https://xiaolan.in/Recent content on Xiaolan XuHugoenSat, 04 Jul 2026 00:00:00 +0000https://xiaolan.in/blog/the-question-after-the-demo/Sat, 04 Jul 2026 00:00:00 +0000https://xiaolan.in/blog/the-question-after-the-demo/On April 24th I gave a demo of an AI-assisted, cloud-native pipeline for the SMAP-NISAR soil moisture algorithm — the kind of talk meant to show a platform working, not to make an argument. It landed well. People were generous about it afterward, including some fairly senior people at NASA HQ. The interesting part happened after, in the informal Q&A. A colleague who works in formal verification — proving software and system contracts correct, not remote sensing — asked a question that had nothing to do with the pipeline I’d just shown.https://xiaolan.in/talk/freeze-thaw-uqtr/Mon, 15 Jun 2026 00:00:00 +0000https://xiaolan.in/talk/freeze-thaw-uqtr/Copyright & Attribution © 2026. California Institute of Technology. Government sponsorship acknowledged. Author: Xiaolan Xu Affiliation: Jet Propulsion Laboratory, California Institute of Technology Funding: The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Invited seminar on continuous (non-binary) freeze-thaw state retrieval from L-band microwave missions. Covers the scientific motivation, algorithm development, and validation work for transitioning from traditional binary freeze-thaw classification to continuous state estimation.https://xiaolan.in/missions/aquarius/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/missions/aquarius/Aquarius is where my freeze–thaw work began. As first author, I developed and validated the first L-band detection of landscape freeze/thaw state from Aquarius’ backscatter data — showing that a scatterometer could reliably flag the frozen/thawed switch across the boreal and Arctic land surface, the signal that marks spring onset and frost timing. That detection method became the basis for the operational SMAP freeze/thaw science product I now lead — a direct line from an early-career research result to a mission deliverable.https://xiaolan.in/closing-the-loop/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/closing-the-loop/Here is the problem that drives me now. The equations we use to retrieve soil moisture or snow are simplified descendants of fundamental physics — wave equations boiled down, step by step, into something simple enough to run. Each simplification makes an assumption. Those assumptions are rarely written down, rarely tested against the conditions where the algorithm actually runs, and almost never corrected when the data hints they’re wrong. We check our answers against ground measurements, but the lesson seldom flows back to fix the equations themselves.https://xiaolan.in/collaborate/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/collaborate/I do my best work with other people — and often with people outside my own field. Some of the work I’m proudest of started with an unsolicited email asking the question I hadn’t thought to ask. Where I’m looking to collaborate Cross-field problems. The agenda I care most about right now is closing the loop between fundamental wave physics and the equations we actually deploy — making model assumptions explicit, putting rigorous uncertainty quantification on retrieved values, and letting validation data improve the equations themselves.https://xiaolan.in/contact/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/contact/I’m always happy to talk — about a possible collaboration, a problem at the edge of our fields, a paper of mine you have questions about, or a student looking for a direction. Some of the work I’m proudest of started with an unsolicited email. The best way to reach me is by email: xiaolan.xu@jpl.nasa.gov You can also find me on Google Scholar, ORCID, and Web of Science.https://xiaolan.in/cv/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/cv/Professional Experience Research Scientist, NASA Jet Propulsion Laboratory. Profiled on JPL’s official Radar Science pages: Soil Moisture · Snow Education Ph.D. / M.S., Electrical Engineering — University of Washington, Seattle (2011) B.Eng., Electrical Engineering — Zhejiang University (2006), Chu Kochen Honors College Selected awards Featured Article, IEEE Transactions on Antennas and Propagation, 2024 Women’s Day JPL Team Award, 2024 — SMAP SDS cloud transition 2022 J-STARS Prize Paper Award — “A Satellite Synthetic Aperture Radar Concept Using P-Band Signals of Opportunity” (Yueh, Shah, Xu, Stiles), IEEE JSTARS 2020 URSI Santimay Basu Prize — “For Developments in Wave Propagation and Scattering in Dense Random Media with Applications to Microwave Remote Sensing of Snow” 2018 IEEE AP-S Ulrich L.https://xiaolan.in/missions/cygnss/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/missions/cygnss/I built JPL’s operational Level-3 soil-moisture product for CYGNSS, and I lead an ongoing NASA ROSES-funded effort — as PI, since 2021 — to improve that retrieval and add a vegetation optical depth product using CYGNSS v3 data. Earlier, I was Co-I on the mission’s original soil-moisture algorithm and validation effort (2018–2021). It’s the same soil-moisture question as SMAP, answered through a completely different measurement: navigation-satellite signals reflected off the land surface instead of a dedicated radiometer.https://xiaolan.in/research/freeze-thaw/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/research/freeze-thaw/I work on detecting whether the land surface is frozen or thawed — the signal that marks the onset of spring and the timing of frost across the landscape. Frozen ground scatters microwaves very differently from thawed ground, which makes the transition legible from orbit. This thread began with the Aquarius mission and grew into an operational SMAP freeze–thaw science product — one of the clearest cases where a piece of wave physics becomes a number people rely on, season after season.https://xiaolan.in/research/wave-physics/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/research/wave-physics/Underneath every retrieval are first-principles models of how microwaves scatter inside snow and off rough, vegetated ground — solving the wave physics of terrain from the ground up rather than fitting curves to data. This is the core of my expertise, and the work recognized with the 2020 URSI Santimay Basu Prize. It’s also the backbone that makes the rest possible: soil moisture, snow, and freeze–thaw are all only as trustworthy as the scattering physics that connects the measured signal to the ground.https://xiaolan.in/missions/new-mission-concept/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/missions/new-mission-concept/This new mission concept has had me as algorithm contributor for over a decade, across several proposal rounds — CubeSat, EVI, and EVM announcements of opportunity, none yet funded. My side of it is the retrieval physics: how a P-band signal scatters off soil and vegetation, and what that means for sensing root-zone moisture and snow water equivalent at a depth L-band can’t reach. Two funded precursor studies have supported that work directly, as Co-I: a signals-of-opportunity concept for root-zone soil moisture and snow, and the theoretical basis for P-band SWE retrieval.https://xiaolan.in/missions/nisar/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/missions/nisar/My NISAR work sits inside SMAP. Since 2024, I’ve been building the active-passive soil-moisture algorithm that fuses SMAP radiometer data with NISAR’s L-band SAR — the retrieval NISAR’s soil-moisture products are expected to draw on once the mission is on orbit. I lead this as PI of a five-year NASA ROSES USPI award, and it’s the direct continuation of the freeze–thaw and soil-moisture work I’ve done under SMAP. I also contribute to the mission’s snow side: as Co-I on a NASA-funded project, I help build a multi-frequency InSAR phase data-assimilation framework for tracking seasonal snow water equivalent, aimed at the kind of repeat-pass InSAR NISAR is expected to support.https://xiaolan.in/publication/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/publication/Peer-reviewed publications and data products spanning snow, soil moisture, freeze–thaw, and the electromagnetic scattering physics underneath them.https://xiaolan.in/missions/smap/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/missions/smap/I’ve worked on SMAP since before launch in 2015, starting in graduate school. I lead development of the mission’s L-band freeze–thaw algorithm — from the original detection method, first validated on Aquarius, to the operational Level-3 Freeze/Thaw data record NASA distributes today. I’m first author on that data product and on the JSTARS paper introducing the Aquarius-based detection method it grew out of. I’m now carrying that L-band expertise into the next era: as PI of a five-year NASA ROSES award, I lead development of the joint SMAP–NISAR active-passive soil-moisture algorithm — the retrieval method the mission will use once NISAR L-band SAR data is available to fuse with SMAP’s radiometer measurements.https://xiaolan.in/research/snow/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/research/snow/For more than a decade I’ve worked on estimating how much water a snowpack holds — its snow water equivalent — from radar. More recent work uses the phase of radar signals across repeat passes (InSAR) to track seasonal snow. What ties the old and new threads together is the physics of how a microwave behaves once it enters a snowpack: scattering among the grains, bouncing between layers, and emerging carrying a record of the snow it passed through.https://xiaolan.in/research/soil-moisture/Mon, 01 Jan 0001 00:00:00 +0000https://xiaolan.in/research/soil-moisture/I develop the algorithms that read soil moisture from radar and radiometer measurements at L-band — the approach behind NASA’s SMAP mission, carried forward into the joint SMAP–NISAR algorithm, and extended to reflected navigation-satellite signals through CYGNSS, where I built JPL’s soil-moisture product. Across these missions the through-line is the same: a soil-moisture value is only as trustworthy as the wave physics that links the measured signal to the water in the ground.