Are there too many new observations to identify?

– and the overly specific identotron only makes it worse.

3 Likes

That’s one of the (very few) scenarios where I wish the observer would not specify their intent:

E.g. Shot of the moon with some branches barely in the lower corner of the photo

  • No placeholder or description?
    Cool, I can ID it as Vascular Plants for the branches!
  • “(Placeholder: moon)” or description that indications the moon is the subject?
    I’ll respect their wishes, and leave a comment asking if they want to change the focus to the branches, and maybe mark it “no evidence of organism” in the DQA in the mean time.
1 Like

I’ve noticed this too. Caveat: it seems like you should be careful if you disagreeing on a specific ID without giving a competing ID, you might have trouble if you skip to the next observation. That can a while to show up and if you don’t wait for it, you might lose your ID. It’s happened a few times where my disagreement didn’t get recorded or was recorded as “I don’t know” rather than “No.”

2 Likes

It is important not to discourage new users and non-expert users by providing as fast as possible IDs.
But, at the same time, it is important not to discourage identifiers and expert users who always have to face a considerable workload in disentangling themselves in a high number of craps.

Let’s valorize those “who knows”.

2 Likes

I agree, and feel like there’s too much emphasis on species ID, and that it’s baked into the user interface to some extent. The prominence of “needs ID” seems to reinforce the message that iNat is mainly for identifying creatures. Sure, I like to get a species ID on photos I post, but documenting interactions can be more interesting. And I feel like my photos that can’t (yet) be identified might be the most important – for example, I post lots of photos of Villa flies (or ones that look like Villas) for the very reason that they cannot be identified to species, hoping that researchers trying to make sense of that genus will find my photos helpful. My main use for iNat is not getting identifications, it’s to impose order upon my observations, so that I can easily find comparable observations from prior years and decide what to look for when I go out in the field. It works quite well for that but could be even better. Addition of a ‘prime suspect’ tag (meaning, it looks like species ‘x’, but I’m not saying it is) would be helpful. Or a tag that conveys “here’s what I think it is, but feel free to ignore my uneducated opinion”, because my tentative ID is for my own personal study only, and not intended to be relied upon by others.

9 Likes

Here’s a useful tip for anyone who wants to make it easy for themselves to contribute more IDs to iNaturalist, based on discussion in this feature request:

That URL is now a customised version of the Identify page which only shows taxa on your list. Bookmark it, and you have an instant list of easily-identifiable low-hanging fruit you can check once a day. You can further customise the filtering (e.g. limiting results only to a particular location) and then bookmark that URL if you want to be pickier about what you see.

I used to subscribe to some taxa which I wanted to get better at IDing, but that quickly became clunky and unmanageable. I find this approach much more flexible. Note that the feature request linked above suggests using your life list for this. While it has the advantage of getting automatically updated, in my experience it includes many observations which I have no chance of identifying, so personally I prefer manually making a list of taxa I know I can confidently identify.

14 Likes

Which way is best probably depends on one’s skills and equipment. I like to use the “identify” button and just write in the name of the plant I want to work on now, in the species place.

I think it is time for me to make a list of taxa I want to keep following.

4 Likes

FYI, everybody, if you want to see some page numbers go down as you ID, try adding IDs to the Unknowns with audio.

There’s fewer of them (currently just 35 pages, as opposed to 14K with photos), so even just a few coarse IDs (Is that sound made by a bird, insect, canine, or frog/toad, human, etc?) will show progress.

5 Likes

Yes, I agree with this. I’m not sure how many people are aware that iNat observations can become research grade without a species id (by clicking that the id “it’s as good as it can be” in DQA).

Oh, that’s great. I do often do what @sedgequeen suggests. There are advantages to working through one species or genus but for me that’s a bit haphazard as there are lots of things I’ll forget about.

Suggestion for anyone else doing this: if you’re adding a species which doesn’t have any close relatives (or close relatives in the geographical area you’ll be looking at) then go a step or two up the taxonomic tree. e.g. in the UK add “Hedgehogs” rather than “European Hedgehog” (our only species) so you pick up misidentifications & genus level ids.

