When in doubt follow Paul Ramsey's GeoTiff compression for dummies strategy.
-co COMPRESS=JPEG \
-co PHOTOMETRIC=YCBCR \
-co TILED=YES \
and if you need overviews too then add
--config COMPRESS_OVERVIEW JPEG \
--config PHOTOMETRIC_OVERVIEW YCBCR \
--config INTERLEAVE_OVERVIEW PIXEL \
It looks like different images to me... On the right side, there is much less green a much more "something" that looks like water. I think that image was acquired with different conditions (during floods?) Images from same sensor can substantially differ in quality, based on weather, time of day, angle of camera and so on... As another one sugestet, try to ...
You need to know four sets of information in order to precisely locate a pixel from the image to the ground.
1) The position of the camera (three coordinates : X,Y,Z)
2) The angle of view of the camera (three angles: omega, phi, kappa)
3) The distance between the camera and the soil (or the scale of the picture)
4) the geometry of the camera (e.g. the ...
LandViewer contains full collections of medium-resolution imagery dating back to 80’s.
Sentinel-1 - archive since 2014
Sentinel-2 - archive since 2015
Landsat 4 - archive 1982-1993
Landsat 5 - archive 1984-2013
Landsat 7 - archive since 1999
Landsat 8 - archive since 2013
MODIS - archive since 2012
You mark the location and it shows you all available ...
Unfortunately, there’s no such thing as live satellite imagery yet. Space agencies and commercial imaging companies are trying to reduce interval between image acquisition and delivery, but the most frequently updated imagery in free public use is still the one from weather satellites. You may choose to buy commercial images from DigitalGlobe, Airbus, ...
As commented by @scai:
There are already several other aerial imagery providers apart from
Google. And there is OpenAerialMap.
OpenAerialMap is for:
The open collection of aerial imagery.
OpenAerialMap is an open service to provide access to a commons of
openly licensed imagery and map layer services. Download or contribute
imagery to the ...
If you want compare values in 2 raster files, I recommend to use raster calculator in QGIS.
Load 2 rasters to QGIS
Raster -> Raster calculator
write "B4@1" - "B5@1" in Raster calculator expression area.
give any name for output layer
The above steps gives you a raster that values are differences of 2 rasters.
To obtain values of that raster at ...
Basically, what you need is to compute the RMS of the positionning error. This type of analysis requires a manual input of points that you should place on your satellite image where you SEE that it should be according to the location on the ground where you took the measurement. So the procedure in ArcGIS would be :
1) create a point feature class
2) In an ...
This index has a slope correction so is not bound to a theoretical -1 to 1 range. Just for reference, here is the pseudo-code for the MSAVI2 that does not require the estimation of L. You may want to either check it against your code or, if using a software function, manually derive the index to see if it makes a difference.
msavi2 = (2 * nir + 1 - sqrt( (...
I don't know for google map but if you use Google Earth (desktop version) the altitude is in the bottom right corner. As the space station altitude is a little more than 400km (or 250 miles) you could try to zoom to the right altitude and have the same view as the astronauts
I'd take a lookt at Planet. They offer three different resolutions (1, 3 and 5m). You can get a free-trial and check if it fits your needs.
For the costs, maybe check this conference paper that does a benchmark of different satellites or this pricing information for reference.
I think you have the gist of it. From Iain H. Woodhouse's text "Introduction to Microwave Remote Sensing" (a great resource on SAR and RADAR):
For convenience, in remote sensing the horizontal axis, x, is defined to be parallel to the surface of the Earth when we are taking oblique (off-nadir) measurements. The vertical axis, y, is then defined as being ...
I can only answer the first question about the GEOS projection.
The GEOS projection displays the earth as a geostationary satellite would see it (this is where its name comes from). Geostationary satellites orbit the Earth with an orbital period that is the same as the Earth's rotational period. To be able to do that, they are placed directly above the ...
There are several methods for transferring attributes from one layer to another. However, they all depend on the two layers having something in common. Given that your data does not share attributes or geometry, there will be a degree of error in every method. You will have to manually fix these errors.
Try each of these methods. Combine the best results ...
Looks like the most effective way to work with Jason data is via this application: http://www.altimetry.info/toolbox/ It provides a means to process and visualize altimetry data from a variety of different sources.
QGIS is applying a contrast stretch.
A simple 2-98% stretch can be accomplished like this:
import numpy as np
def bytescale(data, in_min, in_max):
data = np.clip(data, in_min, in_max)
data = (data - float(in_min)) / float(in_max - in_min)
return np.array(data * 255, dtype=np.uint8)
in_min, in_max = np.percentile(data , (2,98)) # Where data =...
Raw satellite imagery is by no means spatially accurate, so a lot of work is being done to georeference the imagery correctly.
Let us start with a smaller example - the aerial imagery business, which is similar to satellites, but somewhat closer to the ground. In order to get aerial imagery to "be in the right location", a series of 'ground control points' (...
First of all, I would remove all locations where there is some vegetation, because NIR and Red are strongly linked with the vegetation, so they cannot be used for direct soil characterisation if there is a vegetation cover. For a quick and dirty first "non vegetation" map, you could use NDVI < 0.1.
Then, it depends on how much "expert knowledge" you ...
This question is vague, so there are too many answers.
The first question is online or offline, i guess you want to capture google satellite or bing maps or else online, the easiest way programmatically is using WMTS service.
I'm guessing you already know the bounding box of your desired screen which is going to show the images, you can convert this bounding ...
Have you tried Sentinel Playground or EO Browser?
Playground allows users to "fool around” with global archive of Sentinel-2 and Landsat-8, while eo-browser will give you even more datasets and some nice features (like creating time-lapses, possibility to download your area-of-interest, etc.) if you sign up for free account.
First of all, the Copernicus website is adequate, but not really user friendly - in my opinion. Sometimes you need a bit determiniation in order to get your desired images, especially when downloads fail. On the other hand the data is free.
First step when trying to download data: log into the website. Otherwise your search results will be gone and you have ...
In this case the most likely difference is related to year/date of the capture and the ground sample data (GSD) e.g. 6in vs 9in etc...
Also, other factor can be involved, sun angle on the day of capture, type of camera and specifications. Processing etc...
DigitalGlobe is the name of a private company that navigates several Earth observation satellites (listed here). It is difficult to find out the actual satellite that took the picture, but the spatial resolution should provide a good hint.
Besides the obvious difference in dates of acquisition (change), there could also be a difference between the sensor ...
Also, a SAR instrument needs a lot of electricity since it is an active sensor and therefore a sun-synchronous orbit keeps the instrument's solar panels well illuminated, therefore allow plenty of electricity for the instrument.