The colossal Himalayan risks – Himachal Floods of 2023. Are we prepared? 

The Indian Himalayan region (IHR) is spread across 13 states/union territories, and nearly 50 million people reside there. IHR stretches about 2,400 kilometres across the northern border of India, covering an area of approximately 500,000 km2. In IHR, natural hazards such as landslides, avalanches, cloudbursts, floods and flashfloods are common, especially during the June-to-September monsoon season, and they often become disastrous for those living on the Himalaya’s fringes. The disastrous events are becoming more frequent as global warming melts the Himalayan glaciers. According to the Global Climate Risk Index Report 2019, India is the 14th most vulnerable country in the world to climate extreme events. India suffered an economic loss of USD 79.5 billion due to climate-related disasters in the last 20 years, according to the UN report titled Economic Losses, Poverty and Disasters (1998-2017). The economic losses due to disasters in the state of Himachal were nearly Rs 8,000 crore between 2017 and 2022 (Himachal Pradesh State Disaster Management Authority). The annual losses from climate-related disasters are steadily increasing everywhere. This shows that more people and infrastructure are exposed to natural hazards, leading to increased climate risk. The 2,500 km-long Himalayan plate boundary is also intensely prone to powerful earthquakes. Scientists fear a great earthquake of 8.5 magnitude or higher in the region. Such a predicted seismic event will create cascading disasters and have a catastrophic effect on the area. Are we prepared for such extreme events?

Although the population density is not very high, the states in IHR attract a vast number of tourists. The rapid urbanization and tourism activities are leading to increased human interference in the fragile hilly areas, especially in the Himachal and Uttarakhand regions. There has been an unprecedented growth in tourist arrivals in the Indian Himalayan states in the past few years. It is estimated that by 2025, 240 million tourists will visit yearly; it was 100 million in 2014, see Figure 1 (NITI Aayog, 2018). The extensive development and tourism activities will affect the soil strength and cause soil loosening. During extreme rainfall events, the soil can easily crack, trigger landslides and lead to road blockages. The impetus to urbanization and unparalleled tourism is bound to bring rapid regional climate variations and transform natural disasters into man-made or anthropogenic disasters.

Figure 1 Tourist arrival forecast in the IHR states by 2025 (Source: NITI Aayog, 2018)

Hazard scenario in Himachal

Floods in Himachal have been a damaging phenomenon, and one of the earliest records of destructive floods dates back to 1894 in River Beas. There were flash flood events in Beas in the 1980s, and the flood situation worsened from 1992 to 1996, see Figure 2. Extreme rainfall during the monsoon season is the primary cause of floods in the state; however, cloudbursts and landslides also contribute to floods. In 1971-2009, 362 flood events were recorded in the state. Though the flood frequency was high at certain periods, the overall trend shows an increase in flood events in the state. The spatial distribution of floods in the state is shown in Figure 3 (left). 

Figure 2 Flood frequency and trend in Himachal Pradesh from 1971 to 2009
Figure 3 Spatial distribution of floods (left) and landslides (right) in Himachal Pradesh (Source: Simrit Kahlon, 2014)

The state also has an established history of landslides. Landslide activities in the past were majorly associated with earthquakes and extreme rainfall events. As per the Government of India (2003), nearly 97.42% of the state’s geographical area is prone to landslide hazards. Historic landslide locations and frequency are shown spatially in Figure 3 (right). The decadal frequency of landslides in all the districts has risen since the 1980s, refer to Figure 4. In the 1990s, 219 events were recorded in the state, at an annual average of about 22 events. In comparison, 474 events were recorded in the 2000s, at a yearly average of about 47 events per year. Table 1 shows a clear increase in the decadal distribution of floods and landslides in the state from the 1980s till the 2000s.

