Mapping Floods: Exploring Thresholding Methods

As part of our collaboration with Mongabay-India, we have utilised spatial analysis and visualisation to accompany their reporting. In June 2023, they published an explainer by Vinaya Kurtkoti on floodplains and their management in India. Their article discusses the ongoing process of concretisation and development in floodplains, which reduces the carrying capacity of rivers, leading to urban flooding. 

Presence of water bodies in Mahad pre and post-flood event.

We received information from the Mongabay-India team on urban floods in different parts of India. The data spanned periods exceeding ten years as well as recent occurrences. The task was to create maps of the areas before, during and after each flood event. Availability of suitable satellite imagery was key for creating these maps. This was a challenge as cloud cover during monsoon season - when the floods occurred was often 90% or more.  Thus the initial, critical step towards creating these maps was to check if clear imagery existed for the required flood dates. Additionally, for events older than a decade, the issue of low resolution imagery arose. Initially we planned on showing the flood visually using the raw satellite images. Since we found no clear imagery for the flood dates, we had to look for other options that could depict the flood-prone areas. 

Given the lack of clear imagery for the flood dates, I explored alternative approaches to represent flood-prone zones. Three distinct thresholding methods were experimented with, using three different platforms. 

The first method involved utilising Digital Elevation Model (DEM) data in QGIS, an approach that came into play due to QGIS’s simple interface. By loading the area of interest through quick map services and employing the SRTM-downloader plugin, DEM 30m data was directly sourced from NASA Earthdata. I used the DEM data to establish a threshold. This method is a prediction of flood prone areas, given the level of water level rise. I looked for sources like news articles that reported the water level when the areas were flooded. I set that water level as the threshold using the raster calculator. By setting that threshold the algorithm gave the areas based on the elevation that would be inundated, if water level rises to a certain level.

Thresholding flood level from SRTM DEM data.

The second method I tried was using Sentinel-1 Synthetic Aperture Radar (SAR) data, which was available for the exact date when the flooding occurred in this area, using Google Earth Engine (GEE). 

I then analysed pixel values of water by comparing images before and during flooding. Applying a pixel value threshold allowed for identification of sudden changes indicative of flooding. I began by filtering the pre-flood and post-flood dates for the images for Mahad city. So, I had two SAR images: one before the flood and one when it was flooded. I checked the pixel values of the water bodies before the flood from various spots. This pixel value was then set as the threshold. Once I input the threshold and ran the code, GEE highlighted areas with sudden pixel value changes of water bodies in the after image, indicating flood, and those with no change were the existing water bodies. 

Pixel value change of the area marked in red from pre-flood to flood date in the Inspector display box.

The third threshold method I employed was for the Commonwealth Game Village area of Delhi. Initially, we hoped to depict actual visuals of the flooding in one of the areas using satellite imagery. However, demarcating the flood manually for the viewers to clearly differentiate between the pre and post-flood imagery was not possible because clear imagery was not available for the flood dates. When working with older satellite images dating back to 2010, we faced issues stemming from their low spatial resolution. This limitation arose because satellites with enhanced spatial resolutions were launched only after that time, in 2013. In order to show a similar situation, we searched for similar events in recent years and found images from 2022’s flood in Delhi. However, satellite images during the flood were still not useful because of the high cloud cover in them. So I had to look for images just after the flood event when the cloud cover was low but was still indicative of flood, as it takes time for the water to drain away. 

Initially I tried the same method as before, by using SAR data. However, it seemed to detect built up areas like roads instead of water. Therefore I switched to Sentinel-2 L2A data for this region. According to Bhangale et al., 2020 [1] and Lekhak et al., 2023 [2] band 8 (NIR) with band 3 (Green) of Sentinel-2 could be used to identify water bodies. I therefore used the band 8 from both the pre and post-flood images to detect inundation. I checked the pixel values from various spots and noted down an approximate minimum and maximum pixel value of the water body in the image before the flood. This range was then used to differentiate water from non-water areas in post-flood images. After noting the values, I classified this range of values into one category as water and rest as not-water. I similarly applied this step in the post flood image which gave me the change in the water bodies which are the areas that were inundated. 

