Celebrating International Women’s Day- Mapping Insights

Another day, and another ‘international [insert here] day’. However, unlike ‘International Toast Day’ (15th July for those interested), today, 8th March, was one that actually had great significance – International Women’s Day. Despite being a guy,  I recognise that while progress has been made, we are still some way of gender equality. Given that 50% of the world’s population is female, and there is no logical reason why income, job, social, educational opportunities and choices shouldn’t be the same as men – this situation isn’t good enough. However I don’t feel I should go on further, as I don’t think I can do the topic of feminism justice. What I can do is produce some geospatial analysis however to mark this.

There are many areas I thought about looking into to highlight the amount of progress still needed; adult literacy, women in top managerial roles, reproductive rights etc, to name a few. However, I decided to analyse the percentage of the adult labour force that is female, using data sourced by the World Bank. Data from 2014, in the map above, shows geographical and regional patterns of gender inequality in the labour force, particularly in stark in North Africa and the Middle East. Sure, a reasonable amount of ‘Western’ and African countries have more balanced levels of gender in the workforce, but only 8 countries have more women in the labour force than men.

Meanwhile over 100 countries have less than 45% of women in the labour force, 24 of these a shockingly below 30%. There maybe several cultural, social welfare, developmental and even legal reasons why these patterns occur, which I won’t delve into, but it is a important indicator in of itself.  This before you consider that this isn’t even the best indicator of gender inequality. This doesn’t account for the type of work being carried out by women here, which may be of lower wage and status, as well as population sizes and growth, leading to a skewing figures as well. It also doesn’t map, social attitudes to women, statistics can only allude. Even in a more gender equal workforce, this doesn’t mean the same opportunities or treatment.

Progress is a key point here too, and while there is a general positive trend in percentage growth of women in the work force between 1990 – 2014, according another map I produced above, there are many places where growth is stagnant, or even decreasing in percentage. Encouragingly, the areas of low percentage in the previous map, are generally areas of overall relative growth in women in the workforce. Nonetheless, there are many areas, particularly in India and Syria (war an important proviso here), where whatever the story, there is a sharp overall percentage decrease. This is only one indicator, but it highlights that, while for some this may be nauseatingly politically correct, there is much progress to be made.

Why does this matter? One, employment is an important factor in self-independence and social, academic and economic opportunities – a basic value that should be available to all, regardless of gender. Two, any organisation or company needs to thrive on the widest pool of talent and the diversity of ideas – with a greater gender equality (among ethnicity, sexuality and able-bodiedness), this is something that is potentially advantageous for us all.

Cartogram of Female Workforce

Happy Mapping,


PS: I know the cartogram isn’t the ideal analysis for this data metric, as there is no land mass relationship really, but it does weight and enlarge higher workforce percentages more, highlighting interesting case like Nepal, Lithuania and East Africa.

Data Credits: World Bank


Mapping the Arctic Circle – Then and Now

Mapping of the Arctic region has historically proved to be a challenge for cartographers and geo-scientists, though as referred to in a previous article (see here),  local knowledge is valuable in contributing to knowledge of the often perceived ‘wilderness’ by ‘Westerners’. In many ways, as alluded to in Alastair Bonnett’s brilliant book, Off the Map, despite living in an age of digital mapping, there is much geographic knowledge still to be discovered. This is perhaps most relevant and important, given global warming, in the Arctic region, and two recent articles associated to this piqued my interest in this area, and thought it would be a good follow up to my previous Arctic related post.


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Surge of news in UK GIS Flood Datasets

Surge of news in UK GIS Flood Datasets

For those involved in flood mapping, environmental planning /change, or just a passing interest; there has been a recent surge in news on GIS flood mapping datasets in the UK.

