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Uydu Görüntülerinden Elde Edilen Yüzey Sıcaklığı ve Vejetasyon İndeksleri ile Tarımsal Kuraklığın İzlenmesi

Year 2020, The Journal of Agricultural Faculty of Ege University Special Issue 2020, 151 - 160, 31.12.2020
https://doi.org/10.20289/zfdergi.836217

Abstract

Objective: This study aimed to examine and investigate agricultural drought in the Menemen Right Bank Irrigation Area with the help of Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index indices (SAVI).
Material and Method: LANDSAT-8 OLI satellite images were used in the study. Transferring of satellite images to computer and processing of it was carried out with ArcGIS 10.3 and ENVI 10.4 software. NDVI, SAVI and LST indices were used in the assessment of drought.
Results: The result of the study revealed that R2 values between LST and NDVI were 0.82 and 0.95 for the years 2015 and 2016 respectively, while the corresponding values for the LST-SAVI correlation were 0.87 and 0.87. The R2 values between NDVI and SAVI were 0.77 and 0.76 for 2015 and 2016 respectively. This study shows that satellite data and the vegetation indices derived from it can be used in monitoring agricultural drought.

References

  • Abdalla, N.I., Gaiballa, A.K., Kätsch, C., Sulieman, M., Mariod, A. 2015. Using MODIS- Derived NDVI and SAVI to distinguish between different rangeland sites according to soil types in semi-arid areas of Sudan (North Kordofan State). International Journal of Life Science and Engineering. Volume 1(4). pp. 150-164. Available at: https://www.researchgate.net/publication/280113183.
  • Alemu, M.M. 2019. Analysis of spatio-temporal land surface temperature and normalized difference vegetation index changes in the Andassa Watershed Blue Nile Basin. Ethiopia J, Resour. Ecol: 10(1).pp. 77-85. Available at: . doi: 10.5814/j.issn.1674-764X.2019.01.010.
  • Bayar, R. 2018. Arazi Kullanımı Açısından Türkiye’de Tarım Alanlarının Değişimi. Coğrafi Bilimler Dergisi CBD: 16 (2).pp. 187- 200. Available at: https://doi.org/10.1501/Cogbil_0000000197.
  • Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., and Qian, Q. 2018. Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, volume 8, Article number: 641. Available at: doi:10.1038/s41598-017-19088-x.
  • FAO. 2018. The impact of disasters and crises on agriculture and food security. ISBN: 978-92-5-130359-7.pp. 1-168. Available at: http://www.fao.org/3/I8656EN/i8656en.pdf.
  • Gaikwad, S.V., Kale, K.V. 2015. Agricultural drought assessment of post monsoon season of vaıjapur taluka using landsat8. International Journal of Research in Engineering and Technology. eISSN: 2319-1163 | pISSN: 2321-7308. Available at: https://www.academia.edu/21611859.
  • Gorgani, S.A., Panahi, M., Rezaie, F. 2013. The Relationship between NDVI and LST in the urban area of Mashhad, Iran. Conference: International Conference on Civil Engineering Architecture & Urban Sustainable Development at: Tabriz, Iran. Available at: https://www.researchgate.net/publication/265601825.
  • Gündoğdu, K.S., Bantchina, B.B. 2018. Landsat Uydu Görüntülerinden NDVI Değer Dağılımının Parsel Bazlı Değerlendirilmesi, Uludağ Üniversitesi Ziraat Fakültesi Çiftlik Arazisi Örneği. Journal of Agricultural Faculty of Bursa Uludgu University. Volume 32, Issue (2): 45-53. e-ISSN 2651-4044. Available at: http://dergipark.gov.tr/bursauludagziraat; http://www.uludag.edu.tr/ziraatdergi.
  • Hishe, S., Lyimo, J., Bewket, W. 2017. Effects of soil and water conservation on vegetation cover: a remote sensing based study in the Middle Suluh River Basin, Northern Ethiopia. Environmental Systems Research, 6(26). Available at: https://doi.org/10.1186/s40068-017-0103-8.
  • Hu, X., Ren, H., Tansey, K., Zheng, Y., Ghent, D., Liu, X., Yan, L. 2019. Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries. Agricultural and Forest Meteorology. Volume 279, 15 December. Available at: https://doi.org/10.1016/j.agrformet.2019.107707.
  • Huete, A. 1988. Soil-Adjusted Vegetation İndex (SAVI). Remote Sensing of Environment, Volume 25, Issue 3. pp. 295-309. Available at: DOI: 10.1016/0034-4257(88)90106-X.
  • Joshi, J.P., Bhatt, B. 2012. Estimating temporal land surface temperature using remote sensing: a study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences. Volume 2:(1).pp. 123-130. Available at: http://www.cibtech.org/jgee.htm.
  • Kayet, N., Pathak, K., Chakrabarty, A., Sahoo, S. 2016. Urban heat island explored by co-relationship between land surface temperature vs multiple vegetation indices. Spatial Information Research, volume 24. pp.515–529. Available at: DOI 10.1007/s41324-016-0049-3.