Figure 4 Landslide frequency in Himachal Pradesh from 1971 to 2009 (Source: Simrit Kahlon, 2014)
DecadeTotal LandslidesDecadal AverageTotal floodsDecadal Average
Table 1 Decadal distribution of landslides and floods (Source: Simrit Kahlon, 2014 & Chandel et al., 2014)

State Calamity in 2023

Himachal Pradesh and other neighbouring states experienced torrential rains and landslides during the 2023 monsoon season. Himachal Pradesh was worst hit and bore the brunt of the rain. As per the weather department, Himachal has received 249.6 mm of average rainfall between July 1 and July 11 compared to the normal of 76.6 mm, an excess of 226 per cent and the highest for a 12-day period since 2005. In particular, the Kinnaur district received 500 per cent excess rains, followed by Solan, Sirmaur, Shimla, Bilaspur and Kullu districts with 426, 367, 360, 325, and 283 per cent excess rainfall. On August 18, the Himachal state government declared the rains a ‘state calamity’ and the whole state a ‘natural calamity affected area’. According to the government data, 72 flash floods were recorded in the state from the onset of monsoon on June 24 until September 4, 50% of which occurred from July 8-10 only (IMD, Shimla Centre). In comparison, only ten flash flood events were recorded in 2020, see Figure 5. Cloudbursts were reported in the Tunag, Pundoh and Seraj districts, and 131 landslide incidents were reported across the state. Unprecedented extreme rainfall and rainfall-related catastrophic events, cloud bursts, landslides and flash floods demolished buildings, damaged bridges and washed off several vehicles.

Figure 5 Frequency of flash floods from 2020 till 2023


The 6th Assessment Report by the Intergovernmental Panel on Climate Change (IPCC) has clearly stated that the Indian Himalayan region (IHR) and Indian coastal region are at high risk from climate change. As many as 348 people have died, and 336 have been injured since June 24 due to monsoon-led natural calamities such as extreme rainfall, cloudbursts, landslides, and building collapses. The State Disaster Management Department said that nearly 2,230 houses were fully damaged, and 9,819 were partially damaged (retrieved from the Indian Express articles/reports on the events). The monsoon-led calamities have also disrupted roads, power lines, communication networks and railway lines. About 1,200 roads were blocked or inundated due to landslides and floods in the state.

We used the Sentinel-1 SAR data to map the flood extent of the affected area in Google Earth Engine. This was achieved by comparing the before-flood (June) satellite imagery with after-flood satellite imagery (July-Aug). Figure 6 shows that major flooding happened around the Beas River in the Kangra district and the Sutlej River in the Bilaspur district. An assessment at the district level shows that 368 km2, about 6.4% of the district area, got flooded in Kangra district (see Figure 7), and in the case of Bilaspur district, 69 km2, around 5.9% of the district area got flooded (see Figure 8). 

Figure 6 Flood area extent in Himachal Pradesh
Figure 7 Flood area extent in Kangra district
Figure 8 Flood area extent in Bilaspur district of Himachal Pradesh

We have also assessed the extent of damage to the vegetative cover in the state using the Normalized Difference Vegetation Index (NDVI) on Sentinel-2 multi-spectral imagery, see Figure 9. The land cover changes were assessed for five classes, of which three classes are Sparce Vegetation (Crops and grass), Moderate Vegetation (Agroforestry) and Dense Vegetation (Forests); see Table 2 for the changes in the area under each class.  The results show that approximately 3956 km2 of vegetative land, about 7.1% of the state, has been converted to wasteland or fallow land after the floods. In particular, there is a reduction of 5952 kmof forest land in the state. 

Figure 9 NDVI maps of Himachal Pradesh highlighting the extent of vegetation damage. Top left: Before flood, Top right: After flood, Below: Difference image highlighting the damage
ClassesDescriptionBefore floods (in km2)After floods (in km2)
Non-VegetationWater (deep & shallow); sand2613927625
Waste LandFallow/Wasteland650610462
Sparse VegetationCrop, grass32744373
Moderate VegetationAgroforestry71566569
Dense VegetationForest125186566
Table 2 Land cover classification of Himachal Pradesh Using Sentinel-2 and NDVI. Note: Total area of Himachal Pradesh is 55673 km2

A similar analysis is conducted for the most affected districts in the state. In the Kangra district of Himachal Pradesh, about 1238 km2 of land under crops & agroforestry was affected by the floods, which is about 21.5% of the district and 46% of the crops & agroforestry cover, refer to Table 3 and Figure 10.  In Solan district of Himachal Pradesh, about 172 km2 of land under crops & agroforestry was affected by the floods, which is about 9% of the district and 35% of crops & agroforestry cover, refer to Table 4.  In Shimla district of Himachal Pradesh, approximately 1301 km2 of forest land was affected by the floods, which is about 25.35% of the district and 81.5% of the total forest cover, refer to Table 5.  In the Mandi district of Himachal Pradesh, approximately 1278 km2 of forest land was affected by the floods, which is about 32.3% of the district and 72% of the total forest cover, refer toTable 6. The results show that the floods impacted vast areas under crops, agroforestry and forests. 

