Data Collection

Topics: Physical geography includes climatology, geomorphology, soil geography, biogeography and other subfields. Human geography includes historical geography, political geography, economic geography and several other areas
identify at least two databases where you can find the data that you need to perform the Project. providing the name of the database, a brief description of the organization that coordinates the database and the database website link.

Example of a data collection:-
Physical landscape data collection
The physical landscape is the framework of hills, mountains, plains, valleys, rivers, coasts, and other land surface features6. The researcher who decides to better understand the physical landscape seeks to understand the evolution of landforms, what their changes were, who was responsible for these changes and what factors control these forms. The data collection to conduct such research can be done through fieldwork using tools such as a theodolite, global positioning system (GPS), and remote sensing involving aerial and satellite imagery. The set of information collected using these tools can provide the data necessary for the development of three-dimensional models (Figure 5) that help to identify the forms, shapes and patterns of this physical landscape. These models can also support the understanding of relationships between the natural and anthropogenic processes and the topographic relief (landforms) identified.
Figure 5- Three-dimensional model of Mount Fuji, Japan, generated with satellite images. Retrieved from: https://www.google.com/earth/

Example 2: Data collection:
Computational modelling
This method consists of modelling practices that evaluate theoretical structures and processes expressed mathematically, typically in a computer4. Computational modelling performed with Geographic Information Systems (GIS), for example, allows the setup of large amounts of spatial patterns simultaneously, which supports the researcher in understanding some patterns that are observed on the Earth’s surface.
Figure 4 – This visualization depicts Hurricane Sandy’s near-surface winds using the Global Modeling and Assimilation Office (GMAO) GEOS-5 global atmospheric model. The GMAO is running high- resolution global simulations at the NASA Center for Climate Simulation to help improve the prediction of hurricanes and other weather phenomena. Retrieved from

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