7 Likes

I echo @whaichi on this: setting the locations to private has a huge influence. It makes it much harder/less likely for likely identifiers to find your observations. Going to your profile now I see 9/10 are research grade… I guess this post did the trick :)

2 Likes

Yes, I agree with this. I’m not sure how many people are aware that iNat observations can become research grade without a species id (by clicking that the id “it’s as good as it can be” in DQA).

I had no idea you could do this. Such a useful tip for cases where genetic evidence is necessary to get to species level.

5 Likes

You can bookmark this page, which has some copy-paste text you can use to ask new users to do things like add a coarse ID.

https://www.inaturalist.org/pages/responses

The ‘text blaze’ extension on Chrome can be used as a way of giving “frequent responses” with a few key strokes

(e.g. typing “/date” for me --> Hi - the observation date (date you took the photo) has gone missing from this record, could you add it please? More people will then see the record for possible identification )

6 Likes

Yeah, I’m using Text Expander to do the same thing, it’s been so helpful!

3 Likes

This is a genius idea. While I use Safari instead of Chrome, the same idea works by going to System Preferences → Keyboard → Text, then adding a bunch of frequently used responses.

1 Like

Per @zabdiel
Double quote on @Sedgequeen:” The one serious problem I see with not getting things identified quickly: discouraging beginners”

I think that is a pretty strong argument.

Still, as a very naive beginning user of the iPhone app, I was rather ~surprised~ to find other people ~could~ and ~might want to~ ID my photos. It never occurred to me I was doing anything other than feeding my pic into a nameless, uncaring database. And, I was fine with that… it was citizen science!

Of course, now it is so much more interesting to see the evolution of a nameless little bug making it, with luck, to species. Or, even Family.

I remember one of my first obs was a mosquito with (I thought) extra long legs. Months later, I was pretty tickled to learn it was a “Culex” !!! Whew! Imagine that! A culex! And I here I was just thinking it was a weird looking mosquito.” :crazy_face:

9 Likes

This thread is one of the reasons I do more IDing than observing.

And I agree with the WrOP, in that people can get discouraged and leave. Before I discovered iNat, I was looking for a way to learn some Caribbean plants. I found a website that was specifically for that; but in several pages of photos, all were unidentified – it appeared that the only users were observers, not identifiers. Not useful as a learning tool, and I didn’t go back.

At this stage in my life, I’m just more interested in IDing than uploading observations.

5 Likes

I may have missed it, but is there a way of finding out which areas of the world have the largest proportion of Unknown records / new users / backlog that needs clearing? What would you suggest would be most helpful?

1 Like

You can get a general idea by going to the “Explore” page, clicking on the “Unknown” icon category. It also includes things like bacteria and fungi, but those make up a small number compared to the sheer amount of unknowns, then looking at the map view.

Unknown

https://www.inaturalist.org/observations?place_id=any&iconic_taxa=unknown

In general, places with a lot of observations have a lot of unknown observations. So generally speaking, this would probably be like North America, Europe, as well as some spots like Hong Kong and Taiwan that are observation-dense.

at a country level, this will give you number of verifiable records:
https://jumear.github.io/stirfry/iNat_countries.html?verifiable=true&stats=observations

… and this will give you number of verifiable unknown records:
https://jumear.github.io/stirfry/iNat_countries.html?verifiable=true&iconic_taxa=unknown&stats=observations

once you have both data sets, you could calculate the proportion of verifiable unknown to verifiable records… or you modify the parameters above to filter by submit date range, needs ID, etc… whatever floats your boat.

