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  • 1. André, C.
    et al.
    Ottlé, C.
    Royer, A.
    Maignan, F.
    Land surface temperature retrieval over circumpolar Arctic using SSM/I–SSMIS and MODIS data2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 162, 1-10 p.Article in journal (Refereed)
    Abstract [en]

    Abstract Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I–SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I–SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000–2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis. The dataset can be downloaded from the PANGAEA website: http://doi.pangaea.de/10.1594/PANGAEA.833409.

  • 2.
    Bhardwaj, Anshuman
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Sam, Lydia
    Department of Environmental Science, Sharda University.
    Akanksha, Akanksha
    Banaras Hindu University, Varanasi.
    Martin-Torres, Javier
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Kumar, Rejesh
    Department of Environmental Science, Sharda University.
    UAVs as remote sensing platform in glaciology: Present applications and future prospects2016In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 175, 196-204 p.Article in journal (Refereed)
    Abstract [en]

    Satellite remote sensing is an effective way to monitor vast extents of global glaciers and snowfields. However, satellite remote sensing is limited by spatial and temporal resolutions and the high costs involved in data acquisition. Unmanned aerial vehicle (UAV)-based glaciological studies are gaining pace in recent years due to their advantages over conventional remote sensing platforms. UAVs are easy to deploy, with the option of alternating the sensors working in visible, infrared, and microwave wavelengths. The high spatial resolution remote sensing data obtained from these UAV-borne sensors are a significant improvement over the data obtained by traditional remote sensing. The cost involved in data acquisition is minimal and researchers can acquire imagery according to their schedule and convenience. We discuss significant glaciological studies involving UAV as remote sensing platforms. This is the first review work, exclusively dedicated to highlight UAV as a remote sensing platform in glaciology. We examine polar and alpine applications of UAV and their future prospects in separate sections and present an extensive reference list for the readers, so that they can delve into their topic of interest. Because the technology is still widely unexplored for snow and glaciers, we put a special emphasis on discussing the future prospects of utilising UAVs for glaciological research.

  • 3.
    Bhardwaj, Anshuman
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Sam, Lydia
    Department of Environmental Science, Sharda University.
    Bhardwaj, Akanksha
    Banaras Hindu University, Varanasi.
    Martin-Torres, Javier
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    LiDAR remote sensing of the cryosphere: Present applications and future prospects2016In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 177, 125-143 p.Article in journal (Refereed)
    Abstract [en]

    The cryosphere consists of frozen water and includes lakes/rivers/sea ice, glaciers, ice caps/sheets, snow cover, and permafrost. Because highly reflective snow and ice are the main components of the cryosphere, it plays an important role in the global energy balance. Thus, any qualitative or quantitative change in the physical properties and extents of the cryosphere affects global air circulation, ocean and air temperatures, sea level, and ocean current patterns. Due to the hardships involved in collecting ground control points and field data for high alpine glaciers or vast polar ice sheets, several researchers are currently using remote sensing. Satellites provide an effective space-borne platform for remotely sensing frozen areas at the global and regional scales. However, satellite remote sensing has several constraints, such as limited spatial and temporal resolutions and expensive data acquisition. Therefore, aerial and terrestrial remote sensing platforms and sensors are needed to cover temporal and spatial gaps for comprehensive cryospheric research. Light Detection and Ranging (LiDAR) antennas form a group of active remote sensors that can easily be deployed on all three platforms, i.e., satellite, aerial, and terrestrial. The generation of elevation data for glacial and snow-covered terrain from photogrammetry requires high contrast amongst various reflective surfaces (ice, snow, firn, and slush). Conventional passive optical remote sensors do not provide the necessary accuracy, especially due to the unavailability of reliable ground control points. However, active LiDAR sensors can fill this research gap and provide high-resolution and accurate Digital Elevation Models (DEMs). Due to the obvious advantages of LiDAR over conventional passive remote sensors, the number of LiDAR-based cryospheric studies has increased in recent years. In this review, we highlight studies that have utilised LiDAR sensors for the cryospheric research of various features, such as snow cover, polar ice sheets and their atmospheres, alpine glaciers, and permafrost. Because this technology shows immense promise for applications in future cryospheric research, we also emphasise the prospects of utilising LiDAR sensors. In this paper, a large compilation of relevant references is presented to allow readers to explore particular topics of interest.

