A sample of Penang Walking Track Map |
Having worked for Australian travel guide company, Explore Australia, I was exposed to the variety of their products for the travel market. One of my projects I was involved was to produce hiking guides for New South Wales. I think the key successes of this book were dedicated, passionate authors and good quality maps. The authors, who love hiking, logged their tracks and this data was subsequently used for the maps. In a company where mapping is important, we are able to access our database of various map datasets. Mash these information, you have good quality maps with information closely related to the text. I think this is where we should draw inspiration from if we ever embark hiking guides for Malaysia
Having said that, the map above on blog display was created one week before I started doing hiking maps for my company. That is why there is a difference what my map looks like and what my company's maps in its hiking guide. Now, we know the background on the situation. We know what Penang has to offer, what existing Malaysian product demonstrates and what my company's approach to hiking maps. This article will give a gist on the workflow for this map production and the challenges
Preparatory materials
In making a map, roughly 80% of your time would be consumed to find data. Digital spatial data are the lineworks, polygons and dots that you find the map. They have a spatial component (coordinates, height) and attribute component (feature type, classification). For the map above to be made, most important data we need is hiking track data. Other datasets would be required are contour data, rivers, geographical features, roads and points of interest. Well, I do not list out like this way when I did this map. All happened in my brain and modified over time. Datasets consume a lot of money but this project I sourced all of them from free sources. My dad has logged this hiking track many months ago with his GPS. Through my university senior (who shares similar passion in mapping), I have came to know free source of contour datasets. The rivers were not added on the map due to the difficulty of digitization and lack of free viable dataset source. Rest of the information was sourced from government maps, Google and Open Street Map (OSM). These are the preparatory materials for this map.
Procedures to make maps
First of all, in every map you make, you need the datasets which I have described in detail in the previous section. Once the datasets assembled, we need to find out how to transform these datasets into viable and user-friendly map.
1) I have track gpx (a GPS file) file from my Dad. However, I realized my existing geospatial skills became a little obstacle in this process of making map. The gpx file could not be uploaded into my GIS software, ArcGIS version 10. In this process of making maps, we always hit obstacles but the success lies in our problem-solving skills.
2) With my existing knowledge, on Google Earth, I digitized over the gpx file and saved as a kml/kmz file (Google Earth file). For the sake of creating a sample map, this time-consuming process is worth the shot. However, if I am making full-blown hiking guide, better alternatives should be explored.
3) I realized that the kmz file could not be directly uploaded onto the ArcGIS sofware. After bit of search, I came to a website which converts kml to shapefiles (where ArcGIS software can accept and display geographic data). After trials with it, I was successful in converting the kmz files into shapefiles.
4) Meantime, in ArcGIS software, I created a personal geodatabase where I assemble the various datasets. These track shapefiles were exported into the geodatabse. In my limited knowledge, I see a geodatabase an effective storage of datasets for a project. This is opposed to have dataset files kept everywhere.
5) For the case of my existing knowledge, I do not know which map projection is suitable for this track map. I have not been exposed to map projection parameters for Malaysia and specifically, Malaysia. The default coordinates of all the datasets were placed in WGS84 (the coordinate system that underpins the American GPS). The map projection is the process of transforming 3D coordinates (e.g. WGS84) or surfaces into 2D surfaces or coordinates (e.g. Mercator Map projection).
6) In ArcGIS, the datasets layers were organized according to visibility priority. The Track maps, roads and points of interest should be at the top of all layers. Contour data should be placed below. I created new shapefiles such as roads, points of interests, geographical features and place names. I converted a raster (Cell-based datasets) contour file into a vector file (resulted in contour lines).
7) From here, I scaled the map to a large-scale map (which I was pushing the limit of some of datasets' accuracy), added suitable colours for the datasets and final-touch-ups were performed. For further cartographic touch-ups, the ArcGIS map was exported into a Illustrator file.
8) In Illustrator, there was significant fixing with the map layers in the map that was just exported. This is where I placed text for key features. ArcGIS version 10, despite the strides, is still limited in text placement. Text-placement is one of the most difficult part of map production. Additional items on the map (Shown above in the image) were subsequently added.
9) For display purposes, the Illustrator file was exported into JPEG file. It was first posted on facebook and received reasonable liking and subsequently, the same JPEG is exported to the blog.
This is the 9 steps in making the map and it took nearly full two days to complete it. From here, I will address the challenges and limitations of this map.
4) Meantime, in ArcGIS software, I created a personal geodatabase where I assemble the various datasets. These track shapefiles were exported into the geodatabse. In my limited knowledge, I see a geodatabase an effective storage of datasets for a project. This is opposed to have dataset files kept everywhere.
5) For the case of my existing knowledge, I do not know which map projection is suitable for this track map. I have not been exposed to map projection parameters for Malaysia and specifically, Malaysia. The default coordinates of all the datasets were placed in WGS84 (the coordinate system that underpins the American GPS). The map projection is the process of transforming 3D coordinates (e.g. WGS84) or surfaces into 2D surfaces or coordinates (e.g. Mercator Map projection).
6) In ArcGIS, the datasets layers were organized according to visibility priority. The Track maps, roads and points of interest should be at the top of all layers. Contour data should be placed below. I created new shapefiles such as roads, points of interests, geographical features and place names. I converted a raster (Cell-based datasets) contour file into a vector file (resulted in contour lines).
7) From here, I scaled the map to a large-scale map (which I was pushing the limit of some of datasets' accuracy), added suitable colours for the datasets and final-touch-ups were performed. For further cartographic touch-ups, the ArcGIS map was exported into a Illustrator file.
8) In Illustrator, there was significant fixing with the map layers in the map that was just exported. This is where I placed text for key features. ArcGIS version 10, despite the strides, is still limited in text placement. Text-placement is one of the most difficult part of map production. Additional items on the map (Shown above in the image) were subsequently added.
9) For display purposes, the Illustrator file was exported into JPEG file. It was first posted on facebook and received reasonable liking and subsequently, the same JPEG is exported to the blog.
This is the 9 steps in making the map and it took nearly full two days to complete it. From here, I will address the challenges and limitations of this map.
(Article under construction)
Can you share. troydiack@gmail.com
ReplyDeleteI will share with you. Sorry for the late reply
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