Open source GIS tool for planning of water harvesting/recharging zones and appropriate structures in Indian cities

[SGCODEX]

Summary:

The "Open Source GIS Tool for Water Harvesting Planning in Indian Cities" aims to develop a user-friendly and accessible GIS tool to support sustainable water management in urban areas across India. The tool will empower urban planners, engineers, policymakers, and community stakeholders to identify suitable locations for water harvesting and design appropriate structures to harness rainwater effectively. By integrating geospatial data and advanced analytical capabilities, the tool will facilitate informed decision-making, optimize water harvesting strategies, and promote community participation in water conservation initiatives. Emphasizing openness, scalability, and user-centric design, the project seeks to foster collaboration, capacity building, and policy influence to address water scarcity challenges and promote resilience in Indian cities.

Goals

Enhancing water management in a city: Develop a tool that aids urban planners, engineers, and policymakers in identifying suitable locations for water harvesting and designing appropriate structures to optimize water resource management in Indian cities. Pick and choose one small city in India to pilot this tool. Gather all the requirements, like data satellite images, existing GIS tools for analysis etc and create a water rejuvenation plan of a city.

Increase sustainability in water management: Promote sustainable water management practices by facilitating the implementation of rainwater harvesting systems and other water conservation measures at the local level.

Improving accessibility: Ensure the tool is accessible to a wide range of stakeholders, including government agencies, municipal authorities, non-governmental organizations (NGOs), and community groups, regardless of their technical expertise or financial resources.

Context invariant and scalable: Design the tool to be scalable and adaptable to different urban contexts, ranging from smaller NACs to larger municipalities and across diverse geographical and climatic conditions in India.

User-Centric Design: Designing an intuitive and user-friendly interface that facilitates efficient decision-making and planning processes related to water harvesting.

Data Integration: Enable seamless integration of various geospatial datasets, including topography, land use, hydrology, drainage, percolation, lithology, lineament, watershed, slope, rainfall patterns, infrastructure networks, and population density, to provide comprehensive information for water harvesting planning and analysis.

GIS tool for governance in increasing the blue infrastructure at a city level. The tool gives a view of all the blue, grey, and green infrastructure, and city administrations or ward level governance can be established by using the tool to identify the appropriate zones, enhance recharging capacity, and incentivize the best locality for doing so.

Outcomes:

Identification of Suitable Water Recharging Zones: The GIS tool should enable users to identify potential areas for water harvesting structures/zones based on factors such as land use, terrain, slope, drainage, watershed, lineament, lithology, drainage, public infrastructure, topography, population density, and rainfall intensity, helping prioritize locations for intervention.

Optimized Design of Structures: Users will be able to design and optimize the layout and specifications of water harvesting structures, such as rooftop rainwater harvesting systems, check dams, percolation pits, recharge wells, drainage systems, and lakes, to maximize water yield and efficiency.

Risk Assessment and Mitigation: The tool will facilitate risk assessment and mitigation strategies for water harvesting projects by analyzing factors such as flood risk, groundwater contamination, and land use conflicts.

Decision Support: Provide decision support tools and scenario analysis capabilities to evaluate the effectiveness of different water harvesting strategies, compare alternative scenarios, and make informed decisions on investment priorities and resource allocation.