UPDATE: i ran the numbers for unknown verifiable vs all verifiable:

ID Alpha-2 Code Name Parent Place Wikidata ID Population Area (sq km) Unknown Verifiable All Verifiable Percent Unknown of Verifiable
8358 SC Seychelles Africa Q1042 95,843 459 960 7,190 13.35%
8515 NE Niger Africa Q1032 21,477,348 1,267,000.00 235 2,601 9.03%
10311 PM Saint Pierre and Miquelon North America Q34617 6,057 242 9 109 8.26%
10282 AX Åland Europe Q5689 28,983 1,580.00 68 1,201 5.66%
8509 BJ Benin Africa Q962 11,175,692 114,763.00 1,230 22,526 5.46%
7985 GS South Georgia and the South Sandwich Islands Q35086 30 3,718.00 70 1,699 4.12%
8051 DK Denmark Europe Q756617 5,930,987 2,220,930.00 15,015 370,858 4.05%
51356 BL Saint-Barthélemy North America Q25362 9,625 25 8 218 3.67%
6783 BO Bolivia South America Q750 11,051,600 1,098,581.00 3,254 91,712 3.55%
10290 FO Faroe Islands Europe Q4628 52,154 1,399.00 76 2,562 2.97%
6873 PH Philippines Asia Q928 100,981,437 343,448.00 2,008 77,762 2.58%
7218 SO Somalia Africa Q1045 11,031,386 637,657.00 10 421 2.38%
7141 NG Nigeria Africa Q1033 190,886,311 923,768.00 163 6,980 2.34%
8516 TG Togo Africa Q945 7,797,694 56,785.00 16 725 2.21%
96773 Northern Cyprus Europe 16 906 1.77%
6931 DO Dominican Republic North America Q786 10,403,761 48,670.80 537 32,409 1.66%
7887 TW Taiwan Asia Q865 23,593,794 36,193.00 10,740 673,215 1.60%
8858 RO Romania Europe Q218 19,586,539 238,397.00 460 29,851 1.54%
10301 MO Macao Asia Q14773 566,375 115.3 175 11,669 1.50%
10304 MS Montserrat North America Q13353 5,215 102 2 135 1.48%
7305 LY Libya Africa Q1016 6,678,567 1,759,541.00 3 210 1.43%
7846 ML Mali Africa Q912 18,541,980 1,240,192.00 13 911 1.43%
8177 GP Guadeloupe North America Q17012 390,253 1,628.00 51 3,619 1.41%
7143 SZ Eswatini Africa Q1050 1,124,753 17,364.00 204 14,560 1.40%
7506 NL Netherlands Europe Q55 17,282,163 41,543.00 2,854 207,431 1.38%
10317 VC Saint Vincent and the Grenadines North America Q757 109,897 389 13 950 1.37%
8265 EE Estonia Europe Q191 1,324,820 45,339.00 180 13,719 1.31%
10283 AG Antigua and Barbuda North America Q781 102,012 440.3 20 1,550 1.29%
7357 QA Qatar Asia Q846 2,639,211 11,437.00 14 1,089 1.29%
6753 FR France Europe Q142 66,628,000 643,801.00 8,356 695,611 1.20%
7563 SV El Salvador North America Q792 6,420,746 20,742.00 247 20,602 1.20%
7008 BE Belgium Europe Q31 11,431,406 30,528.00 2,228 191,825 1.16%
8264 CZ Czechia Europe Q213 10,693,939 78,866.00 2,360 207,246 1.14%
7003 PA Panama North America Q804 4,098,587 74,177.30 1,648 144,872 1.14%
7578 BY Belarus Europe Q184 9,408,400 207,600.50 711 62,569 1.14%
10295 IO British Indian Ocean Territory Asia Q43448 4,000 1 89 1.12%
9445 CV Cape Verde Africa Q1011 546,388 4,033.00 24 2,148 1.12%
7020 FI Finland Europe Q33 5,501,043 338,424.40 2,311 215,178 1.07%