Checking pixel values of water bodies from pre-flood images.

Setting threshold values to classify water and not-water.

Results after classification.

After applying all the three thresholding methods the question that arises is of their accuracy. While the first method that I applied was a prediction based on elevation and level of water, the other two methods were entirely based on satellite data. 

In the case of Mahad, the first method based on elevation seemed to match the level of inundation to some extent with the SAR output, as it predicted the major areas that were inundated. SAR data, as per existing studies, is widely used and considered appropriate, for detecting floods as it is unaffected by cloud cover. This is because unlike other optical satellite imagery it is able to differentiate land and water contrast easily. However, SAR data [3] can sometimes misclassify shadows of tarmac areas with buildings and roads as water. This issue became evident when I experimented with SAR data in the Delhi case. 

Presence of water bodies in Yamuna floodplain, pre- and post-flood.

On the other hand, Sentinel-2 data gave results similar to the SAR output where built-up areas were misclassified as water. Sentinel-2 data is affected by atmospheric conditions unlike SAR. The process of setting pixel values is more manual, which can be affected by individual judgement, potentially leading to underestimation or overestimation[2].

Sentinel-1 SAR data has been found to have more accuracy in detecting floods than Sentinel 2.  A study by Nhangumbe et al., 2023 [4] suggests combining both the data for attaining higher overall accuracy. 

Overall all three methods provided estimations of the major areas that were inundated or likely to be inundated, fulfilling the purpose of the issue that Mongabay-India wished to convey. Meanwhile, the scope for exploration and improvement remains open!

References

1. Bhangale, U., More, S., Shaikh, T., Patil, S., & More, N. (2020). Analysis of Surface Water Resources Using Sentinel-2 Imagery. Procedia Computer Science, 171, 2645–2654. (https://doi.org/10.1016/j.procs.2020.04.287)

2. Lekhak, K., Rai̇, P., & Budha, P. B. (2023). Extraction of Water Bodies from Sentinel-2 Images in the Foothills of Nepal Himalaya. International Journal of Environment and Geoinformatics, 10(2), 70–81.(https://doi.org/10.30897/ijegeo.1240074)

3. Rahman, Md. R., & Thakur, P. K. (2018). Detecting, mapping and analysing of flood water propagation using synthetic aperture radar (SAR) satellite data and GIS: A case study from the Kendrapara District of Orissa State of India. The Egyptian Journal of Remote Sensing and Space Science, 21, S37–S41. (https://doi.org/10.1016/j.ejrs.2017.10.002)

4. Nhangumbe, M., Nascetti, A., & Ban, Y. (2023). Multi-Temporal Sentinel-1 SAR and Sentinel-2 MSI Data for Flood Mapping and Damage Assessment in Mozambique. ISPRS International Journal of Geo-Information, 12(2), 53.(https://doi.org/10.3390/ijgi12020053)

Mapping port development in Karnataka

There are plans to build a set of ports along the coast of Karnataka, with potential impacts on both coastal communities and wildlife in the region. Independent journalist Supriya Vohra wrote a three-part story on this topic for Mongabay-India, and we prepared a set of maps to accompany these articles.

A visual representation of the 12 planned ports was unavailable; official government documents only contained details regarding the coordinates of the ports, and of the defined port limits.

An example showing the port limit descriptions for port Karwar in the Government document.

Eastern, northern, and southern limits of minor ports limits as defined by the Government, along the coast of Karnataka. Port limits for Tadri and Pavinakurve were unavailable.

For the first story, our task was to map one major and twelve minor ports of Karnataka. Descriptions from the Indian Hydrographic Charts for each port in the official notifications were used to map the port boundaries. The descriptions of the port limits were such that following the details, one could locate the cardinal directions. While the instructions for the northern, southern, and western boundaries were mostly straightforward, the eastern borders were somewhat complex as they went inland. So, obtaining a complete understanding of the descriptions was the necessary first step in creating the maps.

