Report: The Role of Technology in Conservation in India | SCCS-Bangalore 2019

On the 16th October 2019, Technology for Wildlife (TfW) organised a panel discussion on the ‘Role of Technology in Conservation” at the Student Conference on Conservation Science, Bengaluru. The format of the panel discussion was 15-20 minute presentations by each panelist, followed by a few questions from the audience for that panelist; once all the panelists spoke, there was time for questions at the end.

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The panelists were Prithvi from Appiko, Abhi from Wildly, Jose from the Wildlife Trust of India, and Shashank from TfW. Unfortunately, this had to be an all-male panel; though we had invited four women working in this space to participate, none of them were able to make it.

The panel began with Prithvi from Appiko, who walked us through the range of Appiko’s products, with an emphasis on their sensors that allow regular cameras to be used as camera traps. I found their explanation to why they had chosen to build camera traps interesting since there are already off-the-shelf camera traps available. In Prithvi’s opinion, even camera traps used for tiger estimation, which are perhaps one of the most abundantly used technological devices in Indian conservation, were origninally developed to optimize hunting and are not always conducive for wildlife surveys. This is indicative of the current relationship between technology and conservation even for a well-funded issue such as tiger conservation, where there is limited funding for innovation; technological needs are met through ‘jugaad’ of existing technologies meant for other applications. My favourite take-away from Prithvi’s presentation was his outlook on the role of technology in conservation: “Technology is just a tool for conservation, but with the right tool, you can do a lot more.” 

The next speaker, Abhi from Wildly, was also focused on developing hardware for conservation. Their company is currently building acoustic devices to detect illegal activities in protected areas. Later in the conference, I had a chance to listen to them demonstrate their work during another workshop on Machine and Deep Learning, and it was really interesting to learn what applying these techniques in the current Indian conservation context entails. My most valuable take away from Abhi’s presentations was that their technology was created and developed out of a current conservation need. This, coupled with the fact that they are trying to be open-source and affordable makes them a very interesting organisation, who’s work we will be following.

The third presentation, by Jose from the Wildlife Trust of India, was on his work with Wildlife Crime Prevention. It was a very engaging talk and differed from the others in that he focused on the sustainability of technology more than on sustainable technology. He discussed various technological interventions that have been developed for his work, such as HAWK, and on how his team’s vision and working relationship proved to be more important in ensuring effective technological interventions more than the nature of the technologies themselves.

The final presentation was by Shashank from TfW. Multiple people communicated that they enjoyed his talk and that his enthusiasm was communicated in the presentation. It was the only non-hardware technology business in the group and I think his presentation on our work communicated the varied uses of technology in conservation.

Overall, the panel was interesting and unique. In future iterations of this panel, it may also be useful to invite panelists working in areas related to conservation ecology, such as mainstream ecologists or technologists working outside of conservation. This would help add different perspectives and provide an understanding of the larger picture.

Perceptions of Ladakh (Ladakh Lakes #3)

Ladakh. For someone as besotted with the mountains as I am, the name has always stirred something in my soul. Images and sounds of extraterrestrial landscapes, extremophilic biodiversity and a culture shrouded in yak-skin mystique have gnawed at my imagination for years, urging me to venture forth. Something kept holding me back. Thanks to Technology for Wildlife and Shashank, my long spell of indolence paid off and I was able to experience the trans-Himalaya in a special way – not only for the relatively remoter regions we were able to access (owing to some expedition-level planning and permission-seeking by TfW), but also for the work we ultimately set out to do. You have (or will) read enough about the work conducted during the expedition from the keyboards of more qualified persons here on this blog. This post is about the mountains, and time in the mountains is valuable – so let’s get right to it.

The author exploring another part of the Himalayas in October 2017. Photo: Shashank Srinivasan | 2017

The author exploring another part of the Himalayas in October 2017. Photo: Shashank Srinivasan | 2017

I have been exploring the Himalaya (mostly on foot, and in limited pockets) for the last four to five years now. I recently obtained my Basic Mountaineering certification from the National Institute for Mountaineering and Allied Sports, at Dirang (in West Kameng, Arunachal Pradesh). Being as it is under the Ministry of Defence, the Institute also caters to defence personnel who are required, or are looking, to gain competence in mountaineering (whether for warfare, or for participation in armed forces peak-climbing expeditions). Only a fraction of the month-long course is conducted at the Institute itself, and the rest in various stations in Tawang district, right up till the final station at the base of the Meerathang glacier (at about 4600 metres ASL). Most of these areas are not accessible to civilians, and I – along with the rest of my course mates - was fortunate enough to see some truly pristine parts of the Eastern Himalaya, with appropriately breathtaking biodiversity to match the stage.  This region of India is culturally contiguous with southern Tibet, of which Ladakh forms the western frontier. I was almost trembling with anticipation at this - to be travelling to the other end of the Himalayas, mere months after my 28-day boot camp in its eastern reaches.

