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).

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...

 

 

Solving the "land" variable in land-titling equations (and some more on tackling complex urban problems)

My previous blogs have stressed the importance of operational parameters of large and complex urban development projects and how their implementation can become very difficult - if not impossible - without a creative combination of modern computing and community feedback. Perhaps nowhere does this reality hit home harder than in the implementation of mega-sized slum land-titling and upgrading initiatives such as Jaga Mission.

The Odisha Land Rights to Slum Dwellers Act, 2017, which guides the implementation of Jaga Mission, states in section 3, sub-section 1, that 'every landless person occupying land in a slum in any urban area by such date as may be notified by the State Government, shall be entitled for settlement of land and certificate of land right shall be issued in accordance with the provisions of the Act.'

All very well-intentioned and clear so far, but a whole operational quagmire opens up when one begins to implement the provisions of the Act. The art of land administration in India as it exists today, is an elaborate one that pre-dates the Mughal era. Words like 'kissam' (a derivative of the Farsi 'Qism', referring to land-use type) co-exist with the English 'Record of Right' in land revenue records, reflecting the deep and layered history of the subject. The typical planning student of professional is often not even familiar with these terms used by the revenue department, let alone being able to intervene in the operational matters of land administration.

The slums in any city may be located on hundreds of separate parcels of land, which may belong to diverse 'kissam' types, which, further, could be a mix of non-reserved (on which land rights can be given) and reserved (on which land rights cannot be given without initiating a process of re-classification of land in consultation with the revenue department) categories. Furthermore, parcels belonging to different kissams could be owned by an array of government departments or private entities, depending on which it may or may not be possible to grant land rights. It is these attributes that must be cross-referenced with each other and with the location and household data of the slum dwellers in order to satisfy all the conditions necessary to settle land rights.

Quantifying Complexity

Let's take the example of a single city of Balasore in Odisha. The 3128 families living in 41 slums of this city are located on 735 land parcels with belong to 33 different 'kissams'.

Let's further consider a particular 'kissam' called 'gharbari', which refers to homestead. There are 238 parcels corresponding to this kissam out of which 121 parcels are owned by private enitities; 71 parcels are owned by the railways; 23 parcels are owned by temple trusts and 23 parcels are owned by various departments and offices of the state government. Only the slum houses located on the last 23 parcels in the above list, can be settled without getting into special arrangements and negotiations with other government departments and private entities.

This is just one kissam out of 33. Now, also consider the location of the 41 slums in the city and how the 3128 slum houses intersect with the land parcels of various kissam and ownership types. 

What has been described above is the case of just one city out of 115; just 41 slums out of 2919; and a mere 3128 slum houses out of a total of above 400,000.

This is complexity quantified.

And this is why we need the processing power of modern computers (and not for making powerpoint presentations on the achievements of the Mission).

Political will is a necessary condition...but not a sufficient one

This is also the reason why in the first phase of Jaga Mission, which covered about 170,000 slum households in 109 small and medium towns of Odisha, the government reached as impasse after granting about 70,000 land rights certificates. The remaining 100,000 households fell on land parcels belonging to various reserved kissam categories, restricted central government lands, private entities, temple trusts or environmentally hazardous lands.

Instead of basking in glory for having distributed 70,000 land rights certificates in less than two years (no mean feat !) the Department of Housing and Urban Development, the nodal agency overseeing the implementation of the Mission, went out of its way to initiate inter-departmental negotiations with the revenue department, forest and environment department, private entities such as royal families, temple trusts etc to find workable solutions to grant land rights to the remaining slum households. Special standard operating procedures were also developed to address the challenge of slums located on highly restricted central government lands such as those belonging to railways and defence, which may require relocation.

The special measures initiated by the Government were a clear indicator of the strong political will that backed Jaga Mission. It was also a clear indicator that even when a strong political will exists (which is rare in itself), the implementation of any large pro-poor intervention may face serious challenges due to technical and operational reasons.

And it is extremely important for people not directly involved with the implementation of such projects to have a thorough understanding of these operational reasons if they wish to engage effectively and critique accurately.

Consider this news clip (in Odia) from 2019, by a regional news channel which was critical of the Mission. It showed the residents of a slum called 'Godhi Basha', who had not received land rights certificates. However, the news anchor could not give any reason for the state of affairs apart from the usual one that the government was failing to keep its promise to slum dwellers. At the 33 second mark, the clip showed a beneficiary called Ms. Anjana Das holding the card showing her Jaga Mission house number.

However, as we have already seen, lack of political will is definitely not a problem with Jaga Mission. What then is the mystery of the Godhi Basha slum ?

Had the journalist investigated just a little more, he would have discovered that the whole slum was situated on a parcel of land that belonged to "South Eastern Railways" - one of the 72 land parcels in the city which are owned by the Indian Railways. As a matter of fact, the journalist also got the name of the beneficiary wrong.

It was possible to identify all these issues in time less than the duration of the news report, thanks to the digital data collected as part of the Mission, relevant open-source software and quick data analysis on the command line, which we started discussing in the last two blogs. 

Unfortunately, as I have shown through case examples in another blog, the government itself fails to utilise available computing technologies effectively by continuing to rely on archaic bureaucratic methods and pointless application of manual labour (relying on paper maps and field visits despite possessing high-resolution imagery and GIS databases).

It definitely retains operational overview but it cannot solve the complex problems (where complexity is merely a function of processing power available i.e. with respect to the computer, they are simple problems) which not only prevent it from overcoming its operational impasses but also cause community level confusion as shown in the case of the news clip.

Community Empowerment at Slum level...Community dis-empowerment at Mission Level

Just as the Government faces its own difficulties for not using available technologies effectively, so does the community.

As I have pointed out earlier, given the size and complexity of projects such as Jaga Mission, the typical methods of community participation, engagement and critiquing are simply not adequate. 

It is not enough to understand why something is not working in one's own slum - it is only one out of 3000 slums ! 

That means 0.0003 % of the Mission in terms of the number of slums.

How can the community get effective overview of the implementation of the Mission while covering (at the level of each slum) a microscopic 0.0003 % of the Mission, when the Government and its consultants have overview of 100 % ?

Just have a look at the maps above. The one on the left, shows the location of Godhi Basha among all the slums in Balasore city; and the one on the right shows the location of Balasore city among all the cities covered by Jaga Mission. 

I hope this gives some sense of the scale....in other words, what 0.0003 % looks and feels like.

Unfamiliar methods...or merely abandoned ?

This is why it is neither enough for governments to continue using their familiar bureaucratic methods, nor is it enough for community organisations to continue using their familiar participatory development methods. 

Probably it is time to embrace the unfamiliar methods.

The size and complexity of urban challenges in the present times demands the use of methods which were created specifically for tackling large, complex and dynamic systems -- more extensive use of open-source geo-spatial software and data analysis; further refinement of mathematical models for urban and regional planning; application on the principles of cybernetics to understand the functioning of urban systems; techniques of operations research etc. 

It is an irony that huge progress was made in the development and application of many of the above techniques in solving pressing social problems precisely when computing power was very low, and abandoned in favour of feel-good but ineffectual qualitative approaches (not to mention the pseudo-scientific farce that passes for 'tech' in contemporary urban discourses) when computing power is at its peak.

More on that in forthcoming blogs...