BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Sobura Szymon (Kielce University of Technology, Poland), Hejmanowska Beata (AGH University of Science and Technology Kraków, Poland), Widłak Małgorzata (Kielce University of Technology, Poland), Muszyńska Joanna (Kielce University of Technology, Poland)
The Application of Remote Sensing Techniques and Spectral Analyzes to Assess the Content of Heavy Metals in Soil -A Case Study of Barania Góra Reserve, Poland
Geomatics and Environmental Engineering, 2022, nr 16/4, s. 187-213, rys., tab., wykr., bibliogr. 47 poz.
Metale ciężkie, Informacja przestrzenna, Środowisko przyrodnicze
Heavy metals, Spatial information, Natural environment
The understanding of the spatial and temporal dynamics of farmland processes is essential to ensure the proper crop monitoring and early decision making needed to support efficient resource management in agriculture. By creating appropriate crop management strategies, one can increase harvest efficiency while reducing costs, waste, chemical spraying, and inhibiting the impact of biotic and abiotic factors on crop stress. Only reliable spatial information makes it possible to comprehend the influence of various factors on the environment. The main objective of the research presented in the paper was to assess the possibility of using maps of vegetation and soil indices, such as NDVI, SAVI, IRECI, CIred-edge, PSRI and HMSSI, calculated on the basis of images from the Sentinel-2 satellite, to qualitatively determine the increased amount of heavy metals in the soil in the areas of small agricultural plots around the Barania Góra nature reserve in Poland.The conducted pilot project shows that the spectral indices: NDVI, SAVI, IRECI, CIred-edge, PSRI, and HMSSI, calculated on the basis of images from Sentinel-2, have the potential to assess the content of nickel zinc, chromium and cobalt in the soil on agricultural plots. However, the confirmation of the obtained results requires continuation of the research.(original abstract)
Full text
  1. Ahmed F., Dwivedi S., Shaalan N.M., Kumar S., Arshi N., Alshoaibi A., Husain F.M.: Development of Selenium Nanoparticle Based Agriculture Sensor for Heavy Metal Toxicity Detection. Agriculture, vol. 10, 2020, 610.
  2. Choe E., Meer F., Ruitenbeek F., Werff H., Smeth B., Kyoung-Woong K.: 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, vol. 112(7), 2008, pp. 3222-3233.
  3. Clevers J.G.P.W., Kooistra L., Salas E.A.L.: Study of heavy metal contamination in river floodplains using the red-edge position in spectroscopic data. International Journal of Remote Sensing, vol. 25(19), 2004, pp. 3883-3895.
  4. Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions. Thematic Strategy for Soil Protection. Brussels, 22.09.2006, COM(2006)231 final.
  5. Crema A., Boschetti M., Nutini F., Cillis D., Casa R.: Influence of Soil Properties on Maize and Wheat Nitrogen Status Assessment from Sentinel-2 Data. Remote Sensing, vol. 12(14), 2020, 2175.
  6. Dad F.P., Khan W.D., Tanveer M., Ramzani P.M.A., Shaukat R., Muktadir A.: Influence of Iron-Enriched Biochar on Cd Sorption, Its Ionic Concentration and Redox Regulation of Radish under Cadmium Toxicity. Agriculture, vol. 11(1), 2021, 1.
  7. D'Emilio M., Macchiato M., Ragosta M., Simoniello T.: A method for the integration of satellite vegetation activities observations and magnetic susceptibility measurements for monitoring heavy metals in soil. Journal of Hazardous Materials, vol. 241-242, 2012, pp. 118-126.
  8. Dvorakova K., Shi P., Limbourg Q., Van Wesemael B.: Soil Organic Carbon Mapping from Remote Sensing: The Effect of Crop Residues. Remote Sensing, vol. 12(12), 2020, 1913.
  9. Dworak T., Hejmanowska B., Pyka K.: Problemy teledetekcyjnego monitoringu środowiska. Tom 2. Teledetekcja wód i powierzchni Ziemi. Wydawnictwa AGH, Kraków 2011.
  10. El Hajj M., Baghdadi N., Zribi M., Bazzi H.: Synergic Use of Sentinel-1 and Sentinel-2 Images for Operational Soil Moisture Mapping at High Spatial Resolution over Agricultural Areas. Remote Sensing, vol. 9(12), 2017, 1292.
