https://community.wolfram.com RSS Feed for Wolfram Community showing ideas tagged with Geographic Information System with no replies sorted by active. https://community.wolfram.com/groups/-/m/t/3715214 This is the continuation of the [Google Earth Client Paclet][1] posting. &[Wolfram Notebook][2] [1]: https://community.wolfram.com/groups/-/m/t/3714827 [2]: https://www.wolframcloud.com/obj/697f9f54-b7e8-4d7f-96a3-cc44b4e73627 Diego Zviovich 2026-05-12T23:08:24Z https://community.wolfram.com/groups/-/m/t/3563534 In this preliminary post I introduce the idea of dynamical Transformation Functions, that is, the situation where the Transformation Matrices have functions rather than numbers as entries. I apply this specifically in the case of even (direct) isometries of real 3-space. I introduce DITF format which is independent of the construction of the transformation function. I give a geometrical interpretation which shows motion in space not only the position but also the orientation of the object. Several examples are given. Barry H Dayton 2025-10-22T00:17:13Z https://community.wolfram.com/groups/-/m/t/3549441 A huge number of ingest site data repositories for Earth-orbiting data sensors store and publish their data in HDF file format. The HDF Group -- a spinoff from the UIUC-NCSA -- supports users of HDF datasets, including users of the NASA EOS. The HDF Group EOS support effort includes a large, on-line catalog of examples of accessing, processing, analyzing and visualizing the NASA EOS data files using the popularly used tools among Earth and Atmospheric scientists: NCL, IDL and MATLAB -- absent Mathematica. The attached Mathematica notebooks are attempts to replicate the HDF Group's hosted EOS examples in a similar style using Mathematica. - AIRS_L3_Temperature_MW_A_Lvls11.nb: Visualize a GESDISC_AIRS HDF-EOS2 Grid data file in Mathematica - Q20111212011151_L3m_MO_SCISM_V1_0_SSS_1deg_h5.nb: Visualization of a Level-3 gridded Aquarius simulation HDF5 dataset of Monthly (MO) Sea-Surface Salinity (SSS) from the NASA PO.DAAC (Physical Oceanography Distributed Active Archive Data Center) &[Wolfram Notebook][1] &[Wolfram Notebook][2] [1]: https://www.wolframcloud.com/obj/de5dcedb-f484-4586-a238-571876a9b23b [2]: https://www.wolframcloud.com/obj/d966b998-3937-4fa9-87fb-63554afcf9ad Stewart Dickson 2025-09-22T22:44:38Z https://community.wolfram.com/groups/-/m/t/3451550 We would like to inform readers interested in the book Mathematica Beyond Mathematics 2nd-edition ( https://community.wolfram.com/groups/-/m/t/2801704 ), that the supplementary materials have been updated. They can be downloaded from https://www.mathematicabeyondmathematics.com/ The new additions include more complex examples of some of the topics covered in the book. To take full advantage of the new additions, we recommend to go over the examples alongside the relevant book sections. Thank you, Guillermo Sánchez /Ruben García JOSÉ GUILLERMO SÁNCHEZ LEÓN 2025-04-28T07:05:24Z https://community.wolfram.com/groups/-/m/t/3450700 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/586ecf1d-6f9b-4aa4-9e28-4c1120e5a4f7 Daniel Carvalho 2025-04-27T02:01:39Z https://community.wolfram.com/groups/-/m/t/3443223 In French language, A new book on Machine learning A. Dauphiné : Intelligence artificielle et Géographie Avec le langage Wolfram Mathematica Éditions Universitaires Européenne www.morebooks.shop and Amazon André Dauphiné 2025-04-11T12:18:06Z https://community.wolfram.com/groups/-/m/t/3440358 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/782e38ab-f8ff-4273-98fb-f0ef2bd4ad62 Theo Vine 2025-04-06T09:33:53Z https://community.wolfram.com/groups/-/m/t/3379935 ![walkability score][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=proj-4-cover.jpeg&userId=911151 [2]: https://www.wolframcloud.com/obj/8f26469c-3ce8-4609-bb3d-666cf8c9b1d8 Wolfram Education Programs 2025-02-04T15:05:08Z https://community.wolfram.com/groups/-/m/t/3285798 I’ve been exploring the capabilities of the Wolfram Language for a while now, and it’s been fascinating to see how powerful it is for processing and analyzing various types of data. One thing I’ve recently become curious about is how I can better utilize GPS coordinates within the Wolfram system for everyday purposes. Specifically, I’ve noticed that while GPS can be very precise, there