Environment Agency Flood Map for Planning

Firstly, the Environment Agency has recently this month, updated its National Flood Map for Planning (Rivers and Sea) database, mapping Flood Zone 2 (1 in 1,000 year flood) and Flood Zone 3 (1 in 100 year flood), and areas of flood defences and those benefiting from flood defences. My experience of using this data in the past has been that is has been useful at a indicative larger scale, but less so at a smaller scale property level, however this was with much older data. This latest version appears to have greater detail to this, as well as being the most up to date. Along with the highly informative and reliable NaFRA dataset, the Environment Agency, as well as National Resources Wales and SEPA, continue to lead the way in its work in national flood risk assessment. This mapping has for some reason trended among regional online papers particularly (e.g. herehere and here).

However, this wasn’t the only recent bit of news to trickle in, aerial mapping company Bluesky have made available online a Groundwater Flood Map on behalf of JBA Consulting. I cannot comment on the usability of this data, without having downloaded it myself, but it does sound particularly exciting and precise, especially when past groundwater data in UK has often been large scale rasters of all but indicative use. It is based on:

“a range of data, including known locations of past groundwater flooding events, rainfall measurements and aquifer properties, the new map provides classification of hazards on a 50 metre grid using a simple traffic-light system. A three tiered methodology, used to create the map, allows for quick and efficient updates and refining of the map for local areas of particular interest.”

I’d be interested to see what this dataset is like, with groundwater flooding and stores an important element in flood modelling, along with run off, and of course rainfall. I’ve been personally, particularly impressed with Bluesky’s previous work  with WMS services and datasets providing aerial photography, Ordnance Survey data, but also LiDAR and height data, and the use of image (tree crown) detection National Tree map. The latter of these is a personal favourite of mine, given one of my first pieces of work involved mapping notable trees from aerial and street photography. But these are two interesting developments, and with the likelihood of news of further development in TUFLOW and CH2M’s Flood Modeller software, it could be an interesting time in UK flood mapping. Hopefully it will be less interesting in flooding itself!

Happy Mapping,


The Urban Age – Global Population Changes

The Urban Age – Global Population Changes

One of the things I’ve enjoyed so far in creating The Map Den, is being able to share some of the latest and interesting pieces of work and tips coming out of the GIS and mapping industry. The ‘science of where‘ community is alive and strong. However, it’s time I did some original mapping content myself. Today I’m starting simple, but nonetheless importantly, looking at global urban and rural population increases.

Urban Population Change 2010-2015

Created through static maps created in ArcGIS and joining with population data from United Nations between 2010-2015, these maps investigate the continuing phenomenon of global population increase and the urban to rural shift. We can see from the urban map the general increase in urban population, particularly dramatic in Africa and Asia, similar to rocketing growth experienced in ‘Western’ industrialising countries around the industrial revolution. A stark example is you compare China’s urban population boom compared to sharp rural population decrease, where rural poverty and labour surplus have driven these trends (see more here and here)

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Fuzzy Lookup: My Plugin Baby

Fuzzy Lookup: My Plugin Baby

So this isn’t strictly a GIS or mapping tool or tip that I thought I’d share, but considering the amount of time and importance of joins, spreadsheets, datasets and databases in the profession, or even outside geospatial work, this little tool called ‘Fuzzy Lookup’ may come in handy.

Often when trying to query, search or join up one table to another, or for whatever purpose, VLOOKUP can do just the job, ‘vertically looking up’ one value, in order to display another. If you are new or unfamiliar to VLOOKUP, Debra Dalgleish has an awesome blog, Contextures to help with this and much more even for experienced users. There is the ‘range_lookup’ operator, FALSE, which will look for a identical match, or TRUE, an approximate match; the latter of these is useful for numbers, less so for text.


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3. Map of the Day – Map powered cars (ZAP MAP)

3. Map of the Day – Map powered cars (ZAP MAP)

Whether you drive an electric car, a ‘normal’ car, or don’t drive at all, this web and mobile (Android and iOS) application from ZapMap is well worth taking a look at. Powered by Google Maps API, this mapping tool provides the locations of electric car chargers, providing pop up boxes with the latest status of these charging points, types and directions on how to get there. Although the shading of the vector tiles is a bit gaudy, with an ability to log in, map and comment on charging points, there is potential for up-to-date community empowered mapping to provide latest running statuses and charging locations.


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