Metsien kartoitus ja seuranta aktiivisella 3D-kaukokartoituksella

The main aim in forest mapping and monitoring is to produce accurate information for forest managers with the use of efficient methodologies. For example, it is important to locate harvesting sites and stands where forest operations should be carried out as well as to provide updates regarding forest growth, among other changes in forest structure. In recent years, remote sensing (RS) has taken a significant technological leap forward. It has become possible to acquire three-dimensional (3D), spatially accurate information from forest resources using active RS methods. In practical applications, mainly 3D information produced by airborne laser scanning (ALS) has opened up groundbreaking potential in natural resource mapping and monitoring. In addition to ALS, new satellite radars are also capable of acquiring spatially accurate 3D information. The main objectives of the present study were to develop 3D RS methodologies for large-area forest mapping and monitoring applications. In substudy I, we aim to map harvesting sites, while in substudy II, we monitor changes in the forest canopy structure. In studies III-V, efficient mapping and monitoring applications were developed and tested. In substudy I, we predicted plot-level thinning maturity within the next 10-year planning period. Stands requiring immediate thinning were located with an overall accuracy of 83%-86% depending on the prediction method applied. The respective prediction accuracy for stands reaching thinning maturity within the next 10 years was 70%-79%. Substudy II addressed natural disturbance monitoring that could be linked to forest management planning when an ALS time series is available. The accuracy of the damaged canopy cover area estimate varied between -16.4% to 5.4%. Substudy II showed that changes in the forest canopy structure can be monitored with a rather straightforward method by contrasting bi-temporal canopy height models. In substudy III, we developed a RS-based forest inventory method where single-tree RS is used to acquire modelling data needed in area-based predictions. The method uses ALS data and is capable of producing accurate stand variable estimates even at the sub-compartment level. The developed method could be applied in areas with sparse road networks or when the costs of fieldwork must be minimized. The method is especially suitable for large-area biomass or stem volume mapping. Based on substudy IV, the use of stereo synthetic aperture radar (SAR) satellite data in the prediction of plot-level forest variables appears to be promising for large-area applications. In the best case, the plot-level stem volume (VOL) was predicted with a relative error (RMSE%) of 34.9%. Typically, such a high level of prediction accuracy cannot be obtained using spaceborne RS data. Then, in substudy V, we compared the aboveground biomass and VOL estimates derived by radargrammetry to the ALS estimates. The difference between the estimation accuracy of ALS based and TerraSAR X based features was smaller than in any previous study in which ALS and different kinds of SAR materials have been compared. In this thesis, forest mapping and monitoring applications using active 3D RS were developed. Spatially accurate 3D RS enables the mapping of harvesting sites, the monitoring of changes in the canopy structure and even the making of a fully RS-based forest inventory. ALS is carried out at relatively low altitudes, which makes it relatively expensive per area unit, and other RS materials are still needed. Spaceborne stereo radargrammetry proved to be a promising technique to acquire additional 3D RS data efficiently as long as an accurate digital terrain model is available as a ground-surface reference.Metsien kartoitus ja seuranta aktiivisella 3D-kaukokartoituksella. Metsävaroista kerätään mahdollisimman tarkkaa tietoa metsänomistajan päätöksenteon tueksi. Tietoa kerätään puustotunnusten lisäksi toimenpidekohteista ja metsässä tapahtuvista muutoksista, kuten kasvusta ja luonnontuhoista. Laajojen metsäalueiden kartoituksessa käytetään apuna lentokoneesta tai satelliiteista tehtävää kaukokartoitusta. Metsien kaukokartoitus on viime vuosina ottanut merkittävän kehitysaskeleen, kun aktiiviset 3D-kaukokartoitusmenetelmät ovat yleistyneet. Aktiivisessa kaukokartoituksessa, kuten laserkeilauksessa ja tutkakuvauksessa instrumentti vastaanottaa lähettämäänsä säteilyä. Laserkeilaus tuottaa kohteesta 3D-havaintoja, jotka metsäalueilla kuvaavat suoraan puuston pituutta ja metsän tiheyttä. Laserkeilauksella kohteesta saadaan tällä hetkellä tyypillisesti 0,5−20 havaintoa/m2. Laserkeilaus tehdään lentokoneesta 500−3000 m korkeudesta, jolloin aineiston hankinta laajoilta alueilta on kallista verrattuna satelliittikuviin. Myös satelliittitutkakuvilta voidaan tuottaa spatiaalisesti tarkkaa 3D-tietoa, jonka pistetiheys on tosin huomattavasti harvempaa kuin laserkeilauksella. Tutkimuksessa kehitettiin sovelluksia metsien kartoitukseen ja seurantaan hyödyntäen aktiivisia 3D-kaukokartoitusmenetelmiä. Metsiköiden toimenpidetarvetta ennustettiin onnistuneesti laserkeilausaineiston avulla. Harvennettaviksi luokitellut metsiköt pystyttiin kartoittamaan 70%−86% tarkkuudella. Kahden ajankohdan laserkeilausaineistoja käytettiin lumituhojen vuoksi vaurioituneiden puiden kartoittamiseen. Tuhoutuneen latvuspinta-alan kartoitus perustui laserkeilausaineistosta tuotettujen latvusmallien erotuskuviin. Kehitetty menetelmä soveltuu latvusrakenteessa tapahtuneiden muutosten, kuten lumi- ja tuulituhojen, kartoittamiseen ja seurantaan. Laajojen metsäalueiden kartoitus perustuu yleensä kaksivaiheeseen inventointimenetelmään, jossa käytetään maastomittauksia ja tiedon yleistyksessä kaukokartoitusaineistoa. Kartoitusta voidaan tehostaa joko maastomittauksia vähentämällä tai hyödyntämällä mahdollisimman halpaa kaukokartoitusaineistoa. Tutkimuksessa kehitettiin täysin kaukokartoitukseen perustuva kaksivaiheinen metsien inventointimenetelmä. Tarvittava maastotieto mitattiin suoraan laserkeilausaineistosta. Menetelmä soveltuu puuston tilavuuden tai biomassan kartoitukseen erityisesti alueille, joilla maastomittausten kustannukset ovat merkittävät. Satelliittitutkakuvat ovat potentiaalinen aineisto etenkin laajojen alueiden metsävarojen seurannassa. Synteettisen apertuurin tutka (SAR)-stereokuvilta mitattiin automaattisesti 3D-pisteitä, joita käytettiin puustotunnusten ennustamisessa. Keskitilavuus ennustettiin parhaimmillaan lähes samalla tarkkuudella kuin laserkeilauksella. Tutkimus osoitti aktiivisen 3D-kaukokartoitustiedon mahdollistavan entistä yksityiskohtaisemman metsien kartoituksen ja seurannan

Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery

Peer reviewe

Forest inventory attribute estimation using airborne laser scanning, aerial stereoimagery, radargrammetry and interferometry - Finnish experiences of the 3D techniques

Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry and interferometry. Airborne stereo imagery can be used in deriving photogrammetric point clouds, as very-high-resolution synthetic aperture radar (SAR) data are used in radargrammetry and interferometry. ALS is capable of mapping both the terrain and tree heights in mixed forest conditions, which is an advantage over aerial images or SAR data. However, in many jurisdictions, a detailed ALS-based digital terrain model is already available, and that enables linking photogrammetric or SAR-derived heights to heights above the ground. In other words, in forest conditions, the height of single trees, height of the canopy and/or density of the canopy can be measured and used in estimation of forest inventory attributes. In this paper, first we review experiences of the use of digital stereo imagery and spaceborne SAR in estimation of forest inventory attributes in Finland, and we compare techniques to ALS. In addition, we aim to present new implications based on our experiences

Estimating site index from short term TanDEM-X canopy height models

The tree height growth from three vegetation seasons was fitted to height growth curves in order to estimate the site index, which is a variable related to forest site productivity. The tree height growth was evaluated for four different cases, in which remote sensing data from TanDEM-X and airborne laser scanning were used. The used method requires a digital terrain model and knowledge about the tree species. Furthermore, the remote sensing data were calibrated using Lorey'smean height heights or airborne laser scanning data. It was found that four annual acquisitions of calibrated TanDEM-X data covering three vegetation seasons could be used for estimating the site index on 27 0.5-ha field plots with 4.4-m (12.1%) RMSE. The site index could in a similarmanner be estimated from only two airborne laser scanning acquisitions, before and after four vegetation seasons, with 2.3-m (6.3%) RMSE

