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Original Articles

Current development of landscape geochemistry with support of geospatial technologies: A review

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 745-790 | Published online: 17 Jan 2019

References

  • Adiri, Z., Harti, A., Jellouli, A., Maacha, L., & Bachaoui, E. (2016). Lithological mapping using Landsat 8 OLI and Terra ASTER multispectral data in the Bas Draa inlier, Moroccan Anti Atlas. Journal of Applied Remote Sensing, 10(1), 016005. doi:10.1117/1.JRS.10.016005
  • Afzal, P., Alghalandis, Y. F., Khakzad, A., Moarefvand, P., & Omran, N. R. (2011). Delineation of mineralization zones in porphyry Cu deposits by fractal concentration–volume modeling. Journal of Geochemical Exploration, 108, 220–232. doi:10.1016/j.gexplo.2011.03.005
  • Afzal, P., Fadakar, A. Y., Moarefvand, P., Rashidnejad, O. N., & Asadi, H. (2012). Application of power-spectrum–volume fractal method for detecting hypogene, supergene enrichment, leached and barren zones in Kahang Cu porphyry deposit, Central Iran. Journal of Geochemical Exploration, 112, 131–138. doi:10.1016/j.gexplo.2011.08.002
  • Afzal, P., Harati, H., Fadakar, A. Y., & Yasrebi, A. B. (2013). Application of spectrum–area fractal model to identify of geochemical anomalies based on soil data in Kahang porphyry–type Cu deposit, Iran. Chemie der Erde, 73, 533–543. doi:10.1016/j.chemer.2013.08.001
  • Afzal, P., Khakzad, A., Moarefvand, P., Rashidnejad, O. N., Esfandiari, B., & Fadakar, A. Y. (2010). Geochemical anomaly separation by multifractal modeling in Kahang (GorGor) porphyry system, Central Iran. Journal of Geochemical Exploration, 104(1–2), 34–46.
  • Afzal, P., Mirzaei, M., Yousefi, M., Adib, A., Khalajmasoumi, M., Zarifi, A. Z., … Yasrebi, A. B. (2016). Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis. Journal of African Earth Sciences, 119, 139–149. doi:10.1016/j.jafrearsci.2016.03.009
  • Ahamed, T. R. N., Rao, K. G., & Murthy, J. S. R. (2000). GIS-based fuzzy membership model for crop-land suitability analysis. Agricultural Systems, 63, 75–95. doi:10.1016/S0308-521X(99)00036-0
  • Airola, T. M. (1990). Monitoring the impact of arsenic contamination on forest vegetation in New-Jersey using remote-sensing techniques. Journal of Imaging Technology, 16, 120–123.
  • Alam, B. M. (2012). Application of geographic information systems. London, UK: InTech.
  • Albanese, S., De Vivo, B., Lima, A., & Cicchella, D. (2007). Geochemical background and baseline values of toxic elements in stream sediments of Campania region (Italy). Journal of Geochemical Exploration, 93(1), 21–34. doi:10.1016/j.gexplo.2006.07.006
  • Alexis, S., García-Montero, L. G., Hernández, A. J., García-Abril, A., & Pastor, J. (2010). Soil fertility and GIS raster models for tropical agroforestry planning in economically depressed and contaminated Caribbean areas (coffee and kidney bean plantations). Agroforestry Systems, 79, 381–391. doi:10.1007/s10457-009-9263-5
  • Ali, K. H., Cheng, Q., & Zhijun, C. (2007). Multifractal power spectrum and singularity analysis for modelling stream sediment geochemical distribution patterns to identify anomalies related to gold mineralization in Yunnan Province, South China. Geochemistry: Exploration, Environment, Analysis, 7, 293–301. doi:10.1144/1467-7873/06-116
  • Ali, L., Moon, C. J., Williamson, B., Shah, M. T., & Khattak, S. A. (2015). A GIS-based stream sediment geochemical model for gold and base metal exploration in remote areas of northern Pakistan. Arabian Journal of Geosciences, 8, 5081–5093. doi:10.1007/s12517-014-1531-7
  • Ali, M. H., Mustafa, A. R. A., & El-Sheikh, A. (2016). Geochemistry and spatial distribution of selected heavy metals in surface soil of Sohag. Egypt: a Multivariate Statistical and GIS Approach, Environmental Earth Sciences, 75, 1257.
  • Alipour, M. H., Rezakhani, A. T., & Shamsai, A. (2016). Seasonal fractal-scaling of floods in two U.S. water resources regions. Journal of Hydrology, 540, 232–239. doi:10.1016/j.jhydrol.2016.06.016
  • Allegre, C. J., & Lewin, E. (1995). Scaling laws and geochemical distribution. Earth and Planetary Science Letter, 132, 1–13. doi:10.1016/0012-821X(95)00049-I
  • Amblard-Gross, G. R., Maul, A., Férard, J.-F. O., Carrot, F., & Ayrault, S. (2004). Spatial variability of sampling: Grid size impact on atmospheric metals and trace elements deposition mapping with mosses. Journal of Atmospheric Chemistry, 49(1–3), 39–52. doi:10.1007/s10874-004-1213-z
  • Ambrams, M. J. (1984). Landsat thematic mapper and thematic mapper simulator data for a porphyry copper deposit. Photogrammetric Engineering and Remote Sensing, 50, 1171–1173.
  • Amer, R., Kusky, T., & El Mezayen, A. (2012). Remote sensing detection of gold related alteration zones in Um Rus area, Central Eastern Desert of Egypt. Advances in Space Research, 49(1), 121–134. doi:10.1016/j.asr.2011.09.024
  • Ameur, M., Hamzaoui-Azaza, F., & Gueddari, M. (2016). Suitability for human consumption and agriculture purposes of Sminja aquifer groundwater in Zaghouan (north-east of Tunisia) using GIS and geochemistry techniques. Environmental Geochemistry and Health, 38, 1147–1167.
  • Asadi, H. H., Kianpouryan, S., Lu, Y., & McCuaig, T. C. (2014). Exploratory data analysis and C-A fractal model applied in mapping multi-element soil anomalies for drilling: A case study from the Sari Gunay epithermal gold deposit, NW Iran. Journal of Geochemical Exploration, 145, 233–241. doi:10.1016/j.gexplo.2014.07.005
  • Asadi, H. H., Porwal, A., Fatehi, M., Kianpouryan, S., & Lu, Y. J. (2015). Exploration feature selection applied to hybrid data integration modeling: Targeting copper-gold potential in central Iran. Ore Geology Reviews, 71, 819–838. doi:10.1016/j.oregeorev.2014.12.001
  • Asmaryan, S. G., Muradyan, V. S., Sahakyan, L. V., Saghatelyan, A. K., & Warner, T. (2014). Global soil map: Basis of the global spatial soil information system (pp. 429–432). Boca Raton. FL: CRC Press-Taylor & Francis Group.
  • Bai, J., Porwal, A., Hart, C., Ford, A., & Yu, L. (2010). Mapping geochemical singularity using multifractal analysis: Application to anomaly definition on stream sediments data from Funin Sheet, Yunnan, China. Journal of Geochemical Exploration, 104(1–2), 1–11. doi:10.1016/j.gexplo.2009.09.002
  • Batty, M. (1992). The fractal nature of geometry. Geographical Magazine, 33–36.
  • Baugh, W. M., Kruse, F. A., Jr., & Atkinson, W. W. (1998). Quantitative geochemical mapping of ammonium minerals in the Southern Ceder Mountains, Nevada, Using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 65, 292–308. doi:10.1016/S0034-4257(98)00039-X
  • Belic, I., Radosavljevic, L., Milincic, M., & Šabić, D. (2012). Laser system for remote sensing monitoring of air pollution and quality control of the atmosphere. Thermal Science, 16, 1201–1211. doi:10.2298/TSCI120226136B
  • Ben-Dor, E., Patkin, K., Banin, A., & Karnieli, A. (2002). Mapping of several soil properties using DAIS-7915 hyperspectral scanner data: A case study over clayey soils in Israel. International Journal of Remote Sensing, 23, 1043–1062. doi:10.1080/01431160010006962
  • Beratan, K., Peer, B., Dunbar, N. W., & Blom, R. (1997). A remote sensing approach to alteration mapping: AVIRIS data and extension-related potassium metasomatism, Socorro, New Mexico. International Journal of Remote Sensing, 18, 3595–3609. doi:10.1080/014311697216829
  • Bierwirth, P. N., Blewett, R., & Huston, D. (2002). Hyperspectral mapping of mineral assemblages associated with gold mineralization in the West Pilbara, Western Australia. Economic Geology, 97, 819–826. doi:10.2113/gsecongeo.97.4.819
  • Bishop, C. A., Liu, J. G., & Mason, P. J. (2011). Hyperspectral remote sensing for mineral exploration in Pulang, Yunnan Province, China. International Journal of Remote Sensing, 32, 2409–2426. doi:10.1080/01431161003698336
  • Bishop, J. L., Lougear, A., Newton, J., Doran, P. T., Froeschl, H., Trautwein, A. X., … Koeberl, C. (2001). Mineralogical and geochemical analyses of Antarctic lake sediments: A study of reflectance and Mossbauer spectroscopy and C, N, and S isotopes with applications for remote sensing on Mars. Geochimica Et Cosmochimica Acta, 65, 2875–2897. doi:10.1016/S0016-7037(01)00651-2
  • Bohm, M., & Popescu, V. D. (2016). Landscape ecology, biogeography, and GIS methods. In Dodd C. K. (Ed.), Reptile ecology and conservation: A handbook of techniques. New York, NY: Oxford University Press.