Figure 10 NDVI maps of Kangra district of Himachal Pradesh highlighting the extent of vegetation damage. Top left: Before flood, Top right: After flood, Below: Difference image highlighting the damage
ClassesDescriptionBefore floods (in km2)After floods (in km2)
Non-VegetationWater (deep & shallow); sand13281820
Waste LandFallow/Wasteland510825
Sparse VegetationCrop, grass1467500
Moderate VegetationAgroforestry1223952
Dense VegetationForest21771608
Table 3 Land cover classification of the Kangra district in Himachal Pradesh Using Sentinel-2 and NDVI. Note: Total area of Kangra district is 5739 km2

ClassesDescriptionBefore floods (in km2)After floods (in km2)
Non-VegetationWater (deep & shallow); sand182596
Waste LandFallow/Wasteland300491
Sparse VegetationCrop, grass221202
Moderate VegetationAgroforestry466313
Dense VegetationForest787354
Table 4 Land cover classification of Solan district in Himachal Pradesh Using Sentinel-2 and NDVI. Note: Total area of Solan district is 1936 km2

ClassesDescriptionBefore floods (in km2)After floods (in km2)
Non-VegetationWater (deep & shallow); sand15502410
Waste LandFallow/Wasteland9141429
Sparse VegetationCrop, grass348465
Moderate VegetationAgroforestry724532
Dense VegetationForest1595294
Table 5 Land cover classification of Shimla district in Himachal Pradesh Using Sentinel-2 and NDVI. Note: Total area of Shimla district is 5131 km2

ClassesDescriptionBefore floods (in km2)After floods (in km2)
Non-VegetationWater (deep & shallow); sand5081720
Waste LandFallow/Wasteland445760
Sparse VegetationCrop, grass297381
Moderate VegetationAgroforestry918584
Dense VegetationForest1780502
Table 6 Land cover classification of Mandi district in Himachal Pradesh Using Sentinel-2 and NDVI. . Note: Total area of Mandi district is 3950 km2

Is climate change alone to be blamed?

Climate change must have increased the intensity and frequency of extreme weather events, but is climate change alone to blame for all the devastation in Himachal Pradesh? The high impact of the rains was observed in the areas with high infrastructure development, deforestation for infrastructure and hill cutting for road widening. Mega hydropower projects and several dams were constructed in the fragile and eco-sensitive zones of the state. As per the 2022 landslide risk assessment report by the Himachal government, 77 blocks having 18,577 villages are landslide-prone. As per the experts, the reason for that is deforestation and the replacement of old stone and clay houses with concrete ones. An investigation by India Today revealed that many buildings that collapsed or were damaged in the floods were constructed on river banks or active floodplains by encroaching. The revenue records have also not defined the river boundaries, which gave rise to illegal constructions, threatening ecosystems and human life. Thefloods have also brought attention to the illicit mining and construction activities on the river banks. Tourism rush, rapid urbanization and unplanned infrastructure development are the major causes of massive devastation in the state.

Mansi Asher, who has published several papers on the changing climatology of Himachal Pradesh, said, “There is enough data from the department of science and technology of Himachal government to suggest that frequency of cloudbursts have increased, and so have landslides. The maximum impact was seen near the infrastructure sites which disturb the hills.”

Are we prepared?

The Himalayan region is a dynamic landscape and is at a high risk from climate change. The people living in these areas are prone to high seismic activities, cloudbursts, floods, extreme rainfall events, and forest fires. Clearly, massive efforts are required to protect the people and infrastructure in the Himalayan region from climate change disasters. The monsoon floods in Himachal have caused massive devastation, and the state is in need of an effective multi-hazard preparedness and disaster mitigation programme. 

