Probability distribution of groundcover for runoff prediction in rangeland in the Burnett–Mary Region, Queensland
Jagriti Tiwari A , Bofu Yu A D , Bantigegne Fentie B and Robin Ellis C
+ Author Affiliations
- Author Affiliations
A School of Engineering and Built Environment, Griffith University, Kessels Road, Nathan, Qld 4111, Australia.
B Department of Environment and Science, Ecoscience Precinct, 41 Boggo Road, Dutton Park, Qld 4102, Australia.
C Department of Environment and Science, Bundaberg, Qld 4670, Australia.
D Corresponding author. Email: b.yu@griffith.edu.au
The Rangeland Journal 42(2) 97-112 https://doi.org/10.1071/RJ19082
Submitted: 18 November 2019 Accepted: 13 May 2020 Published: 6 June 2020
Abstract
Considering the degree of spatial and temporal variation of groundcover in grazing land, it is desirable to use a simple and robust model to represent the spatial variation in cover in order to quantify its effect on runoff and soil loss. The purpose of the study was to test whether a two-parameter beta (β) distribution could be used to characterise cover variation in space at the sub-catchment scale. Twenty sub-catchments (area range 35.8–231 km2) in the Burnett–Mary region, Queensland, were randomly selected. Thirty raster layers of groundcover at 30-m resolution were prepared for these 20 sub-catchments with the average cover for the 30 layers ranging from 24% to 91%. Three methods were used to test the appropriateness of the β distribution for characterising the cover variation in space: (i) visual goodness-of-fit assessment and Kolmogorov–Smirnov (K-S) test; (ii) the fractional area with cover ≤53%; and (iii) estimated runoff amount for a given rainfall amount for the area with cover ≤53%. The K-S test on 30 × 100 samples of groundcover showed that the hypothesis of β distribution for groundcover could not be rejected at P = 0.05 for 97.5% of the cases. A comparison of the observed and β distributions in terms of the fractional area with cover ≤53% showed that the discrepancy was ≤8% for the 30 layers considered. A comparison in terms of the estimated runoff showed that results using the observed cover distribution and the β distribution were highly correlated (R2 range 0.91–0.98; Nash–Sutcliffe efficiency measure range 0.88–0.99). The mean absolute error of estimated runoff ranged from 0.98 to 8.10 mm and the error relative to the mean was 4–16%. The results indicated that the two-parameter β distribution can be adequately used to characterise the spatial variation of cover and to evaluate the effect of cover on runoff for these predominantly grazing catchments.
Additional keywords: beta distribution, empirical distribution, ground cover.
References
Australian and Queensland Governments (2016). Ground cover methods. Great Barrier Reef Report Card 2016. Reef Water Quality Protection Plan. Queensland Government, Brisbane, Qld. Available at: https://www.reefplan.qld.gov.au/__data/assets/pdf_file/0017/46160/report-card-2016-ground-cover-methods.pdf (accessed 27 August 2019)Bartley, R., Roth, C. H., Ludwig, J., McJannet, D., Liedloff, A., Corfield, J., Hawdon, A., and Abbott, B. (2006). Runoff and erosion from Australia’s tropical semi‐arid rangelands: Influence of ground cover for differing space and time scales. Hydrological Processes: An International Journal 20, 3317–3333.
| Runoff and erosion from Australia’s tropical semi‐arid rangelands: Influence of ground cover for differing space and time scales.Crossref | GoogleScholarGoogle Scholar |
Bartley, R., Corfield, J. P., Hawdon, A. A., Kinsey-Henderson, A. E., Abbott, B. N., Wilkinson, S. N., and Keen, R. J. (2014). Can changes to pasture management reduce runoff and sediment loss to the Great Barrier Reef? The results of a 10-year study in the Burdekin catchment, Australia. The Rangeland Journal 36, 67–84.
| Can changes to pasture management reduce runoff and sediment loss to the Great Barrier Reef? The results of a 10-year study in the Burdekin catchment, Australia.Crossref | GoogleScholarGoogle Scholar |
Bosch, J. M., and Hewlett, J. D. (1982). A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration. Journal of Hydrology 55, 3–23.
| A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration.Crossref | GoogleScholarGoogle Scholar |
Burnash, R. J. C., Ferral, R. L., and McGuire, R. A. (1973). A generalized streamflow simulation system: conceptual modeling for digital computers. Technical Report. Joint Federal and State River Forecast Center, US National Weather Service and California Department of Water Resources, Sacramento, CA, USA.