  • Bojorquez-Tapia, L. A., Diaz-Moadragon, S., & Ezcurra, E. (2001). GIS-based approach for participatory decision making and land suitability assessment. International Journal of Geographical Information Science, 15, 129–151. doi:10.1080/13658810010005534
  • Bolster, S. J. S. (2010). Recent advances in geochemical interpretation for mineral exploration through the application of regolith terrain mapping and the power of new remote sensing and 3D visualisation techniques. Geochimica Et Cosmochimica Acta, 74, A102.
  • Bölviken, B., Stokke, P. R., Feder, J., & Jössang, T. (1992). The fractal nature of geochemical landscapes. Journal of Geochemical Exploration, 43, 91–109. doi:10.1016/0375-6742(92)90001-O
  • Borges, R. C., Fávaro, D. I. T., Caldas, V. G., Lauria, D. C., & Bernedo, A. V. B. (2016). Instrumental neutron activation analysis, gamma spectrometry and geographic information system techniques in the determination and mapping of rare earth element in phosphogypsum stacks. Environmental Earth Sciences, 75, 705.
  • Boško, M., & Aleksandra, B. (2017). Fractal approach in characterization of spatial pattern of soil properties. Eurasian Journal of Soil Science, 6(1), 20–27.
  • Bouaziz, M., Matschullat, J., & Gloaguen, R. (2010). Remote sensing indicators to identify low and moderately salt-affected soils based on MODIS Terra and geochemical data. Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 7824, 78241I.
  • Bowie, F. R. S., & Thornton, I. (1985). Environmental geochemistry and health. Dordrecht, Netherlands: Springer.
  • Brandmeier, M., Erasmi, S., Hansen, C., Höweling, A., Nitzsche, K., Ohlendorf, T., … Wörner, G. (2013). Mapping patterns of mineral alteration in volcanic terrains using ASTER data and field spectrometry in Southern Peru. Journal of South American Earth Sciences, 48, 296–314. doi:10.1016/j.jsames.2013.09.011
  • Brandmeier, M. (2010). Remote sensing of Carhuarazo volcanic complex using ASTER imagery in Southern Peru to detect alteration zones and volcanic structures: A combined approach of image processing in ENVI and ArcGIS/ArcScene. Geocarto International, 25, 629–648. doi:10.1080/10106049.2010.519787
  • Burak, D. L., Fontes, M. P. F., Santos, N. T., Monteiro, L. V. S., Martins, E. D. S., & Becquer, T. (2010). Geochemistry and spatial distribution of heavy metals in Oxisols in a mineralized region of the Brazilian Central Plateau. Geoderma, 160, 131–142. doi:10.1016/j.geoderma.2010.08.007
  • Burrongh, P. A. (1983). Multiscale sources of spatial variation in soil: The application of fractal concept to nested level of soil variation. Journal of Soil Science, 34, 577–597.
  • Butt, C. R. M. (2016). The development of regolith exploration geochemistry in the tropics and sub-tropics. Ore Geology Reviews, 73, 380–393. doi:10.1016/j.oregeorev.2015.08.018
  • Chen, F., Kissel, D. E., West, L. T., & Adkins, W. (2000). Field-scale mapping of surface soil organic carbon using remotely sensed imagery. Soil Science Society of America Journal, 64, 746–753. doi:10.2136/sssaj2000.642746x
  • Chen, G. X., & Cheng, Q. M. (2016). Singularity analysis based on wavelet transform of fractal measures for identifying geochemical anomaly in mineral exploration. Computers & Geosciences, 87, 56–66. doi:10.1016/j.cageo.2015.11.007
  • Chen, G., Cheng, Q., & Zuo, R. (2016). Fractal analysis of geochemical landscapes using scaling noise model. Journal of Geochemical Exploration, 161, 62–71. doi:10.1016/j.gexplo.2015.11.003
  • Chen, Y., Liu, Y., Liu, Y., Lin, A., Kong, X., Liu, D., … Wang, D. (2012). Mapping of Cu and Pb contaminations in soil using combined geochemistry, topography, and remote sensing: A case study in the Le'an river floodplain, China. International Journal of Environmental Research and Public Health, 9, 1874–1886. doi:10.3390/ijerph9051874
  • Cheng, L., & Wang, H. R. (1999). Environmental geochemistry and geographic information system (GIS). Geology-Geochemistry, 27, 110–113.
  • Cheng, Q. M. (2000). Multifractal theory and geochemical element distribution pattern. Earth Science-Journal of China University of Geosciences, 25, 311–318.
  • Cheng, Q., Agterberg, F. P., & Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109–130. doi:10.1016/0375-6742(94)90013-2
  • Cheng, Q., Agterberg, F. P., & Bonham-Carter, G. F. (1996). A spatial analysis method for geochemical anomaly separation. Journal of Geochemical Exploration, 56, 183–195. doi:10.1016/S0375-6742(96)00035-0
  • Cheng, Q., & Agterberg, F. P. (2009). Singularity analysis of ore-mineral and toxic trace elements in stream sediments. Computers & Geosciences, 35, 234–244. doi:10.1016/j.cageo.2008.02.034
  • Choe, E., Meer, F., Ruitenbeek, F., Werff, H., Smeth, B., & Kim, Y. W. (2008). Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain. Remote Sensing of Environment, 112, 3222–3233. doi:10.1016/j.rse.2008.03.017
  • Cicchella, D., De Vivo, B., & Lima, A. (2005). Background and baseline concentration values of elements harmful to human health in the volcanic soils of the metropolitan and provincial areas of Napoli, Italy; selected papers from the 6th international symposium on environmental geochemistry. Geochemistry: Exploration, Environment, Analysis, 5, 29–40. doi:10.1144/1467-7873/03-042
  • Comero, S., Servida, D., De Capitani, L., & Gawlik, B. M. (2012). Geochemical characterization of an abandoned mine site: A combined positive matrix factorization and GIS approach compared with principal component analysis. Journal of Geochemical Exploration, 118, 30–37. doi:10.1016/j.gexplo.2012.04.003
  • Croft, H., Kuhn, N. J., & Anderson, K. (2012). On the use of remote sensing techniques for monitoring spatio-temporal soil organic carbon dynamics in agricultural systems. Catena, 94, 64–74. doi:10.1016/j.catena.2012.01.001
  • Crósta, A. P., De Souza Filho, C. R., Azevedo, F., & Brodie, C. (2003). Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis. International Journal of Remote Sensing, 24, 4233–4240. doi:10.1080/0143116031000152291
  • Crowley, J. K., Hubbard, B. E., & Mars, J. C. (2003). Hydrothermal alteration on the cascade stratovolcanoes: A remote sensing survey. Geological Society of America Abstracts with Programs, 35, 552.
  • Darnley, A. G., Björklund, A., & Bølviken, B. (1995). A global geochemical database for environmental and resource management. Jacqueline E., & Susan D. (Eds.), Earth Science 19. Ottawa: UNESCO Publishing.
  • Darnley, A. G. (1990). International geochemical mapping: A project. Journal of Geochemical Exploration, 39(1–2), 1–13. doi:10.1016/0375-6742(90)90066-J
  • Darnley, A. G. (1993). Some notes on the importance of airborne gamma-ray spectrometry in International Geochemical Mapping. Journal of Geochemical Exploration, 49(1–2), 201–212. doi:10.1016/0375-6742(93)90045-N
  • Darnley, A. G. (1995). International geochemical mapping: A review. Journal of Geochemical Exploration, 55(1–3), 5–10. doi:10.1016/0375-6742(95)00035-6
  • Darvishzadch, R., Skidmorc, A., Schlcrf, M., Atzberger, C., Corsi, F., & Cho, M. (2008). LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements. ISPRS Journal of Photogrammetry & Remote Sensing, 63, 409–426. doi:10.1016/j.isprsjprs.2008.01.001
  • Das, B. S., Sarathjith, M. C., Santra, P., Sahoo, R. N., Srivastava, R., Routray, A., & Ray, S. S. (2015). Hyperspectral remote sensing: Opportunities, status and challenges for rapid soil assessment in India. Current Science, 108, 860–868.
  • Daya, A. A. (2015). Comparative study of C-A, C-P, and N-S fractal methods for separating geochemical anomalies from background: A case study of Kamoshgaran region, northwest of Iran. Journal of Geochemical Exploration, 150, 52–63. doi:10.1016/j.gexplo.2014.12.015
  • de Almeida, T. I. R., de Souza, C. R., Juliani, C., & Branco, F. C. (2009). Application of remote sensing to geobotany to detect hydrothermal alteration facies in Epithermal High-Sulfidation gold deposits in the Amazon region. Remote Sensing and Spectral Geology, 16, 135–142.
