Merge pull request #456 from ualsg/update

Add new open-source software and update the open data SG guide

content/data-code/index.md

@@ -34,6 +34,51 @@ We would be pleased to learn how others are using our work.
 If you are interested in collaborating with us, please get in touch with the lead developer of each resource listed below.
 
 
+## TreeShadeMapper
+
+![](TreeShadeMapper.png)
+
+| | |
+| ------------------| ------------------------------ |
+| Short description: | A panorama-based technique to estimate sky view factor and solar irradiance considering transmittance of tree canopies |
+| Lead developer: | {{% mention "kunihiko" %}} |
+| Further reading: | Please read the [paper](https://doi.org/10.1016/j.buildenv.2024.112071) published in BAE |
+| Code: | [<i class="fab fa-github"></i>  Github repo](https://github.com/kunifujiwara/TreeShadeMapper) |
+| Citation: | {{< spoiler text="Click to view the BibTeX entry" >}}
+@article{2024_bae_svf,
+  author = {Fujiwara, Kunihiko and Ito, Koichi and Ignatius, Marcel and Biljecki, Filip},
+  doi = {10.1016/j.buildenv.2024.112071},
+  journal = {Building and Environment},
+  pages = {112071},
+  title = {A panorama-based technique to estimate sky view factor and solar irradiance considering transmittance of tree canopies},
+  volume = {266},
+  year = {2024}
+}
+{{< /spoiler >}}|
+
+
+## Microclimate Vision
+
+![](microclimate-vision.jpg)
+
+| | |
+| ------------------| ------------------------------ |
+| Short description: | Multimodal prediction of climatic parameters using street-level and satellite imagery |
+| Lead developer: | {{% mention "kunihiko" %}} |
+| Further reading: | Please read the [paper](https://doi.org/10.1016/j.scs.2024.105733) published in SCS |
+| Code: | [<i class="fab fa-github"></i>  Github repo](https://github.com/kunifujiwara/microclimate-vision) |
+| Citation: | {{< spoiler text="Click to view the BibTeX entry" >}}
+@article{2024_scs_microclimate_vision,
+  author = {Fujiwara, Kunihiko and Khomiakov, Maxim and Yap, Winston and Ignatius, Marcel and Biljecki, Filip},
+  doi = {10.1016/j.scs.2024.105733},
+  journal = {Sustainable Cities and Society},
+  pages = {105733},
+  title = {Microclimate Vision: Multimodal prediction of climatic parameters using street-level and satellite imagery},
+  volume = {114},
+  year = {2024}
+}
+{{< /spoiler >}}|
+
 ## Global Streetscapes
 
 ![](global-streetscapes.jpg)
@@ -43,6 +88,7 @@ If you are interested in collaborating with us, please get in touch with the lea
 | Short description: | A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics. |
 | Lead developer: | {{% mention "yujun" %}} |
 | Further reading: | Please read the [paper](https://doi.org/10.1016/j.isprsjprs.2024.06.023) published in the ISPRS Journal of Photogrammetry and Remote Sensing |
+| Website: | [<i class="fas fa-home"></i> Website](/project/global-streetscapes) |
 | Download: | [<i class="fab fa-github"></i> Github repo](https://github.com/ualsg/global-streetscapes) |
 | Main data source(s): | Mapillary, KartaView, OpenStreetMap, GADM, ... and manual labelling |
 | Coverage: | 688 cities around the world | 

content/post/2020-06-open-data-singapore/index.md

@@ -65,8 +65,9 @@ While there are other instances not mentioned here, these are the datasets we co
 It also includes non-residential blocks such as multi-storey carparks.
 It does not contain building footprints though.
 We used this dataset as one of the input datasets to generate [3D building models]({{< ref "/post/2019-08-hdb-3d/index.md" >}}).
+* Geometric footprints of HDB buildings is available [here](https://data.gov.sg/collections/2033/view).
 * Data on non-HDB buildings (landed houses, condos, commercial buildings...) is not as complete and it is scattered around, but [URA's data portal](https://www.ura.gov.sg/realEstateIIWeb/supply/search.action) is a good starting point for exploration.
-* For open data on building footprints the best bet is OpenStreetMap, it has [nearly 100% completeness with rapid updates]({{< ref "/post/2020-08-osm-singapore-building-data-quality/index.md" >}}), but attribute data may lack.
+* For open data on all building footprints the best bet is OpenStreetMap, it has [nearly 100% completeness with rapid updates]({{< ref "/post/2020-08-osm-singapore-building-data-quality/index.md" >}}), but attribute data may lack.
 Data.gov.sg contains [a dataset representing building footprints](https://data.gov.sg/dataset/master-plan-2014-building), but for some reason it is not complete, covering only a subset of buildings several years ago.
 It still might be useful though.
 * Check out [Roofpedia](/project/roofpedia/), our project that maps solar panels and green roofs on buildings, which includes open data on Singapore, together with several other cities.
@@ -223,7 +224,8 @@ Satellite imagery is available for academia through the [Planet's Education and
 
 ### Point clouds (LiDAR), terrain data
 
-None, except terrain data of coarse resolution such as [SRTM](https://www2.jpl.nasa.gov/srtm/).
+Pretty much none, except terrain data of coarse resolution such as [SRTM](https://www2.jpl.nasa.gov/srtm/).
+Please see also [this page](https://ugl.sg/2022/10/03/dem-of-singapore-srtm/) from the [NUS Urban Green Lab](https://ugl.sg).
 
 ### Street-level imagery
 
@@ -276,6 +278,10 @@ The usual caveats:
 * Some geospatial datasets may not pass all validity checks (e.g. they might have self-intersecting polygons), presenting a problem when they are used in spatial analyses.
 You can try fixing them using [prepair](https://github.com/tudelft3d/prepair).
 
+### Further reading
+
+You might also want to check out [this page](https://nusgis.org/data/) by NUS Geography collaborator [Yingwei Yan](https://discovery.nus.edu.sg/19079-yingwei-yan). 
+
 ### Have a suggestion for an entry? Spotted an error?
 
 [Get in touch](/#contact).