Set theory, Systems and Jaga Mission

In his classic book 'A System's View of Planning', George Chadwick wrote:

"Not only can the whole of mathematics be developed from the concept of a set, but, as foreshadowed, the idea of a system stems naturally from that of a set." (p-28)

While we all studied set theory in high school mathematics, its usefulness in making sense of the structure and behaviour of complex systems encountered regularly in urban planning, was never discussed adequately in planning school. The consequence is the absence of yet another powerful tool from the contemporary planners' toolkit and the state of confoundedness that naturally follows.

Created by the German mathematician Georg Cantor in 1874, set theory "stems from the simple idea of a number of things which have a common property or properties and thus can be represented as elements of a set." (ibid)

The relationship of set theory with the systems view of planning is made amply clear when we consider that, "the commonly accepted definition of a system is a set of entities and the relationships between them."

Regions and Sets

Let us consider how set theory helps us to tackle the complexity in Jaga Mission, the flagship slum land-titling and upgrading project of the Government of Odisha, India. But before plunging into that, let's have a quick look at how set theory came to be an integral part of regional science already by the 1960s. 

In his classic paper, 'Mathematical Aspects of the Formalization of Regional Geographic Characteristics' , the Soviet geographer B.B. Rodoman wrote that, if a region is viewed as a set of subregions, then one could "convert into the language of geography the theorem of the five alternative relationships which is part of set theory." 

He elaborated further that, according to set theory, two regions A and B may have the following relationships with each other:

1) They may have no common territory

2) They may intersect

3) A may be part of B

4) B may be part of A

5) They may be identical

The relationships can be expressed as follows by using the symbols of set theory:

1) A ∩ B = ∅    [intersection of A and B is a null set]

2) A ∩ B ≠ ∅ ; A ∩ B ≠ A ; A ∩ B ≠ B   [intersection of A and B is not a null set]

3) A ∩ B ≠ ∅ ; A ∩ B = A ; A ∩ B ≠ B ; A ⊂ B   [A is a sub-set of B]

4) A ∩ B ≠ ∅ ; A ∩ B ≠ A ; A ∩ B = B ; B ⊂ A    [B is a sub-set of A]   

5) A ∩ B ≠ ∅ ; A ∩ B = A ; A ∩ B = B ; A = B    [A is equal to B]

By adding to the above the relationships of the sets with their complements (i.e. the elements present in the universal set but not in the set itself - basically the world outside of itself), one can show the full range of ways in which various overlapping or separated regions interact with each other. This was explained very clearly through an example of wheat growing regions, vegetable growing regions and corn growing regions in Golledge and Amadeo's paper titled 'Some introductory notes on regional division and set theory'

It is clear from the diagram above that every part of the three fields, no matter how complex, could be accurately described using the language of sets. For example parts 4 and 6, which occupy the central part of the fields, where all three type of fields intersect can be described using the following notations -

For part 4 --> (W ∩ V) ∪ (W ∩ C)        

[i.e. the union of the intersection of wheat and vegetable and the intersection of wheat and corn]

For part 5 --> (C ∩ W) ∪ (C ∩ V)

[i.e. the union of the intersection of corn and wheat and the intersection of corn and vegetable]

It is easy to spot the origins of the various vector operations in GIS using logical operations such as AND, OR, != (corresponding to intersection, union and not equal to) etc from the above discussion on set theory and regionalization.  

Slums and Sets 

Any slum land titling project is complex by its very nature, but Jaga Mission is quite the Godzilla of complexity due to its size and geographical coverage. Unlike, slum titling and upgrading projects that target a couple of major cities, the Mission covers all 2919 slums in all 115 cities and towns in the state.

However, by combining the necessary geo-spatial datasets corresponding to the various operational parameters of the mission one can readily apply set theory to simplify and automate the tasks. This was particularly true in the case of the trickiest component of any land titling project - the land parcels themselves. 

In fact, one is bound to spot the visual similarity in the following image of a slum of Jaga Mission shown below and the illustrative diagram of the three fields in Golledge and Amadeo's paper.

The above map shows the location of slum houses overlaid on land parcels which belong to three types - Leasable government land (on which slum land rights can be granted); Reserved government land (on which slum land rights can be granted only after a category conversion process); and Private land (on which slum land rights cannot be granted).

If A is the set of slum houses and B is the set of government leasable land parcels then the slum houses entitled to land titles straight away would be given by - 

A ∩ B    

However, if one would consider the total set of slum houses which are entitled to land titles once the land category conversion for reserved government land parcels are completed (reserved parcels given by set C), then that would be given by -

A ∩ (B ∪ C)

If private land parcels are the only category over which land titles cannot be granted (set D) then the set of entitled slum houses could also be given by -

A ∩ D'    [where D' is the complement of set D]

By defining the sets according to the specific parameters of the mission, the outcome of the interaction of various parameters could be computed by applying the theorem of alternate relationships.

Once such relationships are established then it really does not matter if the process needs to be done for one slum or for a 100 slum or for a 1000 slums. Nor is it any difficulty to divide a particular set into its constituent sub-sets (for example the reserved government land category itself is a union of numerous subsets of land parcel types distinguished by the land-use type and the ownership type -- these particulars can also be described as sets of their own).