Need for climate vulnerability assessments at village level

An effective disaster mitigation programme will have several components. Some of the major components include hazard mapping, hazard impact assessments, vulnerability assessments, risk assessments, and deriving mitigation strategies based on cost-benefit analyses. Vulnerability assessments are an inevitable prerequisite for disaster risk reduction and climate change mitigation measures. Climate change vulnerability assessments at the community level or village level will reinforce the disaster preparedness of the state. Village-level vulnerability and risk assessments will assist policymakers and decision-makers in effectively increasing the adaptive capacity and preparedness towards extreme weather events. It also helps in prioritizing the villages for resource allocation. It also helps in community-based disaster management, i.e., encouraging communities at risk to get engaged in all phases of disaster management. 

Sustainable land-use planning

Another component that needs attention is land-use planning. Sustainable land-use planning, which encourages people living in the most vulnerable areas to move, is essential. Sustainable Land Use Planning for urban climate resilience includes:

  • limiting development in hazard-prone areas
  • ensuring that the built environment can withstand a range of natural disasters
  • helping to preserve natural ecosystems
  • protecting communities against hazards
  • promoting nature-based measures for adaptation
  • educating stakeholders and decision makers about risks and opportunities and fostering dialogue about adaptation

In Himachal, several houses were illegally constructed in the flood plains and river banks. They are at high risk from future climate hazards. The government needs to bring strict land-use planning that encompasses the disaster and climate risks.

We also need to update our risk assessment methodologies and develop disaster mitigation strategies using the geographic information system (GIS) and remote sensing technologies. Web-GIS-based decision support systems are extremely helpful for governments, research organizations, companies, communities, and NGOs to transfer knowledge and expertise, and share the available data.





Unlocking the Transition: Harnessing GISKernel to Move Seamlessly from ArcGIS Web App Builder to Experience Builder

In the rapidly evolving landscape of Geographic Information Systems (GIS), innovation is the compass guiding us forward. As technology ushers in new possibilities, ESRI’s ArcGIS suite stands at the forefront, offering transformative tools like Web App Builder and Experience Builder. If you’re ready to unleash the full potential of your GIS applications, here’s our comprehensive guide to effortlessly transit your applications from Web App Builder to the dynamic Experience Builder. 

Embracing Evolution for Exponential Growth 

In the ever-adapting world of GIS, staying stagnant is not an option. Begin by emphasizing the power of evolution and how transitioning from Web App Builder to Experience Builder is not just a step but a leap towards exponential growth in your application capabilities. As the digital landscape evolves, so do the tools at your disposal. Imagine a future where your GIS applications transcend the ordinary, offering a dynamic user experience that captivates, educates, and engages. This is the promise of Experience Builder, ESRI’s cutting-edge solution that takes your applications from functional to phenomenal.  

From Web App Builder to Experience Builder 

Nearly, all the functionality used in Web AppBuilder is available in Experience Builder, along with the additional functionality. The ready to use widgets can be directly implemented in Experience Builder which are used in Web App Builder. Though Experience Builder is different from Web AppBuilder in a variety of ways. Because of these differences, directly converting custom widgets and themes from WAB to Experience builder is not possible. There’s when we, GISKernel can elevate your experience to shift from WAB to Experience builder very seamlessly and intuitively. You can visit this link where ESRI has provided the functionality matrix between these two. Such implementation of built-in widgets can be done smoothly. Experience Builder, like Web AppBuilder, is a low-to-no-code tool for creating web apps that interact with ArcGIS data. One difference between them is their underlying technology: Experience Builder is built on ArcGIS Maps SDK for JavaScript (Web AppBuilder was built on ArcGIS API for JavaScript). 

Why to choose Experience Builder 

Experience Builder offers a higher level of customization than Web AppBuilder. In Experience Builder, an experience is a web app that you build using drag-and-drop functionality to position maps, images, menus, and other widgets and tools on a page. The developer edition of WAB will be retired in July 2024. See below for some comparison between WAB and Experience Builder. 

  • In WAB, user can opt either for 2D or 3D application to start with. While in Experience Builder, 2D and 3D content are supported in one app. When it comes to variety of templates to start with, Experience Builder offers wide range of options rather than WAB. 

