Estimating above ground biomass as an indicator of carbon storage in vegetated wetlands of the grassland biome of South Africa

International Journal of Applied Earth Observation and Geoinformation

Volumn 78, Issue , 2019, Pages 118-129

  Naidoo, Laven ^a   van Deventer, Heidi ^a,b   Ramoelo, Abel ^c,e   Mathieu, Renaud ^a,d   Nondlazi, Basanda ^a   Gangat, Ridhwannah ^b  

^a DSI CSIR Nanotechnology Innovation Centre   (South Africa)

^b UNIVERSITY OF THE WITWATERSRAND   (South Africa)

^c UNIVERSITY OF LIMPOPO   (South Africa)

^d UNIVERSITY OF PRETORIA   (South Africa)

^e SOUTH AFRICAN NATIONAL PARKS   (South Africa)

Author keywords

AGB; Carbon sequestration; Earth observation; Remote sensing; Sentinel sensors; Vegetation biomass; Wetland types

Indexed keywords

ABOVEGROUND BIOMASS; BIOMASS; BIOME; CARBON SEQUESTRATION; ESTIMATION METHOD; GRASSLAND; REMOTE SENSING; SENSOR; VEGETATION DYNAMICS; WETLAND;

SOUTH AFRICA;

EID: 85062896328     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2019.01.021     Document Type: Article

References (57)