Acceptance Criteria

Functional GIS Tool: The GIS tool should be fully functional and capable of performing key tasks, like identifying suitable water harvesting zones and designing appropriate structures based on user inputs and geospatial data.
User Interface: The user interface should be intuitive, user-friendly, and accessible to users with varying levels of technical expertise. It should enable users to interact with the tool efficiently and effectively.
Data Integration: Relevant geospatial datasets, such as topography, land use, rainfall patterns, and hydrological data, etc should be successfully integrated into the tool to support analysis and decision-making related to water harvesting planning.
Accuracy and Reliability: The tool should produce accurate and reliable results, with minimal errors or discrepancies in the analysis and output generated.
Documentation: Comprehensive documentation, including installation instructions, user manuals, technical specifications, and data sources, should be provided to guide users in installing, configuring, and using the GIS tool effectively.
Testing: Thorough testing should be conducted to ensure the functionality, reliability, and usability of the GIS tool across different operating environments, datasets, and user scenarios.
Performance: The tool should demonstrate satisfactory performance in terms of speed, efficiency, and resource utilization, even when processing large datasets or complex analysis tasks.
Feedback Mechanism: Mechanisms for receiving feedback from users and stakeholders should be established to gather input on the tool's performance, usability, and effectiveness for continuous improvement.
Documentation of Process: The student should maintain documentation of the development process, including design decisions, challenges faced, solutions implemented, and lessons learned throughout the project.
Out of Scope
Large-Scale Deployment: The project's scope may not include the deployment of the GIS tool on a large scale across multiple cities or regions.
Customization for Every City: Customizing the GIS tool for every Indian city or region may be out of scope. The project may focus on developing a generic tool that can be adapted or customized by users based on their specific needs and local conditions.
User Training
Policy Development: The project may not involve the development of policy frameworks, guidelines, or regulations related to water harvesting in Indian cities.
Long-Term Maintenance and Support: While the project may include mechanisms for receiving feedback and making iterative improvements to the GIS tool, long-term maintenance and support beyond the duration of the project may be out of scope. Although online training resources would be provided and online support community would be nurtured
Implementation Details:

Requirement Gathering and Analysis:
User Requirements Analysis:

Scope out the requirements
Document functional and non-functional requirements.
Data Collection and Analysis:

Identify relevant geospatial data sources, such as topography, land use, rainfall, watersheds, infrastructure, etc that are relevant for identification of water harvesting zones.
Assess the quality, availability, and compatibility of data
Design Specification:

Develop a design specification document outlining system architecture, data models, and user interface design.
Development
Prototype Development:

Develop a prototype of the GIS tool, focusing on core functionalities.
Implement basic features for data visualization, spatial analysis, and user interaction.
Data Integration:

Integrate geospatial datasets into the GIS tool using appropriate data formats and protocols.
Develop data processing pipelines for data cleaning and analysis.
Algorithm Development:

Develop algorithms for identifying water harvesting zones and designing appropriate structures based on spatial analysis techniques.
Testing and Validating:
Unit Testing:

Conduct unit tests to validate individual components and functionalities of the GIS tool.
Integration Testing:
Test the integration of different modules and components to ensure interoperability and consistency.
User Acceptance Testing (UAT):

Engage stakeholders and end-users to conduct UAT sessions to validate the tool's usability and functionality.
Performance evaluation and Analysis report
Performance evaluation:

Evaluate the performance of the GIS tool in terms of speed, accuracy, and efficiency.
Benchmark against existing tools or methods for water harvesting planning.
Analysis report

Analyse and publish the report of identifying water rejuvenation zones in a small city in India
Mockups / Wireframes
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Product Name
DIGIT

Project Name
Open source GIS tool for planning of water harvesting zones and appropriate structures in Indian cities

Organization Name:
eGovernments Foundation

Domain
Public Services

Tech Skills Needed:
Creative and Innovative mindset
Proficient knowledge of Geographic Information Systems (GIS)
Programming Languages Python, JavaScript/Java
Spatial Database Management like PostGIS, SQLite etc
Data Integration and Analysis
UI/UX design skills for creating user-friendly interfaces
Documentation, Communication
Scalability and Performance Optimization
Security and Privacy Considerations

Mentor(s)
Aniket Talele

Complexity
High

Category
Feature

Sub Category
API, Frontend, Backend

[SGCODEX]

Weekly Learnings & Updates

Week 1

1. Prerequisites

• Learned about Geographic Information Systems (GIS) and it’s uses.
• Learned topics like GeoPandas, Rasterio, OpenCV, Mapbox, Google Maps API etc.
• Learned what shapefiles are (shp, zip, dbf, prj, shx, cpg, fix, qix, sbn ,shp.xml, osm)

Week 2

1. Satellite Images

• Selected Maputo, Mozambique as the place of interest to work upon
• Downloaded Satellite Images of the region using earthexplorer.usgs.gov and Google Earth Engine
• Learned about different types of Satellite Images, Sentinel Hub and Landsat.
• Still searching for better quality satellite panchromatic images to ease the building detection process in future. (Images in black and white or grayscale, often known as panchromatic images, record a wide range of wavelengths in a single channel and due to their great spatial resolution they are perfect for uses like urban planning where having precise information about infrastructure, roads and buildings is essential) Example - Landsat ETM+ PAN.