Forecasting of ALS data using TanDEM-X

För att ha möjlighet att sköta skogen på ett hållbart sätt krävs att vi har tillgång till tillförlitligt data om det skogliga tillståndet. Fjärranalys är och kommer vara en allt viktigare teknik för att tillägna sig denna information på ett kostnadseffektivt sätt och med önskad kvalitet. Satellitburen radar har visat sig ha potential för insamling av information om det skogliga tillståndet. Satellitparet TanDEM-X och TerraSAR-X levererar InSAR (Interferometric synthetic aperture radar) data med möjlighet till beräkning av en tredje dimension och potential för goda skattningar, med hög temporal upplösning. I detta arbete presenteras en metod för att väga samman en tidsserie av radarbilder tagna med TanDEM-X konstellationen och utifrån bilderna skriva fram skattningar utförda med en laserskanning från år 2010. Genom att nyttja flera radarbilder förväntas skattningsresultatet förbättras, ett antagande som testades genom att längden av tidsserien med radarbilder varierades. Studien utfördes på försöksfastigheten Remningstorp i Västra Götaland och som referensdata användes cirkulära ytor med en radie av 10 meter och 40 meter, inventerade år 2010 och 2014. Om 14 radarbilder tagna under perioden 2011 till 2014 används tillsammans med laserskanningen utförd år 2010, skattas den grundytevägda höjden med ett RMSE på 5,9% och volymen med ett RMSE på 18,2%, för skattningar på beståndsnivå år 2014. Skattningarna gynnades av en längre tidsserie bilder. Framskrivningsmetodiken som är beskriven i denna rapport visar god potential för framskrivning av skogliga skattningar, men behöver utvecklas ytterligare före den kan rekommenderas för praktisk tillämpning inom skogsinventering.To be able to manage the forest in a sustainable manner, we need to have access to reliable data of the forest condition. Remote sensing is and will be an important technique to obtain this information in a cost effective way and with the required quality. Satellite-borne radar has shown to have potential for collecting this information. The Satellite mission TanDEM-X and TerraSAR-X delivers InSAR (Interferometric synthetic aperture radar) data with potential for three dimensional calculations and good estimates, with high temporal resolution. This work presents a method for updating forest parameters from a time series of radar images acquired with the TanDEM-X constellation and a laser scanning from 2010. By using a longer time series of radar images the estimation quality is expected to be improved, an assumption that was tested by changing the length of the time series of radar images. The test site in this study was Remningstorp in southern Sweden and as reference data circular plots with a radius of 10 meter and 40 meter, inventoried in 2010 and 2014, were used. When 14 radar images acquired during the period 2011 to 2014 are used in combination with a laser scanning from 2010, the estimation quality for Lorey´s mean height hade a RMSE of 5.9% and for volume a RMSE of 18.2%, for estimation on stand level in 2014. The estimation quality improved when a longer time-series of radar images were used. The method described in this article shows good potential for forecasting forest variables, but need further development before it can be recommended for practical use in forest inventory

Analysis of seasonal variations for estimation of forest variables with InSAR technology

Skogen är viktig på många sätt, eftersom skog är en resurs både som råvara, energikälla och kolsänka. För kontroll av tillväxt, avgång och planering av skog och skogsskötsel har man historiskt genomfört inventering med manuella metoder genom fältpersonal, vilket både är kostsamt och endast ger en bedömning om skogens tillstånd just i de ögonblick skogen inventeras. De senaste tio åren har metoder baserade på fjärranalys implementerats på många sätt, för bättre och effektivare inventering. Skattningar av skogliga variabler med laserdata har uppvisat hög noggrannhet med god kvalité, men det är ett dilemma att skanningen är kostsam och att utförd skanning snabbt blir oanvändbar när skogen förändras. Satellitburna sensorer som genererar tredimensionella data över skogen har potentialen att ge tillräckligt bra skattningskvalitét, inte minst för att skriva fram befintliga skattningarna, dessa data kan även kombineras med andra skattningstekniker och metoder. Fördelen med satellitburna sensorer är att de kontinuerligt återkommer över samma område på kort tid. I denna studie har data från satellitkonstellationen TanDEM-X använts. Interferometrisk Synthetic Aperture Radar (InSAR) är en radarteknik som satelliterna i TanDEM-X möjliggör. Studier som använt sig av InSAR teknik uppvisar mycket goda skattningsresultat för både höjd och biomassa (Persson & Fransson, 2014a). I flera tidigare studier diskuteras det om säsongs- och vädervariationer eventuellt kan påverka kvalitén på InSAR data. Denna studies syfte har varit att analysera faktorer som kan tänkas påverka InSAR data för skogliga skattningar. Med belägg från andra studier (Solberg m.fl, 2015) kan det i denna studie konstateras att temperatur påverkar skattningar av skogliga variabler med InSAR.The forest is important in many ways because it is a resource as raw material, energy and a carbon sink. For monitoring of growth, mortality and forest management activities, historically forest inventory has been done by field staff, which is costly and only provides an assessment of forest condition at the time of inventory. The last ten years, methods based on remote sensing have been implemented in many ways, for better and more efficient inventory. Estimates of forest variables with airborne laser scanning data have provided high accuracy with good quality, but it´s a problem that scanning is costly and that the data quickly become useless when the forest is changing. Studies show that satellite-borne sensor techniques can provide good quality forest estimations, or can be combined with other estimation techniques and methods. The advantage of satellite-borne sensors is that they return to the same area over short time periods. In this study, data from the satellite constellation TanDEM-X is used. Interferometric Synthetic Aperture Radar (InSAR) is a radar technique that is possible due to the configuration of the TanDEM-X satellites. Studies that use the InSAR technique exhibit very good estimation results of both height and biomass (Persson & Fransson, 2014a). In several previous studies it is discussed whether there are seasonal and weather variations that affect the quality of the InSAR data. The purpose of this study was to analyze the factors that may affect InSAR data for estimating forest variables. This study, together with evidence from previous studies (Solberg m.fl, 2015) provides support for the conclusion that temperature affects the estimates of forest variables when using InSAR

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version