  • Deng, J., Wang, Q. F., Yang, L. Q., Wang, Y. R., Gong, Q. J., & Liu, H. (2010). Delineation and explanation of geochemical anomalies using fractal models in the Heqing area, Yunnan Province, China. Journal of Geochemical Exploration, 105, 95–105. doi:10.1016/j.gexplo.2010.04.005
  • Deng, R. R., Liu, Q. H., Ke, R. P., Cheng, L., & Liu, X. P. (2004). Model for water pollution remote sensing based on double scattering and its application in the Zhujiang River outfall. Acta Oceanologica Sinica, 23(1), 119–127.
  • Deng, R. R., Tian, G. L., Wang, X. M., & Chen, X. X. (2003). Method of quantitative remote sensing for air pollution monitoring and its application in Changrang River Delta area. Journal of Infrared & Millimeter Waves, 22, 181–185.
  • Deroin, J. P., Kheir, R. B., & Abdallah, C. (2017). Geoarchaeological remote sensing survey for cultural heritage management. Case study from Byblos (Jbail, Lebanon). Journal of Cultural Heritage, 23, 37–43. doi:10.1016/j.culher.2016.04.014
  • Dhiman, S. D., & Keshari, A. K. (2006). GIS assisted inverse geochemical modeling for plausible phase transfers in aquifers. Environmental Geology, 50, 1211–1219. doi:10.1007/s00254-006-0293-2
  • Din, S. U., Dousari, A., & Literathy, P. (2008). Evidence of hydrocarbon contamination from the Burgan oil field, Kuwait: Interpretations from thermal remote sensing data. Journal of Environmental Management, 86, 605–615. doi:10.1016/j.jenvman.2006.12.028
  • Ding, Y. H., Wang, R. H., & Ning, H. S. (2011). Characteristics of landscape geochemistry in Karamay artificial carbon-sink forests. Chinese Journal of Eco-Agriculture, 19, 1348–1353. doi:10.3724/SP.J.1011.2011.01348
  • Domenico, L. D., Crisafi, E., Magazzù, G., Puglisi, A., & Rosa, A. L. (1994). Monitoring of petroleum hydrocarbon pollution in surface waters by a direct comparison of fluorescence spectroscopy and remote sensing techniques. Marine Pollution Bulletin, 28, 587–591. doi:10.1016/0025-326X(94)90359-X
  • Douaoui, A. E. K., Nicolas, H., & Walter, C. (2006). Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data. Geoderma, 134(1–2), 217–230. doi:10.1016/j.geoderma.2005.10.009
  • Dwivedi, R. S., Sreenivas, K., & Ramana, K. V. (1999). Inventory of salt-affected soils and waterlogged areas: A remote sensing approach. International Journal of Remote Sensing, 20, 1589–1599. doi:10.1080/014311699212623
  • Eliason, P. T., Donovan, T. J., & Chavez, P. S. (1983). Integration of geologic, geochemical, and geophysical data of the Cement oil field, Oklahoma, using spatial array processing. Geo-physics, 48, 1305–1317. doi:10.1190/1.1441412
  • Emeis, S., & Schäfer, K. (2006). Remote sensing methods to investigate boundary-layer structures relevant to air pollution in cities. Boundary-Layer Meteorology, 121, 377–385. doi:10.1007/s10546-006-9068-2
  • Emengini, E. J., Blackburn, G. A., & Theobald, J. C. (2013). Discrimination of plant stress caused by oil pollution and waterlogging using hyperspectral and thermal remote sensing. Journal of Applied Remote Sensing, 7(1), 073476. doi:10.1117/1.JRS.7.073476
  • Farzamian, M., Rouhani, A. K., Yarmohammadi, A., Shahi, H., Sabokbar, H. A. F., & Ziaiie, M. (2016). A weighted fuzzy aggregation GIS model in the integration of geophysical data with geochemical and geological data for Pb-Zn exploration in Takab area, NW Iran. Arabian Journal of Geosciences, 9, 1–17.
  • Feng, Y., & Liu, Y. (2015). Fractal dimension as an indicator for quantifying the effects of changing spatial scales on landscape metrics. Ecological Indicators, 53, 18–27. doi:10.1016/j.ecolind.2015.01.020
  • Fernández-Prieto, D., & Sabia, R. (2016). Remote sensing advances for earth system science. New York, NY: Springer International Publishing.
  • Ferrier, G., White, K., Griffiths, G., Bryant, R., & Stefouli, M. (2002). The mapping of hydrothermal alteration zones on the island of Lesvos, Greece using an integrated remote sensing dataset. International Journal of Remote Sensing, 23, 341–356. doi:10.1080/01431160010003857
  • Fiannacca, P., Ortolano, G., Pagano, M., Visalli, R., Cirrincione, R., & Zappalà, L. (2017). IG-Mapper: A new ArcGIS® toolbox for the geostatistics-based automated geochemical mapping of igneous rocks. Chemical Geology, 470, 75–92. doi:10.1016/j.chemgeo.2017.08.024
  • Flier, K., & Bartier, P. (1993). Application of geographic information systems to interpretation of coal geochemistry data. International Journal of Coal Geology, 24, 293–308.
  • Fortescue, J. A. C. (1975). The use of landscape geochemistry to process exploration geochemical data. Developments in Economic Geology, 2, 3–7.
  • Fortescue, J. A. C. (1980). Environmental Geochemistry. New York, NY: Springer.
  • Fortescue, J. A. C. (1980). Environmental Geochemistry: A Holistic Approach. New York, NY: Springer.
  • Fortescue, J. A. C. (1992). Landscape geochemistry: Retrospect and prospect 1990. Applied Geochemistry, 7(1), 1–53. doi:10.1016/0883-2927(92)90012-R
  • Fox, G. A., Sabbagh, G. J., Searcy, S. W., & Yang, C. (2004). An automated soil line identification routine for remotely sensed images. Soil Science Society of America Journal, 68, 1326–1331. doi:10.2136/sssaj2004.1326
  • Fraser, S. J. (1991). Discrimination and identification of ferric oxides using satellite Thematic Mapper data: A Newman case study. International Journal of Remote Sensing, 12, 635–641. doi:10.1080/01431169108929678
  • Frazier, B. E., & Cheng, Y. (1989). Remote sensing of soils in the eastern Palouse region with Landsat Thematic Mapper. Remote Sensing of Environment, 28, 317–325. doi:10.1016/0034-4257(89)90123-5
  • Fuge, R., & Johnson, C. C. (2015). Iodine and human health, the role of environmental geochemistry and diet: A review. Applied Geochemistry, 63, 282–302. doi:10.1016/j.apgeochem.2015.09.013
  • Gabr, S. S., Hassan, S. M., & Sadek, M. F. (2015). Prospecting for new gold-bearing alteration zones at El-Hoteib area, South Eastern Desert, Egypt, using remote sensing data analysis. Ore Geology Reviews, 71, 1–13. doi:10.1016/j.oregeorev.2015.04.021
  • Gabr, S., Ghulam, A., & Kusky, T. (2010). Detecting areas of high-potential gold mineralization using ASTER data. Ore Geology Reviews, 38(1–2), 59–69. doi:10.1016/j.oregeorev.2010.05.007
  • Galvâo, L. S., Pizarro, M. A., & Epiphanio, J. C. N. (2001). Variations in reflectance of tropical soils: Spectral-chemical composition relationships from AVIRIS data. Remote Sensing of Environment, 75, 245–255. doi:10.1016/S0034-4257(00)00170-X
  • Garcia-Gomez, M., & Maestre, F. T. (2011). Remote sensing data predict indicators of soil functioning in semi-arid steppes, central Spain. Ecological Indicators, 11, 1476–1481. doi:10.1016/j.ecolind.2011.02.015
  • Garton, E. R., & Deem, K. (1988). Correlation of remote-sensing, earth resistivity, and near-surface geochemical data at offset well test facility, Whitley County, Kentucky. AAPG Bulletin, 72, 962.
  • Gasmi, A., Gomez, C., Zouari, H., Masse, A., & Ducrot, D. (2016). PCA and SVM as geo-computational methods for geological mapping in the southern of Tunisia, using ASTER remote sensing data set. Arabian Journal of Geosciences, 9, 753.
  • Ge, Y. F., Thomasson, J. A., & Sui, R. X. (2011). Remote sensing of soil properties in precision agriculture: A review. Frontiers of Earth Science, 5, 229–238.
  • Ghazban, F., Parizanganeh, A., Zamani, A., & Taghilou, B. (2015). Assessment of heavy metal pollution in water and sediments from the Ghalechay River, Baychebagh Copper Mine Area, Iran. Soil & Sediment Contamination, 24, 172–190.
