Multispectral remote sensing of potential groundwater dependent vegetation in the greater Floristic region of the Western Cape, South Africa

References

• Allsopp, N., Slingsby, J. A., & Esler, K. J. (2019). Identifying research questions for the conservation of the Cape Floristic Region. South African Journal of Science, 115(9/10), 1–8. https://doi.org/10.17159/sajs.2019/5889
   Web of Science ®Google Scholar
• Barron, O. V., Emelyanova, I., Van Niel, T. G., Pollock, D., & Hodgson, G. (2014). Mapping groundwater-dependent ecosystems using remote sensing measures of vegetation and moisture dynamics. Hydrological Processes, 28(2), 372–385. https://doi.org/10.1002/hyp.9609
   Web of Science ®Google Scholar
• Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., & Zemp, M. (2014). The concept of essential climate variables in support of climate research, applications, and policy. Bulletin of the American Meteorological Society, 95(9), 1431–1443. https://doi.org/10.1175/BAMS-D-13-00047.1
   Web of Science ®Google Scholar
• Botai, C. M., Botai, J. O., de Wit, J. P., Ncongwane, K. P., & Adeola, A. M. (2017). Drought characteristics over the Western Cape Province, South Africa. Water (Switzerland), 9(11), 876. https://doi.org/10.3390/w9110876
   Google Scholar
• Brodie, R. S., Green, R., & Graham, M. (2002). Mapping groundwater-dependent ecosystems: A case study in the fractured basalt aquifers of the Alstonville Plateau. Balancing the Groundwater Budget.
   Google Scholar
• Chiloane, C., Dube, T., & Shoko, C. (2021). Impacts of groundwater and climate variability on terrestrial groundwater dependent ecosystems: A review of geospatial assessment approaches and challenges and possible future research directions. Geocarto International, 37(23), 1–25. https://doi.org/10.1080/10106049.2021.1948108
   Web of Science ®Google Scholar
• Colvin, C., Le Maitre, D., & Hughes, S. (2003). Assessing terrestrial groundwater dependent ecosystems in South Africa. Water Research Commission.
   Google Scholar
• Colvin, C., Le Maitre, D., Saayman, I., & Hughes, S. (2007). An introduction to aquifer dependent ecosystems in South Africa. Natural Resources and the Environment, Water Research.
   Google Scholar
• Costanza, R., D’arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’neill, R. V., Paruelo, J., Raskin, R. G., Sutton, P., & van den Belt, M. (1997). The value of the world’s ecosystem services and natural capital. Nature, 387(6630), 253–260. https://doi.org/10.1038/387253a0
   Web of Science ®Google Scholar
• Currie, B., Milton, S. J., & Steenkamp, J. C. (2009). Cost–benefit analysis of alien vegetation clearing for water yield and tourism in a mountain catchment in the Western Cape of South Africa. Ecological Economics, 68(10), 2574–2579. https://doi.org/10.1016/j.ecolecon.2009.04.007
   Web of Science ®Google Scholar
• Dawson, T. E., & Ehleringer, J. R. (1991). Streamside trees that do not use stream water. Nature, 350(6316), 335–337.
   Web of Science ®Google Scholar
• Doody, T. M., Barron, O. V., Dowsley, K., Emelyanova, I., Fawcett, J., Overton, I. C., Pritchard, J. L., Van Dijk, A. I. J. M., & Warren, G. (2017). Continental mapping of groundwater dependent ecosystems: A methodological framework to integrate diverse data and expert opinion. Journal of Hydrology: Regional Studies, 10, 61–81. https://doi.org/10.1016/j.ejrh.2017.01.003
   Google Scholar
• Dresel, P. E., Clark, R., Cheng, X., Reid, M., Terry, A., Fawcett, J., & Cochrane, D. (2010). Mapping terrestrial groundwater dependent ecosystems: Method development and example output. Melbourne, Australia: Department of Primary Industries.
