Introduction
From seeing potential in linking Mapping with Operations Improvement in 2018 to operating Intelloc Mapping Services - the business entity behind Mapmyops.com full-time post the Coronavirus pandemic, I feel excited when I receive responses to my email campaign from prospects seeking to know more about what my firm does, how it could benefit their organization, for addressing a query, or for quoting towards a current requirement. Often, I do get requests for demonstration from prospects - for a drone service trial, web map application, virtual presentation, site visit, and so on.
As there are a wide range of solutions that I offer and given that it is often not viable to provide a customized demonstration free of cost, I prefer to codify useful workflows into an article + video format, post it here on the website, and share those relevant ones with the prospect that come close to addressing the query. Naturally, I feel more inclined to be of service to someone who, by virtue of reviewing the content and knowing how I work, finds the idea of engaging with my firm and exploring a solution to be meaningful & potentially beneficial.
Another advantage of having the (50+) workflows published online is that it attracts readers from around the world, some students/young researchers even connect seeking to know more about a methodology or to access a particular dataset that I've used. This helps me to build my network and I hope to collaborate with a few of them when an opportunity arises, just like I have done before.
In this post, I will cover these workflows (hyperlinked to their respective section)-
You'd not be wrong to think that these topics are somewhat disparate - I had developed these workflow demonstrations for different prospects and well-wishers addressing their individual requirement. Besides the theme of what my firm does - Mapping for Operations, and the headline of this article - Finding Where to be (which I spent more than an hour to arrive at), there is virtually nothing in common between them. In reality, I could have very well chosen to flesh them out and create an individual post for each as the subject matter is wholesome. However, instinctively I felt that I had to close this loop in 2024 itself through this consolidated post - and start 2025 afresh!🤩
Let's begin...
Modeling 'Green' in Supply Chain Network Design
In this workflow, using a fictitious example involving the Supply Chain of Kissan - an established food brand in India, I’ll demonstrate how to apply Linear Programming using the Solver tool in Microsoft Excel to determine/design an optimal Supply Chain with the objective to achieve lower CO2 emissions from inbound and outbound transportation in a three-echelon network involving Agri-farms (Suppliers) → Kissan (Manufacturer) → Distributors (Customers).
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Reducing Greenhouse gas emissions help to progress towards United Nations’ Sustainable Development Goal #.13 on Climate Change which calls for urgent action to prevent the Earth to warm in excess of 1.5 degrees Celsius above pre-industrial levels (breached 1.1 degrees already).
The video demonstration enclosed below covers-
Optimizing Material Flows to arrive at the lowest Total Supply Chain Cost
Modeling in a 5% reduction in total GHG emissions (inbound + outbound CO2)
Explaining how the model adapts to the new constraint and re-optimizes Material Flows
For those unfamiliar with Supply Chain Network Design and how Linear Programming works, I'll recommend that you review my comprehensive work on this topic here. That being said, this demo was designed to be understood on a standalone-basis, so you can choose to view it straightaway.
Slider 1:Â Comparing the Optimized and GHG-Optimized Supply Chain Network of Kissan
While the technology to perform Operations Mapping has become more advanced over the years - with the capability to create really dynamic web and mobile applications - one should never undervalue the utility of having a printed 2D Map as handy reference.
Depicting a Supply Chain Network on a Map can not only serve as a diagram of reference for senior executives, it can even be used as training material to induct new joinees in the organization.
Route Mapping for Ascetics
Those with religious vows are duty bound to lead a self-disciplined and virtuous life. It so happens that in my culture, the ascetics choose not to reside at one location for long periods of time, lest they develop an attachment to it - something they are trying to free themselves from completely through their life of austerity and penance. As a result, they journey barefoot from one location to another throughout the year, barring the monsoon season (rationale here).
I've always harbored an inner wish that my Mapping services can be utilized to preserve and benefit my culture and Indian culture in general, but I had never really thought about how to go about making it a reality. One fine day, a rare visit to pay homage to a group of monks and a chance discussion with one of them about what I do for a living prompted a query-
The ascetics do not own or keep any material possessions and have extensive restrictions pertaining to using everyday-objects as well. So I snapped out my phone and upon querying Google Maps, relayed to the monk- 'There are three distinct routes to travel to Ayodhya, ranging from 550 kilometers to 660 kilometers, and only one viable route to travel to Bhopal subsequently which would be a further 680 kilometers. In order to complete the entire journey in the stipulated time-frame of two months, you'll have to cover 20-25 kilometers on an average daily'.
