Browsing by Subject "COVER"

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  • Wang, Yanhao; Li, Yuchen; Wong, Raymond Chi-Wing; Tan, Kian-Lee (IEEE, 2021)
    IEEE International Conference on Data Engineering
    Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation. The k-regret minimizing set (k-RMS) problem was recently proposed for representative tuple discovery. Specifically, for a large database P of tuples with multiple numerical attributes, the k-RMS problem returns a size-r subset Q of P such that, for any possible ranking function, the score of the top-ranked tuple in Q is not much worse than the score of the k th-ranked tuple in P. Although the k-RMS problem has been extensively studied in the literature, existing methods are designed for the static setting and cannot maintain the result efficiently when the database is updated. To address this issue, we propose the first fully-dynamic algorithm for the k-RMS problem that can efficiently provide the up-to-date result w.r.t. any tuple insertion and deletion in the database with a provable guarantee. Experimental results on several real-world and synthetic datasets demonstrate that our algorithm runs up to four orders of magnitude faster than existing k-RMS algorithms while providing results of nearly equal quality.
  • Amara, Edward; Adhikari, Hari; Heiskanen, Janne; Siljander, Mika; Munyao, Martha; Omondi, Patrick; Pellikka, Petri (2020)
    Savannahs provide valuable ecosystem services and contribute to continental and global carbon budgets. In addition, savannahs exhibit multiple land uses, e.g., wildlife conservation, pastoralism, and crop farming. Despite their importance, the effect of land use on woody aboveground biomass (AGB) in savannahs is understudied. Furthermore, fences used to reduce human-wildlife conflicts may affect AGB patterns. We assessed AGB densities and patterns, and the effect of land use and fences on AGB in a multi-use savannah landscape in southeastern Kenya. AGB was assessed with field survey and airborne laser scanning (ALS) data, and a land cover map was developed using Sentinel-2 satellite images in Google Earth Engine. The highest woody AGB was found in riverine forest in a conservation area and in bushland outside the conservation area. The highest mean AGB density occurred in the non-conservation area with mixed bushland and cropland (8.9 Mg center dot ha(-1)), while the lowest AGB density (2.6 Mg center dot ha(-1)) occurred in overgrazed grassland in the conservation area. The largest differences in AGB distributions were observed in the fenced boundaries between the conservation and other land-use types. Our results provide evidence that conservation and fences can create sharp AGB transitions and lead to reduced AGB stocks, which is a vital role of savannahs as part of carbon sequestration.
  • Pfeifer, Marion; Lefebvre, Veronique; Gardner, Toby A.; Arroyo-Rodriguez, Victor; Baeten, Lander; Banks-Leite, Cristina; Barlow, Jos; Betts, Matthew G.; Brunet, Joerg; Cerezo, Alexis; Cisneros, Laura M.; Collard, Stuart; D'Cruze, Neil; da Silva Motta, Catarina; Duguay, Stephanie; Eggermont, Hilde; Eigenbrod, Felix; Hadley, Adam S.; Hanson, Thor R.; Hawes, Joseph E.; Scalley, Tamara Heartsill; Klingbeil, Brian T.; Kolb, Annette; Kormann, Urs; Kumar, Sunil; Lachat, Thibault; Lakeman Fraser, Poppy; Lantschner, Victoria; Laurance, William F.; Leal, Inara R.; Lens, Luc; Marsh, Charles J.; Medina-Rangel, Guido F.; Melles, Stephanie; Mezger, Dirk; Oldekop, Johan A.; Overal, William L.; Owen, Charlotte; Peres, Carlos A.; Phalan, Ben; Pidgeon, Anna M.; Pilia, Oriana; Possingham, Hugh P.; Possingham, Max L.; Raheem, Dinarzarde C.; Ribeiro, Danilo B.; Ribeiro Neto, Jose D.; Robinson, W. Douglas; Robinson, Richard; Rytwinski, Trina; Scherber, Christoph; Slade, Eleanor M.; Somarriba, Eduardo; Stouffer, Philip C.; Struebig, Matthew J.; Tylianakis, Jason M.; Tscharntke, Teja; Tyre, Andrew J.; Urbina Cardona, Jose N.; Vasconcelos, Heraldo L.; Wearn, Oliver; Wells, Konstans; Willig, Michael R.; Wood, Eric; Young, Richard P.; Bradley, Andrew V.; Ewers, Robert M. (2014)
  • Abera, Temesgen; Heiskanen, Janne; Pellikka, Petri; Adhikari, Hari; Maeda, Eduardo (2020)
