Given a particular zoom level, how accurate is the scale provided by the satellite view in google maps?
Can one use it to ~accurately determine the square footage of a given building in the picture?
Thanks.
The imagery is very accurate, and at the finest zoom levels (19 or 20), you will be able to perform area calculation with great precision. The location information in Google maps would definitely be more accurate than trying to get readings using a handheld GPS device (there are some app out there that let you walk around a perimeter setting waypoints, and then calculating the internal area based on those waypoints).
Here is a relatively painless utility that demonstrates this:
http://www.daftlogic.com/projects-google-maps-area-calculator-tool.htm
One issue if you are trying to calculate square footage using the imagery however would be determining the number of stories.
Not sure about the accuracy. At the 200 ft. zoom level I superimposed the scale over Rice Stadium in Houston and it shows the playing field as a little over 200 ft. long and 50 meters wide. That means the width is about right but the length is way off since the standard football field is 300 ft. long. Probably has something to do with the angle of the photo. If the satellite is directly overhead it's probably more accurate. Just a thought.
the graphic scale is not consistent as you zoom in and out.
I placed two zoom images into a CAD program and sized the images by measuring the graphic scale. I got two different sized maps.
Related
I wanted to see if it was possible to plot WNBA shot charts using bigquery GIS. I saw a lot of articles about bigquery gis for latitude/longtitude data and one post about doing it with images, but was confused and not sure if it's the right use case for BQGIS.
I have the court dimensions and the shots taken this season from the wnba's stats site. If possible I would love to see what zones different shots were taken in and be able to plot out the whole court and then also "zones" within the court so for any point I could check what "zone" it's in (i.e. low post, right wing, etc.). I have the points in half court form so would only be plotting half a court.
I've transposed the points to feet so they all fall within the boundaries of the halfcourt. The rectangle dimensions of the half court are (0, 0) [Lower left corner], (50, 0) Lower Right corner, (0, 47) [Upper left corner], (50, 47) [Upper right corner]
The arc for the three point line is a little more complicated, but i have that as well as well as the other zone dimensions.
You can use it this way, although it might be not the best way to use BigQuery GIS.
Seems like you map court position to coordinates. This is fine for GIS systems working with planar geometries. BQ GIS would interpret them as lat/lon, on a sphere, and with ranges up to 50 degrees this would introduce spherical distortion. While usually BQ GIS provides more precise answer thanks to spherical geography, you'll get less precise one.
If you do go this route, I suggest using smaller ranges, e.g. scale everything down 100x and use range (0, 0) to (0.5, 0.47) to minimize these distortions, the distortions should be tiny at this scale.
I am using geocoding and maps api to heatmap a lot of entries (12000+) (these will be filtered down to ~5-600 a map) currently using a random 500 dataset from these.
The problem is some of these addresses haven't geocoded correctly (e.g. showing miles away sometimes not on same continent) which is not an issue on it's own (happy for these to be ignored and just be in the oblivion) however these are drastically reducing visibility of map so when zoomed in even with opacity set as high as possible they are a barely visible pinprick on map.
Is there a simple way of just stopping these few erroneous entries from interfering or will I have to weed them out?
Below is sample of how it looks...
Compared to how I'd like it to look (different data set created created previously in fusion tables)...
(these are same zoom levels on google maps, top one just cropped more to show how difference)
For anyone else who come across this...
maxIntensity: The maximum intensity of the heatmap. By default, heatmap colors are dynamically scaled according to the greatest concentration of points at any particular pixel on the map. This property allows you to specify a fixed maximum. Setting the maximum intensity can be helpful when your dataset contains a few outliers with an unusually high intensity.
I found setting this on a sliding scale was best to dynamically adjust map depending on amount of data points in map.
When GPS positioning is unavailable (or even when it is available sometimes), Google Maps for mobile shows a blue circle of uncertainty around the blue self-localization dot. What exactly (statistically) does this blue circle represent?
