GIScience Timisoara

Wulff / great-circle circles on the projection sphere and net (same source).

Hi, let's play a quiz game.
Q: Do you know what is "NDVI"? What is its calculation formula? What information does it primarily reflect?

A: NDVI refers to Normalized Difference Vegetation Index.

How to calculate?
NDVI = (NIR - Red) / (NIR + Red)
NIR = Reflectance value in the Near-Infrared band
Red = Reflectance value in the Red band

What information does it reflect?
The degree of vegetation coverage and growth vitality/biomass. Healthy and lush vegetation has high reflectance in the near-infrared band and low reflectance (strong absorption) in the red band, resulting in a high NDVI value (close to 1). Bare soil, water bodies, snow, ice, clouds, etc., have low or negative NDVI values.

NDVI is the most classic and widely used vegetation index. It is an important tool for vegetation monitoring, agricultural yield estimation, ecological research, drought assessment, and more using remote sensing data. Its calculation requires remote sensing images with red and near-infrared bands (e.g., Landsat, Sentinel-2).

📚 Hi, if you’re new to GIS, all those acronyms might look intimidating. Don’t worry — here’s a quick guide to help you decode the most common ones.

📌 – Geographic Information System: The framework for capturing, analyzing, and visualizing spatial data.
📌 - Global Navigation Satellite System:A general term for all satellite navigation systems (e.g., GPS, GLONASS, Galileo, BeiDou).
📌 – Global Positioning System: The satellite-based system that tells us exactly where we are on Earth.
📌 – Digital Elevation Model: A digital representation of terrain elevation for mapping and analysis.
📌 - Digital Terrain Model: A topographic model of the bare Earth, which can include other terrain features like breaklines and ridges, not just elevation points.
📌 – Normalized Difference Vegetation Index: A measure used to assess plant health and vegetation cover.
📌 - Triangulated Irregular Network: A vector-based representation of a surface, formed by irregularly spaced nodes and lines with three-dimensional coordinates.
📌 - Light Detection and Ranging: A remote sensing method that uses light in the form of a pulsed laser to measure variable distances to the Earth.

These acronyms may look simple, but each one represents a powerful concept that drives real-world applications in cities, environment, agriculture, and beyond.
💬 Which of these acronyms do you use most often? Or is there one you’d like us to explain in more detail next?

Dear colleagues
We are pleased to invite you to publish the results of your research in the field of Remote sensing and machine learning in a special issue of Sustainability - "Application of Remote Sensing and Machine Learning in Sustainable Agriculture".
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but need not be limited to) the following:
• Land surveying in the agricultural field, from the established topographic field instrumentations (total stations, GNSS systems, TLS, etc.) to the new methods based on optical remote sensing (UAV or airborne platforms for LiDAR and digital photogrammetry, InSAR, satellite images, etc.);
• Challenges and advances in agriculture;
• Integrating models, methods, techniques, and tools for geospatial applications in agricultural field;
• GIS applications in agriculture management, policy, and decision making;
• Precision agriculture;
• Integration of field data and sensors in decision support systems;
• Techniques for vegetation structure modelling and biomass assessment;
• Land crops dynamics and the environmental/ecological implications;
• Artificial intelligence and machine learning;
• Big data analysis;
• Crop nutrition diagnosis;
• Crop monitoring;
• Smart agriculture;
• Best practices, guidelines, and planning using acquired geospatial data.
We look forward to receiving your contributions.

Application of Remote Sensing and Machine Learning in Sustainable Agriculture Special Issue in journal Sustainability: Application of Remote Sensing and Machine Learning in Sustainable Agriculture

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Certainly! Latitude and longitude are geographic coordinates used to specify a location on the Earth's surface. Latitude measures the distance north or south of the Equator, while longitude measures the distance east or west of the Prime Meridian.

In the given coordinates, latitude is represented in degrees (°), minutes ('), and seconds ("). To convert these values to decimal degrees, you divide the minutes by 60 and the seconds by 3600, then add the results to the degrees.

For example, let's take the first coordinate: 12° 16' 06" S. To convert this to decimal degrees:
- Degrees: 12
- Minutes: 16
- Seconds: 06

Dividing the minutes by 60: 16 / 60 = 0.26666667
Dividing the seconds by 3600: 06 / 3600 = 0.00166667

Adding the results to the degrees: 12 + 0.26666667 + 0.00166667 = 12.26833333

So, the latitude in decimal degrees for the first coordinate is = 12.26833333.

You can follow the same process to convert the remaining coordinates from degrees, minutes, and seconds to decimal degrees. Remember to use negative values for south latitudes and west longitudes.

https://www.gpsworld.com/the-inverted-geospatial-pyramid-shows-our-vulnerability/