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
BibRef
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
BibRef
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
BibRef
Chen, G.Q.[Guo-Qing],
Yang, Y.[Yong],
Liu, X.Y.[Xin-Yao],
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
Carvalho, M.[Morgana],
Cardoso-Fernandes, J.[Joana],
Lima, A.[Alexandre],
Teodoro, A.C.[Ana C.],
Convolutional Neural Networks Applied to Antimony Quantification via
Soil Laboratory Reflectance Spectroscopy in Northern Portugal:
Opportunities and Challenges,
RS(16), No. 11, 2024, pp. 1964.
DOI Link
2406
BibRef
Guo, F.[Fei],
Xu, Z.[Zhen],
Ma, H.[Honghong],
Liu, X.J.[Xiu-Jin],
Gao, L.[Lei],
On Optimizing Hyperspectral Inversion of Soil Copper Content by
Kernel Principal Component Analysis,
RS(16), No. 16, 2024, pp. 2914.
DOI Link
2408
BibRef
Lovynska, V.[Viktoriia],
Bayat, B.[Bagher],
Bol, R.[Roland],
Moradi, S.[Shirin],
Rahmati, M.[Mehdi],
Raj, R.[Rahul],
Sytnyk, S.[Svitlana],
Wiche, O.[Oliver],
Wu, B.[Bei],
Montzka, C.[Carsten],
Monitoring Heavy Metals and Metalloids in Soils and Vegetation by
Remote Sensing: A Review,
RS(16), No. 17, 2024, pp. 3221.
DOI Link
2409
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
BibRef
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 .