Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environment using Spectral Data and Gis Tools

• Autorzy: Grzywna H. , Dąbek P. B. , Olszewska B.

Identyfikatory

DOI

10.12911/22998993/92925

• Języki publikacji: EN

Abstrakty

EN

The studies on agricultural droughts require long-term atmospheric, hydrological and meteorological data. On the other hand, today, the possibilities of using spectral data in environmental studies are indicated. The development of remote sensing techniques, increasing the spectral and spatial resolution of data allows using remote sensing data in the study of water content in the environment. The paper presents the results of the analysis of moisture content of soil-plant environment in the lowland areas of river valley using the spectral data from Sentinel-2. The analyses were conducted between February and November 2016. The spectral data were used to calculate the Normalize Differential Vegetation Index (NDVI) which provided the information about the moisture content of the soil-plant environment. The analyses were performed only on grasslands, on 22 objects located in the research area in the Oder river valley between Malczyce and Brzeg Dolny, Poland. The NDVI values were correlated with the hydrological and meteorological parameters. The analyses showed spatial and temporal variability of the moisture conditions in the soil-plant environment showed by the NDVI variability and existence some relationships between the climatic and spectral indices characterizing the moisture content in the environment.

Słowa kluczowe

EN

drought; soil moisture; NDVI; Sentinel-2; satellite data; remote sensing

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2018
• Tom: Vol. 19, nr 6
• Strony: 56--64
• Opis fizyczny: Bibliogr. 40 poz., rys., tab.

Twórcy

autor

Grzywna H.

• Wrocław University of Environmental and Life Sciences, Institute of Environmental Protection and Development, pl. Grunwaldzki 24, 50-363 Wrocław, Poland

autor

Dąbek P. B.

• Wrocław University of Environmental and Life Sciences, Institute of Environmental Protection and Development, pl. Grunwaldzki 24, 50-363 Wrocław, Poland

autor

Olszewska B.

• Wrocław University of Environmental and Life Sciences, Institute of Environmental Protection and Development, pl. Grunwaldzki 24, 50-363 Wrocław, Poland

