Open Source Application Development
Open source software (OSS) is software that is distributed with its source code, making it available for use, modification, and distribution with its original rights.
M&A team has a vast experience in developing user-friendly, scalable and secure solutions using PHP, jQuery, Magento, AngularJS. We are your one stop for all your open source technologies, enabling your organization to save time and money. Rely on us on solution for:
- Web Programming (Web Mapping)
We deploy the use of:
- GeoServer Java based open source server software that allows users to edit and share geospatial data and uses open standards to publish GIS data.
- MapGuide Open Source allows for the development of web based mapping.
- GeoMajas Written in java, it is an open source GIS framework for the web.
- MapFish a development framework for web mapping applications based on the Pylon Pythons web framework.
- MapServer for building spatially enabled Internet applications
It provides the users a leeway to create, export and add layers in many common geospatial formats (gml, kml, geoJSON, gpx, shapefile, tiff, arcgrid, csv, osm), make vector layers with points, lines, polygons, add WMS layers, use WPS, style their own data, share as embedded maps, share as web pages, customize Interface, use analysis functions, create 2D, 2.5D and 3D maps, charts and so on.
- Open source GIS Frameworks and Software
M&A aims at providing you the liberty to; Control, Secure, Experiment, Share experience with the community of users at any given time and place. Some of the open source software and frameworks include: QGIS, GRASS, SAGAGIS, PostGIS, gvSIG, CartoDB, GMT Mapping Tools, FlowMap, OpenJUMP GIS, uDig GIS, QGIS, SPRING, TNTLite
- GIS Components and Packages (Tools and Resources).
These include: Geo-Tools, EDBS Reader, fmaps, MITAB, CartoDB, Topology Framework .NET (TF.NET), OpenMap, OpenEv, Vhclmaps, Rmap, Tkgeomap, PostgreSQL
- Artificial Intelligence and Machine Learning
M&A brings together the machine learning, artificial intelligence and deep learning as away of transforming how we understand and interact with our world and everything around us. We are part of the geo-spatial world looking at better management of open geo-spatial data, the are and not limited to:
- SpatioTemporal Asset Catalog (STAC)
STAC specification provides a common language to describe a range of geospatial information, so it can more easily be indexed and discovered. A ‘spatiotemporal asset’ is any file that represents information about the earth captured in a certain space and time. The goal is for all providers of spatiotemporal assets (Imagery, SAR, Point Clouds, Data Cubes, Full Motion Video, etc.) to expose their data as SpatioTemporal Asset Catalogs (STAC), so that new code doesn’t need to be written whenever a new data set or API is released.
- Raster Vision
An open source framework for deep learning on satellite and aerial imagery. Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery) can leverage Raster Vision’s built-in support for chip classification, object detection, and semantic segmentation using PyTorch and Tensorflow.
- Front End and Back EndTechnologies
This is the most important part of a Geospatila Application where all the data is visualized and accounts to 90% of geospatial web apps. Examples are: