Hot answers tagged erdas
10
You can't 'remove' clouds from optical imagery, what you see is what you get; they are photographs and there is no optical data recorded from below the clouds in the same way that there is no data underneath building roofs.
If you use remote sensing data of a longer wavelength than light such as microwave, the water particles in the clouds do not absorb the ...
9
The operative word is Resample, the version link is provided, similar links exist for prior versions of Arcmap. Also be aware of resampling issues associated with the resampling method and the nature of the data being assessed.
EDIT
If you want to go the reverse route (ie decrease resolution) see Aggregate
or Resample but be careful to choose your options ...
7
ArcGIS 10 Animation
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/What_is_an_animation/000900000001000000/
ArcGIS 10 Temporal Data
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/A_quick_tour_of_temporal_data_management_and_visualization/005z00000021000000/
You can record either and export to either image (animated gifs) or ...
5
First of all I should mention that this question is addressing very limited space, though important question too.
The first thing that comes to my mind on this subject that you can consider temporal information in short time interval. if certain values are changed in certain areas, it may be easier to detect snow.
and second solution is here from National ...
5
Do you have access to spatial analyst?
If so, the Con function will do exactly what you want. Create a "condition" raster that is 1 where you want the values changed to Ras2 and 0 everywhere else.
Execute the statements:
Ras1 = Con(Raster("condition"), Raster("Ras2"), Raster("Ras1"))
Ras1.save("Ras1")
This will replace Ras1 with your new raster. If you ...
5
You will need a paid Licence of the ERDAS SDK as the free (gratis) SDK is read-only. As an alternative try the Geotiff format with JPG compression.
For example, using the following two commands (but you have GUIs in QGIS, for example) to convert ECWs to TIFFs you get rasters that are more or less 30% bigger than then ECWs but look the same and are also as ...
5
To begin, you need to know the which spectral bands are which in your base image. The equation to calculate NDVI is as follows:
(near infrared - red)/(near infrared + red)
If you are using Landsat TM or LISS IV imagery, this translates to the following band combinations:
(band 4 - band 3)/(band 4 + band 3)
Luckily Erdas has a handy tool that ...
4
I will have to 2nd @blah238's suggestions of using some other method of data access than creating a single mosaiced image. A simple guess would say there is not a desktop out there that could handle the amount of data you would have to process in order to mosaic all of those tiles.
To break it down, there are probably two places where you are running out of ...
4
I would like to add Block Statistics as another method to alter the resolution of a raster. Depending upon your specific goals, Block Statistics allows fine control of how pixels are assigned based on:
A user defined neighborhood (e.g. rectangle, circle, wedge etc)
The type of statistics calculated within each block (e.g. mean,
majority, variety etc).
...
4
To do this correctly you need to recover the NIR and visible bands (VIS). This is because, by definition, NDVI is the ratio (NIR-VIS):(NIR+VIS).
To analyze the situation, let's use subscripts (1) and (2) to denote the two 16-day values and no subscript for the one-month value. Observe that NIR-VIS = NDVI*(NIR+VIS). Also, because the two time periods have ...
4
The simplest way is to create a new point layer for identifying individual cells which have been misclassified: for each incorrect cell, create a point at that location, and update the attribute table with the corrected value.
Then, rasterize the points to a layer with the same extent and cell size as your input layer, then merge the two with a raster ...
4
Though I am not able to understand the difference between the standard
deviation output and the percentage output and what is the
significance of using one over the other?
Those refer to the threshold used to decide whether there has been any change between two images. For percentage change, it uses a symmetric relative difference formula to
...
3
I set my windows temp variables to a different drive so all temp not just ESRI stuff is redirected ("[winkey]+[pause] > Advanced > Environment Variables'). From there slap [new] to override the user profile temp or [edit] to change the system wide temp.
I don't know if this is still true, but I've encountered some geoprocessing tools which would write to ...
3
If you want to use ENVI, it's straightforward. You can find out how to do it here
Given that your datasets are univariate (NDVI, temperature, pecipitation), you may want to encode them into an RGB composite dataset and plot a single "map" for each timestep.