   Google Scholar
• Dube, T., Pandit, S., Shoko, C., Ramoelo, A., Mazvimavi, D., & Dalu, T. (2019). Numerical assessments of leaf area index in tropical savanna rangelands, South Africa using Landsat 8 OLI derived metrics and in-situ measurements. Remote Sensing, 11(7), 11. https://doi.org/10.3390/rs11070829
   Web of Science ®Google Scholar
• Dzikiti, S., Schachtschneider, K., Naiken, V., Gush, M., & Le Maitre, D. (2013). Comparison of water-use by alien invasive pine trees growing in riparian and non-riparian zones in the Western Cape Province, South Africa. Forest Ecology and Management, 293, 92–102. https://doi.org/10.1016/j.foreco.2013.01.003
   Web of Science ®Google Scholar
• Eamus, D., Zolfaghar, S., Villalobos-Vega, R., Cleverly, J., & Huete, A. (2015). Groundwater-dependent ecosystems: Recent insights from satellite and field-based studies. Hydrology and Earth System Sciences, 19(10), 4229–4256. https://doi.org/10.5194/hess-19-4229-2015
   Web of Science ®Google Scholar
• Emelyanova, I., Barron, O., & Alaibakhsh, M. (2018). A comparative evaluation of arid inflow-dependent vegetation maps derived from LANDSAT top-of-atmosphere and surface reflectances. International Journal of Remote Sensing, 39(20), 6607–6630. https://doi.org/10.1080/01431161.2018.1463114
   Web of Science ®Google Scholar
• Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185–201. https://doi.org/10.1016/S0034-4257(01)00295-4
   Web of Science ®Google Scholar
• Franklin, J., Serra Diaz, J. M., Syphard, A. D., & Regan, H. M. (2016). Global change and terrestrial plant community dynamics. Proceedings of the National Academy of Sciences, 113(14), 3725–3734. https://doi.org/10.1073/pnas.1519911113
   PubMed Web of Science ®Google Scholar
• Froend, R., & Sommer, B. (2010). Phreatophytic vegetation response to climatic and abstraction-induced groundwater drawdown: Examples of long-term spatial and temporal variability in community response. Ecological Engineering, 36(9), 1191–1200. https://doi.org/10.1016/j.ecoleng.2009.11.029
   Web of Science ®Google Scholar
• Glanville, K., Ryan, T., Tomlinson, M., Muriuki, G., Ronan, M., & Pollett, A. (2016). A Method for catchment scale mapping of groundwater-dependent ecosystems to support natural resource management (Queensland, Australia). Environmental Management, 57(2), 432–449. https://doi.org/10.1007/s00267-015-0612-z
   PubMed Web of Science ®Google Scholar
• Griffiths, P., Nendel, C., & Hostert, P. (2019). Intra-annual reflectance composites from sentinel-2 and Landsat for national-scale crop and land cover mapping. Remote Sensing of Environment, 220, 135–151. https://doi.org/10.1016/j.rse.2018.10.031
   Web of Science ®Google Scholar
• Gxokwe, S., Dube, T., & Mazvimavi, D. (2020). Multispectral remote sensing of wetlands in semi-arid and arid areas: A review on applications, challenges and possible future research directions. Remote Sensing, 12(24), 1–19. https://doi.org/10.3390/rs12244190
   Web of Science ®Google Scholar
• Havril, T., Tóth, Á., Molson, J. W., Galsa, A., & Mádl-Szőnyi, J. (2018). Impacts of predicted climate change on groundwater flow systems: Can wetlands disappear due to recharge reduction? Journal of Hydrology, 563, 1169–1180. https://doi.org/10.1016/j.jhydrol.2017.09.020
   Web of Science ®Google Scholar
• Hoffman, M. T., & Cowling, R. M. (1990). Vegetation change in the semi-arid eastern Karoo over the last 200 years: An expanding Karoo - fact or fiction? S. African Journal of Science, 86(7), 286.
   Web of Science ®Google Scholar
• Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
   Web of Science ®Google Scholar
• Johansen, O. M., Andersen, D. K., Ejrnæs, R., & Pedersen, M. L. (2018). Relations between vegetation and water level in groundwater dependent terrestrial ecosystems (GWDTEs). Limnologica, 68, 130–141. https://doi.org/10.1016/j.limno.2017.01.010
   Web of Science ®Google Scholar
• Jovanovic, N., Bugan, R. D. H., & Israel, S. (2013). Rainfall, soil water content, and groundwater levels at the riverlands nature reserve (South Africa). Dataset Papers in Geosciences, 2013, 1–14. https://doi.org/10.7167/2013/724819
   Google Scholar
• Jovanovic, N. Z., Jarmain, C., de Clercq, W. P., Vermeulen, T., & Fey, M. V. (2011). Total evaporation estimates from a renosterveld and dryland wheat/fallow surface at the Voëlvlei nature reserve (South Africa). Water SA, 37(4), 471–482. https://doi.org/10.4314/wsa.v37i4.5
   Web of Science ®Google Scholar
• Kinoti, I. K. (2018). Integraded hydrological modeling of surface and groundwater interactions in Heuningnes catchment (South Africa), University of Twente.
