What is the cause for the degradation of environment?
Capitalism, corruption, consuming society? - OVERPOPULATION!
Please, save the Planet - kill yourself...

Tuesday, October 11, 2011

QGIS symbology set

It's been a while since I've updated the status of a notation conventions for QGIS project. Let's fix it! There is a beta-version of the symbology available. See the screen-shots below (all are clickable), and if you like it -  DOWNLOAD the set, use it and provide a feedback!

Fills

How to use:

1. Use QGIS 1.7 or higher.
2. Go to Settings->Style manager.
3. Hit "Import" button.
4. Provide path to the "symbology-ng-style-eng.xml" file in this archive.
5. Pick up needed symbols or choose all of them and hit "Import" button.

Note that there should not be any red circles in symbols after import is complete. If you will see red circles (or do not see some of the symbols despite their names present) it means that paths to some of the SVG icons are broken. You should fix them manually by editing "symbology-ng-style.xml" file LOCATED AT YOUR USRER'S QGIS FOLDER by copying according paths from "symbology-ng-style-eng.xml" file FROM THIS ARCHIVE.

Numbers in the end of the symbol's name is a scale it is designed for (it is for printing purposes). For example "...50_100k" means that this symbol is suitable for printing in 1:50 000 and 1:100 000 scale.

Lines

Lines continue

Points

Wednesday, September 14, 2011

A Study on Illegal Dumpimg Prediction

There is an interesting note about GIS model for illegal dumping occurrence prediction. Researches had an assumption that high accessibility of the site and its low visibility will determine the probability of illegal dumping occurrence. They reported that unfortunately this assumption was wrong and there are no significant influence of these factors on illegal dumping. 

Actually such result is not a surprise for me. Most of the huge dumping sites in St. Petersburg and Leningrad region I'm aware of do not have very high accessibility, I would say that their accessibility is somewhat moderate. Relatively low accessibility affects "visibility" of the dumping sites and I think that these two parameters are correlated. Also it isn't clear if researchers defined the amount of waste that separates illegal dump from just litter. It seems that they haven't used such parameter so their studies could be affected by litter, which can be found almost anywhere.

Sunday, September 4, 2011

No Place for Russia

There is no such country as "Russia" in the witpress registration form))) Romania is absent too... Still I'm happy that Rwanda is not forgotten ;-)


Friday, September 2, 2011

Responsibility of Scientists in Climate Change "Issue"

At the the last week I've spent 5 days amongst Baltic Sea related scientists (there were almost 600 of them) at 8-th Baltic Sea Scientific Congress. The congress was interesting indeed even if I'm not a marine or meteorological scientist. There were a plenty of presentations on climate, winds, curves, salinity modelling, environmental risk assessment and governance (a lot of scientists do have problems with risk assessment). And I had a poster about illegal dumping monitoring.

But I would like to show you the presentation of Hans von Storch about "Knowledge generation vs. decision processes - the issue of regional climate service" which I liked the most. It concerns responsibility of the scientists for the knowledge they provide.  Let me start from the end of the presentation and if you will find yourself interested in further reading - hit the "read more" button. All pictures are clickable.


Friday, August 26, 2011

Illegal Dumping and Cadastre

As a specialist in land monitoring and cadastre I always suspected that uncertainty in legal status of the land parcel may provoke illegal dumping at such parcel. One evidence I collected during the study on implementation of high resolution imagery for monitoring of illegal dumping - illegal landfill occurred on the land parcel with no particular legal status. Today I found another one - illegal dump existed for several years because the land parcel owner wasn't determined.

Friday, August 19, 2011

Relation Between Fires and Distanse to the Nearest Highway


Instead of introduction

Just for fun I decided to investigate relationship between fires intensity in Leningrad region (and St. Petersburg as well) and distance to the nearest road in order to gain the evidence of the major influence of the anthropogenic factor on fire starting.

Materials and methods

Data used:
Software used: QGIS; R.

