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Ground Truthing Protocols for Biomass Estimation in Rangeland Environments

Charity Mundava, Antonius Schut, Richard Stovold, Graham Donald, David Lamb, Petra Helmholz

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

2 Citations (Scopus)

Abstract

Remote sensing for the assessment and mapping of total standing biomass relies on accurate ground data for calibration and validation. The spatial heterogeneity of rangelands pose challenges in sampling methodologies, demanding a large number of replicate measurements that are expensive and labour demanding when working on the scale of pastoral stations. In this paper we present a ground truthing protocol that can be used for biomass estimation in heterogeneous rangeland environments, important for the development of assessments based on remote sensing or growth modelling. The protocol is based on a combination of visual estimates, crop circle NDVI, and disk-plate meter height recordings. Relationships between these indirect measurements and biomass were specific for either season or vegetation type. A combination of these measurements in a multivariate regression provided an accurate alternative, while strongly reducing the number of cuts required.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Place of PublicationLos Alamitos, United States of America
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2122-2124
ISBN (Print)9781479911141
DOIs
Publication statusPublished - 2013
EventIGARSS 2013: IEEE International Geoscience and Remote Sensing Symposium - Building a Sustainable Earth through Remote Sensing - Melbourne, Australia
Duration: 21 Jul 201326 Jul 2013

Conference

ConferenceIGARSS 2013: IEEE International Geoscience and Remote Sensing Symposium - Building a Sustainable Earth through Remote Sensing
CityMelbourne, Australia
Period21/07/1326/07/13

Keywords

  • Agricultural Land Management
  • Agricultural Systems Analysis and Modelling
  • Sustainable Agricultural Development

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