  • Kukul, Y.S., Akçay, S., Anaç, S., Yeşilırmak, E. 2008. Temporal irrigation performance assessment in Turkey: Menemen case study. Agricultural Water Management. Available at: DOI:10.1016/j.agwat.2008.04.005 · Source: RePEc.
  • Kumar, D., Shekhar, S. 2015. Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing. Ecotoxicology and Environmental Safety (121). pp.39-44, https://doi.org/10.1016/j.ecoenv.2015.07.004.
  • Lu, L., Kuenzer, C., Wang, C., Guo, H., Li, Q. 2015. Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring. Remote Sens. 7. Pp.7597-7614. Available at: doi:10.3390/rs70607597.
  • Nivedha Deve, S., Jasmineniketha, M., Geetha, P., Soman, K.P. 2017. Agricultural drought analysis for Thuraiyur Taluk of Tiruchirappali District using NDVI and land surface temperature data. 11 th International Conference on Intelligent Systems and Control (ISCO). Available at: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015105979&doi=10.1109%2fISCO.2017.7855972&partnerID=40&md5=eddcada0ba7cdff368ab85c67c753f84.
  • Orman ve Su İşleri Bakanliği. 2014. Available at: http://basinhaber.ormansu.gov.tr/osb/osb/Bakanlik.aspx?sflang=tr adresinden alındı.
  • Ozkul, S. 2009. Assesment of climate change effects in Aegean river basins: the case of Gediz and Buyuk Menderes Basins. Climatic Change, volume 97. pp.253–283. Available at: DOI 10.1007/s10584-009-9589-z.
  • Pamuk, G., Sensoy, S., Akkuzu, E. 2008. Effects of global climate change on agriculture and water resources. BALWOIS 2008 – Ohrid, Republic of Macedonia – 27. Available at: https://www.researchgate.net/publication/228633521.
  • Perez, G.J., Macapagal, M., Olivaresa, R., Macapagal, E.M., Comisob, J.C. 2016. Forecasting and Monitoring Agricultural Drought in The Philippines The International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, Volume XLI-B8, Congress XXIII ISPRS. Prague: Czech Republic.pp. 12–19. Available at: doi:10.5194/isprsarchives-XLI-B8-1263-2016.
  • Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. 1973. Monitoring vegetation systems in the Great Plains with ERTS, 3rd ERTS Symposium, NASA SP-351, Washington DC, 10-14 December. pp.309-317. Available at: 19740022614.pdf.
  • Saini, V., Gupta, R.P., Arora, M.K. 2016. Relationship between surface temperature and SAVI using Landsat data in a coal mining area in India. SPIE Asia-Pacific Remote Sensing. New Delhi, India. Available at: https://doi.org/10.1117/12.2228094.
  • Topcuoğlu, K., Mengu, P.G., Anac, S. 2008. Ege Bölgesi Meteorolojik Kuraklık Analizi, " Konya Kapalı Havzası Yeraltısuyu ve Kuraklık Konferansı. Çevre ve Orman Başkanlığı Devlet Su İşleri Genel Müdürlüğü. pp. 4-30. Available at: https://www.tarimorman.gov.tr/SYGM/Belgeler/TEZLER/Yeliz%20SARICAN-Uzmanl%C4%B1k%20Tezi%20(2).pdf.
  • Toprak Su. 1971. Gediz Ovası Toprakları, Köy İşleri Bakanlığı Yayınları: 125. Topraksu Genel Müdürlüğü Yayınları: 220. Raporlar Serisi: 8, Ankara s.pp. 3-12. Available at: https://arastirma.tarimorman.gov.tr/tokatarastirma/Belgeler/kitap.pdf.
  • Unal, H.B., Asik, S., Avci, M., Yasar, S., Akkuzu, E. 2004. Performance of water delivery system at tertiary canal level: a case study of the Menemen Left Bank Irrigation System, Gediz Basin, Turkey. Agricultural Water Management (65). pp.155–171. Available at: doi:10.1016/j.agwat.2003.10.002.
  • Vani, V., and Mandla, V.R. 2017. Comparative study of NDVI and SAVI vegetation indices in Anantapur district semi-arid areas. International Journal of Civil Engineering and Technology, volume 8(4). pp.559-566. Available at: http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=4.
  • Waters, R.A. 2002. SEBAL surface energy balance algorithms for land Idaho implementation advanced training and user’s manual. Version 1.0. University of Idaho. Kimberly. Idaho. Available at: http://www.posmet.ufv.br/wp-content/uploads/2016/09/MET-479-Waters-et-al-SEBAL.pdf.
  • Wiesam, E., Boud, V., Johannes, K., Tim, V., Okke, B. 2012. Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation. Volume 19. pp.163-172. Available at: DOI: 10.1016/j.jag.2012.05.010.
  • Yildirim, T. 2012. Menemen Ovası Sulama Uygulamalarının Coğrafi Bilgi Sistemi Ve Uzaktan Algılama İle Değerlendirilmesi. Ege Üniversitesi, Fen Bilimleri Enstitüsü. 78s (Yayımlanmamış).
  • Yue, W., Xu, J., Tan, W., Xu, L. 2007. The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat & ETM+ data. International Journal of Remote Sensing. Volume 28. Issue 15. pp.3205-3226. Aavailable at: https://doi.org/10.1080/01431160500306906.

