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Blockchain and Land Registry

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Blockchain and Land Registry

Combining GIS (Geographic Information Systems) with blockchain technology can create powerful solutions for managing and sharing spatial data. Here are some key points about this integration:

Benefits of Integrating GIS and Blockchain

  1. Data Integrity and Security: Blockchain provides a tamper-proof and decentralized way of storing and sharing spatial data, ensuring data integrity and security.
  2. Transparency and Trust: Blockchain’s transparency allows all participants to access the same data, fostering trust among stakeholders.
  3. Efficient Data Sharing: The decentralized nature of blockchain can facilitate more efficient and secure sharing of geospatial data across different organizations and platforms.
  4. Enhanced Spatial Analysis: GIS tools can analyze and visualize the spatial data stored on the blockchain, providing valuable insights for decision-making.

Use Cases

  • Land Registry: Blockchain can be used to create immutable records of land ownership, reducing fraud and disputes.
  • Supply Chain Management: Combining GIS and blockchain can track the movement of goods, ensuring transparency and efficiency in the supply chain.
  • Disaster Management: Real-time spatial data on a blockchain can help in coordinating disaster response efforts more effectively.

Creating Custom Solutions

To create custom GIS and blockchain solutions for your projects, you can:

  1. Identify the Use Case: Determine the specific problem you want to solve with GIS and blockchain.
  2. Choose the Right Tools: Select appropriate GIS software (like ArcGIS or QGIS) and blockchain platforms (like Ethereum or Hyperledger).
  3. Develop Smart Contracts: Create smart contracts to automate transactions and data sharing on the blockchain.
  4. Integrate and Test: Integrate the GIS and blockchain systems and thoroughly test the solution to ensure it meets your requirements.

Using blockchain technology for land registry can revolutionize the way property ownership is recorded and managed. Here are some key points:

Benefits of Blockchain in Land Registry

  1. Enhanced Security: Blockchain provides a tamper-proof and decentralized ledger, making it extremely difficult for unauthorized parties to alter land records.
  2. Transparency: All transactions are recorded on a public ledger, which can be accessed by anyone, ensuring transparency and reducing the chances of fraud.
  3. Efficiency: Blockchain can streamline the land registration process by eliminating the need for intermediaries, reducing processing times and costs.
  4. Immutable Records: Once a transaction is recorded on the blockchain, it cannot be changed or deleted, ensuring the integrity of land records.

How It Works

  • Smart Contracts: These are self-executing contracts with the terms of the agreement directly written into code. They can automate the transfer of property ownership once certain conditions are met.
  • Decentralized Ledger: Each block in the blockchain contains details of a land transaction, such as property ID, owner details, transaction amount, and previous transaction history.
  • Cryptographic Security: Advanced encryption methods, like SHA-256, ensure that the data is secure and only accessible to authorized parties.

Use Cases

  • India: Several pilot projects are exploring blockchain for land registry to address issues like fraud, inefficiency, and lack of transparency in the current paper-based system.
  • Sweden: The Swedish Land Registry has tested blockchain technology to streamline property transactions and reduce the time required for land registration.

Challenges

  • Regulatory Hurdles: Implementing blockchain for land registry requires changes in existing laws and regulations.
  • Technical Barriers: Integrating blockchain with existing land registry systems can be technically challenging and requires significant investment.

Implementing blockchain for land registry in your country can be a transformative project. Here are the key steps to guide you through the process:

1. Assess the Current System

  • Evaluate Existing Infrastructure: Understand the current land registry system, including its strengths, weaknesses, and the technology in use.
  • Identify Pain Points: Determine the specific issues you aim to address with blockchain, such as fraud, inefficiency, or lack of transparency.

2. Choose the Right Blockchain Platform

  • Scalability: Ensure the platform can handle the volume of transactions expected.
  • Consensus Mechanism: Select a consensus mechanism (e.g., Proof of Work, Proof of Stake) that aligns with your security and efficiency needs.
  • Smart Contract Support: Opt for a platform that supports smart contracts to automate property transactions. Ethereum and Hyperledger are popular choices.

3. Develop Smart Contracts

  • Automate Transactions: Create smart contracts to handle property transfers, ensuring they comply with legal requirements.
  • Verification and Validation: Include mechanisms for verifying and validating transactions to maintain data integrity.

4. Integrate with Existing Systems

  • Data Migration: Plan for the migration of existing land records to the blockchain. This may involve digitizing paper records.
  • Interoperability: Ensure the blockchain system can interact with other government databases and systems.

5. Pilot Testing

  • Small-Scale Implementation: Start with a pilot project in a specific region to test the system and identify any issues.
  • Feedback and Iteration: Collect feedback from users and stakeholders, and make necessary adjustments before a full-scale rollout.