Bibliografia

• 1. Al-Bakri J.T., Suleiman A.S. 2004. NDVI response to rainfall in different ecological zones in Jordan. International Journal of Remote Sensing, 25(19), 3897–3912.
• 2. Barbosa H.A.T.V., Lakshmi K., Aydin E.G. 2009. Using the Satellite-Derived NDVI-OLR Feedbacks over West Sahel Africa to Assess Land-Atmosphere Responses to Environmental Change. In AIP Conference Proceedings. pp. 357–360.
• 3. Biniak-Pieróg M. 2008. Wpływ elementów agrometeorologicznych na zmienność zasobów wodnych gleby w półroczu zimowym. Współczesne Problemy Inżynierii Środowiska, VII.
• 4. Carlson T.C., Ripley D. a. 1997. On the relationship between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62, 241–252.
• 5. Chalfen M., Lyczko W., Plywaczyk L. 2014. The prognosis of influence of the Oder River waters dammed by Malczyce barrage on left bank areas. Journal of Water and Land Development, 21(1), 19–27.
• 6. Congedo L. 2016. Semi-Automatic Classification Plugin Documentation. Release 6.0.1.1.
• 7. Dąbrowska-Zielińska K., Ciołkosz A., Malińska A., Bartold M. 2011. Monitoring of agricultural drought in Poland using data derived from environmental satellite images. Geoinformation Issues, 3(1), 87–97.
• 8. Doroszewski A., Marcinkowska I. 1995. Llimatyczny bilans wodny sezonów wegetacyjnych 1921–1993 w Puławach. Środowisko Przyrodnicze Lubelszczyzny. Gleby i Klimat Lubelszczyzny, cz. II – Klimat (J. Kołodziej, R. Turski, red.). Materiały z Konferencji Naukowej Lublin, 25 kwietnia 1994, 193–197.
• 9. Drusch M., Del Bello U., Carlier S., Colin O., Fernandez V., Gascon F., Hoersch B., Isola C., Laberinti P., Martimort P., Meygret A., Spoto F., Sy O., Marchese F., Bargellini P. 2012. Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services. Remote Sensing of Environment, 120, 25–36.
• 10. Dubicki A. i in. 2002. Zasoby wodne w dorzeczu górnej i środkowej Odry w warunkach suszy. IMGW, Warszawa, s. Atlasy i monografie.
• 11. Dzieżyc J, Nowak L., Panek K. Średnie regionalne niedobory opadów i potrzeby deszczowania roślin uprawnych na glebach lekkich i średnich. Zesz. Probl. Post. Nauk Roln., 314, 1987b, s. 35–47.
• 12. Gao B.C. 1996. NDWI – A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3), 257–266.
• 13. Głuchowska B., Pływaczyk L. 2008. Wody gruntowe w dolinie Odry poniżej stopnia wodnego w Brzegu Dolnym. Wspólczesne Problemy Inżynierii Środowiska. V.
• 14. Groeneveld D.P., Baugh W.M. 2007. Correcting satellite data to detect vegetation signal for eco-hydrologic analyses. Journal of Hydrology, 344(1–2), 135–145.
• 15. Grzywna H., Dąbek P.B., Olszewska B. 2018. Analysis of moisture conditions in the lowland areas using high resolution spectral data from the Sentinel-2 satellite and the GIS tools. In Proc. 10th Conference on Interdisciplinary Problems in Environmental Protection and Engineering EKO-DOK 2018.
• 16. Hisdal H., Tallaksen L.. 2000. Technical Report No. 6 Drought Event Definition.
• 17. Huete A., Didan K., Miura H., Rodriguez E.P., Gao X., Ferreira L.F. 2002. Overview of the radiometric and biopyhsical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195–213.
• 18. Jackson T.J., Chen D., Cosh M., Li F., Anderson M., Walthall C., Doriaswamy P., Hunt E.R. 2004. Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sensing of Environment, 92(4), 475–482.
• 19. Jankowiak J., Bieńkowski J. 2011. Kształtowanie I Wykorzystanie Zasobów Wodnych W Rolnictwie. (5), 39–48.
• 20. Jarząbek A., Sarna S., Karpiarz M. 2013. Ochrona przed suszą w planowaniu gospodarowania wodami.
• 21. Kycko M., Zagajewski B. 2013. Wpływ geometrii źródło promieniowania-roślina-detektor na wartość teledetekcyjnych wskaźników roślinności Assessment of geometry of radiation source-plantdetector on value of the remote sensing indices. Teledetekcja Środowiska, 49, 15–26.
• 22. Łabędzki L., Bąk B. 2015.a. Assessment of Soil Moisture on Permanent Grassland in Upper Noteć Valley Based on Soil Moisture Index. Ecological Engineering, 43, 153–159.
• 23. Łabędzki L., Bąk B. 2015.b. Method of IndicatorBased Assessment and Classification of Soil Moisture on Permanent. Infrastructure and Ecology of Rural Areas, (III), 515–531.
• 24. Łabędzki L., Bąk B. 2013. Monitoring i prognozowanie przebiegu i skutków deficytu wody na obszarach wiejskich. Infrastruktura i ekologia terenów wiejskich, (2), 65–76.
• 25. Lauzon N., Anctil F., Petrinovic J. 2004. Characterization of soil moisture conditions at temporal scales from a few days to annual. Hydrological Processes, 18(17), 3235–3254.
• 26. Martínez-Fernández J., González-Zamora A., Sánchez N., Gumuzzio A., Herrero-Jiménez C.M. 2016. Satellite soil moisture for agricultural drought monitoring: Assessment of the SMOS derived Soil Water Deficit Index. Remote Sensing of Environment, 177, 277–286.
• 27. Martyniak L., Dabrowska-Zielinska K., Szymczyk R., Gruszczynska M. 2007. Validation of satellitederived soil-vegetation indices for prognosis of spring cereals yield reduction under drought conditions – Case study from central-western Poland. Advances in Space Research, 39(1), 67–72.
• 28. Mohd Asaari M.S., Mishra P., Mertens S., Dhondt S., Inzé D., Wuyts N., Scheunders P. 2018. Closerange hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform. ISPRS Journal of Photogrammetry and Remote Sensing, 138, 121–138.
• 29. Nichol J.E., Abbas S. 2015. Integration of remote sensing datasets for local scale assessment and prediction of drought. Science of the Total Environment, 505, 503–507.
• 30. Nicolai-Shaw N., Zscheischler J., Hirschi M., Gudmundsson L., Seneviratne S.I. 2017. A drought event composite analysis using satellite remotesensing based soil moisture. Remote Sensing of Environment, 203, 216–225.
• 31. Nyc K. 1994. Rola retencji gruntowej w bilansowaniu zasobów wodnych. Zeszyty Naukowe Akademii Rolniczej we Wrocławiu, nr 248, Konferencje V: 247–251.
• 32. Olszewska B., Pływaczyk L., Łyczko W. 2012. Oddziaływanie spiętrzenia Odry stopniem wodnym w Brzegu dolnym na przepływach w cieku Jeziorka w latach 1971–2020. Water-EnvironmentRural Areas, 12(3), 161–170.
• 33. Pettorelli N., Vik J.O., Mysterud A., Gaillard J.M., Tucker C.J., Stenseth N.C. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 20(9), 503–510.
• 34. Du Plessis W.P. 1999. Linear regression relationships between NDVI, vegetation and rainfall in Etosha National Park, Namibia. Journal of Arid Environments, 42(4), 235–260.
• 35. Pływaczyk L., Olszewska B. 2014. Changes in the moisture content of the middle fen soils in the Odra river valley in the region of Brzeg Dolny in the vegetation periods 2004–2009. Journal of Ecological Engineering, 15(4), 61–68.
• 36. Schmidt H., Gitelson A. 2000. Temporal and spatial vegetation cover changes in Israeli transition zone: AVHRR-based assessment of rainfall impact. International Journal of Remote Sensing, 21(5), 997–1010.
• 37. Torres G.M., Lollato R.P., Ochsner T.E. 2013. Comparison of drought probability assessments based on atmospheric water deficit and soil water deficit. Agronomy Journal, 105(2), 428–436.
• 38. Wang D., Morton D., Masek J., Wu A., Nagol J., Xiong X., Levy R., Vermote E., Wolfe R. 2012. Impact of sensor degradation on the MODIS NDVI time series. Remote Sensing of Environment, 119, 55–61.
• 39. Wang J., Rich P.M., Price K.P. 2003. Temporal responses of NDVI to precipitation and temperature in the central Great Plains , USA. International Journal of Remote Sensing, 24(11), 2345–2364.
• 40. Wójtowicz A., Wójtowicz M., Piekarczyk J. 2005. Zastosowanie teledetekcji do monitorowania i oceny produktywności plantacji rzepaku. Oilseed Crops, XXVI, 269–276.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).