   Google Scholar
• Krause, S., Heathwaite, A. L., Miller, F., Hulme, P., & Crowe, A. (2007). Groundwater-dependent wetlands in the UK and Ireland: Controls, functioning and assessing the likelihood of damage from human activities. Water Resources Management, 21(12), 2015–2025. https://doi.org/10.1007/s11269-007-9192-x
   Web of Science ®Google Scholar
• Le Maitre, D. C., Scott, D. F., & Colvin, C. (1999). A review of information on interactions between vegetation and groundwater. Water SA, 25(2), 137–152.
   Web of Science ®Google Scholar
• Le Maitre, D. C., Van Wilgen, B. W., Chapman, R. A., & McKelly, D. H. (1996). Invasive plants and water resources in the Western Cape Province, South Africa: Modelling the consequences of a Lack of Management. The Journal of Applied Ecology, 33(1), 161. https://doi.org/10.2307/2405025
   Web of Science ®Google Scholar
• Liao, S., Xue, L., Dong, Z., Zhu, B., Zhang, K., Wei, Q., Fu, F., & Wei, G. (2020). Cumulative ecohydrological response to hydrological processes in arid basins. Ecological Indicators, 111, 106005. https://doi.org/10.1016/j.ecolind.2019.106005
   Web of Science ®Google Scholar
• Loomes, R., Froend, R., & Sommer, B. (2013). Response of wetland vegetation to climate change and groundwater decline on the swan coastal plain, Western Australia: Implications for management. In Ribeiro, L., Stigter, TY., Chambel, A., Condesso de, Melo MT, Monteiro, JP., & Medeiros, A. (Eds.), Groundwater and Ecosystems (pp. 207–219). Leiden, Netherlands: CRC Press.
   Google Scholar
• Lv, J., Wang, X. S., Zhou, Y., Qian, K., Wan, L., Eamus, D., & Tao, Z. (2013). Groundwater-dependent distribution of vegetation in Hailiutu River catchment, a semi-arid region in China. Ecohydrology, 6(1), 142–149. https://doi.org/10.1002/eco.1254
   Web of Science ®Google Scholar
• Mazvimavi, D. (2018). Finding “new” water to address conflicting and competing water demands in the Nuwejaars Catchment, Cape Agulhas. Cape Town.
   Google Scholar
• McDowell, C., & Moll, E. (1992). The influence of agriculture on the decline of West Coast Renosterveld, south-western Cape, South Africa. Journal of environmental management, 35(3), 173–192.
   Web of Science ®Google Scholar
• Mkunyana, Y. P., Mazvimavi, D., Dzikiti, S., & Ntshidi, Z. (2019). A comparative assessment of water use by Acacia longifolia invasions occurring on hillslopes and riparian zones in the Cape Agulhas region of South Africa. Physics and Chemistry of the Earth, Parts A/B/C, 112, 255–264. https://doi.org/10.1016/j.pce.2018.10.002
   Web of Science ®Google Scholar
• Mokoena, P. L. (2019). Novel approach of using hydrogeochemistry, hydrogeologic and hydrostratigraphic techniques in evaluating coastal aquifers in heuningnes catchment. University of th Western Cape.
   Google Scholar
• Móricz, N. (2010). Water balance study of a groundwater-dependent oak forest. Acta Silv. Lignaria Hungarica. Acta Silv. Lignaria Hungarica.
   Google Scholar
• Morris, T. L., Barger, N. N., & Cramer, M. D. (2020). Ecophysiological traits of invasive alien Acacia cyclops compared to co-occuring native species in Strandveld vegetation of the Cape Floristic Region. Austral Ecology, 45(1), 48–59. https://doi.org/10.1111/aec.12827
   Web of Science ®Google Scholar
• Mtengwana, B., Dube, T., Mkunyana, Y. P., & Mazvimavi, D. (2020). Use of multispectral satellite datasets to improve ecological understanding of the distribution of invasive alien plants in a water-limited catchment, South Africa. African Journal of Ecology, 58(4), 709–718. https://doi.org/10.1111/aje.12751
   Web of Science ®Google Scholar
• Mtengwana, B., Dube, T., Mudereri, B. T., & Shoko, C. (2021). Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa. GIScience & Remote Sensing, 58(4), 1–18. https://doi.org/10.1080/15481603.2021.1903281
   Web of Science ®Google Scholar
• Münch, Z., & Conrad, J. (2007). Remote sensing and GIS based determination of groundwater dependent ecosystems in the Western Cape, South Africa. Hydrogeology Journal, 15(1), 19–28. https://doi.org/10.1007/s10040-006-0125-1
   Web of Science ®Google Scholar
• Munoz-Reinoso, J. C. (2001). Vegetation changes and groundwater abstraction in SW Donana, Spain. Journal of Hydrology, 242(3–4), 197–209.