    Bushlands (Acacia-Commiphora) constitute the largest and one of the most threatened ecosystems in East Africa. Although several studies have investigated the climatic impacts of land changes on local and global climate, the main focus has been on forest loss and the impacts of bushland clearing thus remain poorly understood. Measuring the impacts of bushland loss on local climate is challenging given that changes often occur at fragmented and small patches. Here, we apply high-resolution satellite imagery and land surface flux modeling approaches to unveil the impacts of bushland clearing on surface biophysical properties and its associated effects on surface energy balance and land surface temperature. Our results show that bushland clearing leads to an average reduction in evapotranspiration of 0.4 mm day(-1). The changes in surface biophysical properties affected the surface energy balance components with different magnitude. The reduction in latent heat flux was stronger than other surface energy fluxes and resulted in an average net increase in daytime land surface temperature (LST) of up to 1.75 K. These results demonstrate the important impact of bushland-to-cropland conversion on the local climate, as they reveal increases in LST of a magnitude comparable to those caused by forest loss. This finding highlights the necessity of bushland conservation for regulating the land surface temperature in East Africa and, at the same time, warns of the climatic impacts of clearing bushlands for agriculture. (c) 2020 The Authors. Published by Elsevier B.V.
  • Wang, Qingkai; Lu, Peng; Zu, Yongheng; Li, Zhijun; Lepparanta, Matti; Zhang, Guiyong (2019)
    Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (A(w), A(p), and A(i), respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (<10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing A(p), compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.
  • Merkouriadi, Ioanna; Leppäranta, Matti; Järvinen, Onni (2017)
    The interannual variability of the air temperature, precipitation and snow conditions were examined in the Finnish Arctic region based on data from the period 1946-2012. The purpose of this work was to describe the climatology of the region and to examine long-term variations in the climatic parameters. This information is essential for both environmental and socioeconomic aspects of the Finnish Arctic region. The air temperature, precipitation and snow depth records from nine weather stations were analysed in order to study the evolution of the winter duration (sub-zero temperature days), precipitation, snow cover duration and snow depth. The climatological description was based on the most recent 30-year period record available (1982-2011). Since 1946, air temperature has increased significantly by 0.4 degrees C/decade. Significant precipitation trends reached up to 35 mm/decade. For the most part there were no significant trends in snow depth and snow cover duration.
  • Abera, Temesgen; Pellikka, Petri; Heiskanen, Janne; Maeda, Eduardo (2020)
    Land surface temperature (LST) is affected by surface-atmosphere interaction. Yet, the degree to which surface and atmospheric factors impact the magnitude of LST trend is not well established. Here, we used surface energy balance, boosted regression tree model, and satellite observation and reanalysis data to unravel the effects of surface factors (albedo, sensible heat, latent heat, and ground heat) as well as incoming radiation (shortwave and longwave) on LST trends in East Africa (EA). Our result showed that 11% of EA was affected by significant (p <0.05) daytime annual LST trends, which exhibited both cooling of -0.19 K year(-1) (mainly in South Sudan and Sudan) and warming of 0.22 K year(-1) (mainly in Somalia and Kenya). The nighttime LST trends affected a large part of EA (31%) and were dominated by significant warming trend (0.06 K year(-1)). Influenced by contrasting daytime and nighttime LST trends, the diurnal LST range reduced in 15% of EA. The modeling result showed that latent heat flux (32%), incoming longwave radiation (30%), and shortwave radiation (23%) were stronger in explaining daytime LST trend. The effects of surface factors were stronger in both cooling and warming trends, whereas atmospheric factors had stronger control only on surface cooling trends. These results indicate the differential control of surface and atmospheric factors on warming and cooling trends, highlighting the importance of considering both factors for accurate evaluation of the LST trends in the future.
