Mining activity is essential for the Brazilian economy, representing 21% of exports in 2018, but it causes several environmental impacts, including deforestation. To minimize these impacts, replanting techniques are applied for environmental recovery and regulatory compliance. In this context, this study aims to monitor vegetation recovery in decommissioned bauxite mining areas located in the Amazon rainforest. The case study was carried out in the municipality of Paragominas (state of Pará). The monitoring used the series of a newly defined spectral index, called Biomass Composite Index (BCI), and the Enhanced Vegetation Index (EVI), both from Landsat images between 1986 and 2017. The analysis was complemented by interpretation of false-color images and by in situ photographs. The method was applied for periods before mining, during exploitation, and after decommissioning, when the traditional planting technique was implemented. BCI demonstrated greater sensitivity to forest disturbance in areas affected by forest degradation and less influence of canopy homogeneity where the forest was substituted by more open formations. The height homogeneity of recovered areas also affected the EVI data more than the BCI data, since these areas presented higher values of EVI, and some areas had index values close to those detected before mine operation. The analysis could have benefited from sampling intensification, with more images analyzed per year, to overcome the presence of clouds, which block the acquisition of surface data by the sensor. Nevertheless, the method proved to be very promising and can improve the evaluation of forest recomposition even in remote areas, besides facilitating large-scale monitoring of recovered forests.

Graphic abstract

中文翻译：

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亚马逊森林铝土矿开采影响地区的植被恢复分析

采矿活动对于巴西经济至关重要，占2018年出口总额的21％，但它会造成多种环境影响，包括森林砍伐。为了最大程度地减少这些影响，将补植技术应用于环境恢复和法规遵从性。在这种情况下，本研究旨在监测位于亚马逊雨林的退役铝土矿开采区的植被恢复情况。案例研究在帕拉戈米纳斯市（帕拉州）进行。监测使用了一系列新定义的光谱指数，称为生物量综合指数（BCI）和增强植被指数（EVI），均来自1986年至2017年的Landsat影像。通过原地照片。该方法适用于采矿之前，开采期间，退役后，采用传统的种植技术。在受森林退化影响的地区，BCI表现出对森林扰动的更高敏感性，而被更多开放地层替代的林冠同质性影响较小。与BCI数据相比，恢复区的高度均匀性对EVI数据的影响也更大，因为这些区域的EVI值较高，并且某些区域的索引值与矿山运营前检测到的值接近。该分析本应得益于采样强度的提高，每年可以分析更多的图像，以克服云的存在，因为云的存在阻碍了传感器对表面数据的采集。但是，该方法被证明是非常有前途的，即使在偏远地区，也可以改善对森林重组的评估，

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