23.2.19 Soil Heavy Metal Contamination

Chapter Contents (Back)
Heavy Metals. Soil Properties.

Peng, Y.[Yi], Kheir, R.B.[Rania Bou], Adhikari, K.[Kabindra], Malinowski, R.[Radoslaw], Greve, M.B.[Mette B.], Knadel, M.[Maria], Greve, M.H.[Mogens H.],
Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data,
RS(8), No. 12, 2016, pp. 1003.
DOI Link 1612
BibRef

Zhou, G.X.[Gao-Xiang], Liu, X.N.[Xiang-Nan], Zhao, S.[Shuang], Liu, M.[Ming], Wu, L.[Ling],
Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Zhang, B.Y.[Bi-Yao], Liu, X.N.[Xiang-Nan], Liu, M.L.[Mei-Ling], Meng, Y.Y.[Yuan-Yuan],
Detection of Rice Phenological Variations under Heavy Metal Stress by Means of Blended Landsat and MODIS Image Time Series,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Wang, F.[Fenghe], Gao, J.[Jay], Zha, Y.[Yong],
Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges,
PandRS(136), 2018, pp. 73-84.
Elsevier DOI 1802
Heavy metal contamination, Hyperspectral sensing, Analytical modelling, Partial least squares regression, Vegetation indexing BibRef

Lim, J., Yu, J., Wang, L., Jeong, Y., Shin, J.H.,
Heavy Metal Contamination Index Using Spectral Variables for White Precipitates Induced by Acid Mine Drainage: A Case Study of Soro Creek, South Korea,
GeoRS(57), No. 7, July 2019, pp. 4870-4888.
IEEE DOI 1907
Contamination, Pollution measurement, Iron, Sediments, Indexes, Minerals, Heavy metal contamination, mineral composition, white precipitate BibRef

Liu, Z.H.[Zhen-Hua], Lu, Y.[Ying], Peng, Y.P.[Yi-Ping], Zhao, L.[Li], Wang, G.X.[Guang-Xing], Hu, Y.M.[Yue-Ming],
Estimation of Soil Heavy Metal Content Using Hyperspectral Data,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
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Shin, H., Yu, J., Wang, L., Jeong, Y., Kim, J.,
Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils,
GeoRS(58), No. 4, April 2020, pp. 2266-2275.
IEEE DOI 2004
Soil, Moisture, Contamination, Pollution measurement, Zinc, Minerals, Heavy metal contaminated soil, moisture content, spectral interference BibRef