  • Yang, Yu; Cheng, Bin; Kourzeneva, Ekaterina; Semmler, Tido; Rontu, Laura; Lepparanta, Matti; Shirasawa, Kunio; Li, Zhijun (2013)
  • Yang, Yu; Leppäranta, Matti; Cheng, Bin; Li, Zhijun (2012)
  • Gehrmann, Friederike; Hänninen, Heikki; Liu, Che; Saarinen, Timo Pekka (2017)
    Background: In tundra ecosystems, the adjustment of phenological events, such as bud burst, to snowmelt timing is crucial to the climatic adaptation of plants. Natural small-scale variations in microclimate potentially enable plant populations to persist in a changing climate.Aims: To assess how plant phenology responds to natural differences in snowmelt timing.Methods: We observed the timing of eight vegetative and reproductive phenophases in seven dwarf-shrub species in relation to differences in snowmelt timing on a small spatial scale in an alpine environment in subarctic Finland.Results: Some species and phenophases showed accelerated development with later snowmelt, thus providing full or partial compensation for the shorter snow-free period. Full compensation resulted in synchronous occurrence of phenophases across the snowmelt gradient. In other species, there was no acceleration of development. The timing of phenophases varied between two consecutive years and two opposing mountain slope aspects.Conclusions: The results have shown three distinct patterns in the timing of phenophases in relation to snowmelt and suggest alternative strategies for adaptation to snowmelt timing. These strategies potentially apply to other species and tundra ecosystems and provide a framework, enabling one to compare and generalise phenological responses to snowmelt timing under different future climate scenarios.
  • Räsänen, Tuomas; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo (2019)
    Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.
  • Alibakhshi, Sara; Naimi, Babak; Hovi, Aarne; Crowther, Thomas W.; Rautiainen, Miina (2020)
    Forests are critical in regulating climate by altering the Earth's surface albedo. Therefore, there is an urgent need to enhance our knowledge about the effects of forest structure on albedo. Here, we present a global assessment of the links between forest structure and albedo at a 1-km spatial resolution using generalized additive models (GAMs). We used remotely sensed data to obtain variables representing forest structure, including forest density, leaf area index, and tree cover, during the peak growing season in 2005 with pure forest pixels that cover similar to 7% of the Earth's surface. Furthermore, we estimated black-sky albedo at a solar zenith angle of 38 degrees using the most recent collection of the moderate resolution imaging spectroradiometer (MODIS; version 6) at shortwave, near-infrared, and visible spectral regions. In addition, for the first time, we mapped the magnitude of the relationship between forest structure and albedo at each pixel with a 0.5-degree spatial resolution. Our results suggested that forest structure may modulate albedo in most of the sub-biomes. The response of shortwave albedo was always positive to the leaf area index and negative to the tree cover (except for deciduous broadleaf forests in mediterranean and temperate regions), while the response to forest density varied across space in 2005. The spatial map affirmed that the links between forest structure and albedo vary over geographical locations. In sum, our study emphasized the importance of forest structure in the surface albedo regulation. This paper provides the first spatially explicit evidence of the magnitude of relationships between forest structure and albedo on a global scale.