9184 DM Dominica North America Q784 73,925 751.1 23 2,394 0.96%
7196 CO Colombia South America Q739 49,065,615 1,141,748.00 4,167 434,177 0.96%
10300 LC Saint Lucia North America Q760 178,844 617 19 2,048 0.93%
8240 MT Malta Europe Q233 465,292 316 25 2,718 0.92%
7016 NO Norway Europe Q20 5,367,580 385,207.00 662 72,126 0.92%
7254 PY Paraguay South America Q733 6,811,297 406,756.00 83 9,114 0.91%
7399 HU Hungary Europe Q28 9,769,526 93,011.40 218 24,300 0.90%
10284 BH Bahrain Asia Q398 1,492,584 765 7 783 0.89%
6793 MX Mexico North America Q96 130,526,945 1,972,550.00 22,602 2,545,423 0.89%
1303 VE Venezuela South America Q717 28,515,829 916,445.00 114 12,974 0.88%
10285 BB Barbados North America Q244 285,719 439 27 3,073 0.88%
10305 MQ Martinique North America Q17054 372,594 1,128.00 95 10,981 0.87%
8227 MC Monaco Europe Q235 38,695 2 2 232 0.86%
8748 JM Jamaica North America Q766 2,890,299 10,991.90 69 8,021 0.86%
7064 SD Sudan Africa Q1049 40,533,330 1,886,068.00 2 235 0.85%
7358 SA Saudi Arabia Asia Q851 33,000,000 2,250,000.00 25 2,941 0.85%
8510 BF Burkina Faso Africa Q965 19,193,382 274,200.00 20 2,360 0.85%
7783 MG Madagascar Africa Q1019 25,570,895 587,295.00 632 75,358 0.84%
6774 ES Spain Europe Q29 46,733,038 505,990.00 4,096 498,540 0.82%
10297 KN Saint Kitts and Nevis North America Q763 55,345 269.4 42 5,196 0.81%
7312 TN Tunisia Africa Q948 11,565,204 163,610.00 21 2,702 0.78%
7142 RW Rwanda Africa Q1037 12,208,407 26,338.00 24 3,095 0.78%
8226 AD Andorra Europe Q228 76,177 468 9 1,185 0.76%
7526 HT Haiti North America Q790 10,981,229 27,750.00 32 4,258 0.75%
6737 JP Japan Asia Q17 126,785,797 377,972.30 1,079 147,184 0.73%
8004 CI Côte d’Ivoire Africa Q1008 24,294,750 322,463.00 10 1,393 0.72%
6940 GT Guatemala North America Q774 17,263,239 108,889.00 190 27,080 0.70%
8267 SK Slovakia Europe Q214 5,397,036 49,035.00 208 30,507 0.68%
7355 KW Kuwait Asia Q817 4,600,000 17,818.00 59 8,826 0.67%
7106 BI Burundi Africa Q967 10,864,245 27,834.00 3 463 0.65%
6857 GB United Kingdom Europe Q145 66,022,273 242,495.40 8,310 1,293,598 0.64%
7094 GR Greece Europe Q41 10,760,421 131,957.00 742 116,777 0.64%
10291 GG Guernsey Europe Q25230 65,345 78 6 971 0.62%
7800 PL Poland Europe Q36 38,382,576 312,683.00 805 131,641 0.61%
7183 TR Turkey Asia Q43 82,003,882 783,562.10 289 47,551 0.61%
1 US United States North America Q30 328,239,523 9,826,675.00 171,677 28,985,881 0.59%
6712 CA Canada North America Q16 37,894,799 9,984,670.00 24,288 4,133,292 0.59%
6847 VN Vietnam Asia Q881 94,660,000 331,690.00 223 38,802 0.57%
7359 AE United Arab Emirates Asia Q878 9,400,145 83,600.00 80 14,346 0.56%
10296 JE Jersey Europe Q785 105,500 118.2 13 2,357 0.55%
6973 IT Italy Europe Q38 60,317,000 301,338.00 4,091 789,638 0.52%
