How about OpenMapSurfer?

Even theoretically, any high resolution imagery in Bing service can’t be older than 15 years, since first QuickBird satellite was launched in 2001.

For San Fernando City, Bing API says it’s the first half of 2012, and it seems to be true, judging by comparison with historical imagery in Google Earth.

Large stripe, covering area further from coast is even newer - 2014. Other parts are not older that 2011. There are small areas, covered by low resolution imagery, but they are really small.

So, don’t panic.

@Zverik,

I knew you are skillful in turning meaning of someone’s words upside down and reading things between the lines (which aren’t usually there), but your last comment is a masterpiece.

If anyone wants to have Sentinel 2 data, this person has huge amount of options. Including learning some very simple things. It is required to effectively make own composites. Composites, produced by any step-by-step instruction will often (not every time) be close to useless.

These required things are: basics of color correction (histogram manipulation, in particular), basics of QGIS or GDAL (understanding of about five simple operations), basics of graphic formats (concept of bits per pixel, resolutions, image channels, compression). All these things are covered by many different sources of information and could be learned in one day. Examples usually can’t serve as a proof, but back in nineties I learned how to do that having no idea about programming or GIS, just with certain skills of image editing in Photoshop and being able to use Windows command line.

Getting back to asking me to make those composites - the most important result of my experiment was not the fact that people don’t want to ask me to make composites, but the fact they (except a couple of them) don’t want to use ones I already made for them, covering two areas with largest density of mappers in Russia. But I’m still making those (for just a couple of people).

Are you serious about someone being super-shy, which prevents him from asking me? Because if yes, you just said, that people in OSM community have social development level of kindergarten kids. (Which is sometimes true, but in form of self-esteem, primitive demagogy and passive-aggressive behavior.) In that case, they probably have to work on their social skills (for their own good, to live normal life), not on remote sensing skills. In other words, I’m okay with giving food to one, who can hold a spoon, but I don’t want to spoon feed any lazy adult people like you want me to do. If someone is afraid of me because I don’t hesitate to call dumb people “idiots”, that’s not my business either, because I explicitly told it many times: there is nothing bad in lack of knowledge, but it’s really bad if someone doesn’t want to learn anything. “Learn” means “getting some understanding”, not “learning how to repeat steps like a monkey”.

It’s easy to see that I always been supporting meaningful discussions on topic of remote sensing data on Russian forum and answering questions “how it works”, while community was usually quite cold towards this topic. Don’t say that it was because no tutorials were available - there are tons of information and examples on topic of Landsat data, more or less useful, and a couple of people successfully demonstrated that it’s easy to learn how to use it.

@Zverik,

I’d say close to nothing.

• Download procedure - obviously, no, Sentinel data are not hosted by EarthExplorer
• Pansharpening/combining channels together - no, since Dan’s GDAL scripts were written exclusively for Landsat 8 (however, someone can try forking them and rewriting for Sentinel 2)
• Color correction - probably, gdal_contrast_stretch script does the same thing I’m doing with convert -contrast-stretch and preserves georeferencing, but there is no tutorial, which will give you universally usable black point and white point parameters (ones in -percentile-range 0.05 0.95) - it depends on specific circumstances, where and when particular image was taken. User should understand, how to manipulate them or to evaluate image statistics to pick them initially.
• listgeo and geotifcp trick - yes, sometimes - in case of data in GeoTIFF format (L1C data I’m using are in GeoJPEG2000, and I don’t know, if there is a source of GeoTIFFs, however, it’s possible to convert them with GDAL, but that’s a kind of awful workaround)
• Conversion into JPEG with ImageMagick - it’s redundant for this case, in addition to that, there are tons of useful parameters for similar operation, not mentioned there (like chroma subsampling, reduced resolution reading, etc.)
• Building tiled data source - yes - this thing is universal, but if it’s about making something available for everybody, like I’m doing it with NextGIS.com - this step is redundant.

So, bottom line is: it’s irrelevant. And I have to add, that certain decisions anyone has to make when cooking composites, require understanding instead of just careful following predefined steps. But you don’t really believe in things like that, as far as I remember. (And why people spending five years in universities, learning fundamentals, instead of just grabbing some step-by-step instructions and starting working like a pro?)

There supposed to be special software for Sentinel (and many others) data processing - STEP, but I tried it twice with no positive results - it spits out some error message, like it’s unable to read this particular format, but it happens all the time.

Another Landsat 8 turorial is way closer to practical solution (everything before NDVI calculation), but again, it doesn’t give any universal solution for choice of bands and for contrast stretching. It’s easy to play with different bands and parameters in QGIS, because it’s interactive. But again - certain understanding is required, because otherwise it would be endless trial-and-error. Oh, and you need pretty large RAM to load all channels together, including ones you don’t really need.

Did I answer your question?

