I am working with raster data (aerial images) in JPEG2000 using ArcGIS Pro 2.9.
Is there a way in ArcGIS Pro (or using arcpy) how to find out resolution of each pyramid level? And in what scale is certain level displayed? I would like to have a table with pyramid levels, resolution for each level and scale, where the level starts and ends displaying.
Thank you.
AC
Related
Below is a JavaScript page I have created that allows me add and freely move markers on the map. From this map I can figure out the regions I am interested in.
Basically what I want to do is show the same map using ggplot2/MarMap with coastline indicators + bathymetry data. I am really just interested in getting bathymetry data per GPS location, basically getting negative/positive elevation per Lat+Long, so I was thinking if I can plot it then I should be able to export data to a Database. I am also interested in coastline data, so I want to know how close I am (Lat/Long) to coastline, so with plot data I was also going to augment in DB.
Here is the R script that I am using:
library(marmap);
library(ggplot2);
a_lon1 = -79.89836596313478;
a_lon2 = -79.97179329675288;
a_lat1 = 32.76506070891712;
a_lat2 = 32.803624214389615;
dat <- getNOAA.bathy(a_lon1,a_lon2,a_lat1,a_lat2, keep=FALSE);
autoplot(dat, geom=c("r", "c"), colour="white", size=0.1) + scale_fill_etopo();
Here is the output of above R script:
Questions:
Why do both images not match?
In google-maps I am using zoom value 13. How does that translate in ggplot2/MarMap?
Is it possible to zoom in ggplot2/MarMap into a (Lat/Long)-(Lat/Long) region?
Is it possible to plot what I am asking for?
I don't know how you got this result. When I use your script, I get an error since the area your are trying to fetch from the ETOPO1 database using getNOAA.bathy() is too small. However, adding resolution=1 (this gives the highest possible resolution for the ETOPO1 database), here is what I get:
To answer your questions:
Why do both images not match?
Probably because getNOAA.bathy() returned an error and the object dat you're using has been created before, using another set of coordinates
In google-maps I am using zoom value 13. How does that translate in ggplot2/MarMap?
I have no clue!
Is it possible to zoom in ggplot2/MarMap into a (Lat/Long)-(Lat/Long) region?
I urge you to take a look at section 4 of the marmap-DataAnalysis vignette. This section is dedicated to working with big files. You will find there that you can zoom in any area of a bathy object by using (for instance) the subsetBathy() function that will allow you to click on a map to define the desired area
Is it possible to plot what I am asking for? Yes, but it would be much easier to use base graphics and not ggplot2. Once again, you should read the package vignettes.
Finally, regarding the coastline data, you can use the dist2isobath() function to compute the distance between any gps point and any isobath, including the coastline. Guess where you can learn more about this function and how to use it...
I am trying to create a species distribution model in R. I have created raster layers in ArcMap and have imported them into R. They cannot be stacked unless the extents are exactly the same and they all have the same number of rows and columns.
However, when I alter these factors to successfully stack them they lose all their values and my stacked data frame is just filled with NAs.
Does anyone know how I can alter the extent and resolution of my raster layers so they can be successfully stacked -- so I can then attach environmental info to presence points.
Cheers
One way to do this is to choose a raster that has the projection and extent that you want and use that as a template for the others
For example, if you have rasterA and rasterB. You can use projectRaster() to make a new version of rasterA with the same extent and resolution as rasterB. You should then be able to stack new.rasterA & rasterB.
new.rasterA <- projectRaster(rasterB, rasterA) # define the projection and extent
r.stack <- stack(new.rasterA, rasterB) # add them to a raster stack object
I had the same issue and I solved this in arcgis by snapping each raster to a mask of my study area.
This can be done by clicking geoprocessing -> environments -> processing extent - then select a layer you want to snap to in the snap raster box. I did this before I extracted (clipped) each layer and it worked perfectly. You can check the extent in properties when you are done for each layer you do to double check before you upload them into R.
I would like to create an online interactive map with filled contour plot layer like the ones can be seen on openweathermaps (I would like to use my own data for the plots).
What I need is also similar to the Leaflet heatmap (heatmap.js) but without dynamically changing the colors and the extent of the graphical objects (as in case of heatmap.js). Let's call them static heat maps.
I would like to know which mapping code/library can be used to produce such maps.
I am really newbie to these things, so please bear with me.
I tried Leaflet but did not find any plugin which would create filled contour map layers (static heatmap). I created the following map with Leaflet where the rectangles are geojson polylines and the color is based on some assigned values to every rectangle (elevation)
my leaflet attempt
The problem with this approach is that if higher resolution (smaller and more rectangles) is needed the site would really slow down.
