How to estimate LAI in boreal forests?

How should we estimate leaf area index for a stand in a boreal forest? How much do the different LAI estimation methods actually differ? These are questions I’m often asked when people working in other fields need a quick way to get LAI for their study sites.

In an effort to tackle these questions, we pooled together our LAI data for nearly 700 stands measured during the past decade and compared a range of methods such as allometric equations, LAI-2000 measurements and inversion of a canopy radiation model. Even though we did not have the so-called true LAI (from destructive sampling) for these stands, we were still able to get an idea of how the different methods perform. Many ecosystem or growth models need LAI as an input variable, and therefore it is crucial to understand how using LAI data from different sources can affect the modeling results.

 

 Intercalibrating LAI-2000 units in an open area before making measurements in the forest.

 Titta measuring the LAI of a Scots pine stand using the LAI-2000 PCA instrument.

   

Which LAI estimation method should you use then? There is no simple, straight-forward recommendation; the optimal LAI estimation method depends on the spatial and temporal extent of the monitoring activity you will be doing. The optical LAI estimation methods are usually superior if your research focus is on seasonal or abrupt changes (e.g. defoliation or insect outbreaks) in foliage mass. In addition, optical measurements are relatively fast, inexpensive and less laborious than conventional forest inventories – if you have a camera with a hemispherical lens or an LAI-2000 Plant Canopy Analyzer at hand and are familiar with the theory behind them. For large area applications (such as regional or national LAI maps) a more suitable ground reference method is to use allometric equations based forestry databases. However, allometric equations cannot (currently) predict the seasonal development of LAI in a forest. They will only provide you with the peak growing season LAI which corresponds to the maximum foliage mass in a forest.

For more quantitative information, check out Titta’ s new paper:

Majasalmi, T., Rautiainen, M., Stenberg, P. & Lukes, P. 2013. An assessment of ground reference methods for estimating LAI of boreal forests. Forest Ecology and Management, 292: 10-18.

Tiedote: Kasvillisuuden kartoitus avaruudesta käsin muuttuu tarkemmaksi (in Finnish)

Tuoreessa kansainvälisessä tutkimuksessa kehitettiin uusi menetelmä maailmanlaajuiseen metsien kartoitukseen satelliittikuvien avulla. Menetelmä huomioi entistä tarkemmin metsien rakenteen vaikutuksen satelliittien mittaamaan metsien heijastukseen. Tutkimus julkaistaan joulukuun alussa yhdessä maailman arvovaltaisimmista tieteellisistä julkaisusarjoista, Yhdysvaltain tiedeakatemian lehdessä (Proceedings of the National Academy of Sciences of the United States of America, PNAS). Helsingin yliopiston tutkijat ovat olleet keskeisessä roolissa tutkimuksen suunnittelussa ja toteutuksessa.

Tutkimus kumoaa myös vallalla olleen käsityksen siitä, että kasvillisuudessa oleva typpi vaikuttaisi kasvillisuuden heijastamaan auringonsäteilyyn ja sitä kautta maapallon ilmastoon. Tutkimuksessa osoitettiin, että tämä väite perustui aineistojen virheelliseen tulkintaan.

 -Uudet tulokset sen sijaan osoittavat, että metsän lajikoostumus ja latvusrakenne määräävät heijastuneen säteilyn suuruuden, tarkentaa tutkimuksessa mukana ollut Helsingin yliopiston metsänarvioimistieteen professori Pauline Stenberg.

Tutkimuksessa tarkasteltiin kasvillisuuden heijastamaa lyhytaaltoista säteilyä lauhkealla ja havumetsävyöhykkeellä.

 -Metsän heijastama säteily riippui selvästi siitä, kuinka paljon lehti- tai havupuita alueella kasvoi. Lehtimetsät heijastivat huomattavasti enemmän kuin havumetsät, selittää akatemiatutkija Miina Rautiainen Helsingin yliopiston metsätieteiden laitokselta.

-Tuloksillamme on merkittävä rooli uusien hyperspektristen satelliittimissioiden suunnittelussa ja toteutuksessa Yhdysvalloissa ja Euroopassa, kertoo Helsingin yliopiston kaukokartoituksen dosentti Matti Mõttus.