The road connecting Kinnaur to Spiti. Photograph: Shashank Srinivasan | 2019

The road connecting Kinnaur to Spiti. Photograph: Shashank Srinivasan | 2019

We began our journey in Kalka, travelled through Narkanda (in Shimla district), Rampur Bushahr (the gateway to Kinnaur), stopping at Nako (Kinnaur), Dhankar, Kaza (in Spiti) and then via Keylong towards the settlement at Thukje (at Tso-Kar) before proceeding to the other sites on our itinerary. Over about 7 days, and thanks to our first terrific driver Lucky (from Kullu), we negotiated roads (of varying descriptions, but I’ll call them all roads for the sake of convenience) through the foothills, lesser Himalayas and Greater Himalayas before crossing over into the trans-Himalayan region - Kinnaur and Spiti (literally the ‘in-between land’) - and ultimately entering the dramatic cold desert region that is Ladakh.

The changing landscape was very different to the road trip from Gauhati to Dirang, which starts at the floodplains of the Brahmaputra, crosses the lush foothills of the Eastern Himalaya and takes one to the gateway of the higher reaches, towards the McMahon Line and the famous Bailey Trail along the Arunachal Pradesh-Tibet border. For one, the lush forests at the lower latitudes of the Arunachal Pradesh Himalaya are ubiquitous even as high as 3500 metres above sea level. As we move northwards and westwards, the tree line gets lower and lower and vegetation in Ladakh (which is at an average elevation of 3200-3700 metres ASL) is very different – there are poplars and willows but mostly plantations in irrigated areas, or in the lower reaches of the valleys. Other than that, there are bushes typical of desert areas, shrubs and grasses. The land itself is more undulating than mountainous, and the vistas sprawl wider than is possible to see in the Himalaya proper. The cultural contiguities with Arunachal were surprising, though – given the three thousand or so kilometres of mountains, plains and valleys that separate these two regions. The ethnic identities of their peoples as Tibetans is still preserved – in the common traditions of their robes (minor variations of the Tibetan Chuba), their lifestyles (both the Changpa of Ladakh and the Monpa of Tawang are pastoral tribes, chiefly herding goats and yaks), and their faith (Tibetan Buddhism is still the dominantly ‘visible’ religion in both places, and predates Islam and Christianity in Ladakh). Even their wildlife is shared - marmots chatter at the higher reaches of the Arunachal Himalaya, and can be found urgently waddling their way throughout most of Ladakh as well. The black-necked crane (thung thung to the locals of Ladakh) breeds in the wetlands of Ladakh and flies down to Bhutan and Tawang for the winter. It is revered as sacred by the Changpas and the Monpas alike.


The black-necked crane ( Grus nigricollis ), revered in both Arunachal Pradesh and Ladakh. Photo: Shashank Srinivasan | 2017

The black-necked crane (Grus nigricollis), revered in both Arunachal Pradesh and Ladakh. Photo: Shashank Srinivasan | 2017

As the likenesses strike, so do the contrasts. The visual dominance of Tibetan Buddhism over the Ladakh landscape thinly veils the cultural eclecticism of a land that lay at the crossroads of important trade routes, from the Far East to Central and Western Asia. The influence of multiple ethnicities – Uighur, Balti, Kashmiri, Punjabi and Tibetan – is amply visible in Leh, especially in the establishments and homes near the Main Bazaar and old city.  The limited availability of wood in Ladakh is evinced in the mud houses that dominate the rural landscapes (Leh has become increasingly concretised), in contrast to the stone-and-wood houses of Arunachal (more common in the Himalaya and sub-Himalaya). Wood is used in Ladakh, though sparingly, and is more commonly seen in the houses of the affluent, in gömpas (religious buildings), choskhors (religious enclaves) and the palaces. The dominance of tourism as a sector of the economy in Ladakh also struck me; the careful curation of its cultural features for the foreign eye – opening up, so to speak, while trying simultaneously to hold on its identity. We were told by the founder of our travel agency, Jigmet, that local hospitality operators blacklist or even penalize anyone with a MakeMyTrip sticker – an old value of the Ladakhi people and a lesson that has been reinforced from other Indian towns that have become tourist spots at the cost of the local economy and culture, such as Manali. In contrast, the more difficult terrain and remoteness of Western Arunachal have engendered a more culturally homogenous population, as well as a much lower influx of tourists. Their problems are different – of infrastructure, of connectivity, of integration with the rest of the economy.  Their ecology and its associated services are threatened, just not as visibly as in the extremes of Ladakh where the lack of water and the changing precipitation patterns are far more perceptible as effects of anthropogenic climate change.  