Is it the 95% confidence interval? Since it does change in size, I am assuming it is some representation of accuracy. Is it just a rough guideline or are there are some actual numbers going in to an accuracy calculation which is then represented visually?
We define accuracy as the radius of 68% confidence. You may get your current location via getLastLocation position.
I'm working on the following scenario: I have a geographical location and I need to create a heat-map visualization of travel times (by car) from that location to anywhere around. I'm planning on using Google Distance Matrix API for getting travel duration. But, since it has a limit on the no of API calls, I need to somehow limit the calls.
My plan, so far, is the following: compute the travel duration (basically a numeric value) to a set of points evenly distributed on a grid around the given position (e.g. 0.5km east, 0.5 km east-0.5km north, 0.5 km east-1 km north etc.). This points would represent the centers of square-shaped areas and I will consider the travel duration to the center as the travel duration to anywhere in the area. Display these areas as colored squares on a Google Maps in a heatmap style.
A good example of something that looks alike is this: http://project.wnyc.org/transit-time/#40.72280,-73.95464,12,709 .
So, my questions are:
Does it seem like a good strategy?
Is there a better visualisation strategy for something like this?
How can I create those square-shaped colored areas on Google Maps?
Thanks!
Calculating duration would surely involve traffic flow rather than simply distance. If your calculations are purely on distance you could use the Google Maps direction requests to calculate the distance to each point.
I'm not sure a heat map is the way forward for this scenario.
There a number of way you could achieve this. Here's a few:
a. Use a custom overlay
(https://developers.google.com/maps/documentation/javascript/examples/overlay-simple)
b. Draw polygons on the map and give them different colours based on
the journey duration. This would involve taking the area in question and slicing it up in to polygons however you need to. These polygons could take the same shape as your example. You would need to be rather precise with your latlng. SQL's spacial querys would help you here depending on the tech your using. (https://developers.google.com/maps/documentation/javascript/examples/polygon-arrays)
c. Depending on how specific you wanted to be you could draw circles with different radius value and different colours.
d. You could make custom markers in the shapes you require and add them to the map in the correct latlng in order to fill an area. You could have different markers for different duration and add them accordingly.
I'm sure there are other options as well.
I would like to draw a map of current temperatures (or air pressures, etc.) from many weather stations, with the underlying map still recognizable. the problem is easiest to think of as follows:
I have an array of spot measurements from irregularly spaced dots---think triples of GPS coordinates with one temperature value each. my stations can be very close to or very far apart from one another, and a user may want to zoom in or out. cold should be blue, warm should be red. Ideally, I would like to just pass the array, the color range, and have the rest be taken care of. I would prefer everything to be inside a web browser. The user needs to be able to zoom in, zoom out, move around, and get back to his current location.
I do not even know how to think about this problem. If a user has zoomed out enough, non-transparent dots could be so close as to obscure the terrain. However, zooming in, it would be nice to recognize the dot that is the station itself. This presumably requires some intelligence that realizes how many dots there are, e.g., relative to the density of the display? not sure.
I believe google maps charges for many API calls, so I would prefer using an open map and/or open API that can use different underlying maps. It does not have to be fancy. I don't care about directions, etc.---just a map that is recognizable at most zoom settings, with landmark and street names, and my nice temperature station overlay coloring, so that a user can visualize where it is cold and where it is warm.
(Stations come online and offline, but I don't need to update this more than once an hour. I can place the map measurements into a file that is URL web-accessible.)
is this an easy or a hard problem for the high-level web programmer?
/iaw
after looking around for a long time, I think the best way to do this is with html5 openlayers nexrad.
alas, the docs seem to be a mess. half the examples that I found did not seem to work. it's pretty hit-or-miss. similarly, the openlayers cookbook also seems to be outdated and has incorrect examples, but they did have a reasonably short example of such a nexrad map overlaid on the U.S., that one can further study.