I thought I was going to get out in front of all the ChatGPT for GIS discussion for the New York State GIS community, but that turned out to be off by a magnitude of sorts.  YouTube is already replete with ChatGPT for GIS tutorials and if we wait until next week there will probably be another ChatGPT alternative.  (I found the Matt Forrest YouTube video a good ChatGPT for GIS intro – actually formed a question after one of his examples).  Even Amazon jumped into the frey recently with their Amazon Bedrock option.  Take your pick, Bing Chat, Chatsonic, YouChat, Google Bard (available via a waiting list) and a whole host of others on the market in 2023. 

No, the robots aren’t taking over and I suspect we won’t see any of the early Terminator Cyberdyne Systems androids applying for your local GIS Analyst position anytime soon – though it might be a solution for those long dreadful digitizing jobs in the cart lab.  One way or another, Chatbot AI technology is definitely here to stay, evolve, and become another piece of the geospatial toolbox.  

Nothing specific or implied in any the questions.  Just random chains of thought though it does take a little getting used to putting the questions together vs. a basic Google search.  And it does seem to help to refresh and ask the same question twice – or even three times – to get more detailed results.  Never was a programmer, so a little short on questions in that space.

A lot here.  Actually 17 questions in all.  Straight copy and paste. Skim through as you want – find a topic/question you might be interested in.  There are tons more which could have been included.

Without any further adieu, my first machine interview: 

eSpatiallyNewYork:  What freshwater fish datasets are best for mapping fish population based on water depth in the Great Lakes?

ChatGPT:  There are several freshwater fish datasets that can be useful for mapping fish populations based on water depth in the Great Lakes. Here are a few options:

1. Great Lakes Acoustic Telemetry Observation System (GLATOS) – This dataset provide information on the movements and behaviors of tagged fish in the Great Lakes.  It includes data on depth, temperature, and location, which can be used to create maps of fish populations based on water depth.
2. Great Lakes Fishery Commission (GLFC) – The GLFC maintains a database of fish populations in the Great Lakes.  This dataset includes information on fish specifies, size, and location, which can be used to map fish population based on water depth.
3. Great Lakes Environmental Database (GLENDA) – GLENDA is a comprehensive database of environmental data for the Great Lake region.  It includes information on water depth,  temperature, and environmental factors that can be used to map fish populations.
4. USGS Great Lakes Science Center – The USGS Great Lakes Science Center conducts research on fish populations in the Great Lake and maintains a database of fish surveys.  This dataset includes information on fish species, abundance, and location which can be used to map fish populations based on water depth.

Ultimately, the best freshwater fish dataset for mapping fish populations based on water depth in the Great Lakes will depend on the specific research question and the type of analysis being conducted.

eSpatiallyNewYork:  To what degree of accuracy can I map features from New York State orthophotography?

ChatGPT:  The degree of accuracy with which you can map features from New York State orthophotography depends on various factors such as the resolution of the imagery, the accuracy of the ground control points used for georeferencing, and the skill and expertise of the analyst.

New York State orthophotography typically has a resolution ranging from 0.5 to 1 meter, which means that individual features such as buildings, roads, and other infrastructure can be identified and mapped with a reasonable level of accuracy. However, mapping smaller features such as individual trees, shrubs, or small structures may be more challenging, as these features may not be visible at this resolution.

The accuracy of mapping also depends on the quality of the georeferencing. The accuracy of the ground control points used for georeferencing should be of a similar or higher resolution than the orthophotography itself. This ensures that the imagery is correctly aligned with the ground, allowing for accurate measurements and mapping.

The skill and expertise of the analyst are also critical factors in the accuracy of mapping features from orthophotography. A trained analyst with experience in image interpretation and feature extraction techniques can accurately identify and map features with a high degree of accuracy.

Overall, mapping features from New York State orthophotography can provide a reasonable degree of accuracy for larger features such as buildings, roads, and other infrastructure. However, mapping smaller features may require higher resolution imagery or other sources of data. It is always important to validate and verify the accuracy of the mapping results through ground truthing and other quality control measures.

 

eSpatiallyNewYork:  How does the replacement of the North American Datum of 1983 (NAD83) with the new North American Terrestrial Reference Frame (NATRF2022) impact my legacy GIS program?

ChatGPT:  The replacement of NAD83 with NATRF2022 could potentially impact your legacy GIS program, depending on how it was designed and implemented.

