The Impact of Opencast Lignite Mining on Rural Development: A Literature Review and Selected Case Studies Using Desk Research, Panel Data and GIS-Based Analysis

Maciejewska, Anna; Kuzak, Łukasz; Sobieraj, Janusz; Metelski, Dominik

doi:10.3390/en15155402

Cited by 10 publications

(8 citation statements)

References 45 publications

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“…By elucidating dose-dependent effects and long-term soil dynamics, this research contributes to a deeper understanding of soil responses to organic amendments. Moreover, the study resonates with broader soil science discourse, aligning with existing knowledge on soil fertility, humic substances [18], and lignite's multifunctional role in sustainable agriculture [77][78][79][80].…”

Section: Discussionmentioning

confidence: 66%

Assessing the Impact of Lignite-Based Rekulter Fertilizer on Soil Sustainability: A Comprehensive Field Study

Maciejewska,

Sobieraj,

Metelski

2024

Sustainability

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This study aimed to investigate the impact of Rekulter, a lignite-based fertilizer, on various soil parameters, with a focus on promoting sustainable agricultural practices. A multi-year field trial was conducted in Klon, Poland, employing potentiometric techniques, spectrophotometry, and gas chromatography-mass spectrometry to analyze soil samples. Established laboratory procedures were used to assess pH value, sorption properties, granulometric composition, organic carbon content (OC), total nitrogen (TN), polycyclic aromatic hydrocarbons (PAHs), phenolic compounds (PCs), and the fractional composition of organic matter. Hypothesis-driven experiments, including Analysis of Variance (ANOVA) and Tukey’s HSD post hoc tests, were utilized to examine the effects of Rekulter application on soil characteristics. Significant differences were found in organic carbon (OC), total nitrogen (TN), polycyclic aromatic hydrocarbons (PAHs), phenolic compounds (PCs), and fractional organic matter composition among the Rekulter variants. This study underscores the dose-dependent effects of Rekulter on soil properties and provides insights into optimizing application rates for sustainable soil management. Recommendations include tailoring agricultural interventions based on soil characteristics and environmental considerations, integrating organic amendments with mineral fertilizers, and promoting balanced approaches to reclamation. This research contributes to ongoing efforts to improve agricultural sustainability and mitigate environmental impacts, guiding practices that balance productivity with environmental stewardship.

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Section: Discussionmentioning

confidence: 66%

Assessing the Impact of Lignite-Based Rekulter Fertilizer on Soil Sustainability: A Comprehensive Field Study

Maciejewska,

Sobieraj,

Metelski

2024

Sustainability

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“…In the case of Warsaw, the subject of such a study is the Słu żewiecki [5,8] stream catchment in the southern part of Warsaw. One of the methods of estimating impervious surfaces of large-scale projects can be high-resolution remote sensing aerial photographs covering the near-infrared range and mapping the NDVI [74]. This is because vegetation in near-infrared imagery has a relatively high reflectance, which in turn can be very well represented by the NDVI index.…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Different Machine Learning Algorithms in the Classification of Impervious Surfaces: Case Study of the Housing Estate Fort Bema in Warsaw (Poland)

2022

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The aim of this study is to extract impervious surfaces and show their spatial distribution, using different machine learning algorithms. For this purpose, geoprocessing and remote sensing techniques were used and three classification methods for digital images were compared, namely Support Vector Machines (SVM), Maximum Likelihood (ML) and Random Trees (RT) classifiers. The study area is one of the most prestigious and the largest housing estates in Warsaw (Poland), the Fort Bema housing complex, which is also an exemplary model for hydrological solutions. The study was prepared on the Geographic Information System platform (GIS) using aerial optical images, orthorectified and thus provided with a suitable coordinate system. The use of these data is therefore supported by the accuracy of the resulting infrared channel product with a pixel size of 0.25 m, making the results much more accurate compared to satellite imagery. The results of the SVM, ML and RT classifiers were compared using the confusion matrix, accuracy (Root Mean Square Error /RMSE/) and kappa index. This showed that the three algorithms were able to successfully discriminate between targets. Overall, the three classifiers had errors, but specifically for impervious surfaces, the highest accuracy was achieved with the SVM classifier (the highest percentage of overall accuracy), followed by ML and RT with 91.51%, 91.35% and 84.52% of the results, respectively. A comparison of the visual results and the confusion matrix shows that although visually the RT method appears to be the most detailed classification into pervious and impervious surfaces, the results were not always correct, e.g., water/shadow was detected as an impervious surface. The NDVI index was also mapped for the same spatial study area and its application in the evaluation of pervious surfaces was explained. The results obtained with the GIS platform, presented in this paper, provide a better understanding of how these advanced classifiers work, which in turn can provide insightful guidance for their selection and combination in real-world applications. The paper also provides an overview of the main works/studies dealing with impervious surface mapping, with different methods for their assessment (including the use of conventional remote sensing, NDVI, multisensory and cross-source data, ‘social sensing’ and classification methods such as SVM, ML and RT), as well as an overview of the research results.

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“…Furthermore, desk research analysis includes testing, processing, and evaluating data collected from official sources (Maciejewska et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Impact of the US-China Trade War on Foreign Trade of Emerging Economies: Brazil, South Africa, and Indonesia

Kurniawan,

Rizal Luthfi

2023

JSP

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The study analyses the potential impacts of the US-China trade war on the foreign trade of emerging economies, i.e., Indonesia, Brazil, and South Africa, and their foreign economic policies to obtain alternative markets outside the US and China. These countries were chosen because they have similar industrial characteristics and robust commercial relationships with the US and China. This study uses desk review approach and secondary data analysis from the International Trade Center (ITC) Database, the WTO Tariff Database, and the Peterson Institute of International Economics (PIIE). The impacts were portrayed in several views: triangular trade structure, global value chain, China+1, and Global South relationship. In the context of a triangular trade structure with China as the mediator, Indonesia’s and Brazil's trade was relatively secure since they exported considerable natural resources to China. At the same time, they could maintain positive trade performance with the US and China owing to the global value chain. South Africa has extensive imports of intermediate goods from the US and China, mainly for the automotive sector and further processed for the African market. However, since the significant position of the US as a trading partner, Indonesia, Brazil, and South Africa were potentially exposed to protectionism behavior. Indonesia benefits significantly from the US General System Preferences (GSP) trade facilities for developing countries. The consistent trade surplus has raised critical concerns from the US government regarding Indonesian exports. Therefore, the escalation has also enhanced cooperation in the Global South, including the Brazil-led Mercosur free trade negotiation with Singapore and Indonesia's preferential trade agreement with Pakistan and Bangladesh.

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The Impact of Opencast Lignite Mining on Rural Development: A Literature Review and Selected Case Studies Using Desk Research, Panel Data and GIS-Based Analysis

Cited by 10 publications

References 45 publications

Assessing the Impact of Lignite-Based Rekulter Fertilizer on Soil Sustainability: A Comprehensive Field Study

Assessing the Impact of Lignite-Based Rekulter Fertilizer on Soil Sustainability: A Comprehensive Field Study

A Comparison of Different Machine Learning Algorithms in the Classification of Impervious Surfaces: Case Study of the Housing Estate Fort Bema in Warsaw (Poland)

Impact of the US-China Trade War on Foreign Trade of Emerging Economies: Brazil, South Africa, and Indonesia

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