Busby, F. E., and Gifford, G. F. (1981). Effects of livestock grazing on infiltration and erosion rates measured on chained and unchained pinyon-juniper sites in south eastern Utah. Journal of Range Management 34, 400–405.
| Effects of livestock grazing on infiltration and erosion rates measured on chained and unchained pinyon-juniper sites in south eastern Utah.Crossref | GoogleScholarGoogle Scholar |
Chen, J., Shiyomi, M., Yamamura, Y., and Hori, Y. (2006). Distribution model and spatial variation of cover in grassland vegetation. Grassland Science 52, 167–173.
| Distribution model and spatial variation of cover in grassland vegetation.Crossref | GoogleScholarGoogle Scholar |
Chen, J., Shiyomi, M., Bonham, C. D., Yasuda, T., Hori, Y., and Yamamura, Y. (2008a). Plant cover estimation based on the Beta distribution in grassland vegetation. Ecological Research 23, 813–819.
| Plant cover estimation based on the Beta distribution in grassland vegetation.Crossref | GoogleScholarGoogle Scholar |
Chen, J., Shiyomi, M., Hori, Y., and Yamamura, Y. (2008b). Frequency distribution models for spatial patterns of vegetation abundance. Ecological Modelling 211, 403–410.
| Frequency distribution models for spatial patterns of vegetation abundance.Crossref | GoogleScholarGoogle Scholar |
Costa, M. H., Botta, A., and Cardille, J. A. (2003). Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia. Journal of Hydrology 283, 206–217.
| Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia.Crossref | GoogleScholarGoogle Scholar |
Damgaard, C. (2009). On the distribution of plant abundance data. Ecological Informatics 4, 76–82.
| On the distribution of plant abundance data.Crossref | GoogleScholarGoogle Scholar |
Damgaard, C. (2013). Hierarchical and spatially aggregated plant cover data. Ecological Informatics 18, 35–39.
| Hierarchical and spatially aggregated plant cover data.Crossref | GoogleScholarGoogle Scholar |
Damgaard, C. (2014). Estimating mean plant cover from different types of cover data: a coherent statistical framework. Ecosphere 5, art20.
| Estimating mean plant cover from different types of cover data: a coherent statistical framework.Crossref | GoogleScholarGoogle Scholar |
Damgaard, C. (2019). Is the degree of spatial aggregation of Calluna vulgaris regulated by nitrogen deposition or precipitation? Acta Oecologica 97, 1–5.
| Is the degree of spatial aggregation of Calluna vulgaris regulated by nitrogen deposition or precipitation?Crossref | GoogleScholarGoogle Scholar |
Damgaard, C. F., and Irvine, K. M. (2019). Using the beta distribution to analyse plant cover data. Journal of Ecology 107, 2747–2759.
| Using the beta distribution to analyse plant cover data.Crossref | GoogleScholarGoogle Scholar |
DSITIA (2012a). Land use summary 1999–2009 for the Burdekin NRM region. Queensland Department of Science, Information Technology, Innovation and the Arts, Brisbane, Qld.
DSITIA (2012b). Land use summary 1999–2009 for the Burnett Mary NRM region. Queensland Department of Science, Information Technology, Innovation and the Arts, Brisbane, Qld.
Elzinga, C. L., and Salzer, D. W. (1998). Measuring and monitoring plant populations. US Department of the Interior, Bureau of Land Management. Available at: https://books.google.co.in/books?hl=en&lr=&id=nnNsgHm--zYC&oi=fnd&pg=PP17&dq=Elzinga,+C.+L.,+and+Salzer,+D.+W.+(1998).+Measuring+and+monitoring+plant+populations.+US+Department+of+the+Interior,+Bureau+of+Land+Management.+1730-1731.&ots=un-Svl0XFy&sig=pgpMtfmy5MUth3Lq-bLtZXcflSI&redir_esc=y#v=onepage&q&f=false
Eshghizadeh, M., Talebi, A., and Dastorani, M. (2018). Thresholds of land cover to control runoff and soil loss. Hydrological Sciences Journal 63, 1424–1434.