1. Adam, E., Mutanga, O., Rugege, D., Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetl. Ecol. Manag. 18 (2010), 281–296.
2. Adam, E., Mutanga, O., Abdel-Rahman, E.M., Ismail, R., Estimating standing biomass in papyrus (Cyperus papyrus L.) swamp: exploratory of in situ hyperspectral indices and random forest regression. Int. J. Remote Sens. 35:2 (2014), 693–714.
3. Amthor, J.S., Dale, V.H., Edwards, N.T., Garten, C.T., Gunderson, C.A., Hanson, P.J., Muston, M.A., King, A.W., Luxmoore, R.J., McLaughlin, S.B., Marland, G., Muhlolland, P.J., Norby, R.J., O'Neill, R.V., Post, W.M., Shriner, D.S., Rodd, D.E., Tchaplinski, T.K., Rurner, R.S., Tuskan, G.A., Wullschleger, S.D., Terrestrial Ecosystem Responses to Global Change: a Research Strategy, Report, September 1, 1998., 1998, University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department, Tennessee (digital.library.unt.edu/ark:/67531/metadc706583/: Accessed 02, August 2018).
4. Amundson, R., The carbon budget in soils. Annual Review of Earth and Planetary Science. 29 (2001), 535–562.
5. Burgoyne, B.M., Bredenkamp, G.J., van Rooyen, N., Wetland vegetation in the north-eastern Sandy Highveld, Mpumalanga, South Africa. Bothalia. 30:2 (2000), 187–200.
6. Darvishzadeh, R., Skidmore, A.K., Schlerf, M., Atzberger, C., Inversion of a radiative transfer model for estimating vegetation LAI and chorophyll in a heterogeneous grassland. Remote Sens. Environ. 112:5 (2008), 2592–2604.
7. Fan, L., Gao, Y., Brück, H., Bernhofer, C.H., Investigating the relationship between NDVI and LAI in semi-arid grassland in Inner Mongolia using in-situ measurements. Theor. Appl. Climatol. 95 (2009), 151–156.
8. Fourie, L., Rouget, M., Lötter, M., Landscape connectivity of the grassland biome in Mpumalanga, South Africa. Austral Ecol. 40 (2015), 67–76.
9. Gallant, A.L., The challenges of remote monitoring of wetlands. Remote Sens. (Basel) 7 (2015), 10938–10950.
10. GeoTerraImage (GTI) Pty Ltd, The 2013-2014 South African National Land-cover Dataset, 2013-14 SA Landcover Report-contents Vs 05 DEA Open Access. Data User Report and Metadata. Available: http://www.geoterraimage.com/downloads.php Accessed 17, September 2018, 2015.
11. Goudie and Wells, The nature, distribution and formation of pans in arid zone. Earth. Rev. 38:1 (1995), 1–69.
12. Grundling, P.L., Linström, A., Grobler, R., Engelbrecht, J., The tevredenpan peatland complex of the Mpumalanga Lakes District. Couwenberg, J., Joosten, H., (eds.) International Mire Conservation Group Newsletter Issue 2007/3, 2003, International Mire Conservation Group.
13. Huang, C., Ye, X., Spatial modelling of urban vegetation and land surface temperature: a case study of Beijing. Sustainability 7:7 (2015), 9478–9504.
14. Huang, C., Ye, Z., Deng, C., Zhang, Z., Wan, Z., Mapping Above-Ground Biomass by Integrating optical and SAR imagery: a case study of Xixi National Wetland Park, China. Remote Sens. 8 (2016), 1–19.
15. Intergovernmental Panel on Climate Change (IPCC), Working Group I Contribution to the IPCC Fifth Assessment Report Climate Change 2013: the Physical Science Basis. Summary for Policy Makers., 2013, 1–36.
16. Ismail, R., Mutanga, O., Kumar, L., Modelling the potential distribution of pine forests susceptible to Sirex Noctilo infestations in Mpumalanga, South Africa. Trans. GIS 14:5 (2010), 709–726.
17. Janks, M.R., Montane Wetlands of the South African Great Escarpment: Plant Communities and Environmental Drivers. MSc thesis, 2014, South Africa Rhodes University, Grahamstown.
18. Jones, M.B., Donnelly, A., Carbon sequestration in temperate grassland ecosystems and the influence of management, climate and elevated CO2. New Phytol. 164:3 (2004), 423–439.
19. Kayranli, B., Scholz, M., Mustafa, Z., Hedmark, A., Carbon Storage and fluxes within freshwater wetlands : a critical review. Wetlands 30 (2010), 111–124.
20. Kirk, J.T.O., Light and Photosynthesis in Aquatic Ecosystems. 2nd edn, 1994, Cambridge University Press.
21. Le Maitre, D.C., Seyler, H., Holland, M., Smith-Adao, L., Nel, J.L., Maherry, A., Witthüser, K., Identification, Delineation and Importance of the Strategic Water Source Areas of South Africa, Lesotho and Swaziland for Surface Water and Groundwater. Final Integrated Report on Project K5/2431., 2018, Water Research Commission, Pretoria.
22. Li, R., Liu, J., Wetland vegetation biomass estimation and mapping from Landsat ETM data: a case study of Poyang Lake. J. Geog. Sci. 12:1 (2002), 35–41.
23. Liao, J., Shen, G., Dong, L., Biomass estimation of wetland vegetation in Poyang Lake area using ENVISAT advanced synthetic aperture radar. J. Appl. Remote Sens. 7 (2013), 1–15.
24. Li, F., Chen, J.Q., Zeng, Y., Wu, B.F., Zhang, X.Q., Renewed estimates of grassland aboveground biomass showing drought impacts. J. Geophy. Res.: Biogeosci. 123:1 (2018), 138–148.
25. Linström, A., Wetland Status Quo Report: Chrissiesmeer Project. Tevrede Pan wetland W55A (Wetlands W55A - 05 to 07)., 2015, SANBI, Pretoria, South Africa.
26. MacKellar, N., New, M., Jack, C., Observed and modelled trends in rainfall and temperature for South Africa: 1960-2010. S. Afr. J. Sci. - Climate trends in South Africa 110:7/8 (2014), 1–13.
27. Masemola, C., Cho, M.A., Ramoelo, A., Comparison of Landsat 8 OLI and Landsat 7 ETM+ for estimating grassland LAI using model inversion and spectral indices: case study of Mpumalanga, South Africa. Int. J. Remote Sens. 37:18 (2016), 4401–4419.
28. Matayaya, G., Wita, M., Nyamadzawo, G., Effects of different disturbance regimes on grass and herbacious plant diversity and biomass in Zimbabwean dambo systems. International Journal of Biodiversity Science, Ecosystem Services and Management 13:1 (2017), 181–190.
