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Why Sandveld?

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Why Sandveld? Land use/cover changes in the Sandveld, South Africa James T Magidi1, Dr Richard S Knight1, Dr Cornelia B. Krug2 1Biodiversity and Conservation Biology Dept, University of the Western Cape, Bag X17 Bellville, 7535 South Africa 2Dept of Zoology, University of Cape Town, P Bag X3 Rondebosch, 7701, South Africa Why Sandveld? WhyWhy isis PotatoPotato FarmingFarming of majorof major • It is part of the CFR Lowlands concern?concern? • Generally low rainfall ••UtiliseUtilise aa lotlot ofof waterwater ––leadingleading toto • Important part of the Greater Cederberg ••groundground waterwater depletiondepletion Biodiversity Corridor, connection uplands ••reductionreduction ofof wetlandswetlands and lowlands ••illegalillegal undergroundunderground water water • It has these vegetation types: extractionextraction o Piketberg Sandstone Fynbos ••PotatoesPotatoes areare susceptiblesusceptible toto nematodesnematodes o Leipoldtville Sand Fynbos predationpredation ––soso areasareas areare cultivatedcultivated for for Cape Floristic Region (CFR) o Lambert’s Bay Strandveld oneone yearyear thenthen left forleft fourfor beforefour before •One of the 34 biodiversity hotspot o Graatwater Sandstone Fynbos cultivatingcultivating again.again . Introduction • High Degree of species endemism ••60006000 ––70007000 haha ofof landland usedused forfor potatopotato • 70% Transformed due to • It is transformed due to the growing of: • Potato farmingfarming yearlyyearly • Agriculture –Lowlands & Renosterveld • 220 000 tonnes of potatoes produced • Invasive Species • Wheat • 220 000 tonnes of potatoes produced FSP • Urban Development • Rooibos perper annumannum Multi-temporal Image Classification Data Acquisition Pre-processing •Training sites Change Detection (Landsat ) Predicting Future Scenarios •Radiometric •Maximum likelihood classifier •Gains and losses in Landuse •1990 •Markov Chain Analysis •Geometric •Clump, Eliminate, Recode •Contributors of Landuse •Determining probabilities of •2004 •Filtering change change •2007 Accuracy Assessment •Kappa Index •Google Earth •Landuse Persistence •Aerial Photos ERDAS Imagine •Site Visits Methodology IDRISI ANDES Multi-temporal Landuse Maps Categories 1990 2004 2007 Change in 1990-2007 Area (ha) Area (%) Area (ha) Area (%) Area (ha) Area (%) Area (ha) Area (%) Water 1305.81 0.66 875.34 0.44 1170.72 0.59 -135.09 -10.35 Change Analysis Change Natural Vegetation 101422.44 51.04 84409.29 42.48 81120.33 40.82 -20302.11 -20.02 Wetlands 5640.12 2.84 9586.80 4.82 8167.95 4.11 2527.83 44.82 Open Sands 2317.05 1.17 632.52 0.32 1482.93 0.75 -834.12 -36.00 Irrigated Plots 19351.08 9.74 20460.87 10.30 22048.92 11.10 2697.84 13.94 Cultivated Farmlands 50270.31 25.30 38320.29 19.28 42278.94 21.28 -7991.37 -15.90 Disturbed Veld 18313.20 9.22 29279.88 14.74 25860.78 13.01 7547.58 41.21 Urban Areas 88.38 0.04 88.38 0.04 88.38 0.04 0.00 0.00 Burnt Areas 0.00 0.00 15055.02 7.58 16489.44 Kappa Index: 0.7590 Index: Kappa 8.30 16489.44 Kappa Index: 0.6408 Index: Kappa Persistent Landuse classes between 1990 and 2007 Probability of Landuse change by 2020 Probability of changing to Given Natural Wetlands Open Irrigated Cultivated Disturbed Urban Burnt Water Vegetation Sands Plots Farmlands Veld Areas Areas Water 0.86 0.02 0.02 0.07 0.01 0.02 0.01 0.00 0.00 Natural Vegetation 0.01 0.55 0.03 0.01 0.10 0.17 0.12 0.00 0.02 Wetlands 0.05 0.32 0.12 0.02 0.12 0.22 0.13 0.00 0.04 Mapping Persistence Landcover summary Landcover Open Sands 0.01 0.06 0.02 0.49 0.11 0.22 0.05 0.00 0.03 Irrigated Plots 0.00 0.20 0.03 0.03 0.17 0.31 0.12 0.00 0.14 Cultivated Farmlands 0.00 0.20 0.03 0.02 0.18 0.33 0.12 0.00 0.12 Disturbed Veld 0.00 0.32 0.03 0.02 0.15 0.28 0.14 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.00 Predicting Future Scenarios Predicting Future Urban Areas Burnt Areas 0.00 0.03 0.01 0.09 0.09 0.16 0.03 0.00 0.67.
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