| Thresholds of land cover to control runoff and soil loss.Crossref | GoogleScholarGoogle Scholar |
Falls, L. W. (1974). The beta distribution: a statistical model for world cloud cover. Journal of Geophysical Research 79, 1261–1264.
| The beta distribution: a statistical model for world cloud cover.Crossref | GoogleScholarGoogle Scholar |
Fentie, B., Ellis, R., Waters, D., and Carroll, C. (2014). Modelling reductions of pollutant loads due to improved management practices in the Great Barrier Reef catchments—Burnett Mary NRM region. Technical Report, Vol. 7. Queensland Department of Natural Resources and Mines, Brisbane, Qld.
Fraser, G. W., and Stone, G. S. (2016). The effect of soil and pasture attributes on rangeland infiltration rates in northern Australia. The Rangeland Journal 38, 245–259.
| The effect of soil and pasture attributes on rangeland infiltration rates in northern Australia.Crossref | GoogleScholarGoogle Scholar |
Fuhlendorf, S. D., Fynn, R. W., McGranahan, D. A., and Twidwell, D. (2017). Heterogeneity as the basis for rangeland management. In ‘Rangeland Systems’. pp. 169–196. (Springer: Cham, Switzerland.)
Furno, M., and Vistocco, D. (2018). ‘Quantile Regression: Theory and Applications. Vol. 2.’ (Wiley: Hoboken, NJ, USA.)
Great Barrier Reef Marine Park Authority (2012). ‘Informing the Outlook for Great Barrier Reef Coastal Ecosystems.’ (Great Barrier Reef Marine Park Authority: Townsville, Qld.)
Greene, R. S. B., Kinnell, P. I. A., and Wood, J. T. (1994). Role of plant cover and stock trampling on runoff and soil-erosion from semi-arid wooded rangelands. Australian Journal of Soil Research 32, 953–973.
| Role of plant cover and stock trampling on runoff and soil-erosion from semi-arid wooded rangelands.Crossref | GoogleScholarGoogle Scholar |
Hahn, Gerald J., and Shapiro, S. (1994). ‘Statistical Models in Engineering.’ (Wiley: Hoboken, NJ, USA.)
Irvine, K. M., Rodhouse, T. J., and Keren, I. N. (2016). Extending ordinal regression with a latent zero-augmented Beta distribution. Journal of Agricultural Biological & Environmental Statistics 21, 619–640.
| Extending ordinal regression with a latent zero-augmented Beta distribution.Crossref | GoogleScholarGoogle Scholar |
Jarihani, B., Sidle, R., Bartley, R., Roth, C., and Wilkinson, S. (2017). Characterisation of hydrological response to rainfall at multi spatio-temporal scales in savannas of semi-arid Australia. Water 9, 540.
| Characterisation of hydrological response to rainfall at multi spatio-temporal scales in savannas of semi-arid Australia.Crossref | GoogleScholarGoogle Scholar |
Johnson, N. L., Kotz, S., and Balakrishnan, N. (1995). Beta distributions. In ‘Continuous Univariate Distributions. Vol. 2’. Ch. 21. (Wiley: Hoboken, NJ, USA.)
Ko, D. W., Kim, D., Narantsetseg, A., and Kang, S. (2017). Comparison of field-and satellite-based vegetation cover estimation methods. Journal of Ecology and Environment 41, 5.
| Comparison of field-and satellite-based vegetation cover estimation methods.Crossref | GoogleScholarGoogle Scholar |
Langat, P. K., Kumar, L., and Koech, R. (2019). Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow. Water 11, 734.
| Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow.Crossref | GoogleScholarGoogle Scholar |
Lin, M., Lucas, H. C., and Shmueli, G. (2013). Research commentary—too big to fail: large samples and the p-value problem. Information Systems Research 24, 906–917.
| Research commentary—too big to fail: large samples and the p-value problem.Crossref | GoogleScholarGoogle Scholar |
Lintern, A., Webb, J. A., Ryu, D., Liu, S., Bende‐Michl, U., Waters, D., Leahy, P., Wilson, P., and Western, A. W. (2018). Key factors influencing differences in stream water quality across space. Wiley Interdisciplinary Reviews: Water 5, e1260.
