The Streambatch.io API offers two methods for interpolation: Nearest Neighbors and Bilinear. You can specify your preference in your API request, allowing you to customize how the system fills in missing values and tailors the dataset to your specific application requirements. You have the option to select from the following aggregation methods:
nearestbilinear
What is Interpolation?
Interpolation is a technique used to estimate unknown values between known data points. It is commonly used in various fields, including remote sensing, to generate continuous data from discrete observations. Interpolation can help address issues with missing or sparse data, improving the overall quality and usability of a dataset.
Nearest Neighbors Interpolation
Nearest neighbors interpolation is a simple and efficient method to estimate missing values. It operates by finding the nearest known data points to the location where the value is missing and uses their values for estimation.
To use this method, include the following in your API request:
ndvi_request = {
...
"interpolation": "nearest"
}
Bilinear Interpolation
Bilinear interpolation offers a more refined estimation by performing linear interpolation first in one direction, and then again in the perpendicular direction. It takes into account the distance to all four nearest grid points, thus providing a more precise estimation for continuous variations.
To use this method, include the following in your API request:
ndvi_request = {
...
"interpolation": "bilinear"
}
Through the Streambatch.io API, you can leverage these interpolation methods to tailor the data to your specific needs, whether for applications in agriculture, forestry, ecology, or environmental research.