6. Legal and Regulatory Compliance

  • Update Legal Framework: Work with legal experts to ensure that the blockchain-based system complies with national laws and regulations.
  • Stakeholder Engagement: Engage with all relevant stakeholders, including government agencies, legal professionals, and the public, to ensure smooth adoption.

7. Training and Capacity Building

  • Educate Users: Provide training for government officials, legal professionals, and the public on how to use the new system.
  • Technical Support: Establish a support system to assist users with any technical issues.

8. Full-Scale Implementation

  • Gradual Rollout: Gradually expand the system to cover more regions, ensuring that any issues are addressed promptly.
  • Continuous Monitoring: Monitor the system continuously to ensure it operates smoothly and securely.

Case Studies

  • India: Several states in India are exploring blockchain for land registry to address issues like fraud and inefficiency.
  • Sweden: The Swedish Land Registry has successfully tested blockchain to streamline property transactions.

Implementing blockchain for land registry is a complex but rewarding process. 

GIS Day is on Wednesday, November 20, 2024

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GIS Day is on Wednesday, November 20, 2024

Every year, people worldwide celebrate GIS Day. This year, it’s happening on Wednesday, November 20, 2024.

But what’s GIS Day all about?

Let’s explore this special day dedicated to the awesome technology of Geographic Information Systems (GIS).

Countdown Timer

THE COUNTDOWN BEGINS

GIS DAY 2024

WEDNESDAY, NOVEMBER 20, 2024

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What is GIS Day?

GIS Day is a global event celebrating GIS technology. Ralph Nader came up with the idea to raise awareness about geography.

The first GIS Day took place on November 19, 1999, during Geography Awareness Week. The National Geographic Society, Association of American Geographers, and Esri worked together to make it happen.

Since 1987, the National Geographic Society has been organizing Geography Awareness Week every November. GIS Day usually takes place during this special week.

Why GIS Day is Cool

GIS is the tech that helps us understand "where." It helps us find the best place to build a wind farm, predict floods, or plan bus routes.

There are tons of cool things you can do for GIS Day 2024:

  • Geocaching: Use your GPS or phone to hunt for hidden treasures.
  • OpenStreetMap: Help map out your neighborhood or town.
  • Satellite Viewing: Use your phone or a telescope to spot satellites in the sky.
  • Google Earth: Travel the world from your computer.
  • Esri Story Map: Share what you're doing for GIS Day on social media.

How Will You Celebrate GIS Day?

GIS Day is a reminder of how important location is. What will you do to celebrate? Share your ideas in the comments below!

Coursera Free GIS Courses – Learn Essential GIS Skills

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Coursera Free GIS Courses – Learn Essential GIS Skills

Land Terminologies – پٹوار

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Land Terminologies – پٹوار

In Pakistan, land ownership and management are crucial aspects of rural life, overseen by local officials known as Patwaris. These village accountants play a vital role in maintaining accurate records of land parcels, documenting ownership details, and collecting land revenue. Each piece of land is identified by unique numbers called Khewat and Khasra numbers, which help in tracking ownership and boundaries within villages. Patwaris also keep records like Jama Bandi, which outline rights and responsibilities related to land use. They use tools like Fard (land ownership extracts) and Shajra Nasab (genealogical records) to verify ownership and inheritance patterns. This system ensures that land transactions and disputes are properly recorded and managed, contributing to the stability and organization of rural communities across Pakistan.

Land Measurement Calculator

Land Measurement Calculator

In this Calculator 1 karam is equal to 5 ft

  • Patwari: A village accountant responsible for maintaining land records and collecting land revenue.
  • Chak: A revenue estate or village.
  • Khewat (Khewat Number): A unique number assigned to a landholding or estate owned by an individual or family.
  • Khatauni: A record that lists the details of landholdings of individuals in a village.
  • Khasra (Khasra Number): A unique number assigned to a particular piece of land within a village.
  • Jama Bandi: The record of rights and revenue record for a particular area, detailing ownership and cultivation.
  • Girdawari: An agricultural land inspection report that records the details of crops and their cultivation.
  • Fard: An extract from the land record, often used to verify land ownership.
  • Lal Kitab: A detailed record book that includes maps and descriptions of land holdings.
  • Intkaal: Mutation of land, referring to the process of updating land records following a transfer of ownership.
  • Roznamcha Waqiati: A daily register maintained by the Patwari, noting occurrences and changes related to land and agriculture.
  • Shajra Nasab: A genealogical record showing the lineage and inheritance of land ownership.
  • Aks Shajra: A map or plan of a village showing the boundaries and layout of land parcels.
  • Acre: A unit of land measurement, commonly used for larger plots.
  • Kanal: A unit of land measurement equal to 1/8 of an acre.
  • Marla: A unit of land measurement, commonly used in urban and rural settings; 1 Kanal equals 20 Marlas.
  • Bigha: A traditional unit of land measurement varying by region, larger than a Kanal.
  • Murabba: A square plot of land, typically measuring 25 acres.
  • Chakbandi: The consolidation of fragmented landholdings to create larger, more efficient agricultural units.
  • Sajra: A map or plan showing the divisions of a village or a revenue estate.
  • Revenue Circle: An administrative unit for land revenue collection, comprising several villages or estates.
  • Tehsildar: A revenue officer in charge of a Tehsil (sub-district), overseeing the work of Patwaris.