If you also magically can make Mapiliary as popular as Google Street View currently is, that suggestion would make at least some sense for them.

@GOwin, no, the aren’t - if they don’t check that email, used for registration, there is no way to contact them. And it happens often - people, who prefer social networks over “traditional” communication methods, don’t really care about emails. But the problem is larger, since some of them don’t even have an idea that by editing something, they becoming a part of community. And comments with certain demands and suggestions seem strange and unwanted for them. Basically, they are unaware of community and not necessarily want to be a part of it, since Maps.me is a navigation app they using, nothing more.

@SomeoneElse, that suggestions was given to Zverik several times.

To be precise, intention of my diary entry you’ve mentioned wasn’t to report specific bad edits (in that case, I would do the same as you did - gather statistics and present it), but to address current fundamental issues, systematically leading to certain types of mistakes.

Comparing amount good edits with bad ones doesn’t disprove the fact of negative demotivating effect of large amount of bad edits on responsible contributors, which can’t be measured by analyzing OSM database statistics. Negative responses, including quite expressive ones, can be found in changeset comments, forum, mail list and diary postings. Which didn’t happen that often previously, because Maps.me, thanks to its popularity, generates larger absolute amount of edits and proportionally large amount of bad ones.

@imagico,

I’m completely aware of these drawbacks, however, to utilize full extent of dynamic range in case of mountain areas, usage of non-smooth adjustment curves is required, or two (high key and low key) images should be produced by histogram manipulation and then - blended together with “if darker/if brighter” blending mode. It definitely takes time.

@PlaneMad, That work you are doing is important, but reading information you’ve provided, I see no way anyone can perform more or less effective image processing without any knowledge. Image processing requires certain level of understanding, because there is no universal method - processing of every scene depends on types of land use, types of vegetation, urban/rural populated land, climatic zone, season etc. Theoretically, you can make tens of instructions and make people trying different ones without any understanding until they get desired result. But even to see, if result is desired, one need knowledge and understanding. Basically, trained monkey can’t do image processing, only thinking human can. That’s why education is more important than training.

And, as I said, my experiment shows that even having ready-to-use data, many people refusing to use it. Probably, because their mind is inert, and they can’t just easily start using something new. Same thing happens sometimes, when Bing updates imagery. People complaining: “oh, that new image, it’s different, I can’t see familiar things”.

@imagico,

Since we usually do have some high resolution imagery within an area, covered by large Sentinel 2 tile or full scene, it helps to establish certain level of understanding. However, without even basic remote sensing knowledge and skills, it’s barely possible to extract and interpret any significant amount of information from medium-resolution imagery.

To retain low contrast details on some tiles, I used CLAHE in form of ImageJ/Fiji plugin module. It really helps, and it’s okay to use it with relatively large window (256px or something), since nobody is going to use automated classification on this imagery. Combining slightly less aggressive contrast stretch with CLAHE gives nice results, as you can see.

@imagico,

Unfortunately for OSM, general level of proficiency even in basic remote sensing technologies is quite low, despite certain efforts of MapBox to change it by their blog posts on Landsat, for example.

But since there is certain significant difference between active usage of “alternative” data sources in HOT mapping and quite lazy attitude in case of regular mapping, it seems like it’s all about motivation. Just like in that saying: “One who wants to do something, looks for an opportunity and method. One who doesn’t want to, looks for an obstacle”. (By the way, that’s my reason why I don’t want to spend time on making detailed step-by-step tutorials how to process remote sensing data - if someone says he needs one, he’s probably uses it as an excuse too, because there are tons of information on this topic on the Web.)

Regarding of contrast stretching - if I wouldn’t do any, some details will be completely lost, since original dynamic range is huge and linear min-max stretch will give no real difference between forest, bushes, forested wetlands and other visually similar features. It’s also hard to differentiate this year, last year and older logging parcels without NIR data, since young trees and tall grass look similar in visible light.

То, что вы описываете в пункте (2) - фиксированный набор типов и свойств - в традиционных ГИС называется “классификатор”. В OSM классификатор тоже есть, только не в традиционной форме: он свободно расширяемый (any tags you like).

Верифицируемость, на самом деле - не просто возможность проверить данные (то есть посмотреть на них, свериться с чем-то и сказать “да, годится”), а нечто перекликающееся с научным понятием воспроизводимости результата, то есть возможностю того, что независимый маппер, глядя на тот же реальный объект и располагая теми же сведениями о нем (но не зная о существующем обозначении), может обозначить его таким же, либо не противоречащим исходному способом. Такая трактовка критерия верифицируемости позволяет куда эффективнее фильтровать невнятные обозначения.

This is an old topic, but since Google lists it on the first place when someone is looking for “Sentinel 2 OpenStreetMap”, I think, it worth mentioning. Copernicus data section of Contributors Wiki page Which means, it’s enough to add credit information such as “Copernicus Sentinel data [Year]” in source= of your changeset or specific feature.

