关于获取同分辨率年度多时相卫星遥感影像的技术咨询

Hey there! Great question—securing consistent multi-temporal satellite imagery for your change detection research is absolutely critical, and I’ve got a handful of reliable go-to sources that should match your requirements perfectly:

• USGS EarthExplorer: This is my top pick for most change detection projects. It hosts fully free data from the Landsat series (especially Landsat 8/9, 30m resolution) with decades of archive, making it easy to find a year’s worth of imagery for the same location. You can filter by sensor (to lock in consistent resolution), cloud cover (aim for <10% for best results), and geographic bounds directly. It also includes Sentinel-2 data (10m resolution) from the European Space Agency, which has frequent updates and flexible cloud filtering.
• Sentinel Hub EO Browser: Built specifically for ESA’s Sentinel missions, this tool lets you visually preview Sentinel-2 imagery (10m resolution) first, then quickly filter for your target area and one-year time window. You can download raw or preprocessed imagery directly, and the intuitive interface makes it super easy to zero in on the exact shots you need.
• NASA GIBS: If you prefer a visual timeline-based approach to browsing, GIBS lets you scroll through time to view imagery of your target location across different dates. It supports multiple datasets like Landsat and Sentinel, and once you find suitable imagery, it links you directly to the download source.

If your research demands sub-meter or ultra-high resolution data, these options are worth considering:

• Google Earth Engine (GEE): While it’s more of a processing platform than a direct download tool, GEE integrates massive archives of both free and paid imagery. You can use simple code snippets to filter for same-location, same-resolution, one-year imagery batches, and even do preprocessing (like cloud masking, spatial alignment) directly on the platform. It’s a huge time-saver for large-scale change detection work.
• Maxar (formerly DigitalGlobe): Offers ultra-high resolution imagery (as low as 0.3m) with strict consistency in resolution for the same location. You can request a year’s worth of imagery tailored to your study area, but it comes with a cost—ideal if you have funding and need top-tier resolution.
• Planet Labs: Provides daily-updated high-resolution imagery (around 3m resolution), so you can get a dense time series over a year. This is perfect if your change detection requires capturing frequent, small-scale changes. Like Maxar, it’s a paid service.

• Always filter for the same satellite/sensor across your time series—this guarantees consistent resolution and avoids headaches with spatial alignment later.
• Prioritize imagery with cloud cover below 10% whenever possible; cloud contamination can ruin change detection accuracy.
• For free data, look for preprocessed levels (e.g., Landsat Level-2) which include atmospheric correction—this saves you hours of prep work.

内容的提问来源于stack exchange，提问作者vkSinha