   Web of Science ®Google Scholar
• Murray, B. R., Hose, G. C., Eamus, D., & Licari, D. (2006). Valuation of groundwater-dependent ecosystems: A functional methodology incorporating ecosystem services. Australian Journal of Botany, 54(2), 221–229. https://doi.org/10.1071/BT05018
   Web of Science ®Google Scholar
• Olofsson, P., Foody, G. M., Stehman, S. V., & Woodcock, C. E. (2013). Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122–131. https://doi.org/10.1016/j.rse.2012.10.031
   Web of Science ®Google Scholar
• Parker, B. M., Sheldon, F., Phinn, S., & Ward, D. (2018). Changes in foliage projective cover and its implications for mapping groundwater dependent vegetation across a precipitation gradient. Ecohydrology, 11(4), 1–9. https://doi.org/10.1002/eco.1937
   Web of Science ®Google Scholar
• Páscoa, P., Gouveia, C. M., & Kurz-Besson, C. (2020). A simple method to identify potential groundwater-dependent vegetation using NDVI MODIS. Forests, 11(2), 147. https://doi.org/10.3390/f11020147
   Web of Science ®Google Scholar
• Pereira, H. M., Ferrier, S., Walters, M., Geller, G. N., Jongman, R. H., Scholes, R. J., & Wegmann, M. (2013). Essential biodiversity variables. Science, 339(6117), 277–278.
   PubMed Web of Science ®Google Scholar
• Pérez Hoyos, I., Krakauer, N., & Khanbilvardi, R. (2016). Estimating the probability of vegetation to be groundwater dependent based on the evaluation of tree models. Environments, 3(4), 9. https://doi.org/10.3390/environments3020009
   Google Scholar
• Pérez Hoyos, I. C., Krakauer, N. Y., Khanbilvardi, R., & Armstrong, R. A. (2016). A review of advances in the identification and characterization of groundwater dependent ecosystems using geospatial technologies. Geosciences, 6(2), 17.
   Google Scholar
• Rhyma, P. P., Norizah, K., Hamdan, O., Faridah-Hanum, I., & Zulfa, A. W. (2020). Integration of normalised different vegetation index and Soil-Adjusted Vegetation Index for mangrove vegetation delineation. Remote Sensing Applications: Society and Environment, 17, 100280. https://doi.org/10.1016/J.RSASE.2019.100280
   Google Scholar
• Rouget, M., Richardson, D. M., Cowling, R. M., Lloyd, J. W., & Lombard, A. T. (2003). Current patterns of habitat transformation and future threats to biodiversity in terrestrial ecosystems of the Cape Floristic Region, South Africa. Biological Conservation, 112(1–2), 63–85. https://doi.org/10.1016/S0006-3207(02)00395-6
   Web of Science ®Google Scholar
• Rutherford, M. C., Mucina, L., & Powrie, L. W. (2006). Biomes and bioregions of southern Africa. The vegetation of South Africa Vol. 19, (pp. 30–51).
   Google Scholar
• Scott, D. F., & le Maitre, D. C. (1998). The interaction between vegetation and groundwater: Research priorities for South Africa 100.
   Google Scholar
• Scott, D. F., & Prinsloo, F. W. (2008). Longer‐term effects of pine and eucalypt plantations on streamflow. Water Resources Research, 44(7).
   Google Scholar
• Seyler, H., Lemieux, M., Dhaliwal, R., Seyler, H., MacEachern, K. N., & Heyland, D. K. (2017). Novel, family-centered intervention to improve nutrition in patients recovering from critical illness: A feasibility study. Nutrition in Clinical Practice: Official Publication of the American Society for Parenteral and Enteral Nutrition, 32(3), 392–399. https://doi.org/10.1177/0884533617695241
   PubMed Web of Science ®Google Scholar
• Shoko, C., Mutanga, O., & Dube, T. (2016). Progress in the remote sensing of C3 and C4 grass species aboveground biomass over time and space. Isprs Journal of Photogrammetry and Remote Sensing, 120, 13–24. https://doi.org/10.1016/j.isprsjprs.2016.08.001
   Web of Science ®Google Scholar
• Shoko, C., Mutanga, O., & Dube, T. (2020). Remotely sensed characterization of Acacia longifolia invasive plants in the Cape Floristic region of the Western Cape, South Africa. Journal of Applied Remote Sensing, 14(4), 044511–044511.
