Drone Data Metrics for Orchard Farming: Making Sense of Drone-Derived Data for Perennial Crops

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Ken Treloar

Drone Data Metrics for Orchard Farming

Name: Drone Data Metrics for Orchard Farming
Price: 26.20 AUD
Availability: OutOfStock
ISBN: 9781049227610

Making Sense of Drone-Derived Data for Perennial Crops

Ken Treloar

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Paperback

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English

Agtech Publications
20 November 2025

Sustainable agriculture

Series: Orchard Farming with Uavs

Maps are not the goal. Management is.

Go from pixels to pruning; from insights to intelligent irrigation; from yield predictions to predictable profit.

Build a data-savvy orchard mindset without the guesswork.

Drone data can feel complex. It doesn't have to be. In Drone Data Metrics for Orchard Farming, AgTech writer and strategist Ken Treloar outlines how to effectively read RGB, DEMs, multispectral indices, thermal metrics, canopy statistics, and analyse plant census data with clarity.

Turning information from above into practical field actions with a simple, repeatable workflow. The perfect guide for for UAV mapping management of perennial crops.

What you'll learn:

How to choose survey timing that actually helps (early season; mid season; post-harvest). How to layer data (RGB + DEM + NDVI/NDRE + Thermal) to diagnose why planted assets are underperforming. How to use plant census and canopy metrics to target replanting, pruning, and VRA programs. When NDVI is the right tool; when NDRE sees stress sooner in dense canopies. How Transpiration Uniformity and Transpiration Variance surface irrigation issues before they cost you yield. How to design Smart Sampling routes that cut walking time and remove bias. How to compare seasons; measure variance; and track ROI with confidence. Practical thresholds and rules-of-thumb for quick triage in the field.

Make better decisions from your very next drone flight!

By: Ken Treloar
Imprint: Agtech Publications
Volume: 1
Dimensions: Height: 216mm, Width: 140mm, Spine: 17mm
Weight: 372g
ISBN: 9781049227610
ISBN 10: 1049227611
Series: Orchard Farming with Uavs
Pages: 320
Publication Date: 20 November 2025
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Ken Treloar is a writer, strategist, and AgTech advocate focused on helping farmers turn drone data into practical decisions. With a background in horticulture, media, design, entrepreneurship, and business management, he has spent the last decade or so working at the intersection of precision agriculture and perennial crops such as macadamias, citrus, avocados, and grape vines.Ken works with farmers, agronomists, and agribusiness teams across Africa, Europe, and Latin America; helping them make sense of complex orchard data from drones, satellites, smart app's, and AI-powered platforms. His work centres on one simple idea: technology only matters when it is a catalyst for action, useful in the field, and built around real-world farming constraints.Ken is the director of AgTech Publications, his company that support experts in their respective fields in finding a voice through media. And he is the founder and writer of the AgTech Diaries blog, where he shares ideas, concepts, and case studies from the exciting confluence of agriculture and technology.His latest book Drone Data Metrics for Orchard Farming is a clear, practical guide for anyone who wants to move beyond ""pretty pictures from above"" and actually understand and use drone-derived insights to improve orchard performance over time. When he is not writing or working with farmers and agronomists on their drone data, Ken can be found enjoying the wild outdoors, gardening, reading, or sketching ideas for his next book.

Reviews for Drone Data Metrics for Orchard Farming: Making Sense of Drone-Derived Data for Perennial Crops

""Excellent! All the basics and key info about each metric type, and without getting bogged down in technicalities like some textbook style drone mapping books. But still enough meat to get stuck into when any drone mapping results come out. I liked how easy it was to read and the short case studies brought home the ideas in a practical way. Must admit, enjoyed the AI precision sampling chapter quite a bit, very interesting.""