NATRF2022 is a new geodetic reference system that incorporates new technology and updated data to more accurately represent the Earth’s surface. It is designed to replace NAD83 as the standard reference frame for North America.

If your GIS program relies on NAD83 for spatial reference and coordinate system, you may need to update it to support NATRF2022 to ensure that your data is correctly aligned with the new reference frame.

If your GIS program is designed to support multiple reference frames, it may already be compatible with NATRF2022 or may require a software update to add support for it.

It’s worth noting that many GIS software providers have already started to support NATRF2022, so it’s possible that your program may already be compatible. However, it’s always best to check with your software provider or consult the documentation to confirm compatibility and determine whether any updates or changes are required.

eSpatiallyNewYork:  I am a new geospatial programmer and developer.  What are the best uses for the following languages:  Pandas, GeoPandas, Shapely, ArcPy and Fiona?

As a new geospatial programmer and developer, understanding the best uses for different programming languages and libraries is important. 

Here are some common use cases for the following languages and libraries:

Pandas: Pandas is a powerful library for data manipulation and analysis. It is commonly used for handling tabular data, such as CSV files, Excel spreadsheets, and SQL databases. It can be used for cleaning and filtering data, computing statistics, and creating visualizations.

GeoPandas: GeoPandas is an extension of Pandas that adds support for geospatial data. It provides tools for working with vector data, such as shapefiles and GeoJSON files. GeoPandas can be used for tasks such as spatial joins, buffering, and spatial queries.

Shapely: Shapely is a library for working with geometric objects in Python. It provides support for creating and manipulating points, lines, and polygons. Shapely can be used for tasks such as calculating area, distance, and intersection between geometric objects.

ArcPy: ArcPy is a Python library for working with Esri ArcGIS software. It provides access to the full range of ArcGIS tools, including geoprocessing, spatial analysis, and map automation. ArcPy can be used for tasks such as creating new layers, performing spatial analysis, and automating map production.

Fiona: Fiona is a Python library for working with vector data in a variety of formats, including shapefiles, GeoJSON files, and other OGR-compatible formats. Fiona provides a simple interface for reading and writing vector data, and can be used for tasks such as data conversion, feature extraction, and spatial analysis.

Overall, these libraries are well-suited to different aspects of geospatial programming and development. Pandas and GeoPandas are useful for working with tabular and vector data, respectively, while Shapely provides tools for geometric manipulation. ArcPy is a powerful library for working with Esri ArcGIS software, while Fiona provides a more general-purpose solution for working with vector data in a variety of formats.

eSpatiallyNewYork:  I need to tell a local surveyor our GIS program is just as accurate as their company’s.  What should I tell him/her?

ChapGPT:  When speaking with a local surveyor about the accuracy of your GIS program, it is important to emphasize the steps taken to ensure the accuracy and reliability of the data. Here are some points you can make:

1. Data Standards: Your GIS program has established data standards for data collection and formatting to ensure data quality, consistency, and interoperability across departments and agencies.
2. Quality Assurance: Your GIS program has implemented quality assurance procedures to ensure that data is accurate and reliable, including validation and verification of data.
3. Expert Staff: Your GIS program is managed and maintained by expert staff who are trained in GIS technology and data analysis.
4. Precision Technology: Your GIS program utilizes precision technology such as GPS and satellite imagery to capture and process data with high accuracy.
5. Alignment with Standards: Your GIS program follows industry standards such as the National Spatial Data Infrastructure (NSDI) and Federal Geographic Data Committee (FGDC) to ensure data accuracy and reliability.

By highlighting these points, you can assure the local surveyor that your GIS program is just as accurate as their surveying work and can be relied upon for making informed decisions based on spatial data. It is important to maintain open communication and collaboration with surveyors and other stakeholders to ensure that GIS data is used appropriately and in conjunction with other sources of information.

eSpatiallyNewYork:  How do NextGen E-911 systems integrate Geographic Information Systems technology (GIS)?

ChatGPT:  NextGen E-911 systems integrate Geographic Information Systems (GIS) technology by leveraging geospatial data to improve emergency response accuracy and efficiency. Here are some ways that GIS technology can be integrated into NextGen E-911 systems:

Call routing: GIS data can be used to route emergency calls to the appropriate public safety answering point (PSAP) based on the location of the caller. By using GIS data, NextGen E-911 systems can route calls based on geographic boundaries, such as city or county boundaries, to ensure that emergency calls are answered by the correct PSAP.

