Use cases · Sports & field operations
Field scouting from phone and drone images
Turn the photos scouts and drones already capture into a map of possible problem areas, such as weeds, pests, disease or water stress, so agronomists can decide where to look first.
Where it starts
The trigger.
Scouts walk fields or a drone flight is completed.
How it runs today
- Scouting depends on how much ground a person can cover.
- Photos are taken but rarely reviewed together or mapped.
- Problems are found late, when they have already spread.
The workflow
Four bounded steps.
Each step has an owner and a stop rule.
- 01 / Capture
Collect geotagged images from scout phones or drone flights for each field.
- 02 / Detect
Flag images or areas that may show weeds, pests, disease or stress, with a confidence for each.
- 03 / Map
Place flagged areas on a field map with the source images attached.
- 04 / Decide
An agronomist reviews flagged areas, confirms or dismisses them and decides on action.
Where people stay in control
Approval points.
- An agronomist confirms every finding before any treatment decision.
- Low-confidence areas are marked for a person to check in the field.
How we would measure it
Against a baseline.
Measured before and after, on the same work.
Share of flagged areas confirmed by agronomists.
Time from capture to reviewed field map.
Acres reviewed per scouting day.
Related
Go deeper.
More use cases
Other places to start.
Movement and activity analysis from video
Count repetitions, score form or track activity from ordinary video, with results a coach or supervisor can check.
See the workflow Sports & field operationsField inspection photo reports
Turn the photos and notes field crews capture on site into an organized inspection report, with possible issues flagged for a qualified person to confirm.
See the workflow Sports & field operationsVenue occupancy and crowd flow
Count people entering, leaving and gathering in areas of a venue from existing cameras, without identifying anyone, so staff can open gates, move people and plan staffing.
See the workflowAn illustrative workflow pattern, not a result from a specific customer.
Bring the messy version
One workflow.
A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
---
title: "Field scouting from phone and drone images: AI Use Case"
description: "Turn the photos scouts and drones already capture into a map of possible problem areas, such as weeds, pests, disease or water stress, so agronomists can decide where to look first."
url: https://lidvizion.ai/use-cases/field-scouting-from-images/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Use cases](https://lidvizion.ai/use-cases/) · Sports & field operations
# Field scouting from phone and drone images
Turn the photos scouts and drones already capture into a map of possible problem areas, such as weeds, pests, disease or water stress, so agronomists can decide where to look first.
[Talk through this workflow](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Fuse-cases%2Ffield-scouting-from-images%2F#write) · [Build the missing piece](https://lidvizion.ai/services/custom-software/)
Where it starts
## The trigger.
Scouts walk fields or a drone flight is completed.
How it runs today
- Scouting depends on how much ground a person can cover.
- Photos are taken but rarely reviewed together or mapped.
- Problems are found late, when they have already spread.
The workflow
## Four bounded steps.
Each step has an owner and a stop rule.
1. 01 / Capture
Collect geotagged images from scout phones or drone flights for each field.
2. 02 / Detect
Flag images or areas that may show weeds, pests, disease or stress, with a confidence for each.
3. 03 / Map
Place flagged areas on a field map with the source images attached.
4. 04 / Decide
An agronomist reviews flagged areas, confirms or dismisses them and decides on action.
Where people stay in control
## Approval points.
- An agronomist confirms every finding before any treatment decision.
- Low-confidence areas are marked for a person to check in the field.
How we would measure it
## Against a baseline.
Measured before and after, on the same work.
### Share of flagged areas confirmed by agronomists.
### Time from capture to reviewed field map.
### Acres reviewed per scouting day.
Related
## Go deeper.
- [Build the missing piece](https://lidvizion.ai/services/custom-software/): Custom tools and applications for the gaps that matter.
- [Image vs. video processing](https://lidvizion.ai/resources/basics/image-vs-video-processing/): When a single frame is enough, and when you need motion, sequence and time.
- [Map problem areas from field images](https://lidvizion.ai/guides/map-problem-areas-from-field-images/): A four-step playbook to standardize how fields are photographed, test detection on your own crops and conditions, map flagged areas for agronomists and measure whether scouting gets faster and earlier.
- [How Much Data Does a Computer Vision Project Need?](https://lidvizion.ai/answers/how-much-data-does-a-computer-vision-project-need/): How many images or videos does a business need to start a computer vision project?
More use cases
## Other places to start.
[All use cases](https://lidvizion.ai/use-cases/)
- [Movement and activity analysis from video](https://lidvizion.ai/use-cases/video-movement-analysis/): Sports & field operations Count repetitions, score form or track activity from ordinary video, with results a coach or supervisor can check.
- [Field inspection photo reports](https://lidvizion.ai/use-cases/field-inspection-photo-reports/): Sports & field operations Turn the photos and notes field crews capture on site into an organized inspection report, with possible issues flagged for a qualified person to confirm.
- [Venue occupancy and crowd flow](https://lidvizion.ai/use-cases/venue-occupancy-and-crowd-flow/): Sports & field operations Count people entering, leaving and gathering in areas of a venue from existing cameras, without identifying anyone, so staff can open gates, move people and plan staffing.
An illustrative workflow pattern, not a result from a specific customer.
Bring the messy version
## One workflow. A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)