1. August 20, 2015 Mapping croplands using Landsat data with generalized classifier over large areas Aparna Phalke and Mutlu Ozdogan Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison

2. Updates on following Stratification of study area Developing New LDA models at three different levels according to new strata Scaling of data Area Based Accuracy

6. ZoneCore_SceneRandom_Scene zone1177p39r (Egypt)171p39r 182p38r(EgyptR1/Libya)177p40r 194p36r 198p38r 201p38r zone2174p35r (Syria)171p35r 172p34r (Turkey)175p33r 179p33r(bulgariaR3) zone3200p33r (Spain)196p35r 201p37r (Morocco)202p34r 193p35r(Algeria)200p31r 192p35r(Tunisia) zone4181p26r (Ukraine)174p28r 176p26r 173p25r zone5182p30r (Bulgaria)190p26r 187p27r(Hungary)183p27r 182p29r(Romania)185p28r 184p30r zone6199p26r(France)196p26r 202p24r (UK)197p27r 200p27r 207p22r zone7189p24r(Poland)187p19r 193p24r(Germany)182p24r 182p21r(ukraineR1/Russia and some part Belarus)183p25r 185p24r 186p22r 188p25r 192p23r 196p23r 194p25r 175p23r zone8203p33r(Portugal)191p27r 192p29r(Italy)189p31r 196p29r(algeriaR1/france)192p30r 200p29r 202p31r 201p32 193p27r Total eight zones covering 23 core footprints and 36 random footprints

7. New own LDA model coefficients meansdmaxminvarrangecountslopeelevationcutoffpoint egypt(177p39r)4.87-13.24-2.87-10.4850.08-2.400.000.020.01-1.97 libya(182p38r)41.4647.23-19.04-8.65-14.85-16.080.010.080.000.17 syria(174p35r)2.3714.97-2.585.34-31.72-3.340.000.070.000.33 turkey_west(172p34r)8.72-36.560.620.8758.220.450.010.060.002.12 turkey_east(179p33r)7.12-3.17-2.083.71-7.21-2.610.010.100.001.87 spain15.59-14.50-1.250.3736.72-1.300.000.110.002.38 morocco9.12-3.07-4.53-5.449.46-3.070.020.090.00-0.54 algeria8.67-40.55-1.23-7.12105.42-0.370.010.140.00-0.40 tunisia10.01-47.080.07-2.10127.860.26-0.010.140.00-0.06 ukraine (181p26r)14.55-22.66-5.33-1.9240.20-0.570.03-0.040.00-1.65 176p26r 173p25r bulgaria (182p30r)14.14-19.81-5.16-1.9653.15-1.570.000.090.00-0.84 hungary(187p27r)13.60-56.00-0.88-9.1091.641.210.000.100.00-1.85 romania(182p29r)12.56-43.12-2.01-4.5788.51-0.460.020.180.00-0.55 france(199p26r)8.79-12.25-2.81-2.7312.72-1.450.210.11-0.010.21 UK(202p24r)2.28-25.32-2.67-5.7617.982.02-0.060.190.00-4.65 poland(189p24r)13.21-34.20-4.69-14.8062.44-1.47-0.010.630.00-2.94 germany(193p24r)13.49-45.13-2.95-14.2970.55-0.040.000.180.00-3.34 Russia and some part Belarus(182p21r) 15.25-29.06-11.44-9.68170.91-7.380.130.300.02-1.12 portugal(203p33r)11.2139.14-3.965.29-155.80-4.470.020.140.003.45 italy(192p29r)6.01-7.18-4.07-4.11-3.46-1.800.020.080.00-1.29 franceORalgeriaR1(196 p29r) 14.05-11.51-5.30-5.8111.29-2.04-0.040.040.00-0.07

8. New zonal LDA model coefficients meansdmaxminvarrangecountslopeelevationcutoffpoint zone14.819058-6.02105-4.3991-7.3625358.08601-4.674520.0186250.0405490.002289-1.45194 zone24.750754-22.1928-2.93649-3.4777889.60278-3.506230.0238590.0997380.000543-1.00297 zone38.569337-8.63518-1.94773-0.779520.47229-1.851490.0221770.1332890.00051.698421 zone512.17899-28.8478-3.87646-3.2091165.33539-0.985150.0223390.1285690.000497-0.44505 zone68.837099-16.128-4.35398-6.2690612.97489-0.264070.001130.174757-0.00569-2.55152 zone718.62642-4.18397-7.01027-15.10315.688592-3.82965-0.090170.2506040.001585-2.56448 zone810.25779-1.15233-5.14634-2.37113.32551-3.557840.0483220.0632770.0001520.514091

9. New segment-based (Own-based accuracy) Overall accuracy producer_accuracy_cro p.i. producer_accurac y_noncrop.i. user_accuracy_crop.i. user_accuracy_n oncrop.i. egypt(177p39r)84.93%90.61%69.65%89.03%72.95% libya(182p38r)87.55%44.63%95.52%64.57%90.30% syria(174p35r)76.77%75.74%78.07%78.26%75.40% turkey_west(172p34r ) 87.32%87.59%86.91%92.66%78.73% turkey_east(179p33r ) 78.30%70.94%85.32%81.91%75.68% spain83.23%82.76%84.27%91.19%71.18% morocco77.68%64.57%90.00%85.65%73.15% algeria74.93%62.86%87.42%83.57%69.64% tunisia72.45%66.92%78.71%77.69%68.14% ukraine (181p26r)70.08%69.43%70.68%65.57%74.12% 176p26r 173p25r bulgaria (182p30r)79.36%77.96%80.98%80.24%78.60% hungary(187p27r)71.04%83.49%55.65%70.08%72.94% romania(182p29r)78.52%85.54%67.58%80.68%74.56% france(199p26r)76.77%87.39%65.45%73.16%82.71% UK(202p24r)63.24%71.46%50.23%69.62%52.37% poland(189p24r)72.25%89.73%40.73%73.29%68.54% germany(193p24r)74.28%78.23%70.89%70.59%78.37% Russia and some part Belarus(182p21r) 67.12%21.01%94.25%68.12%67.01% portugal(203p33r)76.98%59.00%88.64%76.77%77.09% italy(192p29r)81.08%80.35%81.89%80.07%82.04% franceORalgeriaR1( 196p29r) 76.81%53.25%89.49%72.54%78.32% zone egypt(177p39r)86.07% libya(182p38r)85.61% syria(174p35r)73.78% turkey_west(17 2p34r) 84.60% turkey_east(17 9p33r) 75.84% spain83.98% morocco75.89% algeria67.74% tunisia69.80% ukraine (181p26r) 176p26r 173p25r bulgaria (182p30r) 77.30% hungary(187p2 7r) 73.01% romania(182p2 9r) 80.00% france(199p26r)71.87% UK(202p24r)57.81% poland(189p24r ) 73.18% germany(193p2 4r) 68.07% Russia and some part Belarus(182p21 r) 83.25% portugal(203p3 3r) 62.88% italy(192p29r)72.99% franceORalgeri aR1(196p29r) 77.94%

10. Area Based Accuracy Traditional pixel based approach accuracy: where π is overall accuracy, Ci is equal to 1 or 0 if the validation sample unit i is correctly classified (yes and no, respectively), and n is the number of validation units collected. The accuracy of a map created using OBIA should be computed using: where N is the total number of segments in the image, and Si is the area of a single sample unit i.

11. Reference: Meghan MacLean, Russell Congalton, “Map accuracy assessment issues when using an object based oriented approach” Dissertation, University of New Hampshire.

12. Thank you phalke@wisc.edu