# Tag Info

20

This question is similar to: Clip raster by raster with data extraction and resolution change, but coming from a different angle. However, I think the answer is likely the same. First off, choose which raster you wish to be definitive. I'll repeat my previous answer here for ease: Load required libraries: library(raster) library(rgdal) Read rasters: r1 = ...

18

Actually it's not all that situation dependent and is all about statistical error. Any time you resample to a higher resolution, you are introducing false accuracy. Consider a set of data measured in feet at whole numbers only. Any given point may be +/- 0.5 feet from its actual location. If you resample to the nearest tenth, you are now saying any given ...

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 ...

14

Check resample function of raster package. When resample is used with 'bilinear method, the output is the same one than aggregate: if (!skipaggregate) { rres <- res(y) / res(x) resdif <- max(rres) if (resdif > 2) { ag <- pmax(1, floor(rres-1)) if (max(ag) > 1) { if (method == 'bilinear') { ...

10

You can use gSimplify from the rgeos package, and if you add the topologyPreserve=TRUE flag it will preserve the topology. Note that you can still end up with overlapping lines - we need an implementation of this robust D-P algorithm in R: http://www.sciencedirect.com/science/article/pii/S0098300413002380 [that link possibly behind a paywall]

9

Ok, with some initial issues cleared out the task is relatively simple. Scale, prepresented as f.ex 1:50000 means that one unit on the map corresponds to 50.000 units in the real world. For a paper map printed a scale of 1:50000 this means that 1 meter on the map corresponds to 50.000 meters in the real world, or to make it easier: 1 cm on the map ...

9

Question 1 The attached script mosaics a list of rasters into a new raster dataset. Make sure to specify "MINIMUM" if you would like to maintain your 10m resolution raster datasets. Question 2 Bilinear interpolation and cubic convolution are both good choices for resampling continuous data. Nearest neighbor is best for discrete raster datasets. Keep ...

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 ...

9

Depending on the version of GDAL, there are a few different resample options available; see gdalwarp. GDAL 1.10 or later using -r average average resampling, computes the weighted average of all non-NODATA contributing pixels This isn't tested, but should look something like: gdalwarp -t_srs EPSG:4326 -tr 0.5 0.66 -r average fine_one_sq_km.tif ...

9

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 ...

8

I think I can answer it for you. If you look at the precision vs. accuracy image on the link you provided, precision refers to the repeatability of the observation. For example, if I measure the distance from one point to another and it is always vaying only by a very small amount, then I am making measurements at a high precision. But, basically, ...

8

Both clients - QGIS and ArcGIS Desktop/Pro - are rendering the same information - tiles of imagery, basemaps, etc. So really just images at the exact same resolution, so it has nothing to do with the software. As to the source of that imagery, here is a good post here about adding the various services from ESRI, Google, Bing, and OSM to your QGIS sources: ...

7

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). In ...

7

From a cartographic point of view, it is commonly assumed that the human perception of a line position is around 0.3 mm. For a given map scale of 1:20,000 or smaller, the USGS’ NMAS has established that 90% of all the points tested must fall within 1/50 of an inch (0.5 mm) (as measured on the map) to their known positions on the planet (see here). This can ...

7

You can improve the result with this command line: gdal_translate -of GTiff PARAmap1.pdf out1File.tif --config GDAL_PDF_DPI 300 According to http://www.gdal.org/frmt_pdf.html, the default is 150dpi. For higher quality than 300dpi, you have to be very patient ;-) I was able to extract vector data from USGS topo PDFs with ogr2ogr in Convert GeoPDF with ...

7

You can: Load required libraries: library(raster) library(rgdal) Read rasters: r1 = raster("./dir/r1.tif") r2 = raster("./dir/r2.tif") Resample to the finer grid r.new = resample(r1, r2, "bilinear") If required (for masking), set extents to match ex = extent(r1) r2 = crop(r2, ex) Removed unrequired data r.new = mask(r.new, r2)

7

Since the data that you have in WGS 84, this means that the cell size is in degree unit. In order to get the cell size in meter, you need to change the projection of your raster from WGS84 to meter projection such as UTM or any other projections that is meter unit depending of the size of the study area. To change the projection of your raster data in ArcGIS ...