7042 KE Kenya Africa Q114 48,468,138 581,309.00 317 61,649 0.51%
7182 CL Chile South America Q298 18,054,726 756,102.00 575 119,843 0.48%
6986 ZA South Africa Africa Q258 59,622,350 1,221,037.00 5,229 1,118,401 0.47%
10281 AI Anguilla North America Q25228 16,086 91 2 431 0.46%
7122 PT Portugal Europe Q45 10,600,000 92,212.00 1,414 307,554 0.46%
7315 TC Turks and Caicos Islands North America Q18221 33,098 417 8 1,788 0.45%
8050 LV Latvia Europe Q211 1,909,000 64,589.00 26 5,848 0.44%
9753 PS Palestine Asia Q219060 4,684,777 27,000.00 14 3,240 0.43%
7306 MA Morocco Africa Q1028 36,029,138 710,850.00 50 11,704 0.43%
8241 BG Bulgaria Europe Q219 7,000,039 110,993.60 103 24,826 0.41%
7512 EC Ecuador South America Q736 16,624,858 283,560.00 1,828 449,768 0.41%
7342 KZ Kazakhstan Asia Q232 18,276,500 2,724,900.00 77 19,738 0.39%
7300 DZ Algeria Africa Q262 41,318,142 2,381,741.00 97 25,131 0.39%
7599 SE Sweden Europe Q34 10,373,225 528,861.10 377 98,441 0.38%
7353 SJ Svalbard and Jan Mayen Europe Q842829 9 2,406 0.37%
7375 TT Trinidad and Tobago South America Q754 1,369,125 5,128.00 101 27,621 0.37%
7313 BS Bahamas North America Q778 395,361 13,878.00 44 12,248 0.36%
9992 GD Grenada North America Q769 107,825 348.5 5 1,400 0.36%
8638 BM Bermuda North America Q23635 65,024 53 8 2,268 0.35%
7054 CD Democratic Republic of the Congo Africa Q974 86,790,567 2,344,858.00 48 13,704 0.35%
7074 TD Chad Africa Q657 15,477,751 1,284,000.00 3 889 0.34%
6878 BR Brazil South America Q155 210,147,125 8,515,767.00 1,498 455,014 0.33%
10306 YT Mayotte Africa Q17063 256,518 374 6 1,825 0.33%
6903 CN China Asia Q148 1,409,517,397 9,596,961.00 425 130,085 0.33%
10318 VG British Virgin Islands North America Q25305 31,758 153 6 1,860 0.32%
51360 MF Saint-Martin North America Q126125 35,684 53.2 2 625 0.32%
7133 MR Mauritania Africa Q1025 4,420,184 1,030,700.00 1 322 0.31%
7513 PE Peru South America Q419 29,381,884 1,285,216.00 359 118,367 0.30%
7259 UY Uruguay South America Q77 3,456,750 176,215.00 52 17,368 0.30%
8268 BA Bosnia and Herzegovina Europe Q225 3,507,017 51,197.00 10 3,440 0.29%
10411 SX Sint Maarten North America Q26273 37,132 34 4 1,376 0.29%
6924 CR Costa Rica North America Q800 4,905,769 51,100.00 751 262,383 0.29%
6968 UG Uganda Africa Q1036 42,862,958 241,038.00 49 17,389 0.28%
8504 WS Samoa Oceania Q683 196,440 2,842.00 2 716 0.28%
7833 JO Jordan Asia Q810 10,428,241 89,341.00 15 5,518 0.27%
10408 CW Curaçao South America Q25279 160,337 444 16 6,299 0.25%
51754 SS South Sudan Africa Q958 12,575,714 619,745.30 1 402 0.25%
6734 SG Singapore Asia Q334 5,888,926 719.1 336 138,222 0.24%
6681 IN India Asia Q668 1,326,093,247 3,287,263.00 1,182 496,603 0.24%
8228 SI Slovenia Europe Q215 2,066,880 20,273.00 66 29,181 0.23%
