Altimeters use barometric pressure to measure altitude or elevation. Your watch likely uses a Baro-Altimeter. The problem with that is that the barometric pressure also changes with the weather. As the barometric pressure goes down your altimeter watch will think you are going up in altitude even though you are solidly on the ground.
For such watch ...
Imagine several satellites spread out evenly above you. Now pick just one satellite. Visualise a sphere centered around that satellite with a radius of your exact distance from it. Do the same for every satellite in view.
What you're seeing now is a bunch of spheres that intersect exactly where you're standing. That's how a GPS reading works, essentially....
0 altitude in Bangladesh is likely not exactly the same then 0 altitude in Sweden even when you define both being equivalent to the sea level. This is because sea level is not the same every where. It is rather complex. As explanation I show what wikipedia says about Vertical datum:
A vertical datum is used for measuring the elevations of points on the
There could be a number of problems in play here depending on where you are, what the terrain is like, and what the capabilities of your device are?
If your device uses pressure sensors they may not be physically able to provide accurate altitude readings. Certainly, in a device using typical consumer-grade chips, and sensors, they may not be sensitive ...
See, the elevation (altitude) is the distance between the surface of the datum and the certain point. The datum - is the mathematical model of the Earth shape. You can assume its shape as if the still sea that was extended under continents. So given the same datum the same values of elevation will be equal to each other no matter where ...
Map resolution is in no way related to the altitude, ESRI defines resolution as
The detail with which a map depicts the location and shape of geographic features. The larger the map scale, the higher the possible resolution. As scale decreases, resolution diminishes and feature boundaries must be smoothed, simplified, or not shown at all; for example, ...
The geoidal separation just reports the height difference between the ellipsoidal surface and the geoid model's surface. Natively, GNSS calculates ellipsoidal height (height above ellipsoid surface) but it's usually more useful to have a geoidal height, approximately a height above mean sea level.
The geoidal height is often called an altitude or elevation.
For the purpose of measuring the height of objects on land, the usual
datum used is mean sea level (MSL). This is a tidal datum which is
described as the arithmetic mean of the hourly water elevation taken
over a specific 19 years cycle. This definition averages out tidal
highs and lows (caused by the gravitational effects of the ...
For me; in the beginning TCX worked perfectly but suddenly the same thing happend to me so i tried this; after saving your .kml file from google earth, go to http://www.gpsvisualizer.com/elevation and load the file there. Click "Convert and Add Elevation," and output as a .gpx file. Download the link that it gives you and import that into TCX Converter. Do ...
if gdal can help you, you can check out my answer here. beside this there are some python codes in here. you can convert it to c++..
With gdallocationinfo, we can query the elevation at one point :
$ gdallocationinfo gmted/all075.vrt -geoloc 2 49 Report: Location: (87360P,19679L) Band 1: gmted/30N000E_20101117_gmted_bln075.vrt Value:
i hope it ...
More answers can be found here:
I recommend you to read this article.
Height can be measured in two ways. The GPS uses height (h) above the
reference ellipsoid that approximates the earth's surface. The
traditional, orthometric height (H) is the height above an imaginary
surface called the geoid, which is determined by the earth's gravity
and approximated by MSL.
This is simply not doable in WebGLEarth (with its current API as of early 2019). As noted in the project webpages, WebGLEarth is a wrapper which simplifyes the CesiumJS API in order to create something that looks like the Leaflet API. One of those simplifications is the height of markers.
For this particular task, I'd suggest using the CesiumJS API directly,...
I think there is a problem with the way you are thinking about the whole thing.
To sum up:
You use Cesium points which are from a Digital Elevation Model. Those points are expressed in WGS84 and the height representation is ellipsoidal height
GPS gives you height which is ellipsoidal height
You have geoid height from the EGM2008 model
So when you ...
There is no difference in the rate of change of altitudes with respect to planimetric coordinates. Satellite navigators calculate their position in a geocentric Cartesian system. At the equator, at longitude 0º, the altitudes can correspond to the X axis, at longitude 90º they can correspond to the Y axis, at the poles with the Z axis. And for all ...
As an engineer having worked with GPS satellites, I can give you an explanation- it has to do with how many GPS satellites you are receiving signals from for your readings. There are 24 working satellites in the present Global Positional System and depending upon your location (inside a building, under trees, between tall buildings, etc. you will pick ...
With libtiff you can't get altitude from you file. I spent a lot of time trying to do it with libgeotiff.
My advice is to install GDAL.
GDALRasterIO( hBand_ , GF_Read , p, l, 1, 1, &pafScanline, 1, 1, GDT_Float32, 0, 0 );
From my understanding the current version of QGIS does not have 3D capabilities. You would have do, as you stated, 3D work in PostGIS or Spatialite. There may be a method to do the 3D functions you are inquiring about in Grass, which has a QGIS plugin.
Drone companies typically solve this issue by using structure from motion (SFM) software, made available by commercial programs like Pix4D and Agisoft, and open source software like VisualSFM. These software programs create point clouds, orthoimages, DEMs, etc., similar to those created using LiDAR, but with SFM instead. With an RTK mounted on your platform, ...
You can't. That is a derived "hillshade" product and does not contain any elevation values. From the link you provided:
Pixels do not contain any of the original explicit elevation information.
You need to download the raw elevation values.
My two cents from the conversation following the previous answer: from what @Thiatt explains, he wants to define resolution as the apparent size of a pixel, viewed from an altitude A (which is actually a good definition). So, this is a simple trigonometry problem.
First, you have to set an "angular swath" (or "field of view", I don't know the english ...
This is likely the difference between the ellipsoid surface and the geoid / gravity-related vertical coordinate system in the area. I used Charles Karney's online geoid calculator to check a point in Pristina. The geoid undulation is about 45.7 m there.
QGIS use an WMS OGC standard called GetFeatureInfo to get feature info values from the WMS. If you in a newer QGIS turn on the Debugging/Development Tools Panel and start logging you can see the request sent to the WMS server. If you copy the GET URL and run it in a browser you will download a QML file with the info as GML. You cannot get the entire map only ...
The process you're describing is called point sampling, and there's a QGIS plugin called Point Sampling Tool which you can download from the plugin manager.
Make sure that the point layer and the raster have the same CRS
Just use as.data.frame() from raster package (obviously, before you need to load your shapefile with readOGR() or shapefile(), from rgdal
Here an example
# Reproducible example
pts = cbind(1:5, 1:5)
dimnames(pts)[] = letters[1:5]
df = data.frame(a = 1:5,b = 2:6, c=3:7, d= letters[1:5])
row.names(df) = letters[5:1]
The first step is save your layer alt_pts to a Comma Separeted Value format file. To do this, just do right click over your layer and Save as. Give the file destination folder and name of the file and in Layer options specify AS_XY in the GEOMETRY box.
# Load data
df <- read.csv("/path/to/alt_pts.csv", header = TRUE)
# Print first six ...