  • Goetz, A. F. H., Rock, B. N., & Rowan, L. C. (1983). Remote sensing for exploration: An overview. Economic Geology, 78, 573–590. doi:10.2113/gsecongeo.78.4.573
  • Gomez, C., Viscarra Rossel, R. A., & McBratney, A. B. (2008). Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: An Australian case study. Geoderma, 146, 403–411. doi:10.1016/j.geoderma.2008.06.011
  • Goncalves, M. A., Mateus, A., & Oliveira, V. (2001). Geochemical anomaly separation by multifractal modeling. Journal of Geochemical Exploration, 72, 91–114. doi:10.1016/S0375-6742(01)00156-X
  • Gondwe, B. R. N., Lerer, S., Stisen, S., Marin, L., Rebolledo-Vieyra, M., Merediz-Alonso, G., & Bauer-Gottwein, P. (2010). Hydrogeology of the south-eastern Yucatan Peninsula: New insights from water level measurements, geochemistry, geophysics and remote sensing. Journal of Hydrology, 389(1–2), 1–17. doi:10.1016/j.jhydrol.2010.04.044
  • Groves, D. I., & Dunphy, J. M. (2000). Applications of geochronology, geochemistry and GIS to mineral exploration- Introduction. Australian Journal of Earth Sciences, 47, 827–827. doi:10.1046/j.1440-0952.2000.00823.x
  • Grunfeld, K. (2007). The separation of multi-element spatial patterns in till geochemistry of southeastern Sweden combining GIS, principal component analysis and high-dimensional visualization. Geochemistry Exploration Environment Analysis, 7, 303–318.
  • Grunwald, S., Vasques, G. M., & Rivero, R. G. (2015). Fusion of soil and remote sensing data to model soil properties. Advances in Agronomy, 131, 1–109.
  • Guinness, E. A., Arvidson, R. E., & Leff, C. E. (1984). Correlations between geochemical, topography, and remote-sensing data for southern Missouri as determined by digital image-processing. Abstracts of Papers of the American Chemical Society, 187, 25.
  • Gupta, R. P. (2003). Remote sensing geology. Berlin Heidelberg: Springer.
  • Hale, M. (2009). Handbook of exploration and environmental geochemistry volume 11 foreword. In Carranza E. J. M. (Ed.), Geochemical anomaly and mineral prospectivity mapping in GIS. Netherlands: Elsevier Science BV.
  • Hamzeh, M. A., Aftabi, A., & Mirzaee, M. (2011). Assessing geochemical influence of traffic and other vehicle related activities on heavy metal contamination in urban soils of Kerman city, using a GIS-based approach. Environmental Geochemistry and Health, 33, 577–594.
  • Hanes, J. M. (2014). Biophysical applications of satellite remote sensing. Berlin Heidelberg: Springer.
  • Harris, J. R., Wilkinson, L., & Bernier, M. (2001). Analysis of geochemical data for mineral exploration using a GIS – A case study from the Swayze greenstone belt, northern Ontario, Canada. Geological Society of London Special Publication, 185(1), 4–13.
  • Hassan, S. M., & Ramadan, T. M. (2015). Mapping of the late Neoproterozoic Basement rocks and detection of the gold-bearing alteration zones at Abu Marawat-Semna area, Eastern Desert, Egypt using remote sensing data. Arabian Journal of Geosciences, 8, 4641–4656. doi:10.1007/s12517-014-1562-0
  • Hawkes, H. E., & Webb, J. S. (1962). Geochemistry in mineral exploration. New York, NY: Harper & Row.
  • He, Y. B., Yang, K., & Hou, Y. Y. (1997). A brief introduction to remote sensing geochemistry. Geology-Geochemistry, 4, 98–103.
  • Herzfeld, U. C. (1993). A method for seafloor classification using directional variogram, demonstrated for data from the western flank of the Mid-Atlantic Ridge. Mathematical Geology, 25, 901–924. doi:10.1007/BF00891050
  • Hick, P. T., & Russell, W. G. R. (1990). Some spectral considerations for remote sensing of soil salinity. Australian Journal of. Soil Research, 28, 417–431. doi:10.1071/SR9900417
  • Hom, L. W. (1968). Remote sensing of water pollution. Journal, 40, 1728–1738.
  • Hong, Y., Jiang, J., Yu, Z., & Yao, Z. (1979). Environmental geochemistry of molybdenum and its bearing on heart health. Geochimica, 32, 156.
  • Hoogenboom, H. J., Dekker, A. G., & Althuis, I. J. A. (1998). Simulation of AVIRIS sensitivity for detecting Chlorophyll over coastal and inland waters. Remote Sensing of Environment, 65, 333–340. doi:10.1016/S0034-4257(98)00042-X
  • Hosseini, S. A., Afzal, P., Sadeghi, B., Sharmad, T., Shahrokhi, S. V., & Farhadinejad, T. (2015). Prospection of Au mineralization based on stream sediments and lithogeochemical data using multifractal modeling in Alut 1:100,000 sheet, NW Iran. Arabian Journal of Geosciences, 8, 1–13.
  • Houborg, R., Anderson, M., & Daughtry, C. (2009). Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales. Remote Sensing of Environment, 113(1), 259–274. doi:10.1016/j.rse.2008.09.014
  • Howari, F. M. (2004). Investigation of hydrocarbon pollution in the vicinity of United Arab Emirates coasts using visible and near infrared remote sensing data. Journal of Coastal Research, 20, 1089–1095. doi:10.2112/03-0023R.1
  • Hu, L. P., Li, Y., Zhang, L., & Wang, J. D. (2006). Advanced development of remote sensing FTIR in air environment monitoring. Spectroscopy and Spectral Analysis, 26, 1863–1867.
  • Huang, C. C., Yang, H., Li, Y. M., Zou, J., Zhang, Y. M., Chen, X., … Zhang, M. L. (2015). Investigating changes in land use cover and associated environmental parameters in Taihu lake in recent decades using remote sensing and geochemistry. PLoS One, 10, e0120319. doi:10.1371/journal.pone.0120319
  • In, Z. H. (1992). Landscape geochemistry. Advances in Earth Sciences, 7, 63–64.
  • Ishaq, A. M. (1985). Remote-sensing techniques for monitoring of pollution in coastal waters: Potential application to Saudi-Arabia. Arabian Journal for Science and Engineering, 10(1), 15–26.
  • Izadikhah, M., & Saen, R. F. (2016). A new preference voting method for sustainable location planning using geographic information system and data envelopment analysis. Journal of Cleaner Production, 137, 1347–1367. doi:10.1016/j.jclepro.2016.08.021
  • Jerrett, M., Turner, M. C., Beckerman, B. S., Pope, C. A., van Donkelaar, A., Martin, R. V., & Serre, M. (2017). Comparing the health effects of ambient particulate matter estimated using ground-based versus remote sensing exposure estimates. Environmental Health Perspectives, 125, 552–559.
  • Jesus, A. P., Mateus, A., Gonçalves, M. A., & Munhá, J. (2013). Multi-fractal modelling and spatial Cu–soil anomaly analysis along the southern border of the Iberian Terrane in Portugal. Journal of Geochemical Exploration, 126-127, 23–44. doi:10.1016/j.gexplo.2012.12.010
  • Jiang, B., & Anders, B. S. (2016). A fractal perspective on scale in geography. ISPRS International Journal of Geo-Information, 5, 1–12.
  • Jiang, L., Yi, Y. F., You, S. Y., Wang, Z. B., & He, L. L. (2013). A method of alteration information extracted of uranium mine base on TM remote sensing image. Intelligent Computing Theories, 7995, 507–515.
  • Jimenez, C., Baciu, C., Cordos, E., & Tatu, C. (2009). Environmental geochemistry and drinking water resources in the Pannonian Basin (Western Romania). Epidemiology, 20, S73–S74. doi:10.1097/01.ede.0000362929.01314.ce
  • Jordan, C., Zhang, C. S., & Higgins, A. (2007). Using GIS and statistics to study influences of geology on probability features of surface soil geochemistry in Northern Ireland. Journal of Geochemical Exploration, 93, 135–152. doi:10.1016/j.gexplo.2007.03.001
  • Jordan, G., & Scucs, A. (2002). Environmental mapping of geochemical systems. In Bobrowsky P. T. (Ed.), Geoenvironmental Mapping: Method, Theory and Practice. Rotterdam: A. A. Balkema Publishers.
  • Kasimov, N., Kosheleva, N., & Wagner, V. (2008). Modeling geochemical fields based on landscape-guided interpolation. Ecological Modelling, 212(1–2), 109–115. doi:10.1016/j.ecolmodel.2007.10.008
  • Khan, S. D., & Jacobson, S. (2008). Remote sensing and geochemistry for detecting hydrocarbon microseepages. Geological Society of America Bulletin, 120(1–2), 96–105.
  • Korobova, E. M., Veldkamp, A., Ketner, P., & Kroonenberg, S. B. (1997). Element partitioning in sediment, soil and vegetation in an alluvial terrace chronosequence, limagne rift valley, France: A landscape geochemical study. Catena, 31(1–2), 91–117. doi:10.1016/S0341-8162(97)00029-5
  • Krummel, J. R., Gardner, R. H., Sugihara, G., O'Neill, R. V., & Coleman, P. R. (1987). Landscape patterns in a disturbed environment. Oikos, 48, 321–324. doi:10.2307/3565520
  • Kuznetsov, V. A., & Xiu, M. (1985). Geochemical study of landscape: Current situation and problems. Science and Society, 4, 66–72.
