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Research Article
Statistical Analysis of Oversize, Slimes, and Heavy Mineral Fractions of the Ranobe Mineral Sands Deposit (Atsimo-Andrefana Region, Madagascar)
Ria Raonison*
,
Tsiorisoa Harempahasoavana,
Théodore Razakamanana
Issue:
Volume 15, Issue 5, October 2026
Pages:
216-223
Received:
10 August 2026
Accepted:
22 August 2026
Published:
9 September 2026
Abstract: This study presents an exploratory statistical analysis of oversize (OS), slimes (SL), and heavy mineral (HM) fractions from 598 deep drilling samples collected across the Ranobe mineral sands deposit, located within the Atsimo-Andrefana region of southwestern Madagascar. Robust descriptive statistical methods and exploratory graphical analyses were employed to quantitatively characterize the spatial distributions, central tendencies, and inherent heterogeneities of these mineralized coastal formations. The structural results indicate a clear dominance of the HM fraction, which features a remarkably stable distribution centered around a high median value of 4.80%. This pattern strongly implies the persistent influence of highly efficient regional enrichment processes driven by hydraulic sorting and gravity concentration dynamics in a moderate-energy beach environment. Conversely, the fine-grained SL fraction exhibits a significantly wider dispersion and pronounced sample-to-sample variability (median of 3.33%, standard deviation of 11.64%), reflecting active hydrodynamic fluctuations and episodic inputs of suspended fine particles during deposition. The coarse OS fraction remains virtually negligible across the vast majority of analyzed samples, maintaining a median of 0%. Bivariate correlation assessments reveal a moderate positive coupling between the OS and SL phases (r ≈ 0.48), whereas their respective linear relationships with heavy minerals are remarkably weak or negative r OS-HM ≈ -0.07; r SL-HM ≈ -0.17). These statistical outputs demonstrate that heavy mineral concentration is entirely decoupled from primary grain-size metrics. Consequently, future operational campaigns must evaluate the economic potential of the Ranobe orebody using independent spatial models.
Abstract: This study presents an exploratory statistical analysis of oversize (OS), slimes (SL), and heavy mineral (HM) fractions from 598 deep drilling samples collected across the Ranobe mineral sands deposit, located within the Atsimo-Andrefana region of southwestern Madagascar. Robust descriptive statistical methods and exploratory graphical analyses wer...
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Research Article
GIS-Based Mapping and Geodatabase Development for Expansive Soils: A Case Study of Selected Towns in the Wolaita Zone, Southern Ethiopia
Issue:
Volume 15, Issue 5, October 2026
Pages:
224-233
Received:
27 September 2026
Accepted:
8 October 2026
Published:
23 October 2026
Abstract: Expansive soils cause costly damage to infrastructure through seasonal moisture-driven swelling and shrinkage, yet in many developing regions the geotechnical data needed to manage this hazard remains fragmented across paper records and individual project reports. This study addresses that gap by evaluating the engineering properties of expansive soils in three rapidly urbanizing towns in the Wolaita Zone of southern Ethiopia, namely Tebela, Wolaita Sodo, and Boditi, and consolidating the results into a spatially referenced ArcGIS geodatabase to support preliminary engineering design. Fourteen test pits were investigated following ASTM and AASHTO standards, combining ten newly collected field samples with four secondary data sources; index and strength properties, including Atterberg limits, free swell index, swelling pressure, and California Bearing Ratio, were determined in the laboratory, and all test-pit locations were captured by GPS and georeferenced onto rectified imagery in UTM Zone 37N. The results classified the soils at Tebela and Wolaita Sodo as highly plastic clays (CH, AASHTO A-7-5) with high fines contents of 91.8 to 95.1%, free swell indices exceeding 100%, and swelling pressures of 145 to 170 kPa, while the Boditi soils were similarly classified as high-plasticity clays (CH, A-7-6) but showed low California Bearing Ratio values of 2.2 to 2.8%, indicating weak subgrade support. These laboratory results, together with the GPS coordinates, were structured in an ArcGIS file geodatabase organized by town and test pit, with fully searchable laboratory attributes. The resulting system converts scattered paper-based geotechnical records into an interactive, query able geospatial tool and offers an adaptable workflow that can be extended to manage expansive soil risk in other regions facing similar infrastructural and data-management challenges.
Abstract: Expansive soils cause costly damage to infrastructure through seasonal moisture-driven swelling and shrinkage, yet in many developing regions the geotechnical data needed to manage this hazard remains fragmented across paper records and individual project reports. This study addresses that gap by evaluating the engineering properties of expansive s...
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Research Article
Monitoring of Open-pit Mining Disturbance and Restoration Using GEE-LandTrendr: A Case Study of Huolinhe Coalfield in Inner Mongolia, China
Issue:
Volume 15, Issue 5, October 2026
Pages:
234-246
Received:
6 October 2026
Accepted:
15 October 2026
Published:
28 October 2026
DOI:
10.11648/j.earth.20261505.13
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Abstract: Increasing open-pit mining is considered to have a remarkable impact on the regional ecological environments due to drastic surface excavation and vegetation damage, therefore there is an urgent need for large-scale disturbance monitoring and restoration effect evaluation. Taking the Huolinhe Mining Coalfield as an example, this study employed the LandTrendr algorithm integrated with the Google Earth Engine (GEE) platform to detect mining disturbances and vegetation recovery using the Normalized Difference Vegetation Index (NDVI) calculated from long-term Landsat images. The results show that: (1) the extent of mining disturbance expanded before 2010 and remained broadly stable until 2017, after which it decreased following the implementation of the restoration project from 2018 onwards. (2) Breakpoints were identified in all years within the study period, and the detection rate for mining-disturbed areas exceeded 96% in the validation years of 2000, 2010, 2017, and 2021. (3) Vegetation recovery started in two periods, 2010-2012 and 2017-2019, the earlier period followed the severe drought of 2010 and is attributed to natural recovery, whereas the larger latter period coincided with the implementation of artificial restoration projects. (4) A lag of approximately one growing season was found between the implementation of reclamation engineering and the first detectable vegetation recovery, so that detection in the implementation year identified only 14.9% to 30.0% of the implemented restoration area, whereas a one year lag adjustment increased the value to 70.0% to 85.1%. (5) NDVI increased in the mining area between 2017 and 2022, and the increase was spatially concentrated in the restoration project area, which is consistent with a positive vegetation-cover response associated with the restoration projects. The results indicate that LandTrendr is an effective tool in change detection and can support rapid identification of large-scale disturbance in mining areas. The results provide a basis for subsequent monitoring of vegetation cover and for the sustainable development of a typical mining area, and they define the conditions under which annual mining-disturbance monitoring can be interpreted at face value.
Abstract: Increasing open-pit mining is considered to have a remarkable impact on the regional ecological environments due to drastic surface excavation and vegetation damage, therefore there is an urgent need for large-scale disturbance monitoring and restoration effect evaluation. Taking the Huolinhe Mining Coalfield as an example, this study employed the ...
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