  • Amara, Edward; Heiskanen, Janne; Aynekulu, Ermias; Pellikka, Petri Kauko Emil (2019)
    Global sustainable development goals include reducing greenhouse gas emissions from land-use change and maintaining biodiversity. Many studies have examined carbon stocks and tree species diversity, but few have studied the humid Guinean savanna ecosystem. This study focuses on a humid savanna landscape in northern Sierra Leone, aiming to assess carbon stocks and tree species diversity and compare their relationships in different vegetation types. We surveyed 160 sample plots (0.1 ha) in the field for tree species, aboveground carbon (AGC) and soil organic carbon (SOC). In total, 90 tree species were identified in the field. Gmelina arborea, an exotic tree species common in the foothills of the Kuru Hills Forest Reserve, and Combretum glutinosum, Pterocarpus erinaceous and Terminaria glaucescens, which are typical savanna trees, were the most common species. At landscape level, the mean AGC stock was 29.4 Mg C ha(-1) (SD 21.3) and mean topsoil (0-20 cm depth) SOC stock was 42.2 Mg C ha(-1) (SD 20.6). Mean tree species richness and Shannon index per plot were 7 (SD 4) and 1.6 (SD 0.6), respectively. Forests and woodlands had significantly higher mean AGC and tree species richness than bushland, wooded grassland or cropland (p <0.05). In the forest and bushland, a small number of large diameter trees covered a large portion of the total AGC stocks. Furthermore, a moderate linear correlation was observed between AGC and tree species richness (r = 0.475, p <0.001) and AGC and Shannon index (r = 0.375, p <0.05). The correlation between AGC and SOC was weak (r = 0.17, p <0.05). The results emphasise the role of forests and woodlands and large diameter trees in retaining AGC stocks and tree species diversity in the savanna ecosystem.
  • Ribeiro, Sofia; Sejr, Mikael K.; Limoges, Audrey; Heikkilä, Maija; Andersen, Thorbjorn Joest; Tallberg, Petra; Weckstrom, Kaarina; Husum, Katrine; Forwick, Matthias; Dalsgaard, Tage; Masse, Guillaume; Seidenkrantz, Marit-Solveig; Rysgaard, Soren (2017)
    In order to establish a baseline for proxy-based reconstructions for the Young Sound-Tyrolerfjord system (Northeast Greenland), we analysed the spatial distribution of primary production and sea ice proxies in surface sediments from the fjord, against monitoring data from the Greenland Ecosystem Monitoring Programme. Clear spatial gradients in organic carbon and biogenic silica contents reflected marine influence, nutrient availability and river-induced turbidity, in good agreement with in situ measurements. The sea ice proxy IP25 was detected at all sites but at low concentrations, indicating that IP25 records from fjords need to be carefully considered and not directly compared to marine settings. The sea ice-associated biomarker HBI III revealed an open-water signature, with highest concentrations near the mid-July ice edge. This proxy evaluation is an important step towards reliable palaeoenvironmental reconstructions that will, ultimately, contribute to better predictions for this High Arctic ecosystem in a warming climate.
  • Liu, Jinxiu; Maeda, Eduardo; Du, Wang; Heiskanen, Janne (2021)
    Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices.
  • Etongo, Daniel; Djenontin, Ida Nadia S.; Kanninen, Markku; Kalame, Fobissie (2015)
    Climate variability and change significantly affect smallholder farmers' food security and livelihoods in sub-Saharan Africa. Tree planting is one of the measures promoted by development programs to mitigate and adapt to climate change. Tree planting is also believed to positively contribute to livelihoods. This paper examines factors influencing smallholders' tree planting activities in four villages in the Ziro province, Southern Burkina Faso. Furthermore, it analyses the challenges encountered and willingness to continue tree planting under current tenure arrangements. The data was obtained through key informants, household interviews, focus group discussions, and field observations. Results indicate that the majority of farmers interviewed planted Mangifera indica (50%), Anacardium occidentale (32%) and Moringa oleifera (30%). In a number of trees planted, Eucalyptus camaldulensis, Mangifera indica and Anacardium occidentale dominated. Tree planters were mainly farmers who held large and old farm areas, were literate and relatively wealthy, had favorable attitudes toward tree planting, and with considerable years of participation in a farmers' group. The main reasons for planting trees included income generation from the sale of tree products, access to markets and local support for tree planting. Preference for agriculture, tenure insecurity and lack of sufficient land were the main reasons cited for not planting trees. Farm households that were relatively poor, had smaller workforces and smaller farm sizes were not willing to continue tree planting. To effectively engage farmers in tree planting and to make it more attractive, policies are needed that address tenure insecurity for migrants, enable better access to markets, and support fair pricing structures for wood and other tree resources.