I checked OpenLayers but did not see any similar examples.
I have the data in a matrix format:
Lat; Long; Value
.
.
Values are given in every gridpoints.
(if needed I would convert into other formats, like in case of the above attempt into geojson format)
The data is static, would be saved on the server.
So what I basically want to accomplish is a site where some spatial data is represented as filled contour map (static heatmap) and it is plotted over a map.
Here is my solution to the problem using open-source programs and free, online service:
(1) Processing the data in a GIS program. I used QGIS. I interpolated my data which is in grid points to get a high resolution raster map.
(2) Save the post-processed raster map as a georeferenced *.tif image.
(3) Import the image into TileMill. Remove the basemap and keep only the image as the only layer (style it).
(4) Export the 'map' from TileMill as MBTiles. This will save numerous *.png files (tiles) corresponding to different zoom levels. These are the same type as google or openstreetmap use for their online maps.
(5) Create a free account at Mapbox and create a new map project. Upload the MBTiles created by TileMill (can be directly uploaded from it). Style it.
(6) Use the Map ID corresponding to your created project to embed the map into html sites, e.g. the javascript code:
// Provide your access token
L.mapbox.accessToken = 'Mapbox will generate this for you';
// Create a map in the div #map
var map = L.mapbox.map('map', 'username.mapid', {
minZoom: 5,
maxZoom: 10
}).setView([47, 20], 8);
Example hosted on Mapbox
Sample image(I do not how long will the above link live):
In retrospect, the question would have been better fit to GIS stack exchange.
I have home range data sets for 6 animals using UTM coordinates. I have successfully read them into R and calculated each home range using the Minimum Convex Polygon(MCP) method. I would like to know if it is possible to do an "incremental area analysis" on these data. What I am looking for is a graph for each home range data set that has the number of data points on the X axis, and the MCP area of the points on the Y axis. The idea is to look for an asymptote. If an asymptote is found, then the area is not increasing with additional data. This would allow me to conclude that the home range of the animal has been fully revealed.
Essentially, I need to know the area gained for each sequential data point. Does adehabitatHR or its brother packages have this capability?
You can find a script for IAA at the Faunalia webpage, I used it and it worked perfectly for MCP:
https://trac.faunalia.it/animove/wiki/AnimoveHowto
I have asked this question in the GIS part of stack exchange https://gis.stackexchange.com/questions/95265/r-how-to-create-a-pre-determined-number-of-identical-square-polygons-to-use-fo - I am asking it here as well as it has also topics of wider interest (e.g. calculation of density) - I hope not to be penalised for this! :)
I am trying to plot crime data density (again!) over a city map, say of NY. As a well known problem there are plenty of examples on this (http://www.obscureanalytics.com/2012/12/07/visualizing-baltimore-with-r-and-ggplot2-crime-data/). These methods plot the crime density through isoclines, while I need to represent it through identical density squares of a pre-determined area (and the area / side length may change from one iteration to the other). This is actually done in commercially available COTS packages like PredPol (see http://www.predpol.com). The reason for representing crime density through squares is that the square are the hotspot areas to be patrolled. The size will influence the overall amount of police people required.
This is what I am trying to achieve:
I would like to be able to create identical square polygons with pre-determined size to overimpose to the map (is it a raster? apologies but I've just started to learn to spell GIS!)
I would like to use the above squares as items to colour as in a choropleth map (i.e. different colouring in relation to frequency of crime in the area), probably using ggplot2 or similar.
This should allow me to see how the density of crimes per square kilometre varies changing the size (i.e. the area) of the square, proposing different patrolling areas.
I do not have a clue if it is possible to use R to create regularly shaped squares polygons of a pre-defined size to use for this (as the code snipped below attests). Any help or links to examples are welcome.
I would be glad to get some indication on alternative ways to calculate the density. I have used the stat_density2 (part of ggplot2) but maybe there are better / faster ways?
(
In hindsight, do I need a density function at all? I just need to count the crimes in a cell and colour-plot it accordingly...)
This is where I got to:
library(rgdal)
library(raster)
library(sp)
#NY boroughs shapefile downloaded from NY website
shp <- readOGR(dsn = "nybb_14a_av", layer = "nybb")
r <- raster(extent(shp))
res(r)=0.05
# using BoroCode as an experiment...
r <- rasterize(shp, field="BoroCode", r)
plot(r)
plot(shp,lwd=10,add=TRUE)
#don't know the result of the above: the laptop basically hangs processing
#plot(r) :)