| Key factors influencing differences in stream water quality across space.Crossref | GoogleScholarGoogle Scholar |
Liu, J., Gao, G., Wang, S., Jiao, L., Wu, X., and Fu, B. (2018). The effects of vegetation on runoff and soil loss: multidimensional structure analysis and scale characteristics. Journal of Geographical Sciences 28, 59–78.
| The effects of vegetation on runoff and soil loss: multidimensional structure analysis and scale characteristics.Crossref | GoogleScholarGoogle Scholar |
Loch, R. J. (2000). Effects of vegetation cover on runoff and erosion under simulated rain and overland flow on a rehabilitated site on the Meandu Mine, Tarong, Queensland. Australian Journal of Soil Research 38, 299–312.
| Effects of vegetation cover on runoff and erosion under simulated rain and overland flow on a rehabilitated site on the Meandu Mine, Tarong, Queensland.Crossref | GoogleScholarGoogle Scholar |
Makkonen, L., and Pajari, M. (2014). Defining sample quantiles by the true rank probability. Journal of Probability and Statistics 2014, 326579.
| Defining sample quantiles by the true rank probability.Crossref | GoogleScholarGoogle Scholar |
McIvor, J. G., Williams, J., and Gardener, C. J. (1995). Pasture management influences run-off and soil movement in the semi-arid tropics. Australian Journal of Experimental Agriculture 35, 55–65.
| Pasture management influences run-off and soil movement in the semi-arid tropics.Crossref | GoogleScholarGoogle Scholar |
Melo, I., Tomášik, B., Torrieri, G., Vogel, S., Bleicher, M., Koróny, S., and Gintner, M. (2009). Kolmogorov–Smirnov test and its use for the identification of fireball fragmentation. Physical Review. C 80, 024904.
| Kolmogorov–Smirnov test and its use for the identification of fireball fragmentation.Crossref | GoogleScholarGoogle Scholar |
Mwendera, E. J., and Saleem, M. M. (1997). Infiltration rates, surface runoff, and soil loss as influenced by grazing pressure in the Ethiopian highlands. Soil Use and Management 13, 29–35.
| Infiltration rates, surface runoff, and soil loss as influenced by grazing pressure in the Ethiopian highlands.Crossref | GoogleScholarGoogle Scholar |
Owens, J. S., Silburn, D. M., McKeon, G. M., Carroll, C., and Willcocks, J. (2003). Cover–runoff equations to improve simulation of runoff in pasture growth models. Australian Journal of Soil Research 41, 1467–1488.
| Cover–runoff equations to improve simulation of runoff in pasture growth models.Crossref | GoogleScholarGoogle Scholar |
Peña-Arancibia, J. L., van Dijk, A. I. J. M., Guerschman, J. P., Mulligan, M., Bruijnzeel, L. A., and McVicar, T. R. (2012). Detecting changes in streamflow after partial woodland clearing in two large catchments in the seasonal tropics. Journal of Hydrology 416–417, 60–71.
| Detecting changes in streamflow after partial woodland clearing in two large catchments in the seasonal tropics.Crossref | GoogleScholarGoogle Scholar |
Podwojewski, P., Janeau, J. L., Grellier, S., Valentin, C., Lorentz, S., and Chaplot, V. (2011). Influence of grass soil cover on water runoff and soil detachment under rainfall simulation in a sub‐humid South African degraded rangeland. Earth Surface Processes and Landforms 36, 911–922.
| Influence of grass soil cover on water runoff and soil detachment under rainfall simulation in a sub‐humid South African degraded rangeland.Crossref | GoogleScholarGoogle Scholar |
Prebble, R. E., and Stirk, G. B. (1988). Hydrological effects of land use change on small catchments at the Narayen Research Station, Queensland. Australian Journal of Soil Research 26, 231–242.
| Hydrological effects of land use change on small catchments at the Narayen Research Station, Queensland.Crossref | GoogleScholarGoogle Scholar |
Raschke, M. (2011). Empirical behaviour of tests for the Beta distribution and their application in environmental research. Stochastic Environmental Research and Risk Assessment 25, 79–89.
| Empirical behaviour of tests for the Beta distribution and their application in environmental research.Crossref | GoogleScholarGoogle Scholar |
Sanjari, G., Yu, B., Ghadiri, H., Ciesiolka, C. A., and Rose, C. W. (2009). Effects of time-controlled grazing on runoff and sediment loss. Australian Journal of Soil Research 47, 796–808.
