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smzw1s%Wv^4#}mZUTj>1VH-Qx$6vh*H#3BV&5Tt=_L(0Xaq@_&yKQAL#T>t<8 literal 0 HcmV?d00001 From 2513116165beaf7799d82d287e6e1861c1f8815b Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:15:18 +0000 Subject: [PATCH 2/4] Creating 10.21105.joss.07123.crossref.xml --- joss.07123/10.21105.joss.07123.crossref.xml | 230 ++++++++++++++++++++ 1 file changed, 230 insertions(+) create mode 100644 joss.07123/10.21105.joss.07123.crossref.xml diff --git a/joss.07123/10.21105.joss.07123.crossref.xml b/joss.07123/10.21105.joss.07123.crossref.xml new file mode 100644 index 0000000000..85ea4f8784 --- /dev/null +++ b/joss.07123/10.21105.joss.07123.crossref.xml @@ -0,0 +1,230 @@ + + + + 20241112161436-754e67c994e04326511627c03b4afc22298bba32 + 20241112161436 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 11 + 2024 + + + 9 + + 103 + + + + startinpy: A Python library for modelling and +processing 2.5D triangulated terrains + + + + Hugo + Ledoux + + Delft University of Technology, the Netherlands + + https://orcid.org/0000-0002-1251-8654 + + + + 11 + 12 + 2024 + + + 7123 + + + 10.21105/joss.07123 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.14001126 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/7123 + + + + 10.21105/joss.07123 + https://joss.theoj.org/papers/10.21105/joss.07123 + + + https://joss.theoj.org/papers/10.21105/joss.07123.pdf + + + + + + Voronoi diagrams and Delaunay +triangulations + Aurenhammer + 10.1142/8685 + 2012 + Aurenhammer, F., Klein, R., & +Lee, D.-T. (2012). Voronoi diagrams and Delaunay triangulations. World +Scientific. https://doi.org/10.1142/8685 + + + Transforming triangulations + Lawson + Discrete Applied Mathematics + 3 + 10.1016/0012-365X(72)90093-3 + 1972 + Lawson, C. L. (1972). Transforming +triangulations. Discrete Applied Mathematics, 3, 365–372. +https://doi.org/10.1016/0012-365X(72)90093-3 + + + Spatial height prediction of ICESat-2 data +using random forest regression + Kan + 2024 + Kan, L. W. L. (2024). Spatial height +prediction of ICESat-2 data using random forest regression [Master’s +thesis]. MSc thesis in Geomatics, Delft University of +Technology. + + + Canopy gap fraction estimation from ICESat-2 +ATL08 product + Meschin + 2023 + Meschin, K. (2023). Canopy gap +fraction estimation from ICESat-2 ATL08 product [Master’s thesis]. MSc +thesis in Geomatics, Delft University of +Technology. + + + A brief description of natural neighbour +interpolation + Sibson + Interpreting multivariate +data + 1981 + Sibson, R. (1981). A brief +description of natural neighbour interpolation. In V. Barnett (Ed.), +Interpreting multivariate data (pp. 21–36). +Wiley. + + + The non-Sibsonian interpolation: A new method +of interpolation of the values of a function on an arbitrary set of +points + Belikov + Computational Mathematics and Mathematical +Physics + 37 + 1997 + Belikov, V. V., Ivanov, V. D., +Kontorovich, V. K., Korytnik, S. A., & Semenov, A. Y. (1997). The +non-Sibsonian interpolation: A new method of interpolation of the values +of a function on an arbitrary set of points. Computational Mathematics +and Mathematical Physics, 37, 9–15. + + + Fast polygonal approximation of terrain and +height fields + Garland + 1995 + Garland, M., & Heckbert, P. S. +(1995). Fast polygonal approximation of terrain and height fields +(CMU-CS-95-181). School of Computer Science, Carnegie Mellon University; +School of Computer Science, Carnegie Mellon +University. + + + DeltaDTM: A global coastal digital terrain +model + Pronk + Nature Scientific data + 273 + 11 + 10.1038/s41597-024-03091-9 + 2024 + Pronk, M., Hooijer, A., Eilander, D., +Haag, A., Jong, T. de, Vousdoukas, M., Vernimmen, R., Ledoux, H., & +Eleveld, M. (2024). DeltaDTM: A global coastal digital terrain model. +Nature Scientific Data, 11(273). +https://doi.org/10.1038/s41597-024-03091-9 + + + Delete and insert operations in +Voronoi/Delaunay methods and applications + Mostafavi + Computers & Geosciences + 4 + 29 + 10.1016/S0098-3004(03)00017-7 + 2003 + Mostafavi, M. A., Gold, C. M., & +Dakowicz, M. (2003). Delete and insert operations in Voronoi/Delaunay +methods and applications. Computers & Geosciences, 29(4), 523–530. +https://doi.org/10.1016/S0098-3004(03)00017-7 + + + Compact representations of simplicial meshes +in two and three dimensions + Blandford + International Journal of Computational +Geometry and Applications + 1 + 15 + 10.1142/S0218195905001580 + 2005 + Blandford, D. K., Blelloch, G. E., +Cardoze, D. E., & Kadow, C. (2005). Compact representations of +simplicial meshes in two and three dimensions. International Journal of +Computational Geometry and Applications, 15(1), 3–24. +https://doi.org/10.1142/S0218195905001580 + + + Robust adaptive floating-point geometric +predicates + Shewchuk + Proceedings 12th annual symposium on +computational geometry + 10.1145/237218.237337 + 1996 + Shewchuk, J. R. (1996). Robust +adaptive floating-point geometric predicates. Proceedings 12th Annual +Symposium on Computational Geometry, 141–150. +https://doi.org/10.1145/237218.237337 + + + + + + From 62f3af78b36b653d4ddd5a92cf3a546bcef98c03 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:15:18 +0000 Subject: [PATCH 3/4] Creating 10.21105.joss.07123.jats --- .../paper.jats/10.21105.joss.07123.jats | 376 ++++++++++++++++++ 1 file changed, 376 insertions(+) create mode 100644 joss.07123/paper.jats/10.21105.joss.07123.jats diff --git a/joss.07123/paper.jats/10.21105.joss.07123.jats b/joss.07123/paper.jats/10.21105.joss.07123.jats new file mode 100644 index 0000000000..f87c05810b --- /dev/null +++ b/joss.07123/paper.jats/10.21105.joss.07123.jats @@ -0,0 +1,376 @@ + + +

