Using Optimized Spectral Indices and Machine Learning Algorithms to Assess Soil Copper Concentration in Mining Areas
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Gerald Forkuor & Ozias K L Hounkpatin & Gerhard Welp & Michael Thiel, 2017. "High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-21, January.
- Peroni Venancio, Luan & Chartuni Mantovani, Everardo & do Amaral, Cibele Hummel & Usher Neale, Christopher Michael & Zution Gonçalves, Ivo & Filgueiras, Roberto & Coelho Eugenio, Fernando, 2020. "Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction," Agricultural Water Management, Elsevier, vol. 236(C).
- Qing Zhong & Mamattursun Eziz & Rukeya Sawut & Mireguli Ainiwaer & Haoran Li & Liling Wang, 2023. "Application of a Hyperspectral Remote Sensing Model for the Inversion of Nickel Content in Urban Soil," Sustainability, MDPI, vol. 15(18), pages 1-14, September.
- Cheng Han & Jilong Lu & Shengbo Chen & Xitong Xu & Zibo Wang & Zheng Pei & Yu Zhang & Fengxuan Li, 2021. "Estimation of Heavy Metal(Loid) Contents in Agricultural Soil of the Suzi River Basin Using Optimal Spectral Indices," Sustainability, MDPI, vol. 13(21), pages 1-21, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Guillermo Martínez Pastur & Marie-Claire Aravena Acuña & Jimena E. Chaves & Juan M. Cellini & Eduarda M. O. Silveira & Julián Rodriguez-Souilla & Axel von Müller & Ludmila La Manna & María V. Lencinas, 2023. "Nitrogenous and Phosphorus Soil Contents in Tierra del Fuego Forests: Relationships with Soil Organic Carbon, Climate, Vegetation and Landscape Metrics," Land, MDPI, vol. 12(5), pages 1-18, April.
- Jules Degila & Ida Sèmévo Tognisse & Anne-Carole Honfoga & Sèton Calmette Ariane Houetohossou & Fréjus Ariel Kpedetin Sodedji & Hospice Gérard Gracias Avakoudjo & Souand Peace Gloria Tahi & Achille Ep, 2023. "A Survey on Digital Agriculture in Five West African Countries," Agriculture, MDPI, vol. 13(5), pages 1-15, May.
- Kingsley JOHN & Isong Abraham Isong & Ndiye Michael Kebonye & Esther Okon Ayito & Prince Chapman Agyeman & Sunday Marcus Afu, 2020. "Using Machine Learning Algorithms to Estimate Soil Organic Carbon Variability with Environmental Variables and Soil Nutrient Indicators in an Alluvial Soil," Land, MDPI, vol. 9(12), pages 1-20, December.
- Showmitra Kumar Sarkar & Saifullah Bin Ansar & Khondaker Mohammed Mohiuddin Ekram & Mehedi Hasan Khan & Swapan Talukdar & Mohd Waseem Naikoo & Abu Reza Towfiqul Islam & Atiqur Rahman & Amir Mosavi, 2022. "Developing Robust Flood Susceptibility Model with Small Numbers of Parameters in Highly Fertile Regions of Northwest Bangladesh for Sustainable Flood and Agriculture Management," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
- Zhihui Li & Yang Yang & Siyu Gu & Boyu Tang & Jing Zhang, 2021. "Research on the Prediction of Several Soil Properties in Heihe River Basin Based on Remote Sensing Images," Sustainability, MDPI, vol. 13(24), pages 1-14, December.
- Kangbéni Dimobe & Jean Léandre N’djoré Kouakou & Jérôme E. Tondoh & Benewinde J.-B. Zoungrana & Gerald Forkuor & Korotimi Ouédraogo, 2018. "Predicting the Potential Impact of Climate Change on Carbon Stock in Semi-Arid West African Savannas," Land, MDPI, vol. 7(4), pages 1-21, October.
- Shiny Abraham & Chau Huynh & Huy Vu, 2019. "Classification of Soils into Hydrologic Groups Using Machine Learning," Data, MDPI, vol. 5(1), pages 1-14, December.
- Chenxia Hu & Alan L Wright & Gang Lian, 2019. "Estimating the Spatial Distribution of Soil Properties Using Environmental Variables at a Catchment Scale in the Loess Hilly Area, China," IJERPH, MDPI, vol. 16(3), pages 1-14, February.