   Web of Science ®Google Scholar
• Stehman, S. V. (2000). Practical implications of design-based sampling inference for thematic map accuracy assessment. Remote Sensing of Environment, 72(1), 35–45. https://doi.org/10.1016/S0034-4257(99)00090-5
   Web of Science ®Google Scholar
• Stehman, S. V. (2009). Sampling designs for accuracy assessment of land cover. International Journal of Remote Sensing, 30(20), 5243–5272. https://doi.org/10.1080/01431160903131000
   Web of Science ®Google Scholar
• Suhet, H. B. (2015). Sentinel-2 user handbook. ESA Standard Document, 1.
   Google Scholar
• Thamaga, K. H., & Dube, T. (2018). Remote sensing of invasive water hyacinth (Eichhornia crassipes): A review on applications and challenges. Remote Sensing Applications: Society and Environment, 10, 36–46. https://doi.org/10.1016/j.rsase.2018.02.005
   Google Scholar
• Thamaga, K. H., Dube, T., & Shoko, C. (2021). Advances in satellite remote sensing of the wetland ecosystems in Sub-Saharan Africa Advances in satellite remote sensing of the wetland. Geocarto International, 37(20), 1–22. https://doi.org/10.1080/10106049.2021.1926552
   Web of Science ®Google Scholar
• Thamaga, K. H., Dube, T., & Thamaga, K. H. (2018). Testing two methods for mapping water hyacinth (Eichhornia crassipes) in the Greater Letaba river system, South Africa: Discrimination and mapping potential of the polar-orbiting Sentinel-2 MSI and Landsat 8 OLI sensors. International Journal of Remote Sensing, 39(22), 8041–8059. https://doi.org/10.1080/01431161.2018.1479796
   Web of Science ®Google Scholar
• Turpie, J. K., Heydenrych, B. J., & Lamberth, S. J. (2003). Economic value of terrestrial and marine biodiversity in the Cape Floristic Region: Implications for defining effective and socially optimal conservation strategies. Biological Conservation, 112(1–2), 233–251. https://doi.org/10.1016/S0006-3207(02)00398-1
   Web of Science ®Google Scholar
• van Wilgen, B. W., Reyers, B., Le Maitre, D. C., Richardson, D. M., & Schonegevel, L. (2008). A biome-scale assessment of the impact of invasive alien plants on ecosystem services in South Africa. Journal of Environmental Management, 89(4), 336–349. https://doi.org/10.1016/j.jenvman.2007.06.015
   PubMed Web of Science ®Google Scholar
• Van Wilgen, B. W., & Richardson, D. M. (2012). Three centuries of managing introduced conifers in South Africa: Benefits, impacts, changing perceptions and conflict resolution. Journal of Environmental Management, 106, 56–68. https://doi.org/10.1016/j.jenvman.2012.03.052
   PubMed Web of Science ®Google Scholar
• Vilà, M., Espinar, J. L., Hejda, M., Hulme, P. E., Jarošík, V., Maron, J. L., & Pyšek, P. (2011). Ecological impacts of invasive alien plants: A meta‐analysis of their effects on species, communities and ecosystems. Ecology letters, 14(7), 702–708.
   PubMed Web of Science ®Google Scholar
• Wang, X., Xie, S., Zhang, X., Chen, C., Guo, H., Du, J., & Duan, Z. (2018). A robust Multi-Band Water Index (MBWI) for automated extraction of surface water from Landsat 8 OLI imagery. International Journal of Applied Earth Observation and Geoinformation, 68, 73–91. https://doi.org/10.1016/j.jag.2018.01.018
   Web of Science ®Google Scholar
• Wessels, K. J., Pretorius, D. J., & Prince, S. D. (2008). The reality of rangeland degradation mapping with remote sensing: The South African experience. 14th Australas. Remote Sensing Photogrammetry Conference, 7.
   Google Scholar
• Williams, S. (2018). Perceptions of wetland ecosystem services in a region of climatic variability. University of the Western Cape.
   Google Scholar
• Zhang, G., Su, X., & Singh, V. P. (2020). Modelling groundwater-dependent vegetation index using Entropy theory. Ecological Modelling, 416, 108916. https://doi.org/10.1016/j.ecolmodel.2019.108916
   Web of Science ®Google Scholar
• Zhao, X., Zhou, D., & Fang, J. (2012). Satellite-based Studies on large-scale vegetation changes in China. Journal of Integrative Plant Biology, 54(10), 713–728. https://doi.org/10.1111/j.1744-7909.2012.01167.x
   PubMed Web of Science ®Google Scholar
• Zhu, Z. (2017). Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications. Isprs Journal of Photogrammetry and Remote Sensing, 130, 370–384. https://doi.org/10.1016/j.isprsjprs.2017.06.013
   Web of Science ®Google Scholar