Open Data...or Open Disdain ? Cognitive dissonance and Urban India's Open (GIGO) Portals

Have you even visited your own "Open Data" portals ?

In Satyajit Ray's classic film "Jana Aranya", the character played by Utpal Dutt asks a banana seller if he had ever himself tasted the bananas that he sells. 

Better hear the voice of the great Utpal Dutt yourself, and keep the tone in your mind -

We can then ask the officials and consultants of India's various urban missions in the same tone, if they have ever visited their own "open data" portals. 

A few months ago, at a conference on the smart cities mission, a senior official of the mission said that he was very glad that so much data was now available freely to the public through open data platforms such as the Open Government Data (OGD) platform , the Indian Urban Data Exchange (IUDX) platform etc. 

One wonders how he could say something like that at a public forum and how none of the die-hard supporters and critics of the mission in the audience had no questions regarding such a statement.

Open data and my neighbour's laundry list

I have made multiple visits to both the above platforms and downloaded various data files. Never have I ever found anything with any more usefulness or relevance to my work than ... let's say....my neighbour's laundry list. It seems as if the professionals tasked with uploading data to these portals found every scrap of excel spreadsheet lying around in their respective offices and dumped them in these digital bins. May be they are rewarded for the sheer number of files that they upload rather than what those files contain.

It is also amusing to discover that individuals who talk passionately about these platforms have never visited them or have downloaded any data from them. A large part of the problem is also the unfamiliarity with the basic standards of data storing and a lack of clarity regarding the tasks that the data should be used for.

The fact that this useless data is available in a range of file types such as csv, json, ods etc further compounds the irony of the situation.

And of course, let's not forget that entering the website and accessing the data are not always the same thing. 

Often you will encounter this at some point -

Or this -

Strangely, when I had checked the portal sometime back, many of the "private" buttons were "open" and coloured a welcoming green. Of course in the name of smart traffic signal data they often contained something as amazing as column containing names of certain squares (all the rest is left to the Sherlock Holmsian powers of imagination and deduction on the part of the website visitor).

Consider the following csv (comma separated value) file available on the OGD portal -

This is all the information that this downloaded csv file contains. The file contains no metadata (which means there is no data on the data itself) such as - when was it uploaded, who uploaded it, which period is represented in the data, what do the fields mean (does "Nos. of IHHL" mean number of individual household toilets under construction or already constructed or targeted ?), does the data correspond to the Swachh Bharat Mission (SBM) or some other project...and, how on earth does a person not dealing daily with Indian development lingo know what "IHHL" stands for in the first place ??...etc. etc. etc.

The incompleteness of the data further renders it useless. Even if we were to assume that the data shows how many toilets have been constructed, what is the use of that if not compared against the total toilets that were supposed to be constructed ? Even if that data were available in another file on the portal, they would not be comparable due to the lack of metadata.

The hard fact regarding any data management process is that any data that does not contain meta-data is garbage data. And considering the inevitable thing that happens when garbage data is fed into any analytical or decision-making system (Garbage In - Garbage Out....aka GIGO)....none of this data should be used by anyone actually trying to do something useful.

Genuine open data portals

It is normal for the "defenders" of these portals to wax apologetic when confronted with these issues with predictable statements such as - "Yes...but it also contains things which are useful...with time it will improve...it takes time to build something like this" etc etc. 

There is no need for all that. Just a quick visit to any of the following would give one a clear idea on what serious open data portals should be like.

Bhuvan portal of the Indian Space Research Organisation (ISRO)+National Remote Sensing Centre (NRSC)

Automatic Weather Station portal of the Indian Meteorological Department. 

USGS EarthExplorer of the United States Geological Survey.

AND not to forget the wonderful....

Census of India.

At the end it all boils down to this - if you have something serious to do and you know what you are talking about, your data won't have to be a pile of BS...open or not.

Disaggregation Dilemma - Part 2...(from static land-use color codes to something like OSM features indexing)

Information density at lowest levels of disagregation

Let us continue the discussion on information loss and data aggregation by comparing the maps of different planning levels that I showed in the first part of the blog, with their corresponding scales on OpenStreetMap and google satellite imagery. 

Instead of starting from the top (the city level), let's start from the bottom (the layout level) this time, and remember the words of Prastacos again- 

that computerisation basically allows us to maintain data at the lowest level of disaggregation and then readily aggregate it as the need arises.

There is of course no restriction on further zooming into the osm (OpenStreetMap) or the satellite imagery to study the area on greater detail. Similary, one can zoom out and reduce the scale to any extent to study larger areas. One does not have to stay restricted to certain categories of pre-defined map-scales (and needless to say, we also get our freedom from the scanned copies of water-soaked blue-prints that the government generously shares as "open data" and get a feel of the power of the REAL open data).

 

What is information loss due to aggregation ?

If we zoom into the area of the layout plan in the City level land use plan, then this is all the detail that we could possibly get -

 

Now compare the above level of detail (left) with what we saw in the case of the osm image (right) -

 

The above comparison is a simple visual representation of the amount of information loss that happens when spatial data is aggregated to higher levels using non-computerised cartographic methods.

There was simply no other way - in the absence of computers - than to prepare maps of different scales; covering different geographical extents in order to show different planning levels.

