- Multispectral analysis of the Tres Cantos wildfire with Sentinel-2 data
A few days ago, I posted about a recent wildfire in Tres Cantos, Madrid, Spain, sharing images of Pléiades Neo and Sentinel-2 that showed the extent of the fire. Since the Sentinel-2 data products can be downloaded for free and they include multispectral data covering 13 bands including visible, near infrared and short wave infrared spectrum, I have decided to do an analysis of this data. There are two main goals to this. The first is to learn. I have never done this before. It is an interesting topic, and I mostly learn by doing. So bare with me that although all my results seem to make sense, I could have made some mistakes or done something in a suboptimal way.
The second is to understand how badly the holm oak woodland in “Monte de Viñuelas” has been burnt. In the previous post I explained that this is a 30 km² estate and that a large part of it has been hit by the fire. From the wall that borders the estate I can see that the oaks that are near the wall have not burnt, but the grass in the ground has burnt completely. The leaves on these oaks are mostly fine. Some of them might wither with time if the fire has killed the tree (in some previous smaller fires I have seen that if the fire has killed only part of the tree, just that part will wither). Here are some images published by a hunting journal showing how some of these areas look like a few days after the fire.
However, deeper into the woodlands there seems to be more damage and trees burnt completely. This is not so easy to see from the wall, and I cannot just walk in, as it is private land. Aerial photography would be best, but without it, satellite imagery is the next best thing. It is hard to tell how large the damage is from the visible spectrum imagery, but as we will see in this post, the infrared bands have much more information.
- Tres Cantos wildfire
This post is going to be slightly unusual for the topics of this blog, because there is no RF, but nevertheless there is space-based remote sensing, which fits somewhat well with the things I usually write about. I wanted to write down this information somewhere, and it was too long for a series of tweets.
As some of you might have heard in the news, there has been a large wildfire in Tres Cantos, Madrid, Spain, which is the city where I live. This has even been featured in international news. First of all, I am okay, as are all the family and friends I have in the city. The fire broke out on 2025-08-11 17:45 UTC (19:45 local time) and by the next morning its perimeter was already contained. As of writing this post on the morning of 2025-08-13, the fire is almost put out and is considered to be controlled. We have been lucky that a fire so close to the city has caused relatively low damage. I am not keeping a tally, but what I heard is: one person’s life, a few houses in the borders of the city, as well as a few countryside houses and sheds, the King’s College British school, and the 17th century Viñuelas castle, as well as part of the castle grounds, which consist of 3000 hectares of holm oak woodland, commonly known as “Monte de Viñuelas”.
Since I woke up on the morning of 2025-08-12, I have been very interested in understanding which area has been affected by the fire. The information I could see in Google maps, and even in some news articles (which could have been based off Google maps) didn’t quite match what I had seen in pictures and videos shared in social media, as well as what I saw by driving on the streets bordering the town. An official map has not been published, as far as I know. So I have been keeping an eye on space-based imagery platforms to see when the first images taken on 2025-08-12 would pop up. I don’t use these services frequently, so this has also helped me get up to speed on the current constellations, platforms and services. This is the topic of this post.
- n78 band 5G NR recordings
In my last post about 5G NR, which was part of a series in which I analyzed the signals in a short recording of an idle srsRAN gNB, I mentioned that I had already decoded all the signals that appear in the recording, and that to move on with my 5G series I would need to make and use some more complex real world recordings next.
A 5G band I’m particularly interested in is n78 (3.3 – 3.8 GHz TDD). This is being used to deploy 5G in many European countries, including Spain, as showed by this list in Wikipedia. Due to the large bandwidth available, it is common to see cells with 100 MHz bandwidth in this band.
- Galileo OSNMA chain renewal
Galileo OSNMA (open service navigation message authentication) is a cryptographic system that is used to authenticate the navigation message (satellite ephemeris and clocks, etc.) in the Galileo GNSS. I have spoken before about OSNMA in this blog, since I implemented an OSNMA library in Rust a few years back. A good introduction to OSNMA for readers unfamiliar with how it works can be found in Bert Hubert‘s short series of OSNMA posts. The OSNMA system is currently in the public observation test phase.
On July 4, an OSNMA live test notification went out with the following message:
EVENT DESCRIPTION: USERS ARE ADVISED THAT, AS PART OF THE PUBLIC OBSERVATION TEST PHASE ACTIVITIES, A TESLA CHAIN RENEWAL IS PLANNED ON 2025-07-07 10:00 UTC AND THE TRANSITION WILL OCCUR ON 2025-07-08 10:00 UTC. THE TESLA CHAIN RENEWAL PROCESS IS DESCRIBED IN THE OSNMA SIS ICD (LINK).
NOTE THAT USER RECEIVERS SHALL PREVENT THE USE OF ANY CHAIN THAT HAS BEEN SUBJECT TO A RENEWAL PROCESS.
I have used the utilities from the Galmon project to record the Galileo INAV data received by a uBlox GNSS receiver that I have at home. This dataset can be used to test OSNMA implementations and to study how the chain renewal was done. The dataset is publised in Zenodo as “Galileo INAV data for OSNMA chain renewal test in July 2025“. In this post I study the chain renewal using my galileo-osnma Rust implementation.
- About FLLs with band-edge filters
Using band-edge filters for carrier frequency recovery with an FLL is an interesting technique that has been studied by fred harris and others. Usually this technique is presented for root-raised cosine waveforms, and in this post I will limit myself to this case. The intuitive idea of a band-edge FLL is to use two filters to measure the power in the band edges of the signal (the portion of the spectrum where the RRC frequency response rolls off). If there is zero frequency error, the powers will be equal. If there is some frequency error, the signal will have more “mass” in one of the two filters, so the power difference can be used as an error discriminant to drive an FLL.
The band-edge FLL is presented briefly in Section 13.4.2 of fred harris’ Multirate Signal Processing for Communication Systems book. Additionally, fred also gave a talk at GRCon 2017 that was mainly focused on how band-edge filters can also be used for symbol timing recovery, but the talk also goes through the basics of using them for carrier frequency recovery. Some papers that are referenced in this talk are fred harris, Elettra Venosa, Xiaofei Chen, Chris Dick, Band Edge Filters Perform Non Data-Aided Carrier and Timing Synchronization of Software Defined Radio QAM Receivers and fred harris, Band Edge Filters: Characteristics and Performance in Carrier and Symbol Synchronization.
Recently I was looking into band-edge FLLs and noticed some problems with the implementation of the FLL Band-Edge block in GNU Radio. In this post I go through a self-contained analysis of some of the relevant math. The post is in part intended as background information for a pull request to get these problems fixed, but it can also be useful as a guideline for implementing a band-edge FLL outside of GNU Radio.
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