  • 4.
    Bhardwaj, Anshuman
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Singh, Shaktiman
    Institut für Kartographie, Technische Universität Dresden.
    Sam, Lydia
    Institut für Kartographie, Technische Universität Dresden.
    Bhardwaj, Akanksha
    Banaras Hindu University, Varanasi.
    Martin-Torres, Javier
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Singh, Atar
    Department of Environmental Science, Sharda University.
    Kumar, Rajesh
    Department of Environmental Science, Sharda University.
    MODIS-based estimates of strong snow surface temperature anomaly related to high altitude earthquakes of 20152017In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 188, 1-8 p.Article in journal (Refereed)
    Abstract [en]

    The high levels of uncertainty associated with earthquake prediction render earthquakes some of the worst natural calamities. Here, we present our observations of MODerate resolution Imaging Spectroradiometer (MODIS)-derived Land Surface Temperature (LST) anomaly for earthquakes in the largest tectonically active Himalayan and Andean mountain belts. We report the appearance of fairly detectable pre-earthquake Snow Surface Temperature (SST) anomalies. We use 16 years (2000–2015) of MODIS LST time-series data to robustly conclude our findings for three of the most destructive earthquakes that occurred in 2015 in the high mountains of Nepal, Chile, and Afghanistan. We propose the physical basis behind higher sensitivity of snow towards geothermal emissions. Although the preliminary appearance of SST anomalies and their amplitudes vary, we propose employing a global-scale monitoring system for detecting and studying such spatio-temporal geophysical signals. With the advent of improved remote sensors, we anticipate that such efforts can be another step towards improved earthquake predictions.

  • 5. Brown, Laura C.
    et al.
    Howell, Stephen E. L.
    Mortin, Jonas
    Stockholm University, Faculty of Science, Department of Meteorology .
    Derksen, Chris
    Evaluation of the Interactive Multisensor Snow and Ice Mapping System (IMS) for monitoring sea ice phenology2014In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 147, 65-78 p.Article in journal (Refereed)
    Abstract [en]

    We present an evaluation of the Interactive Multisensor Snow and Ice Mapping System (IMS) for monitoring northern hemisphere sea ice phenology. Analysts utilize a variety of datasets to manually derive the daily extent of snow, ice, water and land, available at both 24 and 4 km. The 4 km IMS product was assessed for 2004-2008 against several previously established melt/freeze algorithms using Scatterometer Image Reconstruction (SIR) SeaWinds/QuikSCAT (QuikSCAT) backscatter (sigma degrees), Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) brightness temperature (T-B) measurements, data from the Special Sensor Microwave/Image data (SSM/I) and sea ice concentrations derived from DMSP Special Sensor Microwave/Imager-Special Sensor Microwave Imager Sounder (SSMI-SSMIS) data (NASATeam dataset). The resolution possible with the 4 km IMS product allows for better spatial representation of sea ice along the coastlines, the ice edges and in the narrow channels of the Canadian Arctic Archipelago as compared to the microwave products. IMS detects open water earlier and freeze onset later than the automated microwave products, and also allows for the detection of opening, and the subsequent closing, of leads that the other datasets are unable to detect. Using RADARSAT-1 imagery for evaluation, IMS is shown to outperform the other datasets for the timing and extent of the first open water detection. IMS identified between 17 and 53% greater open water coverage than the other datasets in the narrow channels of the Northwest Passage (Barrow Strait). In order to further the use of IMS for sea ice applications, we derived two new spatial datasets using the full record of IMS data (4 km: 2004-present 24 km: 1997-present): melt duration to open water (duration from melt onset detected with SSM/I passive microwave until open water detected by IMS) and first year ice cover duration (duration from freeze onset until open water, both detected by IMS). Crown Copyright (C) 2014 Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).

