Amruth Kiran

Spatial Data Infrastructure (SDI) simply put, is the organization, dissemination and visualization of spatial data. – Amruth Kiran

Interview with Amruth Kiran

Amruth Kiran

Senior Associate – Geospatial Lab at IIHS
Bengaluru, Karnataka, India

Q1. Please share your educational and professional journey with us?

My journey in Geospatial was a bit of a surprise. I started out with a bachelor’s degree in Computer Science and Engineering in Bengaluru. During which, the final semester project for 6 months I was an intern at the University of Trans-Disciplinary Health Sciences and Technology (TDU). The project involved mapping medicinal plants and primary health care centers as an interactive Android application. This was my first introduction to the geospatial domain.

After graduating, I moved to Dehradun, Uttarakhand as an MTech scholar of Geoinformatics at the Indian Institute of Remote Sensing (IIRS), where I specialized in building Earth Observation Data Cubes, under the Indian Bioresource Information Network (IBIN) project, funded by the Department of Biotechnology. Towards the end of my term at IIRS, I applied for an internship at the Indian Institute for Human Settlements (IIHS) back in Bengaluru in 2017 and currently I am a Senior Associate at the Geospatial Lab (GSL) at IIHS.

Q2. You work mostly revolves around Spatial Data Infrastructure. What exactly it is and what kind of work you are doing currently in Geospatial Domain?

Spatial Data Infrastructure (SDI) simply put, is the organization, dissemination and visualization of spatial data. A majority of organisations/institutions and researchers today can be safely called as spatial data consumers with data providers being a select few in the country. The onus is on these institutions themselves to manage project level spatial data. Building a robust, centralized and scalable SDI is a complex and long process that is interdisciplinary in nature, cutting across departments such IT, geospatial and data labs, academic and research teams.

An institutional level SDI has a single goal – To completely incorporate the latest standards in spatial and non-spatial data management, metadata protocols, processing and visualization guidelines with their supporting tools and services for all users regardless of their technical capabilities.

At GSL – IIHS, Bengaluru I’m leading the development of such a system. Over the years, we have started from scratch in understanding what are the prerequisites of a scalable SDI under different silos i.e., data collection (spatial/non-spatial), storage (cloud), dissemination and visualization (portals). I also work with academic and research teams at IIHS in building scalable digital surveys and managing the digital and cloud assets of the lab.

Q3. You have experience in Open-Source tools. Please give your comments on the open-source geospatial technology and its future?

At GSL – IIHS, Bengaluru we are committed to opensource technologies. We not only use and contribute to opensource repositories but also teach our students and practitioners using the very same tools throughout the year. The geospatial domain has improved drastically in recent times and a good by-product is the high number of researchers opting to use opensource tools and services such as QGIS, Geoserver, GDAL, ODK etc. Some of these tools have been around for decades, but the proliferation into mainstream academia and independent researchers for example, is a recent phenomenon due to better outreach, documentation and contributions which has always been a roadblock in the opensource community.

Content creators on YouTube, Medium,, other blogs and a lot of personal websites showcase, in detail a lot of spatial projects and code. Students and researchers alike are forking repositories on GitHub, customizing products to their specific needs and writing about them. Organizations are funding large geospatial conferences, supporting independent developers and making their institutional codebase public. The future is bright. If geospatial can be incorporated deeper into our educational systems, we will see drastic rise in the number of people consuming data, products and eventually contributing to them. These are healthy signs of the open-source geospatial domain heading in the right direction.

Q4. How do you see the latest technologies like AI, ML, Cloud, Web GIS and Data Science in Geospatial Domain?

Thanks to geospatial being an interdisciplinary subset of many domains, it is only natural that Artificial Intelligence (AI) and Machine Learning (ML) will be part of it. A primary differentiator between some-what similar geospatial products in the industry is how easy and accessible is the product, rather than what are the features that it can provide. AI and ML geospatial products bound with strong visualization capabilities can go a long way, but retaining users is all about selling the user experience and solution/insights, not only the product.

Cloud and WebGIS on the other hand is another game altogether. Building “cloud-based geospatial solutions” is different from “building cloud-native geospatial solutions”. Utilizing existing services on AWS or Azure for example definitely has its benefits to build scalable solutions, but cloud-native geospatial is building products for the cloud, not just on it.