However, none of those limitations remain if one is working with digital spatial data and computers - there is no information loss at higher levels of aggregation of the same map. 

The trouble is that we continue to operate with the same methodology even when we have computers and geo-spatial software at out disposal.

Coding spatial information - learning from OSM features

When one understands the fundamental manner in the way in which computerisation allows aggregation and disaggregation of data, then one can also understand that the manner in which land and building uses were coded in earlier non-computerised map-making systems are no longer adequate or relevant.

Incidentally, a very powerful and effective alternative to older methods of land-use coding has already started appearing in the form of the "Map Features" of OpenStreetMap. 

Here is a description of the system from osm's wiki page -

OpenStreetMap represents physical features on the ground (e.g., roads or buildings) using tags attached to its basic data structures (its nodes, ways, and relations). Each tag describes a geographic attribute of the feature being shown by that specific node, way or relation.

Most features can be described using only a small number of tags, such as a path with a classification tag such as highway=footway, and perhaps also a name using name=*. But, since this is a worldwide, inclusive map, there can be many different feature types in OpenStreetMap, almost all of them described by tags.

The osm feature indexing system is extremely thorough and exhaustive and designed for use by the computer. Have a look at the difference between a typical color coded land use system and the osm map features system below.

This is how land uses are color coded in a typical land-use plan -

And this is how the osm map features indexing system looks like -

Just a casual glance is enough to see the power of this feature indexing system. It lists the various types of uses as key-value pairs, states what osm map elements they belong to, provide a clear description of each feature, the rendering and also photographs of typical examples.

The wealth of information that gets collected and maintained using such an indexing system is truly mind-boggling.

The analytical opportunities such systems open up can help us go toe-toe with the most complex urban problems that we face - and win.

 

Disaggregation dilemma - Part 1...(Of GIS based PDFs and Water Soaked Blue-prints)

What is wrong with our land-use plans ?

Well...nothing. Except, perhaps, the fact that they belong to an earlier epoch of technological development - a period when one necessarily had to prepare maps at different spatial scales in order to show greater or lesser detail; and use specific colours to aggregate the primary land uses at different scales - for example, yellow for residential use; red for commercial use (depending on prevalent cartographic rules).

One can also say that the technology of land-use maps, as they continue to be used to urban planning in India, corresponds to the period of map making prior to the advent of computerised cartography and geo-spatial analysis.

Using present technology, we do not need to switch between different maps prepared at different scales to study different degrees of spatial detail. Instead, we can simply zoom in and out within the same map. 

In most aspects of our lives we take this for granted - when we are booking an uber; or checking directions to a destination on google maps; or checking how far the swiggy delivery partner is at a particular point of time. 

In all such businesses, computerised geo-spatial analysis and decision-making is not just one of the components to be considered -  it is the most fundamental science and technology on which the business operations play out.

However, in a vital and complex activity such as urban planning, whose social and economic significance far exceeds that of profit maximisation in the gig economy, such technology is still a sort of a novelty which is far from having been internalised by the rank and file of the profession.  

In fact, the inadequacy of technical knowledge becomes amply clear precisely when one takes a look at the manner in which the planning profession attempts to internalise geo-spatial technologies. I discussed this in an earlier blog.

It is perhaps too difficult for our planning professionals and educators - too busy flaunting tech-terms and buzzwords - to come to terms with the simple fact that if your planning maps are made using GIS software then you do not need separate sets of maps at the levels of the city - i.e. the city level, the zone level and the layout level -- they are all part of the same geo-spatial database ! 

I am not even getting into the travesty of making such "GIS" maps available online in PDF format and then providing the attribute data in separate spreadsheet files and THEN announcing this pointless hotch-potch as Open-data ! A tighter slap on the face of the open-data movement was never landed. This is not open-data...this is an open disdain of the citizen.

 

From GIS based PDFs to Water soaked Blueprints

Let's have a look at such maps as they are available from the website of the Delhi Development Authority -

a) Here is the "big honcho" - the proposed land-use map of all Delhi. The highest level of the plan and the one with the smallest geographical scale and level of detail. Most of the time lay-persons attempting an analysis of the Delhi Master Plan remain pre-occupied with this level. Of course, it shows nothing more than the most general and most aggregated land-use distribution at the level of the city.

b) The next level of planning detail comes in the form of Zone level land-use maps. Shown below is the map of Zone-F in South Delhi. As per the zonal plan report, already in 2001, this zone had an area of 11958 hectares (i.e. 119.5 square kilometres) and a population of 12,78,000. That basically means that while it is just a part of the city of Delhi, it is still larger than many smaller sized cities of India (it is, in fact, larger than the smart city of Bhubaneswar in terms of population). 

The Zone too, therefore, is at a substantially high level of aggregation and can be compared to city level land use plans of one-million plus cities in India.

(NOTE - pay attention to the key-map in the attachment below and marvel at the cartographic genius of whoever prepared this "GIS based" pdf output)

c) And something peculiar happens when we go down to the level of the layout that contains the maximum geographical detail - the layout plans; which are more like a plan for a cluster of neighbourhood blocks. 

Here is what the plan of one of the layouts constituting Zone-F looks like...if you can make anything out that is. The keen observer would realise that this is actually a well drafted layout map (at least the key map is correct !), but we have suddenly descended from the world of GIS based PDF map outputs, to the world of water-soaked and worn-out archives of crumpled gateway sheets and blueprints. 