'We are familiar with the onward route to Bhopal, however, we've never visited Ayodhya from Parasnath before. Can you elaborate the three options for making this journey?'
'Route 1 is the shortest and it goes via Azamgarh...
Route 2 is slightly longer via Varanasi...
Route 3 is much longer via Gorakhpur, but you'll encounter several pilgrimage sites on the way...'
'Sounds interesting. You are into mapping, isn't it - can you chart these options on a map? I'll use it to consult the head monk and he will take the final decision about which route we should embark on.'
'Sure', I said sensing the glorious opportunity, 'I'll look to come back to you day-after-tomorrow'.
'That is fine. Do not waste a lot of paper.'
On my way back home, my mind had already begun racing-
- 'It is such an open-ended task!,' I muttered to myself - I should have asked the monk to specify what he wanted me to depict on the map
- 'Should I use Google Maps, or Google Earth, or a GIS software to create the map output?'
- 'How to best depict a 500+ kilometers-long walking route on a single piece of paper?'
- 'Should I use English or do I opt for a regional language to label the map?'
- 'How do I make a map that is of utility, something that the monks will will cherish?'
The navigation instructions to travel to Ayodhya, both visual and written, were highly detailed on Google Maps - the latter ran into more than half a dozen pages in standard font size. I wondered to myself-
- 'Can I find a way to condense this information without it losing its efficacy?'
- 'Is there any other way to depict the route information on a map?'
While I could toggle the language mode and download the instructions from Google Maps in the regional Hindi as well as the native Gujarati language, I decided against using the navigation instructions altogether - it dawned on me that I'd be better off using a professional map-making software (GIS) to present all relevant information aesthetically on a piece of paper instead of obtusely trying to fit in all of Google Maps' navigation instructions somehow. As a result, I turned to the highly reliable Esri ArcGIS Pro software.
Because it is a creator platform (Geographic Information System) and not a navigation tool like Google Maps, I would have to first build my own Location dataset and subsequently reverse geocode it onto the map layer in ArcGIS Pro.
Given that the monks would need to travel ~20 kilometers daily on an average and reach a resting place by evening, I deemed it necessary to depict a suitable stopover location at/below this distance interval on the map. Therefore, I began to scour Google Maps for urban, semi-urban, and large rural settlements that lie directly adjacent or near the route which are compatible with this criteria.
As the routes to Ayodhya from Parasnath traversed through populous plains in the states of Jharkhand, Bihar and Uttar Pradesh respectively, I had little difficulty in finding reasonably large settlements 15-20 kilometers apart from each other. Fortunately, Google Maps even labels settlements based on its relative importance in the search extent - notice how the village Aoura is labelled in caps at 0:12 mark in Video 3 above - this made it easier for me to spot and select the largest settlement from the available options.
Now having a list of settlements which could be suitable for night halts, I proceeded to add their coordinates and other relevant attributes to the dataset, knowing fully well that it would be useful while working on the labelling and symbology later.
And with the help of Google Translate, I also created a Gujarati language version of the Location Dataset (native to the ascetics)-
I chose to do this as I preempted that just having a Map-based visual output wouldn't be ideal. Instead, this data table can be printed on the back of the map document and would serve as a handy ready-reckoner. As it is, the text and labels on the map would be written in English as ArcGIS Pro doesn't seem to support regional Indian languages - while the monks can read and understand simple English, having the information printed separately in their native language on the map document itself would be convenient. Besides, I had also anticipated that depicting all the information on the map a) may not be necessary and b) would contribute to clutter, and hence, having a separate data table capturing all the attributes of the location dataset would be a much better option.
Slowly but surely, the skeleton of my output was forming and I felt optimistic...
While I had identified the settlements that were compatible with the daily distance criteria, I wondered if I could go a step ahead and find a resting spot within each of them. I had known that, when stationary during the monsoon season, the ascetics typically reside at a resting place attached to/in the vicinity of their religion's place of worship. The only thing they need is a covered shelter - no beds (as they sleep on the floor), no kitchen (as they seek food as alms everyday, typically from households from the same religious background), no electricity or telephones (as they desist from material comforts) and no security guards (as they do not possess anything worth securing).
