Panchromatic images are created when the imaging sensor is sensitive to a wide range of wavelengths of light, typically spanning a large part of the visible part of the spectrum. Here is the thing, all imaging sensors need a certain minimum amount of light energy before they can detect a difference in brightness. If the sensor is only sensitive (or is only ...
If you don' want the values above 255 to be cut, you need to scale them down. For that purpose gdal_translate provides the option -scale:
From the Manual:
-scale [src_min src_max [dst_min dst_max]]:
Rescale the input pixels values from the range src_min to src_max to the range dst_min to dst_max. If omitted the output range is 0 to
255. If ...
The resolution of imagery in Google Earth varies depending on the source of the data. When you zoom out, you will see the nice, pretty global coverage produced from a mosaic of many Landsat scenes, which have a native resolution of ~30m (~15m pan-sharpened).
Zooming in, you'll start to get high-resolution in most places. There are many rural areas ...
For images of the same location but different dates, I would rather talk about compositing than mosaicing (which combines images from different extents into a larger image). You will find a lot of details if you search "compositing" keyword, but here is a short summary:
There are two main approaches for the compositing of time series:
Best available pixel ...
Unfortunately I can't view that video from Canada but based on the screen shot I believe something like that could be rendered in Pov-Ray.
A while back I asked a question about how to generate a high resolution rendering of the globe and @scw suggested I try Pov-Ray.
Using this guide I was able to create custom globes with a combination of my own inputs ...
GDAL has a wonderful file format called VRT, which is an XML wrapper around one or more raster files.
One feature of VRTs is their ability to encode square convolution kernels for any given band. It does involve playing around with XML in a text editor (or programatically), but if you're already used to the GDAL tools, it shouldn't be too hard.
In QGIS, you can use Raster Calculator with the following calculation:
("your_raster" != -32768) * "your_raster"
With this calculation, if the cell value is -32768 you will get a 0 in that cell and if it is different from -32768 the cell will keep the value it had.
IMAGE REVERSE SEARCH WITH GOOGLE IMAGES
Doing a reverse search using images.google.com I found this link from wikimedia commons:
Which states it is a File called "München Geiselgasteig Filmstadt Aerial.jpg"
Which was posted a few later than you question (2012) by http:/...
If there was a shadow in the raw image, say from a tree or tall building, it will still be in the image after the rectification process. Essentially, parts the photo are being stretched or warped to match the position of visible objects in the photo to known places on a map; this will correct for the pitch, yaw, and roll of the plane during the flight, and ...
How about firing up an EC2 or rackspace instance and installing the EarthExplorer bulk download application:
You could hit the EarthExplorer service with a POST request to submit jobs programmatically:
You would need to provide standingRequestName, frequency, ...
I saw a blog post from developmentseed for their command line utility landsat-util.
Power tools for Satellite Imagery
The landsat-util can be forked from github and compiled from source unless your OS offers it in a binary ready to go.
The blog describes it simply as:
a command line utility that makes it easy to search, download, and
process Landsat ...
The simplest one-step and, IMO, most consistently reliable solution to reclassifying NoData to zero is to use the Reclassify Grid Values tool (SAGA) in the processing toolbox.
After selecting the raster to be reclassified, simply scroll to the bottom of the dialog, ensure the box replace no data values box is checked. The default value is zero (but you can ...
I found this good discussion at http://www.cartotalk.com/index.php?showtopic=7109 and thought it would be useful to add to GIS.stackexchange for posterity.
in ArcMap 10.2, choose > Windows > Image Analysis
in the top panel, select the input image
in the Processing section, choose the first tool (Clip)
this adds a new temporary raster to the TOC
Maybe is to late to answer the specific question, but I hope that will help someone else:
To identify a platform the historical imagery of Google Earth (GE):
Turn ON Layers -> More -> SPOT Image OR
SPOT: from 2010 - series of orange rectangles, possible to click on the icon, you see the relevant information of your scene
An alias, in signal processing which is what we're dealing with when we are talking about images, is when a signal is sampled at a resolution that makes it impossible to recreate the original signal exactly.
Take this 1-dimensional case:
The original signal is the purple sine wave, and the blue dots are where it has been sampled. The blue line is the ...
I've used Enhanced Vegetation Index (EVI) data extensively for analyzing agricultural areas. Although I've never used it with NAIP imagery, all you need is red, blue, and IR data.
For your purposes, the biggest advantage of EVI is that it does not "saturate" as easily as NDVI--it offers more contrast (dynamic range) when examining highly vegetated areas ...
Glovis is one of the best places to start compiling free satellite imagery. For a new user, LANDSAT imagery is a great place to start - you will be able to find data covering the 1970's to present day. There is also a wealth of information available for working with this data. For example, if you are using ArcGIS you can quickly learn how to develop a ...
Your biggest issue will be that aerial photographs from the 50s may well be in black and white and this doesn't provide good basis for standard classification, such as the tutorial linked by @user3338197
Instead, you will have two paths open for you:
Manual digitization (possibly outsourced)
Object-based image analysis. The professional standard software ...
As others have shown interest for this question I'll answer it using the information I've been able to gather so far:
There might be more than one archive or old Soviet Union imagery. As there were both military and civil missions (in contrast, film-recovery mission were forbidden in the US for non-military proposes).
The archive I know of so far is ...
Having the same problem, in the end I used Python directly -- you may have to adjust numpy.where for your specific purpose. In the case below, the pixel values are kept as they are if they are >= 0, all other pixels -- in this case this is only ones with the no-data value -- are set to "0"
import gdal, gdalconst, numpy
maskfile = gdal.Open('C:\Users\max\...
I find QGis's georeferencer to be pretty decent for a point and click tool. I wrote a little guide - image georeferencing with QGIS - which is slightly Canadian data-source specific, but walks through all the steps you need to get an arbitrary map into QGis.
There are a number of places where footprints can come in very handy
Taxation: As @Mapperz said, taxation is one area. The percentage of
property that is built on is sometimes used as a tax criterion.
Planning: Knowing where structures already exist on property can
help in the planning process due to applied setbacks and minimum
There are published coefficients available for MSS, TM5 ETM+7, QuickBird and IKONOS but I do not believe that anybody has derived coefficients for Rapid Eye. Here is a paper that describes how the authors derived the coefficients for Quickbird (http://www.asprs.org/a/publications/proceedings/pecora16/Yarbrough_L.pdf).
All of the specific answers I can come up with would have likely already occurred to you as a photographer. A low distortion lens with a shorter focal length (based on your prospective altitude). High shutter speed to minimize motion/vibration impacts. Interval and speed are something of a function of your flight plan and altitude - I don't know if there ...
you can find the H and V index in all MODIS product file name. These indices refer to the grid below (from the MODIS Website). For instance you have H8V6 (MOD17A3.A2000001.h08v06.055.2011276103801.hdf).
According to https://www.digitalglobe.com/sites/default/files/ISD_External.pdf you should have a field called satellite with a mnemonic like:
“QB02”, “WV01”, “WV02”, “WV03”, “GE01”, “Aerial”
Which I assume correspond to the satellites operated by DigitalGlobe:
QuickBird, WorldView 1/2/3, GeoEye-1, IKONOS
if you are interested with RS - Remote Sensing, you can check out Orfeo Toolbox here. following information from their site:
a set of algorithmic components, adapted to large remote sensing
images, which allow to capitalize the methodological know how, and
therefore use an incremental approach to benefit from the results of
the methodological ...