  • Kwatli, M. A., Gillot, P. Y., Gharib, I., & Lefevre, J. C. (2012). Integration of K-Ar geochronology and remote sensing: Mapping volcanic rocks and constraining the timing of alteration processes (Al-Lajat Plateau, Syria). Quaternary International, 251, 22–30. doi:10.1016/j.quaint.2011.04.019
  • Ladoni, M., Alavipanah, S. K., Bahrami, H. A., & Noroozi, A. A. (2010). Remote sensing of soil organic carbon in semi-arid region of Iran. Arid. Land Research & Management, 24, 271–281. doi:10.1080/15324982.2010.502917
  • Lausch, A., Erasmi, S., King, D. J., Magdon, P., & Heurich, M. (2017). Understanding forest health with remote sensing-part II—A review of approaches and data models. Remote Sensing, 9, 129. doi:10.3390/rs9020129
  • Lee, C. S., Li, X., Shi, W. Z., Cheung, S. C., & Thornton, I. (2006). Metal contamination in urban, suburban, and country park soils of Hong Kong: A study based on GIS and multivariate statistics. Science of the Total Environment, 356(1–3), 45–61. doi:10.1016/j.scitotenv.2005.03.024
  • Leite, M. E., & Rocha, A. M. (2016). Geographic information system (GIS) applied to the calculation of morphometric index in watershed. Geo Uerj, 28, 44–65.
  • Lerche, I., & Glaesser, W. (2006). Environmental risk assessment. Berlin Heidelberg: Springer.
  • Li, C. J., Ma, T. H., & Shi, J. F. (2003). Application of a fractal method relating concentrations and distances for separation of geochemical anomalies from background. Journal of Geochemical Exploration, 77, 167–175. doi:10.1016/S0375-6742(02)00276-5
  • Li, C. J., Ma, T. H., & Xu, Y. L. (1995). Geochemical landscape attractor and its implications. Geology of Zhejiang, 11(1), 86–90.
  • Li, N., Lv, J. S., & Altermann, W. (2010). Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution. Spectroscopy and Spectral Analysis, 30, 2508–2511.
  • Li, P., & Xu, K. (2013). Application Progress of Fractal Theory in Pedology Researches. Acta Agriculturae Jiangxi, 25, 78–84.
  • Li, P., Zheng, M., Bi, H., Wu, S. T., & Wang, X. R. (2017). Pore throat structure and fractal characteristics of tight oil sandstone: A case study in the Ordos Basin, China. Journal of Petroleum Science & Engineering, 149, 665–674. doi:10.1016/j.petrol.2016.11.015
  • Li, Q. M., & Cheng, Q. M. (2005). A GIS-based W-A fractal model for extracting spatial information from geophysical and geochemical data. GIS and Spatial Analysis, 1-2, 470–474.
  • Li, Q. M., & Cheng, Q. M. (2006). Visual Anomaly: A GIS-based multifractal method for geochemical and geophysical anomaly separation in Walsh domain. Computers & Geosciences, 32, 663–672. doi:10.1016/j.cageo.2005.09.006
  • Li, X., Lee, S. L., Wong, S. C., Shi, W. Z., & Thornton, I. (2004). The study of metal contamination in urban soils of Hong Kong using a GIS-based approach. Environmental Pollution, 129(1), 113–124. doi:10.1016/j.envpol.2003.09.030
  • Lima, A., De Vivo, B., Cicchella, D., Cortini, M., & Albanese, S. (2003). Multifractal IDW interpolation and fractal filtering method in environmental studies: An application on regional stream sediments of Campania region (Italy). Applied Geochemistry, 18, 1853–1865. doi:10.1016/S0883-2927(03)00083-0
  • Lima, A., Plant, J. A., De Vivo, B., Tarvainen, T., Albanese, S., & Cicchella, D. (2008). Interpolation methods for geochemical baseline maps: A comparative study using arsenic in European stream waters. Geochemistry: Exploration, Environment, Analysis, 8(1), 41–48. doi:10.1144/1467-7873/07-146
  • Lindgren, D. T. (1985). Land use planning and remote sensing. Dordrecht, Netherlands: Springer.
  • Lopez-Granados, F., Jurado-Exposito, M., Pena-Barragan, J. M., & García-Torres, L. (2005). Using geostatistical and remote sensing approaches for mapping soil properties. European Journal of Agronomy, 23, 279–289. doi:10.1016/j.eja.2004.12.003
  • Loughlin, W. P. (1991). Principal component analysis for alteration mapping. Photogrammetric Engineering and Remote Sensing, 57, 1163–1169.
  • Lu, P., Wang, L., Niu, Z., Li, L., & Zhang, W. (2013). Prediction of soil properties using laboratory VIS–NIR spectroscopy and Hyperion imagery. Journal of Geochemical Exploration, 132, 26–33. doi:10.1016/j.gexplo.2013.04.003
  • Luz, F., Mateus, A., Matos, J. X., & Gonçalves, M. A. (2014). Cu- and Zn-Soil Anomalies in the NE Border of the South Portuguese Zone (Iberian Variscides, Portugal) Identified by Multifractal and Geostatistical Analyses. Natural Resources Research, 23, 195–215. doi:10.1007/s11053-013-9217-5
  • Lyon, R. J. P., & Lee, K. (1970). Remote sensing in exploration for mineral deposits. Economic Geology, 65, 785–800. doi:10.2113/gsecongeo.65.7.785
  • Malczewski, J. (2006). Ordered weighted averaging with fuzzy quantifiers: GIS-based multi-criteria evaluation for land-use suitability analysis. International Journal of Applied Earth Observation and Geoinformation, 8, 270–277. doi:10.1016/j.jag.2006.01.003
  • Mallick, S., Dutta, D., & Min, K. H. (2017). Quality assessment and forecast sensitivity of global remote sensing observations. Advances in Atmospheric Sciences, 34, 371–382. doi:10.1007/s00376-016-6109-8
  • Mandelbrot, B. B. (1977). Fractal: Form chance and dimension. New York, NY: W H Freeman and Company.
  • Mandelbrot, B. B. (1967). How long is the coast of Britain? Statistical self-similarity and fractional dimension. Science, 150, 636–638. doi:10.1126/science.156.3775.636
  • Mandelbrot, B. B. (1982). The fractal geometry of nature. New York, NY: W H Freeman and Company.
  • Mansouri, E., & Feizi, F. (2016). Introducing Au potential areas, using remote sensing and geochemical data processing using fractal methods in Chartagh, Western Azerbijan – Iran. Archives of Mining Sciences, 61, 397–414. doi:10.1515/amsc-2016-0029
  • Mashyanov, N. R., & Reshetov, V. V. (1995). Geochemical ecological monitoring using the remote-sensing technique. Science of the Total Environment, 159, 169–175.
  • Maya, M., Musekiwa, C., Mthembi, P., & Crowley, M. (2015). Remote sensing and geochemistry techniques for the assessment of coal mining pollution, Emalahleni (Witbank), Mpumalanga. South African Journal of Geomatics, 4, 174–188.
  • Melesse, A. M., & Abtew, W. (2016). Landscape dynamics, soils and hydrological processes in varied climates. New York, NY: Springer International Publishing.
  • Mello, M. R., Babinski, N. A., Goncalves, F. T., & Miranda, E. P. (1996). Hydrocarbon prospecting in the Amazon Rain Forest: Application of surface geochemical, microbiological, and remote sensing methods. Hydrocarbon Migration and Its near-Surface Expression, 66, 401–411.
  • Mendas, A., & Delali, A. (2012). Integration of multi criteria decision analysis in GIS to develop land suitability for a culture: Application to durum wheat cultivation in the region of Mleta in Algeria. Computers and Electronics in Agriculture, 83, 117–126. doi:10.1016/j.compag.2012.02.003
  • Meng, X. G. (1991). A new tool for quantification of earth science: Fractal theory. Journal of Earth Science, 3, 318–334.
  • Meng, X. G., & Zhao, P. D. (1991). Fractal structure of geological data. Earth Science, 16, 207–212.
  • Meng, X. W., & Ye, X. C. (1994). Fractal landscape of the geochemical field and geochemical grading prognosis. Geophysical and Geochemical Exploration, 5, 393–397.
  • Metternicht, G. I., & Zinck, J. A. (2003). Remote sensing of soil salinity: Potentials and constraints. Remote Sensing of Environment, 85(1), 1–20. doi:10.1016/S0034-4257(02)00188-8
  • Mhamdi, H. S., Raji, M., Maimouni, S., & Oukassou, M. (2017). Fractures network mapping using remote sensing in the Paleozoic massif of Tichka (Western High Atlas, Morocco). Arabian Journal of Geosciences, 10, 125.
  • Milton, N. M., Collins, W., Chang, S. H., & Schmidt, R. G. (1984). Remote detection of metal anomalies on Pilot Mountain, Randolph County, North Carolina; reply. Economic Geology, 79, 1760–1761. doi:10.2113/gsecongeo.79.7.1760
  • Mirzaee, S., Ghorbani-Dashtaki, S., Mohammadi, J., Asadi, H., & Asadzadeh, F. (2016). Spatial variability of soil organic matter using remote sensing data. Catena, 145, 118–127. doi:10.1016/j.catena.2016.05.023
  • Molan, Y. E., Refahi, D., & Tarashti, A. H. (2014). Mineral mapping in the Maherabad area, eastern Iran, using the HyMap remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 27, 117–127. doi:10.1016/j.jag.2013.09.014
  • Momo, M. N., Yemefack, M., Tematio, P., Beauvais, A., & Ambrosi, J. P. (2016). Distribution of duricrusted bauxites and laterites on the Bamiléké plateau (West Cameroon): Constraints from GIS mapping and geochemistry. Catena, 140, 15–23. doi:10.1016/j.catena.2016.01.010
  • Nahid, D. S., & Mohamed, G. A. (2006). Remote sensing analysis of the gorge of the Nile, Ethiopia with emphasis on dejen-gohatsion region. Journal of African Earth Sciences, 44, 135–150.
