Methodology for the Automatic Inventory of Olive Groves at the Plot and Polygon Level

Abstract

The aim of this study was to develop and validate a methodology to carry out olive grove inventories based on open data sources and automatic photogrammetric and satellite image analysis techniques. To do so, tools and protocols have been developed that have made it possible to automate the capture of images of different characteristics and origins, enable the use of open data sources, as well as integrating and metadating them. They can then be used for the development and validation of algorithms that allow for improving the characterization of olive grove surfaces at the plot and cadastral polygon scales. With the proposed system, an inventory of the Andalusian olive grove has been automatically carried out at the level of cadastral polygons and provinces, which has accounted for a total of 1,519,438 hectares and 171,980,593 olive trees. These data have been contrasted with various official statistical sources, thus ensuring their reliability and even identifying some inconsistencies or errors of some sources. Likewise, the capacity of the Sentinel 2 satellite images to estimate the FCC at the cadastral polygon, parcel and 10 × 10 m pixel level has been demonstrated and quantified, as well as the opportunity to carry out inventories with temporal resolutions of approximately up to 5 days.

Plant phenotyping relevance

オリーブ樹園の自動インベントリと、衛星画像による樹冠被覆率（FCC）推定手法の開発・検証が中心であり、植物の樹冠状態を定量化している。

Code and data availability

The paper's olive grove inventory data (PNOA orthophoto-derived FCC/density measurements, Sentinel-2 NDVI data, and analysis code) are not publicly deposited; the Data Availability Statement states they are available only on request from the first author. All URLs in the text are cited external sources (SIGPAC, RAIF, P

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