7055 EG Egypt Africa Q79 94,798,827 1,010,407.90 28 12,480 0.22%
7140 NA Namibia Africa Q1030 2,533,794 825,615.00 72 32,259 0.22%
6718 IE Ireland Europe Q27 4,761,865 70,273.00 88 39,750 0.22%
7228 GH Ghana Africa Q117 26,908,262 238,535.00 16 7,848 0.20%
7100 AO Angola Africa Q916 29,784,193 1,246,700.00 11 5,481 0.20%
8859 ME Montenegro Europe Q236 622,359 13,812.00 13 6,591 0.20%
7147 RS Serbia Europe Q403 7,022,268 88,361.00 44 23,252 0.19%
6748 PF French Polynesia Oceania Q30971 275,918 4,167.00 11 5,878 0.19%
8266 LT Lithuania Europe Q37 2,790,842 65,300.00 218 120,418 0.18%
6803 NZ New Zealand Oceania Q664 4,942,500 268,021.00 1,620 898,632 0.18%
7207 DE Germany Europe Q183 83,149,300 357,400.00 1,420 798,427 0.18%
6953 BZ Belize North America Q242 374,681 22,966.00 68 38,255 0.18%
7841 TO Tonga Oceania Q678 108,020 748.5 1 565 0.18%
7002 KH Cambodia Asia Q424 16,005,373 181,035.00 39 22,227 0.18%
7352 UZ Uzbekistan Asia Q265 33,570,609 448,978.00 4 2,283 0.18%
10289 CY Cyprus Europe Q229 1,141,166 9,242.50 15 8,713 0.17%
6992 MM Myanmar Asia Q836 53,370,609 676,577.20 8 4,710 0.17%
7333 NF Norfolk Island Oceania Q31057 1,748 34.6 1 589 0.17%
8357 MU Mauritius Africa Q1027 1,264,613 2,040.00 8 4,741 0.17%
96774 Akrotiri and Dhekelia Europe 4 2,393 0.17%
7190 AR Argentina South America Q414 44,938,712 2,780,400.00 477 288,272 0.17%
6925 NI Nicaragua North America Q811 6,217,581 130,375.00 51 31,125 0.16%
7278 IS Iceland Europe Q189 357,050 103,004.00 31 19,069 0.16%
8505 AL Albania Europe Q222 3,020,209 28,748.00 23 14,562 0.16%
10292 GI Gibraltar Europe Q1410 33,140 6.8 1 636 0.16%
6744 AU Australia Oceania Q408 24,511,800 7,692,024.00 2,587 1,684,030 0.15%
10303 MK Macedonia Europe Q221 2,075,301 25,713.00 5 3,299 0.15%
8356 CF Central African Republic Africa Q929 4,659,080 622,984.00 1 667 0.15%
7001 LA Laos Asia Q819 6,858,160 236,800.00 12 8,065 0.15%
10314 TL East Timor Asia Q574 1,296,311 14,918.70 6 4,120 0.15%
10302 MD Moldova Europe Q217 2,550,900 33,846.00 2 1,382 0.14%
8514 LR Liberia Africa Q1014 4,731,906 111,369.00 2 1,440 0.14%
8206 IQ Iraq Asia Q796 38,274,618 437,072.00 5 3,610 0.14%
7046 CG Republic of Congo Africa Q971 5,260,750 342,000.00 5 3,625 0.14%
7146 ZW Zimbabwe Africa Q954 16,529,904 390,757.00 25 18,333 0.14%
7134 MZ Mozambique Africa Q1029 29,668,834 801,590.00 16 12,409 0.13%
10298 null Kosovo Europe 7 5,678 0.12%
10322 FM Federated States of Micronesia Oceania Q702 105,544 702 2 1,661 0.12%
7546 CM Cameroon Africa Q1009 24,053,727 475,442.00 14 11,768 0.12%
7704 GL Greenland North America Q223 56,081 2,166,086.00 3 2,568 0.12%
7838 BN Brunei Asia Q921 428,697 5,765.30 3 2,640 0.11%
7155 MY Malaysia Asia Q833 31,624,264 330,290.00 256 227,525 0.11%
