16

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 ...


14

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

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 = ...


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

It is possible that there is something wrong with resolution and tolerance in PGDB. Take a look at sections X,y resolution and X,y tolerance in this topic. Try increasing these values. What coordinate system are you using? What values are set for resolution and tolerance?


9

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

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 ...


9

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') { ...


8

You can download Census Blocks from TIGER; you'll just have to download the data on a state-by-state basis and merge it all together. EDIT: See this page for block-level shapefiles that already have the population and housing unit counts attached, so you don't have to deal with joining SF1 tables!


8

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 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

GDAL 1.10 added a few resampling methods which will help, see gdalwarp. In particular, the -r average method, documented as: average resampling, computes the 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 coarse_average.tif Then to ...


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: 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 ...


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

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

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

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 ...


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

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.


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

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.


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

PROJCS details the coordinate system, the first line is: PROJCS["WGS 84 / UTM zone 32N", and then it says: UNIT["metre",1, which means that these numbers: Origin = (357377.652999999991152,5610076.298999999649823) Pixel Size = (0.004545650000000,-0.004545649999975) are in metres. So that's a 4.5mm x 4.5mm pixel size, which is what we would call the ...


5

You are probably generating your hillshade from a surface model that is referencing a geographic coordinate reference system like WGS84. Re-project your data into a Cartesian coordinate reference system (like UTM) and then recreate your hillshade.


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