Agricultural Drought Monitoring Using Surface Temperature and Vegetation Indices from Satellite Images

Year 2020, The Journal of Agricultural Faculty of Ege University Special Issue 2020, 151 - 160, 31.12.2020
https://doi.org/10.20289/zfdergi.836217

Abstract

Amaç: Bu çalışmanın amacı, LST, NDVI ve SAVI indeksleri yardımıyla LANDSAT 8 uydu görüntüleri kullanılarak Menemen Sağ Sahil sulama alanındaki tarımsal kuraklığı irdelemek ve incelemektir.
Materyal ve Metot: Araştırmada LANDSAT-8 OLI uydu görüntülerinin bilgisayar ortamına aktarılması ve işlenmesi, ArcGIS 10.3 ve ENVI 10.4 yazılımlarıyla gerçekleştirilmiştir. Kuraklığın değerlendirilmesinde, NDVI, SAVI ve LST indeksleri kullanılmıştır.
Sonuçlar: Araştırma sonucunda, LST-NDVI arasındaki ilişkinin R2 değerleri 2015 ve 2016 yıllarında sırasıyla 0,8203 ve 0,9496 olurken LST-SAVI arasındaki ilişkinin R2 değerleri ise yıllara göre sırasıyla 0,8725 ve 0,8682 olmuştur. NDVI ve SAVI arasındaki ilişkinin R2 değerleri 2015 ve 2016 yıllarında sırasıyla 0,7702 ve 0,7574 olmuştur. Bu çalışmayla, uydu verilerinin ve bunlara bağlı olarak elde edilen vejetasyon indekslerinin tarımsal kuraklığın izlenmesinde kullanılabileceği ortaya konulmuştur.

