Delineation of Management Zones Based on the Agricultural Potential Concept for Potato Production Using Optical Satellite Images

Abstract

Highlights: What are the main findings? NDVI composite metrics (mean, standard deviation, skewness) successfully delineated three agricultural potential (AP) zones (high, intermediate, low) that aligned with tuber yield and soil nutrient patterns (total N and C). Multi-year NDVI composites from Sentinel-2 and Landsat 8 effectively captured spatial and temporal variability in crop productivity, demonstrating robustness and scalability across multiple fields. What are the implications of the main findings? This approach demonstrates that freely available satellite data (Sentinel-2, Landsat 8) can reduce reliance on expensive soil sampling and specialized equipment for MZ delineation, making precision agriculture more accessible to growers. The methodology provides a scalable, cost-effective framework that supports the identification of stable productivity patterns and guiding sustainable management decisions. Management zones (MZs) are a key precision agriculture strategy for managing spatial variability in crops, but conventional delineation methods are costly, time-consuming, and rely on specialized equipment. Previous studies in potato production have primarily relied on single-year NDVI or proximal soil sensor data analyses, limiting their ability to capture temporal stability and variability across multiple fields. This study addresses this gap by applying multi-year, multi-source NDVI composites to characterize spatial and temporal patterns of agricultural potential across 17 commercial potato fields at McCain’s Farm of the Future, Florenceville-Bristol, New Brunswick. A total of 230 NDVI images from Sentinel-2 and Landsat 8 (2015–2023) were processed into composite metrics (mean, standard deviation, skewness) to delineate three agricultural potential (AP) MZs. Validation was conducted using 2023 potato tuber yield and soil physicochemical properties. The results showed statistically significant correlations between NDVI metrics and key soil nutrients (total carbon: |r| < 0.19; total nitrogen: |r| < 0.28), with tuber yield (|r| < 0.41). Spatial patterns of total carbon and nitrogen corresponded with delineated MZs, and tuber yield variability partially aligned with these zones. These findings demonstrate that multi-year NDVI composites provide a cost-effective and scalable approach for mapping agricultural potential, capturing both spatial and temporal variability, and supporting data-driven management decisions in potato production systems.