8834 RE Reunion Africa Q17070 853,659 2,512.00 9 8,009 0.11%
7690 FK Falkland Islands South America Q9648 4,550 12,200.00 2 1,795 0.11%
7707 BT Bhutan Asia Q917 807,610 38,394.00 16 14,606 0.11%
8359 AW Aruba South America Q21203 102,911 178.9 3 2,892 0.10%
8860 UA Ukraine Europe Q212 42,558,328 603,629.00 167 164,584 0.10%
6815 IL Israel Asia Q801 9,093,000 20,770.00 68 67,950 0.10%
7346 KG Kyrgyzstan Asia Q813 6,201,500 199,951.00 3 3,014 0.10%
10299 LB Lebanon Asia Q822 6,100,075 10,452.00 3 3,087 0.10%
10294 IM Isle of Man Europe Q9676 85,888 572 3 3,143 0.10%
7827 SR Suriname South America Q730 563,402 163,270.00 7 7,353 0.10%
7144 TZ Tanzania Africa Q924 57,310,019 947,303.00 52 55,413 0.09%
7320 PW Palau Oceania Q695 21,729 465.6 6 6,409 0.09%
7154 BD Bangladesh Asia Q902 164,669,751 147,570.00 6 6,417 0.09%
6845 SN Senegal Africa Q1041 15,850,567 196,722.00 5 5,387 0.09%
8360 BQ Bonaire, Sint Eustatius and Saba North America Q27561 25,019 322 7 8,207 0.09%
8196 HR Croatia Europe Q224 4,105,493 56,594.00 41 50,205 0.08%
7487 SL Sierra Leone Africa Q1044 7,557,212 71,740.00 1 1,243 0.08%
7613 HK Hong Kong Asia Q8646 7,500,700 2,755.00 358 483,837 0.07%
7082 VU Vanuatu Oceania Q686 276,244 12,190.00 2 2,731 0.07%
7356 OM Oman Asia Q842 4,829,480 309,500.00 4 5,626 0.07%
6966 ID Indonesia Asia Q252 270,625,568 1,904,570.00 141 200,577 0.07%
8207 SY Syria Asia Q858 18,269,868 185,180.00 1 1,456 0.07%
8057 AT Austria Europe Q40 8,809,212 83,879.00 153 223,431 0.07%
7488 KY Cayman Islands North America Q5785 58,435 264 4 6,004 0.07%
6967 TH Thailand Asia Q869 65,931,550 513,119.50 58 87,875 0.07%
8425 MV Maldives Asia Q826 436,330 298 4 6,203 0.06%
7083 NC New Caledonia Oceania Q33788 278,500 18,576.00 11 17,172 0.06%
8857 GE Georgia Asia Q230 3,717,100 69,700.00 13 20,515 0.06%
7105 BW Botswana Africa Q963 2,291,661 581,737.00 29 48,160 0.06%
7112 GA Gabon Africa Q1000 2,025,137 267,667.00 2 3,463 0.06%
7161 RU Russia Asia Q159 146,804,372 17,125,191.00 834 1,536,067 0.05%
6944 CU Cuba North America Q241 11,484,636 109,884.00 13 25,167 0.05%
6929 HN Honduras North America Q783 9,265,067 112,492.00 37 74,712 0.05%
7145 ZM Zambia Africa Q953 17,094,130 752,618.00 9 18,897 0.05%
8434 AZ Azerbaijan Asia Q227 10,127,874 86,600.00 1 2,203 0.05%
6949 GF French Guiana South America Q3769 268,700 83,534.00 4 9,376 0.04%
7113 MW Malawi Africa Q1020 18,622,104 118,484.20 5 13,200 0.04%
7077 LK Sri Lanka Asia Q854 21,444,000 65,610.00 18 47,899 0.04%
8142 GY Guyana South America Q734 777,859 214,970.00 2 5,551 0.04%
7076 PK Pakistan Asia Q843 216,565,318 881,913.00 6 16,731 0.04%
6818 IR Iran Asia Q794 79,966,230 1,648,195.00 2 7,331 0.03%
7236 CH Switzerland Europe Q39 8,466,017 41,285.00 49 181,815 0.03%
7335 NP Nepal Asia Q837 29,400,000 147,181.30 4 16,343 0.02%