This is what gets uploaded as digital layout maps on the website of the premier urban planning agency of the capital of the country. 

There is therefore a complete dissonance between what digital and geo-spatial technologies truly are and how they are being utilised. 

In this matter the critics and activists of the civil-society and consultants of the private sector are often more technically incompetent than government planners. The government officials may not be familiar with the modern software but they know their cartography well enough (as illustrated by the water-soaked map), while civil society critics and private sector consultants (who often actually prepare the "GIS" outputs) are often poor in both technology and cartography.

 

In the next part we will see how computerised geo-spatial methods eliminate the problems of aggregation by allowing data to be maintained at as disaggregated a level as allowed by its granularity and aggregating the base-data as per requirement to whatever level necessary processing power of the computer.

In the words of planning expert and theorist Poulicos Prastacos -

"Data should be maintained at the lowest level of disaggregation and then readily aggregated as the need arises."

(Source - 'Integrating GIS technology in urban transportation planning and modeling' - P. Prastacos)

To be continued...

The Data exists...right under our Mouses !

The capital irony

It is perhaps a capital irony of our times that precisely at the time when computers are more powerful and affordable than ever before and the access to powerful and previously expensive software provided by the  Linux + FOSS (Free and Open Source Software) movement, the general ability to use computers effectively to address the various problems faced by our cities is at an all time low.

I myself come from a background of primarily qualitative and participatory techniques in urban planning. I continue to have a natural fondness for such techniques, but have increasingly also discovered the power that effective use of computers bring to my work.

Contrary to the myth that the quantitative and qualitative worlds are poles apart (which leads to the further myth that professionals dealing with qualitative techniques cannot use computers for serious quantitative analysis), the two are in fact friends and allies of each other and help each other continuously.

Without waxing complex, think of a rather simple example. I would like to undertake participatory exercises in various slums in my city and I use all kinds of creative ideas to undertake the same inside those communities.

But alongside that, I could also prepare a GIS database of the slums in the city that gives me spatial and quantitative information on slums - such as their location, distance from each other, distance from other city facilities, size and density of the settlements, the population and occupational characteristics of the settlements etc.

This quantitative database can actually help me increase the effectiveness of my qualitative techniques by helping me to schedule meetings, use different techniques in slums of different sizes and shapes, check the probability of consensus-building (fewer meetings could build consensus faster in a smaller slum than in a larger and denser slum) etc.

Rather than focusing too much on whether to deploy quantitative or qualitative methods, it is better to focus on the problem that needs to be solved and deploy whatever methods that may be necessary.

Why computers ?

As long as I want to do participatory activities in a handful of slums, I may not need any support of computers at all. However, if I would like to undertake such activities in tens or hundreds or thousands of slums, then I begin to feel the need of the processing power of the computer.

It is as simple as that.

As more and more resources are made available to various urban development programs and schemes in India, their sizes, duration and scale of operation are all increasing. It is not difficult to understand that in a country the size of India, urban development projects would need to be undertaken at a scale where one can at least hope to make a meaningful difference. 

But of course, computers need instructions to follow - and they need data to work on.

The data exists...right under our mouses

Quite often, the impossibility of obtaining data is cited as one of the main barriers to effective use of computers in solving urban problems in India. I have written on this topic on multiple occasions. And I have stressed on earlier blogs that mere accumulation of digital data is not of much use if one does know how to use computers effectively to process it.

However, another capital irony of our times is that much of the data whose absence we so lament - does indeed exist...and sometimes right under our noses (or mouses).

Let me demonstrate.

This particular link will take you to the dashboard of the "GIS based Master Plan" sub-scheme of AMRUT. 

The very first component of this sub-scheme was geo-database creation and in the following screen-shot of the dashboard we can see its status -

 

If we look at the first three steps of the component, we can see that satellite data had been acquired and processed for about 450 cities. In the pie chart on administrative works is not self-explanatory, but it could mean that the National Remote Sensing Centre (NRSC) of the Indian Space Research Organisation (ISRO) may have handled the satellite data acquisition and processing for 240 cities and private companies may have done it for another 220 cities.

In any case, according to the official dashboard itself, we can conclude that processed satellite data exist for about 450 cities. As per the status chart, final GIS maps also seem to exist for 351 cities.

From if it exists...to where it exists

Finding evidence and clear arguments for the claim that something exists, is the first step in finding something. If I know for sure that something exists, then I need not succumb to the fallacy that it doesn't even exist. 

The task after that is to discover, where it exists, rather than wonder if it exists.

The same method can be applied to understand exactly what all data has been collected and processed under the myriad central and state government schemes that are going on in the country and have already been executed in the past.

Believe me, we will have more data than we would need for getting most of our tasks done.

The catch here is this...a person who does not have the imagination to discover the data, most likely would not have the imagination to use that data either.

But let's keep that blast for a later post ;)

Indian Space Assets and Urban Planning

Smart in Space...Clueless on Land

As India's capabilities in the field of space technologies increase continuously, the gap between the data generated by our space based assets and the utilisation of the same for solving pressing social and economic problems is felt palpably...and painfully.

After all, the vision of our space program has always been to -

"Harness, sustain and augment space technology for national development, while pursuing space science research and planetary exploration."

