Advertisement

Experts’ Opinions on the Use of NDVI for Land Degradation Assessment

  • Genesis T. Yengoh
  • David Dent
  • Lennart Olsson
  • Anna E. Tengberg
  • Compton J. TuckerIII
Chapter
Part of the SpringerBriefs in Environmental Science book series (BRIEFSENVIRONMENTAL)

Abstract

Methodological issues were raised by Wessels (2009) regarding the GLADA assessment, chiefly the interpretation of RUE outside arid and semiarid regions, growing season differences between the northern and southern hemisphere and their implications for calendar year summations of NPP, and issues of scale in the interpretation of AVHRR NDVI vs. MODIS NPP relationships. He also maintained that the RESTREND technique provided a more dependable alternative. In response, Dent et al. (2009) clarified that RUE was not being used as an indicator of land condition but simply to separate NDVI trends caused by drought in those areas where biomass potential is directly related to rainfall, essentially drylands. Regarding seasonal differences in growing season between the northern and southern hemispheres, there was no difference in the long-term trends when the hydrological year was used for the southern hemisphere. And, finally, the RESTREND approach was also applied to the GLADA data and showed no significant difference with the RUE-adjusted NDVI approach; the choice of the RUE-adjusted NDVI was made on account of its simplicity and amenability to economic evaluation (Dent et al. 2009).

Keywords

Southern Hemisphere Land Degradation Semiarid Region Rainfall Change Annual Biomass Production 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Bai ZG, Dent DL, Olsson L, Schaepman ME (2008) Proxy global assessment of land degradation. Soil Use Manag 24(3):223–234CrossRefGoogle Scholar
  2. Bajocco S, De Angelis A, Perini L, Ferrara A, Salvati L (2012) The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study. Environ Manage 49(5):980–989CrossRefGoogle Scholar
  3. Dardel C, Kergoat L, Hiernaux P, Grippa M, Mougin E, Ciais P, Nguyen C-C (2014) Rain-use-efficiency: what it tells us about the conflicting Sahel greening and Sahelian Paradox. Remote Sens 6(4):3446–3474CrossRefGoogle Scholar
  4. de Jong R, de Bruin S, de Wit A, Schaepman ME, Dent DL (2011a) Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sens Environ 115(2):692–702. doi:http://dx.doi.org/10.1016/j.rse.2010.10.011
  5. de Jong R, de Bruin S, Schaepman M, Dent D (2011b) Quantitative mapping of global land degradation using Earth observations. Int J Remote Sens 32(21):6823–6853CrossRefGoogle Scholar
  6. de Jong R, Verbesselt J, Schaepman ME, De Bruin S (2011c) Detection of breakpoints in global NDVI time series. In: 34th International Symposium on Remote Sensing of Environment (ISRSE), pp 10–15Google Scholar
  7. Dent D, Bai Z, Schaepman M, Olsson L (2009) Letter to the editor. Soil Use Manag 25(1):93–97CrossRefGoogle Scholar
  8. Fensholt R, Rasmussen K (2011) Analysis of trends in the Sahelian ‘rain-use efficiency’ using GIMMS NDVI, RFE and GPCP rainfall data. Remote Sens Environ 115(2):438–451CrossRefGoogle Scholar
  9. Fensholt R, Langanke T, Rasmussen K, Reenberg A, Prince SD, Tucker C, Scholes RJ, Le QB, Bondeau A, Eastman R, Epstein H, Gaughan AE, Hellden U, Mbow C, Olsson L, Paruelo J, Schweitzer C, Seaquist J, Wessels K (2012) Greenness in semi-arid areas across the globe 1981–2007—an Earth Observing Satellite based analysis of trends and drivers. Remote Sens Environ 121:144–158. doi: 10.1016/j.rse.2012.01.017 CrossRefGoogle Scholar
  10. Fensholt R, Rasmussen K, Kaspersen P, Huber S, Horion S, Swinnen E (2013) Assessing land degradation/recovery in the African Sahel from long-term earth observation based primary productivity and precipitation relationships. Remote Sens 5(2):664–686CrossRefGoogle Scholar
  11. Le Houerou HN (1984) Rain use efficiency: a unifying concept in arid-land ecology. J Arid Environ 7(3):213–247Google Scholar
  12. Le QB, Nkonya E, Mirzabaev A (2014) Biomass productivity-based mapping of global land degradation hotspots. ZEF-Discussion Papers on Development Policy (193)Google Scholar
  13. Nkonya E, Gerber N, Baumgartner P, Von Braun J, De Pinto A, Graw V, Kato E, Kloos J, Walter T (2011) The economics of desertification, land degradation, and drought: toward an integrated global assessment. ZEF Discussion Papers on Development PolicyGoogle Scholar
  14. Verón SR, Oesterheld M, Paruelo JM (2005) Production as a function of resource availability: slopes and efficiencies are different. J Veg Sci 16(3):351–354CrossRefGoogle Scholar
  15. Wessels K (2009) Letter to the editor: comments on ‘Proxy global assessment of land degradation’ by Bai et al. (2008). Soil Use Manag 25:91–92CrossRefGoogle Scholar

Copyright information

© The Author(s) 2015

Authors and Affiliations

  • Genesis T. Yengoh
    • 1
  • David Dent
    • 2
  • Lennart Olsson
    • 1
  • Anna E. Tengberg
    • 1
  • Compton J. TuckerIII
    • 3
  1. 1.Lund University Centre for Sustainability Studies - LUCSUSLundSweden
  2. 2.Chestnut Tree Farm, Forncett EndNorthfolkUK
  3. 3.Department of Hydrospheric and Biospheric SciencesNASA Goddard Space Flight CenterGreenbeltUSA

Personalised recommendations