Merge pull request #125 from arfon/patch-3

Minor fixes

paper/paper.md

@@ -28,11 +28,6 @@ affiliations:
     index: 2
 date: 16 October 2020
 bibliography: paper.bib
-
-# Optional fields if submitting to a AAS journal too, see this blog post:
-# https://blog.joss.theoj.org/2018/12/a-new-collaboration-with-aas-publishing
-# aas-doi: 10.3847/xxxxx <- update this with the DOI from AAS once you know it.
-# aas-journal: Astrophysical Journal <- The name of the AAS journal.
 ---
 
 # Summary
@@ -43,23 +38,23 @@ Examples of such environmental factors are noise [@Stoter08], wind [@GarciaSanch
 However, those 3D models, which typically contain buildings and other man-made objects such as roads, overpasses, bridges, and trees, are in practice complex to obtain, and it is very time-consuming and tedious to reconstruct them manually.
 
 The software *3dfier* addresses this issue by automating the 3D reconstruction process.
-It takes 2D geographical datasets (eg topographic datasets) that consist of polygons and "3dfies" them (as in "making them three-dimensional"). 
+It takes 2D geographical datasets (e.g., topographic datasets) that consist of polygons and "3dfies" them (as in "making them three-dimensional"). 
 The elevation is obtained from an aerial point cloud dataset, and the semantics of the polygons is used to perform the lifting to the third dimension, so that it is realistic.
 The resulting 3D dataset is semantically decomposed/labelled based on the input polygons, and together they form one(many) surface(s) that aim(s) to be error-free: no self-intersections, no gaps, etc.
 Several output formats are supported (including the international standards), and the 3D city models are optimised for use in different software. 
 
 
 # Statement of need
 
-The 3D city models needed as input in environmental simulations have specific requirements that go beyond the typical 3D models used for visualisation: they require semantic information (ie an object, modelled with one or more surfaces, "knows" what it is, for instance a window or a roof surface) and they should be free of geometric errors.
+The 3D city models needed as input in environmental simulations have specific requirements that go beyond the typical 3D models used for visualisation: they require semantic information (i.e., an object, modelled with one or more surfaces, "knows" what it is, for instance a window or a roof surface) and they should be free of geometric errors.
 It is known that practitioners and researchers wanting to perform some simulations or analysis can spend a significant part of their time constructing and repairing the input 3D models; @McKenney98 estimates this to as much as 70\% of their time.
 Furthermore, the formats required by the different software and/or the agencies (for instance [the international standard CityGML](https://www.ogc.org/standards/citygml)), are complex to generate [@Ledoux19].
 
 The software *3dfier* automates the reconstruction step, it enriches the data with semantics, and it supports several output formats (used in different fields).
 
-It builds upon previous work done for reconstructing the whole country of the Netherlands (with 10M+ buildings) [@OudeElberink13], and provides the following improvements: use of recent and maintained libraries (eg [CGAL](https://www.cgal.org/), [GDAL](https://gdal.org/) and [Boost](https://www.boost.org/)), a clear open-source license, recent formats and international standards are supported, no geometric errors in output.
+It builds upon previous work done for reconstructing the whole country of the Netherlands (with 10M+ buildings) [@OudeElberink13], and provides the following improvements: use of recent and maintained libraries (e.g., [CGAL](https://www.cgal.org/), [GDAL](https://gdal.org/) and [Boost](https://www.boost.org/)), a clear open-source license, recent formats and international standards are supported, no geometric errors in output.
 
-There exist different commercial software that can perform extrusion (eg [Safe FME](https://www.safe.com/fme/) or [ArcGIS](https://www.arcgis.com/)), but these extrude each classes of objects separately (usually only buildings), without ensuring that adjacent objects should be "stitched" together.
+There exist different commercial software that can perform extrusion (e.g., [Safe FME](https://www.safe.com/fme/) or [ArcGIS](https://www.arcgis.com/)), but these extrude each classes of objects separately (usually only buildings), without ensuring that adjacent objects should be "stitched" together.
 As a result, the resulting 3D dataset is often unsuitable as input for other spatial analysis software.
 
 
@@ -79,7 +74,7 @@ Each of the classes in the input 2D polygons is mapped to a specific class: *Ter
 The semantics of every input 2D polygon is used to perform the lifting to the third dimension.
 For example, water polygons are extruded to horizontal polygons, buildings to prismatic blocks, roads as smooth surfaces, etc. 
 Every polygon is triangulated and in a next step the lifted polygons are "stitched" together so that one surface is reconstructed. 
-In this step, priority is given to "hard" objects such as roads, ie vegetation polygons are moved to be aligned with the road polygons.
+In this step, priority is given to "hard" objects such as roads, i.e., vegetation polygons are moved to be aligned with the road polygons.
 The output of the software is one watertight surface with no intersecting triangles and no holes, and features such as buildings and trees can be added or omitted.  
 Triangles are grouped and labelled with the class and the attributes that were in the input 2D polygons they decompose.
 This surface can be used directly as input in several urban applications, such as simulations of noise or wind.