Upon enquiring, I figured that the monks are accustomed to not finding temple-affiliated rest houses everyday on their journey and instead seek shelter at schools, bus stations and other public spots. They gather the information about suitable resting spots from the locals daily during their journey.
I felt that if I could find and map one temple per settlement, the monks can visit it straightaway and obtain directions to a suitable resting spot from there, thereby saving them time and effort as well as allowing them to rest at a private enclosure.
I began the online search for it, however, as anticipated, there weren't many such temples to be found on two of the three routes to Ayodhya.
Having no option but to manage with what I had, I proceeded to visualize the completed Location Dataset on a map - the outer skin of the activity. However, it took me a lot of time to do so. Let me highlight the dilemmas that I faced-
Selecting an appropriate Basemap was a bit confusing to begin with - whether to show the terrain, or the topography, or aerial imagery, or to keep the background plain
There were roughly sixty settlements in a route to plot and label on the map and by virtue of it being a contiguous path, the data points appeared clustered on the map i.e. they were not dispersed evenly across the map extent which would have rendered well visually
Settling on a Symbology was challenging too - what size of text to use?, what colors to use in order to best represent the relativity between the attributes (villages vs. towns vs. cities)?, etc.
Basemaps are usually accompanied by Reference layers which display the location and labels of major topographic features such as cities, rivers and roads. To determine whether to display all of them, or any of them, or which ones from them was a difficult decision
Navigation and directionality were important aspects that needed to be taken care of. Displaying the actual path to take, besides being technically arduous to do, wouldn't have added meaning to the map output given there were hundreds of roads and streets strewn across the length of the journey and the visual rendition of it would either be unreadable, uninterpretable, cluttered, or even partially invisible if I set up preferential labeling based on some logic. I was not even sure whether the roads data would be completely reliable as I would extract it from the open-source Open Street Maps datasets. I was ready to compromise on visual aesthetics in favor of displaying relevant data-points but limited workable space on the map was a major obstacle
Certain minor aspects were also there, such as - 'should I display the Water bodies?'. There were several of them, big and small, alongside/intersecting the route - 'perhaps the monks would prefer a route which had fewer of them due to the risk of flooding?', I wondered...
Eventually, I was able to settle down on this visualization-
To summarize, I chose-
to keep label sizes relative, based on the type of settlement
to use a single text color to maintain consistency
to use a different color for the reverse geocoded settlement, bases on the type (city/town/village)
to highlight the total distance elapsed in the label - one can calculate distance to the next stop, if needed, using this information (both these data points would be depicted in the data table)
to use a terrain basemap without hillshade and reference layer in order to keep the map whitey-clean and devoid of unnecessary/rarely needed visual or text information
to only depict the highways on the route and without labels - just to give a visual indication to the monks where they would have the benefit of utilizing a prime path and where they would have to leave it to venture into the interiors. Besides, the data table also captured the name of the primary road which connected one settlement to the next, which the ascetics can refer to
While the navigation instructions are not depicted, the general directionality can still be gauged from the map - whether the next milestone is north or north-west, for example
to highlight the temple locations with an icon and only label them with serial numbers which could be cross-referenced to the data table at the back which would contain the details such as name of the temple, its address, nearest landmark, and phone number if available
I printed the output - one map each for the three route options to Ayodhya and one map for the onward journey to Bhopal - on four sheets of A3 paper. I preferred size A3 to A4 as it preserved and positively impacted the visual aesthetics of both, the map as well as the data table - it would be comfortable to read and refer to, in my opinion...
...and in the monk's opinion as well! He appreciated the effort I had put in for this initiative and took me along to discuss it with the head monk. They decided to use Route 2 via Varanasi to travel to Ayodhya as it had more and reasonably better-known urban and semi-urban settlements besides having better highway and primary roads connectivity compared to Route 1 which was the shortest but not by a large margin (only 16 kilometers). Besides, Varanasi was a major urban centre by itself and also had an important pilgrimage site within which the monks would appreciate visiting.
P.S. the head monk requested that I print just the data table for Route 2 on another A4 sheet of paper so that he could keep it handy with him during the journey!