Location validation: GIS data can be used to validate the location of a caller, helping emergency services to respond more quickly and accurately. This can include using location-based services to determine the precise location of a caller, or verifying the address of the caller using GIS data.

Resource allocation: GIS data can be used to optimize emergency response by identifying the location of emergency services resources, such as fire stations, police stations, and hospitals. This can help emergency responders to identify the closest available resources to a given emergency location, improving response times and saving lives.

Situational awareness: GIS data can be used to provide real-time situational awareness to emergency responders, allowing them to visualize the location of an emergency incident and the resources available to respond to it. This can help emergency responders to make informed decisions and respond more effectively to emergency situations.

Overall, the integration of GIS technology into NextGen E-911 systems can help to improve emergency response times, reduce errors, and save lives.

eSpatiallyNewYork:  My organization is considering bare earth Lidar data capture for approximately 30-square miles in our county. Based on current technology standards and capabilities, is this a project that can be accomplished by using Unmanned Aircraft Systems (UAS), aka drones, or conventional fixed-wing aerial data capture?

Both unmanned aircraft systems (UAS) and conventional fixed-wing aerial data capture can be used for bare earth Lidar data capture. However, the choice of technology will depend on a number of factors, including the size and complexity of the area to be surveyed, the desired resolution and accuracy of the data, and regulatory and safety considerations.

UAS platforms have several advantages for Lidar data capture, including the ability to fly at lower altitudes and capture higher-resolution data, as well as the flexibility to navigate through complex terrain and obstacles. However, UAS platforms have limitations in terms of flight time, payload capacity, and operational range. In addition, UAS operations are subject to Federal Aviation Administration (FAA) regulations, which can restrict flight in certain areas and require special permits and certifications.

Conventional fixed-wing aircraft, on the other hand, have longer flight times, larger payload capacities, and greater operational range, making them better suited for larger survey areas. Fixed-wing aircraft also have higher cruising speeds, which can reduce the total survey time. However, fixed-wing aircraft typically fly at higher altitudes than UAS platforms, which can result in lower resolution data.

Ultimately, the choice of technology will depend on a careful analysis of the specific requirements and constraints of the project. It may be beneficial to consult with a geospatial service provider or aerial surveying company to determine the most appropriate technology and approach for your project.

eSpatiallyNewYork:  What are the pros and cons of GISP Certification?

ChatGPT: GISP certification (GIS Professional Certification) is a voluntary certification program for GIS professionals that was developed by the GIS Certification Institute (GISCI). The program is designed to establish and promote professional practice standards and recognize individuals who have met certain qualifications and experience criteria. Here are some of the pros and cons of GISP Certification:

Pros:

Demonstrates Professional Competency: GISP Certification demonstrates that an individual has met certain professional standards and has demonstrated a level of knowledge and expertise in the field of GIS.

Industry Recognition: GISP Certification is recognized by many employers, government agencies, and other organizations as a standard of professional competence in GIS.

Career Advancement: GISP Certification can enhance career advancement opportunities by demonstrating professional expertise and dedication to the field.

Networking: GISCI provides opportunities for GISP-certified professionals to network with other GIS professionals and to participate in professional development opportunities.

Cons:

Cost: GISP Certification can be expensive, with application fees, examination fees, and ongoing maintenance fees required.

Limited Recognition: While GISP Certification is recognized in the GIS industry, it may not be widely recognized outside of the industry or in other countries.

Ongoing Requirements: GISP Certification requires ongoing maintenance and continuing education to remain active, which can be time-consuming and costly.

Lack of Consistency: Some critics of GISP Certification argue that it lacks consistency in terms of qualifying requirements, exam content, and professional standards.

Overall, GISP Certification can be a valuable credential for GIS professionals who want to demonstrate their expertise and commitment to the field. However, it’s important to carefully consider the costs and benefits before deciding to pursue certification.

eSpatiallyNewYork:  How is lidar data used in the building of interior 3D models?

ChatGPT:  Lidar (Light Detection and Ranging) data can be used in the building of interior 3D models in several ways. Lidar is a remote sensing technology that uses laser pulses to measure distances and create 3D point clouds of the environment. Here are some ways lidar data is used in the building of interior 3D models:

Point Cloud Generation: Lidar data can be used to generate a point cloud of the interior environment. This point cloud can be used as a basis for creating a 3D model of the space. The point cloud contains millions of points that accurately represent the surfaces and features of the environment.