are times when the coordinates I get seem to be a little off, especially when I’m using them in rural or highly dense urban areas. I’ve been thinking about this issue a lot lately, especially after a recent experience where I was trying to find a location based on the coordinates given to me, and they led me to a slightly incorrect place. This got me wondering about the ways in which GPS data might be processed within the Wolfram Language, and whether there are any inherent limitations or things I might need to adjust to get better results. In particular, I’m interested in how the Wolfram Language handles GPS data input from a standard smartphone or device. I know that there are various levels of accuracy in GPS data depending on the device used, but I’m curious whether there’s any way to refine the GPS coordinates once they’re in Wolfram—perhaps using some mathematical techniques that could adjust for inaccuracies based on location factors. I’m especially inspired by the fact that Wolfram is excellent at working with real-world data and applying sophisticated mathematical models to it. This makes me wonder if there’s a way to apply that same level of precision to GPS data to make it even more reliable for personal use. GPS coordinates refer to the geographical positioning system that provides a set of numerical values—latitude and longitude—representing a specific point on the Earth's surface. These coordinates are derived from signals sent by satellites orbiting the Earth, which triangulate a device's exact position based on time and distance. GPS data is widely used in everything from navigation to mapping, and it's fascinating how such a small set of numbers can precisely define where you are in the world. What’s really interesting is the growing number of tools that allow you to [Display your GPS coordinates online][1], making it easier to share your location or use it for various applications. I’ve always been curious if Wolfram Language can take this basic GPS data and refine it further, perhaps by compensating for any minor inaccuracies that might arise due to environmental factors or device limitations. One thing that has piqued my interest is the idea of incorporating other types of location data alongside the GPS coordinates. For example, I’ve heard that some tools can use Wi-Fi signals or cell tower data in combination with GPS to get a more accurate reading of someone’s location. Does Wolfram Language have any capabilities like this? Could I feed it multiple data points to improve the precision of my location data? The core of my question centers around GPS coordinates because that’s what most devices tend to use by default. I know that GPS satellites calculate positions based on a range of factors, like time, distance, and satellite position. However, even with all of these factors in play, inaccuracies can creep in due to things like satellite positioning, atmospheric conditions, or even the quality of the receiver in the device. What I’m wondering, specifically, is how Wolfram might be able to compensate for those variations. For example, if I notice that the coordinates are off by a few meters, can I use Wolfram’s tools to adjust or refine the location data based on some known variables? This would be especially helpful when trying to pinpoint exact locations for activities like hiking or meeting someone in an unfamiliar area. I was positively inspired by this idea because it seems like Wolfram Language’s mathematical robustness could provide a real solution to the challenge of location accuracy. Also, I’m curious about the general workflow people use when processing and refining GPS data in the Wolfram ecosystem. I’ve been thinking about how different data sources might affect the end result—whether the location data is gathered from a smartphone, a dedicated GPS device, or some other source. Does anyone have any experience working with this in Wolfram, and are there any particular functions or techniques that have been helpful in refining the accuracy of GPS data? I’ve also read that some data smoothing techniques might be useful in reducing error. Does Wolfram have built-in capabilities for smoothing out small inaccuracies in GPS data? For example, if I’m gathering data over time (say, over the course of a walk or hike), is there a way to use