| 1. |
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| 2. |
- Eklundh, Lars, et al.
(author)
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Bearbetning av geografiska data
- 2008
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In: Geografisk informationsbehandling: teori, metoder och tillämpningar. - 9789154060153 ; , s. 162-181
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Book chapter (other academic/artistic)
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| 3. |
- Eklundh, Lars, et al.
(author)
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Bearbetning av geografiska data
- 2013
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In: Geografisk informationsbehandling : teori, metoder och tillämpningar. - 9789144088778 ; , s. 183-209
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Book chapter (other academic/artistic)
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| 4. |
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| 5. |
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| 6. |
- Pilesjö, Petter, et al.
(author)
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Metoder för rumslig dataanalys
- 2000
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In: Geografisk Informationsbehandling. - 915405841 4 ; , s. 195-266
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Book chapter (other academic/artistic)
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| 7. |
- Ågren, Jonas, et al.
(author)
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Insamling av geografiska data
- 2013
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In: Geografisk informationsbehandling : teori, metoder och tillämpningar. - 9789144088778 ; , s. 103-137
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Book chapter (other academic/artistic)
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| 8. |
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| 9. |
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| 10. |
- Eklundh, Lars, et al.
(author)
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Insamling av geografiska data
- 2020. - 7
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In: Geografisk informationsbehandling. - : Studentlitteratur AB. - 9789144131740 ; , s. 85-126
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Book chapter (pop. science, debate, etc.)abstract
- Det här kapitlet fokuserar på att förklara de grundläggande principerna för insamling av geografiska data, och vi lägger tonvikten på fjärranalys och geodetiska metoder. Fjärranalys innefattar olika tekniker som fotogrammetri, laserskanning och analys av bilder från mark, flyg och satelliter. Geodetiska datainsamling används för att mäta in koordinater för objekt på marken och innefattar satellitbaserade tekniker såväl som användning av fältinstrument. Olika tekniker, avseende både fjärranalys och geodesi, används i olika situationer beroende på krav på noggrannhet och innehåll, och kompletterar därför varandra. Vi börjar med att beskriva satellitfjärranalys som kan täcka stora områden med relativt begränsad detaljeringsgrad, beskriver sedan flygbilder och laserskanning där detaljnivån ökar, för att till sist beskriva de geodetiska metoderna för noggranna mätningar på marknivå.
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| 11. |
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| 13. |
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| 14. |
- Jönsson, Anna Maria, et al.
(author)
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Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology
- 2010
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 114:11, s. 2719-2730
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Journal article (peer-reviewed)abstract
- Remote sensing provides spatially and temporally continuous measures of forest reflectance, and vegetation indices calculated from satellite data can be useful for monitoring climate change impacts on forest tree phenology. Monitoring of evergreen coniferous forest is more difficult than monitoring of deciduous forest, as the new buds only account for a small proportion of the green biomass, and the shoot elongation process is relatively slow. In this study, we have analyzed data from 186 coniferous monitoring sites in Sweden covering boreal, southern-boreal, and boreo-nemoral conditions. Our objective was to examine the possibility to track seasonal changes in coniferous forests by time-series of MODIS eight-day vegetation indices, testing the coherence between satellite monitored vegetation indices (VI) and temperature dependent phenology. The relationships between two vegetation indices (NDVI and WDRVI) and four phenological indicators (length of snow season, modeled onset of vegetation period, tree cold hardiness level and timing of budburst) were analyzed. The annual curves produced by two curve fitting methods for smoothening of seasonal changes in NDVI and WDRVI were to a large extent characterized by the occurrence of snow, producing stable seasonal oscillations in the northern part and irregular curves with less pronounced annual amplitude in the southern part of the country. Measures based on threshold values of the VI-curves, commonly used for determining the timing of different phenological phases, were not applicable for Swedish coniferous forests. Evergreen vegetation does not have a sharp increase in greenness during spring, and the melting of snow can influence the vegetation indices at the timing of bud burst in boreal forests. However, the interannual variation in VI-values for specific eight-day periods was correlated with the phenological indicators. This relation can be used for satellite monitoring of potential climate change impacts on northern coniferous spring phenology. (C) 2010 Elsevier Inc. All rights reserved.
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| 15. |
- Abdi, Abdulhakim M., et al.