OSM data about major roads of Leningrad region was used to create a distance map. Distance map and data about locations of the fires detected from 2001 to June 2011 were used as arguments for the R "rhohat" function of "spatstat" package in order to investigate dependence of fires intensity on distance to the nearest highway.
Results and discussion

Firstly lets look at the map of the fires intensity distribution in space below (this map is rough and was created just to demonstrate the situation in general and it wasn't used for the computations described below). Due to usage of the roads at this map will be a hinder for fire data I used railways instead.

Rough fires intensity distribution in Leningrad region


As you can see, fires intensity is [somewhat] related to the location of the railways: note that there are almost no fires at the east side of the map where railways net is sparse (north side of the map is similar, but there is Ladoga Lake located). Ofcourse railways are not the cause for the fires by themselves, but I suppose that in this particular case this can be evidence of the significant human influence on the fire events.

I believe you think that if we want to find clear evidence of the human influence on starting fire than we should investigate density of the population and compare it to the fires intensity. Fair enough, but you may do it by yourself using official data if you want. I will not do it because the results will be flawed. There is an issue with  population - there is no data for the actual population of Leningrad region in summer (late spring and early autumn as well) time - the time of fires. At this time a lot of people from St.Petersburg go to their summer houses in Leningrad region (take into account that the population of St. Petersburg is 5 times higher than a population of Leningrad region) and you have to estimate population of the region accordingly, and it is far not a trivial task.

So we have to investigate not the population density by itself, but the proximity of the areas that were on fire to the population. We will measure the proximity as a distance to the nearest highway. Ofcourse it is better to use all available roads for such research, but if we will do so, R will calculate it for a very long time (there are over 80 000 features in the shp-file) - I've stopped the process after 10 hours of waiting. So I've used only major highways (with "primary", "secondary", "trunk", "tertiary" and "motorway" attributes in OSM) - over 10 000 features.

rhohat{spatstat} function was used to create the following graph:

Dependence of the fires distribution on the distance to the nearest highway
The graph is somewhat weird (and we will talk about it) but it is obvious that intensity of fires have maximum at 2-3 kilometres from the highway and then goes down. So we have the piece of evidence that anthropogenic factor has a major influence on the fire events indeed.

There is an interesting "sinusoid" from 18th to 38th kilometre. Narrow gray stripe demonstrates possible error so I assume that this graph is reliable. I need to explain it somehow. My wife who is better mathematician than I tells that the best explanation is a shitty computation. Well, it is possible. But I have another opinion.

Possible explanations:
  1. Remember that we left more than 70 000 roads outside our calculations for this graph and there are a lot of roads which are not recorded in OSM. I suppose that if we would use almost complete dataset of roads in Leningrad region and more powerful computer than mine we would have more adequate graph where this sinusoid may disappear.
  2. Proximity, estimated here is not only a proximity for "occasional fire starters" but also a proximity for fire fighters. If a fire starts far away from the road it is more difficult to fight it. So this is about fire data and how we treat it for the computation: it is possible that fire events are continuously less frequent as we move away from the highway, but single event produce fire which covers larger area than average due to it is hard to fight it quickly, and this single event produce more "hotspots" (which were used for this mini-research) than average event.
Conclusions

We have got a strong evidence that anthropogenic factor plays a major role as cause for fire in Leningrad region: intensity of fires riches its maximum at distance of 2-3 km away from the road and then goes down.

"Sinusoid" between 18th and 38th kilometres may be caused by insufficiency of the road data used. Calculations should be repeated with more comprehensive data. Also it may be necessary to pre-process fire data in order to replace "hotspots" related to a single fire event with the single point i.e. to make it one point for one fire.

Wednesday, August 10, 2011

R spgrass6 Library Installation in openSUSE: workaround

I've encountered a problem with connecting R and GRASS in openSUSE to multiply their power. "spgrass6" library was unwilling to install properly. Here is a workaround for this issue.

"spgrass6" needs libxml2-dev (can be found here) package for installation (actually this  package is required by "XML" library that needed for "spgrass6") so install it ;-)

If you will try to install "spgrass6" normally (as root), you may receive the message (first two lines of installation logs) that this library will be installed in '/root/R/x86_64-unknown-linux-gnu-library/2.13’ because 'lib' is not defined which means that this library will be available only for root. So you need to perform installation as user and everything will be fine.

Related post: R-commander installation in openSUSE