Feature Extraction: Lidar data can be used to extract features such as walls, floors, ceilings, and furniture from the point cloud. These features can be automatically identified and classified using algorithms that analyze the shape, size, and location of the points.

Modeling: The extracted features can be used to create a 3D model of the interior space. The model can be textured and rendered to create a realistic visualization of the environment.

Analysis: Lidar data can be used to perform analysis of the interior space, such as calculating the volume of a room, identifying potential hazards or obstacles, or optimizing the layout of furniture and equipment.

Overall, lidar data provides a highly accurate and detailed representation of the interior environment, which can be used to create precise and realistic 3D models. This technology is particularly useful in industries such as architecture, engineering, construction, and facility management.

eSpatiallyNewYork:  What GIS software packages and datasets would be helpful in reading New York State satellite imagery data, analyzing it for flooded areas, and determining impacts to vulnerable populations particularly in the New York City area?

ChatGPT:  To analyze New York State satellite imagery data for flooded areas and determine impacts to vulnerable populations, particularly in the New York City area, the following GIS software packages and datasets can be helpful:

GIS software packages:

ArcGIS: This is a widely used GIS software package that has a range of tools for working with satellite imagery data. It has tools for image classification, change detection, and spatial analysis, which can be used to identify flooded areas and determine impacts to vulnerable populations.

QGIS: This is a free and open-source GIS software package that has a range of tools for working with satellite imagery data. It has tools for image processing, analysis, and visualization, which can be used to identify flooded areas and determine impacts to vulnerable populations.

Google Earth Engine: This is a cloud-based platform that allows for the analysis of large amounts of satellite imagery data. It has tools for image processing, analysis, and visualization, which can be used to identify flooded areas and determine impacts to vulnerable populations.

Datasets:

FEMA Flood Insurance Rate Maps: These maps show areas that are at high risk of flooding due to coastal storm surges, river flooding, and heavy rainfall. They can be helpful for identifying areas that are most vulnerable to flooding.

NYC Hurricane Evacuation Zones: These zones are based on flood risk and can be used to determine which areas of New York City are most vulnerable to the impacts of a hurricane.

Census Bureau American Community Survey: This survey provides demographic data for neighborhoods across the United States, including information on income, age, disability status, and other factors that can affect vulnerability to flooding.

Environmental Protection Agency EJSCREEN: This is a mapping and screening tool that provides access to data on environmental indicators and demographic factors. It can be used to identify areas that are most vulnerable to the impacts of flooding.

It’s important to note that working with satellite imagery data can be complex and requires specialized knowledge and skills. You may want to consider consulting with a GIS professional or taking a training course to ensure that you are using the software packages and datasets correctly and effectively.

eSpatiallyNewYork:  How can I use GitHub code and resources to help build an open source interactive web mapping application?

ChatGPT:  GitHub is an excellent platform for sharing and collaborating on open source projects, including interactive web mapping applications. Here are the general steps you can follow to use GitHub code and resources to help build your application:

Search for relevant repositories: Use the GitHub search feature to find repositories related to web mapping applications. You can use keywords like “web mapping,” “interactive maps,” or “GIS” to narrow down your search.

Explore the code and resources: Once you find relevant repositories, take some time to explore the code and resources available. Look for examples of how to implement features and functionality you need in your own application.

Fork a repository: If you find a repository that has code and resources that are useful for your project, you can fork the repository to make a copy of it in your own GitHub account. This will allow you to modify the code and resources to meet your needs.

Customize the code and resources: Once you have forked a repository, you can customize the code and resources to fit your specific needs. You can modify the code to include your own data, change the look and feel of the application, and add new features.

Test and deploy: Once you have customized the code and resources, you can test your application to make sure it works as expected. You can then deploy the application to a hosting service like GitHub Pages or Heroku to make it publicly accessible.

Contribute back: If you make improvements to the code and resources you used from other repositories, consider contributing those changes back to the original repository as a pull request. This will help the broader community benefit from your contributions and help ensure that the original repository stays up-to-date with the latest improvements.

By following these steps, you can use GitHub to help build an open source interactive web mapping application and contribute to the broader community of developers working on similar projects.

eSpatiallyNewYork:  What are the most accessible open source New York State business directories which include business type and address?