  • Semmler, Tido; Cheng, Bin; Yang, Yu; Rontu, Laura (2012)
  • Rissanen, Tuuli Katariina; Niittynen, Pekka; Soininen, Janne; Luoto, Miska (2021)
    Aim To examine how snow cover and permafrost affect plant species distributions at a subcontinental extent. Location Mountain realm of Fennoscandia, northern Europe. Time period Species data from 1 January 1990-25 February 2019. Major taxa studied Arctic-alpine and boreal vascular plants. Methods We examined the effect of snow persistence and permafrost occurrence on the distributions of arctic-alpine and boreal plant species while controlling for climate, topography and geological factors. Data comprised 475,811 observations from 671 species in the Fennoscandian mountains. We investigated the relationships between species distributions and environmental variables using four modelling methods and ensemble modelling building on both non-spatial and spatial models. Results Snow persistence was the most important driver of plant species distributions, with the greatest variable importance for both arctic-alpine (38.2%) and boreal (49.9%) species. Permafrost had a consistent minor effect on the predicted distributions. Arctic-alpine plants occur in areas with long snow persistence and permafrost, whereas boreal species showed the opposite habitat preferences. Main conclusions Our results highlight the importance of snow persistence in driving the distribution of vascular plant species in cold environments at a subcontinental scale. The notable contribution of the cryosphere to plant species distribution models indicates that the inclusion of snow information in particular may improve our understanding and model predictions of biogeographical patterns in cold regions.
  • Wachiye, Sheila; Merbold, Lutz; Vesala, Timo; Rinne, Janne; Rasanen, Matti; Leitner, Sonja; Pellikka, Petri (2020)
    Field measurement data on greenhouse gas (GHG) emissions are still scarce for many land-use types in Africa, causing a high level of uncertainty in GHG budgets. To address this gap, we present in situ measurements of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions from the lowlands of southern Kenya. We conducted eight chamber measurement campaigns on gas exchange from four dominant land-use types (LUTs) comprising (1) cropland, (2) bushland, (3) grazing land, and (4) conservation land between 29 November 2017 and 3 November 2018, accounting for regional seasonality (wet and dry seasons and transitions periods). Mean CO2 emissions for the whole observation period were the highest by a significant margin (p value <0.05) in the conservation land (75 +/- 6 mg CO2-C m(-2)h(-1)) compared to the three other sites, which ranged from 45 +/- 4 mg CO2-C m(-2)h(-1) (bush-land) to 50 +/- 5 mg CO2-C m(-2)h(-1) (grazing land). Further-more, CO2 emissions varied between seasons, with significantly higher emissions in the wet season than the dry season. Mean N2O emissions were highest in cropland (2.7 0.6 lug N2O-N m(-2) h(-1)) and lowest in bushland (1.2 0.4 pg N2O-N m(-2)h(-1)) but did not vary with season. In fact, N2O emissions were very low both in the wet and dry seasons, with slightly elevated values during the early days of the wet seasons in all LUTs. On the other hand, CH4 emissions did not show any significant differences across LUTs and seasons. Most CH4 fluxes were below the limit of detection (LOD, 0.03 mg CH4-C m(-2) h(-1)). We attributed the difference in soil CO2 emissions between the four sites to soil C content, which differed between the sites and was highest in the conservation land. In addition, CO2 and N2O emissions positively correlated with soil moisture, thus an increase in soil moisture led to an increase in emissions. Furthermore, vegetation cover explained the seasonal variation in soil CO2 emissions as depicted by a strong positive correlation between the normalized difference vegetation index (NDVI) and CO2 emissions, most likely because, with more green (active) vegetation cover, higher CO2 emissions occur due to enhanced root respiration compared to drier periods. Soil temperature did not show a clear correlation with either CO2 or N2O emissions, which is likely due to the low variability in soil temperature between seasons and sites. Based on our results, soil C, active vegetation cover, and soil moisture are key drivers of soil GHG emissions in all the tested LUTs in southern Kenya. Our results are within the range of previous GHG flux measurements from soils from various LUTs in other parts of Kenya and contribute to more accurate baseline GHG emission estimates from Africa, which are key to reducing uncertainties in global GHG budgets as well as for informing policymakers when discussing low -emission development strategies.
  • Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Rasanen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika (2017)
    Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 degrees C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R-adj.(2) 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.