These terms are integral to understanding land management, ownership, and agriculture in Pakistan, particularly within the traditional Patwari system.

Senior Manager, Data Visualization & GIS

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Senior Manager, Data Visualization & GIS
NEOM, Saudi Arabia

Job Description

Sector

NEOM Authority

OVERVIEW
PositionSenior Manager Data Visualization and GISJob Code  
Reports toSenior Manager Data Science and InnovationDirect ReportsN/A 
Division/SectionData and StatisticsDepartmentEconomics, Data and Statistics 
SectorEconomics, Data and StatisticsJob Family  
Role Purpose The Economics, Data and Statistics Sector is tasked to build a brand-new Statistics Office for NEOM in a greenfield environment in order to produce robust data and statistics about people, the economy and different sectors of interest. Building such a Statistics Office in a fully digitalized context offers unique opportunities to gain deep real-time statistical insights and take the production of official statistics to a level way beyond what is possible in legacy environments. We are seeking an experienced and talented Senior Manager for Data Visualization and GIS to lead the development and implementation of cutting-edge data visualization techniques and Geographic Information Systems (GIS) solutions. The successful candidate will play a critical role in transforming complex datasets into intuitive and insightful visualizations and maps, enabling informed decision-making and enhancing stakeholder understanding across various domains.  
KEY ACCOUNTABILITIES & ACTIVITIES
StatisticalData Visualization Lead the design and development of interactive and visually compelling data visualizations, dashboards, and reports using a variety of tools and technologies, such as Tableau, Power BI, D3.js, and others.Collaborate with cross-functional teams to gather requirements, define visualization objectives, and ensure alignment with business goals and user needs.Utilize advanced statistical techniques and data analysis methodologies to identify key insights and trends within datasets, and translate them into meaningful visual representations.Develop and maintain GIS databases, spatial datasets, and mapping applications to support spatial analysis, geospatial visualization, and decision-making processes.Design and implement custom GIS workflows and analytical models to address specific spatial analysis requirements and solve complex spatial problems.Conduct quality assurance checks and data validation processes to ensure the accuracy, reliability, and consistency of visualizations and GIS outputs.Stay up-to-date with emerging trends, best practices, and advancements in data visualization, GIS, and related technologies, and contribute to the continuous improvement of visualization techniques and tools.Communicate findings and insights effectively to diverse audiences through presentations, reports, and interactive demonstrations.
BACKGROUND, SKILLS & QUALIFICATIONS
Knowledge, Skills and ExperienceMinimum of 8 years of professional experience in data visualization, GIS analysis, or a related field, with a strong portfolio demonstrating expertise in creating compelling visualizations and GIS applications.Proficiency in data visualization tools such as Tableau, Power BI, or D3.js, and experience with GIS software such as ArcGIS, QGIS, or similar platforms.Solid understanding of statistical analysis techniques, spatial analysis concepts, and geospatial data processing methods.Strong programming skills in languages such as Python, JavaScript, or R for data manipulation, scripting, and automation tasks.Excellent design sensibility and attention to detail, with the ability to create aesthetically pleasing and user-friendly visualizations and maps.Proven ability to manage multiple projects simultaneously, prioritize tasks effectively, and deliver high-quality results within tight deadlines.Excellent communication and interpersonal skills, with the ability to collaborate effectively with multidisciplinary teams and communicate complex concepts to diverse audiences.
QualificationsBachelor’s or Master’s degree in geography, GIS, computer science, data science, or a related field with a focus on data visualization and spatial analysis.
COMMUNICATION – MAIN STAKEHOLDERS
InternalExternal
Senior Managers within the NEOM AuthoritySenior Managers within the NEOM CompanyDirectors from relevant Departments of NEOM regions  General Authority for Statistics (GASTAT)Saudi Authority for Data and Artificial Intelligence (SDAIA)Ministries and Institutions in Saudi ArabiaProject Management ConsultantsExternal Stakeholders of official statisticsAcademiaInternational Statistics Experts

Top 15 Python Libraries for GIS

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Top 15 Python Libraries for GIS

Python Libraries for GIS and Mapping

Python libraries are great tools for GIS because they help you do a lot more with it. Using Python libraries, you can go beyond the basics of GIS and explore more advanced data science. Today, we’re focusing on Python libraries in GIS. What are the most popular Python packages that GIS professionals use? Let’s find out!

