How to Perform Spatial Analysis
Feb. 13, 2023
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Spatial analysis, which solves complex location-oriented problems, allows you to explore and understand your data from a geographic perspective, identify relationships, detect and quantify patterns, evaluate trends, and make predictions and decisions. Spatial analysis goes beyond mapping and allows you to study the characteristics of locations and the relationships between them. Spatial analysis can provide you with some new perspectives on your decision making.
With spatial analysis, you can combine information from many sources by applying a set of spatial operators to get new information. Our spatial analysis services allow you to explore the answers to complex spatial questions. Statistical analysis determines whether the patterns you observe are significant. You can analyze individual layers to calculate the suitability of a location for a particular activity, and you can use image analysis to detect changes over time.
In GIS, each data set is managed as a layer and can be combined graphically using analysis operators (called overlay analysis). By using operators and displaying combined layers, GIS enables you to use these layers to explore critical questions and find answers to those questions.
In addition to location and attribute information, spatial data itself contains geometric and topological attributes. Geometric attributes include location and measurements, such as length, orientation, area, and volume. Topological properties represent spatial relationships such as connectivity, inclusion, and adjacency. Using these spatial attributes, you can ask more types of questions about the data to gain deeper insights.
OVERLAY ANALYSIS PROFILING
GIS analysis can be used to answer questions such as: Where is the best place for residential development? A number of seemingly unrelated factors - land cover, relative slope, distance to existing roads and streams, and soil composition - can be modeled as layers and then analyzed together using a weighted overlay.
The real power of GIS lies in the ability to perform analysis. Spatial analysis is a process in which you geographically model the problem, process it through a computer to produce results, and then explore and examine those results. This type of analysis has proven to be very effective for assessing the geographic suitability of a particular location for a particular purpose, estimating and predicting outcomes, interpreting and understanding change, detecting important patterns hidden in information, and more.
SPATIAL DATA EXPLORATION
Spatial data exploration involves interacting with a collection of data and maps relevant to answering a specific question, which allows you to visualize and explore the geographic information and analysis results relevant to that question. This allows you to extract knowledge and insights from the data. Spatial data exploration involves the use of interactive maps and associated tables, charts, graphs, and multimedia. This combines a geographic perspective with statistical information in attributes. It is an iterative process of interactive exploration and visualization of maps and data.
Smart mapping is one of the primary ways to explore data in ArcGIS. It's interesting because it allows you to interact with data in the context of a map notation system. Smart maps are built around data-driven workflows that generate intelligent data displays and effective default ways to view information and interact with it to see things like data distribution.
COMBINE INTERACTIVE CHARTS AND GRAPHS WITH GIS MAPS
Visualizing with charts, graphs, and tables is one way to extend your data exploration, providing a whole new way to interpret analysis results and communicate findings. Typically, you might start by browsing the raw data and looking at the records in a table. You might then plot (geocode) these points onto a map using a different notation system and begin creating different types of charts (bar charts, line charts, scatter charts, etc.) in different ways (by region, by type, or by date).
Next, you can start examining the temporal trend of the data by plotting time on the line chart. Information design is used to arrange different data visualizations to interpret the analysis results. Combine a range of your most powerful and clear elements (such as maps, charts, and text) in a layout that you display and share.
Find the signal in the noise. Visualizing data through charts helps reveal patterns, trends, relationships, and structures in data that might otherwise be difficult to see as raw numbers. Describe Chicago's violent crime statistics with a combination of chart and map styles that work together to unravel patterns and meaning from what is initially pure tabular data.
Feiyan Aerial Remote Sensing Tech Co., Ltd. has been the nation's largest independent geospatial data firm that provides geographic insights to many of the most influential projects in China. An industry leader in advanced mapping technology, Feiyan delivers the leading data quality with efficiency, while leveraging the most cutting-edge technologies for aerial data acquisitions, geospatial processing/analytics, and GIS visualization solutions.
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