The next step consisted of downloading bathymetry data. Bathymetric data are depth contours of the sea floor. For most of the ports, coordinates were available for north and south directions in the description to estimate limits that fell in or around the shores. Lines from these points extended towards the west into the sea to the 30 metre contour line that forms the northern and southern boundary. The western limit is the line joining the northern and southern limits along the 30 metre contour line in the sea. As required, I mapped only the northern, southern, and western limits for all the ports, using the coastline of India as the eastern border. I downloaded the bathymetry data from GEBCO (General Bathymetric Charts of the Oceans) in GeoTIFF format. The other options for downloading the dataset are in 2D netCDF and ESRI ASCII raster format. The reason I chose the GeoTIFF format is simply because it is a more commonly used format. After importing the data to ArcGIS Pro, I created contours to locate the port limits. 

Locating Port Honnavar’s northern and southern points in Google Earth Pro.

For each port, I followed the description in the notification. I used Google Earth to locate the coordinate points. I used Google to search for a few landmarks in the descriptions first, as they were unavailable via either Google Earth or labelled base maps in ArcGIS Pro. After confirming the locations, I then marked the northern and southern points as described in Google Earth Pro and exported them to ArcGIS Pro in a .KML file format. It was only done for the northern and southern points, mostly because only these directions had landmarks or coordinates in their description. The western border would be the 30 metre contour line connecting north-south. Once I created the contours and located the coordinates for each port, I finally started digitising the port limits by connecting those points in ArcGIS Pro. The coordinates of the few ports marked on the map were sourced from the official Karnataka Port website and exported after locating it on Google Earth.

Map on the road connecting the ongoing Honnavar port project.

The second story focused on the proposed port at Honnavar, where a road of around four kilometres long is being constructed. The entire stretch is the fish-drying ground of the coastal communities, and part of the proposed road also cuts through forest land. The port area includes confirmed nesting sites for the vulnerable Olive Ridley turtle, and there are also a few nests close to the road. 
We were provided with the turtle nesting sites data, originally collected by the Honnavar Forest Department, while the boundaries of the proposed Honnavar port and road were available in .kml format from PARIVESH. Making this map was relatively straightforward, as most of the data were already available, and it just had to be combined and represented.

Turtle nesting sites (2015-2022) as per Honnavar Forest Department records.

The third story lists the discrepancy between the turtle nesting sites as reported by the Honnavar Forest Department, and that presented to the public by the National Centre for Sustainable Coastal Management (NCSCM). In brief, the NCSCM actually indicates that the turtle nesting sites are in the Arabian Sea; Olive Ridley turtles, like all sea turtles, nest on land. Our analysis indicates that the NCSCM made a very basic conversion error when converting latitude-longitude pair values from one format to another, which was not identified before publication of their report.

Creating these maps was exciting as well as challenging; the most difficult part was to create port boundaries from only the written descriptions of directions, locations and depths. By visualising the issues surrounding these developments, we hope for the best possible ethical outcome for these ecologically sensitive areas, and the human and wildlife communities resident in them. 

Using PARIVESH for effective conservation advocacy

The following article authored by Pakhi Das, Shashank Srinivasan, Nancy Alice, Ashwathy Satheesan, Nandini Mehrotra and Anand Srinivasan was first published as ‘The PARIVESH Portal: Pros, Cons And How To Use’ by Sanctuary Asia on 03rd August, 2022.

Until July 15, 2014, the process for any development project to obtain a green clearance in India involved several stages - the circulation of physical project files between different officials at multiple stages of approval. File access was limited to the government, the applicants seeking green clearances, and the authorities granting approvals. Moreover, the complex nature of clearance processes and the lack of accountability created a lack of trust in the process.

