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The southeastern Amazon region has been intensively occupied by human settlements over the past three decades. To evaluate the effects of human settlements on land-cover and land-use (LCLU) changes over time in the study site, we evaluated multitemporal Landsat images from the years 1984, 1994, 2004, 2013 and Sentinel to the year 2017. Then, we defined the LCLU classes, and a detailed "from-to" change detection approach based on a geographic object-based image analysis (GEOBIA) was employed to determine the trajectories of the LCLU changes. Three land-cover (forest, montane savanna and water bodies) and three land-use types (pasturelands, mining and urban areas) were mapped. The overall accuracies and kappa values of the classification were higher than 0.91 for each of the classified images. Throughout the change detection period,~47% (19,320 km 2 ) of the forest was preserved mainly within protected areas, while almost 42% (17,398 km 2 ) of the area was converted from forests to pasturelands. An intrinsic connection between the increase in mining activity and the expansion of urban areas also exists. The direct impacts of mining activities were more significant throughout the montane savanna areas. We concluded that the GEOBIA approach adopted in this study combines the advantages of quality human interpretation and the capacities of quantitative computing.to improve image classification accuracy [5]. Primarily, GEOBIA has been able to be applied due to the advent of very high (spatial)-resolution images that show mainly land-cover and land-use (LCLU) changes within urban areas [6], forests [7], and agriculture areas [8], where image objects are digitally constructed from dozens to hundreds of pixels [9,10]. However, the use of GEOBIA has been increasingly expanded to include moderate-resolution images if a higher hierarchical image-object level is applied [11][12][13][14].In a global and regional context, the investigation of variations in the LCLU constitute a broad field in terms of the diversity of remote sensing methods that are available to map and monitor the different types of human-driven changes in the environments. Although many change detection techniques have been developed at the per-pixel level, new insights have been obtained from GEOBIA and hybrid methods centered on "from-to" change trajectories to better qualify and quantify LCLU change patterns [15].In the Amazon region, the dynamics of forest conversion to pastureland are well documented using a per-pixel approach [2], and the findings of these studies are mainly provided in annual reports on the Satellite Monitoring System of the Brazilian Amazon Forest (PRODES) (www.dpi.inpe. br/prodesdigital/prodes). Nevertheless, information is lacking regarding the conversion of forests and montane savanna regions to mining infrastructure, with the exception of a few studies on gold mining using high-resolution images [16]. Recent publications have demonstrated the influence of mining projects on the LCLU changes in the Brazilian Amazon from "pixel-to-...

The eastern Brazilian Amazon contains many isolated ferruginous savanna ecosystem patches (locally known as ‘canga vegetation’) located on ironstone rocky outcrops on the top of plateaus and ridges, surrounded by tropical rainforests. In the Carajás Mineral Province (CMP), these outcrops contain large iron ore reserves that have been exploited by opencast mining since the 1980s. The canga vegetation is particularly impacted by mining, since the iron ores that occur are associated with this type of vegetation and currently, little is known regarding the extent of canga vegetation patches before mining activities began. This information is important for quantifying the impact of mining, in addition to helping plan conservation programmes. Here, land cover changes of the Canga area in the CMP are evaluated by estimating the pre-mining area of canga patches and comparing it to the actual extent of canga patches. We mapped canga vegetation using geographic object-based image analysis (GEOBIA) from 1973 Landsat-1 MSS, 1984 and 2001 Landsat-5 TM, and 2016 Landsat-8 OLI images, and found that canga vegetation originally occupied an area of 144.2 km2 before mining exploitation. By 2016, 19.6% of the canga area was lost in the CMP due to conversion to other land-use types (mining areas, pasturelands). In the Carajás National Forest (CNF), located within the CMP, the original canga vegetation covered 105.2 km2 (2.55% of the CNF total area), and in 2016, canga vegetation occupied an area of 77.2 km2 (1.87%). Therefore, after more than three decades of mineral exploitation, less than 20% of the total canga area was lost. Currently, 21% of the canga area in the CMP is protected by the Campos Ferruginosos National Park. By documenting the initial extent of canga vegetation in the eastern Amazon and the extent to which it has been lost due to mining operations, the results of this work are the first step towards conserving this ecosystem.