Index System to Evaluate the Quarries Ecological Restoration

Zhang, Qiuqin; Zhang, Tianzhu; Liu, Xiang

doi:10.3390/su10030619

Cited by 24 publications

(10 citation statements)

References 23 publications

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“…З іншого, такі об'єкти є чудовими полігонами для вивчення динаміки рослинності за різних едафічних умов (Hobbs, 2004). Тут ми можемо спостерігати за первинними сукцесіями безпосередньо в районі гірничих робіт, або за вторинними на деяких елементах відвалів чи перелогах поруч із виробкою (Zhang et al, 2018).…”

Section: вступunclassified

Syntaxonomy of restoration vegetation in quarries in Central Polissya

Khomiak¹

2022

Ukr. Bot. J.

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Syntaxonomy of restoration vegetation in quarry sites in Central Polissya of Ukraine, including 25 classes, 36 orders, 62 alliances, 116 associations, and two unranked communities, is presented. Based on the frequency of occurrence of vegetation plots, we have identified typical and atypical environments in existing and abandoned quarries. The classes Molinio-Arrhenatheretea, Artemisietea vulgaris, Phragmiti-Magnocaricetea, Plantagenetea majoris, and Epilobietea angustifolii were found to be the most common. Predominance of the grassland stage in vegetation restoration under significant or moderate anthropogenic impact is demonstrated. The environmental factors and features of seed dispersal affect the mode and tempo of vegetation restoration in disturbed habitats of open pit mining. Meadow vegetation is predominant on the plateau around the zone of active production; herbaceous and woody plants penetrate the slopes simultaneously. Steep vertical outcrops of crystalline rocks for a long time remain uninhabited by higher vascular plants. Plants grow exclusively in the crevices of crystal blocks filled with loose rocks, soil, and small organic residues. On the slopes of loose sedimentary rocks, the meadow stage is not gradually transformed into the phanerophyte stage. The rate of vegetation restoration depends on the slope angle. Such successions form large ecotone areas due to numerous unfilled ecological niches in the quarry ecosystems. These areas are most vulnerable to the penetration of invasive plant species.

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Section: вступunclassified

Syntaxonomy of restoration vegetation in quarries in Central Polissya

Khomiak¹

2022

Ukr. Bot. J.

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“…As part of a project involving ARPAT, several remote sensing methods were used to derive areal and volumetric datasets, which were used to calculate a set of experimental indicators related to the potential impact of MQW/MCW on the entire Carrara industrial basin (Licciardello et al, 2021). The indicators proposed in this work are targeted at local monitoring of individual quarries, while those already in the literature were limited to monitoring of high-level plans, being mainly based on (a) the life cycle assessment (LCA) method applied to building materials (Bianco et al, 2016;Zabalza et al, 2011), (b) the influence of the adoption of industrial best practices (Zabalza et al, 2011), (c) other hybrid approaches (Capitano et al, 2018), or (d) the restoration of natural habitats (Zhang Q. et al, 2018), are mainly aimed at monitoring regional plans that require Strategic Environmental Assessment (SEA) (Huang et al, 2007) The multidimensional nature of the proposed indicators, which vary over time and space, requires further work to facilitate the use of the indicators by decision makers. With this in mind, the development of appropriate user interfaces, based on dynamic web maps with time-dependent data and 3-D representations highlighting critical areas, plays an important role in planning environmental monitoring.…”

Section: Introductionmentioning

confidence: 99%

2d/3d Soil Consumption Tracking in a Marble Quarry District

Licciardello

Marco

Biagini

et al. 2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Complex extractive districts, such as the marble quarries in the Apuan Alps (northern Italy), require soil consumption monitoring over the years that could be achieved through high-resolution remotely sensed data. To derive 2D and 3D indicators with appropriate resolution for annual monitoring of high-resolution changes in soil consumption, aerial images, LiDAR acquisitions, satellite data, and Remotely Piloted Aircraft Systems (RPAS) acquisitions were used. In particular, open-access Sentinel-2 multispectral satellite imagery with a spatial resolution of 10 m was used to assess cover changes (2D), and then refined by manual interpretation for 5 years (2016-2021). 3D changes were detected by comparing free aerial LiDAR data from 2009 and 2017, integrated with two stereo models obtained from Pléiades high-resolution satellite images from 2020 and 2022. 3D changes observed over the years by algebraic elevation comparison, performed in QGIS 3.x environment, highlight quarries characterized by intense mining activities (extracted marble blocks, characterized by positive elevation differences) and quarry area management (debris disposal and service infrastructure construction, characterized by negative elevation differences). The combined use of 2D and 3D change indicators can be challenging in order to correctly represent soil consumption over the years. A dual 2D/3D webgis client have been developed for proper representation of 2D/3D spatial indicators of ongoing extraction activities in the Carrara marble basin: high-resolution images have been served as tiled data, while 2D/3D spatial indicators are served as static and/or tiled vector data. Open-Source libraries have used in data processing, serving and representation inside a map interface.

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“…The potential of seed-dispersing birds to assist revegetation of degraded areas by mining or quarrying activities remains overlooked, since interactions between bird and plant communites in restored areas are poorly understood (Šálek, 2012 ;Makoto & Wilson, 2018). Seed dispersal services are highly sensitive to human disturbance (Neuschulz et al, 2016), and the evaluation of such services offers evidence on ecosystem integrity as an indicator of suitable restoration practices (García et al, 2010;Zhang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%