Hopefully, the work our team has started will go some way in bolstering the conservation efforts already underway in Ladakh (and eventually, other high-altitude regions as well), and ensure these fascinating landscapes survive as more than just stories.

The author removing litter from a high-altitude lake in Ladakh. Photo: Shashank Srinivasan | 2019

The author removing litter from a high-altitude lake in Ladakh. Photo: Shashank Srinivasan | 2019

Mountains of Trash (Ladakh Lakes #2)

Twenty four Mountain Dew bottles and counting. It has now become a game to count the number of freakishly fluorescent fizzy drink bottles we see strewn along the roads in Ladakh. As the car snakes its way towards the most remote of lakes, we continue to find bottle after bottle. 

Here in a remote part of the Indo-Tibetan plateau sits Lake Yaye Tso, like a jewel in a crown of Himalayan mountains. The lake is luminous, changing colour from grey-green to turquoise and then back to an other-worldly blue. On the shores of this beautiful isolated lake sits another Mountain Dew bottle, now an integral feature of the landscape. 

A discarded Mountain Dew bottle found on the shores of a high-altitude lake in Ladakh. Photo: Gabriella D’Cruz | 2019

A discarded Mountain Dew bottle found on the shores of a high-altitude lake in Ladakh. Photo: Gabriella D’Cruz | 2019

The Himalayas have over the years grown in popularity, with tourist towns springing up across the region. Lack of planning and foresight have led to a mounting waste problem that’s getting harder and harder to resolve. Ladakh, with its stark desert landscape and sheer mountains, is now glittering with garbage. 

Who do we hold responsible for contaminating even the most remote corners of our planet?

For starters - ourselves. We decided to calculate how much waste four environmentally conscious people generated over a two week expedition in the mountains. My Snicker-bar addiction combined with Nandini’s potato-crisps obsession didn’t help, but we tried to keep our plastic consumption to the bare minimum, carrying our own drinking water bottles and not chewing gum made a difference. At the end of our little Himalayan adventure we had generated a total of sixty individually identifiable pieces of litter.

Keeping track of everything we generated on a daily basis was a distressing process. One butter pack, one biscuit wrapper, two cigarette butts, a packet of Maggi noodles - single use and destined to end up buried underground, dumped in a landfill or blowing across some pristine plateau. I haven’t had to document what I’ve generated before. This was both educative and depressing. 

However, our waste footprint was dwarfed by the amount of garbage we found at the nine lakes we surveyed. We began fervently removing all the plastic waste we saw, from large gunny bags to earphones to tiny slivers of plastic wrappers, soon realising that the more human litter we collected the more we found. Plastic disintegrating in the soil, plastic floating in the lakes and sunken plastic at the bottom. After documenting a total of six hundred and ninety eight pieces of litter in varying forms at the nine lakes we visited, from beer cans to flip-flops, and from sanitary napkins to ketchup sachets, we carried it with us to Leh. We added it to the city’s waste cycling stream, in the hope that ultimately, it would be sensibly disposed of. 

A majority of the waste generated in remote Himalayan towns remains where it is, clogging up streams, sinking into the soil and contaminating lakes. Pangong Tso, one of the most popular among tourists attracts over six hundred vehicles to its shores every day. The lesser known lakes such as Yaye Tso and Chilling Tso are still relatively pristine; however, with Ladakh’s new status as a Union Territory it is only a matter of time before tourists make their way to these more isolated lakes, with Maggi noodle packets and Mountain Dew bottles in tow. 