3
You could reference individual bands in Arcmap 10 by using the full path name and "\Layer_X" where X is the band you want (Eg: "D:\GIS\layerstacks\1993_stack.img\Layer_27"). So if I wanted to save the 27th band from the stacked images, I would write a simple raster calculator statement like
"D:\GIS\layerstacks\1993_stack.img\Layer_27" * 1
and put it in ...
3
From the USGS FAQ: the blue band is useful for "Bathymetric mapping, distinguishing soil from vegetation and deciduous from coniferous vegetation".
It's my experience that you get better results by using band combination, however.
2
You could classifly your NDVI image based on the index pixel values from -1 to 1. Pixels that have a value of less than zero show no reflectance in the NIR band. Values from 0.1-0.2 are usually from soils that reflect in the NIR, and values from 0.3-1 (increasing in vegetation density) are dense vegetation canopy.
Within ArcMap you could use the ...
2
Not using Arc or ENVI, but another option is GDAL. You could also use gdal_translate with the -b option. The command would look something like:
gdal_translate -b 1 input.tif output.tif
Where the '1' is the number of the band you want to extract.
The gdal_translate man page has all the other options you may need.
2
Since each individual photo has such a small footprint, you could use the open source photo-stitching software Hugin to stitch a few tiles together. I have used Hugin (not for aerial photos, but for landscape photography), and it's incredibly good at tiling images. Then you'd have multiple points per scene to georeference on.
2
If you know the image size (pixels) and scale you can work out the top left corner from the centroid. You can use Excel to do the math.
Then create a txt list and create world files for each image.
I would do one manually in ArcGIS.
To georeference one see:
http://library.columbia.edu/indiv/dssc/eds/georef.html
Then you can use the values in Excel to ...
2
You can use GDAL to convert ADF to ECW. The ECW driver is not provided by default in GDAL, you need to compile GDAL and link to the external ECW SDK libraries provided by ERDAS.
2
To start you could use one of the ESRI map service (world imagery) basemap layers to georeference off of. Depending on the date of your aerials you will have to use natural features to georeference to (e.g. forest edges or stream channels).
2
In model builder,
iterating rasters from a workspace,
constructing raster file path and file names
feeding the path into Raster Calculator and extend file names with the desired band ID.
defining an output path
This may help.
2
It has been mentioned in the related question (http://gis.stackexchange.com/questions/19297/how-to-add-raster-legends-in-qgis-map-composer) that QGIS got raster legend support in print composer after version 1.7.
You can install the current developer version from OSGeo4W if you are on Windows.
You'll will have to add the text with highest and lowest ...
2
Firstly: if your map is pixelated, whatever GIS you are using, try setting the paper to a lareger size and upping the DPI (dots per inch). This presupposes you are using vector data and/or the resolution of any raster is suitable for printing at the size you want. I wouldn't recommend using anything less than 300 dpi and I think printers prefer 600 dpi. ...
2
That sounds pretty familiar to me, we also produce large single ECW Files out of 500 too 1TB of TIF Files. But I wouldnt last on ArcGIS (ArcObjects and the Geoprocessing Engine), since it is not able to mosaic this amount in a reliable way. If you want to stay in the ESRI World I would recommend to mosaic chunks of about 50 GB or even smaller at once to a ...
2
550gb of input TIF data is easily handled by a single ECW file. We have many customers compressing much larger datasets than this so please do not think the format is not capable in this area.
Your strategy of splitting the project into small tiles to minimize null area is also a good approach to take with the current format version as it will reduce the ...
2
Most MODIS QA data (including the Cloud Mask data) are not stored as separate raster bands, where each band is a grid where each cell is one value of one QA data field. Instead, the QA data are concatenated into strings of bits. So instead of having Band 1 be 00 and Band 2 be 11, they just concatenated them (right-to-left) as 1100 which is a completely ...
2
You can achieve this using the numpy.argmax() function. Enter the following into the Python console (adjust to taste):
import arcpy
import numpy
# convert the raster to a 3-dimensional numpy array (x, y, band)
values = arcpy.RasterToNumPyArray("ras2")
# calculate the index of the maximum value along the band axis
#(1-based, rather than the default ...
1
Do you mean the outside edge of the combined image, or along the join?
Perhaps the Near Black tool in QGIS would help. Raster->Analysis->Near black.
Or if the colour is not present anywhere else, you can Reclassify that pixel type to NoData or whatever class you want.
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