Taghizadeh-Mehrjardi, R.[Ruhollah], Fathizad, H.[Hassan], Ardakani, M.A.H.[Mohammad Ali Hakimzadeh], Sodaiezadeh, H.[Hamid], Kerry, R.[Ruth], Heung, B.[Brandon], Scholten, T.[Thomas],
Spatio-Temporal Analysis of Heavy Metals in Arid Soils at the Catchment Scale Using Digital Soil Assessment and a Random Forest Model,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
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Kim, H.[Hyesu], Yu, J.[Jaehyung], Wang, L.[Lei], Jeong, Y.[Yongsik], Kim, J.[Jieun],
Variations in Spectral Signals of Heavy Metal Contamination in Mine Soils Controlled by Mineral Assemblages,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
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Chen, G.Q.[Guo-Qing], Yang, Y.[Yong], Liu, X.[Xinyao], Wang, M.J.[Ming-Jiu],
Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Sun, Y.L.[Yan-Long], Qian, X.M.[Xin-Ming], Liu, Y.Y.[Yang-Yang], Wang, J.W.[Jian-Wei], Lv, Q.[Qunbo], Yuan, M.Q.[Meng-Qi],
Identification of Typical Solid Hazardous Chemicals Based on Hyperspectral Imaging,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Xu, X.T.[Xi-Tong], Chen, S.B.[Sheng-Bo], Ren, L.G.[Li-Guo], Han, C.[Cheng], Lv, D.L.[Dong-Lin], Zhang, Y.F.[Yu-Feng], Ai, F.[Fukai],
Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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Tu, Y.L.[Yu-Long], Zou, B.[Bin], Feng, H.H.[Hui-Hui], Zhou, M.[Mo], Yang, Z.H.[Zhi-Hui], Xiong, Y.[Ying],
A Near Standard Soil Samples Spectra Enhanced Modeling Strategy for Cd Concentration Prediction,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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Mouazen, A.M.[Abdul M.], Nyarko, F.[Felix], Qaswar, M.[Muhammad], Tóth, G.[Gergely], Gobin, A.[Anne], Moshou, D.[Dimitrios],
Spatiotemporal Prediction and Mapping of Heavy Metals at Regional Scale Using Regression Methods and Landsat 7,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Huang, Z.Q.[Zhao-Qiang], Huang, W.X.[Wen-Xuan], Li, S.[Sheng], Ni, B.[Bin], Zhang, Y.[Yalong], Wang, M.W.[Ming-Wei], Chen, M.L.[Mao-Lin], Zhu, F.[Fuxiao],
Inversion Evaluation of Rare Earth Elements in Soil by Visible-Shortwave Infrared Spectroscopy,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Khosravi, V.[Vahid], Ardejani, F.D.[Faramarz Doulati], Gholizadeh, A.[Asa], Saberioon, M.[Mohammadmehdi],
Satellite Imagery for Monitoring and Mapping Soil Chromium Pollution in a Mine Waste Dump,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhao, D.[Danyun], Xie, D.[Danni], Yin, F.[Fang], Liu, L.[Lei], Feng, J.[Jilu], Ashraf, T.[Tariq],
Estimation of Pb Content Using Reflectance Spectroscopy in Farmland Soil near Metal Mines, Central China,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Zeng, L.[Ling], Jiang, S.[Shan], Jing, L.H.[Lin-Hai], Xue, Y.[Yuan],
Source Apportionment of Heavy Metal Contamination in Urban-Agricultural-Aquacultural Soils near the Bohai Bay Coast, Using Land-Use Classification and Google Satellite Tracing,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
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Fang, Y.[Yuan], Xu, L.L.[Lin-Lin], Wong, A.[Alexander], Clausi, D.A.[David A.],
Multi-Temporal Landsat-8 Images for Retrieval and Broad Scale Mapping of Soil Copper Concentration Using Empirical Models,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
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Chen, M.[Mulin], Cai, H.Y.[Hong-Yan], Wang, L.[Li], Lei, M.[Mei],
Grid-Scale Regional Risk Assessment of Potentially Toxic Metals Using Multi-Source Data,
IJGI(11), No. 8, 2022, pp. xx-yy.
DOI Link 2209
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Guo, B.[Bin], Guo, X.[Xianan], Zhang, B.[Bo], Suo, L.[Liang], Bai, H.[Haorui], Luo, P.P.[Ping-Ping],
Using a Two-Stage Scheme to Map Toxic Metal Distributions Based on GF-5 Satellite Hyperspectral Images at a Northern Chinese Opencast Coal Mine,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Chalkley, R.[Richard], Crane, R.A.[Rich Andrew], Eyre, M.[Matthew], Hicks, K.[Kathy], Jackson, K.M.[Kim-Marie], Hudson-Edwards, K.A.[Karen A.],
A Multi-Scale Feasibility Study into Acid Mine Drainage (AMD) Monitoring Using Same-Day Observations,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Tang, T.[Ting], Chen, C.[Canming], Wu, W.B.[Wei-Bin], Zhang, Y.[Ying], Han, C.Y.[Chong-Yang], Li, J.[Jie], Gao, T.[Ting], Li, J.[Jiehao],
Hyperspectral Inversion Model of Relative Heavy Metal Content in Pennisetum sinese Roxb via EEMD-db3 Algorithm,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Kimijima, S.[Satomi], Nagai, M.[Masahiko], Sakakibara, M.[Masayuki],
Distribution of Enhanced Potentially Toxic Element Contaminations Due to Natural and Coexisting Gold Mining Activities Using Planet Smallsat Constellations,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Wen, Q.Q.[Qi-Qian], Yang, L.S.[Lin-Sheng], Yu, J.P.[Jiang-Ping], Wei, B.G.[Bing-Gan], Yin, S.H.[Shu-Hui],
Sources and Risk Characteristics of Heavy Metals in Plateau Soils Predicted by Geo-Detectors,
RS(15), No. 6, 2023, pp. 1588.
DOI Link 2304
BibRef