References

  • Abdalla, N.I., Gaiballa, A.K., Kätsch, C., Sulieman, M., Mariod, A. 2015. Using MODIS- Derived NDVI and SAVI to distinguish between different rangeland sites according to soil types in semi-arid areas of Sudan (North Kordofan State). International Journal of Life Science and Engineering. Volume 1(4). pp. 150-164. Available at: https://www.researchgate.net/publication/280113183.
  • Alemu, M.M. 2019. Analysis of spatio-temporal land surface temperature and normalized difference vegetation index changes in the Andassa Watershed Blue Nile Basin. Ethiopia J, Resour. Ecol: 10(1).pp. 77-85. Available at: . doi: 10.5814/j.issn.1674-764X.2019.01.010.
  • Bayar, R. 2018. Arazi Kullanımı Açısından Türkiye’de Tarım Alanlarının Değişimi. Coğrafi Bilimler Dergisi CBD: 16 (2).pp. 187- 200. Available at: https://doi.org/10.1501/Cogbil_0000000197.
  • Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., and Qian, Q. 2018. Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, volume 8, Article number: 641. Available at: doi:10.1038/s41598-017-19088-x.
  • FAO. 2018. The impact of disasters and crises on agriculture and food security. ISBN: 978-92-5-130359-7.pp. 1-168. Available at: http://www.fao.org/3/I8656EN/i8656en.pdf.
  • Gaikwad, S.V., Kale, K.V. 2015. Agricultural drought assessment of post monsoon season of vaıjapur taluka using landsat8. International Journal of Research in Engineering and Technology. eISSN: 2319-1163 | pISSN: 2321-7308. Available at: https://www.academia.edu/21611859.
  • Gorgani, S.A., Panahi, M., Rezaie, F. 2013. The Relationship between NDVI and LST in the urban area of Mashhad, Iran. Conference: International Conference on Civil Engineering Architecture & Urban Sustainable Development at: Tabriz, Iran. Available at: https://www.researchgate.net/publication/265601825.
  • Gündoğdu, K.S., Bantchina, B.B. 2018. Landsat Uydu Görüntülerinden NDVI Değer Dağılımının Parsel Bazlı Değerlendirilmesi, Uludağ Üniversitesi Ziraat Fakültesi Çiftlik Arazisi Örneği. Journal of Agricultural Faculty of Bursa Uludgu University. Volume 32, Issue (2): 45-53. e-ISSN 2651-4044. Available at: http://dergipark.gov.tr/bursauludagziraat; http://www.uludag.edu.tr/ziraatdergi.
  • Hishe, S., Lyimo, J., Bewket, W. 2017. Effects of soil and water conservation on vegetation cover: a remote sensing based study in the Middle Suluh River Basin, Northern Ethiopia. Environmental Systems Research, 6(26). Available at: https://doi.org/10.1186/s40068-017-0103-8.
  • Hu, X., Ren, H., Tansey, K., Zheng, Y., Ghent, D., Liu, X., Yan, L. 2019. Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries. Agricultural and Forest Meteorology. Volume 279, 15 December. Available at: https://doi.org/10.1016/j.agrformet.2019.107707.
  • Huete, A. 1988. Soil-Adjusted Vegetation İndex (SAVI). Remote Sensing of Environment, Volume 25, Issue 3. pp. 295-309. Available at: DOI: 10.1016/0034-4257(88)90106-X.
  • Joshi, J.P., Bhatt, B. 2012. Estimating temporal land surface temperature using remote sensing: a study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences. Volume 2:(1).pp. 123-130. Available at: http://www.cibtech.org/jgee.htm.
  • Kayet, N., Pathak, K., Chakrabarty, A., Sahoo, S. 2016. Urban heat island explored by co-relationship between land surface temperature vs multiple vegetation indices. Spatial Information Research, volume 24. pp.515–529. Available at: DOI 10.1007/s41324-016-0049-3.
  • Kukul, Y.S., Akçay, S., Anaç, S., Yeşilırmak, E. 2008. Temporal irrigation performance assessment in Turkey: Menemen case study. Agricultural Water Management. Available at: DOI:10.1016/j.agwat.2008.04.005 · Source: RePEc.
  • Kumar, D., Shekhar, S. 2015. Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing. Ecotoxicology and Environmental Safety (121). pp.39-44, https://doi.org/10.1016/j.ecoenv.2015.07.004.
  • Lu, L., Kuenzer, C., Wang, C., Guo, H., Li, Q. 2015. Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring. Remote Sens. 7. Pp.7597-7614. Available at: doi:10.3390/rs70607597.
  • Nivedha Deve, S., Jasmineniketha, M., Geetha, P., Soman, K.P. 2017. Agricultural drought analysis for Thuraiyur Taluk of Tiruchirappali District using NDVI and land surface temperature data. 11 th International Conference on Intelligent Systems and Control (ISCO). Available at: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015105979&doi=10.1109%2fISCO.2017.7855972&partnerID=40&md5=eddcada0ba7cdff368ab85c67c753f84.
  • Orman ve Su İşleri Bakanliği. 2014. Available at: http://basinhaber.ormansu.gov.tr/osb/osb/Bakanlik.aspx?sflang=tr adresinden alındı.
  • Ozkul, S. 2009. Assesment of climate change effects in Aegean river basins: the case of Gediz and Buyuk Menderes Basins. Climatic Change, volume 97. pp.253–283. Available at: DOI 10.1007/s10584-009-9589-z.
  • Pamuk, G., Sensoy, S., Akkuzu, E. 2008. Effects of global climate change on agriculture and water resources. BALWOIS 2008 – Ohrid, Republic of Macedonia – 27. Available at: https://www.researchgate.net/publication/228633521.
  • Perez, G.J., Macapagal, M., Olivaresa, R., Macapagal, E.M., Comisob, J.C. 2016. Forecasting and Monitoring Agricultural Drought in The Philippines The International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, Volume XLI-B8, Congress XXIII ISPRS. Prague: Czech Republic.pp. 12–19. Available at: doi:10.5194/isprsarchives-XLI-B8-1263-2016.
  • Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. 1973. Monitoring vegetation systems in the Great Plains with ERTS, 3rd ERTS Symposium, NASA SP-351, Washington DC, 10-14 December. pp.309-317. Available at: 19740022614.pdf.
  • Saini, V., Gupta, R.P., Arora, M.K. 2016. Relationship between surface temperature and SAVI using Landsat data in a coal mining area in India. SPIE Asia-Pacific Remote Sensing. New Delhi, India. Available at: https://doi.org/10.1117/12.2228094.
  • Topcuoğlu, K., Mengu, P.G., Anac, S. 2008. Ege Bölgesi Meteorolojik Kuraklık Analizi, " Konya Kapalı Havzası Yeraltısuyu ve Kuraklık Konferansı. Çevre ve Orman Başkanlığı Devlet Su İşleri Genel Müdürlüğü. pp. 4-30. Available at: https://www.tarimorman.gov.tr/SYGM/Belgeler/TEZLER/Yeliz%20SARICAN-Uzmanl%C4%B1k%20Tezi%20(2).pdf.
  • Toprak Su. 1971. Gediz Ovası Toprakları, Köy İşleri Bakanlığı Yayınları: 125. Topraksu Genel Müdürlüğü Yayınları: 220. Raporlar Serisi: 8, Ankara s.pp. 3-12. Available at: https://arastirma.tarimorman.gov.tr/tokatarastirma/Belgeler/kitap.pdf.
  • Unal, H.B., Asik, S., Avci, M., Yasar, S., Akkuzu, E. 2004. Performance of water delivery system at tertiary canal level: a case study of the Menemen Left Bank Irrigation System, Gediz Basin, Turkey. Agricultural Water Management (65). pp.155–171. Available at: doi:10.1016/j.agwat.2003.10.002.
  • Vani, V., and Mandla, V.R. 2017. Comparative study of NDVI and SAVI vegetation indices in Anantapur district semi-arid areas. International Journal of Civil Engineering and Technology, volume 8(4). pp.559-566. Available at: http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=4.
  • Waters, R.A. 2002. SEBAL surface energy balance algorithms for land Idaho implementation advanced training and user’s manual. Version 1.0. University of Idaho. Kimberly. Idaho. Available at: http://www.posmet.ufv.br/wp-content/uploads/2016/09/MET-479-Waters-et-al-SEBAL.pdf.
  • Wiesam, E., Boud, V., Johannes, K., Tim, V., Okke, B. 2012. Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation. Volume 19. pp.163-172. Available at: DOI: 10.1016/j.jag.2012.05.010.
  • Yildirim, T. 2012. Menemen Ovası Sulama Uygulamalarının Coğrafi Bilgi Sistemi Ve Uzaktan Algılama İle Değerlendirilmesi. Ege Üniversitesi, Fen Bilimleri Enstitüsü. 78s (Yayımlanmamış).
  • Yue, W., Xu, J., Tan, W., Xu, L. 2007. The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat & ETM+ data. International Journal of Remote Sensing. Volume 28. Issue 15. pp.3205-3226. Aavailable at: https://doi.org/10.1080/01431160500306906.
There are 31 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Şerafettin Aşık 0000-0002-5888-8829

Publication Date December 31, 2020
Submission Date December 5, 2020
Acceptance Date December 14, 2020
Published in Issue Year 2020 The Journal of Agricultural Faculty of Ege University Special Issue 2020

Cite

APA Aşık, Ş. (2020). Agricultural Drought Monitoring Using Surface Temperature and Vegetation Indices from Satellite Images. Journal of Agriculture Faculty of Ege University151-160. https://doi.org/10.20289/zfdergi.836217

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