# Tag Info

## Hot answers tagged geospatial

7

Welcome to an interesting and important field of research! Interpolation is a large topic and there are many techniques. I agree that the GIS or math forum could be more initiated, but for completeness, I'll post some thoughts here. The choice of method depends on the type of data you are using and the implementation depends on your environment. GIS ...

7

Depending on the nature of the data, the approach of Hess, K., R. Schmalz, C. Zervas, and W. Collier, 2004. 'Tidal Constituent and Residual Interpolation (TCARI): A New Method for the Tidal Correction of Bathymetric Data'. NOAA Technical Report NOS CS 4, Silver Spring, MD, 112 pp. (http://www.nauticalcharts.noaa.gov/staff/docs/TCARI_CS4.pdf) might be ...

7

A very neat approach for optimal interpolation, which consider not only breaklines along the coast but also anisotropies caused by currents and horizontal diffusion, was given by Lynch & McGillicuddy (2001). Their approach is quite elegant and takes advantage of the finite element methodology to avoid the transfer of information across boundaries.

7

The best open-source and free geospatial database is in my opinion PostGIS. It is easy to use and has a huge support group (also for example at https://gis.stackexchange.com/) It also connect to all sorts of different open-source programs and web-interfaces which should make data editing, viewing and sharing easy. It can handle the date-line and the poles:...

6

A good place to looking is geostatistics. It is a branch of statistics focusing on spatial or spatiotemporal datasets. In its earlier days, geostatistics was also known as the theory of regionalized variables. Geostatistics was initially developed by George Matheron, a French mathematician and geologist - though when I first heard about him in the 1980s he ...

4

I agree with Speissburger that PostGIS (an extension of Postgre) has excellent Geospatial support. In the open source world, this would also be my recommendation. (MySQL claims to have some geospatial support but it is very limited in capabilities) For completeness, Microsoft's SQL Server also has good geospatial support - I think it was introduced as an ...

4

Your understanding is inaccurate. The shifts by $\frac{1^\circ}{24}$ are only relevant for figuring out, where the pixel centers are located and where to start when you are looking to find the right grid index for a certain point. As for the resolution, it is much simpler. We have $4320$ pixels covering $360^\circ$ in longitude direction, i.e. a resolution ...

4

It sounds to me like the reviewer is fixated on a 'rule' they encountered in grad school, but the rule ignores some real-world nuance (as rules do). Quick caveat: my answer isn't definitive, it's more of an opinion, but it was too long for a comment. It seems intuitively true that some phenomena just are smooth, so the resolution of the data is not the ...

3

After a lenghty unsuccessful search, I found an option to do my own mapping. There are global datasets with the percentages of clay, silt and loam available from the Land-Atmosphere Interaction Research Group at Sun Yat-sen University and I used the R soiltexture package for the classification. I ended up making a dataset covering my domain of interest in 2 ...

3

It is far too complex a process to estimate surface irradiances utilising satellite data. No software takes just satellite images as input and gives out irradiances. I am pasting link to an article that describes algorithm to convert geostationary satellite measurements to surface reaching solar irradiance. Gadhavi et al., 2008; doi: 10.1029/2007JD009308 ...

2

Partial answer: after some further research: It looks as though the terminology that I am looking for is "Breakline". I need to define my coastlines as being breaklines. Now I need to figure out how to implement them in the languages that I am using, but that's probably a question for GIS.SE or Stackoverflow.

1

Yes, but it will not be a very good dataset. You will only be limited to the size of the dataset. You can use Python's griddata function. But of course, you will need to make your grid before using the function. Or you can use the interp2d function.

1

This is a non-trivial problem. Short answer: I don't think it can be done with monthly satellite data to a useful precision. Here's where I started: https://earthobservatory.nasa.gov/Search/index.php?hq=site%3Aearthobservatory.nasa.gov%2FFeatures%2F&q=measuring+rainfall They now have a tropical rainfall project. https://earthobservatory.nasa.gov/...

1

Exciting question... it's something I've wondered as well, both for interest purposes and for utility in programs like you mention (I posed a fairly related question in the cartography SE site proposal). I've searched a long time but could not find any term/calculation for this... perhaps I too just did not know the correct term to use? As a result, for a ...

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