And this is the level that we have already reached in this domain -

 

When it comes to space, we are not just good - we are among the best in the world and sometimes better.

The Indian satellite cartosat-3, launched in November 2019, is one of the most advanced high-resolution earth observation satellites in the world. 

With a resolution of 25 cm, Cartosat-3 surpasses the American World View-3 satellite owned by Maxar Technologies, which has a resolution of 31 cm.

And guess what is written in the Mission document of Cartosat-3 as the primary application of this third generation satellite -

You can access the document on this link.

One would expect that such high resolution products would be developed for the defense sector alone, but we have reached a level of technological development, where the mission document lists purely civilian sectors as the target users of Cartosat-3.

I seriously wonder whether the scores of professionals of India's urban development sector are aware that one of the most advanced products of one of the most advanced fields of human technology has been produced by their country for them.

Is it really so hard to imagine, what all becomes possible when you have high resolution satellite data available for the whole city and the region ?

From data collection to serious data analysis

With the development of advanced earth observation satellites we can finally take a pause from the gigantic spatial survey exercises that take up all the energy and creativity that could and should be dedicated to data analysis, forecasting, modelling etc. In any case, the fragmented and project specific data generated by these large urban development projects is used poorly and then abandoned and forgotten the moment the projects come to an end (refer to previous blogs for more details).

Consider the fact that Jaga Mission - which created one of the largest high-resolution geo-spatial database of urban slums in the world, had to deploy three separate drone survey companies, multiple quadcopter drones, teams of surveyors and the resources of over a hundred city governments to complete that survey in less than a year.

Given the logistics of covering almost 2000 slums in 109 small and medium cities spread across the length and breadth of the state of Odisha, which has an area of 155,000 square kilometres, it was a daunting task. Typically, in large urban development projects in India (and they are all large nowadays), so much energy and resources are devoted to conduct the surveys and create the datasets that serious analysis never gets a chance to take off. 

Such a daunting logistics would also imply, that while the urban reality is extremely dynamic, the probability of repeating such a spatial survey exercise at regular intervals would be very low.

From the point of view of temporal change, the ultra-high resolution data collected under Jaga Mission in 2018 may already be out of date. And there exist no plans of updating that data set.

Satellite data has no such problem with temporal resolution (the interval of time after which the same area of the surface of the earth would be captured again by the satellite in orbit).

With Cartosat-3 data, one can not only get a detailed picture of slum settlements (not just in Odisha, but through the country), but one can also analyse the spatial changes over time and also relate the location of slums to other features in the city (none of these are possible with Jaga Mission drone data, which only captured images of individual slum settlements.

Data without scientific knowledge is useless

There is a never-ending clamour for data among urban development professionals and researchers in India...a tendency I described as "data hunting-gathering" in a previous blog. However, it was not access to unlimited amounts of data that made the Indian space program what it is today - but scientific knowledge and the intelligent application of that knowledge.

Data is crucial - but only when one possesses the necessary scientific knowledge to effectively use that data. 

The trouble is that many (definitely not all) professionals demanding access to all kinds of digital data - i) would not be able to recognise that data if it were staring at them from their computer screens; ii) would not know what to do with the data even if by some miracle they figured out that it was indeed the data that they were looking for.

The usual excuse given by scholars and practitioners alike is that urban challenges are too complex. Of course, they are complex - but complexity of a problem is as much a function of the knowledge of the problem-solver as it is an intrinsic characteristic of the problem itself.

Finding an address too can be a very complex task - if someone doesn't know how to read a map. 

It is always nice to check whether a problem is really complex or if I am too dumb ! It may be very nice to discover that it is the latter, because then I know that the problem is solvable and I also get an opportunity to study and learn something new and useful.

Unless that knowledge gap is bridged, the brilliant developments in the field of Indian space technologies shall be unable to solve the relatively mundane challenges of urban planning and development.

And that would be a real shame.

You cannot "find" data, if you cannot recognise it

I have written in earlier blogs about the trouble with GIGO (Garbage-In-Garbage-Out), which basically means that if the data that goes into your software is garbage, then your output would be garbage too. However, sometimes the problem may be what Andrei Martyanov describes as "double-GIGO" (I can't remember which video it was in but feel free to check out this one anyway), where both the data used and the formulation of the problem may be garbage. Needless to say, that it is one hell of a tragedy when that happens. Unfortunately, it is not a rare phenomenon at all.

However, quit often, the problem is simply not knowing what data to look for and where to look. For example, last year the CITIIS program of the National Institute of Urban Affairs (NIUA) organised a training workshop for the Department of Housing and Urban Development in Odisha for mapping of water bodies in urban areas of the state. The program started with the mapping of 19 water bodies in the pilot phase.

Having engaged with the implementation of such programs from the inside, I know for a fact that "there is many a slip betwixt the cup and the lip", when it comes to their objectives and the data that they use for achieving it. I have written extensively on the state of data in government projects in multiple blogs.

Even without going into any detail of this specific program, isn't it a bit peculiar to do such a gala workshop on such a theme, when the following already exists ?? 

This is the dashboard of the Water Bodies Information System (WBIS) of the Indian Space Research Organisation (ISRO). Here is the link to it. 