Tulevan vuosikymmenen aikana on tarkoitus laukaista useita uusia satelliitteja, joissa on maapallon kasvillisuuden tilaa seuraavia hyperspektrisiä mittalaitteita. Näiden mittalaitteiden tuottamien aineistojen tulkintaan tarvitaan laskentamenetelmiä, joita on julkaistu tässä artikkelissa.


Artikkeli on luettavissa verkossa: http://www.pnas.org/content/early/2012/12/03/1210196109). Artikkeli on syntynyt Bostonin yliopiston ja Helsingin yliopiston yhteisen, NASA:n rahoittaman tutkimusprojektin puitteissa.

A Paper in PNAS - Hyperspectral Remote Sensing of Foliar Nitrogen Content

Our paper on remote sensing of foliar nitrogen was published in the highly esteemed 'Proceedings of the National Academy of Sciences of the United States of America' (PNAS) on December 4th. We were lucky to celebrate it with many of the co-authors who were with us at the AGU fall meeting in San Francisco. For those interested in what all this is about, please read our paper. It is available online: http://www.pnas.org/content/early/2012/12/03/1210196109

Physically based optical remote sensing: a teaching perspective

My current vacancy at the UEF is "university researcher", but "lecturer" would be more correct as far as early 2012 is concerned. At the moment, I'm running course "advanced remote sensing", which has a strong focus on laser scanning but also other topics such as satellite images, radars and photogrammetry are covered. Visiting experts give most of the lectures, and my job mostly consists of supervising the students in computer labs.

Last week dealt with a topic that was especially important to me: physically based optical remote sensing. In previous years, the physical approach was covered in two lectures, but I wanted to emphasize this part more - after all, the University of Helsinki has an entire course on it (thanks to LAIDetectives!). So first I gave an introductory lecture where the basic concepts from irradiance to LAI were discussed. In the following computer lab, the students analyzed a set of hemispherical canopy images and had to consider different uncertainties of the process.

The highlight of the week was certainly the two lectures given by Miina. The topics included different reflectance model types, global monitoring with MODIS, and finally an introduction to PARAS reflectance model. We restricted the amount of equations on purpose - when the audience consists of forestry students, either the math has to be simple, or plenty of time must be reserved for explaining it. Miina's part ended with a detailed derivation of the PARAS model equation on the whiteboard, so everyone who followed certainly got the main idea!

The physical week ended with a PARAS exercise, where the students used the model to simulate the spectra of two forest stands in Sodankylä with different types of ground reflectance. Finally, the results were compared with BRFs obtained from SPOT satellite. The level of difficulty was OK: first the students really had to study the model equation and see what it means, but finally everyone figured it out and got the exercise done in the given time. Hopefully they now have an understanding why the digital numbers of the forest pixels in a satellite image are what they are - I'll see that soon in the exam!

Looking back

This year has indeed been interesting. The thesis defence was certainly a highlight, but when it comes to personal development, teaching was the most important new challenge I faced. I started by teaching the basics of forest mensuration to our first year students in January. This information was then applied to practice as I was the assistant teacher at our forest mensuration field course. In the autumn, I continued by teaching the same bunch of students the basics of remote sensing. Congratulations to all of you who made it through! Hopefully some became interested in the forest inventory issues: for a teacher that would be the best recognition. Often the students seem to be overwhelmed by the technical stuff that is required in these courses, so few want to study it further.

Research was thus less in focus this year. Most of the time I spent dealing with lidar-based inventory of seedling stands; some working papers have already been delivered and a scientific article will follow later. In the field of canopy research my only output was to organize a new field campaign in Hyytiälä and participate in Ilkka's new field photogrammetry experiment. Now we have some quite unique new data sets; hopefully next year will bring time to squeeze everything out of them. However, before that there is some more (international) teaching to be done...

Happy holidays!

Two months in Switzerland

Research visits are an important part of my term as Academy of Finland Research Fellow. This year, my bodyguard and I spent February and March visiting the University of Zurich in Switzerland. My original plan for the visit had been to learn about the various activities going on at the Remote Sensing Laboratories and to see if there would be opportunities for future collaboration.

