Spatial

This question already has answers here : GIS: PostGIS/PostgreSQL vs. MySql vs. SQL Server? [closed] (5 answers) Closed 4 years ago . We're building a small-sized GIS Web application (as a school project) right now. In terms of spatial database support and capabilities, which is better? Check it out for yourself, you know what you're looking for in your GIS-application: http://www.bostongis.com/PrinterFriendly.aspx?content_name=sqlserver2008_postgis_mysql_compare In general PostGIS is much more mature and is very flexible. You can create any function, operator, index type or what so ever. It

I need to get the cell numbers within a distance (e.g., 10 km) of one point using R, but I didn't figure out how to handle it for the raster data. library(raster) r <- raster(ncols=10, nrows=10) cellFromXY(r, c(2,2)) # get the cell number of one point How to get the cell numbers within a distance of one point? Use extract with the buffer option and cellnumbers=TRUE r <- raster(ncols=100, nrows=100) r[]<-runif(ncell(r)) xy <- cbind(-50, seq(-80, 80, by=20)) extract(r, xy[1:3,], buffer=1000000,cellnumbers=TRUE) 来源： https://stackoverflow.com/questions/13996256/get-cell-number-within-a-distance-of

I have an issue that I just cannot seem to sort out. I have a dataset that was derived from a raster in arcgis. The dataset represents every fire occurrence during a 10-year period. Some raster cells had multiple fires within that time period (and, thus, will have multiple rows in my dataset) and some raster cells will not have had any fire (and, thus, will not be represented in my dataset). So, each row in the dataset has a column number (sequential integer) and a row number assigned to it that corresponds with the row and column ID from the raster. It also has the date of the fire. I would

I have a NetCDF file of a probability surface. It's a 30x30 grid of 0.25 degree lat/lon intervals with a probability surface described in the z dimension. I can easily import this into Panoply, a NetCDF viewer: And it's then a breeze (checking one box) to interpolate/smooth the raw data to a finer grid size: However, I don't just want to visualize the data, I want to plot it in R along with bathymetry and point data. That all is no problem, but I have not found a straightforward way to interpolate the gridded data in R. Here's the code I use to import and plot the data: library(RNetCDF) nc <-

I have spatial lines as 'list': > SL1 [[1]] class : SpatialLines nfeatures : 1 extent : 253641, 268641, 2621722, 2621722 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=46 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 [[2]] class : SpatialLines nfeatures : 1 extent : 253641, 268641, 2622722, 2622722 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=46 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0 [[3]] class : SpatialLines nfeatures : 1 extent : 253641, 268641, 2623722, 2623722 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=46 +datum=WGS84 +units=m