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Assessment of Rangeland Vegetation Condition from Time Series NDVI Data

Year 2014, Volume: 23 Issue: 1, 14 - 22, 23.07.2014
https://doi.org/10.21566/tbmaed.41458

Abstract

The great spatial extent of rangelands has prompted a need for more efficient and cost effective management tools. Satellite based normalized difference vegetation index (NDVI) data offers improved and timely monitoring of rangeland vegetation. Since elevation is one of the factors affecting vegetation phenology, it should be considered when assessing vegetation status of rangelands.  In this study, rangeland condition was determined by classifying an elevation-normalized NDVI image (EN-NDVI) produced by a conditional rule approach based on elevation data representing active growing season of rangelands in whole project area.  A supervised classification algorithm was used to obtain four rangeland conditions called “very good”, “good”, “moderate” and “poor”.   The results revealed that the coverage of each range condition was; 10.02% “very good”,  20.55% “good”, 31.83% “moderate” and  37.60% “poor”. General classification accuracy and Kappa statistic values were 52.5% and 0.30 respectively.  

References

  • Alesheikh A.A., Fard FSN., 2007. Design and implementation of a knowledge based system to improve maximum likelihood classification accuracy. Canadian Journal of Remote Sensing, 33: 459-467
  • Avağ A., Simsek U., Uzun M., 2012. Database activities of national grassland management project. Tarım Bilimleri Dergisi. 5: 102-106
  • Congalton R.E.G., 1991. A review of assessing the accuracy of classification of remotely sensed data. Remote Sensing of Environment, 37: 35-36
  • Çomaklı B., Fayetörtbay D., Daşcı M., 2012. Changing of botanical composition and canopy Coverage Ratio in Rangelands at Different Altitudes. Journal of Agriculture Faculty of Atatürk University., 43: 17-21
  • Dyksterhuis E.J., 1949. Condition and management of range land based on quantitative ecology. Journal of Range Management, 2: 104-115
  • Dymond J.R., Stephens P.R., Newsome P.F., Wilde R.H., 1992. Percentage vegetation cover of a degrading rangeland from SPOT. International Journal of Remote Sensing, 13: 1999–2007
  • ESRI 1998. ESRI Shapefile Technical Description. An ESRI White Paper—July 1998
  • Fırıncıoglu H.K., 2004. An assessment of the pasture and forage production of Turkey. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, 13: 1-28
  • Frost W.E., and Smith E.L., 1991. Biomass productivity and range condition on range sites in southern Arizona. J. Range Manage. 44:64-67
  • Friedl M.H., 1991. Range condition assessment and the concept of thresholds: A viewpoint. Journal of Range Management, 44: 422-426
  • Friedl M.A., Michaelsenn J., Dawis F.W., Walker H. and Schimel D.S., 1994. Estimating grassland biomass and leaf area index using ground and satellite data. International Journal of Remote Sensing, 15: 1401-1420
  • Foody G.M., 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80: 185-201
  • Geerken R., Zaitchik B., Evans J.P., 2005. Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity. International Journal of Remote Sensing. Vol. 26, No. 24, 5535–5554
  • Gitelson A., 2004. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology 161: 165-173
  • Holben B.N., 1986. Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing, 7: 1417-1434
  • Javzandulam T., Tateishi T., Sanjaa T., 2005. Analysis of vegetation indices for monitoring vegetation degradation in semi-arid and arid areas of Mongolia. International Journal of Environmental Studies, 62: 215–225
  • Jianlong L., Tiangang L., Quangong C., 1998. Estimating grassland yields using remote sensing and GIS Technologies in China. New Zealand Journal of Agricultural Research, 41: 31-38
  • Kennedy P., 1989. Monitoring the vegetation of Tunisian grazing lands using the normalized difference vegetation index. Ambio, 18: 119-123
  • Koç A., Çakal Ş., 2004. Comparison of Some Rangeland Canopy Coverage Methods. In: Proceedings of International Soil Congress Natural Resource Management for Sustainable Development. 7-10 June, Erzurum, Türkiye, pp.41-45
  • Kogan F., Stark R., Gitelson A., Jargalsaikhan L., Dugrajav C., Tsooj S., 2004. Derivation of pasture biomass in Mongolia from AVHRR-based vegetation health indices. International Journal of Remote Sensing, 25: 2889-2896
  • Laycock W.A, 1991. Stable states and thresholds of range condition of North American rangelands: A viewpoint. Journal of Range Management, 44:427-433
  • Manandhar R., Inakwu O.A., Ancev T., 2009. Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement. Remote Sensing of Environment 1: 330-344
  • Reeves M.C., Winslow J.C., Running S.W., 2001. Mapping Weekly Rangeland Vegetation Productivity Using MODIS Algorithms. Journal of Range Management, 54: 90-105
  • Mermer A., Unal E., Aydogdu M., Urla O., Yıldız H., Torunlar H., Avağ A., Tugaç M.G., Ozaydın K.A., Dedeoglu F., Aydogmus O., 2012. Determining Rangeland Areas by Satellite Images. Tarım Bilimleri Dergisi, 5: 107-110
  • Solorio T., Fuentes O., 2002. Improving Classification Accuracy of Large Test Sets Using the Ordered Classification Algorithm. In: Proceeding of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence. pp:70-79
  • Todd S.W., Hoffer R.M., Milchunas D.G., 1998. Biomass estimation on grazed and ungrazed rangelands using spectral indices. International Journal of Remote Sensing, 19: 427- 438
  • USDA 1997. National Range and Pasture Handbook, Grazing Lands Technology Institute, Natural Resource Conservation Service, USDA, Washington, D.C
  • Ünal E., 2011. Işık Kullanım Etkinliği (LUE) Modeli ile Çankırı İlindeki Meralarda Biyokütle Tahmini. Doktora Tezi. Ankara Üniversitesi. Fen Bilimleri Enstitüsü, Ankara, Türkiye
  • Wessels K.J., Prince S.D., Zambatis N., MacFadyen S., Frost P.E., Van Zyl D., 2006. Relationship between herbaceous biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa. International Journal of Remote Sensing, 27: 951-97