ChatGPT:  There are several open-source business directories that include business type and address information for businesses in New York State. Here are a few examples:

OpenStreetMap: OpenStreetMap (OSM) is a collaborative, open-source mapping platform that provides detailed information on businesses, including business type and address. OSM is constantly updated by its community of contributors, making it a reliable source of information.

New York State Open Data Portal: The New York State Open Data Portal provides access to a variety of datasets, including a directory of businesses registered in New York State. The dataset includes business names, addresses, and industry classifications.

OpenDataSoft: OpenDataSoft is a data portal that provides access to a wide range of open data, including business directories. The platform allows users to search for businesses by location and industry classification.

Socrata Open Data Portal: Socrata is a cloud-based platform that provides access to a variety of open data, including business directories. The platform allows users to filter businesses by location, industry, and other attributes.

It’s important to note that while these directories are open-source and accessible, they may not be completely comprehensive or up-to-date. It’s always a good idea to verify information with the businesses themselves or with other sources.

eSpatiallyNewYork:  I  need to inform my supervisor what the key components of a GIS for local government.  What are they?

ChatGPT:  Building a successful Geographic Information System (GIS) program for local government involves several key components, including

1. Define Objectives: First and foremost, it is important to define the objectives and goals of the GIS program. This will help guide the development and implementation of the program and ensure that it meets the needs of the community.
2. Develop Data Standards: Standardizing data collection and formatting is essential for ensuring data quality, consistency, and interoperability. It is important to establish a set of data standards that will be followed by all departments and agencies that will use the GIS program.
3. Acquire and Organize Data: Acquiring and organizing data is a critical step in building a GIS program. This may involve gathering data from various sources, such as aerial imagery, survey data, and existing GIS layers. Data must be organized in a way that is easily accessible, and should be regularly updated and maintained.
4. Establish Infrastructure: A GIS program requires a robust technical infrastructure to support data storage, processing, and analysis. This may include hardware, software, and network infrastructure, as well as dedicated GIS staff to manage and maintain the system.
5. Provide Training and Support: It is important to provide training and support to staff and stakeholders who will use the GIS program. This may include providing access to training resources, such as online tutorials and workshops, as well as ongoing technical support.
6. Develop Applications: Developing GIS applications can help to make data more accessible and usable for staff and the public. This may include creating web-based applications that allow users to view and analyze data, or developing custom applications to meet specific departmental needs.
7. Promote the Use of GIS: Finally, promoting the use of GIS across departments and agencies can help to build support for the program and ensure its long-term success. This may involve creating a GIS advisory committee, conducting outreach and education campaigns, and highlighting success stories and use cases.

eSpatiallyNewYork:  What are the most popular add-on tools which can be used to increase the spatial accuracy of mapping with cell phones?

ChatGPT:  There are several popular add-on tools that can be used to increase the spatial accuracy of mapping with cell phones. Here are some of them:

External GPS Receiver: Using an external GPS receiver can significantly increase the spatial accuracy of mapping with cell phones. External GPS receivers can provide centimeter-level accuracy, which is much higher than the built-in GPS of most cell phones. Some popular external GPS receivers include the Trimble R1, Bad Elf Surveyor, and Garmin GLO.

Bluetooth Rangefinders: Bluetooth rangefinders can be used to measure distances and improve the accuracy of mapping with cell phones. These devices can be used to measure the distance from the cell phone to a specific point or object, which can then be used to calculate the coordinates of that point. Some popular Bluetooth rangefinders include the Leica DISTO and Bosch GLM.

GNSS Corrections: Global Navigation Satellite System (GNSS) corrections can be used to improve the accuracy of GPS positioning. GNSS correction services such as Real-Time Kinematic (RTK) and Post-Processing Kinematic (PPK) can provide centimeter-level accuracy for mapping with cell phones. Services such as Trimble Catalyst and Eos Arrow provide these correction services.

Photogrammetry Apps: Photogrammetry apps can be used to create 3D models and accurate maps from aerial images captured with cell phones. These apps use advanced algorithms to calculate the position and orientation of the camera and can provide high-resolution, accurate maps. Some popular photogrammetry apps include DroneDeploy, Pix4D, and Agisoft Metashape.

By using these add-on tools, you can increase the spatial accuracy of mapping with cell phones and create more accurate and reliable maps. It is important to consider the specific needs of your project and select the appropriate tools to ensure the highest level of accuracy.

eSpatiallyNewYork:  How do I explain to New York elected officials the spatial accuracy differences between the U.S. Census Bureau TIGER files and local tax maps?

