFO#nXdY?ZW?u&~PFiO-;yfWKL+)NgBJVfk@lVTFWYVVwX)AzpmaQ^7wl0**fAJ4d$rDA>JD2xU^h+Nc--LbIv*)TuYKCczLu(0so+21kpFw)kN zwsLmlhdy++wC4A5biq(z$@)kGkB-(JP!=CYn3KD-j~w`C3u)jPQ!D^x`Psz7K@M!B zt;eG5>}Jg(&M(L>2$sLh!oni!_RvQ9HbnJza^NpHu$_m8i?o1%x3@RHw+O$po2`J5 zl$4Z!ps;|jFdxu@&)wI_1M0))_Zr#~Nk?v3Im~ zatHQMUPx5*52|0Q{*l!9FH%Wy!QaRGN%^;$zfofLOj^ScYHNMZ{-KARys)SwFy61F 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a/content/post/2024-05-sd-ebm/index.md b/content/post/2024-05-sd-ebm/index.md new file mode 100644 index 0000000..fb346bd --- /dev/null +++ b/content/post/2024-05-sd-ebm/index.md @@ -0,0 +1,40 @@ +--- +# Documentation: https://sourcethemes.com/academic/docs/managing-content/ + +title: "Filip Biljecki joins the Editorial Board of Scientific Data" +subtitle: "Our open science efforts continue to be recognised." +summary: "Our open science efforts continue to be recognised." +authors: [admin] +tags: [journals, publications, papers, open science, open data, open-source software] +categories: [] +date: 2024-05-19T13:39:19+08:00 +lastmod: 2024-05-19T13:39:19+08:00 +featured: false +draft: false +show_related: true +pager: true + +# Featured image +# To use, add an image named `featured.jpg/png` to your page's folder. +# Focal points: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight. +image: + caption: "" + focal_point: "" + preview_only: false + +# Projects (optional). +# Associate this post with one or more of your projects. +# Simply enter your project's folder or file name without extension. +# E.g. `projects = ["internal-project"]` references `content/project/deep-learning/index.md`. +# Otherwise, set `projects = []`. +projects: [] +--- + +Dr {{% mention "filip" %}}, the principal investigator of our research group, joins the Editorial Board of [Scientific Data](https://www.nature.com/sdata/), a top journal that is part of the [Nature Portfolio](https://www.nature.com/nature-portfolio). +[It is a peer-reviewed, open-access journal for descriptions of datasets, and research that advances the sharing and reuse of scientific data](https://www.nature.com/sdata/journal-information). + + +Our Lab is committed to open science, and [often releases data and software outputs openly](/data-code/). + +We have a couple of new exciting open datasets and open-source software packages coming out soon, stay tuned for the announcements! + diff --git 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