Asynchronous canopy physiological and structural cycles reveal complex bimodal seasonality in the Congo rainforest - Qi Xie; Feng Tian; Torbern Tagesson; Lanhui Wang; Rasmus Fensholt; Xiaoye Tong; Hongxiao Jin; Xuanlong Ma; Zhanzhang Cai; Yujie Dou; Luwei Feng; Lars Eklundh (Agricultural and Forest Meteorology, 2026)

Contrasting roles of ground, trees, ponds and grazing in carbon dioxide, methane and nitrous oxide fluxes of an African semi-arid savanna - Aleksander Wieckowski; Patrik Vestin; Jonas Ardö; Olivier Roupsard; Ousmane Ndiaye; Seydina Ba; Claire Delon; Dominique Serça; Torbern Tagesson (Agriculture, Ecosystems & Environment, 2026)

Varying sensitivities of RED-NIR-based vegetation indices to the input reflectance affect the detected long-term trends - Qing Tian; Hongxiao Jin; Rasmus Fensholt; Torbern Tagesson; Luwei Feng; Feng Tian (ISPRS Journal of Photogrammetry and Remote Sensing, 2026)

Assessing the elevational synchronization in vegetation phenology across Northern Hemisphere mountain ecosystems under global warming - Chen Yang; Feng Tian; Hongxiao Jin; Rasmus Fensholt; Luwei Feng; Torbern Tagesson (Global and Planetary Change, 2025)

Satellite canopy water content from Sentinel-2, Landsat-8 and MODIS: Principle, algorithm and assessment - Hongliang Ma; Marie Weiss; Daria Malik; Beatrice Berthelot; Marta Yebra; Rachael H. Nolan; Arnaud Mialon; Jiangyuan Zeng; Xingwen Quan; Håkan Torbern Tagesson; Albert Olioso; Frederic Baret (Remote Sensing of Environment, 2025)

Eddy covariance measurements reveal a decreased carbon sequestration strength 2010–2022 in an African semiarid savanna - Aleksander Wieckowski; Patrik Vestin; Jonas Ardö; Olivier Roupsard; Ousmane Ndiaye; Ousmane Diatta; Seydina Ba; Yélognissè Agbohessou; Rasmus Fensholt; Wim Verbruggen; Haftay Hailu Gebremedhn; Torbern Tagesson (Global Change Biology, 2024)
Monitoring the changes of ecosystem functioning is pivotal for understanding the global carbon cycle. Despite its size and contribution to the global carbon cycle, Africa is largely understudied in regard to ongoing changes of its ecosystem functioning and their responses to climate change. One of the reasons is the lack of long‐term in situ data. Here, we use eddy covariance to quantify the net ecosystem exchange (NEE) and its components—gross primary production (GPP) and ecosystem respiration ( R eco ) for years 2010–2022 for a Sahelian semiarid savanna to study trends in the fluxes. Significant negative trends were found for NEE (12.7 ± 2.8 g C m 2 year −1 ), GPP (39.6 ± 7.9 g C m 2 year −1 ), and R eco (32.2 ± 8.9 g C m 2 year −1 ). We found that NEE decreased by 60% over the study period, and this decrease was mainly caused by stronger negative trends in rainy season GPP than in R eco . Additionally, we observed strong increasing trends in vapor pressure deficit, but no trends in rainfall or soil water content. Thus, a proposed explanation for the decrease in carbon sink strength is increasing atmospheric dryness. The warming climate in the Sahel, coupled with increasing evaporative demand, may thus lead to decreased GPP levels across this biome, and lowering its CO 2 sequestration.

