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Articles | Volume XLVIII-M-1-2023
https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-189-2023
https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-189-2023
21 Apr 2023
 | 21 Apr 2023

DETECTION OF PHYTOGEOGRAPHIC INDICATORS WITH REMOTE SENSING AND GEOARCHAEOLOGY FOR DEVELOPMENT OF A LONG-TERM CLIMATE MONITORING STATION IN ISRAEL

N. Manspeizer and A. Karnieli

Keywords: geoarchaeology, remote sensing, vegetation dynamics, climate monitoring, Mediterranean, UN SDG 13

Abstract. The Mediterranean basin is a strong candidate for monitoring climate change successfully, a priority of UN SDG 13, because of its long settlement history. Human-environmental contact has typically hindered monitoring efforts because the natural indicators that enable dependable monitoring have been altered anthropogenically. This research describes a two-step process which turns that synanthropism into an advantage through geoarchaeology, remote sensing, GIS, meteorology, and floristic classification. First, archaeological survey data were employed in a semi-arid region of Israel to identify areas of more and less intensive land-use over 2300 years. Trend surfaces were derived in GIS from ancient periods of most intense monoculture agriculture (Hellenistic, Byzantine, and Ottoman). 2020 land-cover was classified using VENμS satellite wet / dry season NDVI imagery and an airborne LiDAR canopy height model. This was reclassed after fieldwork to three broad land-cover classes and cross-tabulated with the 2300-year land-use intensity model in GIS. The results indicate a land-use legacy whereby woody perennial species are more abundant where land-use was cumulatively less intense. Second, unmanned aerial vehicle surveys were conducted in these areas of less-intense land-use. There, on lightly grazed lands where woody encroachment occurs but chamaephytes regenerate due to the grazing, microplots were established. Phanerophyte and chamaephyte shrubs were identified based on Raunkiaer type and the species associated with chorotype (geographic origin). This was compared with aridity index values derived for the study area between 2010-2022. The study provides a prototype, using dependable phytogeographic indicators, that may be developed into a long-term climate monitoring station (LTCMS).