Mera Vejetasyonu Durumunun Zaman Serisi NDVI Verileri ile Belirlenmesi

Year 2014, Volume: 23 Issue: 1, 14 - 22, 23.07.2014
https://doi.org/10.21566/tbmaed.41458

Abstract

Geniş alanları kapsayan meraların daha etkin ve ekonomik yönetimi için yeni yöntemlerin geliştirilmesine gereksinim duyulmaktadır.Uydu verilerinden elde edilen normalleştirilmiş fark bitki indeksi (NDVI) verisi mera vejetasyonunun zamana bağlı olarak izlenmesine olanak verir. Yükselti vejetasyon gelişimini etkileyen önemli faktörlerden birisi olduğundan meraların vejetasyon durumunu belirlerken rakımın dikkate alınması gereklidir. Bu amaçla; çalışma alanındaki benzer yükseltiye sahip mera alanlarını temsil eden 10 yıllık (2000-2009) ortalama NDVI verisinden şartlı kural yöntemiyle yükseltiye göre normalleştirilmiş EN-NDVI verisi üretilmiştir. Daha sonra, EN-NDVI verisine kontrollü sınıflandırma yöntemi uygulanarak çalışma alanına ait dört farklı mera durum sınıfı elde edilmiştir. Bu sınıflar; “çok iyi”, “iyi”, “orta” ve “zayıf” olarak adlandırılmıştır. Sonuçlar, her bir mera durumu için kaplama alanının; “çok iyi” %10,02, “iyi” % 20,55, “orta” % 31,83 ve “zayıf” %37,60 şeklinde olduğunu göstermiştir. Yapılan değerlendirmede genel doğruluk  %52,5 ve  Kappa istatistiği 0,30 olarak bulunmuştur.

