Assessing the effectiveness of satellite and UAV-based remote sensing for delineating alfalfa management zones under heterogeneous rootzone soil salinity

Site-specific application of agricultural inputs is crucial for optimizing resource utilization in alfalfa ( Medicago sativa L.) production and addressing challenges such as soil salinity. The main objective of this study was to assess the effectiveness of PlanetScope and UAV-based NDVI imagery for delineating alfalfa management zones under heterogeneous rootzone soil salinity. The research was conducted in the alfalfa field located in Imperial Valley, CA. The extent of rootzone soil salinity was assessed using Electromagnetic induction (EMI) technology and deep soil sampling. Reference management zones were then defined using the soil salinity (ECe) map derived from apparent electrical conductivity (ECa) data. Additionally, a time series of NDVI images from PlanetScope imagery and an NDVI image captured using an unmanned aerial vehicle were used to delineate remote sensing-based management zones. Laboratory analysis of disturbed soil samples collected at various depths provided soil physicochemical property data. Soil salinity of the samples ranged from 2.2 to 13.4 dS m −1 with a moderate level of variability (CV = 37.7 %). ECe-based management zones accounted for approximately 83 % of the field's variability and exhibited substantial differentiation among delineated zones concerning diverse soil properties, including ECa, ECe, gravimetric water content, Mg 2+ , boron, Ca 2+ , Na + , and Cl − . Notably, NDVI images effectively captured field variability on par with ECe-based zoning. Moreover, NDVI images recommended the same optimal number of zones (i.e., three) to address the field's variability, aligning with the ECe-based zoning approach. Our findings highlight that heterogeneity of soil salinity in the root zone primarily impacts the variability of alfalfa NDVI early in the growing season. Consequently, this early stage emerges as the most opportune timeframe for NDVI-based zoning for rapid assessment of rootzone soil salinity concerns.

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Publication Details

Journal
Smart Agricultural Technology
Published
2024-09-28
DOI
https://doi.org/10.1016/j.atech.2024.100583
Citations
6
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
2.75

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article

Assessing the effectiveness of satellite and UAV-based remote sensing for delineating alfalfa management zones under heterogeneous rootzone soil salinity

Elia Scudiero, Anish Sapkota, Amir Verdi, A. Montazar
6 citations
Smart Agricultural Technology
Remote Sensing in Agriculture
2.75
article

Assessing the effectiveness of satellite and UAV-based remote sensing for delineating alfalfa management zones under heterogeneous rootzone soil salinity

Elia Scudiero, Anish Sapkota, Amir Verdi, A. Montazar
article en
6 citations

Abstract

Site-specific application of agricultural inputs is crucial for optimizing resource utilization in alfalfa ( Medicago sativa L.) production and addressing challenges such as soil salinity. The main objective of this study was to assess the effectiveness of PlanetScope and UAV-based NDVI imagery for delineating alfalfa management zones under heterogeneous rootzone soil salinity. The research was conducted in the alfalfa field located in Imperial Valley, CA. The extent of rootzone soil salinity was assessed using Electromagnetic induction (EMI) technology and deep soil sampling. Reference management zones were then defined using the soil salinity (ECe) map derived from apparent electrical conductivity (ECa) data. Additionally, a time series of NDVI images from PlanetScope imagery and an NDVI image captured using an unmanned aerial vehicle were used to delineate remote sensing-based management zones. Laboratory analysis of disturbed soil samples collected at various depths provided soil physicochemical property data. Soil salinity of the samples ranged from 2.2 to 13.4 dS m −1 with a moderate level of variability (CV = 37.7 %). ECe-based management zones accounted for approximately 83 % of the field's variability and exhibited substantial differentiation among delineated zones concerning diverse soil properties, including ECa, ECe, gravimetric water content, Mg 2+ , boron, Ca 2+ , Na + , and Cl − . Notably, NDVI images effectively captured field variability on par with ECe-based zoning. Moreover, NDVI images recommended the same optimal number of zones (i.e., three) to address the field's variability, aligning with the ECe-based zoning approach. Our findings highlight that heterogeneity of soil salinity in the root zone primarily impacts the variability of alfalfa NDVI early in the growing season. Consequently, this early stage emerges as the most opportune timeframe for NDVI-based zoning for rapid assessment of rootzone soil salinity concerns.

Smart Agricultural TechnologyVol. 9
University of California, Riverside (US), Montana State University (US), University of California Division of Agriculture and Natural Resources (US), U.S. Salinity Laboratory (US)
National Institute of Food and Agriculture
Life in Land
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
2.75
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