+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +7123 +10.21105/joss.07123 + +startinpy: A Python library for modelling and processing +2.5D triangulated terrains + + + +https://orcid.org/0000-0002-1251-8654 + +Ledoux +Hugo + + + + + +Delft University of Technology, the +Netherlands + + + + +17 +7 +2024 + +9 +103 +7123 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2024 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Delaunay triangulation +Python +terrain +interpolation +GIS + + + + + + Summary +

startinpy is a Python library for modelling and + processing terrains using a two-dimensional (2D) Delaunay + triangulation (DT). The triangulation is computed in 2D, but the + z-elevation of the vertices is kept (which is referred to as 2.5D + modelling).

+

Given a dataset formed of elevation samples (eg collected with + lidar or photogrammetry), startinpy allows us to reconstruct a + terrain, to remove points, to search efficiently in the triangulation, + to attach attributes to the vertices, and to convert to a gridded + terrain. Additional functionality is provided, including a few spatial + interpolation methods based on the DT and/or its dual structure, the + Voronoi diagram, have been implemented: linear interpolation, natural + neighbours + (Sibson, + 1981), and Laplace interpolation + (Belikov + et al., 1997).

+

The core of the library is written in + Rust + (so it can process large datasets quickly), robust arithmetic is used + for the updating of the DT (the robust predicates of Shewchuk + (1996) + are used), and it uses NumPy for input/output of data, which allows it + to integrate with other Python libraries used by researchers.

+

The core of the library has been used to build a global coastal + terrain using laser altimetric measurements from the space station + (Pronk + et al., 2024), and it has been used for several projects + dealing with aerial and space lidar datasets, for instance Meschin + (2023) and + Kan + (2024).

+

While startinpy was developed primarily to build and manipulate + terrains, it can be used as an easy-to-use and fast 2D Delaunay + triangulator (and Voronoi diagram generator), which, as elaborated in + Aurenhammer et al. + (2012), + are two structures that play an essential role in several disciplines: + astronomy, geology, ecology, engineering, etc.

+ +

A lidar dataset terrain reconstructed with startinpy and + visualised with another Python library (Polyscope).

+ +
+
+ + Statement of need +

While there exist many Python libraries for computing the DT in 2D + (a search for “Delaunay triangulation” in the + Python + Package Index (PyPI) returns over 200 packages), + most of them are not fully suitable for the modelling of 2.5D + triangulated terrain.

+

startinpy has the following properties, which greatly improve the + modelling and processing of 2.5D terrains.

+

It is fast for large datasets. With a modern lidar + scanner, we can easily collect 50 + samples/ + + m2, + which means that a 1 + + km2 + area will contain 50+ million samples. Since constructing a DT + requires several steps, if those steps are implemented in pure Python + then the library becomes very slow. As can be seen in the + DT + construction comparison, startinpy is faster than most + other libraries for large datasets. This is partly because it is 100% + developed in Rust; the core library is called “startin” and its the + source code is available at + https://github.com/hugoledoux/startin.

+

Its data structure is exposed. Most libraries only + return a list of vertices and triangles (triplets of vertex + identifiers), which means that the user has to build an auxiliary + graph to be able to find the adjacent triangles of a given one, or to + find all the triangles that are incident to a given vertex (eg to + calculate the normal). The name “startinpy” comes from the fact that + the data structure implemented is based on the concept of + stars in a graph + (Blandford + et al., 2005), which allows us to store adjacency and + incidence, and have a very compact data structure. startinpy exposes + methods to search triangles, find the adjacent triangles of a + triangle, and find the incident triangles to a vertex.

