Zonal, neighbourhood and local operations in GIS

 1. Local Operations in GIS

👀 Looks at one pixel at a time — like checking only one house on a map.

We do math or comparisons using just that pixel's value.

✅ Simple Examples:

• Add two maps together: temperature map + rainfall map

• Reclassify: Change values — e.g., if temperature > 30°C, mark as HOT

📌 Think of it like doing math problem by problem, not looking at neighbors.

 Neighbourhood Operations in GIS

🏡 Looks at a pixel and all its surrounding neighbours — like checking your house and nearby houses.

We use this to smooth, sharpen, or highlight details in the map.

✅ Simple Examples:

• Low Pass Filter: Makes the map look smooth (like blur in photos)

• High Pass Filter: Makes sharp edges stand out (like outlines in drawings)

• Edge Enhancement: Highlights boundaries between areas (like drawing a border between forest and farmland)

📌 Think of it like checking what your neighbours are doing before painting your own house!

Zonal Operations in GIS

🗺️ Looks at large zones or areas (groups of pixels with the same label), not just one or a few pixels.

We compare or summarize values inside a whole zone, like a city, forest, or lake.

✅ Simple Examples:

• Calculate the average rainfall in each district

• Find the highest temperature in each forest area

• Compare population across different zones

📌 Think of it like checking how an entire neighbourhood or city is doing, instead of just one house.

Type of Operation	What it Looks At	Simple Meaning	Example
Local	One pixel	Checks and changes one spot only	Mark areas where temperature > 30°C
Neighbourhood	Pixel + nearby pixels	Looks around before making a decision	Blur or sharpen parts of a map
Zonal	Groups of pixels (zones)	Analyzes a whole area together	Average rainfall in each district