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6

Think of the geometry. The incidence angle refers to the angle from nadir, or directly beneath the satellite, which would be 0°. As the sensor looks out to the sides from this nadir, the angle of incidence increases as does the fov (field of view). This is why the resolution decreases with increase in incidence angle. This illustration from the Sentinel ...


3

It depends upon the intended use of the Landsat data. Generally speaking, if you are doing multi-temporal analyses, you need atmospherically corrected data, otherwise DN format is sufficient. I would recommend reading the following landmark paper on the subject: Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001). ...


3

Reading the images works with the gdal palsar driver and therefore also in Python. You have to make sure to point gdal to the VOL file so it works. >>> palsar = gdal.Open("D:\Downloads\psr_fbs15\PSR_FBS15\VOL-ALPSRP150170690-H1.5_UA") >>> pal_arr = palsar.ReadAsArray() >>> type(pal_arr) <type 'numpy.ndarray'> Saving in ...


2

The look direction of the C-SAR instrument is right. The resolution as well as the pixel spacing depends on the product and the acquisition mode. They can range from 1.7m x 4.3 for Level 1 SLC SM to 52m by 51m for Level 1 GRD WV. ESA provides a list of all resolutions and pixel spacings for Sentinel-1 products.


1

You are probably also getting more backscatter because there is bare rock at the summit instead of vegetation. Vegetation holds moisture, which would absorb microwaves rather than backscattering. Besides, the foreshortening which affects the fore slope increases its intensity (having more backscatter returned into the same cell yield more intensity + Double ...


1

According to NASA, a spectral radiometer is a multispectral sensor. Spectroradiometer—A radiometer that measures the intensity of radiation in multiple wavelength bands (i.e., multispectral). Many times the bands are of high-spectral resolution, designed for remotely sensing specific geophysical parameters Perhaps you're thinking of a spectrometer, ...


1

Depends on satellite, but most of them have one or two sensors with the same angle of view. For example, Landsat 8 has 2 sensors, TIRS (2 bands) and OLI (9 bands). All of bands have the same angle while sensing. Figuratively speaking - you can not sense Africa with 4 OLI bands and at the same time sense Europe with other 5 bands.


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extract pulls raster values out based on an intersection with a vector. That could be helpful if you wanted to sample raster values given something like a points shapefile. In this case, however, you want a to identify the cells based on value, and then get the data directly from the raster. This may need to be modified if performance in reading the data is ...


1

You can use the OpenCV package in Python for image thresholding. This example shows not only how to perform the binary image thresholding, but also the limitations of this method. Here, I use a 1m spatial resolution NAIP image that shows a dirt road surrounded by arid vegetation. You can see that the road is extracted but there is also a significant amount ...


1

I have also had a lot of success using the image classification tools in ArcGIS (http://resources.arcgis.com/en/help/main/10.2/index.html#//00nv00000008000000). The documentation is great and the results have been very accurate. Unsupervised classification is tricky because defining the number of classes will always result in some degree of mixing. Even ...


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I am a damage prevention specialist, and I use the receiver and transmitter equipment to locate all buried utilities. I went thru a small village 2 years ago and located all residential water services because these are private and not marked out when 811 is called. To map for the village, I utilized a Trimble Geo to create a map file for them for all future ...



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