+

The DT is incrementally constructed and deletion of vertices + is possible. Unlike the majority of 2D DT implementations, + startinpy implements an incremental insertion + algorithm + (Lawson, + 1972), which allows for constructing a simplified TIN that best + approximates the original terrain with only 10% of the points; see + Garland & Heckbert + (1995) for + different strategies. startinpy also implements a modification of the + deletion algorithm in Mostafavi et al. + (2003), + extended to allow the deletion of vertices on the boundary of the + convex hull. The deletion of vertices in a DT is useful to remove + outliers (which are detected by analysing neighbouring triangles in + the DT) and for the implementation of the natural neighbours + interpolation method + (Sibson, + 1981).

+

The z-values are stored and xy-duplicates handled. + Some libraries allow us to attach extra information to a vertex, but + most often one has to build an auxiliary data structure in Python to + manage those. Doing so is error-prone, tedious, and makes operations + in 3D more complex (eg calculating the slope of an area, calculating + the normal of a vertex, estimating the elevation with spatial + interpolation, calculating volumes). By storing the z-values, + startinpy allows us to merge vertices that are close to each other (in + the xy-plane; the tolerance can be defined by the user) and if there + are xy-duplicates, then a user-defined z-value can be kept (eg lowest + or highest, depending on the application).

+

Extra attributes can be stored in the DT. It is + possible to attach extra attributes with each vertex of the terrain. + This can be used to preserve the lidar properties of the input points + (eg intensity, RGB, number of returns, etc.).

+

The + documentation + of startinpy contains several examples of the library and + how it can be used to prepare datasets for input to machine learning + algorithms, to convert to different formats used in practice, to + interpolate, etc.

+
+ + Acknowledgements +

I acknowledge the help of the students following the course + Digital + terrain modelling (GEO1015) at TUDelft over the + last few years. Their feedback, questions, and frustrations on + preliminary versions of startinpy helped me greatly.

+
+ + + + + + + + AurenhammerFranz + KleinRolf + LeeDer-Tsai + + Voronoi diagrams and Delaunay triangulations + World Scientific + 2012 + 10.1142/8685 + + + + + + LawsonCharles L. + + Transforming triangulations + Discrete Applied Mathematics + 1972 + 3 + 10.1016/0012-365X(72)90093-3 + 365 + 372 + + + + + + KanL. W. L. + + Spatial height prediction of ICESat-2 data using random forest regression + MSc thesis in Geomatics, Delft University of Technology + 2024 + + + + + + MeschinKatrin + + Canopy gap fraction estimation from ICESat-2 ATL08 product + MSc thesis in Geomatics, Delft University of Technology + 2023 + + + + + + SibsonRobin + + A brief description of natural neighbour interpolation + Interpreting multivariate data + + BarnettVic + + Wiley + New York, USA + 1981 + 21 + 36 + + + + + + BelikovV. V. + IvanovV. D. + KontorovichV. K. + KorytnikS. A. + SemenovA. Y. + + The non-Sibsonian interpolation: A new method of interpolation of the values of a function on an arbitrary set of points + Computational Mathematics and Mathematical Physics + 1997 + 37 + 9 + 15 + + + + + + GarlandMichael + HeckbertPaul S. + + Fast polygonal approximation of terrain and height fields + School of Computer Science, Carnegie Mellon University; School of Computer Science, Carnegie Mellon University + Pittsburgh, PA, USA + 1995 + + + + + + PronkMaarten + HooijerAljosja + EilanderDirk + HaagArjen + JongTjalling de + VousdoukasMichalis + VernimmenRonald + LedouxHugo + EleveldMarieke + + DeltaDTM: A global coastal digital terrain model + Nature Scientific data + 2024 + 11 + 273 + 10.1038/s41597-024-03091-9 + + + + + + MostafaviMir Abolfazl + GoldChristopher M. + DakowiczMaciej + + Delete and insert operations in Voronoi/Delaunay methods and applications + Computers & Geosciences + 2003 + 29 + 4 + 10.1016/S0098-3004(03)00017-7 + 523 + 530 + + + + + + BlandfordDaniel K. + BlellochGuy E. + CardozeDavid E. + KadowClemens + + Compact representations of simplicial meshes in two and three dimensions + International Journal of Computational Geometry and Applications + 2005 + 15 + 1 + 10.1142/S0218195905001580 + 3 + 24 + + + + + + ShewchukJonathan Richard + + Robust adaptive floating-point geometric predicates + Proceedings 12th annual symposium on computational geometry + ACM Press + Philadelphia, USA + 1996 + 10.1145/237218.237337 + 141 + 150 + + + + +
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