Wolfram to average or otherwise process that data so that any outliers or errors are minimized? I’d love to hear others’ thoughts on how they use Wolfram Language for working with GPS data and whether there are any tricks or tips for getting the most accurate results possible! It would be especially helpful to hear from anyone who has encountered similar challenges and has found a solution that’s worked for them. Thank you! [1]: https://onlinecompass.net/gps-coordinates Shadi Maia 2024-09-27T16:30:13Z https://community.wolfram.com/groups/-/m/t/3211829 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/f2a646c4-420b-44d9-9606-97d2e728ba3f Andrew Herrera 2024-07-10T18:09:23Z https://community.wolfram.com/groups/-/m/t/3094952 ![enter image description here][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=9521image.jpeg&userId=911151 [2]: https://www.wolframcloud.com/obj/00b1ee9a-deef-493b-b8ba-e29aeb087708 Wolfram Education Programs 2024-01-02T19:00:40Z https://community.wolfram.com/groups/-/m/t/3094902 ![map comparisons][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=4144image.jpeg&userId=911151 [2]: https://www.wolframcloud.com/obj/38a05ff7-1afc-473d-be87-658503c398f1 Wolfram Education Programs 2024-01-02T17:19:37Z https://community.wolfram.com/groups/-/m/t/3094660 ![image of glucose molecule][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=image.jpeg&userId=911151 [2]: https://www.wolframcloud.com/obj/af8877e4-e217-434a-8ca6-f91935263102 Wolfram Education Programs 2024-01-02T16:55:44Z https://community.wolfram.com/groups/-/m/t/2964488 ![Comparison of Routes Within Washington D.C.][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=7.13.23TitleImage.PNG&userId=2964405 [2]: https://www.wolframcloud.com/obj/244e570a-362b-4c38-b265-56e5db82de19 Ryan Tong 2023-07-13T21:39:54Z https://community.wolfram.com/groups/-/m/t/2710038 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/bd20372d-0637-460f-81e6-7116c0c65c09 Peter Burbery 2022-11-26T03:25:00Z https://community.wolfram.com/groups/-/m/t/2618730 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/d278b962-75e1-4160-a392-24d0bec5938c Theodore Mollano 2022-09-17T21:27:00Z https://community.wolfram.com/groups/-/m/t/2549319 The [European Wolfram Tech Conference][1] has just started. The event is taking place in Frankfurt, which is one of the few European cities with a large cluster of high rise building in its downtown area. For this reason, Frankfurt is sometimes referred to as "Mainhattan" (a portmanteau of the local Main river and Manhattan). The following is a small computational exploration of the tallest buildings. Note that in this list there even is the building where the conference is happening, the Leonardo Royal Hotel Frankfurt, with exactly 100 meters. &[Wolfram Notebook][2] [1]: https://www.wolfram.com/events/technology-conference-eu/2022/ [2]: https://www.wolframcloud.com/obj/jofree/Published/Frankfurt-skyscrapers-computational-exploration.nb Jofre Espigule-Pons 2022-06-13T16:20:00Z https://community.wolfram.com/groups/-/m/t/2451695 Looking forward to joining [@Brett Champion][at0], [@Jose M. Martin-Garcia][at1] and Nirmal Malapaka for the upcoming New in Wolfram Language 13 webinar on Tuesday, January 25, and seeing what's new in visualization and geographic visualization. Seats are available. > **REGISTER HERE:** > https://www.bigmarker.com/wolfram-u/new-in-13-visualization-geovisualization > **About This Webinar:** This webinar features an overview and exploration of new visualization and geo visualization features and improvements in the Wolfram Language. [![enter image description here][2]][1] [at0]: https://community.wolfram.com/web/brettc [at1]: https://community.wolfram.com/web/jose [1]: https://www.bigmarker.com/wolfram-u/new-in-13-visualization-geovisualization?utm_bmcr_source=community [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=ScreenShot2022-01-14at1.20.53PM.jpg&userId=20103 Jamie Peterson 2022-01-21T17:49:43Z https://community.wolfram.com/groups/-/m/t/2424580 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/5a0934c7-8bde-49b1-b3d8-9849b45c2163 Daniel Carvalho 2021-12-14T17:32:31Z https://community.wolfram.com/groups/-/m/t/2409914 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/2eabf4c5-616d-489d-81d9-6182e7932b19 Jose Martin-Garcia 2021-11-19T16:34:31Z