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Table 5 Population estimates from analysis stratified by assessed population density

From: The validity of an area-based method to estimate the size of hard-to-reach populations using satellite images: the example of fishing populations of Lake Victoria

Id Name Population estimates Discrepancies % discrepancies
M1 M2 Reg M1 M2 Reg M1 M2 Reg
32 Lwanga Muto 143 125 182 − 65 − 83 − 26 − 31.25 − 39.90 − 12.50
33 Kisigala 281 245 274 − 254 − 290 − 261 − 47.48 − 54.21 − 48.79
34 Maala 261 267 206 11 17 − 44 4.40 6.80 − 17.60
35 Kayunyu 498 510 478 211 223 191 73.52 77.70 66.55
36 Batwala 244 250 187 − 155 − 149 − 212 − 38.85 − 37.34 − 53.13
37 Lugumba 778 797 801 332 351 355 74.44 78.70 79.60
38 Kisso 551 564 540 − 159 − 146 − 170 − 22.39 − 20.56 − 23.94
39 Kalangala 81 71 141 − 27 − 37 33 − 25.00 − 34.26 30.56
40 Kamaliba 359 313 326 169 123 136 88.95 64.74 71.58
41 Kassa 142 124 182 − 120 − 138 − 80 − 45.80 − 52.67 − 30.53
42 Kalokoso 297 260 285 2 − 35 − 10 0.68 − 11.86 − 3.39
43 Kisuku 416 363 364 − 137 − 190 − 189 − 24.77 − 34.36 − 34.18
44 Namirembe 544 475 449 − 75 − 144 − 170 − 12.12 − 23.26 − 27.46
45 Kamuwunga 870 759 666 − 443 − 554 − 647 − 33.74 − 42.19 − 49.28
46 Ddimo 1450 1265 1053 − 195 − 380 − 592 − 11.85 − 23.10 − 35.99
47 Lambu 1898 1943 2087 − 506 − 461 − 317 − 21.05 − 19.18 − 13.19
  1. Reg regression
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