(author)
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Biodiversity decline with increasing crop productivity in agricultural fields revealed by satellite remote sensing
- 2021
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In: Ecological Indicators. - : Elsevier BV. - 1470-160X. ; 130
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Journal article (peer-reviewed)abstract
- Increasing land-use intensity is a main driver of biodiversity loss in farmland, but measuring proxies for land-use intensity across entire landscapes is challenging. Here, we develop a novel method for the assessment of the impact of land-use intensity on biodiversity in agricultural landscapes using remote sensing parameters derived from the Sentinel-2 satellites. We link crop phenology and productivity parameters derived from time-series of a two-band enhanced vegetation index with biodiversity indicators (insect pollinators and insect-pollinated vascular plants) in agricultural fields in southern Sweden, with contrasting land management (i.e. conventional and organic farming). Our results show that arable land-use intensity in cereal systems dominated by spring-sown cereals can be approximated using Sentinel-2 productivity parameters. This was shown by the significant positive correlations between the amplitude and maximum value of the enhanced vegetation index on one side and farmer reported yields on the other. We also found that conventional cereal fields had 17% higher maximum and 13% higher amplitude of their enhanced vegetation index than organic fields. Sentinel-2 derived parameters were more strongly correlated with the abundance and species richness of bumblebees and the richness of vascular plants than the abundance and species richness of butterflies. The relationships we found between biodiversity and crop production proxies are consistent with predictions that increasing agricultural land-use intensity decreases field biodiversity. The newly developed method based on crop phenology and productivity parameters derived from Sentinel-2 data serves as a proof of concept for the assessment of the impact of land-use intensity on biodiversity over cereal fields across larger areas. It enables the estimation of arable productivity in cereal systems, which can then be used by ecologists and develop tools for land managers as a proxy for land-use intensity. Coupled with spatially explicit databases on agricultural land-use, this method will enable crop-specific cereal productivity estimation across large geographical regions.
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| 16. |
- Abdi, Hakim, et al.
(author)
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The supply and demand of net primary production in the Sahel
- 2014
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In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 9:9, s. 11-094003
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Journal article (peer-reviewed)abstract
- Net primary production (NPP) is the principal source of energy for ecosystems and, by extension, human populations that depend on them. The relationship between the supply and demand of NPP is important for the assessment of socio-ecological vulnerability. We present an analysis of the supply and demand of NPP in the Sahel using NPP estimates from the MODIS sensor and agri-environmental data from FAOSTAT. This synergistic approach allows for a spatially explicit estimation of human impact on ecosystems. We estimated the annual amount of NPP required to derive food, fuel and feed between 2000 and 2010 for 22 countries in sub-Saharan Africa. When comparing annual estimates of supply and demand of NPP, we found that demand increased from 0.44 PgC to 1.13 PgC, representing 19% and 41%, respectively, of available supply due to a 31% increase in the human population between 2000 and 2010. The demand for NPP has been increasing at an annual rate of 2.2% but NPP supply was near-constant with an inter-annual variability of approximately 1.7%. Overall, there were statistically significant (p < 0.05) increases in the NPP of cropland (+6.0%), woodland (+6.1%) and grassland/savanna (+9.4%), and a decrease in the NPP of forests (−0.7%). On the demand side, the largest increase was for food (20.4%) followed by feed (16.7%) and fuel (5.5%). The supply-demand balance of NPP is a potentially important tool from the standpoint of sustainable development, and as an indicator of stresses on the environment stemming from increased consumption of biomass.
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| 17. |
- Ahmed, Mohamed, et al.
(author)
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Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region
- 2017
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In: International Journal of Remote Sensing. - : Informa UK Limited. - 1366-5901 .- 0143-1161. ; 38:19, s. 5408-5429
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Journal article (peer-reviewed)abstract
- Over the last few decades, the African Sahel has become thefocus of many studies regarding vegetation dynamics and theirrelationships with climate and people. This is because rainfalllimits the production of biomass in the region, a resource onwhich people are directly dependent for their livelihoods. In thisstudy, we utilized a remote-sensing approach to answering thefollowing two questions: (1) how does the dynamic relationshipbetween soil moisture and plant growth vary across hydrologi-cal regimes, and (2) are vegetation-type-dependent responsesto soil moisture availability detectable from satellite imagery? Inorder to answer these questions, we studied the relationshipbetween monthly modelled soil moisture as an indicator forwater availability and the remotely sensed normalized differ-ence vegetation index (NDVI) as a proxy for vegetation growthbetween a“recovery rainfall period”(1982 to 1997) and a“stable rainfall period”(1998 to 2013), at different time lagsacross the Sahel region. Using windowed cross-correlation, wefind a strong significant positive relationship between NDVI andsoil moisture at a concurrent time and at NDVI lagging behindsoil moisture by 1 month for grassland, cropland, and decid-uous shrubland vegetation–the dominant vegetation classes inthe Sahel. South of the Sahel (the Sudanian and Guinean areas),wefind longer optimal lags (soil moisture lagged by 1–3 months) in association with mixed forest and deciduousshrubland. Wefind no major significant change in optimal lagbetween the recovery and stable periods in the Sahelian region;however, in the Sudanian and Guinean areas, we observe atrend towards shorter time lags. This change in optimal lagsuggests a vegetation change, which may be a response to aclimatic shift or land-use change. This approach of identifyingspatiotemporal trends in optimal lag correlations between mod-elled soil moisture and NDVI could prove to be a useful tool formapping vegetation change and ecosystem behaviour, in turnhelping inform climate change mitigation approaches and agri-cultural planning
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| 18. |
- Balzarolo, Manuela, et al.