To remedy this and to ensure better transparency and efficiency in the clearance process, the Ministry of Environment, Forest and Climate Change (MoEFCC) has established the PARIVESH website.

PARIVESH stands for Pro-Active Responsive facilitation by Interactive and Virtuous Environmental Single-window Hub. It is a web-based, workflow application that has digitised the entire process of submission and monitoring of Environment, Forest, Wildlife, and Coastal Regulation Zone (CRZ) Clearance proposals submitted by proponents to the Central, State, and District Level authorities. The portal allows project proponents to register themselves and submit applications for various green clearances in digital formats. Although seemingly designed for project proponents, PARIVESH has become a valuable resource of collated information that is open for viewing by the general public.

There are currently more than 10,000 land-use proposals submitted for clearance at the MoEFCC in India, ranging from the construction of multi-state national highways to the establishment of small-scale cottage industries. Various government officers and committees are assessing the potential impact of these proposed projects before granting approval.

The Benefits

The PARIVESH website hosts an enormous amount of information about all old and new projects seeking green clearances, organised by state, year, category and stage of approval. The information comprises spatial data regarding the outlines of the project site location and alignment, the area of forest land being diverted, site inspection, and biodiversity assessment reports. Such information is of immense value for conservation and is freely available on the portal.

Using the appropriate search functions, project information concerning any given project is available for viewing or, in some cases, even downloading. The portal also hosts details of discussions of various expert committees through the agenda and meeting minutes, allowing people from outside the system to view and analyse the processes that ultimately affect India’s wildlife and environment. All the relevant information is presented as an application package with downloadable file attachments, which could prove beneficial for conservation research and advocacy. The quantity and variety of information on the portal make it a treasure trove for anyone and everyone interested in the green clearance space of India.

Information that can be found on the PARIVESH website about any development project in India:

1. Area sought for clearance
2. Project cost
3. Spatial information about project location in KML (Keyhole Markup Language) format, details of the land required for clearance such as forest division names, area of forest and non-forest land, village and district wise breakup of the total proposed land, etc.
4. Details of Project Proponent/User Agency
5. Cost Benefit Analysis undertaken
6. Status/links to associated environmental or wildlife clearance (if any)
7. Project plan/ feasibility reports/ site inspection reports

Non-user Friendly Interface

While introducing PARIVESH for digitising the green clearance process in India helps to bring about transparency and accountability in the system, the portal is not user-friendly and is cumbersome to navigate.

The system should be able to streamline important projects and allow easy access to relevant information however, most of the files are not appropriately tagged, making the search options unreliable. To be able to ‘find’ specific projects within a timeframe, the user must know specific project details such as the exact name of the project, project file number, and the clearance level.

Additionally, green clearances are complex processes and involve multiple levels of reviews and recommendations from various government departments. These processes are broadly divided into three clearance verticals, namely Environmental Clearance, Forests Clearance, and Wildlife Clearance. Each of these verticals has its own set of processes and organisation hierarchies that the project file must circulate through at the level of first the state and then the centre. In the instance that a user is able to trace the details of a particular project on the platform, comprehending what stage of approval that project could be at and what that stage of approval entails is a task in itself.

Problems with the PARIVESH website

1. Low Discoverability: Navigating through the PARIVESH portal is complicated as information is not organised uniformly across types/categories and sometimes even regarding regions.
2. Decision Fatigue: Because of the structure of the portal, too many steps are involved in obtaining a particular project’s information
3. Inappropriate Project Tagging: Proposals, projects or additional attached documents are not appropriately tagged, which makes finding them using the search function cumbersome.
4. Complexities of the Clearance Processes: The complexities of the clearance processes and organisational hierarchies make access to information additionally difficult. The portal does not describe the various stages of approval under different clearances.

How Can This Be Improved?

For effective conservation advocacy, knowledge of potential areas of intervention is crucial, which makes a clear understanding of what happens at each level of approval imperative.