| Effects of time-controlled grazing on runoff and sediment loss.Crossref | GoogleScholarGoogle Scholar |
Scanlan, J. C., Pressland, A. J., and Myles, D. J. (1996). Run-off and soil movement on mid-slopes in north-east Queensland [Australia] grazed woodlands. The Rangeland Journal 18, 33–46.
| Run-off and soil movement on mid-slopes in north-east Queensland [Australia] grazed woodlands.Crossref | GoogleScholarGoogle Scholar |
Scarth, P., Byrne, M., Danaher, T., Henry, B., Hassett, R., Carter, J., and Timmers, P. (2006). State of the paddock: monitoring condition and trend in groundcover across Queensland. In ‘Proceedings of the 13th Australasian Remote Sensing Conference’. 21–24 November 2006, Canberra. (Spatial Science Institute: Canberra, ACT.) https://figshare.com/articles/State_of_the_paddock_monitoring_condition_and_trend_in_ground_cover_cross_Queensland_/94248
Scarth, P., Röder, A., Schmidt, M., and Denham, R. (2010). Tracking grazing pressure and climate interaction—the role of Landsat fractional cover in time series analysis. In ‘Proceedings of the 15th Australasian Remote Sensing and Photogrammetry Conference’. Alice Springs, NT. pp. 13–17. (Remote Sensing and Photogrammetry Commission of the Spatial Sciences Institute: Canberra, ACT.)
SCS (1985). Hydrology. In ‘SCS National Engineering Handbook’. Section 4. (Soil Conservation Service, USDA: Washington, DC, USA.)
Seefeldt, S. S., and Booth, D. T. (2006). Measuring plant cover in sagebrush steppe rangelands: a comparison of methods. Environmental Management 37, 703–711.
| Measuring plant cover in sagebrush steppe rangelands: a comparison of methods.Crossref | GoogleScholarGoogle Scholar | 16485162PubMed |
Sharma, D., and Chakrabarty, T. K. (2017). Some general results on quantile functions for the generalized beta family. Statistics, Optimization and Information Computing 5, 360–377.
| Some general results on quantile functions for the generalized beta family.Crossref | GoogleScholarGoogle Scholar |
Shiyomi, M. (2003). A new vegetation survey method. 1. Using beta-binomial distribution. Chkusan-no-kenkyu 57, 171–175.
Shiyomi, M., Takahashi, S., and Yoshimura, J. (2000). A measure for spatial heterogeneity of a grassland vegetation based on the beta‐binomial distribution. Journal of Vegetation Science 11, 627–632.
| A measure for spatial heterogeneity of a grassland vegetation based on the beta‐binomial distribution.Crossref | GoogleScholarGoogle Scholar |
Silburn, D. M., Carroll, C., Ciesiolka, C. A., DeVoil, R. C., and Burger, P. (2011). Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. I. Influences of cover, slope, and soil. Soil Research 49, 105–117.
| Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. I. Influences of cover, slope, and soil.Crossref | GoogleScholarGoogle Scholar |
Siriwardena, L., Finlayson, B. L., and McMahon, T. A. (2006). The impact of land use change on catchment hydrology in large catchments: the Comet River, Central Queensland, Australia. Journal of Hydrology 326, 199–214.
| The impact of land use change on catchment hydrology in large catchments: the Comet River, Central Queensland, Australia.Crossref | GoogleScholarGoogle Scholar |
Sulaiman, M. Y., Oo, W. H., Wahab, M. A., and Zakaria, A. (1998). Application of probability models to Malaysian sunshine data. International Journal of Energy Research 22, 833–842.
| Application of probability models to Malaysian sunshine data.Crossref | GoogleScholarGoogle Scholar |
Thompson, S. E., Harman, C. J., Heine, P., and Katul, G. G. (2010). Vegetation–infiltration relationships across climatic and soil type gradients. Journal of Geophysical Research. Biogeosciences 115, G02023.
| Vegetation–infiltration relationships across climatic and soil type gradients.Crossref | GoogleScholarGoogle Scholar |
Thornton, C. M., Cowie, B. A., Freebairn, D. M., and Playford, C. L. (2007). The Brigalow Catchment Study: II. Clearing brigalow (Acacia harpophylla) for cropping or pasture increases runoff. Australian Journal of Soil Research 45, 496–511.