7

there are a lot of ways of achieving this in QGIS as you surmise. One is to use the raster calculator and adjust the rows and columns to suite your new desired resolution (do this via Raster->Raster Calculator and then edit the appropriate values in the dialog box). QGIS uses GDAL under the hood so you can also achieve the same resolutions changes via ...

6

Make sure you're using a 64 bit build of QGIS. The limitation on exported composer sizes/DPI is much higher on a 64 bit build.

6

There is now a solution to using ArcMap with high dpi screens at least on Windows 10. Install the Windows 10 Creators Update then change the settings on the ArcMap executable as shown below.

6

EPSG:4326 does not convert nicely into meters, but you can calculate the lengths of latitude and longitude degrees for example with http://www.csgnetwork.com/degreelenllavcalc.html At 54°N the length of latitude is 111304.96 m and length of longitude is 65575.75 m. Your BBOX is 0.1537 degrees high and 0.1977 degrees wide. HEIGHT = 0.1537 / (1/111304.96) = ...

6

Before creating your slope layer (Slope tool is the right choice) you can use the Resample tool to change the cellsize of your input raster, without changing the rasters extent. It is however important that you change Resampling Technique to Bilinear or Cubic which is the right choice for continuus data.

5

I have written this on Android and it works. Google map tiles are 256 device independent pixels. So this first line calculates a tile size in device dependent pixels. The second calculates the number of tiles at a given zoom level. The third calculates the size of a tile in meters at a given latitude for spherical projection. Then the final line will give ...

5

As @Dave Pitman points out in his answer, that a user, Stu Smith, got the manifest hack to work. I actually got it to work too. Follow the instructions using the link: http://www.danantonielli.com/adobe-app-scaling-on-high-dpi-displays-fix/ Once the manifest.txt file is downloaded, copy it to the QGIS bin folder. In my case: C:\Program Files\QGIS 2.18\...

5

Based on my own understanding: In SAR images resolution and pixel spacing are two different things. Resolution means the maximum ability to distinguish two close scatters. The resolution of one SAR image is usually based on the bandwidth of signal (in Range direction) and the 'synthetic bandwidth' in azimuth direction. Well Pixel spacing is easier, it ...

5

Ground sampling distance is the distance between each measurement at nadir. Pixel size refers to what is delivered when data is purchased. Some (commercial) data providers use a smaller pixel size than the ground sampling distance. This means that the data is interpolated from the measured image grid into the delivered image grid. In the case of RapidEye, ...

5

30m - 45m is a lot of change in a coastline over one year and only very dynamic areas see that kind of change rate. As such, you are correct in your assessment of the impact of imagery resolution on the analysis. However, your assumption about "same time of day, so tides were more or less the same" is not a very good assumption as tides are more variable ...

5

With regards to your question of the difference betwen SRTM and EU-DEM the ESA quotes: The EU-DEM is a hybrid product based on SRTM and ASTER GDEM data fused by a weighted averaging approach and it has been generated as a contiguous dataset divided into 1 degree by 1 degree tiles, corresponding to the SRTM naming convention. As they mention ASTER I and ...

5

This is a bit of an apples and oranges comparison. The Sentinel-1A sensor is an active radar system carrying a C-band synthetic aperture radar array. Whereas, Landsat 8 is a passive spectral system with 16-bit radiometric resolution across 0.43 - 2.29 micrometers (excluding the 100m2 IR bands). The characteristics of the sensors will dictate the feature ...

5

You can use projectRaster() to resample to a new resolution (also extent and CRS): r2resampled <- projectRaster(r2,r1,method = 'ngb') r3resampled <- projectRaster(r3,r1,method = 'bilinear') The first one is categorical, so it's necessary to use nearest neighbor as method (ngb). The second one is numeric, so you can use bilinear (bilinear) or nearest ...

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