  • Neto, O. C. D. R., Teixeira, A. D. S., Moreira, L. C. J., & Galvão, L. S. (2017). Hyperspectral remote sensing for detecting soil salinization using ProSpecTIR-VS aerial imagery and sensor simulation. Remote Sensing, 9(1), 42. doi:10.3390/rs9010042
  • Nouri, R., Jafari, M., Arian, M., Feizi, F., & Afzal, P. (2013). Prospection for copper mineralization with contribution of remote sensing, geochemical and mineralographical data in Abhar 1:100,000 sheet, NW IRAN. Archives of Mining Sciences, 58, 1071–1084.
  • Oerke, E. C., Gerhards, R., Menz, G., & Sikora, R. A. (2010). Precision crop protection: The challenge and use of heterogeneity. Dordrecht, Netherlands: Springer.
  • Oliveira, M. T. G., Rolim, S. B. A., de Mello-Farias, P. C., Meneguzzi, A., & Lutckmeier, C. (2008). Industrial pollution of environmental compartments in the Sinos River Valley, RS, Brazil: Geochemical-biogeochemical characterization and remote sensing. Water, Air, and Soil Pollution, 192(1), 183–198. doi:10.1007/s11270-008-9645-8
  • Oparin, V. N., Potapov, V. P., Giniyatullina, O. L., Andreeva, N. V., Schastlivtsev, E. L., & Bykov, A. A. (2014). Evaluation of dust pollution of air in Kuzbass coal-mining areas in winter by data of remote earth sensing. Journal of Mining Science, 50, 549–558. doi:10.1134/S1062739114030168
  • Oparin, V. N., Potapov, V. P., Giniyatullina, O. L., & Andreeva, N. V. (2012). Water body pollution monitoring in vigorous coal extraction areas using remote sensing data. Journal of Mining Science, 48, 934–940. doi:10.1134/S106273914805019X
  • Othman, A. A., & Gloaguen, R. (2014). Improving lithological mapping by SVM classification of spectral and morphological features: The discovery of a new chromite body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq). Remote Sensing, 6, 6867–6896. doi:10.3390/rs6086867
  • Pal, S. K., Majumdar, T. J., Bhattacharya, A. K., & Bhattacharyya, R. (2011). Utilization of Landsat ETM + data for mineral-occurrences mapping over Dalma and Dhanjori, Jharkhand, India: An advanced spectral analysis approach. International Journal of Remote Sensing, 32, 4023–4040. doi:10.1080/01431161.2010.484430
  • Palacios-Orueta, A., Pinzon, J. E., Ustin, S. L., & Roberts, D. A. (1999). Remote sensing of soil properties in the Santa Monica Mountains. Remote Sensing of Environment, 68, 138–151. doi:10.1016/S0034-4257(98)00106-0
  • Panahi, A., Cheng, Q. M., & Bonham-Carter, G. F. (2004). Modelling lake sediment geochemical distribution using principal component, indicator kriging and multifractal power-spectrum analysis: A case study from Gowganda, Ontario. Geochemistry Exploration Environment Analysis, 4(1), 59–70. doi:10.1144/1467-7873/03-023
  • Panahi, A., & Cheng, Q. M. (2004). Multifractality as a measure of spatial distribution of geochemical patterns. Mathematical Geosciences, 36, 827–846. doi:10.1023/B:MATG.0000041181.32596.5d
  • Paredes, C., & Elorza, F. J. (1999). Fractal and multifractal analysis of fractured geological media: Surface-subsurface correlation. Computers & Geosciences, 25, 1081–1096. doi:10.1016/S0098-3004(99)00069-2
  • Parsa, M., Maghsoudi, A., Yousefi, M., & Sadeghi, M. (2016). Prospectivity modeling of porphyry-Cu deposits by identification and integration of efficient mono-elemental geochemical signatures. Journal of African Earth Sciences, 114, 228–241. doi:10.1016/j.jafrearsci.2015.12.007
  • Parsons, C. T., Rodriguez-Lado, L., Reuter, H. I., & Montanarella, L. (2009). Modelling of groundwater arsenic contamination in Nepal: Geostatistical predictions of risk using remote sensing images. Geochmica Et Cosmochimica Acta, 73, A997.
  • Pazand, K., Hezarkhani, A., Ataei, M., & Ghanbari, Y. (2011). Application of multifractal modeling technique in systematic geochemical stream sediment survey to identify copper anomalies: A case study from Ahar, Azarbaijan, Northwest Iran. Chemie Der Erde - Geochemistry, 71, 397–402. doi:10.1016/j.chemer.2011.08.003
  • Pearce, J. A., Stern, J., Bloomer, S. H., & Fryer, P. (2005). Geochemical mapping of the Mariana arc basin system: Implications for the nature and distribution of subduction components. Geochemistry, Geophysics, Geosystems, 6, 1–27.
  • Peijl, M. J., & Verhoeven, J. T. A. (2000). Carbon, nitrogen and phosphorus cycling in river marginal wetlands: A model examination of landscape geochemical flows. Biogeochemistry, 50(1), 45–71.
  • Peng, Y., Kheir, R. B., Adhikari, K., Malinowski, R., Greve, M. B., Knadel, M., & Greve, M. H. (2016). Digital mapping of toxic metals in Qatari soils using remote sensing and ancillary data. Remote Sensing, 8, 1003. doi:10.3390/rs8121003
  • Petrovic, A., Khan, S. D., & Thurmond, A. K. (2012). Integrated hyperspectral remote sensing, geochemical and isotopic studies for understanding hydrocarbon-induced rock alterations. Marine & Petroleum Geology, 35(1), 292–308. doi:10.1016/j.marpetgeo.2012.01.004
  • Pieters, C. M., & Englert, P. A. (1993). Remote geochemical analysis: Elemental and mineralogical composition. New York, NY: Cambridge University Press.
  • Pirajno, F. (1985). Hydrothermal Processes and Mineral Systems, Springer Netherlands, 2009. Nevada, Abstracts of Papers of the American Chemical Society, 190, 10.
  • Pour, A. B., Hashim, M., & van Genderen, J. (2013). Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data: Bau goldfield, Sarawak, Malaysia. Ore Geology Reviews, 54 (, 181–196. doi:10.1016/j.oregeorev.2013.03.010
  • Praharaj, I., Swain, S. P., Powell, M. A., Hart, B. R., & Tripathy, S. (2002). Delineation of groundwater contamination around an ash pond: Geochemical and GIS approach. Environment International, 27, 631–638. doi:10.1016/S0160-4120(01)00121-0
  • Preston, J., Engel, B., Lalor, G. C., & Vutchkov, M. K. (1996). The application of geographic information systems to geochemical studies in Jamaica. Environmental Geochemistry and Health, 18, 99–104.
  • Prud'homme, G., Dobbin, N. A., Sun, L., Burnett, R. T., Martin, R. V., Davidson, A., & Cakmak, S. (2013). Comparison of remote sensing and fixed-site monitoring approaches for examining air pollution and health in a national study population. Atmospheric Environment, 80, 161–171. doi:10.1016/j.atmosenv.2013.07.020
  • Ramadan, T. M., & Kontny, A. (2004). Mineralogical and structural characterization of alteration zones detected by orbital remote sensing at Shalatein District, SE Desert, Egypt. Journal of African Earth Sciences, 40(1–2), 89–99. doi:10.1016/j.jafrearsci.2004.06.003
  • Ranaldi, M., Lelli, M., Tarchini, L., Carapezza, M. L., & Patera, A. (2016). Estimation of the geothermal potential of the Caldara di Manziana site in the Sabatini Volcanic District (central Italy) by integrating geochemical data and 3D-GIS modelling. Geothermics, 62, 115–130. doi:10.1016/j.geothermics.2016.04.003
  • Rani, N., Mandla, V. R., & Singh, T. (2017). Spatial distribution of altered minerals in the Gadag Schist Belt (GSB) of Karnataka, Southern India using hyperspectral remote sensing data. Geocarto International, 32, 225–237. doi:10.1080/10106049.2015.1132484
  • Rina, K., Singh, C. K., Datta, P. S., Singh, N., & Mukherjee, S. (2013). Geochemical modelling, ionic ratio and GIS based mapping of groundwater salinity and assessment of governing processes in Northern Gujarat, India. Environmental Earth Sciences, 69, 2377–2391. doi:10.1007/s12665-012-2067-3
  • Robert, D. A., Gardner, M., Church, R., Ustin, S., Scheer, G., & Green, R. O. (1998). Mapping chaparral in the Santa Monica Mountains using multipleend member spectral mixing models. Remote Sensing of Environment, 65, 267–279. doi:10.1016/S0034-4257(98)00037-6
  • Rodriguez-Galiano, V., Sanchez-Castillo, M., Chica-Olmo, M., & Chica-Rivas, M. (2015). Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines. Ore Geology Reviews, 71, 804–818. doi:10.1016/j.oregeorev.2015.01.001
  • Rose, S., & Shea, J. A. (2007). Environmental geochemistry of trace metal pollution in urban watersheds. Developments in Environmental Science, 5, 99–131.