- Ramalingam Kumaraperumal & Sellaperumal Pazhanivelan & Vellingiri Geethalakshmi & Moorthi Nivas Raj & Dhanaraju Muthumanickam & Ragunath Kaliaperumal & Vishnu Shankar & Athira Manikandan Nair & Manoj , 2022. "Comparison of Machine Learning-Based Prediction of Qualitative and Quantitative Digital Soil-Mapping Approaches for Eastern Districts of Tamil Nadu, India," Land, MDPI, vol. 11(12), pages 1-26, December.
- Gonçalves, I.Z. & Ruhoff, A. & Laipelt, L. & Bispo, R.C. & Hernandez, F.B.T. & Neale, C.M.U. & Teixeira, A.H.C. & Marin, F.R., 2022. "Remote sensing-based evapotranspiration modeling using geeSEBAL for sugarcane irrigation management in Brazil," Agricultural Water Management, Elsevier, vol. 274(C).
- Fuat Kaya & Gaurav Mishra & Rosa Francaviglia & Ali Keshavarzi, 2023. "Combining Digital Covariates and Machine Learning Models to Predict the Spatial Variation of Soil Cation Exchange Capacity," Land, MDPI, vol. 12(4), pages 1-20, April.
- Sumin Park & Haemi Park & Jungho Im & Cheolhee Yoo & Jinyoung Rhee & Byungdoo Lee & ChunGeun Kwon, 2019. "Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-23, October.
- Jasmina Defterdarović & Lana Filipović & Filip Kranjčec & Gabrijel Ondrašek & Diana Kikić & Alen Novosel & Ivan Mustać & Vedran Krevh & Ivan Magdić & Vedran Rubinić & Igor Bogunović & Ivan Dugan & Kre, 2021. "Determination of Soil Hydraulic Parameters and Evaluation of Water Dynamics and Nitrate Leaching in the Unsaturated Layered Zone: A Modeling Case Study in Central Croatia," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
- Fatemeh Sadat Hosseini & Myoung Bae Seo & Seyed Vahid Razavi-Termeh & Abolghasem Sadeghi-Niaraki & Mohammad Jamshidi & Soo-Mi Choi, 2023. "Geospatial Artificial Intelligence (GeoAI) and Satellite Imagery Fusion for Soil Physical Property Predicting," Sustainability, MDPI, vol. 15(19), pages 1-25, September.
- Wu Xiao & Wenqi Chen & Tingting He & Linlin Ruan & Jiwang Guo, 2020. "Multi-Temporal Mapping of Soil Total Nitrogen Using Google Earth Engine across the Shandong Province of China," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
- Fahao Wang & Weidong Lu & Jingyun Zheng & Shicheng Li & Xuezhen Zhang, 2020. "Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000," Sustainability, MDPI, vol. 12(3), pages 1-16, February.
- Mi Tian & Chao Wu & Xin Zhu & Qinghai Hu & Xueqiu Wang & Binbin Sun & Jian Zhou & Wei Wang & Qinghua Chi & Hanliang Liu & Yuheng Liu & Jiwu Yang & Xurong Li, 2024. "Spatial–Temporal Variations in Soil Organic Carbon and Driving Factors in Guangdong, China (2009–2023)," Land, MDPI, vol. 13(7), pages 1-18, July.
- Nausheen Mazhar & Safdar Ali Shirazi, 2023. "Community perceptions of the impacts of desertification as related to adaptive capacity in drylands of South Punjab, Pakistan," Asia-Pacific Journal of Regional Science, Springer, vol. 7(2), pages 549-568, June.
- Clement Nyamekye & Michael Thiel & Sarah Schönbrodt-Stitt & Benewinde J.-B. Zoungrana & Leonard K. Amekudzi, 2018. "Soil and Water Conservation in Burkina Faso, West Africa," Sustainability, MDPI, vol. 10(9), pages 1-24, September.
- Seyedalireza Khatibi & Azadeh Aghajanpour, 2020. "Machine Learning: A Useful Tool in Geomechanical Studies, a Case Study from an Offshore Gas Field," Energies, MDPI, vol. 13(14), pages 1-16, July.
More about this item
Keywords
soil Cu concentration; machine learning; optimized two- and three-band spectral indices (Opt-TBIs); hyperspectral monitoring technique; soil environmental protection;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4153-:d:1395347. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.