Increasing global ecosystem respiration between 1982 and 2015 from Earth observation‐based modelling - Torbern Tagesson; Julia Kelly; Guy Schurgers; Feng Tian; Jonas Ardö; Stephanie Horion; Anders Ahlström; Stefan Olin; Rasmus Fensholt (Global Ecology and Biogeography, 2024)
Aim Earth observation‐based estimates of land–atmosphere exchange of carbon are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. Temperature, soil water content and gross primary production are the main drivers of ecosystem respiration (R eco ), and the main aims of this study are to develop an R eco model driven by long‐term global‐scale Earth observations and to study R eco spatiotemporal dynamics 1982–2015. Location Global scale. Time Period 1982–2015. Major Taxa Studied Terrestrial ecosystems. Methods We parameterized and applied a global R eco model for 1982–2015 using novel Earth observation‐based data. We studied the relationships between R eco measured at field sites globally and land surface temperature, gross primary production and soil water content. Trends 1982–2015 were quantified, and the contributions from terrestrial regions to the spatiotemporal variability were evaluated. Results The R eco model (LGS‐R eco ) captured the between‐site and intra‐ and interannual variability in field‐observed R eco and soil respiration well in comparison with other Earth observation‐based products. The global annual R eco was on average 105.6 ± 2.3 Pg C for 1982–2015, which is close to 105 Pg C according to residuals of the carbon exchange processes within the global carbon budgets. The trend in global terrestrial R eco 1982–2015 was 0.19 ± 0.02 Pg C y −1 , with the strongest positive trends found in cropland areas, whereas negative trends were primarily observed for savannah/shrublands of Southern Africa and South America. Trends were especially strong during the eighties and nineties, but substantially smaller 1998–2015. Main Conclusions The LGS‐R eco model revealed a substantial increase in global R eco during recent decades. However, the growth rates of global R eco were slower during 1998–2015, partially explaining the reduced growth rates of atmospheric CO 2 during this period. The LGR‐Reco product may be an essential source for studying carbon sources and sinks and functioning of the Earth system.

Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration - Xiuli Xing; Mousong Wu; Wenxin Zhang; Weimin Ju; Torbern Tagesson; Wei He; Songhan Wang; Jun Wang; Lu Hu; Shu Yuan; Tingting Zhu; Xiaorong Wang; et al. (Agricultural and Forest Meteorology, 2023)

To what extent are greenhouse-gas emissions offset by trees in a Sahelian silvopastoral system? - Yélognissè Agbohessou; Claire Delon; Eric Mougin; Manuela Grippa; Torbern Tagesson; Moussa Diedhiou; Seydina Ba; Daouda Ngom; Rémi Vezy; Ousmane Ndiaye; Mohamed H. Assouma; Mamadou Diawara; et al. (Agricultural and Forest Meteorology, 2023)

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions - Christin Abel; Abdulhakim M. Abdi; Torbern Tagesson; Stephanie Horion; Rasmus Fensholt (Global Change Biology, 2023)
Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor‐pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water‐related stress as compared to areas not exposed to water‐related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non‐stressed systems. Conversely, opposite relationships were found for soil parameters such as root‐zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water‐related stress (or no stress) is important, for example within management strategies to maintain and restore dryland vegetation.

Convergence and divergence emerging in climatic controls of polynomial trends for northern ecosystem productivity over 2000–2018 - Wenxin Zhang; Hongxiao Jin; Sadegh Jamali; Zheng Duan; Mousong Wu; Youhua Ran; Jonas Ardö; Lars Eklundh; Anna Maria Jönsson; Huaiwei Sun; Guojie Hu; Xiaodong Wu; et al. (Science of The Total Environment, 2023)

Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget - Jennifer D. Watts; Mary Farina; John S. Kimball; Luke D. Schiferl; Zhihua Liu; Kyle A. Arndt; Donatella Zona; Ashley Ballantyne; Eugénie S. Euskirchen; Frans‐Jan W. Parmentier; Manuel Helbig; Oliver Sonnentag; et al. (Global Change Biology, 2023)
Arctic‐boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic‐boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration ( R eco ), net ecosystem CO 2 exchange (NEE; R eco − GPP), and terrestrial methane (CH 4 ) emissions for the Arctic‐boreal zone using a satellite data‐driven process‐model for northern ecosystems (TCFM‐Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM‐Arctic to obtain daily 1‐km 2 flux estimates and annual carbon budgets for the pan‐Arctic‐boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO 2 ‐C year −1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH 4 emissions from tundra and boreal wetlands (not accounting for aquatic CH 4 ) were estimated at 35 Tg CH 4 ‐C year −1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high‐latitude carbon status and also indicates a continued need for integrated site‐to‐regional assessments to monitor the vulnerability of these ecosystems to climate change.

Assessing the upper elevational limits of vegetation growth in global high-mountains - Linqing Zou; Feng Tian; Tianchen Liang; Lars Eklundh; Xiaoye Tong; Torbern Tagesson; Yujie Dou; Tao He; Shunlin Liang; Rasmus Fensholt (Remote Sensing of Environment, 2023)

Reliability of using vegetation optical depth for estimating decadal and interannual carbon dynamics - Yujie Dou; Feng Tian; Jean-Pierre Wigneron; Torbern Tagesson; Jinyang Du; Martin Brandt; Yi Liu; Linqing Zou; John S. Kimball; Rasmus Fensholt (Remote Sensing of Environment, 2023)