  • The most important feature of Experience Builder is that user can change the widget setting from docked window and visualize it in real-time on application. Whereas in WAB, the widget setting page comes with popup window which restricts the user to see changes while applying from the page. 

Experience Builder Widget Settings Page

Web App Builder Widget Settings Page 

  • Experience builder supports integration of multipage apps for display on fixed or scrolling screens. That means a user can add an internal Page link button which will redirect the application to another page. The page can be map-centric or just the info page.  
  • Experience builder can create interactions between widgets. Data actions provide an Actions button that end users can click in widgets at runtime and select from a list of actions to perform, such as exporting records to a file. Such implementations cannot be done in WAB.  

Challenges in shifting and how GISKernel can help you with it? 

The most important challenge to face while migrating from WAB to Experience Builder is the technology difference between these two. While WAB is built on ESRI JS API (3.x), Experience builder is developed using JavaScript SDK (4.x). Along with that, another major difference or we can say the advantage is React integration with Experience Builder. It is very important to stay up to date with recent innovations and developments. Such integration of React along with Redux is very helpful to carry out the advance level of custom widget development. That is where GIS Kernel can be very resourceful for such tasks. Transitioning from Web App Builder to Experience Builder is not a leap into the unknown—it’s a well-guided journey. We at GIS Kernel have experience in both WAB and Experience Builder custom development. Already many of the stakeholders have started shifting to Experience builder the major concerns come when developing a custom widget that has already been there in WAB. We have segmented the process of such custom widget development in Experience Builder which explain the step-by-step process for it.  

GISKernel helps you the shift from WAB to Experience Builder by implementing your WAB widgets and transforming them into the Experience Builder widgets with more efficient design. We can also help you with developing the out of the box custom widgets based on your requirement and integrate it to the Experience Builder Application. We can help you to design your application by developing the UI/UX theme for the application for the smooth user experience without any hassles. Experience builder comes with ready-to-use and advanced level widgets, but when it comes to develop the custom widget or enhance the default widgets, we can help you for such developments. Also, as we have learned above that we can add pages to the experience builder application, GISKernel can help you to design and develop such applications where user can navigate to multiple pages for more informative content.  

The journey from Web App Builder to Experience Builder is a transformative adventure—one that promises innovation, engagement, and growth. We are ready to take the next step in shaping the future of your GIS applications, are you? If yes, then sooner than better! Let’s dive into Experience Builder today and unlock a world of possibilities that will elevate your applications beyond imagination. 

The Curious case of querying large raster datasets on the fly via an internet facing portal.

Geospatial data is quite different from any other data you can work with it being difficult to understand and manipulate, one of our clients came up with a unique request to work with raster datasets and find a particular value of a pixel and statistical information on the fly which was also understandable to a no GIS user. Although, this may seem simple enough process but let me explain how it is quite different on the surface and what’s beneath. But first of all, let’s get into what are different Geospatial datasets.

Geospatial data can be broadly divided into two parts:-

Vector Data: Vector data represents geographic features as points, lines, and polygons. It includes information about the coordinates, shape, and attributes of these features. Examples of vector data include road networks, boundaries, buildings, and vegetation boundaries. Vector data is often used for detailed spatial analysis and precise representation of features.

Raster Data: Raster data represents geographic information as a grid of cells or pixels, where each cell contains a value. It is commonly used to represent continuous phenomena, such as elevation, satellite imagery, and climate data. Raster data is structured as a grid, and each cell corresponds to a specific location and carries information about the attribute being represented.

Since in GISKernel, we have an expertise in working with different type of Geospatial data one of our client came up with a unique request of processing Raster data quite smoothly and fast, as Raster data is continuous and quite large on the fly information of a particular cell/ grid have to either stored as a cache or takes time to show up. Furthermore, the client which we were working on doesn’t have any mapping interface to process the request as they wanted a particular cells grid/ information either as a pixel value or a band value.

As Raster are huge files, finding a particular pixel value on a non-mapping interface is like finding a needle in the stack. Also, Raster’s and databases dont fit in well with each other as the data tables are to be created with raster datasets which eventually leads to change in raster datasets data creation, furthermore we needed to filter huge amount of spatial data which tens of thousands of people would be able to query on the fly via just uploading the raster files to the portal.

