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

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.

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Publication Details

Journal
Remote Sensing
Published
2025-11-14
DOI
https://doi.org/10.3390/rs17223709
Citations
2
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
1.60
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article

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

Athyna N. Cambouris, Karem Chokmani, Michelle D'Souza, David A. Ramirez-Gonzalez
2 citations
Remote Sensing
Soil Geostatistics and Mapping
1.60
article

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

Athyna N. Cambouris, Karem Chokmani, Michelle D'Souza, David A. Ramirez-Gonzalez
article en
2 citations

Abstract

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.

Remote SensingVol. 17(22)
Agriculture and Agri-Food Canada (CA), Institut National de la Recherche Scientifique (CA), Bristol-Myers Squibb (Canada) (CA), Quebec Research and Development Centre
Openalex Percentile: Top 15%
Soil Geostatistics and Mapping
1.60
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