  • 6. Chierici, Melissa
    et al.
    Signorini, Sergio R.
    Mattsdotter-Björk, My
    Fransson, Agneta
    Olsen, Are
    Surface water fCO2 algorithms for the high-latitude Pacific sector of the Southern Ocean2012In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 119, 184-196 p.Article in journal (Refereed)
    Abstract [en]

    The feasibility of using remotely sensed data jointly with shipboard measurements to estimate the carbon dioxide fugacity in the surface water (fCO2sw) of the Pacific sector of the Southern Polar Ocean (S > 60°S) is evaluated using a data set obtained during austral summer 2006. A comparison between remotely sensed chlorophyll a (chl a) and sea-surface temperature (SST) with in-situ measurements, reveals the largest bias in areas with rapid and large concentration changes such as at the ice edge, the polar front and in the Ross Sea Polynya. The correlation between fCO2sw and SST, chl a, biological productivity estimates and mixed layer depth (MLD) are evaluated, and single and multiple regression methods are used to develop fCO2sw algorithms. Single regressions between the study parameters and fCO2sw show that most of the fCO2sw variability is explained by chl a. The Multi-Parameter Linear regressions were used to create fCO2sw algorithms derived from field measurements, and using solely remote-sensing products. Based on the best fits from the two data sets fCO2sw estimates have a root means square deviation of ± 14 Όatm and coefficient of determination of 0.82. The addition of satellite derived estimates of biological productivity in the algorithm does not significantly improve the fit. We use the algorithm with remotely sensed chl a and SST data to produce an fCO2sw map for the entire high-latitude Southern Ocean south of 55°S. We analyze and discuss the seasonal and spatial robustness of the algorithm based on the remotely sensed data and compare with climatologic fCO2sw data.

  • 7. Dokken, S T
    et al.
    Winsor, P
    Markus, T
    Askne, J
    Bjork, G
    ERS SAR characterization of coastal polynyas in the Arctic and comparison with SSM/I and numerical model investigations2002In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 80, no 2, 321-335 p., PII S0034-4257(01)00313-3Article in journal (Refereed)
    Abstract [en]

    Coastal polynyas in the Arctic basin from the A inter period (January to April) are characterized using ESA European Remote Sensing satellite (ERS)-1/2 Synthetic Aperture Radar (SAR) Precision (Precise Image, PRI) and Browse images. A SAR polynya algorithm is used to delineate open water, new ice, and young ice, and to define the size and shape of polynyas. In order to extract radiometric and contextual information in the ERS SAR PRI images. three different image classification routines are developed and applied. No in situ data have been available for verification of the polynya shapes and sizes, but one of the ice classification routines have been verified earlier using ground truth data. The SAR polynya algorithm is demonstrated to be able to discriminate between the polynya and the surrounding ice area for 85 analyzed cases. The results from the SAR algorithm are compared to ERS Browse images. passive microwave data (a recent Polynya Signature Simulation Method (PSSM), and the Bootstrap and the NASA Team ice concentration algorithms), and a numerical polynya model (NPM) forced by National Center for Environmental Predictions (NCEP) wind fields and air temperatures. The ERS SAR Browse images show a relatively good correlation with the ERS SAR PRI images (.88) while the Special Sensor Microwave Imager (SSM/I) Bootstrap and the NASA Team ice concentration algorithms both have low correlation coefficients (below .3). The PSSM calculates the polynya shape and size, and delineates open water and thin ice. For polynyas of all sizes it has a correlation of .69 compared to the SAR PRI images. For polynyas with widths greater than 10 km the correlation increases to .83. The NPM computes offshore coastal polynya widths, heat exchange. and ice production. Compared to SAR data, it overestimates the maximum size of the polynya by about 15% and has a correlation of .71 compared to the analyzed SAR PRI images. The polynyas in our main investigation area, located at Franz Josef Land, are found to be primarily wind driven. The surrounding large-scale ice drift and tidal currents have little effect on the polynya behavior. One overall conclusion from this investigation is that SAR images processed through the SAR polynya algorithm in combination with the NPM is a powerful tool for investigating and characterizing polynyas at various scales in the Arctic. (C) 2002 Elsevier Science Inc. All rights reserved.