Suleymanov, A.[Azamat], Suleymanov, R.[Ruslan], Kulagin, A.[Andrey], Yurkevich, M.[Marija],
Mercury Prediction in Urban Soils by Remote Sensing and Relief Data Using Machine Learning Techniques,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
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Wu, Y.T.[Ya-Ting], Zhou, L.F.[Ling-Feng], Meng, Y.B.[Yao-Bin], Lin, Q.[Qigen], Fei, Y.[Yang],
Influential Topographic Factor Identification of Soil Heavy Metals Using GeoDetector: The Effects of DEM Resolution and Pollution Sources,
RS(15), No. 16, 2023, pp. 4067.
DOI Link 2309
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Zheng, M.[Meiduan], Luan, H.J.[Hai-Jun], Liu, G.S.[Guang-Sheng], Sha, J.M.[Jin-Ming], Duan, Z.[Zheng], Wang, L.[Lanhui],
Ground-Based Hyperspectral Retrieval of Soil Arsenic Concentration in Pingtan Island, China,
RS(15), No. 17, 2023, pp. 4349.
DOI Link 2310
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Nogueira, P.[Pedro], Silva, M.[Marcelo], Roseiro, J.[José], Potes, M.[Miguel], Rodrigues, G.[Gonçalo],
Mapping the Mine: Combining Portable X-ray Fluorescence, Spectroradiometry, UAV, and Sentinel-2 Images to Identify Contaminated Soils: Application to the Mostardeira Mine (Portugal),
RS(15), No. 22, 2023, pp. 5295.
DOI Link 2311
BibRef


Ech-Chafay, H., Najy, M., El Ghazouany, A., Akkaoui, O., Lachhab, M., Belghyti, D.,
Evaluation of the Heavy Metals Contamination of the Water of The Moulouya Medium,
SmartCityApp21(193-196).
DOI Link 2201
BibRef

Oyunbat, P., Batkhishig, O., Batsaikhan, B., Lehmkuhl, F., Knippertz, M., Nottebaum, V.,
Spatial Distribution, Pollution, and Health Risk Assessment of Heavy Metal In Industrial Area Soils of Ulaanbaatar, Mongolia,
ISPRS21(B4-2021: 123-133).
DOI Link 2201
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Chen, L., Tan, K.,
Estimation of Soil Heavy Metal Combining Fractional Order Derivative,
ISPRS20(B3:1439-1444).
DOI Link 2012
BibRef

Lee, M., Chen, X.Y., Lee, H.C.,
Spectral Preprocessing for Hyperspectral Remote Sensing of Heavy Metals In Water,
HyperMLPA19(1869-1873).
DOI Link 1912
BibRef

Chen, X., Lee, H., Lee, M.,
Feasibility of Using Hyperspectral Remote Sensing for Environmental Heavy Metal Monitoring,
Environmental19(1-4).
DOI Link 1904
water quality monitoring. BibRef

Wang, P., Huang, F., Liu, X.N.,
A Simple Interpretation Of The Rice Spectral Indices Space For Assessment Of Heavy Metal Stress,
ISPRS16(B7: 129-135).
DOI Link 1610
BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Other Soil Properties, Remote Sensing .


Last update:Mar 16, 2024 at 20:36:19