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Table 4 Population estimates from analysis stratified by location

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 Discrepancy % discrepancy
M1 M2 Reg M1 M2 Reg M1 M2 Reg
32 Lwanga Muto 229 223 234 21 15 26 10.10 7.21 12.50
33 Kisigala 450 439 444 − 85 − 96 − 91 − 15.89 − 17.94 − 17.01
34 Maala 235 229 240 − 15 − 21 − 10 − 6.00 − 8.40 − 4.00
35 Kayunyu 449 438 443 162 151 156 56.45 52.61 54.36
36 Batwala 220 215 225 − 179 − 184 − 174 − 44.86 − 46.12 − 43.61
37 Lugumba 702 685 683 256 239 237 57.40 53.59 53.14
38 Kisso 497 485 489 − 213 − 225 − 221 − 30.00 − 31.69 − 31.13
39 Kalangala 108 111 19 0 3 − 89 0.00 2.78 − 82.41
40 Kamaliba 481 491 469 291 301 279 153.16 158.42 146.84
41 Kassa 190 194 118 − 72 − 68 − 144 − 27.48 − 25.95 − 54.96
42 Kalokoso 398 407 369 103 112 74 34.92 37.97 25.08
43 Kisuku 557 569 561 4 16 8 0.72 2.89 1.45
44 Namirembe 729 744 768 110 125 149 17.77 20.19 24.07
45 Kamuwunga 1165 1190 1295 − 148 − 123 − 18 − 11.27 − 9.37 − 1.37
46 Ddimo 1943 1984 2235 298 339 590 18.12 20.61 35.87
47 Lambu 1432 1463 1618 − 972 − 941 − 786 − 40.43 − 39.14 − 32.70
  1. Reg regression
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