GIS IN REMOTE SENSING TECHNOLOGY
Mama Information Technology and GIS Solutions have understood fully that remote sensing is different from GIS and the combination of the two gives a spectacular technology today our clients cannot resist is applying the technology for informed decision making. GIS Remote sensing technology gives abstracts of reality that is real. Remote sensing: – Is an act of surveying and data collection technique; a technique used to survey and collect data regarding an object or a phenomenon without any physical contact with the object or the phenomenon being observed. It is designed to collect and retrieve large amounts of data regarding an object or a phenomenon. The data could be about various aspects of the object including its position on the earth’s surface. It uses technical instruments (Sensors, Satellite Eyes, etc) to collect data over large areas which reduce the manual work that could otherwise have required a lot of people and financial inputs to do. Remote sensing can allow data to be retrieved in places where humans cannot access such as over volcanic mountains, the ocean depths and several other locations relatively within short period of time. The data collected can be used to analyze various aspects of the object or area being analyzed and more skilled personnel to interpret it using GIS tools. If we can take a look into temperature issues on the globe today using January 1981 raster below; is a demonstration of temperature Raster Data (it involves the value field which is in Kelvin temperature or (+273.15 degree Celcious )). A made ready raster comes as an integer value and the building of attribute table for the extraction to be accurate and successful temperature value using GIS tools:- There are many type of remote sensing dataset we can extract like:-
- Sensing for DEMS
- Sensing for Water bodies.
- Sensing for Agricultural Precision.
- Sensing for Minerals deposits like Gold (AU), Zink (Zn) , Copper (CU), e.t.c
- Sensing for Hydrocarbon.
- Sensing for Water Table.
- Sensing for 3D Buildings
- Sensing through Machine Learning through CNN (Convolution Neural Networks).
- Sensing for Atmospheric conditions.
- Sensing for Hurricane and flood.
- Sensing for Military Purposes.
- Sensing for all other natural phenomenon not listed above.