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Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey

Year 2021, Volume: 32 Issue: 4, 10995 - 11011, 01.07.2021
https://doi.org/10.18400/tekderg.590356

Abstract

Climate change and global warming are among the issues that humanity is most concerned about the future. The growing drought and flood risks that increase despite the taken measures have led to the adoption of an integrated understanding on the topic of water management in recent years. To manage the increased risk of drought and to make sustainable planning, the dimensions of drought should be known first. For this purpose, many drought indices have been developed. The Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI), which determined by remote sensing, are two of these. In this study, in which the agricultural drought was analyzed with vegetation indices by taking into consideration the historical drought archive, the Asi Basin was addressed. The data of the Asi Basin, which covers an area of 7800 km2 and was obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High-Resolution Radiometer (AVHRR) satellites, was used in this study. With the satellites benefited in remote sensing and with the Coordination of Information on the Environment (CORINE), where the layers of vegetation were determined, agricultural and forest areas were evaluated separately. The vegetation indices, which change with the increase in temperature, have revealed the necessity of a long-term drought management for the Asi Basin. Result of the work pointed that NDVI index is more appropriated to the Asi Basin than the VCI index to monitor drought.

References

  • D.A. Wilhite, Drought : A Global Assessment, 2000. doi:10.4324/9781315830896.
  • UNDP, DROUGHT RISK MANAGEMENT, 2016.
  • D.A. Wilhite, M.V.K. Sivakumar, R. Pulwarty, Managing drought risk in a changing climate: The role of national drought policy, Weather Clim. Extrem. 3 (2014) 4–13. doi:10.1016/j.wace.2014.01.002.
  • Water Scarcity and Droughts Expert Network, Drought Management Plan Report Including Agricultural, Drought Indicators and Climate Change Aspects European Commission Directorate of Environment, 2008.
  • G.W.P.C. and E. Europe, Guidelines for preparation of the Drought Management Plans Guidelines for preparation of the Drought Management Plans, 2015.
  • M.D. Svoboda, B.A. Fuchs, Handbook of drought indicators and indices, 2017. doi:10.1201/b22009.
  • S. Tekin, 19.Yüzyılın Sonu 20.Yüzyılın Başlarında Batı Anadolu’da Yaşanan Kuraklık Olayları, He J. Acad. Soc. Sci. Stud. Int. (2015) 329–341.
  • S.T. Sarıköse, XIX. Yüzyilda Çukurova’da Doğal Afetler Ve Salgin Hastaliklar, 2013.
  • A. Akbaş, Türkiye Üzerindeki Önemli Kurak Yıllar, Coğrafi Bilim. Derg. 12 (2014) 101–118. doi:10.1501/Cogbil_0000000155.
  • O. Şimşek, M. Yildirim, N. Gördebil, 2013 – 2014 Tarim Yili Kurakli Anali̇zi̇, (2014).
  • I. Nalbantis, Evaluation of a Hydrological Drought Index, Eur. Water. 2324 (2008) 67–77.
  • A.D. Özdemir, M.K. Erkuş, Havza Bazında Hidrolojik Kuraklık Analizi, in: IX Natl. Hydrol. Congr., 2017.
  • V. Gümüş, Akım Kuraklık İndeksi ile Asi Havzasının Hidrolojik Kuraklık Analizi, 5 (2017) 65–73.
  • F.B. Sanli, A. Delen, Assessment of vegetation indices for the determination of agricultural crop types, J. Environ. Prot. Ecol. 19 (2018) 417–425.
  • B. Bulut, M.T. Yılmaz, Türkiye’deki 2007 ve 2013 Yılı Kuraklıklarının NOAH Hidrolojik Modeli ile İncelenmesi, Tek. Dergi. 27 (2016) 7619–7634. http://dergipark.gov.tr/tekderg/issue/28142/299116.
  • O. Gökdemir, A. Arikan, NOAA-AVHRR Uydu Girintileri ile Bölgesel Buharlaşma-Terlemenin Belirlenmesi, (1999) 187–198.
  • M.R. Elowitz, What is Imaging Spectroscopy (Hyperspectral Imaging), (2018). http://www.markelowitz.com/Hyperspectral.html (accessed May 28, 2019).
  • H. Yıldız, A. Mermer, E. Ünal, F. Akbaş, Türkiye Bitki Örtüsünün NDVI Verileri ile Zamansal ve Mekansal Analizi, Tarla Bitk. Merk. Araştırma Enstitüsü Derg. 21 (2012) 50–56. doi:10.21566/tbmaed.43176.
  • M.A. ÇELIK, Investigation the Effect of the Drought Year of 2014 on the Vegetation in the Seyhan Basin, J. Int. Soc. Res. 10 (2017) 424–432. doi:10.17719/jisr.20175434606.
  • A.P.. Cracknel, Advanced very high resolution radiometer, CRC Press, 1997.
  • C.J. Tucker, J.E. Pinzon, M.E. Brown, D.A. Slayback, E.W. Pak, R. Mahoney, E.F. Vermote, N. El Saleous, An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens. 26 (2005) 4485–4498. doi:10.1080/01431160500168686.
  • J.E. Pinzón, M.E. Brown, C.J. Tucker, EMD Correction of Orbital Drift Artifacts in Satellite Data Stream, in: Hilbert?Huang Transform Its Appl., WORLD SCIENTIFIC, 2013: pp. 241–260. doi:10.1142/9789814508247_0011.
  • H. Yin, T. Udelhoven, R. Fensholt, D. Pflugmacher, P. Hostert, How normalized difference vegetation index (NDVI) trends from advanced very high resolution radiometer (AVHRR) and système probatoire d’observation de la terre vegetation (SPOT VGT) time series differ in agricultural areas: An inner mongolian case study, Remote Sens. 4 (2012) 3364–3389. doi:10.5829/idosi.mejsr.2012.12.3.64113.
  • E. Lee, Analysis of MODIS 250 m NDVI Using Different Time-Series Data for Crop Type Separability, 2014.
  • J.R. Nagol, E.F. Vermote, S.D. Prince, Quantification of impact of orbital drift on inter-annual trends in AVHRR NDVI data, Remote Sens. 6 (2014) 6680–6687. doi:10.3390/rs6076680.
  • J.E. Pinzon, C.J. Tucker, A non-stationary 1981-2012 AVHRR NDVI3g time series, Remote Sens. 6 (2014) 6929–6960. doi:10.3390/rs6086929.
  • D.K. Hall, G.A. Riggs, N.E. Digirolamo, K.J. Bayr, MODIS Snow-Cover Products, Remote Sens. Environ. 83 (2002) 181–194. doi:10.1016/S0034-4257(02)00095-0.
  • J.W. Pomeroy, D.M. Gray, T. Brown, N.R. Hedstrom, W.L. Quinton, R.J. Granger, S.K. Carey, The cold regions hydrological model: a platform for basing process representation and model structure on physical evidence, Hydrol. Process. 21 (2007) 1534–1547. doi:10.1002/hyp.6787.
  • T. Lillesand, R.W. Kiefer, J. Chipman, Remote Sensing and Image Interpretation, 7th ed., Wiley, 2015.
  • NASA, NDVI Nasa Data, (n.d.). https://gimms.gsfc.nasa.gov/MODIS/std/GMOD09Q1/tif/NDVI/ (accessed April 25, 2019).
  • M.A. Celik, M. Karabulut, Ahir Daği (Kahramanmaraş) ve Çevresinde Bitki Örtüsü ile Yağiş Koşullari Arasindaki İlişkilerin MODIS Verileri Kullanilarak İncelenmesi, Havacılık VE Uzay Teknol. Derg. 6 (2013) 123–133.
  • S. Aksoy, O. Gorucu, E. Sertel, Drought monitoring using MODIS derived indices and google earth engine platform, 2019 8th Int. Conf. Agro-Geoinformatics, Agro-Geoinformatics 2019. (2019) 1–6. doi:10.1109/Agro-Geoinformatics.2019.8820209.
  • H.E. Beck, T.R. McVicar, A.I.J.M. van Dijk, J. Schellekens, R.A.M. de Jeu, L.A. Bruijnzeel, Global evaluation of four AVHRR-NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sens. Environ. 115 (2011) 2547–2563. doi:10.1016/j.rse.2011.05.012.
  • R.K. Nayak, N. Mishra, V.K. Dadhwal, N.R. Patel, M. Salim, K.H. Rao, C.B.S. Dutt, Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India, J. Earth Syst. Sci. 125 (2016) 1189–1204. doi:10.1007/s12040-016-0723-9.
  • F.N. Kogan, Application of vegetation index and brightness temperature for drought detection, Adv. Sp. Res. 15 (1995) 91–100. doi:10.1016/0273-1177(95)00079-T.
  • S.M. Quiring, S. Ganesh, Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas, Agric. For. Meteorol. 150 (2010) 330–339. doi:10.1016/j.agrformet.2009.11.015.
  • W.T. Liu, F.N. Kogan, Monitoring regional drought using the Vegetation Condition Index, Int. J. Remote Sens. 17 (1996) 2761–2782. doi:10.1080/01431169608949106.
  • S.K. Jain, R. Keshri, A. Goswami, A. Sarkar, Application of meteorological and vegetation indices for evaluation of drought impact: A case study for Rajasthan, India, Nat. Hazards. 54 (2010) 643–656. doi:10.1007/s11069-009-9493-x.
  • O. Orhan, S. Ekercin, Konya Kapalı Havzasında Uzaktan Algılama ve CBS Teknolojileri, in: TUFUAB VIII. Tek. Sempozyumu, Konya, 2015: pp. 202–208.
  • M.A. Çelik, M. Karabulut, Farklı Bi̇tki̇ İndeks Modelleri̇ (Evi, Ndvi, Vci) Kullanılarak Resulosman Dağı Ki̇li̇s Bi̇tki̇ Örtüsünü İncelenmesi̇, in: Coğrafyacılar Derneği Uluslararası Kongresi, Coğrafyacılar Derneği, Muğla, 2014: pp. 372–379.
  • R. Fensholt, I. Sandholt, Evaluation of MODIS and NOAA AVHRR vegetation indices with in situ measurements in a semi-arid environment, Int. J. Remote Sens. 26 (2005) 2561–2594. doi:10.1080/01431160500033724.

Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey

Year 2021, Volume: 32 Issue: 4, 10995 - 11011, 01.07.2021
https://doi.org/10.18400/tekderg.590356

Abstract

Climate change and global warming are among the issues that humanity is most concerned about the future. The growing drought and flood risks that increase despite the taken measures have led to the adoption of an integrated understanding on the topic of water management in recent years. To manage the increased risk of drought and to make sustainable planning, the dimensions of drought should be known first. For this purpose, many drought indices have been developed. The Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI), which determined by remote sensing, are two of these. In this study, in which the agricultural drought was analyzed with vegetation indices by taking into consideration the historical drought archive, the Asi Basin was addressed. The data of the Asi Basin, which covers an area of 7800 km2 and was obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High-Resolution Radiometer (AVHRR) satellites, was used in this study. With the satellites benefited in remote sensing and with the Coordination of Information on the Environment (CORINE), where the layers of vegetation were determined, agricultural and forest areas were evaluated separately. The vegetation indices, which change with the increase in temperature, have revealed the necessity of a long-term drought management for the Asi Basin. Result of the work pointed that NDVI index is more appropriated to the Asi Basin than the VCI index to monitor drought.

References

  • D.A. Wilhite, Drought : A Global Assessment, 2000. doi:10.4324/9781315830896.
  • UNDP, DROUGHT RISK MANAGEMENT, 2016.
  • D.A. Wilhite, M.V.K. Sivakumar, R. Pulwarty, Managing drought risk in a changing climate: The role of national drought policy, Weather Clim. Extrem. 3 (2014) 4–13. doi:10.1016/j.wace.2014.01.002.
  • Water Scarcity and Droughts Expert Network, Drought Management Plan Report Including Agricultural, Drought Indicators and Climate Change Aspects European Commission Directorate of Environment, 2008.
  • G.W.P.C. and E. Europe, Guidelines for preparation of the Drought Management Plans Guidelines for preparation of the Drought Management Plans, 2015.
  • M.D. Svoboda, B.A. Fuchs, Handbook of drought indicators and indices, 2017. doi:10.1201/b22009.
  • S. Tekin, 19.Yüzyılın Sonu 20.Yüzyılın Başlarında Batı Anadolu’da Yaşanan Kuraklık Olayları, He J. Acad. Soc. Sci. Stud. Int. (2015) 329–341.
  • S.T. Sarıköse, XIX. Yüzyilda Çukurova’da Doğal Afetler Ve Salgin Hastaliklar, 2013.
  • A. Akbaş, Türkiye Üzerindeki Önemli Kurak Yıllar, Coğrafi Bilim. Derg. 12 (2014) 101–118. doi:10.1501/Cogbil_0000000155.
  • O. Şimşek, M. Yildirim, N. Gördebil, 2013 – 2014 Tarim Yili Kurakli Anali̇zi̇, (2014).
  • I. Nalbantis, Evaluation of a Hydrological Drought Index, Eur. Water. 2324 (2008) 67–77.
  • A.D. Özdemir, M.K. Erkuş, Havza Bazında Hidrolojik Kuraklık Analizi, in: IX Natl. Hydrol. Congr., 2017.
  • V. Gümüş, Akım Kuraklık İndeksi ile Asi Havzasının Hidrolojik Kuraklık Analizi, 5 (2017) 65–73.
  • F.B. Sanli, A. Delen, Assessment of vegetation indices for the determination of agricultural crop types, J. Environ. Prot. Ecol. 19 (2018) 417–425.
  • B. Bulut, M.T. Yılmaz, Türkiye’deki 2007 ve 2013 Yılı Kuraklıklarının NOAH Hidrolojik Modeli ile İncelenmesi, Tek. Dergi. 27 (2016) 7619–7634. http://dergipark.gov.tr/tekderg/issue/28142/299116.
  • O. Gökdemir, A. Arikan, NOAA-AVHRR Uydu Girintileri ile Bölgesel Buharlaşma-Terlemenin Belirlenmesi, (1999) 187–198.
  • M.R. Elowitz, What is Imaging Spectroscopy (Hyperspectral Imaging), (2018). http://www.markelowitz.com/Hyperspectral.html (accessed May 28, 2019).
  • H. Yıldız, A. Mermer, E. Ünal, F. Akbaş, Türkiye Bitki Örtüsünün NDVI Verileri ile Zamansal ve Mekansal Analizi, Tarla Bitk. Merk. Araştırma Enstitüsü Derg. 21 (2012) 50–56. doi:10.21566/tbmaed.43176.
  • M.A. ÇELIK, Investigation the Effect of the Drought Year of 2014 on the Vegetation in the Seyhan Basin, J. Int. Soc. Res. 10 (2017) 424–432. doi:10.17719/jisr.20175434606.
  • A.P.. Cracknel, Advanced very high resolution radiometer, CRC Press, 1997.
  • C.J. Tucker, J.E. Pinzon, M.E. Brown, D.A. Slayback, E.W. Pak, R. Mahoney, E.F. Vermote, N. El Saleous, An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens. 26 (2005) 4485–4498. doi:10.1080/01431160500168686.
  • J.E. Pinzón, M.E. Brown, C.J. Tucker, EMD Correction of Orbital Drift Artifacts in Satellite Data Stream, in: Hilbert?Huang Transform Its Appl., WORLD SCIENTIFIC, 2013: pp. 241–260. doi:10.1142/9789814508247_0011.
  • H. Yin, T. Udelhoven, R. Fensholt, D. Pflugmacher, P. Hostert, How normalized difference vegetation index (NDVI) trends from advanced very high resolution radiometer (AVHRR) and système probatoire d’observation de la terre vegetation (SPOT VGT) time series differ in agricultural areas: An inner mongolian case study, Remote Sens. 4 (2012) 3364–3389. doi:10.5829/idosi.mejsr.2012.12.3.64113.
  • E. Lee, Analysis of MODIS 250 m NDVI Using Different Time-Series Data for Crop Type Separability, 2014.
  • J.R. Nagol, E.F. Vermote, S.D. Prince, Quantification of impact of orbital drift on inter-annual trends in AVHRR NDVI data, Remote Sens. 6 (2014) 6680–6687. doi:10.3390/rs6076680.
  • J.E. Pinzon, C.J. Tucker, A non-stationary 1981-2012 AVHRR NDVI3g time series, Remote Sens. 6 (2014) 6929–6960. doi:10.3390/rs6086929.
  • D.K. Hall, G.A. Riggs, N.E. Digirolamo, K.J. Bayr, MODIS Snow-Cover Products, Remote Sens. Environ. 83 (2002) 181–194. doi:10.1016/S0034-4257(02)00095-0.
  • J.W. Pomeroy, D.M. Gray, T. Brown, N.R. Hedstrom, W.L. Quinton, R.J. Granger, S.K. Carey, The cold regions hydrological model: a platform for basing process representation and model structure on physical evidence, Hydrol. Process. 21 (2007) 1534–1547. doi:10.1002/hyp.6787.
  • T. Lillesand, R.W. Kiefer, J. Chipman, Remote Sensing and Image Interpretation, 7th ed., Wiley, 2015.
  • NASA, NDVI Nasa Data, (n.d.). https://gimms.gsfc.nasa.gov/MODIS/std/GMOD09Q1/tif/NDVI/ (accessed April 25, 2019).
  • M.A. Celik, M. Karabulut, Ahir Daği (Kahramanmaraş) ve Çevresinde Bitki Örtüsü ile Yağiş Koşullari Arasindaki İlişkilerin MODIS Verileri Kullanilarak İncelenmesi, Havacılık VE Uzay Teknol. Derg. 6 (2013) 123–133.
  • S. Aksoy, O. Gorucu, E. Sertel, Drought monitoring using MODIS derived indices and google earth engine platform, 2019 8th Int. Conf. Agro-Geoinformatics, Agro-Geoinformatics 2019. (2019) 1–6. doi:10.1109/Agro-Geoinformatics.2019.8820209.
  • H.E. Beck, T.R. McVicar, A.I.J.M. van Dijk, J. Schellekens, R.A.M. de Jeu, L.A. Bruijnzeel, Global evaluation of four AVHRR-NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sens. Environ. 115 (2011) 2547–2563. doi:10.1016/j.rse.2011.05.012.
  • R.K. Nayak, N. Mishra, V.K. Dadhwal, N.R. Patel, M. Salim, K.H. Rao, C.B.S. Dutt, Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India, J. Earth Syst. Sci. 125 (2016) 1189–1204. doi:10.1007/s12040-016-0723-9.
  • F.N. Kogan, Application of vegetation index and brightness temperature for drought detection, Adv. Sp. Res. 15 (1995) 91–100. doi:10.1016/0273-1177(95)00079-T.
  • S.M. Quiring, S. Ganesh, Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas, Agric. For. Meteorol. 150 (2010) 330–339. doi:10.1016/j.agrformet.2009.11.015.
  • W.T. Liu, F.N. Kogan, Monitoring regional drought using the Vegetation Condition Index, Int. J. Remote Sens. 17 (1996) 2761–2782. doi:10.1080/01431169608949106.
  • S.K. Jain, R. Keshri, A. Goswami, A. Sarkar, Application of meteorological and vegetation indices for evaluation of drought impact: A case study for Rajasthan, India, Nat. Hazards. 54 (2010) 643–656. doi:10.1007/s11069-009-9493-x.
  • O. Orhan, S. Ekercin, Konya Kapalı Havzasında Uzaktan Algılama ve CBS Teknolojileri, in: TUFUAB VIII. Tek. Sempozyumu, Konya, 2015: pp. 202–208.
  • M.A. Çelik, M. Karabulut, Farklı Bi̇tki̇ İndeks Modelleri̇ (Evi, Ndvi, Vci) Kullanılarak Resulosman Dağı Ki̇li̇s Bi̇tki̇ Örtüsünü İncelenmesi̇, in: Coğrafyacılar Derneği Uluslararası Kongresi, Coğrafyacılar Derneği, Muğla, 2014: pp. 372–379.
  • R. Fensholt, I. Sandholt, Evaluation of MODIS and NOAA AVHRR vegetation indices with in situ measurements in a semi-arid environment, Int. J. Remote Sens. 26 (2005) 2561–2594. doi:10.1080/01431160500033724.
There are 41 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Mehmet Dikici 0000-0001-5955-3425

Murat Aksel 0000-0002-6456-4396

Publication Date July 1, 2021
Submission Date July 10, 2019
Published in Issue Year 2021 Volume: 32 Issue: 4

Cite

APA Dikici, M., & Aksel, M. (2021). Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey. Teknik Dergi, 32(4), 10995-11011. https://doi.org/10.18400/tekderg.590356
AMA Dikici M, Aksel M. Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey. Teknik Dergi. July 2021;32(4):10995-11011. doi:10.18400/tekderg.590356
Chicago Dikici, Mehmet, and Murat Aksel. “Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey”. Teknik Dergi 32, no. 4 (July 2021): 10995-11. https://doi.org/10.18400/tekderg.590356.
EndNote Dikici M, Aksel M (July 1, 2021) Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey. Teknik Dergi 32 4 10995–11011.
IEEE M. Dikici and M. Aksel, “Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey”, Teknik Dergi, vol. 32, no. 4, pp. 10995–11011, 2021, doi: 10.18400/tekderg.590356.
ISNAD Dikici, Mehmet - Aksel, Murat. “Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey”. Teknik Dergi 32/4 (July 2021), 10995-11011. https://doi.org/10.18400/tekderg.590356.
JAMA Dikici M, Aksel M. Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey. Teknik Dergi. 2021;32:10995–11011.
MLA Dikici, Mehmet and Murat Aksel. “Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey”. Teknik Dergi, vol. 32, no. 4, 2021, pp. 10995-11, doi:10.18400/tekderg.590356.
Vancouver Dikici M, Aksel M. Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey. Teknik Dergi. 2021;32(4):10995-1011.