References

  • Alesheikh A.A., Fard FSN., 2007. Design and implementation of a knowledge based system to improve maximum likelihood classification accuracy. Canadian Journal of Remote Sensing, 33: 459-467
  • Avağ A., Simsek U., Uzun M., 2012. Database activities of national grassland management project. Tarım Bilimleri Dergisi. 5: 102-106
  • Congalton R.E.G., 1991. A review of assessing the accuracy of classification of remotely sensed data. Remote Sensing of Environment, 37: 35-36
  • Çomaklı B., Fayetörtbay D., Daşcı M., 2012. Changing of botanical composition and canopy Coverage Ratio in Rangelands at Different Altitudes. Journal of Agriculture Faculty of Atatürk University., 43: 17-21
  • Dyksterhuis E.J., 1949. Condition and management of range land based on quantitative ecology. Journal of Range Management, 2: 104-115
  • Dymond J.R., Stephens P.R., Newsome P.F., Wilde R.H., 1992. Percentage vegetation cover of a degrading rangeland from SPOT. International Journal of Remote Sensing, 13: 1999–2007
  • ESRI 1998. ESRI Shapefile Technical Description. An ESRI White Paper—July 1998
  • Fırıncıoglu H.K., 2004. An assessment of the pasture and forage production of Turkey. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, 13: 1-28
  • Frost W.E., and Smith E.L., 1991. Biomass productivity and range condition on range sites in southern Arizona. J. Range Manage. 44:64-67
  • Friedl M.H., 1991. Range condition assessment and the concept of thresholds: A viewpoint. Journal of Range Management, 44: 422-426
  • Friedl M.A., Michaelsenn J., Dawis F.W., Walker H. and Schimel D.S., 1994. Estimating grassland biomass and leaf area index using ground and satellite data. International Journal of Remote Sensing, 15: 1401-1420
  • Foody G.M., 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80: 185-201
  • Geerken R., Zaitchik B., Evans J.P., 2005. Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity. International Journal of Remote Sensing. Vol. 26, No. 24, 5535–5554
  • Gitelson A., 2004. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology 161: 165-173
  • Holben B.N., 1986. Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing, 7: 1417-1434
  • Javzandulam T., Tateishi T., Sanjaa T., 2005. Analysis of vegetation indices for monitoring vegetation degradation in semi-arid and arid areas of Mongolia. International Journal of Environmental Studies, 62: 215–225
  • Jianlong L., Tiangang L., Quangong C., 1998. Estimating grassland yields using remote sensing and GIS Technologies in China. New Zealand Journal of Agricultural Research, 41: 31-38
  • Kennedy P., 1989. Monitoring the vegetation of Tunisian grazing lands using the normalized difference vegetation index. Ambio, 18: 119-123
  • Koç A., Çakal Ş., 2004. Comparison of Some Rangeland Canopy Coverage Methods. In: Proceedings of International Soil Congress Natural Resource Management for Sustainable Development. 7-10 June, Erzurum, Türkiye, pp.41-45
  • Kogan F., Stark R., Gitelson A., Jargalsaikhan L., Dugrajav C., Tsooj S., 2004. Derivation of pasture biomass in Mongolia from AVHRR-based vegetation health indices. International Journal of Remote Sensing, 25: 2889-2896
  • Laycock W.A, 1991. Stable states and thresholds of range condition of North American rangelands: A viewpoint. Journal of Range Management, 44:427-433
  • Manandhar R., Inakwu O.A., Ancev T., 2009. Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement. Remote Sensing of Environment 1: 330-344
  • Reeves M.C., Winslow J.C., Running S.W., 2001. Mapping Weekly Rangeland Vegetation Productivity Using MODIS Algorithms. Journal of Range Management, 54: 90-105
  • Mermer A., Unal E., Aydogdu M., Urla O., Yıldız H., Torunlar H., Avağ A., Tugaç M.G., Ozaydın K.A., Dedeoglu F., Aydogmus O., 2012. Determining Rangeland Areas by Satellite Images. Tarım Bilimleri Dergisi, 5: 107-110
  • Solorio T., Fuentes O., 2002. Improving Classification Accuracy of Large Test Sets Using the Ordered Classification Algorithm. In: Proceeding of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence. pp:70-79
  • Todd S.W., Hoffer R.M., Milchunas D.G., 1998. Biomass estimation on grazed and ungrazed rangelands using spectral indices. International Journal of Remote Sensing, 19: 427- 438
  • USDA 1997. National Range and Pasture Handbook, Grazing Lands Technology Institute, Natural Resource Conservation Service, USDA, Washington, D.C
  • Ünal E., 2011. Işık Kullanım Etkinliği (LUE) Modeli ile Çankırı İlindeki Meralarda Biyokütle Tahmini. Doktora Tezi. Ankara Üniversitesi. Fen Bilimleri Enstitüsü, Ankara, Türkiye
  • Wessels K.J., Prince S.D., Zambatis N., MacFadyen S., Frost P.E., Van Zyl D., 2006. Relationship between herbaceous biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa. International Journal of Remote Sensing, 27: 951-97
There are 29 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Ediz Ünal

Ali Mermer

Hakan Yıldız

Publication Date July 23, 2014
Published in Issue Year 2014 Volume: 23 Issue: 1

Cite

APA Ünal, E., Mermer, A., & Yıldız, H. (2014). Assessment of Rangeland Vegetation Condition from Time Series NDVI Data. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, 23(1), 14-22. https://doi.org/10.21566/tbmaed.41458
AMA Ünal E, Mermer A, Yıldız H. Assessment of Rangeland Vegetation Condition from Time Series NDVI Data. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi. July 2014;23(1):14-22. doi:10.21566/tbmaed.41458
Chicago Ünal, Ediz, Ali Mermer, and Hakan Yıldız. “Assessment of Rangeland Vegetation Condition from Time Series NDVI Data”. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi 23, no. 1 (July 2014): 14-22. https://doi.org/10.21566/tbmaed.41458.
EndNote Ünal E, Mermer A, Yıldız H (July 1, 2014) Assessment of Rangeland Vegetation Condition from Time Series NDVI Data. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi 23 1 14–22.
IEEE E. Ünal, A. Mermer, and H. Yıldız, “Assessment of Rangeland Vegetation Condition from Time Series NDVI Data”, Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, vol. 23, no. 1, pp. 14–22, 2014, doi: 10.21566/tbmaed.41458.
ISNAD Ünal, Ediz et al. “Assessment of Rangeland Vegetation Condition from Time Series NDVI Data”. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi 23/1 (July 2014), 14-22. https://doi.org/10.21566/tbmaed.41458.
JAMA Ünal E, Mermer A, Yıldız H. Assessment of Rangeland Vegetation Condition from Time Series NDVI Data. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi. 2014;23:14–22.
MLA Ünal, Ediz et al. “Assessment of Rangeland Vegetation Condition from Time Series NDVI Data”. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, vol. 23, no. 1, 2014, pp. 14-22, doi:10.21566/tbmaed.41458.
Vancouver Ünal E, Mermer A, Yıldız H. Assessment of Rangeland Vegetation Condition from Time Series NDVI Data. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi. 2014;23(1):14-22.