The site clearly mentions -

"The water spread area information is extracted using images of 6 m to 56 m resolution for delineating water bodies of sizes as small as 0.025 ha and 50 ha respectively. This information is made available as Water Bodies Information System (WBIS) for visualisation and download."

One would expect that the organisers of the workshop to be atleast aware of the existence of such an information system prepared by such a respectable organisation - Alas, nothing of the sort !

When the knowledge and technical abilities of urban development professionals increasingly gets limited to preparing powerpoint presentations, having endless online meetings and organising various kinds of "capacity-building" events, then the probability of being able to identify relevant data (even when it stares at you point blank) is bound to decrease...and at a steep slope.

One can safely argue that it is hovering somewhere very close to zero if not already there

The ability to find data is very much a function of being able to recognise relevant data and that in turn is dependant of ones knowledge of the subject, which needs constant updating.

But is there any time left for that after the relentless "labour" of back-to-back online meetings ? 

Planning and the Complexity Conundrum

Implementing at the cost of Planning

A characteristic feature of large urban development schemes in India is that they are heavily implementation oriented. In a way, they seem to have overcome the "the-plan-was-good-but-the-implementation-was-bad" impasse in Indian urban planning.

To be sure, this lacuna of planning has been overcomeby abandoning planning itself and opting for large, sectoral schemes implemented by specific line departments of the government.  For what else are these large urban development schemes in India if not projects of specific infrastructure verticals undertaken in mega-scale?

It is not difficult to resolve the difficulties of planning, if urban planning itself -- the science and art of forecasting future development scenarios in a city or region and preparing for it by integrating the activities of multiple components of the urban system i.e. land, housing, economy, infrastructure -- is abandoned.

Urban systems are complex by their very nature. The discipline of urban planning, therefore, by its very nature, is tasked with anticipating the behaviour of this highly complex and dynamic system in a scientific manner and preparing for it. 

Planning and Complexity

Rather than talking in vague and general terms (as is increasingly common these days), it is perhaps better to use the concept of "variety", which is used in the field of cybernetics as a measure of complexity.

W. Ross Ashby, one of the pioneers in the field of cybernetics, described "variety" as the number of possible states that a system can take. As systems become larger in size, the amount of "variety", and therefore complexity, increases exponentially.

Looking at urban systems, examples of this could be found everywhere. For a very small town a single, small commercial area with a small cluster of shops of various kinds may suffice. But a larger city would inevitable give rise to a whole range of commercial areas of various sizes and types, having different areas of coverage and located in various parts of the city.

I sometimes gave the example of a footpath to my planning students, which, in a sweet little Scandinavian town would be just a footpath, but in a city of even moderate size in India could turn into a space for shopping, hawking, begging, sleeping, living, storing, parking...and, if possible, a space for pedestrians for walking. 

In the former case the footpath would have a variety of 1 and in the latter a variety of n...and counting !

In his book "Designing Freedom", Stafford Beer showed the calculation to estimate variety -

If there are n people in a system, and each of them has variety x (each can adopt x number of possible states), then the variety of the total system thus defined will be xⁿ.

So if there are only 40 people (n=40), each of whom has only two possible states (x=2), there are still 2⁴⁰ possible states of the system.

2⁴⁰ =  1,099,511,627,776

      ('Designing Freedom', Stafford Beer, p - 11)                 

 

This is complexity quantified.

Better to not even attempt to calculate the total possible states that our second footpath can take ! 

Now that we have developed a healthy respect for the mind-numbing salvo of variety (therefore complexity) that urban systems can hurl at the planning profession, it is perhaps possible to at least understand (if not entirely forgive) why the profession often fails to successfully execute the task that it has taken on.

The planning paradox and the world of probabilities

Any serious discussion on a topic as complex as the planning of urban systems in the 21st century, has to begin by acknowledging that it is a near impossible task. And yet, it has to be done.

Therefore, the discipline has to be approached like any complex system has to be approached - not with the demands of certainty...but with the estimation of probability.

As the geopolitical expert Andrei Martyanov said in a recent talk -

"The world of prognostication and serious analysis is the world of probabilities."

In the context of planning, this was discussed wonderfully by Poulicos Prastacos in one of his papers on the Projective Optimization Land Use Information System (POLIS) land-use transportation model. He wrote that one of the problems of the first generation of land use-transportation models, developed by planners in the US during 1960-75, was that their goals were too ambitious. 

Prastacos wrote the following lines way back in 1985, which I find extremely relevant given the planning challenges we face today -

"Critics of urban modelling were correct in pin-pointing the limitations of the early models, but failed to notice that most of these arose from either the overambitious expectations about the role of models in planning or the general lack of knowledge about the state of the art and the capability to implement successfully complex mathematical equations. They did not provide an alternative methodology that could address some of the more modest goals and potential applications of large-scale models (consistent set of forecasts, evaluation of alternative transportation improvements)."

Instead of an abandonment of the models, the empirical criticism should have instead allowed for the calibration of the goals and ambitions - applying them to more modest problems and building them up based on the results.  

If 'certainty' is impossible, then it is pointless to keep it as the only measure of success. There is no methodology that exists which can forecast the future population of a city with certainty. However, there are many splendid methods by which the future population can be estimated, depending on the assumptions used. 

