An Overview of the Data Access & Visualization Portal for Geographic Information System and Its Application

Data Access & Visualization Portal for Geographic Information System

I. Introduction

The management, analysis, and visualization of spatial data have all been transformed by Geographic Information Systems (GIS). In order to capture, manage, and display any type of geographically linked data, these systems combine hardware, software, and data. Tools that can easily transform data into meaningful graphical representations are needed in a country as big and diverse as India, where a lot of data is frequently kept in tabular formats like Excel. "Data Access & Visualization Portal for Geographic Information System" is a project that attempts to meet this demand. Through database connectivity, the portal is intended to convert unprocessed Excel data into informative graphical representations. This promotes improved comprehension and decision-making. by using spatial datasets and visual analytics. The project's goals, difficulties, approach, outcomes, and conclusions are all covered in length in this document. This page is designed to allow users to access and visualize Geographic Information System (GIS) data by selecting specific parameters: The State and the Site Name.

STEP 1 – To open project copy link fromVS Code and paste in browser.

Dropdown Menu: "Select State":

• Users are presented with a dropdown menu labeled "Select State."
• This dropdown likely contains a list of states from which users can choose.

Fig 1

Fig 3

STEP 4- After completing step 1 and step 2 and step 3 then this step start and after select state from select state field and after selecting site name or city name from site name field and after click on submit button.

Then This graph is shown

This graph represents a time series of some parameter (possibly displacement or velocity) at a specific location (Site Name: AMAN).

? The dots on the graph represent individual data points collected over time.

? The line represents a trend or regression line fitted to the data, indicating the general direction of change

Fig 4

STEP 5- ?

• The image displays two time-series plots, representing the movement of a specific location (a GPS station) over time.
• The movement is being analyzed in two directions: Northing (vertical) and Easting (horizontal).

Top Plot (Northing):

• Data: The blue dots represent individual measurements of the Northing movement taken at different times.
• Trend Line: The black dashed line is a linear regression fit to the data. This line indicates the general trend of the movement over time.
• Slope (Vn): The value "Vn = 3.740 cm/yr" represents the slope of the trend line. This means that the location is moving northward at an average rate of 3.740 centimeters per year.

Bottom Plot (Easting):

• Data: The blue triangles represent individual measurements of the Easting movement.
• Trend Line: Similar to the top plot, the dashed line shows the trend of the Easting movement.
• Slope (Vu): "Vu = -0.623 cm/yr" indicates that the location is moving westward at an average rate of 0.623 centimeters per year.

Fig 5

STEP 6- The image presents four time-series plots, each representing the number of "IOD Cycle Slips" over time for different categories.

• Y-axis: Number of IOD Cycle Slips
• X-axis: Time (likely in days or hours)

Plot Titles:

• G_IOD_CS
• R_IOD_CS
• E_IOD_CS
• J_IOD_CS

Interpretation:

• Cycle Slips: These likely refer to errors or discontinuities in a signal or measurement.
• Time Series: Each plot tracks the occurrence of cycle slips over time for a specific category (G_IOD_CS, R_IOD_CS, etc.).
• Dots: Each dot represents an instance of a cycle slip at a particular time.
• Variations: The number of cycle slips varies significantly across the time period for each category. Some periods show a higher density of dots, indicating more frequent cycle slips.

Fig 6

STEP 7- The image displays four time-series plots, each representing the "Multipath" levels for different GNSS (Global Navigation Satellite System) constellations.

• Y-axis: Multipath (in meters) - This indicates the level of multipath interference, which is a source of error in GPS measurements. Higher values suggest more significant multipath.
• X-axis: Time (in days or hours)

Plot Titles:

• G_MP1, G_MP2, G_MP5: These likely correspond to different types of multipath measurements or sources associated with the GPS constellation.
• R_MP1, R_MP2, R_MP5: Similar to above, but for the GLONASS constellation.
• E_MP1, E_MP2, E_MP5: For the Galileo constellation.
• J_MP1: For the QZSS constellation.

Interpretation:

• Multipath Variations: The plots show that the multipath levels fluctuate over time for each constellation and measurement type. Some periods exhibit higher multipath, indicating a greater potential for error in GPS positioning.
• Constellation Differences: Comparing the plots, we can observe that different constellations might experience varying levels of multipath interference.

Fig 7

STEP 8 - The image presents a time-series plot titled "Percentage Observation Plot of AMAN."

• Y-axis: Percentage Observation Available
• X-axis: Year (in decimal)

Interpretation:

• Data Points: The plot shows individual data points scattered around the 100% line.
• Trend: The overall trend suggests that the percentage of observations available has been relatively stable and close to 100% throughout the period shown. There are some fluctuations, with a few data points slightly above or below 100%.

• Data: The spreadsheet appears to contain daily records of geospatial data for a specific location

• ? Time Series of Ellipsoidal Height: This would show how the elevation of the location changes over time. You could use a line graph to visualize this trend.
• ? Time Series of Latitude and Longitude: You could create two separate line graphs, one for latitude and one for longitude, to see if there are any significant changes in the location's coordinates over time.

Fig 12

Level 1 (Process Overview): This level breaks down the system into five major processes: Data Input, Database Interaction, Data Processing, Visualization, and Output Delivery.

Fig: 15

Level 2 (Detailed Processes): This level further refines each process from Level 1 into more specific modules: Data Input Module, Database Module, Data Processing Module, Visualization Module, and User Interaction Module.

CONCLUSION

The difficulties in evaluating and displaying geographic data in Excel files are effectively handled by the Data Access & Visualization Portal for Geographic Information System. The portal enables users to effectively make data-driven decisions by fusing database connectivity with sophisticated visualization capabilities.

The project's major accomplishments include:
smooth connection between a GIS platform and Excel data. Visualizations for spatial datasets that are both interactive and intuitive. enhanced data usability and accessibility via a consolidated gateway. Future improvements might incorporate machine learning for predictive analytics, compatibility for more file formats, and integration with sophisticated GIS tools. This research provides a strong basis for using geographic data to generate insightful conclusions and promote well-informed decision-making in a variety of fields.

Appendices

full software code for visualizing GIS data and connecting to databases.