  11. EN 13346:2000: Characterization of sludges - Determination of trace elements and phosphorous - Aqua regia extraction methods. Comité européen de normalisation, Bruxelles.
  12. Fabre S., Gimenez R., Elger A., Rivière T.: Unsupervised Monitoring Vegetation after the Closure of an Ore Processing Site with Multi-Temporal Optical Remote Sensing. Sensors, vol. 20(17), 2020, 4800.
  13. Gu Y.W., Li S., Gao W., Wei H.: Hyperspectral estimation of the cadmium content in leaves of Brassica rapa chinensis based on spectral parameters. Acta Ecologica Sinica, vol. 35(13), 2015, pp. 4445-4453 [in Chinese with English abstract].
  14. Haneklaus S.H., Bloem E., Schnug E.: Hungry Plants - A Short Treatise on How to Feed Crops under Stress. Agriculture, vol. 8(3), 2018, 43.
  15. Hao P., Löw F., Biradar C.: Annual Cropland Mapping Using Reference Landsat Time Series - A Case Study in Central Asia. Remote Sensing, vol. 10(12), 2018, 2057.
  16. Hejmanowska B., Kramarczyk P., Głowienka E., Mikrut S.: Reliable Crops Classification Using Limited Number of Sentinel-2 and Sentinel-1 Images. Remote Sensing, vol. 13(16), 2021, 3176.
  17. Instrukcja pobierania próbek glebowych z gruntów ornych i użytków zielonych opracowana na podstawie PN-R-04031:1997. [access: 25.09.2022].
  18. ISO 14887:2000: Sample Preparation - Dispersing procedures for powders in liquids.
  19. Jełowicki Ł., Sosnowicz K., Ostrowski W., Osińska-Skotak K., Bakuła K.: Evaluation of Rapeseed Winter Crop Damage Using UAV-Based Multispectral Imagery. Remote Sensing, vol. 12(16), 2020, 2618.
  20. Kabała C., Karczewska A.: Metodyka analiz laboratoryjnych gleb i roślin. Wyd. 8a. Uniwersytet Przyrodniczy we Wrocławiu, Wrocław 2019. [access: 25.09.2022].
  21. Kavats O., Khramov, D., Sergieieva, K., Vasyliev V.: Monitoring Harvesting by Time Series of Sentinel-1 SAR Data. Remote Sensing, vol. 11(21), 2019, 2496.
  22. Khabbazan S., Vermunt P., Steele-Dunne S., Ratering-Arntz L., Marinetti C., van der Valk D., Iannini L. et al.: Crop Monitoring Using Sentinel-1 Data: A Case Study from The Netherlands. Remote Sensing, vol. 11(16), 1887, 2019.
  23. Khaliq A., Comba L., Biglia A., Ricauda Aimonino D., Chiaberge M., Gay P.: Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment. Remote Sensing, vol. 11(4), 2019, 436.
  24. Krasowicz S., Oleszek W., Horabik J., Dębicki R., Jankowiak J., Stuczyński T., Jadczyszyn J.: Racjonalne gospodarowanie środowiskiem glebowym Polski. Polish Journal of Agronomy, vol. 7, 2011, pp. 43-58.
  25. Li M.S., Luo Y.P., Su Z.Y.: Heavy metal concentrations in soils and plant accumulation in a restored manganese mineland in Guangxi, South China. Environmentall Pollution, vol. 147, 2007, pp. 168-175.
  26. Liu K., Zhao D., Fang J., Zhang X., Zhang Q., Li X.: Estimation of HeavyMetal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach. Journal of the Indian Society of Remote Sensing, vol. 45, 2017, pp. 805-813.
  27. Liu T., Liu X., Liu M., Wu L.: Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology. Sensors, vol. 18(3), 2018, 860.
  28. Louis J., Debaecker V., Pflug B., Main-Knorn M., Bieniarz J., Mueller-Wilm U., Cadau E., Gascon F.: Sentinel-2 Sen2cor: L2A Processor for Users. [in:] Ouwehand L. (ed.), Proceedings of Living Planet Symposium 2016, 9-13 May 2016, Prague, Czech Republic, SP-740, European Space Agency, 2016, pp. 1-8.