A marmot bounding away from the camera. Photo: Shashank Srinivasan | 2019

A marmot bounding away from the camera. Photo: Shashank Srinivasan | 2019

For now Yaye Tso sits beautiful and nearly free of plastic, its waters supporting a fragile marshland full of bar-headed geese and colonies of pikas and marmots. I pick up the rogue Mountain Dew bottle as we leave for Leh. A spot of paradise, plastic free for a day.

The author photographing a Mountain Dew bottle before removing it from the lake shore. Photo: Nandini Mehrotra | 2019

The author photographing a Mountain Dew bottle before removing it from the lake shore. Photo: Nandini Mehrotra | 2019

Introduction: Machine Perspectives on Alien Landscapes (Ladakh Lakes #1)


In August and September 2019, a team of four humans and two robots set out to survey a set of high-altitude lakes in the Indian trans-Himalayan region. The purpose of this expedition was two-fold; for the robots to explore the lakes, providing a perspective on them impossible from human eyes, and for the humans to assess the amount of human litter in and around the lakes, with a special emphasis on plastic. Over the next few weeks, we’ll be sharing our experiences and imagery from the expedition in the form of blogposts on this blog, and will eventually be cross-posting them on National Geographic’s OpenExplorer portal as well.


This expedition was supported by a National Geographic Early Career Grant and by the National Geographic/OpenROV S.E.E. Initiative.

Assessing Ecosystem Carbon using Drones: The State of the Art

We use imagery from UAVs to calculate the heights and volume of individual mangrove trees, and can use this information to calculate the above-ground carbon stock within a given area.

We use imagery from UAVs to calculate the heights and volume of individual mangrove trees, and can use this information to calculate the above-ground carbon stock within a given area.

While quantifying the actual value of nature may not always be possible or even desirable, the scientific community has been developing methods to quantify ecosystem services to bolster the case for the conservation of those ecosystems for a while. In our previous blogposts, we summarised methods used to estimate ecosystem carbon based on satellite imagery and field work. In this blogpost, the last in this series (for now), we examine potential methods of estimating carbon using Unmanned Aerial Vehicles (UAV). With UAVs rapidly becoming more accessible, it is important for us to understand how they could be used to provide ecosystem carbon estimates that are more accurate and precise than those derived solely from satellite data.

We examine two broad approaches to assessing carbon using UAVs. The first is based on volumetric assessments of vegetation using UAVs and the second is an attempt to use UAV-based imagery to mimic LiDAR-based methods for carbon estimation. We found several studies (Messinger, 2016; Shin, 2018; Mlambo, 2017) that demonstrated the use of UAVs for the assessment of vegetation biomass; while none of the articles we found subsequently estimated carbon, we think its possible to adapt this method for carbon estimation as well. 

A recent study by Warfield and Leon (2019) is a prime example of the first approach, of assessing vegetation volumes using UAVs. They recently conducted a comparative analysis of UAV imagery and Terrestrial Laser Scanning (TLS) to capture the forest structure and volume of three mangrove sites. The data obtained from the UAV and TLS surveys were processed to make point clouds to create 3D models from which the volume of the mangrove forest was estimated. A canopy height model (CHM) was created by subtracting a digital terrain model (DTM) from a digital surface model (DSM). This approach normalises object heights above ground, and as all the pixels in the image are linked to vegetation, the total volume is estimated by multiplying the canopy height value of a raster cell by its resolution. The UAV method produced lower height values in each patch of mangrove forest compared to the TLS surveying method and its accuracy was found to be correlated with mangrove maturity. Identifying fine scale gaps in dense forest is one of the primary limitations of using UAVs to calculate aboveground biomass. This study highlighted the suitability of utilising UAVs to calculate canopy volume in forests that are not very dense.

Though carbon stock was not calculated in the Warfield and Leon (2019) study, it can theoretically be estimated from the values obtained for the canopy volume. As shown in a report published by the USDA (Woodall, 2011), biomass can be calculated using volume, density and mass relationships, as described in equation 1.

Bodw = Vgw * SGgw * W . . . (1)

where Bodw is the oven-dry biomass (lb) of wood, Vgw is the cubic volume of green wood in the central stem, SGgw is the basic specific gravity of wood (i.e. the oven-dry mass of green volume), and W is the weight of one cubic foot of water (62.4lb).

Converting this into the metric system is a trivial calculation, and the resulting value for dry biomass can then be replaced in equation (2) to calculate carbon stock.

Cp = Bodw * CF . . . (2)

where Cp is the carbon stock within a plot, Bodw is the dry biomass in the plot and CF is the species specific carbon fraction (Goslee, 2012).