Overall, I felt good about the output as well as the overall outcome - I hope that the monks stand to benefit from it. The interpretation of a map's design is largely subjective in nature provided the basic objective needs are taken care of. I am grateful to have been exposed to aspects that go into effective map-making by practising tutorials on Esri Learn ArcGIS over time although I am sure professional cartographers and formally-trained GIS professionals would be able to do an even better job. Perhaps, you have some opinions and suggestions for me too😊 - I'd be happy to hear them.
Terrain Change Detection for Physical Security Planning
The video demonstration enclosed below was developed as part of a larger proposal to develop a Geographic Early Warning System for a prospect - the head of Physical Security at a reputed Indian conglomerate - it included other workflows such as Climate EWS and Line of Sight-based-Security Planning as well. The business group in consideration has 100+ manufacturing units and mining locations across India, several very large in size and some located in remote areas. To prevent incidents of theft, and for the safety of the workforce and assets, physical security personnel are deployed in multiple shifts at various locations around the site's perimeter 24x7x365.
Upon discussing this project with another Security Head I had worked with previously, I figured that the terrain around a site's perimeter influences the security deployment considerably. For example, if there are marshy spots around, those zones are less susceptible to incursions compared to an area with dense foliage, which miscreants can easily utilize to their advantage. Thus, planning for and allocating security personnel wisely, by virtue of them being a limited resource, is fundamental.
As a result, I prepared this video to demonstrate how Mapping Technology can be utilized to perform Terrain Change Detection around a sensitive site and provide valuable insights to the Security decision makers-
While I have used a Vegetation Index (NDVI) on Multispectral Satellite Imagery to classify the terrain and to monitor the spots with dense vegetation and their evolution through time, I can just as well use a Water Index to do the same for marshy spots, or even generate an Urban Footprint utilizing Radar Remote Sensing to spot and measure the Built-up areas surrounding the site.
As Satellites typically prioritize temporal resolution (wide swath and short revisit interval) over spatial resolution (pixel size), one is better off using a Drone equipped with a Multispectral payload to map the area surrounding the site perimeter with better clarity and with the freedom to surveil and obtain as much data acquisitions as desired - this would facilitate better Change Detection.
Expanding Market Coverage for Consumer Goods Distribution
An organization's growth potential is usually determined by vertical growth (expansion of offerings) and/or horizontal growth (expansion of markets). I happen to encounter ~20+ news articles every month which revolve around the latter-
The video demonstration enclosed below was developed for a former employer of mine who wanted to see how Mapping technology can help identify locations which have high business potential but are currently untapped by the Field Sales team.
The Location Analytics methodology used in the demo is straightforward and can be beneficial to several organizations, particularly those involved in the distribution of Consumer Goods. I have used Esri ArcGIS Pro, a leading geospatial analytics platform, to-
load the PIN code layer of India and clip it to the city of Mumbai
enrich the PIN codes with population data
load an open source Road Network layer and clip it to the city of Mumbai
filter the layer to keep just the Primary, Secondary, Tertiary and Residential roads
reverse-geocode existing Store coverage - using a hypothetical list scraped from Google Maps
compare the Store coverage with the Population of that PIN code
derive a 10-minute walking-time coverage for each Store, which represents its customer reach
filter those roads that lie outside the walking-time coverage areas - provided the Population of that PIN code is high, catering the Stores that fall on these road sections would help expand the distribution network and stimulate business growth for the organization
Hope you enjoyed reviewing these Operations Mapping workflows. Wish you a happy 2025!
ABOUT US - OPERATIONS MAPPING FOR YOU
Intelloc Mapping Services, Kolkata | Mapmyops.com offers Mapping services that can be integrated with Operations Planning, Design and Audit workflows. These include but are not limited to Drone Services, Subsurface Mapping Services, Location Analytics & App Development, Supply Chain Services, Remote Sensing Services and Wastewater Treatment. The services can be rendered pan-India and will aid your organization to meet its stated objectives pertaining to Operational Excellence, Sustainability and Growth.
Broadly, the firm's area of expertise can be split into two categories - Geographic Mapping and Operations Mapping. The Infographic below highlights our capabilities-
Our Mapping for Operations-themed workflow demonstrations can be accessed from the firm's Website / YouTube Channel and an overview can be obtained from this brochure. Happy to address queries and respond to documented requirements. Custom Demonstration, Training & Trials are facilitated only on a paid-basis. Looking forward to being of service.
Regards,