(author)
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Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies
- 2011
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In: Sensors. - : MDPI AG. - 1424-8220. ; 11:8, s. 7954-7981
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Research review (peer-reviewed)abstract
- This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903-"Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe" that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.
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| 19. |
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| 20. |
- Beck, P S A, et al.
(author)
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A ground-validated NDVI dataset for monitoring vegetation dynamics and mapping phenology in Fennoscandia and the Kola peninsula
- 2007
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In: International Journal of Remote Sensing. - : Informa UK Limited. - 1366-5901 .- 0143-1161. ; 28:19, s. 4311-4330
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Journal article (peer-reviewed)abstract
- An NDVI dataset covering Fennoscandia and the Kola peninsula was created for vegetation and climate studies, using Moderate Resolution Imaging Spectroradiometer 16-day maximum value composite data from 2000 to 2005. To create the dataset, ( 1) the influence of the polar night and snow on the NDVI values was removed by replacing NDVI values in winter with a pixel- specific NDVI value representing the NDVI outside the growing season when the pixel is free of snow; and ( 2) yearly NDVI time series were modelled for each pixel using a double logistic function defined by six parameters. Estimates of the onset of spring and the end of autumn were then mapped using the modelled dataset and compared with ground observations of the onset of leafing and the end of leaf fall in birch, respectively. Missing and poor-quality data prevented estimates from being produced for all pixels in the study area. Applying a 5 km x 5 km mean filter increased the number of modelled pixels without decreasing the accuracy of the predictions. The comparison shows good agreement between the modelled and observed dates ( root mean square error = 12 days, n = 108 for spring; root mean square error = 10 days, n = 26, for autumn). Fennoscandia shows a range in the onset of spring of more than 2 months within a single year and locally the onset of spring varies with up to one month between years. The end of autumn varies by one and a half months across the region. While continued validation with ground data is needed, this new dataset facilitates the detailed monitoring of vegetation activity in Fennoscandia and the Kola peninsula.
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| 21. |
- Boke-Olén, Niklas, et al.
(author)
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Analyzing savannah vegetation phenology with remotely sensed data, lagged time-series models and phenopictures
- 2016
-
Conference paper (peer-reviewed)abstract
- It is predicted that savannah regions will see changes in precipitation patterns due to current climate change pro-jections. The change will most likely affect leaf phenology which controls net primary production. It is thereforeimportant to; 1) study those changes and its drivers, 2) to be able to correctly model the changes to vegetationphenology due to climate change. To our knowledge there is no existing global savannah phenology model thatcan capture both the phenological events and the vegetation state between the events. We therefore, investigate howday length, mean annual precipitation and soil moisture affects and controls the vegetation phenology of savannahs(using MODIS NDVI as a proxy for phenological state) with a lagged time series model for global application. Wefurthermore use phenological pictures (phenopictures) to investigate savannah tree and grass phenology. Phenopic-tures are pictures taken with a digital time-lapse camera with the purpose of recording and studying phenologicalevents. We used climate data from 15 flux towers sites located in 4 continents together with normalized differencevegetation index from MODIS for the model development. Two of the sites located in Africa were further ana-lyzed using phenopictures. The developed model identified all three considered variables as usable for modellingof savannah leaf phenology but showed some inconsistent result for some of the sites indicating the difficultiesin creating a simple common model that works equally well across sites. We attribute some of these difficultiesto site specific differences (e.g. grazing or tree and grass ratio) that the simplified model did not consider. Butwe expect it to on average give the cross-validated result (r2= 0.6, RMSE = 0.1) when applied to other savannahareas. The preliminary analysis of the phenological pictures with respect to tree and grass to some extent supportthis by showing differences in the start of the leaves development in the beginning of the season. However, thisdiffered between the two studied sites which further highlights the difficulties in creating a common model thatworks equally well for individual sites.
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| 22. |
- Boke-Olén, Niklas, et al.
(author)
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Estimating and analyzing savannah phenology with a lagged time series model
- 2016
-
In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:4
-
Journal article (peer-reviewed)abstract
- Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.