  • Rowan, L. C., Goetz, A. F. H., & Ashley, R. P. (1977). Discrimination of hydrothermally altered and unaltered rocks in visible and near-infrared multispectral images. Geophysics, 42, 522–535. doi:10.1190/1.1440723
  • Rozenstein, O., & Adamowski, J. (2017). A review of progress in identifying and characterizing biocrusts using proximal and remote sensing. International Journal of Applied Earth Observation, 57, 245–255. doi:10.1016/j.jag.2017.01.002
  • Rozpondek, K., & Rozpondek, R. (2017). Issues of Sustainable Development in the Light of a GIS-based Assessment of the Geochemical State of the Aquatic Environment. Problemy Ekorozwoju, 12(1), 131–137.
  • Ruhling, A., & Tyler, G. (1971). Regional differences in the deposition of heavy metals over Scandinavia. Journal of Applied Ecology, 8, 497–507. doi:10.2307/2402886
  • Sadeghi, B., Moarefvand, P., Afzal, P., Yasrebi, A. B., & Saein, L. D. (2012). Application of fractal models to outline mineralized zones in the Zaghia iron ore deposit, Central Iran. Journal of Geochemical Exploration, 122, 9–19. doi:10.1016/j.gexplo.2012.04.011
  • Saffarini, G., Jarrar, G. H., Dill, H. G., Ghanem, H., & Yaseen, N. (2016). Data analysis of a revisited exploration geochemical dataset of quartz porphyrites from SW Jordan using GIS techniques. Chemie Der Erde- Geochemistry, 76, 519–527. doi:10.1016/j.chemer.2016.09.003
  • Samadzadegan, F., & Partovi, T. (2014). Optimum band selection for hyperspectral imagery based on Ant Colony Optimization. International conference on Environmental Pollution and Public Health, Hong Kong.
  • Schwaller, M. R., & Tkach, S. J. (1985). Premature leafs senescence as: Remote sensing detection and utility for geobotanical prospecting. Economic Geology, 80, 250–255. doi:10.2113/gsecongeo.80.2.250
  • Selige, T., Böhner, J., & Schmidhalter, U. (2006). High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures. Geoderma, 136(1–2), 235–244. doi:10.1016/j.geoderma.2006.03.050
  • Sergeyev, Y. (1941). A Geochemical Method of Prospecting for Ore Deposits. USGS (Translation from Russian, 1950), 1941, 1–87.
  • Seta, F., Biswas, A., Khare, A., & Sen, J. (2017). Understanding built environment. Singapore: Springer.
  • Shamseddin, M. M., Afzal, P., Gholinejad, M., Yasrebi, A. B., & Sadeghi, B. (2014). Delineation of geochemical anomalies using factor analysis and multifractal modeling based on stream sediments data in Sarajeh 1:100,000 sheet, Central Iran. Arabian Journal of Geosciences, 7, 5333–5343. doi:10.1007/s12517-013-1074-3
  • Shen, W., & Zhao, P. (2002). Theoretical study of statistical fractal model with applications to mineral resource prediction. Computers & Geosciences, 28, 369–376.
  • Siegel, F. R. (1974). Applied geochemistry. Hoboken, NJ: John Wiley.
  • Silva, Y. J. A. B. D., Nascimento, C. W. A. D., Straaten, P. V., Biondi, C. M., Júnior, V. S. D. S., & Silva, Y. J. A. B. D. (2017). Effect of I- and S-type granite parent material mineralogy and geochemistry on soil fertility: A multivariate statistical and GIS-based approach. Catena, 149, 64–72. doi:10.1016/j.catena.2016.09.001
  • Sim, B. L., Agterberg, F. P., & Beaudry, C. (1999). Determining the cutoff between background and relative base metal contamination levels using. Computers and Geosciences, 25, 1023–1041. doi:10.1016/S0098-3004(99)00064-3
  • Singh, C. K., Shashtri, S., & Mukherjee, S. (2011). Geochemical assessment of groundwater quality integrating multivariate statistical analysis with GIS in Shiwaliks of Punjab, India. Environmental Earth Sciences, 62, 1387–1405. doi:10.1007/s12665-010-0625-0
  • Singh, S. K., Srivastava, P. K., Pandey, A. C., & Gautam, S. K. (2013). Integrated assessment of groundwater influenced by a confluence river system: Concurrence with remote sensing and geochemical modelling. Water Resources Management, 27, 4291–4313. doi:10.1007/s11269-013-0408-y
  • Singh, S. K., Srivastava, P. K., & Pandey, A. C. (2013). Fluoride contamination mapping of groundwater in Northern India integrated with geochemical indicators and GIS. Water Science and Technology: Water Supply, 13, 1513–1523. doi:10.2166/ws.2013.160
  • Skidmore, A. K., Varekamp, C., Wilson, L., Knowles, E., & Delaney, J. (1997). Remote sensing of soils in a eucalypt forest environment. International Journal of Remote Sensing, 18(1), 39–56. doi:10.1080/014311697219268
  • Soltani, F., Afzal, P., & Asghari, O. (2014). Delineation of alteration zones based on Sequential Gaussian Simulation and concentration–volume fractal modeling in the hypogene zone of Sungun copper deposit, NW Iran. Journal of Geochemical Exploration, 140, 64–76. doi:10.1016/j.gexplo.2014.02.007
  • Sullivan, D. G., Shaw, J. N., Rickman, D., Mask, P. L., & Luvall, J. C. (2005). Using remote sensing data to evaluate surface soil properties in Alabama Ultisols. Soil Science, 170, 954–968. doi:10.1097/01.ss.0000187350.39611.d7
  • Sun, Y., Zhao, Y. J., Zhang, D. H., Qin, K., & Tian, F. (2016). Application of hydrothermal alteration mineral mapping using airborne hyperspectral remote sensing: Data taken in the Baixianishan region of Gansu Province as an example. Proceedings of Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 10156: UNSP 101561P.
  • Swayze, G. A., Smith, K. S., Clark, R. N., Sutley, S. J., Pearson, R. M., Vance, J. S., … Roth, S. (2000). Using imaging spectroscopy to map acidic mine waste. Environmental Science & Technology, 34(1), 47–54. doi:10.1021/es990046w
  • Szücs, A., Jordán, G., & Qvarfort, U. (2002). Integrated modelling of acid mine drainage impact on a wetland stream using landscape geochemistry, GIS technology and statistical methods. In Fabbri A. G., Gaál G., & McCammon R. B. (Eds.), Deposit and geoenvironmental models for resource exploitation and environmental security. Dordrecht, Netherlands: Springer.
  • Tang, X. G., Liu, D. W., Zhang, B., Du, J., Lei, X. C., Zeng, L. H., … Song, K. S. (2011). Research on hyperspectral remote sensing in monitoring snow contamination concentration. Spectroscopy & Spectral Analysis, 31, 1318–1321.
  • Tangestani, M. H., & Moore, F. (2000). Iron oxide and hydroxyl enhancement using the Crosta Method: A case study from the Zagros Belt, Fars Province, Iran. International Journal of Applied Earth Observation and Geoinformation, 2, 140–146. doi:10.1016/S0303-2434(00)85007-2
  • Thorton, I. (1993). Environmental geochemistry and health in the 1990s: A global perspective. Applied Geochemistry, 8, 203–210.
  • Tiwari, A. K., Singh, P. K., & Mahato, M. K. (2016). Environmental geochemistry and a quality assessment of mine water of the west bokaro coalfield, India. Mine Water and the Environment, 35, 525–535. doi:10.1007/s10230-015-0382-0
  • Tiwari, T., Lidman, F., Laudon, H., Lidberg, W., & Agren, A. M. (2017). GIS-based prediction of stream chemistry using landscape composition, wet areas, and hydrological flow pathways. Journal of Geophysical Research Biogeosciences, 122(1), 65–79.
  • Wang, H. S., Cheng, Q. M., & Zuo, R. G. (2015). Quantifying the spatial characteristics of geochemical patterns via GIS-based geographically weighted statistics. Journal of Geochemical Exploration, 157, 110–119.
  • Wang, K., Franklin, S. E., Guo, X. L., He, Y. H., & Mcdermid, G. (2009). Problems in remote sensing of landscapes and habitats. Progress in Physical Geography, 33, 747–768. doi:10.1177/0309133309350121
  • Wang, R. H., Ning, H. S., Zhao, Z. Y., & Zhang, H. Z. (2009). Coupling relations between oasis soil moisture and salt and its landscape geochemistry characteristics. Jurnal of Nanjing University of Information Science and Technology: Natural Science Edition, 1, 97–101.
  • Wang, S. C., & Cheng, Q. M. (1989). Modelling of gold deposit prospecting. Journal of Jilin University (Earth Science Edition), 19, 311–316.