Abandoning probability based scientific methods (just because they "fail" to offer the certainty demanded by decision-makers) relegates planning to a position where its only hopes are various kinds of purely qualitative discursive practices; the tribal knowledge of long established planning offices and the individual genius of this or that planning officer, engineer or administrator etc.

That's no way to handle a system, let alone a complex and dynamic one such as the urban system. 

This dooms the profession to be eternally engaged with last minute fire-fighting with ad hocism as its primary tool.

Compared to this visible form of acting and responding to various urban challenges, the voluminous master plans (where they exist) with all their guidelines, development controls,  land-use plans seem unrealistic and farcical like the detailed diet-chart of a person who is gobbling junk food everyday because he never gets enough time to cook and eat healthy food.

This is also what strengthen the arguments in favour of ditching planning altogether, or effectively bypassing it by directly implementing the separate infrastructure components without requiring an overall plan to guide the process. 

Thus a mission like the Atal Mission for Rejuvenation and Transformation  (AMRUT) would cover a range of infrastructure veticals such as water supply, sewerage and septage management, storm water drainage to reduce flooding, green spaces and parks and non-motorised transport. Similarly, Swachh Bharat Mission would focus on construction of toilets, solid waste management etc. 

As the implementation of these verticals can be measured in the form of easily quantifiable metrics - number of toilets constructed; kilometers of drains laid; number of parks made etc - they, naturally, become favourites of politicians and bureaucrats alike.

But this can lead to serious problems.

Duplication dilemma

A distinct benefit of planning, even when it totally fails to predict or influence the course of urban development, is its ability to get some sense - however limited - of how the different components of the urban system interact with each other. Being obliged to operate over a specific geographical territory it can at least figure out how the various sectoral components are located with respect to each other. Operating purely within the sectoral domains eliminates this advantage. In fact, this is not very different from the arguments offered in favour of economic planning - the ability to monitor the activities of individual firms and attempt to coordinate them for the fulfillment of overall plan targets - as opposed to a purely market driven approach where each firm strives to maximise its profits irrespective of the consequences that may have for the overall economy and the environment.  

The eagerness to maximise the implementation of individual sectoral schemes leads to a tendency to overlook how different sectors interact with each other in an urban system.

Just take a look at the image below. It shows the location of a slum in the northern part of the city of Bhubaneswar. Right next to it, one can see the affordable housing units being constructed to house the residents of the slum shown in the image and also the residents of other neighbouring slums. 

The affordable housing units were being constructed under a public private partnership model and overseen by the Bhubaneswar Development Authority and the Bhubaneswar Municipal Corporation (a process which had been in the works almost since 2017). In the meantime, Jaga Mission - the flagship slum land-titling and upgrading programme of the Government of Odisha - was launched and was overseen by the Department of Housing and Urban Development.

Jaga Mission selected the same slum in its pilot phase of slum upgrading in 2020-2021 and did a very fine job of upgrading it in consultation with the residents of the slum.

However, a successful of upgrading of this slum means that there really is no need for these families to move into the nearby affordable housing site. Not only would the families have no need of moving there, the units of the housing site may now need to be filled by families of slums which are located further away - hence increasing the probability of reluctance of the residents of even those slums to move in here. 

Each scheme aimed at maximising their individual benefits, without considering that they may just end up duplicating the benefits churned out by another scheme.

A more planned and coordinated approach would probably have been to choose other slums for the pilot upgrading phase and let the present slum be catered to by the affordable units - since they were already under construction. 

This is just one example. In a situation where such lack of coordination and a continuous maximisation of implementation of individual sector verticals is the norm, such examples are innumerable and constantly proliferating. 

Yet, there are ways to turn this situation around by making intelligent use of the tools and techniques that are available to us - that we either tend to forget or abandon.

As Prastacos pointed out - we don't need to throw away our tools...we may only need to make the goals more modest and realistic.

More on that in future blogs...

 

 

Regarding farcical flirting...and GIS based master plans

Earlier today, I wrote the following on my linkedin status -

GIS based Master Plans...it's a bit like saying pen based novels...or camera based photographs.
India's farcical flirting with technical terms has to stop.
It shows an unreflected acceptance of meaningless sentences - in other words, it helps accelerate collective stupidity.

I felt that this should be elaborated upon. 

To be sure, I am not against flirting - it is a creative art. Anyone who wishes to study it seriously could turn to Act 5, Scene 2 of William Shakespeare's play "Henry V". 

Here is a youtube link to the scene in the classic film adaptation by Sir Lawrence Oliver -

 

Of course, one is free to point out that strictly speaking Henry was wooing Lady Katherine and not flirting with her. 

But then I am equally free to reply, that while Henry was indeed wooing Katherine...he was also flirting - not with her - but with the just altered geo-political situation in Europe following the battle of Agincourt where Henry achieved decisive victory over the French and was in a position to dictate terms to her. 

Yes, flirting is art indeed - of geo-political scale and significance.

So much for my admiration for genuine (geo-political or not) flirting. 

But the recent tendency (increasing at an exponential rate) in India to flirt with "tech" terminology (including the ridiculous sounding word "tech") without any regard for what they really mean, can be considered farcical indeed.

