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37

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 ...


29

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 ...


17

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.


16

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 ...


15

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 ...


14

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 ...


11

IMAGE REVERSE SEARCH WITH GOOGLE IMAGES Doing a reverse search using images.google.com I found this link from wikimedia commons: https://commons.wikimedia.org/wiki/File:M%C3%BCnchen_Geiselgasteig_Filmstadt_Aerial.jpg Which states it is a File called "München Geiselgasteig Filmstadt Aerial.jpg" Which was posted a few later than you question (2012) by http:/...


11

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 ...


11

How about firing up an EC2 or rackspace instance and installing the EarthExplorer bulk download application: http://earthexplorer.usgs.gov/bulk/ You could hit the EarthExplorer service with a POST request to submit jobs programmatically: http://earthexplorer.usgs.gov/subscription/submit/ You would need to provide standingRequestName, frequency, ...


11

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 ...


10

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 right-click ...


9

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 DigitalGlobe Coverage. SPOT: from 2010 - series of orange rectangles, possible to click on the icon, you see the relevant information of your scene ...


8

I was able to georeference an xglobe image using gdal_translate gdal_translate -a_srs WGS84 -a_ullr -180 +90 +180 -90 xglobe-2400.jpg xglobe-2400.tiff


8

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\...


8

If you want only the extent of one image and not the full directory you can go to Vector->Research Tool->Polygon from layer extent here select the image you want the extent and save the output.


8

You can use r.patch for that (see help file) You probably want to set the region first to encompass all raster layers, after which you can use r.patch to 'mosaic' the layers. The following example is from the helpfile: export MAPS=`g.mlist type=rast sep=, pat="map_*"` g.region rast=$MAPS -p r.patch in=$MAPS out=mosaic Use the keyword export when you are ...


8

You can do this with the Identify tool, just use it to click the World Imagery layer and it will tell you a few things about the imagery, including the date it was collected:


8

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 ...


8

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 ...


8

The Rasterio Plotting documentation describes how to visualize multiband imagery. For example, using 4-band NAIP imagery: import rasterio from rasterio.plot import show src = rasterio.open("path/to/your/image/m_3511642_sw_11_1_20140704.tif") show(src) To visualize specific band combination use the following approach (source). In this case, I am creating a ...


7

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 ...


7

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).


7

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


7

Atmospheric correction is particularly usefull if you need consistency between dates and/or adjacent tiles. Some studies showed that the use of atmospherically corrected images improve the subsequent use of the data. In addition, L2A images also contain flags for unusable data (e.g. clouds, snow...). The drawback is that the flags may contain some errors and ...


6

The effects you are seeing are atmospheric effects due to differences in atmospheric aerosols, sun angle, and Rayleigh scattering. Since you have two scenes of the same location, though at different time periods, I would recommend using a technique called Dark Object Subtraction (DOS) (Song et al. 2001). From the ENVI web site: Dark object subtraction ...


6

The US Naval Research Laboratory has developed the "Special Sensor Ultraviolet Spectrographic Imager" (SSUSI). Versions of it have been aboard DMSP satellites since 2003, improving in accuracy. It records in the extreme ultraviolet and far ultraviolet spectral ranges. The most recent numbers I could find (from 2011) said it has 7km resolution and records ...


6

A simple workaround is to bind the imageOverlay to a draggable Polygon (thanks to w8r for this idea, developer of Leaflet.Path.Drag) var poly1 = [ [40.71222, -74.22655], [40.77394, -74.22655], [40.77394, -74.12544], [40.71222, -74.12544] ]; var pg = new L.Polygon([poly1],{ draggable: true, opacity: 0, fillOpacity: 0 ...


6

Below is a simple example (rasterio 1.0.0 or later, won't work in 0.3.6). There might be better/simpler ways (and there is an easier way if your raster is internally tiled and the tile block sizes match your desired output tile size). The rasterio docs have some examples of concurrent processing if you want to go down that road. import os from itertools ...


5

The short answer is you can't produce a clipped sid image in ArcGIS 10, the format is proprietary. But you should be able to produce a clipped jpeg 2000 (jp2) which is similar. A typical sid compression is 20 to 1. In ArcGIS to get the equivalent compression on a jp2 you would use 5 in the Environment - Raster Storage form compression quality box. (That ...


5

I am the author of the R package gapfill, which is a flexible tool to predict missing values in spatio-temporal remote sensing data sets. https://CRAN.R-project.org/package=gapfill It could be helpful in your case. For an overview of published methods to predict missing values in remote sensing data sets see Table 1 of the corresponding publication https://...


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