Abstract
Given the diversity of the biophysical and socioeconomic processes involved, the types, extent, and severity of land degradation cannot be encapsulated by a few simple measures (Stocking and Murnaghan 2000). In the assessment of land degradation or changes in land productivity, two complementary approaches may be distinguished:
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Albalawi EK, Kumar L (2013) Using remote sensing technology to detect, model and map desertification: a review. J Food Agric Environ 11:791–797
Anyamba A, Tucker CJ (2012) Historical perspective of AVHRR NDVI and vegetation drought monitoring. Remote Sens Drought: Innovative Monit Approaches 23
Bai ZG, Dent DL, Olsson L, Schaepman ME (2008) Proxy global assessment of land degradation. Soil Use Manag 24(3):223–234
Bennett R, Welham K, Hill RA, Ford AL (2012) The application of vegetation indices for the prospection of archaeological features in grass‐dominated environments. Archaeol Prospect 19(3):209–218
Cook BI, Pau S (2013) A global assessment of long-term greening and browning trends in pasture lands using the GIMMS LAI3g dataset. Remote Sens 5(5):2492–2512
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):6823–6853
Field CB, Randerson JT, Malmström CM (1995) Global net primary production: combining ecology and remote sensing. Remote Sens Environ 51(1):74–88
Gilabert M, González-Piqueras J, Garcıa-Haro F, Meliá J (2002) A generalized soil-adjusted vegetation index. Remote Sens Environ 82(2):303–310
Higginbottom TP, Symeonakis E (2014) Assessing land degradation and desertification using vegetation index data: current frameworks and future directions. Remote Sens 6(10):9552–9575
Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83(1):195–213
Jensen J (2007) Remote sensing of the environment. Pearson Prentice Hall, Upper Saddle River
Jiang Z, Huete AR, Didan K, Miura T (2008) Development of a two-band enhanced vegetation index without a blue band. Remote Sens Environ 112(10):3833–3845
Liang S (2005) Quantitative remote sensing of land surfaces, vol 30. Wiley, New York
Morton DC, Nagol J, Carabajal CC, Rosette J, Palace M, Cook BD, Vermote EF, Harding DJ, North PR (2014) Amazon forests maintain consistent canopy structure and greenness during the dry season. Nature 506(7487):221–224
Pearson RL, Miller LD (1972) Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie. Remote Sens Environ VIII:1355
Prince SD, Goward SN (1995) Global primary production: a remote sensing approach. J Biogeogr 22:815–835
Purkis SJ, Klemas VV (2011) Remote sensing and global environmental change. Wiley, Oxford
Ross J (1981) The radiation regime and architecture of plant stands, vol 3. Springer, Dordrecht
Rouse J Jr, Haas R, Schell J, Deering D (1974) Monitoring vegetation systems in the Great Plains with ERTS. NASA Spec Publ 351:309
Saleska SR, Didan K, Huete AR, Da Rocha HR (2007) Amazon forests green-up during 2005 drought. Science 318(5850):612
Shalaby A, Tateishi R (2007) Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. Appl Geogr 27(1):28–41
Stocking M, Murnaghan N (2000) Land degradation–guidelines for field assessment. Overseas Development Group, University of East Anglia, Norwich, p 121
Strand H, Höft R, Strittholt J, Horning N, Miles L, Fosnight E, Turner W (2007) Sourcebook on remote sensing and biodiversity indicators, vol Technical Series no. 32. Secretariat of the Convention on Biological Diversity, Montreal
Symeonakis E, Drake N (2004) Monitoring desertification and land degradation over sub-Saharan Africa. Int J Remote Sens 25(3):573–592
Townshend JR, Masek JG, Huang C, Vermote EF, Gao F, Channan S, Sexton JO, Feng M, Narasimhan R, Kim D (2012) Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges. Int J Digital Earth 5(5):373–397
Tucker CJ, Garratt MW (1977) Leaf optical system modeled as a stochastic process. Appl Optics 16(3):635–642
Verrelst J, Koetz B, Kneubühler M, Schaepman M (2006) Directional sensitivity analysis of vegetation indices from multi-angular Chris/PROBA data. In: ISPRS Commission VII Mid-term symposium, pp 677–683
Vlek P, Le Q, Tamene L (2010) Assessment of land degradation, its possible causes and threat to food security in Sub-Saharan Africa. In: Lal R, Stewart BA (eds) Food security and soil quality, Advances in soil science. Taylor & Francis, Boca Raton, pp 57–86
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 The Author(s)
About this chapter
Cite this chapter
Yengoh, G.T., Dent, D., Olsson, L., Tengberg, A.E., Tucker, C.J. (2015). The Potential for Assessment of Land Degradation by Remote Sensing. In: Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales. SpringerBriefs in Environmental Science. Springer, Cham. https://doi.org/10.1007/978-3-319-24112-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-24112-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24110-4
Online ISBN: 978-3-319-24112-8
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)