To tackle all the abovementioned scenarios, we curated a custom application which consisted of:-

Using AWS S3 buckets for Data storage:- We chose S3 buckets for Data Storage for continuous access over the cloud and availability of data, as different users can upload, and the application can access the data everywhere once connected with internet.

Backend data management via POSTGRES SQL:- We chose POSTGRES as it was open source and free to use. Also, it is malleable with geospatial data types, these included running fast spatial queries either from a database or an API with using raster2pgsql extension in backend to allow raster datasets to sit in and be allowed to query.

GDAL Libraries:- To properly use this tool, we also used GDAL libraries which improved raster data handling massively.

Django Based API application:- We used this API to provide a seamless experience for our users once they have the access to the application hosted over the internet. This frontend assisted our users in querying out all the requirements from getting a particular pixel value in a raster dataset to getting a mean median and mode of an extent which massively reduced their dependency on directly accessing the datasets and then applying queries. 


Application Overview:-

The simple application structure of an odd task greatly reduced the stress on database maintenance, user accessibility, and non-GIS users accessing spatial datasets. As a GIS folk we understand how rasters work and a particular value from a grid is easy for us to load up on a map and imagine, but the effectiveness of this tool can help any non GIS user to extract data from a raster dataset without the hassle of loading, downloading and deleting a GIS software.

Celebrating 5 Years of Innovation: The Journey of GISKernel

Revisiting the History

The journey of GISKernel started about five years ago in February 2018. A young and passionate founder, Akshay Loya, who had the vision to revolutionize the world of GIS through its advanced and innovativ use to solve complex business problems.

Akshay started his career as a Biotechnology student who was introduced to the world of GIS by his mentor. His mentor mentioned “GIS is basically like a map on steroids! Trust me, you’re going to love it.” which inspired Akshay to explore more. He was fascinated and was determined to make a career in it.

He went on to crack an interview for the Symbiosis Institute of Geo-Informatics and the journey has only been onwards and upwards from there.

Akshay’s entrepreneurial spirit led him to pursue his passion for GIS through freelancing. His first project at the University of Washington proved to be a success, allowing him to hire his first employee and lay the foundation of GISKernel. The company, GISKernel, reflects the core essence of GIS, which serves as the foundation for all the work they do.

Milestones and Accomplishments

Since its inception, GISKernel has achieved several milestones and accomplishments in its five years journey.

Milestone #1: Recognition as a Startup by the Government of India

GISKernel received recognition as a Startup by the Government of India for the Promotion of Industry and Internal Trade in January 2019 – a testament to its potential. This recognition opened up new opportunities for the company to grow.

Milestone #2: Tax Exemptions under the “Startup India” Scheme

GISKernel received tax exemptions under the “Startup India” scheme in April 2021 for 3 years – an enormous financial support during its early stages.

Milestone #3: Showcasing Work at Dubai Expo

The steadily growing company showcased its work at the Dubai Expo 2020 to potential investors, engaged with different stakeholders and networked with other startups –  a significant achievement and recognition of its innovative work in the field of GIS.

Milestone #4: Exhibit their Work at Science City, Ahmedabad

In September 2022, GISKernel was selected to showcase its work at Science City Ahmedabad to 500 bureaucrats from all over India. It was a good channel to network with the know how’s of the industry

Milestone #5: Restarting the Office after Covid-19

The COVID-19 pandemic was a global challenge that affected almost every aspect of life, including businesses. Despite the difficulties posed by the pandemic, GISKernel persevered and successfully restarted its operations in January 2023. This accomplishment is a testimony to the company’s resilience and determination in the face of adversity. It showcases the company’s commitment to its mission and ability to overcome challenges and emerge stronger.

Each of these milestones and accomplishments serves as a reminder of the company’s journey so far and its unwavering commitment to innovation and growth.

Looking Forward

GISKernel has a clear vision for the future with plans and goals that are ambitious and attainable. The company is focused on continuing to provide innovative solutions and services to its clients while exploring new opportunities and markets. With its dedicated team of experts and its commitment to excellence, GISKernel is poised for continued success and growth by making a positive impact in the world of GIS.