Satellite imagery becomes considerably more useful when organizations can collect it consistently. A single image provides a snapshot, but repeated captures can reveal construction progress, environmental change, crop conditions, infrastructure development, and other patterns over time.
Manually searching for and ordering every new image can quickly become inefficient, particularly when dozens or hundreds of locations are involved. Automation offers an alternative, allowing satellite imagery to become part of an ongoing data pipeline.
Define What You Need to Monitor
Start by establishing exactly what the imagery needs to show.
An agricultural business might monitor crop development, while a construction company could track progress across several sites. Infrastructure operators may be more interested in detecting physical or environmental changes around important assets.
You should also define the geographical boundaries of each area of interest. Using consistent boundaries makes it much easier to compare imagery collected at different times.
Set the Right Capture Frequency
Not every location needs to be photographed every day.
The appropriate frequency depends on how quickly meaningful changes are likely to happen. Construction sites might benefit from weekly or monthly observations, while seasonal agricultural monitoring could require imagery at particular stages throughout the year.
Setting an appropriate schedule prevents organizations from paying for or storing imagery that provides little additional information.
Choose Suitable Satellite Data
Automation still requires decisions about what type of imagery should be collected.
Optical imagery works well when visible changes are the main concern. Multispectral imagery can provide additional information about vegetation and land conditions, while synthetic aperture radar, or SAR, can collect observations at night and through cloud cover.
Resolution is equally important. Higher-resolution imagery provides greater detail but is not necessary for every application. Large-scale environmental monitoring, for example, may work effectively with lower-resolution data.
Connect Satellite Imagery to an API
An API allows software to communicate directly with a satellite imagery platform, removing much of the manual work involved in finding and ordering data.
Through an open source satellite image API, organizations can build workflows that search imagery archives, request new satellite captures, and send imagery into existing systems. SkyFi’s API supports archive searches, satellite tasking, recurring orders and notifications, providing several ways to automate imagery acquisition.
This can be particularly useful for organizations monitoring many locations, where manually repeating the same process would become increasingly difficult to manage.
Automate New Capture Requests
If suitable imagery already exists, automated systems can search satellite archives for data matching predefined criteria.
When recent imagery is required, satellite tasking can be used instead. This involves requesting a new capture according to parameters such as the area of interest, sensor, resolution, cloud-cover requirements, and acquisition window.
Recurring collections can take this further by creating an ongoing monitoring program rather than placing each order individually.
Automate Delivery and Storage
Capturing imagery is only one part of the process. The resulting files also need to reach the people or systems that will analyze them.
Instead of downloading every image manually, an automated workflow can send imagery directly to cloud storage. SkyFi, for example, supports delivery to AWS S3, Google Cloud Storage and Azure Blob Storage, with imagery available in formats including GeoTIFF and PNG alongside metadata.
Webhooks can also provide automatic updates when an order changes status or imagery has been delivered.
Connect Imagery to Analysis Tools
The final stage is turning collected imagery into useful information.
New files can be passed into GIS software, analytics platforms, or machine-learning systems. Depending on the application, these systems might identify vegetation changes, compare construction progress or highlight significant differences between current and previous images.
This is where automation can provide the greatest benefit. Rather than simply collecting more satellite images, organizations can create a pipeline in which imagery is captured, delivered, processed, and analyzed with less manual intervention.