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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Choose satellite imagery by working backward from the decision you need to make—not by picking the smallest pixel size. Define the feature or change you must detect, the area and deadline, and the cost of missing an observation. Then compare spatial detail, revisit, delivery latency, sensor and bands, data quality, geographic coverage, access, licensing, and total cost. The right choice can differ sharply between mapping flood extent today, monitoring crops through a season, and measuring infrastructure change over time.
What should you decide before comparing imagery?
Write down the operational question in measurable terms. “Monitor a bridge” is too broad; “map visible surface damage after a flood” and “measure displacement against a baseline” are different tasks and may require different data, processing, and validation. Record the area of interest, the observation window, how often an update is useful, the latest time a usable result can arrive, and what happens if the observation is late or wrong.
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Set the minimum useful detail
Start with the smallest feature or change that must be detected, then ask whether the candidate data can resolve it reliably. A stated pixel size or ground sample distance (GSD) is not the same as achieved detection or measurement accuracy. Geolocation error, image quality, viewing conditions, processing, and the method used to interpret the data all matter. The finest nominal resolution is not automatically the best operational product if it arrives too late, lacks the right sensor signal, or has unsuitable quality or licensing.
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Separate revisit from delivery latency
Revisit is how often a satellite or constellation can observe an area. Delivery latency is the time between acquisition and a usable result, including processing and delivery. A short revisit does not guarantee that a new image will be acquired on the needed date or that a processed product will arrive quickly. For each candidate, verify the achievable acquisition window and any product-specific service commitment; do not infer delivery time from revisit alone.
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Match the sensor and bands to the signal
Optical imagery measures visible and other spectral information, but clouds can prevent a useful observation of the ground. Synthetic aperture radar (SAR) is an active radar modality; NASA says SAR can observe Earth’s surface day and night through most weather conditions. SAR can therefore complement optical data for cloud-affected response or crop-damage work, but it is not a universal substitute: suitability depends on the question, product, radar frequency, polarization, acquisition mode, and processing.
For optical data, check which bands are available and whether the product is surface reflectance or another processing level. For SAR, compare the frequency, polarization, and mode rather than relying on the label “radar.” If a task depends on spectral distinctions or radar response, confirm that the specific product supplies the relevant measurements and that your analysis method is appropriate.
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Check quality, maturity, and readiness
Review calibration and validation, geolocation, metadata completeness and accuracy, documentation, processing level, archive depth, product maturity, and whether the data have been assessed for your intended use. NASA’s Commercial Satellite Data Acquisition (CSDA) evaluation criteria include accessibility, metadata accuracy and completeness, user support, usefulness, and imagery or data quality. NASA’s joint assessment framework has domain-specific guidance for optical and SAR data. Its optical guidelines were released April 26, 2026, and its SAR guidelines June 9, 2024; those dates mark guidance publications, not blanket approval of every product.
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How do the priorities differ by use case?
Disaster response: prioritize a usable observation in the response window
For rapid mapping, establish how soon the affected area must be observed and when the map must be ready. Check tasking or archive availability for the affected geography, acquisition feasibility, revisit, delivery latency, minimum feature size, and cloud conditions. Optical imagery can provide visual and multispectral context when a clear acquisition is available. When clouds obscure the surface, SAR may provide an observation through most weather conditions; combining radar and optical imagery can be useful when the response question benefits from both signals.
Do not treat a catalogue revisit figure as a promise of acquisition or delivery for a specific emergency. Confirm the geography, workflow, and any service-level timing commitment with the provider. Choose the processing and interpretation method for the response question—for example, mapping an extent is not the same as assessing damage to individual structures.
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Agriculture: choose cadence for the decision, not for the crop in general
A NASA-sponsored user-needs report prepared by RTI International in 2021 found different acceptable observation intervals for different agricultural uses. These are findings from the interviewed user communities, not universal agronomic thresholds.
| Decision or use | Reported observation interval | How to interpret the finding |
|---|---|---|
| Global yield monitoring, tillage-practice monitoring, and crop-insurance structuring | Weekly repeat was reported as acceptable. | This describes interviewed users’ needs in the 2021 study; it does not establish a schedule for every crop, region, or operation. |
| Crop-damage assessment and variable-rate fertilizer use | Daily revisit was reported as ideal; data could still be useful at intervals up to six days. | Whether a particular acquisition is actionable depends on the event, crop, location, and decision deadline. |
| Irrigation decisions | One- to two-day or intraday revisit was reported as ideal; the study reported little or no value after six days. | These are reported user preferences, not a universal irrigation rule. |
The same study reported that SAR could support crop-damage assessment and flood detection after storms because radar can observe through clouds that obscure optical imagery. Interviewed users expressed interest in L-band for crop classification and soil analysis, X-band for detecting in-field ponding and crop lodging, and multiband SAR more broadly. Treat these as reported preferences: performance and suitability must be checked for the actual sensor, product, crop, and analysis.
