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Data Sheet 1_High-resolution remote sensing suggests greater vegetation resilience in maize-based intercropping systems than monocropping.docx

Domaine:

agriculturegeospatial

Type de record:

dataset
Créateur:
figAmaCheAnd
Hôte:avatar
Introduction

Intercropping is widely promoted as a strategy to enhance crop resilience, but spatial evidence for its vegetation- stress benefits in smallholder systems based on remote sensing data remains limited.

Methods

We used Sentinel-1 and Sentinel-2 data to map maize monocrop and maize intercrop in western Kenya, and Sentinel-2 vegetation indices to compare vegetation-stress conditions across these systems during the 2021 and 2023 long-rain seasons. We tracked monthly vegetation condition using normalized difference indices of vegetation, (VCI from NDVI, MCI from NDMI, and GCI from GNDVI) and were integrated into an ensemble stress index ENS. All these four metrics were subsequently incorporated into the Intercrop Advantage Score (IAS) - a remote-sensing proxy that combines the magnitude, uncertainty and seasonal consistency of intercrop-monocrop differences.

Results and Discussion

Across both seasons, maize intercrop generally showed higher vegetation condition and lower stress than maize monocrop. The relatively small, but statistically significant differences, provide evidence for resilience from remotesensing, in the absence of yield data. The IAS provides an interpretable transferable framework for comparing crop-system vegetation-stress profiles using satellite data and has potential application for evaluating of a wider range of agricultural interventions.

Visit

figshare.com

Tags

Agronomyclimate-smart agriculturecrop resilienceintercrop advantage scoreintercroppingremote sensingsentinel-2smallholder agriculturevegetation stress

Licenses

CC BY 4.0

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