@Omnific,

When you are talking about one wrong edit - it’s not a big concern. However, Maps.me users can sometimes generate several tens of edits per day, each edit in own changeset. Try counting time, required for reviewing all of them, using WhoDidIt and achavi tools. Then, imagine, that it happens every day.

Another thing is that it doesn’t matter, what anyone can potentially do using particular editor. In JOSM, you can make lots of bad things, much worse than in Maps.me or Potlatch and iD. But to address an actual problem instead of its imaginary vision, we have to look at real results. iD users currently doing bad edits not because there is something wrong with iD’s concept, but because lack of knowledge, while in case of Maps.me, certain concepts of editing workflow are wrong and provoking wrong edits.

@Kilkenni,

I support your point completely. Even if we’d ignore the fact of non-existent “expert” definition, original statement is false. There are people, who prefer to learn first than - to start doing something. I did that before making my first edit (with Potlatch, by the way) and I’m still doing that every time I face some new problem. However, there are people, who prefer doing something first. I’m not judging them while they don’t think that someone else should clean up after them.

@Zverik,

I was pretty sure you will take anything personally, regardless of how detailed it was explained, therefore I will not even bother saying you got it wrong again. (You doing it this way pretty often even if it’s not about you or your work.) Just try to abstain from replying on things nobody said or suggested, otherwise it’s quite immature and makes zero sense.

To all:

In this diary entry, I’m using Maps.me as an example (currently - the first and only one) of similarity between imports and certain style of editing data. If someone can’t see this similarity after my explanation, I can try explaining it further, just ask, if you are interested.

@marczoutendijk,

Thank you for your comment. Your observations are consistent with complains of other people, who tried to interact with maps.me users. Saying that nothing bad happens is either ignorant or it’s just an expression of pollyannaism.

@alexkamp,

Thank you for correction - English is obviously not my first language, and I appreciate it, when someone helps me to improve it. Unlike you, in case of OSM rules.

@alexkemp,

It seems like you accept only those rules, conventions and advises you personally like. Okay, got it, will save my time in other cases.

Unfortunately, current tagging seems to be partially messed up.

• To describe it as a flood lagoon (AKA “detention pond” or “dry basin”), not just some general small reservoir, https://wiki.openstreetmap.org/wiki/Tag:basin=detention should be added.
• phone= key must have phone number indicated in international format (there is also newer scheme for it).
• operator=, https://wiki.openstreetmap.org/wiki/Tag:landuse=basin, https://wiki.openstreetmap.org/wiki/Tag:basin=detention and ref= tags together with history of this way making current description= obviously redundant and unnecessary.
• name= in this case is also questionable: “flood lagoon 5805” is not it’s proper name (like if it were “Foxhill flood lagoon”, for example). It should not be used to make it searchable by specific search engine or software, or to display it on Standard or any other map style. If anyone wants to search for detention all basins (by it’s function, indicated with proper tagging, not by name) or to find a basin with specific reference number, one might want to use Overpass Turbo query (it has quite functional query wizard, so you don’t have to be a programmer to use it).

Boundary contour is a kind of questionable too: basin itself doesn’t occupy the whole fenced territory and deserves own contour, showing its true area. Fenced territory could be properly indicated by separate contour with barrier= tag.

Pretty much space for improvement of small flood lagoon, right?

@joost schouppe,

No, situation with Maps.me is different from one with iD, because Maps.me provides a tool, way more isolated from OSM community.

First, Maps.me users not necessarily receiving private messages and changeset comments, since some of them could use one-time emails they never check after completing the registration (in case of iD, you will always see message notification, if you’ll get back to osm.org).

Second, the whole UX concept is different: Maps.me isn’t an editor, or a part of “something OSM” - it’s a navigation app. That’s why certain people thinking that they adding their own POIs or sending feedback to professional mapping team.

Third, map in Maps.me doesn’t change immediately, it has own (relatively long) update cycle, which is also different.

Fourth, iD provides “full immersion” into map, you can (if you want) see all tags and geometry of other objects. Indeed, you still don’t know much about OSM rules, but you can learn from examples way better. And if empirical evidence works for you, I’ve seen all kinds of mistakes, made by using Potlatch and iD, and majority of them were caused by genuine lack of knowledge (except relations, broken by Potlatch users, where it was provoked by its interface), not by completely wrong idea of what people are doing.

Speaking of demotivating developers - I don’t think anything is demotivating them more than they naturally are, since it doesn’t seem like they are interested in feedback at all (read again that part about GitHub issue tracker and another part about several members of development team already leaving for their own project).

I can’t be responsible for other people (and there are cases in Russian community forum section, where people even used obscene words to express their disappointment caused by those massive wrong edits), but I consider my feedback constructive, since I’m not making emotional general statements, but referring to specific real flaws and mistakes in this situation.