Hence novel technologies such as Spatial Temporal Asset Catalogue (STAC) and Cloud Optimised GeoTiffs (COGs) are excellent solutions that can leverage the cloud and break barriers of entry to users. It is exponentially easier to access a tile from the Landsat archives on AWS using a simple query, compared to manually searching for it otherwise.

In conjunction with the cloud, WebGIS products are equally important. A product or data is only useful when it is handed down to users/consumers with the least number of steps/complexities. Products such as the excellent Google Earth Engine, geemap/leafmap, Geoserver, TerriaMap, Open Data Cube, Mapbox and libraries that support WebGIS such as Leaflet and Openlayers have made it easier for users to interact with spatial data at scale. Enabling active development of such technologies by making it opensource is a critical aspect of geospatial outreach and WebGIS tools and services have been the forefront of it for quite a while.

Q5. What did attract you towards Geospatial Domain? What are the essential key things required to become a Full Stack Geo Developer?

When I joined as an intern initially, I was part of a project trying to survey and study the effect of floods in Kerala. A major part was to understand if post-disaster relief and services discriminate between the various castes of people in the region. Once data collection and mapping were complete, the report was submitted to the governing body, and we saw actual implementations of our study and considerations. Solving, or at least trying to solve real-world problems, paved my way forward in choosing geospatial as my career.

Full Stack Geo Developer is quite a mouthful to pronounce and even harder to function, but the basic gist is to be proficient in multiple parallels. Front end to back end, a developer would be required to understand the technical requirements of a project from the user’s perspective as well as various development steps. A holistic approach to see the larger picture, filter out the unnecessary technologies that can be a barrier of access while maintaining standard practice is the basic overview of a Full Stack Geo Dev.

If we go into the details, learning at least one or two programming languages in each vertical for example, SQL for databases, Java Script for interfaces and Python for data wrangling is a minimum. There is also the aspect of server administration, cloud computing on AWS/Azure/Google-Cloud, computer networking and security one needs to concentrate on as well. In simple words, this is an “all-rounder”, and it comes with a slight learning curve. The outcome of such a position is that this enables a developer to see a problem from all the possible perspectives and in terms of personal growth, I believe it offers way more future opportunities and enhanced learning.

Q6. The domain of geospatial technology is visualizing a massive change. Where do you see the geospatial industry to go in the long term?

Within India, GIS and Remote Sensing already has a vital role to play. Across domain, institutions from the likes of ISRO to MapMyIndia have contributed immensely for decades. We are at the cusp of a revolution. The advent of the new geospatial guidelines for India has a been a welcome change in making data, maps, and products more accessible across a spectrum of users. Continuously evolving practices, start-ups and research institutions with innovative methodologies, long-term support both financially and legally will propel India as a major player in the geospatial industry.

Access to internet is a critical function and with India expected to reach 900 million users by 2025 (IAMAI, 2019) the geospatial industry will directly benefit. Geospatial outreach into the rural areas of the country can help mitigate issues pertaining to agriculture, disaster response and relief, education, sanitation and nutrition effectively linking to UNs Sustainability Development Goals (SDGs).

Across the world, we would probably see more funding in universities and think tanks, private players investing heavily in spatial decision-making and business intelligence and creating an equal ground for geospatial researchers compared to their traditional IT counterparts.

Q7. Why college pass out students have a lack of real industrial knowledge in practical terms?

There is a stark difference between what academics teach us and what the industry follows. Sure, the foundational concepts remain the same but things like tools, technical reasoning, documentation, interdisciplinary thought processes and even social interactions with peers is a different ball game. There is no way one can emulate real industry knowledge and practices in college, without disrupting the entire system that has been laid out for decades.

Regardless of it being an undergraduate or postgraduate degree, the only practical way of gaining industrial knowledge in college is through internships. Recently, universities have started a credit-based system where each student has to complete ‘x’ set of months as an internship which adds to their final grade card. This is an excellent step forward in nurturing industrial or even academic practices at an early stage.

Like with everything else, it boils down to the curiosity, the urge to learn and keep up with the trending practices in the modern age. The least universities can do is to provide a healthy space for competition, knowledge sharing, internship opportunities and interactions with industry experts to keep the students interested and occasionally stoke the embers that once ignited a flame.

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