  • Wang, S. C. (2000). Theory and method of synthetic information mineral resources prognosis. Beijing, China: Science Press.
  • Wang, X. Q. (2003). Exploration geochemistry: Past achievements and future challenges. Earth Science Frontiers, 10(1), 239.
  • Wang, Y. P., & Shen, Y. (2015). Identifying and characterizing yield limiting soil factors with the aid of remote sensing and data mining techniques. Precision Agriculture, 16(1), 99–118. doi:10.1007/s11119-014-9365-6
  • Wang, Y. P. (2000). Trace element geochemical characteristics of plants and their influence on the remote-sensing spectral properties in the North Jiangsu oil field. Chinese Science Bulletin, 45(s1), 26–34. doi:10.1007/BF02893781
  • Wang, Y. X. (1997). Advances in environmental geochemistry: A brief review of the fourth international symposium on environmental geochemistry. Geological Science and Technology Information, 16, 75–77.
  • Welch, R. (1971). Remote sensing for water pollution control. Photogrammetric Engineering, 37, 1285.
  • White, K., & Eckardt, F. (2006). Geochemical mapping of carbonate sediments in the Makgadikgadi basin, Botswana using moderate resolution remote sensing data. Earth Surface Processes and Landforms, 31, 665–681. doi:10.1002/esp.1289
  • Wu, Y. Z., Chen, J., Ji, J. F., Tian, Q. J., & Wu, X. M. (2005). Feasibility of reflectance spectroscopy for the assessment of soil mercury contamination. Environmental Science & Technology, 39, 873–878. doi:10.1021/es0492642
  • Wu, Y. Z., Tian, Q. J., Ji, J. F., & Chen, J. (2003). Study on the remote-sensing geochemistry. Advance in Earth Sciences, 18, 228–235.
  • Wu, Y. Z., Zhang, X., Liao, Q. L., & Ji, J. F. (2011). Can contaminant elements in soils be assessed by remote sensing technology: A case study with simulated data. Soil Science, 176, 196–205. doi:10.1097/SS.0b013e3182114717
  • Xiao, F., & Chen, J. G. (2012). Fractal projection pursuit classification model applied to geochemical survey data. Computers & Geosciences, 45(4):, 75–81. doi:10.1016/j.cageo.2011.10.019
  • Xie, H. P., & Wang, J. N. (1999). Multifractal behaviors of fracture surfaces in rocks. Acta Mechanica Sinica, 30, 314–320.
  • Xie, X. J., & Cheng, H. X. (2001). Global geochemical mapping and its implementation in the Asia–Pacific region. Applied Geochemistry, 16, 1309–1321.
  • Xie, X. J. (2003a). Geochemical mapping and sustainable development of the national economic. Geological Bulletin of China, 22, 863–868.
  • Xie, X. J. (2003b). Exploration geochemistry in 2020: From exploration geochemistry to applied geochemistry. Geological Bulletin of China, 22, 863–868.
  • Xu, R. S. (1992). Remote sensing study of gold biogeochemical effects in the Western Guangdong-Hainan Region- A case study of the Hetai gold deposit. Acta Geologica Sinica, 5, 411–425.
  • Xu, Y. G., & Cheng, Q. M. (2001). A fractal filtering technique for processing regional geochemical maps for mineral exploration. Geochemistry: Exploration, Environment, Analysis, 1, 147–156. doi:10.1144/geochem.1.2.147
  • Xu, Y. M., Smith, S. E., Grunwald, S., Abd-Elrahman, A., & Wani, S. P. (2017). Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields. ISPRS Journal of Photogrammetry & Remote Sensing, 123, 1–19. doi:10.1016/j.isprsjprs.2016.11.001
  • Yang, H. (1999). A Back-propagation Neural Network for mineralogical mapping from AVIRIS data. International Journal of Remote Sensing, 20(1), 97–110. doi:10.1080/014311699213622
  • Yousefi, M., & Carranza, E. J. M. (2015a). Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. Computers and Geosciences, 79, 69–81. doi:10.1016/j.cageo.2015.03.007
  • Yousefi, M., & Carranza, E. J. M. (2015b). Geometric average of spatial evidence data layers: A GIS-based multi-criteria decision-making approach to mineral prospectivity mapping. Computers and Geosciences, 83, 72–79. doi:10.1016/j.cageo.2015.07.006
  • Yu, H., He, Z. W., Kong, B., Weng, Z. Y., & Shi, Z. M. (2016). The Spatial Relationship between Human Activities and C, N, P, S in Soil based on Landscape Geochemical Interpretation. Environmental Geochemistry and Health, 38, 381–398. doi:10.1007/s10653-015-9725-9
  • Yu, H., Kong, B., Du, R. X., Shi, Z. M., & He, Z. W. (2017). The distribution characteristics of halogen elements in soil under the impacts of geographical backgrounds and human disturbances. Geoderma, 305, 236–249. doi:10.1016/j.geoderma.2017.06.011
  • Yu, H., Ni, S. J., He, Z. W., Zhang, C. J., Nan, X., Kong, B., & Weng, Z. Y. (2014). Analysis of the Spatial Relationship between Heavy Metals in Soil and Human Activities based on Landscape Geochemical Interpretation. Journal of Geochemical Exploration, 146, 136–148. doi:10.1016/j.gexplo.2014.08.010
  • Zarina, L. M., Lebedev, S. V., & Nesterov, E. M. (2011). Ecological Geochemical Investigations of the Contents of Heavy Metals in the Snow Cover in the Saint-Petersburg Region with Application of GIS Technologies. International Journal of Chemical Engineering and Applications, 2, 117–121. doi:10.7763/IJCEA.2011.V2.87
  • Zeghouane, H., Allek, K., & Kesraoui, M. (2016). GIS-based weights of evidence modeling applied to mineral prospectivity mapping of Sn-W and rare metals in Laouni area. Central Hoggar, Algeria, Arabian Journal of Geosciences, 9, 373.
  • Zhan, Y., Li, C. Y., Shi, X. H., & Zhang, Y. (2012). Application of fractal theory to the evaluation of water quality in Wuliangsuhai Lake. Journal of Water Resources and Water Engineering, 23, 37–43.
  • Zhang, C. S., Jordan, C., & Higgins, A. (2007). Using neighbourhood statistics and GIS to quantify and visualize spatial variation in geochemical variables: An example using Ni concentrations in the topsoils of Northern Ireland. Geoderma, 137, 466–476. doi:10.1016/j.geoderma.2006.10.018
  • Zhang, C. S., Selinus, O., & Kjellstrom, G. (1999). Discrimination between natural background and anthropogenic pollution in environmental geochemistry: Exemplified in an area of south-eastern Sweden. Science of the Total Environment, 243–244, 129–140. doi:10.1016/S0048-9697(99)00368-X
  • Zhang, C. S., & Selinus, O. (1998). Statistics and GIS in environment geochemistry: Some problems and solutions. Journal of Geochemical Exploration, 64(1–3), 339–354. doi:10.1016/S0375-6742(98)00048-X
  • Zhang, G. L., Gong, Z. T., Zhao, Y. G., Zhao, W. J., & Yang, J. L. (2007). Environmental geochemistry in relation to agriculture and human health in Hainan Island. China, Geochimica Et Cosmochimica Acta, 71, A1156–A1156.
  • Zhang, X., Pazner, M., & Duke, N. (2007). Lithologic and mineral information extraction for gold exploration using ASTER data in the south Chocolate Mountains (California). ISPRS Journal of Photogrammetry & Remote Sensing, 62, 271–282. doi:10.1016/j.isprsjprs.2007.04.004
  • Zuo, R. G., & Carranza, J. (2016). Geoinformatics in applied geochemistry preface. Journal of Geochemical Exploration, 164, 1–2. doi:10.1016/j.gexplo.2016.03.003
  • Zuo, R. G., Cheng, Q. M., Agterberg, F. P., & Xia, Q. L. (2009). Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, western China. Journal of Geochemical Exploration, 101, 225–235. doi:10.1016/j.gexplo.2008.08.003
  • Zuo, R. G., Cheng, Q. M., & Xia, Q. L. (2009). Application of fractal models to characterization of vertical distribution of geochemical element concentration. Journal of Geochemical Exploration, 102(1), 37–43. doi:10.1016/j.gexplo.2008.11.020
  • Zuo, R. G. (2011). Identifying geochemical anomalies associated with Cu and Pb-Zn skarn mineralization using principal component analysis and spectrum–area fractal modeling in the Gangdese Belt, Tibet (China). Journal of Geochemical Exploration, 111 (1–2), 13–22. doi:10.1016/j.gexplo.2011.06.012
  • Zuo, R. G. (2014). Identification of weak geochemical anomalies using robust neighborhood statistics coupled with GIS in covered areas. Journal of Geochemical Exploration, 136, 93–101. doi:10.1016/j.gexplo.2013.10.011
  • Zuo, R. G. (2015). Geoinformatics in applied geochemistry. Journal of Jilin University (Earth Science Edition), 45(s1), 151511–151527.
  • Zuo, R., & Wang, J. (2016). Fractal/multifractal modeling of geochemical data: A review. Journal of Geochemical Exploration, 164, 33–41. doi:10.1016/j.gexplo.2015.04.010

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