Development of the grass LAI and CCC remote sensing-based models and their transferability using sentinel-2 data in heterogeneous grasslands

Tsele, PhilemonRamoelo, AbelQabaqaba, Mcebisi2023-11-272023Philemon Tsele, Abel Ramoelo & Mcebisi Qabaqaba (2023) Development of the grass LAI and CCC remote sensing-based models and their transferability using sentinel-2 data in heterogeneous grasslands, International Journal of Remote Sensing, 44:8, 2643-2667, DOI: 10.1080/01431161.2023.2205982.0143-1161 (print)1366-5901 (online)10.1080/01431161.2023.2205982http://hdl.handle.net/2263/93464Please read abstract in the article.en© 2023 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in International Journal of Remote Sensing, vol. 44, no. 8, pp. 2643–2667, 2023. doi : 10.1080/01431161.2023.2205982. International Journal of Remote Sensing is available online at : http://www.tandfonline.com/loi/tres20.Leaf area index (LAI)Canopy chlorophyll content (CCC)Sentinel-2 imageryIndicesStepwise multiple linear regression (SMLR)Random forest (RF)Golden Gate Highlands National Park (GGHNP)Marakele National Park (MNP)South Africa (SA)SDG-15: Life on landDevelopment of the grass LAI and CCC remote sensing-based models and their transferability using sentinel-2 data in heterogeneous grasslandsPostprint Article