First, why use Python libraries for GIS?

Have you ever needed GIS to do something it just can’t do? No GIS software can do everything, but Python libraries can add those missing features.

A Python library is basically code written by someone else to help make our lives easier. Developers have made open libraries for things like machine learning, reporting, graphing, and more in Python.

If you want these extra features, you can use these libraries by adding them to your Python script. Then, you can use functions that aren’t normally part of your GIS software.

Python Libraries for GIS

If you were to create a dream team of Python libraries for GIS, this would be it. These libraries help you do much more than just manage, analyze, and visualize spatial data. That’s what a Geographic Information System is all about!

  1. Arcpy

If you use Esri ArcGIS, you’ve probably heard of the ArcPy library. ArcPy is designed for geoprocessing operations. It helps with not just spatial analysis, but also data conversion, management, and map production in Esri ArcGIS.

  1. Geopandas

Geopandas is like pandas for GIS. Instead of just regular data analysis, Geopandas adds a geographic element. For overlay operations, Geopandas uses Fiona and Shapely, which are other Python libraries.

  1. GDAL/OGR

The GDAL/OGR library helps convert between different GIS formats and extensions. Almost all GIS software, like QGIS, ArcGIS, ERDAS, ENVI, and GRASS GIS, use it for this purpose. Right now, GDAL/OGR supports 97 vector and 162 raster drivers.

  1. RSGISLib

The RSGISLib library has tools for remote sensing and raster analysis. It can classify, filter, and do statistics on images. One of the coolest features is its module for object-based segmentation and classification (GEOBIA).

  1. PyProj

The main job of the PyProj library is to work with spatial referencing systems. It can project and transform coordinates using different geographic reference systems. PyProj can also do geodetic calculations and measure distances for any given datum.

Python Libraries for Data Science

Data science helps us understand data by finding insights. It takes data and makes sense of it, like by creating graphs or using machine learning. Here is a list of Python libraries that can help you do this.

  1. NumPy

Numerical Python (NumPy) helps you organize your data into a structured array, making it faster for scientific computing. It’s great because it works well with other Python libraries like SciPy for complex statistical operations.

  1. Matplotlib

When you have lots of data points, sometimes the best way to understand them is to plot them out. Matplotlib is a library that helps you create graphs, charts, and maps. It’s good at handling even large amounts of data.

  1. Pandas

The Pandas library is very popular for handling data. It’s not just for statisticians; it’s useful for GIS too. Pandas is great because its data frames are optimized to work with big data, much more efficiently than something like Microsoft Excel.

  1. Re (Regular Expressions)

Regular expressions (Re) are a powerful tool for searching and filtering text in your data. You can use it to find, detect, extract, and replace specific patterns in your tables.

  1. ipyleaflet

If you want to create interactive maps, ipyleaflet is a combination of Jupyter notebook and Leaflet. It lets you customize maps, load basemaps, geojson, and widgets, and choose from various map types like choropleth and side-by-side views.

  1. ReportLab

ReportLab is great for creating detailed reports. GIS often lacks good reporting capabilities, but with ReportLab, you can create custom report templates. It’s a valuable tool that deserves more attention.

  1. Folium

Like ipyleaflet, Folium helps you make interactive web maps using Leaflet. You can manipulate your data in Python and then visualize it with this open-source JavaScript library.

  1. Geemap

Geemap is used for scientific data analysis with Google Earth Engine (GEE). Scientists and researchers use it to explore the huge catalog of satellite imagery in GEE for remote sensing applications.

  1. LiDAR

The LiDAR Python Package is for processing and visualizing LiDAR data. It includes tools to smooth, filter, and extract properties from digital elevation models (DEMs). It’s useful for terrain and hydrological analysis.

  1. Scikit

Machine learning is very popular right now, and Scikit is a Python library that makes it possible. Built on NumPy, SciPy, and Matplotlib, Scikit is great for data mining, classification, and making predictions with machine learning.

The Python Libraries All-Star Team

These are the Python libraries we think are the best for GIS and data science. Now it’s your turn. If you could build an all-star team of Python libraries, which ones would you choose? Let us know in the comments below!

PRO TIP:

If you want a simple list of functions for Python libraries, take a look at DataCamp’s Cheat Sheets.

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