Abd-Elrahman, Amr
0000-0002-6182-4017

Specialist

professor, geomatics, School of Forest Resources and Conservation, UF/IFAS Gulf Coast REC, Plant City

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Publications

A Step-by-Step Guide for Automated Plant Canopy Delineation Using Deep Learning: An Example in Strawberry Using ArcGIS Pro Software

Amr Abd-Elrahman, Katie Britt, and Vance Whitaker

This publication presents a guide to image analysis for researchers and farm managers who use ArcGIS software. Anyone with basic geographic information system analysis skills may follow along with the demonstration and learn to implement the Mask Region Convolutional Neural Networks model, a widely used model for object detection, to delineate strawberry canopies using ArcGIS Pro Image Analyst Extension in a simple workflow. This process is useful for precision agriculture management.

Stewardship Ecosystem Services Study Series: Assessing Forest Water Yield and Regulation Ecosystem Services in the Lower Suwannee River Watershed, Florida

Sonia Delphin, Francisco J. Escobedo, Amr Abd-Elrahman, Alison E. Adams, Jackie Martin, Ronald Cademus

A UF/IFAS numbered Fact Sheet. in support of UF/IFAS Extension program: ==Water==

Deep Learning Classification of High-Resolution Drone Images Using the ArcGIS Pro Software

Amr Abd-Elrahman, Katie Britt, and Tao Liu

Deep learning classification of invasive species using widely used ArcGIS Pro software and increasingly common drone imagery can aid in identification and management of natural areas. A step-by-step implementation, with associated data for users to access, is presented to make this technology more widely accessible to GIS analysts, researchers, and graduate students working with remotely sensed data in the natural resource field.

Geomatics