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| 23. |
- Boke-Olén, Niklas, et al.
(author)
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Remotely sensed soil moisture to estimate savannah NDVI
- 2018
-
In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 13:7
-
Journal article (peer-reviewed)abstract
- Satellite derived normalized difference vegetation index (NDVI) is a common data source for monitoring regional and global ecosystem properties. In dry lands it has contributed to estimation of inter-annual and seasonal vegetation dynamics and phenology. However, due to the spectral properties of NDVI it can be affected by clouds which can introduce missing data in the time series. Remotely sensed soil moisture has in contrast to NDVI the benefit of being unaffected by clouds due to the measurements being made in the microwave domain. There is therefore a potential in combining the remotely sensed NDVI with remotely sensed soil moisture to enhance the quality and estimate the missing data. We present a step towards the usage of remotely sensed soil moisture for estimation of savannah NDVI. This was done by evaluating the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture and three of its individual products with respect to their relative performance. The individual products are from the advance scatterometer (ASCAT), Soil Moisture and Ocean Salinity (SMOS), and the Land Parameter Retrieval Model-Advanced Microwave Scanning Radiometer-Earth Observing System (LPRM-AMSR-E). Each dataset was used to simulate NDVI, which was subsequently compared to remotely sensed NDVI from MODIS. Differences in their ability to estimate NDVI indicated that, on average, CCI soil moisture differs from its individual products by showing a higher average correlation with measured NDVI. Overall NDVI modelled from CCI soil moisture gave an average correlation of 0.81 to remotely sensed NDVI which indicates its potential to be used to estimate seasonal variations in savannah NDVI. Our result shows promise for further development in using CCI soil moisture to estimate NDVI. The modelled NDVI can potentially be used together with other remotely sensed vegetation datasets to enhance the phenological information that can be acquired, thereby, improving the estimates of savannah vegetation phenology.
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| 24. |
- Bolin, David, et al.
(author)
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Fast estimation of spatially dependent temporal trends using Gaussian Markov Random fields
- 2009
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In: Computational Statistics & Data Analysis. - : Elsevier BV. - 0167-9473. ; 53:8, s. 2885-2896
-
Journal article (peer-reviewed)abstract
- There is a need for efficient methods for estimating trends in spatio-temporal Earth Observation data. A suitable model for such data is a space-varying regression model, where the regression coefficients for the spatial locations are dependent. A second order intrinsic Gaussian Markov Random Field prior is used to specify the spatial covariance structure. Model parameters are estimated using the Expectation Maximisation (EM) algorithm, which allows for feasible computation times for relatively large data sets. Results are illustrated with simulated data sets and real vegetation data from the Sahel area in northern Africa. The results indicate a substantial gain in accuracy compared with methods based on independent ordinary least squares regressions for the individual pixels in the data set. Use of the EM algorithm also gives a substantial performance gain over Markov Chain Monte Carlo-based estimation approaches.
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| 25. |
- Bolton, Douglas K., et al.
(author)
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Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery
- 2020
-
In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 240
-
Journal article (peer-reviewed)abstract
- Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, and characterize temporal dynamics in land surface properties with unprecedented spatial detail and quality. By combining imagery from the Landsat 8 Operational Land Imager and the MultiSpectral Instrument on-board Sentinel-2A and -2B, the remote sensing community now has access to moderate (10–30 m) spatial resolution imagery with repeat periods of ~3 days in the mid-latitudes. At the same time, the large combined data volume from Landsat 8 and Sentinel-2 introduce substantial new challenges for users. Land surface phenology (LSP) algorithms, which estimate the timing of phenophase transitions and quantify the nature and magnitude of seasonality in remotely sensed land surface conditions, provide an intuitive way to reduce data volumes and redundancy, while also furnishing data sets that are useful for a wide range of applications including monitoring ecosystem response to climate variability and extreme events, ecosystem modelling, crop-type discrimination, and land cover, land use, and land cover change mapping, among others. To support the need for operational LSP data sets, here we describe a continental-scale land surface phenology algorithm and data product based on harmonized Landsat 8 and Sentinel-2 (HLS) imagery. The algorithm creates high quality times series of vegetation indices from HLS imagery, which are then used to estimate the timing of vegetation phenophase transitions at 30 m spatial resolution. We present results from assessment efforts evaluating LSP retrievals, and provide examples illustrating the character and quality of information related to land cover and terrestrial ecosystem properties provided by the continental LSP dataset that we have developed. The algorithm is highly successful in ecosystems with strong seasonal variation in leaf area (e.g., deciduous forests). Conversely, results in evergreen systems are less interpretable and conclusive.
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