| The Brigalow Catchment Study: II. Clearing brigalow (Acacia harpophylla) for cropping or pasture increases runoff.Crossref | GoogleScholarGoogle Scholar |
Tindall, D., Scarth, P., Schmidt, M., Muir, J., Trevithick, R., Denhama, R., Pringle, M., and Witte, C (2012). The Queensland Ground Cover Monitoring Program. In ‘International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISPRS Congress’. Melbourne, Australia. Volume: XXXIX-B8, 2012 XXII. Available at: https://www.academia.edu/19430664/THE_QUEENSLAND_GROUND_COVER_MONITORING_PROGRAM?auto=download
Tothill, J. C., McDonald, C. K., Jones, R. M., and Hargreaves, J. N. G. (1992). ‘BOTANAL: A Comprehensive Sampling and Computing Procedure for Estimating Pasture Yield and Composition. Field Sampling.’ (CSIRO Division of Tropical Crops and Pastures: Brisbane, Qld.) Available at: https://www.researchgate.net/publication/303169091_BOTANAL_A_comprehensive_sampling_procedure_for_estimating_pasture_yield_and_composition_I_Field_sampling
Vásquez-Méndez, R., Ventura-Ramos, E., Oleschko, K., Hernández-Sandoval, L., Parrot, J. F., and Nearing, M. A. (2010). Soil erosion and runoff in different vegetation patches from semiarid Central Mexico. Catena 80, 162–169.
| Soil erosion and runoff in different vegetation patches from semiarid Central Mexico.Crossref | GoogleScholarGoogle Scholar |
Wasserstein, R. L., and Lazar, N. A. (2016). The ASA’s statement on p-values: context, process, and purpose. The American Statistician 70, 129–133.
| The ASA’s statement on p-values: context, process, and purpose.Crossref | GoogleScholarGoogle Scholar |
Wei, W., Chen, L., Fu, B., Huang, Z., Wu, D., and Gui, L. (2007). The effect of land uses and rainfall regimes on runoff and soil erosion in the semi-arid loess hilly area, China. Journal of Hydrology 335, 247–258.
| The effect of land uses and rainfall regimes on runoff and soil erosion in the semi-arid loess hilly area, China.Crossref | GoogleScholarGoogle Scholar |
Wilk, M. B., and Gnanadesikan, R. (1968). Probability plotting methods for the analysis for the analysis of data. Biometrika 55, 1–17.
| Probability plotting methods for the analysis for the analysis of data.Crossref | GoogleScholarGoogle Scholar | 5661047PubMed |
Wright, W. J., Irvine, K. M., Warren, J. M., and Barnett, J. K. (2017). Statistical design and analysis for plant cover studies with multiple sources of observation errors. Methods in Ecology and Evolution 8, 1832–1841.
| Statistical design and analysis for plant cover studies with multiple sources of observation errors.Crossref | GoogleScholarGoogle Scholar |
Zeng, X., Wang, D., and Wu, J. (2015). Evaluating the three methods of goodness of fit test for frequency analysis. Journal of Risk Analysis and Crisis Response 5, 178–187.
| Evaluating the three methods of goodness of fit test for frequency analysis.Crossref | GoogleScholarGoogle Scholar |
Zhang, G., Liu, G., Zhang, P., and Yi, L. (2014). Influence of vegetation parameters on runoff and sediment characteristics in patterned Artemisia capillaris plots. Journal of Arid Land 6, 352–360.
| Influence of vegetation parameters on runoff and sediment characteristics in patterned Artemisia capillaris plots.Crossref | GoogleScholarGoogle Scholar |
Zhou, Q., Robson, M., and Pilesjo, P. (1998). On the ground estimation of vegetation cover in Australian rangelands. International Journal of Remote Sensing 19, 1815–1820.
| On the ground estimation of vegetation cover in Australian rangelands.Crossref | GoogleScholarGoogle Scholar |
Zuazo, V. H. D., and Pleguezuelo, C. R. R. (2009). Soil-erosion and runoff prevention by plant covers: a review. In ‘Sustainable Agriculture’. pp. 785–811. (Springer: Dordrecht, The Netherlands.)