Global maps of soil temperature - Jonas J. Lembrechts; Johan van den Hoogen; Juha Aalto; Michael B. Ashcroft; Pieter De Frenne; Julia Kemppinen; Martin Kopecký; Miska Luoto; Ilya M. D. Maclean; Thomas W. Crowther; Joseph J. Bailey; Stef Haesen; et al. (Global Change Biology, 2022)
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km 2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km 2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties - Anna‐Maria Virkkala; Juha Aalto; Brendan M. Rogers; Torbern Tagesson; Claire C. Treat; Susan M. Natali; Jennifer D. Watts; Stefano Potter; Aleksi Lehtonen; Marguerite Mauritz; Edward A. G. Schuur; John Kochendorfer; et al. (Global Change Biology, 2021)
The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.

A physiology‐based Earth observation model indicates stagnation in the global gross primary production during recent decades - Torbern Tagesson; Feng Tian; Guy Schurgers; Stephanie Horion; Robert Scholes; Anders Ahlström; Jonas Ardö; Alvaro Moreno; Nima Madani; Stefan Olin; Rasmus Fensholt (Global Change Biology, 2021)
Earth observation‐based estimates of global gross primary production (GPP) are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. In this study, we attempt an ecosystem‐level physiological approach of estimating GPP using an asymptotic light response function (LRF) between GPP and incoming photosynthetically active radiation (PAR) that better represents the response observed at high spatiotemporal resolutions than the conventional light use efficiency approach. Modelled GPP is thereafter constrained with meteorological and hydrological variables. The variability in field‐observed GPP, net primary productivity and solar‐induced fluorescence was better or equally well captured by our LRF‐based GPP when compared with six state‐of‐the‐art Earth observation‐based GPP products. Over the period 1982–2015, the LRF‐based average annual global terrestrial GPP budget was 121.8 ± 3.5 Pg C, with a detrended inter‐annual variability of 0.74 ± 0.13 Pg C. The strongest inter‐annual variability was observed in semi‐arid regions, but croplands in China and India also showed strong inter‐annual variations. The trend in global terrestrial GPP during 1982–2015 was 0.27 ± 0.02 Pg C year −1 , and was generally larger in the northern than the southern hemisphere. Most positive GPP trends were seen in areas with croplands whereas negative trends were observed for large non‐cropped parts of the tropics. Trends were strong during the eighties and nineties but levelled off around year 2000. Other GPP products either showed no trends or continuous increase throughout the study period. This study benchmarks a first global Earth observation‐based model using an asymptotic light response function, improving simulations of GPP, and reveals a stagnation in the global GPP after the year 2000.

Revealing turning points in ecosystem functioning over the Northern Eurasian agricultural frontier - Stéphanie Horion; Alexander V. Prishchepov; Jan Verbesselt; Kirsten de Beurs; Torbern Tagesson; Rasmus Fensholt (Global Change Biology, 2016)
The collapse of the Soviet Union in 1991 has been a turning point in the World history that left a unique footprint on the Northern Eurasian ecosystems. Conducting large scale mapping of environmental change and separating between naturogenic and anthropogenic drivers is a difficult endeavor in such highly complex systems. In this research a piece‐wise linear regression method was used for breakpoint detection in Rain‐Use Efficiency ( RUE ) time series and a classification of ecosystem response types was produced. Supported by earth observation data, field data, and expert knowledge, this study provides empirical evidence regarding the occurrence of drastic changes in RUE (assessment of the timing, the direction and the significance of these changes) in Northern Eurasian ecosystems between 1982 and 2011. About 36% of the study area (3.4 million km 2 ) showed significant ( P RUE during the observation period. A large proportion of detected turning points in RUE occurred around the fall of the Soviet Union in 1991 and in the following years which were attributed to widespread agricultural land abandonment. Our study also showed that recurrent droughts deeply affected vegetation productivity throughout the observation period, with a general worsening of the drought conditions in recent years. Moreover, recent human‐induced turning points in ecosystem functioning were detected and attributed to ongoing recultivation and change in irrigation practices in the Volgograd region, and to increased salinization and increased grazing intensity around Lake Balkhash. The ecosystem‐state assessment method introduced here proved to be a valuable support that highlighted hotspots of potentially altered ecosystems and allowed for disentangling human from climatic disturbances.