Sentences beginning with the following should immediately put one's BS-filtering systems on high alert -

• "We are developing digital tools for..."
• "According to our AI based tools..."
• "As per our machine learning algorithms..."
• "We use high-resolution satellite imagery for..."
• "We have adopted a data-driven approach for...."

The trouble is not with terms like digital, AI, machine learning, high-resolution satellite imagery etc., but with the things that generally appear in the second part of the sentence.

Consider the following statement - "We use high-resolution satellite imagery to track land-use violations in Bhubaneswar smart-city on a monthly basis."

If this video clip (with an animation showing a satellite "diving" from its orbit every time it tries to get a better look at Bhubaneswar and other such wonderful things) is not enough to turn you numb, consider the following questions -

• How exactly does a high-resolution satellite imagery help me understand what use the buildings it shows are put to - commercial, residential etc. ?
• How does it help me understand violations in bye-laws such as height restrictions ?
• How exactly does it help me understand the prescribed use of the land on which the building is situated ?

 

 AND...

• What about the fact that last I checked the master plan of Bhubaneswar was under revision the new one is not even out in the public yet ??

High-resolution satellite imagery is indeed extremely useful for city planning purposes, but let's just say -

there is many a slip 'twixt the cup and the lip.

 

In other words, there is a whole range of activities that have to be done, and done properly, before high-resolution satellite imagery can perform the task of tracking and preventing land-use violations.

By beginning the sentence with the 'cup' and ending it conveniently with the 'lip', without ever clearly mentioning what all lies in between betrays either complete ignorance of the processes involved or a sly ploy to shock-n-awe anyone not familiar with such technology for the sake of furthering ones agenda.

As regarding all that lies in between the cup (the technology) and the lip (its successful application), we can turn to Shakespeare again and say,

"Ay, there is the rub !"

It is precisely in all the activities that need to be done to make a technology effective, that the real professional grind lies - and that which most would like to steer clear of.

It is easy to write a software...but notoriously hard to organise and clean the data that would be used by the software; and fix the organisations that would use the software.

 

And now let's turn to the star of the show...one that really cracks me up every time I hear it - 

GIS based Master Planning.

I wonder who came up with that one, and most importantly - why ?

Do we ever say ludicrous things such as a pen-based novel; or a camera-based photograph; or a type-writer based article  etc ?

What exactly is the point of defining a planning process using one of the many tools, which may be deployed to aid its preparation, apart from either or both of the following -

    a) Zero understanding of planning.

    b) Zero understanding of the role of GIS in planning.

Well, there is a set of more realistic causes which are far more sinister than the above two - but let's go with these for the moment.

Applying the GIGO (garbage-in-garbage-out) model - which suggests that if the input (data) is garbage, then the output (solution) would be garbage too - to our present topic, we can argue that if the input (the planning approach) is meaningless, then the output (plans produced), would be meaningless too.

Thankfully, we have an elaborate dash-board available in the public domain to support our argument. 

As expected, the dash-board is a cool and elaborate one containing all kinds of information, except the most important one - the plans themselves. 

The first alarm bell rings when we scroll to the middle of the page and look at the master plan formulation status. We learn, that after 8 years of implementation, only 135 out of the total 500 cities covered by the scheme have reached the final step of "Final Master Plan". A total of 257 have reached the level of "Draft Master Plan".

But where are these amazing 135 GIS based Master Plans ?

For that one has to scroll right to the bottom of the page and click on the relevant states (or cities) on a map to access the plans. One has to repeat a few more rounds of needless clicking until one finally reaches the page from which two separate files can be downloaded - Master Plan Report and Land Use Map.

As Gujarat was proudly colored green (all tasks completed for all cities), I decided to click on a random city called Botad.

I didn't expect to hit jackpot on the first city I clicked on, but this is the Master Plan Report that popped up -

 

 You can download the report directly from this link.

It was a pdf copy of a 30 page long report in Gujarati language. And here is a screenshot and direct link to the land use map that accompanied it -

The map too is in pdf format; a jumble of different layers overlaid on top of each other; with no clear distinction between existing and proposed land-use. 

The map is a cartographic nightmare but that's the least of our worries.

Forget about using available technology to develop a planning approach based on decades of theoretical and practical advances and reflections in the field of planning, we are offered a national level scheme which purports to use GIS but provides us with pdf files that tell us nothing and which we can use for nothing.

The reports and plans of different cities seem to be prepared by different private consultants, each following their own cartographic rules; structure of report; and occupying their own unique positions on the scale of being slapdash.

The only thing that we can be certain of regarding the meaning of the term "GIS based Master Planning" is that all consultants have made some use of GIS software in preparing the maps.

Pardon my French, but what the F*** is the use of that ?

And yet, why is it that we don't burst out laughing and brush aside the moment we are presented with these ludicrous "tech"-loaded planning terms, be it GIS based planning or the galaxy of terms following that other ubiquitous and incomprehensible adjective - Smart ?

What makes us take such tragic farces seriously....discuss them, develop projects around them, organise conferences and webinars on them ?

May be because we are distracted from the real tasks that face us...and alienated from the scienctific knowledge that we need to tackle the urban challenges facing us.

This nonsense seems to be everywhere...and relentless.

But it seems to contain the petrified brittleness of all things insecure...one tiny push and it may crumble to dust.

Then why not give it a resounding whack ?