Week 3

1. Shape Files and Folium

• Learned about www.openstreetmap.org and started Downloading shape files of smaller regions (osm format)
• Learned and started working with QGIS software for processing and obtaining required features from the shape files (roads and routes).
• Delved deeper into Folium and Pandas for using maps in Google Colab.
• Started using their pre-built functions to work and process Satellite Images.

Week 4

1. Google Earth Engine and Water Sources

• Paused working with Folium for now, will visit it later to use more features.
• Started learning about Google Earth Engine (Code Editor and API)
• Started Pre-processing the satellite images for cloud removal, enhancing image quality and observing between a specific time periods.
• Started identifying Landsat Global Inland Water for identifying water sources for the GIS Tool using satellite data on Google Earth Engine - Code Editor

Week 5

1. Adding Shape Files and Household Estimation

• Due to less data on African Continent, started testing some things out for Delhi Region. Will make the same for Maputo.
• Defined a circular Region of Interest (ROI) around the lake with a radius of 1.5 Km. Users can define their own region of interest in any polygon shape as well.
• Using computer vision and Open Buildings V3 Polygons did building detections and household estimation in the region of interest. Assuming 3 people as average number of residents per household, calculated the estimated population.
• Found another dataset, which provides population density of regions. Calculated population density around the lake with the help of estimated population and area of region of interest. Compared this Calculated Population Density with Observed Population Density from the dataset. Final values of both Population Densities were almost comparable. Thus backing up our household estimation as well.

Week 6

1. Refining ROI and Household Estimation V2

• Refined Region of Interest for more accurate Household Estimation
• Used the shapefile of Delhi Wards 2022 to define a function to choose any ward as ROI and using the consensus data found out exact population of the ward selected. Thus did Household Estimation with number of buildings detected and actual population. Also the function finds out the area of the selected ward in sq km (almost equal to actual area of the ward). Also worked upon labels.
• Screenshots:
  

Week 7

1. Geemap and More Functionalities

• Learned in-depth about the Geemap Library.
• Working on converting the obtained functionalities from Code Editor to Python API in Google Colab using Geemap for African region – Maputo.
• Developing a Computer Vision model using Yolo and OpenCV for more precise building detection and route detection using shape files. Also, working on developing an algorithm to find shortest distance between two given points.
• Also, worked on refining the presentation and problem statement for Mid-Point Evaluation:
  

Week 8

1. Scope of the Project and Python Conversion

• Updated Issue Ticket content for more generalized project and not just working on “Planning of water harvesting/recharging zones and appropriate structures”
• Converted the main functionalities from Google Earth Engine to Python (Colab Notebook) using Geemap Library. Working on converting more features and incorporating Folium Library.

Week 9

1. Data Acquisition and Preparation

• Identified and collect relevant data on facilities (warehouses), road networks, and geographic information (latitude, longitude) in Delhi Region.
• Overlaid this data on the interactive map to help in planning the distribution routes and logistics.

Week 10

1. Shortest Distance/Path Algorithm Development

• Implemented a suitable algorithm using osmnx library to calculate the shortest distance between two given facilities based on their latitude and longitude.
• Route Optimization: Considered factors like road types and distance to be loaded to optimize the calculated route and give faster results.

Week 11

1. Network Visualization

• Allowed users to filter the network by type (all, all_public, bike, drive, drive_service, walk) and customize the visualization (e.g., color, thickness).
• Integrated osmnx part with geemap part.

Week 12

1. Application Development and Testing

• Developed code to handle user interactions, perform calculations, and update the visualization accordingly.
• Working on the front end part