2026-10-12T12:07:18Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33954721 2026-10-07T14:44:19Z category_26998 item_type_3 month_year_10_2026

Xylella fastidiosa remote sensing detection: a bibliographic dataset from Scopus (2018–2026) Sofia Bajocco (656020) Danilo Morelli (13140199) Elisabetta Raparelli (14854513) Other environmental sciences not elsewhere classified Olive Quick Decline Syndrome Scopus Earth observation Thematic evolution Satellite <p dir="ltr">This dataset contains the bibliographic metadata (authors, title, year, source, abstract, keywords, DOI, citation counts, affiliations, etc.) of 43 scientific documents on the use of remote sensing technologies (satellite, airborne, UAV/drone, hyperspectral, thermal and multispectral imaging) for the detection and monitoring of the plant pathogen Xylella fastidiosa and associated diseases such as Olive Quick Decline Syndrome (OQDS). Records were retrieved from Scopus (Elsevier) using the query: TITLE-ABS-KEY(xylella AND fastidiosa) AND TITLE-ABS-KEY(remote AND sensing) OR TITLE-ABS-KEY(satellite) OR TITLE-ABS-KEY(drone) OR TITLE-ABS-KEY(uav) OR TITLE-ABS-KEY(airborne). The dataset covers publications from 2018 to 2026 and is intended to support systematic literature reviews and bibliometric analyses of remote sensing applications in plant epidemiology. </p> 2026-10-07T14:44:19Z Dataset Dataset 10.6084/m9.figshare.33954721.v2 https://figshare.com/articles/dataset/UntitledXylella_fastidiosa_remote_sensing_detection_a_bibliographic_dataset_from_Scopus_2018_2026_Item/33954721 CC BY 4.0