Can We Use the Relationship Between Within-Field Elevation and NDVI as an Indicator of Drought-Stress?

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

2 Citations (Scopus)

Abstract

Large farmers’ datasets can help shed light on agroecological processes if used in the context of hypothesis testing. Here we used an anonymized set of data from the geoplatform Akkerweb to better understand the correlation between within-field elevation and normalized differential vegetation index (NDVI, a proxy for biomass). The dataset included 3249 Dutch potato fields, for each of which the cultivar, the field polygon, the year of cultivation and the soil type (clay or sandy) was known. We hypothesize that under dry conditions such correlation is negative, meaning that the lowest portions of the field have more biomass because of water redistribution. From the data, we observed that in dry periods, such as the summer of 2018, the correlation was negative in sandy soils. Furthermore, we observed that early cultivars show a weaker correlation between NDVI and elevation than late cultivars, possibly because early cultivar escape part of the long dry summer spells. We conclude that the correlation between NDVI and elevation may be a useful indicator of drought stress, and deviations from the norm may be useful to evaluate the resistance to drought of individual cultivars.
Original languageEnglish
Title of host publicationInternational Symposium on Environmental Software Systems (ISESS 2020)
Subtitle of host publicationEnvironmental Software Systems. Data Science in Action
Place of PublicationWageningen
PublisherSpringer
Chapter12
Pages122-131
ISBN (Electronic)9783030398156
ISBN (Print)9783030398149
DOIs
Publication statusPublished - 29 Jan 2020

Publication series

NameIFIP Advances in Information and Communication Technology
Volume554
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Keywords

  • Actueel hoogtebestand nederland
  • AHN2
  • DEM
  • Drought
  • Elevation
  • NDVI
  • Netherlands
  • Potato
  • Precision agriculture
  • Within-field variability

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