After a couple of days in Zurich the visit took new course -- active collaboration started immediately! The spectroscopy laboratories (especially the goniometerlab) were something we can only dream of in Helsinki, and my host, Michael, kindly offered us the opportunity to use the labs and to have help from a skilled technician. The offer was very tempting, and in a few days, a plan for an experiment was drawn together. We decided to develop a method for measuring the spectral albedo of coniferous shoots -- something that has not been reported in scientific literature prior to this. In collaboration with RSL's needle optics team, we were also able to measure needle spectral albedo for our study shoots. In addition, we did a detailed structural analysis of the shoots.

This all sounds very simple in a blog. But it wasn't! Just setting up the lab for measuring shoot albedo took us three weeks of intensive planning in a dark laboratory room. The measurements were another story -- we ended up working close to 10 hours per day in the lab and spending a couple of more hours per day preanalyzing the data. Didn't see much sunlight during those days...

The intensive period did pay off: we are now proud to present results from a unique study on the spectral properties of Scots pine shoots. We now have an idea of how needle spectral albedo scales up to shoot spectral albedo, what the scattering phase function of coniferous shoots looks like and how it affects canopy reflectance (and remote sensing of forests!).

Two papers presenting the results from our experiment have been accepted for publication during the past week. You can all enjoy them (soon online):

Rautiainen, M., Mõttus, M., Yáñez-Rausell, L., Homolová, L., Malenovský, Z. & Schaepman, M. 2011. A note on upscaling coniferous needle spectra to shoot spectral albedo. Remote Sensing of Environment, in press.

Mõttus, M., Rautiainen, M. & Schaepman, M. 2011. Shoot scattering phase function for
Scots pine and its effect on canopy reflectance. Agricultural and Forest Meteorology, in press.

(And this is what Switzerland looked like when we were not in the lab. )

New challenges

My thesis project was finally finished a month ago and now it is time to think of something new. May was really busy, because I had three projects going on simultaneously: preparing for final exams needed for PhD, planning the field campaign scheduled to start in June, and the seedling stand inventory project, for which I mainly work at the moment.

The seedling-laser project is aimed at predicting the seedling stand management need directly from laser data and aerial images. An expert forester determined management need categories (urgent / five years / no need) for each of 238 sample plots in our data. The problem is to make the supervised classification work so that this training data could be used to predict the management need for new stands. Basically, we need to determine which remotely sensed features provide the best class separability, and which analysis methods or models work the best. This is quite difficult, as the classes are defined subjectively and overlap heavily. Nevertheless, it seems to be possible to detect at least the recently managed stands, as well as the stands where conifer seedlings are heavily shadowed by rapidly growing deciduous species.

From the LAI Detectives' viewpoint, the Toplaser-project field measurements are more interesting, as they are a direct continuation for my earlier work with canopy measurements. Two students are working at Hyytiälä for two months - apparently I've become too well educated to work in the field for longer periods... First, they rephotograph the 2008 hemispherical image plots that has already been used in two papers by me and Janne. They also make tree level crown shape and transparency measurements. This data should be very useful for studying the canopy structure with full-waveform LiDAR data. There will be plenty of calculations and analysis next winter!

Juha measures crown shape

In addition, during the week I spent supervising the workers at Hyytiälä, I helped Ilkka to establish a special close-range photogrammetry experiment in the forest. We placed some calibration targets high into the canopy, measured their coordinates with a tacheometer, and took photos of them from carefully located image points. This should enable us to visualize the LiDAR waveforms in the images, like in this experimental photo where you can see the waveforms of some LiDAR pulses from the building and ground. Extremely interesting!

Intensity peaks at ground and roof edge

Calibration targets in up in the trees

Before my vacation starts in the middle of June, there's also some teaching in sight. I'll work as an assistant teacher in the field course for the UEF first-year forestry students at Mekrijärvi research station. The course is quite the same as it was back in 2002 when I passed it myself: students learn to use relascopes, calipers, hypsometers etc. It is interesting to see how the students are able to apply the theory taught in the winter in a real forest.

Have a nice summer!