Global‐scale mapping of changes in ecosystem functioning from earth observation‐based trends in total and recurrent vegetation - Rasmus Fensholt; Stéphanie Horion; Torbern Tagesson; Andrea Ehammer; Eva Ivits; Kjeld Rasmussen (Global Ecology and Biogeography, 2015)
Aim To evaluate trend analysis of earth observation ( EO ) dense time series as a new way of describing and mapping changes in ecosystem functioning at regional to global scales. Spatio‐temporal patterns of change covering 1982–2011 are discussed in the context of changes in land use and land cover ( LULCC ). Location Global. Methods This study takes advantage of the different phenological cycles of recurrent vegetation (herbaceous vegetation) and persistent vegetation (woody/shrub cover) in combining trend analyses of global‐scale vegetation based on different annual/seasonal normalized difference vegetation index ( NDVI ) metrics. Spatial patterns of combined vegetation trends derived from the G lobal I nventory M odeling and M apping S tudies NDVI are analysed using land‐cover information ( GLC 2000). Results The direction of change in annual and seasonal NDVI metrics is similar for most global terrestrial ecosystems, but areas of diverging trends were also observed for certain regions across the globe. These areas are shown to be dominated by land‐cover classes of deciduous forest in tropical/subtropical areas. Areas of observed change are found in dry deciduous forest in South America and central southern Africa and are in accordance with studies of hotspot LULCC areas conducted at local and regional scales. The results show that dense time series of EO data can be used to map large‐scale changes in ecosystem functional type that are due to forest cover dynamics, including forest degradation, deforestation/reforestation and bush encroachment. Main conclusions We show that areas characterized by changes in ecosystem functioning governed by LULCC at regional and global scales can be mapped from dense time series of global EO data. The patterns of diverging NDVI metric trends can be used as a reference in evaluating the impacts of environmental changes related to LULCC and the approach may be used to detect changes in ecosystem functioning over time.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability - Torbern Tagesson; Rasmus Fensholt; Idrissa Guiro; Mads Olander Rasmussen; Silvia Huber; Cheikh Mbow; Monica Garcia; Stéphanie Horion; Inge Sandholt; Bo Holm‐Rasmussen; Frank M. Göttsche; Marc‐Etienne Ridler; et al. (Global Change Biology, 2015)
The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index ( NDVI ), hyperspectral characteristics (350–1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation ( FAPAR ), biomass, vegetation water content, and land‐atmosphere exchanges of carbon ( NEE ) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE , with high values of ~−7.5 g C m −2 day −1 during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata . This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350–1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models.

Using earth observation-based dry season NDVI trends for assessment of changes in tree cover in the Sahel - Stéphanie Horion; Rasmus Fensholt; Torbern Tagesson; Andrea Ehammer (International Journal of Remote Sensing, 2014)

Land‐atmosphere exchange of methane from soil thawing to soil freezing in a high‐ A rctic wet tundra ecosystem - Torbern Tagesson; Meelis Mölder; Mikhail Mastepanov; Charlotte Sigsgaard; Mikkel P. Tamstorf; Magnus Lund; Julie M. Falk; Anders Lindroth; Torben R. Christensen; Lena Ström (Global Change Biology, 2012)
The land‐atmosphere exchange of methane ( CH 4 ) and carbon dioxide ( CO 2 ) in a high‐ A rctic wet tundra ecosystem ( R ylekærene) in Z ackenberg, north‐eastern G reenland, was studied over the full growing season and until early winter in 2008 and from before snow melt until early winter in 2009. The eddy covariance technique was used to estimate CO 2 fluxes and a combination of the gradient and eddy covariance methods was used to estimate CH 4 fluxes. Small CH 4 bursts were observed during spring thawing 2009, but these existed during short periods and would not have any significant effect on the annual budget. Growing season CH 4 fluxes were well correlated with soil temperature, gross primary production, and active layer thickness. The CH 4 fluxes remained low during the entire autumn, and until early winter. No increase in CH 4 fluxes were seen as the soil started to freeze. However, in autumn 2008 there were two CH 4 burst events that were highly correlated with atmospheric turbulence. They were likely associated with the release of stored CH 4 from soil and vegetation cavities. Over the measurement period, 7.6 and 6.5 g C m −2 was emitted as CH 4 in 2008 and in 2009, respectively. R ylekærene acted as a C source during the warmer and wetter measurement period 2008, whereas it was a C sink for the colder and drier period of 2009. Wet tundra ecosystems, such as R ylekærene may thus play a more significant role for the climate in the future, as temperature and precipitation are predicted to increase in the high‐ A rctic.

Applicability of leaf area index products for boreal regions of Sweden - Torbern Tagesson; Lars Eklundh; Anders Lindroth (International Journal of Remote Sensing, 2009)