29. Mathieu, R., Naidoo, L., Cho, M.A., Leblon, B., Main, R., Wessels, K., Asner, G.P., Buckley, J., Van Aardt, J., Erasmus, B.F.N., Smit, I.P.J., Toward structural assessment of semi-arid African savannahs and woodlands: the potential of multitemporal polarimetric RADARSAT-2 fine beam images. Remote Sens. Environ. 138 (2013), 215–231.
30. Middleton, B.J., Bailey, A.K., Water Resources of South Africa, 2005 Study (WR2005) and Book of Maps. WRC Research Reports No.TT381/08 & TT382/08., 2008.
31. Mitsch, W.J., Gosselink, J.G., Wetlands. 5th ed., 2015, John Wiley & Sons, Hoboken (NJ).
32. Mpumalanga Tourism and Parks Agency (MTPA), Declaration of Chrissiesmeer Protected Environment in Terms of the Matopma; Environmental Management: Protected Areas Act,2003 (Act No 57 of 2003, As Amended). Government Gazzette, 22 January 2014. 2014.
33. Mucina, L., Rutherford, M.C., The Vegetation of South Africa, Lesotho and Swaziland. 2006, South African National Biodiversity Institute (Strelizia), Pretoria.
34. Mueller-Wilm, U., Sentinel 2 MPC – Sen2Cor configuration and user manual. European Space Agency (ESA)(Issue 1), 2017, 1–56 Date: 2018-03-22.
35. Mutanga, O., Adam, E., Cho, M.A., High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm. Int. J. Appl. Earth Obs. Geoinf. 18 (2012), 399–406.
36. Nahlik, A.M., Fennessy, M.S., Carbon storage in US wetlands. Nat. Commun. 7:13835 (2016), 1–9.
37. Naidoo, L., Mathieu, R., Main, R., Kleynhans, W., Wessels, K., Asner, G.P., Leblon, B., The assessment of data mining algorithms for modelling savannah woody cover using multi-frequency (X-, C- and L-band) synthetic aperture radar (SAR) datasets. IEEE International Geoscience and Remote Sensing Symposium, Quebec, Canada, 13-18 July, 2014, 1–4.
38. Ollis, D.J., Ewart-Smith, J.L., Day, J.A., Job, N.M., Macfarlane, D.M., Snaddon, C.D., Sieben, E.J.J., Dini, J.A., Mbona, N., The development of a classification system for inland aquatic ecosystems in South Africa. Water Sa 41:5 (2015), 727–745.
39. Owers, C.J., Rogers, K., Woodroffe, C.D., Spatial variation of above-ground carbon storage in temperate coastal wetlands. Estuar. Coast. Shelf Sci. 210 (2018), 55–67.
40. Parton, W.J., Scurlock, J.M.O., Ojima, D.S., Gilmanov, T.G., Scholes, R.J., Schimel, D.S., Kirchner, T., Menaut, J.-C., Seastedt, T., Garcia Moya, E., Kamnalrut, A., Kinyamario, J.I., Observations and modelling of biomass and soil organic matter dynamics for the Grassland Biome worldwide. Global Biogeochem. Cycles 7:4 (1993), 785–809.
41. Penuelas, J., Gamon, J.A., Griffin, K.L., Field, C.B., Assessing community type, plant biomass, pigment composition, and photosynthetic efficiency of aquatic vegetation from spectral reflectance. Remote Sens. Environ. 46 (1993), 110–118.
42. Poiani, K.A., Johnson, W.C., Kittel, T.G.F., Sensitivity of a prairie wetland to increased temperature and seasonal precipitation changes. J. Am. Water Resour. Assoc. 31:2 (1995), 283–294.
43. Ramoelo, A., Cho, M.A., Mathieu, R., Madonsela, S., van de Kerchove, R., Kaszta, Z., Wolff, E., Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data. Int. J. Appl. Earth Obs. Geoinf. 43 (2015), 43–54.
44. Reid, H., Huq, S., Climate change-biodiversity and livelihood impacts. Tropical Forests and Adaptation to Climate Change, 2005, 57 https://books.google.co.za/books.
45. Republic of South Africa (RSA), National Water Act (NWA), Act 36 of 1998. Government Printers. Pretoria, South Africa, 1998.
46. Schulze, R.E., South African Atlas of Agrohydrology and -climatology. Water Research Commission, Pretoria, South Africa. Report TT82/96., 1997.
47. Sibanda, M., Mutanga, O., Rouget, M., Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments. Isprs J. Photogramm. Remote. Sens. 110 (2015), 55–65.
48. Sibanda, M., Mutanga, O., Rouget, M., Kumar, L., Estimating biomass of native grass grown under complex management treatments using WorldView-3 spectral derivatives. Remote Sens. 9:55 (2017), 1–21.
49. Sieben, E.J.J., Mtshali, H., Janks, M., National Wetland Vegetation Database: Classification and Analysis of Wetland Vegetation Types for Conservation Planning and Monitoring. Water Research Commission (WRC) Report No. 1980/1/14., 2014, WRC, Pretoria, South Africa.
50. Silva, T.S.F., Costa, M.P.F., Melack, J.M., Novo, E.M.L.M., Remote sensing of aquatic vegetation theory and applications. Environ. Monit. Assess. 140 (2008), 131–145.
51. Truus, L., Estimation of above ground biomass of wetland, biomass of wetland. Atazadeh, I., (eds.) Biomass and Remote Sensing of Biomass, 2011, Shanghai: InTech; pp 75–86.
52. Van Deventer, H.; Van Niekerk, L.; Adams, J.; Dinala, M.K.; Gangat, R.; Lamberth, S.J.; Lötter, M.; Mbona, N.; MacKay, F.; Nel, J.L.; Ramjukadh, C-L.; Skowno, A.; Weerts, S.P. submitted. National Wetland Map 5 – improving the spatial extent and representation of inland aquatic and estuarine ecosystems in South Africa.
53. Van Wijk, M.T., Williams, M., Optical instruments for measuring leaf area index in low vegetation: application in artic ecosystems. Ecol. Appl. 15:4 (2005), 1462–1470.
54. Van Wilgen, N.J., Goodall, V., Holness, S., Chown, S.L., McGeoch, M.A., Rising temperatures and changing rainfall patterns in South Africa's national parks. Int. J. Climatol. 36:2 (2016), 706–721.
55. Xie, Y., Sha, Z., Yu, M., Bai, Y., Zhang, L., A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia. China. Ecol. Modell. 220:15 (2009), 1810–1818.
56. Ye, Y., Zhou, C., Sun, Y., Zhou, D., Estimation of wetland aboveground biomass based on SAR image: a case study of honghe national natural reserve in heilongjiang, China. 2010 18th International Conference on Geoinformatics, 2010 (ISBN: 978-1-4244-7303-8).
57. Zhang, C., Denka, S., Cooper, H., Mishra, D.R., Quantification of sawgrass marsh aboveground biomass in the coastal Everglades using object-based ensemble analysis and Landsat data. Remote Sens. Environ. 204 (2018), 366–379.