8147 LU Luxembourg Europe Q32 626,108 2,586.40 16 65,407 0.02%
7347 MN Mongolia Asia Q711 3,075,647 1,566,000.00 2 8,421 0.02%
7332 FJ Fiji Oceania Q712 905,502 18,274.00 3 14,629 0.02%
6891 KR South Korea Asia Q884 51,466,201 100,295.00 33 186,525 0.02%
6846 ET Ethiopia Africa Q115 104,957,438 1,104,300.00 2 11,575 0.02%
8433 AM Armenia Europe Q399 2,930,450 29,743.40 1 17,617 0.01%
7341 AF Afghanistan Asia Q889 34,940,837 652,230.00 0 491 0.00%
7616 CX Christmas Island Asia Q31063 1,843 135 0 2,664 0.00%
10287 CC Cocos Islands Asia Q36004 596 14 0 536 0.00%
8421 KM Comoros Africa Q970 823,652 2,034.00 0 630 0.00%
10288 CK Cook Islands Oceania Q26988 17,434 240 0 2,302 0.00%
8511 DJ Djibouti Africa Q977 956,985 23,200.00 0 352 0.00%
9240 GQ Equatorial Guinea Africa Q983 1,267,689 28,051.00 0 695 0.00%
8208 ER Eritrea Africa Q986 3,497,000 117,600.00 0 661 0.00%
9319 TF French Southern Territories Q129003 196 7,829.00 0 470 0.00%
7063 GM Gambia Africa Q1005 2,100,568 11,300.00 0 3,350 0.00%
8512 GN Guinea Africa Q1006 12,717,176 245,857.00 0 1,436 0.00%
8513 GW Guinea-Bissau Africa Q1007 1,861,283 36,125.00 0 585 0.00%
10293 HM Heard Island and McDonald Islands Q131198 0 368 0 20 0.00%
10323 KI Kiribati Oceania Q710 116,398 811 0 577 0.00%
8489 LS Lesotho Africa Q1013 2,233,339 30,355.00 0 1,150 0.00%
8263 LI Liechtenstein Europe Q347 37,922 160 0 828 0.00%
10324 MH Marshall Islands Oceania Q709 53,127 181.4 0 1,925 0.00%
10308 NR Nauru Oceania Q697 13,650 21 0 65 0.00%
10307 NU Niue Oceania Q34020 1,612 260 0 549 0.00%
8432 KP North Korea Asia Q423 25,490,965 120,540.00 0 1,182 0.00%
7013 PG Papua New Guinea Oceania Q691 8,251,162 462,840.00 0 5,919 0.00%
10309 PN Pitcairn Islands Oceania Q35672 50 47 0 79 0.00%
6685 SH Saint Helena Africa Q192184 4,534 394 0 263 0.00%
10310 SM San Marino Europe Q238 33,400 61.2 0 253 0.00%
9173 ST Sao Tome and Principe Africa Q1039 204,327 1,001.00 0 1,496 0.00%
7081 SB Solomon Islands Oceania Q685 611,343 28,400.00 0 6,590 0.00%
8435 TJ Tajikistan Asia Q863 8,921,343 143,100.00 0 2,012 0.00%
10313 TK Tokelau Oceania Q36823 1,499 10 0 127 0.00%
7351 TM Turkmenistan Asia Q874 5,850,901 491,210.00 0 180 0.00%
10315 TV Tuvalu Oceania Q672 11,192 26 0 80 0.00%
10316 UM United States Minor Outlying Islands Oceania Q16645 300 34.2 0 746 0.00%
9213 VA Vatican City Europe Q237 1,000 0.4 0 327 0.00%
7334 WF Wallis and Futuna Oceania Q35555 12,197 274 0 52 0.00%
10321 EH Western Sahara Africa Q6250 582,000 266,000.00 0 772 0.00%
7837 YE Yemen Asia Q805 28,250,420 555,000.00 0 402 0.00%
54505 AQ Antarctica 53669 Q21590062 N/A N/A N/A
10286 BV Bouvet Island Q23408 0 49 0 0 N/A
10320 null Clipperton Island 0 0 N/A
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