In the case of mangroves, the value for carbon fraction would be in the 0.45 to 0.48 range; in a previous blogpost, we described how Bindu et al. (2018) use a factor of 0.4759 on the AGB to generate an estimate of carbon.

The second approach for using UAVs to estimate carbon is based on a study conducted by Messinger (2016) in the Peruvian Amazon. In this study, UAVs were used to create a 3D model of the forest, which was compared with data of the same forest obtained through a LiDAR survey conducted in 2009. In order to estimate carbon stocks in the forest, the authors used a formula and coefficients developed by Asner (2013) which is a method designed to estimate regional carbon stock using LiDAR data.  For carbon estimation they used equation 3.

EACD = a * (TCH ^ b1) * ( BA ^ b2) * (R ^ b3) ………(3)

where EACD is estimated above ground carbon density, TCH is top of canopy height, BA is the regional average basal area, R is the regional average basal area-weighted wood density, and a, b1, b2, and b3 are coefficients estimated from the data.

Basal area is defined as the area within a plot that is occupied tree trunks and stems, and can be calculated using equation 4.

BA = 0.005454 * DBH^2……..(4)

We were unable to find a definite formula to calculate the regional average basal area-weighted wood density. The paper by Asner et al. (2013) uses coefficients based on fieldwork done by the authors and their team in Panama and does not specify the applicability of these coefficients to other forests. Since these coefficients are not specified as universal, it appears that one would have to conduct field work to calculate the variables for this formula. This, coupled with the ambiguity of measuring and calculating the regional average basal area-weighted wood density, makes this study difficult to replicate.

The calculation of the Top of Canopy Height also suffered a setback in this study. In order to derive the TCH, one has to first create a DTM (Digital Terrain Model) and CHM (Canopy Height Model) . The method used in this paper requires the use of LiDAR data in order to calculate canopy height.  In their study, the GPS on the drone was not accurate enough to create a good estimation of the CHM. They thus had to combine their UAV-based Structure-from-Motion model with LiDAR data to make this estimation. They state that this barrier can be overcome by the use of higher precision GPS where error in X, Y, and Z is less than 1m, which is now possible using UAVs in conjunction with directional-GPS (D-GPS) systems, such as the DJI Phantom 4 RTK.

In conclusion, we think that technology and research has advanced to a point where it can be used to carbon stocks using UAVs, but a clear methodology for doing so is still not publicly available. There is a need to synthesize existing methods into the most effective workflow based on these studies and current technology. We believe that having a clear and accessible method that has been tested for accuracy is crucial to bridge the gap between science, policy and conservation, and we’re going to be working on this over the next few months!    


Asner, G. & Mascaro, J. (2013). Mapping tropical forest carbon: Calibrating plot estimates to a simple LiDAR metric. Elsevier. 

Bindu,   G., Rajan,   P., Jishnu, E.   S., & Joseph, K.  A. (2018). Carbon stock   assessment of mangroves using remote sensing and geographic information system. The Egyptian Journal of Remote Sensing and Space Science.

Goslee, K., Walker, S., Grais, A., Murray, L., Casaraim, F., Brown, S. (2012). Module C-CS: Calculations for Estimating Carbon Stocks. Winrock International. 

Messinger, M., Asner, G., Silman, M. (2016). Rapid Assessments of Amazon Forest Structure and Biomass Using Small Unmanned Aerial Systems. MDPI (Remote Sensing), 8(8), 615.

Mlambo, R., Woodhouse, I., Gerard, F., Anderson, K., (2017). Structure from Motion (SfM) Photogrammetry with Drone Data: A Low Cost Method for Monitoring Greenhouse Gas Emissions from Forests in Developing Countries. MDPI (Forests), 8, 68. 

Shin, P., Sankey, T., Moore, M., & Thode, A. (2018). Estimating Forest Canopy Fuels in a Ponderosa Pine Stand. Remote Sensing, 10, 1266. 

Warfield, A., Leon, J. (2019). Estimating Mangrove Forest Volume Using Terrestrial Laser Scanning and UAV-Derived Structure-from-Motion. MDPI (Drones), 3, 32.

Woodall, C., Heath, L., Domke, G., & Nichols, M. (2011). Methods and Equations for Estimating Aboveground Volume, Biomass, and Carbon for Trees in the U.S. Forest Inventory, 2010. USDA (U.S. Forest Service).