ChatGPT:  To explain the spatial accuracy differences between the U.S. Census Bureau TIGER files and local tax maps to New York elected officials, you can use the following points:

Purpose and Methodology: The U.S. Census Bureau’s TIGER files are designed to provide a standardized spatial framework for conducting the decennial census, redistricting, and other statistical and administrative purposes. They are derived from a variety of sources, including aerial photography, satellite imagery, and other data, and are processed using automated algorithms to create the final product. Local tax maps, on the other hand, are typically created by local governments for tax assessment purposes and are based on more detailed surveys and measurements of property boundaries and features.

Accuracy and Precision: TIGER files are designed to provide a broad level of spatial accuracy and precision, suitable for statistical and administrative purposes. However, they may not accurately represent the precise location and shape of features such as property boundaries, building footprints, or other infrastructure. Local tax maps, on the other hand, are typically based on more detailed surveys and measurements, and may provide a higher level of accuracy and precision for specific features.

Updates and Maintenance: TIGER files are updated on a regular basis by the U.S. Census Bureau, typically every 10 years or more frequently for certain geographic areas. Local tax maps are typically updated by local governments on a more frequent basis, such as annually or biannually. This means that local tax maps may provide more up-to-date information on changes to property boundaries, infrastructure, and other features.

Integration and Compatibility: TIGER files are designed to be compatible with a wide range of GIS software and applications, making them easier to integrate and use in various spatial analysis and mapping projects. Local tax maps may not be as widely compatible, as they are typically designed for specific tax assessment purposes and may not be readily available in a digital format or compatible with standard GIS software.

Overall, it is important to recognize that both TIGER files and local tax maps have their strengths and limitations, and that the appropriate choice of data depends on the specific application and analysis being conducted. By understanding these differences, New York elected officials can make informed decisions about the use of spatial data in their work.

eSpatiallyNewYork:  What are the pros and cons of an organization adopting and using Open Source GIS software?

Open Source GIS software has become increasingly popular in recent years. Here are some of the pros and cons of an organization adopting and using Open Source GIS software:

Pros:

Cost-effective: Open Source GIS software is often free to use and distribute, which can significantly reduce licensing and maintenance costs.

Customizable: Open Source GIS software can be customized to meet specific needs and can be adapted to different types of projects.

Community Support: Open Source GIS software is often supported by a large community of developers and users who provide support, bug fixes, and new features.

Flexibility: Open Source GIS software can be used on a wide variety of platforms, including desktops, servers, and mobile devices.

Interoperability: Open Source GIS software often supports open standards, which can facilitate interoperability between different GIS applications and data sources.

Cons:

Lack of Support: Open Source GIS software may not have the same level of customer support as proprietary software, and may not have dedicated technical support.

Complexity: Open Source GIS software may require more technical expertise and resources to implement and maintain than proprietary software.

Integration Challenges: Open Source GIS software may not integrate as easily with other software tools as proprietary software.

Security Risks: Open Source GIS software may be more vulnerable to security risks if patches and updates are not implemented promptly.

Lack of Professional Services: Open Source GIS software may lack professional services such as training, consulting, and customization that may be available with proprietary software.

Overall, the decision to adopt and use Open Source GIS software depends on the specific needs and resources of an organization. Open Source GIS software can be a cost-effective and flexible solution for many organizations, but it requires careful consideration of the potential benefits and drawbacks.

eSpatiallyNewYork:  I am interviewing a candidate for a mid-level GIS position in my organization.  Can you generate a list of questions which could be asked to measure the candidate’s GIS competency?

Certainly! Here are some potential questions that you could ask your candidate to assess their GIS competency:

Can you explain the difference between raster and vector data?

How do you convert a raster dataset to a vector dataset, or vice versa?

How do you handle data projections and coordinate systems in GIS?

Can you describe some common methods of spatial analysis in GIS?

How do you geocode an address in GIS?

Can you explain the difference between top-down and bottom-up cartography?

How would you create a map that shows population density in a given area?

How do you extract information from satellite imagery in GIS?

Can you describe some common techniques for dealing with large datasets in GIS?

How do you handle missing or incomplete data in GIS?

These questions should give you a good sense of your candidate’s proficiency in GIS and their ability to handle common GIS tasks. Good luck with your interviews!