  29. Mastersizer 3000. Laser diffraction particle size analyzer. [access: 28.10.2020].
  30. McCauley A., Jones C., Olson-Rutz K.: Soil pH and Organic Matter. Nutrient Management Module, no. 8, 2009, 4449-8.
  31. Melendez-Pastor I., Navarro-Pedreño J., Gómez I., Almendro-Candel M.B.: The use of remote sensing to locate heavy metal as source of pollution. [in:] Daniels J.A. (ed.), Advances in Environmental Research. Volume 7, Nova Science Publishers, Hauppauge, New York 2011, pp. 225-233.
  32. Messina G., Peña J.M., Vizzari M., Modica G.: A Comparison of UAV and Satellites Multispectral Imagery in Monitoring Onion Crop. An Application in the 'Cipolla Rossa di Tropea' (Italy). Remote Sensing, vol. 12(20), 2020, 3424.
  33. Osińska-Skotak K.: Metodyka wykorzystania superi hiperspektralnych danych satelitarnych w analizie jakości wód śródlądowych. Prace Naukowe Politechniki Warszawskiej. Geodezja, z. 47, 2010, pp. 3-153.
  34. Osińska-Skotak K.: Wpływ korekcji atmosferycznej zdjęć satelitarnych na wyniki cyfrowej klasyfikacji wielospektralnej. Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarum, vol. 4(1), 2005, pp. 41-53.
  35. PN-ISO 10390:1997: Jakość gleby - Oznaczenie pH. Polski Komitet Normalizacyjny, Warszawa.
  36. Polykretis C., Grillakis M.G., Alexakis D.D.: Exploring the Impact of Various Spectral Indices on Land Cover Change Detection Using Change Vector Analysis: A Case Study of Crete Island, Greece. Remote Sensing, vol. 12(2), 2020, 319.
  37. Rozporządzenie Ministra Środowiska z dnia 5 września 2016 r. w sprawie sposobu prowadzenia oceny zanieczyszczenia powierzchni ziemi [Ordinance of the Minister of the Environment of 5 September 2016 on how to conduct an assessment of land surface pollution]. Dz.U. 2002 nr 165, poz. 1359.
  38. Semikolennykh A.A.: European thematic strategy for soil protection: a review of major documents. Eurasian Soil Science, vol. 41, 2008, pp. 1349-1351.
  39. Sentinel-2 Products Specification Document. Thales Alenia Space, 2017. [access: 20.04.2022].
  40. Shivers S.W., Roberts D.A., McFadden J.P., Tague C.: Using Imaging Spectrometry to Study Changes in Crop Area in California's Central Valley during Drought. Remote Sensing, vol. 10(10), 2018, 1556.
  41. Wang F., Gao J., Zha Y.: Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 136, 2018, pp. 73-84.
  42. Wang P., Chen H., Kopittke P.M., Zhao F.: Cadmium contamination in agricultural soils of China and the impact on food safety. Environmental Pollution, vol. 249, 2019, pp. 1038-1048.
  43. Yi Z., Jia L., Chen Q.: Crop Classification Using Multi-Temporal Sentinel-2 Data in the Shiyang River Basin of China. Remote Sensing, vol. 12, 2020, 4052.
  44. Yuzugullu O., Lorenz F., Fröhlich P., Liebisch F.: Understanding Fields by Remote Sensing: Soil Zoning and Property Mapping. Remote Sensing, vol. 12(7), 2020, 1116.
  45. Zagajewski B., Lechnio J., Sobczak M.: Wykorzystanie teledetekcji hiperspektralnej w analizie roślinności zanieczyszczonej metalami ciężkimi. Teledetekcja Środowiska, vol. 37, 2007, pp. 82-100.
  46. Zhang H., Jiang L., Tanveer M., Ma J., Zhao Z., Wang L.: Indexes of Radicle are Sensitive and Effective for Assessing Copper and Zinc Tolerance in Germinating Seeds of Suaeda salsa. Agriculture, vol. 10, 2020, 445.
  47. Zhang Z., Liu M., Liu X., Zhou G.: A New Vegetation Index Based on Multitemporal Sentinel-2 Images for Discriminating Heavy Metal Stress Levels in Rice. Sensors, vol. 18(7), 2018, 2172.
Cited by
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu