
Overview The land use and land cover maps encompass the Katanino Forest Reserve in the Copperbelt province, Zambia. These maps categorize the area into two classes: forest and non-forest. They were derived from NICFI, Sentinel-2, and Sentinel-1 mosaics, resulting in a spatial resolution of 4.77 meters, covering the period from 2019 to 2023. Maps Accuracy The overall accuracy of the final annual maps (2019–2023) ranged from 0.90 to 0.94. The user’s and producer’s accuracies are detailed in Table 1. Table 1: Land use and land cover maps validation, including overall, producer (PA) and user (UA) accuracies values for each class. 2019 2020 2021 2022 2023 PA UA PA UA PA UA PA UA PA UA Forest 0.87 0.99 0.83 0.99 0.88 0.99 0.91 0.99 0.88 1 Non Forest 0.99 0.86 0.99 0.82 0.99 0.99 0.99 0.89 1 0.87 Overall Accuracy 0.92 0.90 0.93 0.94 0.93 Files descripion KAT_2019.tif: 2019 land use and land cover map KAT_2020.tif: 2020 land use and land cover map KAT_2021.tif: 2021 land use and land cover map KAT_2022.tif: 2022 land use and land cover map KAT_2023.tif: 2023 land use and land cover map qgis_style.qml: QGIS style file KAT_training_samples(.shp, .shx, .dbf, .prj): training samples with class labels KAT_validation_samples(.shp, .shx, .dbf, .prj): validation samples with class labels
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
