Details of the JSON output and object table of city map cells API of Azavea

In this article, I will provide a clear explanation of the object table and JSON output of the Azavea City Map Cells API. As a programmer, you already know what these two concepts are, but understanding the specifics of how they are implemented in this API can be essential in working with the data effectively. By the end of this article, you will have a thorough understanding of the object table and JSON output of the Azavea City Map Cells API and be better equipped to use the data to meet your programming needs.

Object and Description

• geometry: This object represents the spatial or geometric data associated with a feature in the dataset. It typically includes the type of geometry (e.g., point, line, polygon), as well as the coordinates that define its location and shape.

• type: This object specifies the type of feature being represented in the dataset. For example, it might indicate whether a feature is a road, a building, or a park.

• coordinates: This object provides the precise location of a feature's geometry using a coordinate system, such as latitude and longitude. The specific structure of the coordinates object will vary depending on the type of geometry being represented.

• properties: This object contains additional non-spatial data associated with a feature in the dataset. This might include attributes such as the name of a building or the population of a city.

• dataset: This object represents the entire dataset and can include metadata such as the dataset's name, description, and source.

The information in the table is useful because it provides a clear and concise summary of the key objects that are typically included in a dataset that uses spatial or geographic data. Understanding these objects and their associated properties is essential in working with and manipulating such datasets. The table also provides a helpful reference for developers and analysts who need to interact with or integrate with these datasets, as it outlines the key objects and their expected format. By having a clear understanding of the objects and their purpose, users can more easily extract insights and information from the dataset, and build applications or visualizations that make use of this data.

Json output

The JSON output is an array of two objects, each representing a feature with spatial data. Each object has three key-value pairs: type, geometry, and properties. The type key specifies that each object is a Feature. The geometry key contains an object that specifies the type of geometry (Point) and its location, which is represented by an array of two numbers (coordinates). Finally, the properties key provides additional non-spatial data associated with the feature, including the name of the dataset to which the feature belongs. In this case, the first feature is associated with the NEX-GDDP dataset, while the second feature is associated with the LOCA dataset. This JSON output could be used to represent spatial data for mapping purposes or to analyze relationships between features in different datasets.

[
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [0,0]
},
"properties": {
"dataset": "NEX-GDDP"
}
}, {
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [1,1]
},
"properties": {
"dataset": "LOCA"
}
}
]

In summary

We covered various topics related to working with spatial data, including object tables, JSON output, and the structure of a sample JSON output. We discussed the importance of understanding key objects in spatial datasets, such as geometry, type, and properties, and how to manipulate this information using JSON output. Understanding these concepts is essential for developers and analysts who work with spatial data and need to extract insights and information from these datasets. By understanding the structure and content of spatial data, users can build powerful applications and visualizations that make use of this valuable information.

Source

It is possible to request access to the Azavea City Map Cells API through the third-party data marketplace of Worldindata. This marketplace offers a range of datasets and APIs from various providers, including the Azavea City Map Cells API. By requesting access to this API through Worldindata, users can obtain access to valuable spatial data for use in their own applications and analyses. The process for requesting access may vary, but typically involves creating an account with Worldindata and following the steps outlined on their platform to request access to the desired dataset or API.