Use HLS as a public optical starting point when its scale fits
NASA’s Harmonized Landsat and Sentinel-2 (HLS) product combines Landsat 8 and 9 with Sentinel-2A, Sentinel-2B, and Sentinel-2C as analysis-ready surface-reflectance data. NASA reports global land coverage except Antarctica, 30-meter spatial resolution, and a global median repeat frequency of two days for the five-satellite constellation. The reported temporal coverage begins with Landsat 8 acquisitions in 2013 and Sentinel-2 acquisitions in 2015.
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Those are dataset-level attributes, not a guarantee of a clear-sky image of a particular field every two days. HLS is a sensible public starting point for broad-area, repeated optical analysis when 30-meter resolution and cloud-affected observation frequency are acceptable. It should not be assumed to meet a field-level, urgent, or all-weather requirement simply because its constellation has a two-day global median repeat.
Infrastructure monitoring: define the measurement before selecting resolution
Specify whether the job is visual inspection, construction or land-cover change mapping, surface-disturbance detection, or displacement measurement. Those tasks call for different combinations of spatial detail, temporal baseline, modality, processing, and validation. A displacement analysis, for example, needs a suitable time series and an appropriate measurement method; a single image’s pixel size does not establish displacement accuracy.
NASA’s CSDA catalog includes commercial SAR and other data products, and its evaluation framework emphasizes quality, calibration, validation, documentation, and maturity. There is no single pixel-size or displacement-accuracy threshold established here for all infrastructure. Roads, bridges, pipelines, dams, and buildings do not share one universal imagery specification, so set and validate the requirement for the particular asset and measurement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you compare candidate products?
Use the same questions for every provider and product. Record the evidence and conditions attached to each specification, not just the headline number.
- Spatial detail and geolocation: What are the stated resolution or GSD and geolocation characteristics? What feature or change must be resolved? Do not equate GSD with detection or measurement accuracy.
- Acquisition and cadence: What is the revisit, and what acquisition window is achievable for your area and dates? Is it based on latitude, tasking availability, or a constellation-wide statistic?
- Delivery: How long after acquisition is the specified product available, and what processing is included? Obtain a product-specific commitment if timing is operationally critical.
- Sensor information: For optical data, which bands and processing levels are supplied? For SAR, which frequency, polarization, and mode? Are the measurements suitable for the signal you need?
- Coverage and archive: Does the product cover the full area of interest? Are historical acquisitions available for a baseline, comparison, or seasonal analysis?
- Quality and readiness: What calibration, validation, metadata, documentation, maturity, and intended-use assessment are available?
- Operational access: Can your team obtain the data through the needed download, API, or delivery workflow? What support and reliability are documented?
- Rights and total cost: Who may use the data? Are redistribution and derived products allowed? What access restrictions, procurement fees, processing costs, or eligibility rules apply?
One concrete example of why specifications must remain tied to their source and date: NASA’s CSDA vendor profile for Pixxel lists more than 135 visible and near-infrared bands for Firefly, a 5.36-meter GSD, and revisit of one to two days based on latitude. Those are vendor-profile specifications, version 3.2 dated May 2026; specifications can change. The listed GSD is not a statement of achieved feature-detection accuracy, and revisit is not delivery latency. Check the current product terms and technical documentation before relying on the figures.
Quick Recap
What is a practical selection process?
- Write the decision and deadline. State what must be detected or measured, where, by when, and what error or delay would mean operationally.
- Set a minimum useful detail and acceptable uncertainty. Define the target feature or measurement, then check resolution, geolocation, quality, and validation requirements together.
- Set the observation cadence and delivery deadline independently. Decide how often a new observation matters, then obtain acquisition-window and acquisition-to-delivery information for the particular product.
- Choose modality and measurements. Decide whether optical data, SAR, or both can answer the question; specify needed bands or radar characteristics and account for cloud exposure.
- Screen for coverage, archive, and readiness. Confirm geography, acquisition feasibility, historical baseline, processing level, calibration, validation, documentation, and maturity.
- Verify operational and legal fit. Confirm user eligibility, access method, support, allowed use, redistribution and derivative rights, and full procurement and processing cost.
- Test against a representative decision. Where possible, evaluate candidate data on a known location or event with the intended workflow. Check whether the result is accurate and timely enough for the decision—not merely whether an image can be downloaded.
Why can a seemingly suitable imagery choice fail?
- The smallest pixel size wins by default: nominal GSD does not establish detection accuracy, geolocation quality, or analytical suitability.
- Revisit is mistaken for delivery speed: an observation opportunity says nothing by itself about acquisition success, processing time, or delivery.
- Optical imagery is assumed to be available on schedule: clouds can block useful surface observations, which is material in storm response and some crop assessments.
- SAR is treated as universally interchangeable with optical: radar can observe through most weather conditions, but the appropriate frequency, mode, polarization, and processing depend on the task.
- A constellation statistic is applied to one site: a global median or a latitude-qualified vendor revisit figure is not a guarantee for a particular location or date.
- A user study is turned into a universal rule: the agricultural intervals above describe findings from interviewed users in a 2021 report, not every farm or decision.
- Access and rights are checked last: availability, licensing, redistribution, eligibility, and cost can make technically suitable data unusable in the intended workflow.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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