Simple features, such as an option to view projects cumulatively across the clearance types, or to view projects on a spatial platform, would increase the efficiency of the portal manifold. The dashboards for different types/verticals of clearances use abbreviations for the stages of approval with no description of what those abbreviations stand for nor what each of those stages entails, thus creating a limitation in the understanding of the clearance procedures altogether. Furthermore, there is a lack of features that would allow users interested in specific projects to subscribe or receive notifications for any updates on the approvals.

PARIVESH, although perhaps designed for project proponents seeking clearances, has been a useful portal for other stakeholders. The inclusion of features such as these would revolutionise accessing vast amounts of publicly available data for all stakeholders and will allow them to be more involved.

To truly achieve the goal of increased transparency and efficiency in the green clearance process in India, providing better access to information is key. India has a growing population of aware citizens from an array of backgrounds and a better system would greatly empower them to play an active role in determining the future of the environment, forests, and wildlife of the country.

Flowchart illustrating an user agency’s process in PARIVESH.

How to Use PARIVESH: A step-by-step guide with tips

PARIVESH hosts a large volume of project information, which is of immense use for awareness, campaigning or advocacy. However, navigating the portal to get to relevant information often involves many steps. It is important to narrow down search to the farthest extent possible by applying relevant filters. One might also have to scan through multiple project forms and verify information from other media articles and web reports. However, if a project is cleared, it is mandatory for it to have gone through PARIVESH, and information about it must be available on the portal. Here's how to access this information.

Step 1: Make a list of all the known information about the project one is seeking information on

For example, let us do so for the Etalin Hydropower Project.

Critical known information about Etalin hydropower project
- State name: Arunachal Pradesh
- Area: Dibang Valley
- Project Proponent: Jindal Power Ltd.
- Category of Project: Hydroelectric/hydel
- Date proposed: Before 2016 (although not crucial, it is often helpful to review other existing information/media reports about the project of interest. Information such as the timeline of the project helps in narrowing down search)

Step 2: Explore PARIVESH Portal

Note: All projects proposed on PARIVESH are organised according to the type of clearance sought into three categories -- environment, forest and wildlife clearance.

To find information, each of these types can be explored independently. The following sections provide a step by step guide to navigating the portal.

For Forest Clearance
1. Open https://parivesh.nic.in/ homepage, scroll down and select ‘Forest Clearance’.

2. To view all forest clearance projects, select ‘Dashboard’ option on the header.

3. Once clicked dashboard, apply filters to narrow down search filters such as state, category and hit search.

Note: Projects under forest clearance on PARIVESH are organised in two categories - Stage I and Stage II. If the status of clearance of the project is known, lead search by that status. However, if this information is not known, explore both stages.

4. To view all Stage 1 projects, click on the ‘Form A part II, Under Stage I’ button on the dashboard. As seen below, there are a total of 12 hydel projects proposed in Arunachal Pradesh, which are currently under stage 1.

5. Click on ‘ACCEPTED’ (these are all the relevant projects according to the applied filters).

6. A dataset of all projects as per the chosen category will be displayed with unique project IDs, and other relevant information, which should allow one to review and identify the project of interest.

Things to note while trying to identify project of interest:
(i) Is the project proponent the same as known information? Eg. Jindal Power Ltd.
(ii) Is the forest division/area the same as known information? Eg. Dibang Valley.
(iii) Is the project proposed in the known timeline? Eg. 2015.

(Screen grab of all hydel projects in Arunachal as on May 5, 2022)

7. Each project has a corresponding form, which hosts information about the project.
To view this information and to recognise project of interest, click on magnifying glass icon under column titled ‘View Report on Allocation of Fresh Forest Land (Form-A) Part-I’

8. The Form A part I includes information such as the forest division details, area for clearance, spatial data, additional documents, etc. all in downloadable formats.

9. All the documents and the form itself can be downloaded as PDFs. It is important to note that until the project is granted final clearance, the proponents can make edits, add or delete files on the portal.

Note: The precedent blogpost on decoding and navigating PARIVESH can be read here.