  • 8.
    Ehsani, Amir Houshang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Environmental and Natural Resources Information System.
    Quiel, Friedrich
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Environmental and Natural Resources Information System.
    Application of Self Organizing Map and SRTM data to Characterize Yardangs in the Lut Desert, Iran2008In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 112, no 7, 3284-3294 p.Article in journal (Refereed)
    Abstract [en]

    Yardangs, an exclusive landform due to intensive wind erosion, cover a large area in the hyper-arid Lut desert of Iran. This paper presents a new approach using Self Organizing Map (SOM) as unsupervised algorithm of artificial neural networks for analysis and characterization of yardangs.

    Nowadays, the Shuttle Radar Topography Mission (SRTM) with 3 arc sec data (approximately 90 m resolution) and nearly world wide coverage provides uniform good quality data.

    The SRTM 3 arc sec data were re-projected to a 90 m UTM grid. Bivariate quadratic surfaces with moving window size of 5 x 5 were fitted to this DEM. The first derivative, slope steepness and the second derivatives minimum, maximum curvature and cross-sectional curvatures were calculated as geomorphometric parameters used as input to the SOMs. 42 SOMs with different learning parameter settings, e.g. initial and final radius, number of iterations, and the effect of random initial weights on average quantization error were investigated. A SOM with a low average quantization error (0.1040) was used for further analysis. Feature space analysis, morphometric signatures, three-dimensional inspection, auxiliary data like Landsat ETM+ and high resolution satellite imagery from QuickBird facilitated the assignment of semantic meaning to the output classes in terms of geomorphometric features. Results are provided in a geographic information system as thematic maps of landform entities based on form and slope, e.g. yardangs (ridge), corridors (valley) or planar areas.

    The results showed that all yardangs and corridors were clearly recognized and classified by this method when their width was larger than the DEM resolution but became unrecognizable if their width is much smaller than the grid resolution. The identified yardangs and corridors are aligned NNW-SSE parallel to the prevailing direction of the strong local 120 days wind and cover about 31% and 42% of the study area respectively. The results demonstrate that SOM is a very efficient tool for analyzing aeolian landforms in hyper-arid environments that provides very useful information for terrain feature analysis in remote regions.

  • 9. Giardino, Claudia
    et al.
    Brando, Vittorio E.
    Dekker, Amold G.
    Strömbeck, Niklas
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Evolution, Limnology.
    Candiani, Gabriele
    Assessment of water quality in Lake Garda (Italy) using Hyperion2007In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 109, no 2, 183-195 p.Article in journal (Refereed)
    Abstract [en]

    For testing the integration of the remote sensing related technologies into the water quality monitoring programs of Lake Garda (the largest Italian lake), the spatial and spectral resolutions of Hyperion and the capability of physics-based approaches were considered highly suitable. Hyperion data were acquired on 22nd July 2003 and water quality was assessed (i) defining a bio-optical model, (ii) converting the Hyperion atsensor radiances into subsurface irradiance reflectances, and (iii) adopting a bio-optical model inversion technique. The bio-optical model was parameterised using specific inherent optical properties of the lake and light field variables derived from a radiative transfer numerical model. A MODTRAN-based atmospheric correction code, complemented with an air/water interface correction was used to convert Hyperion at-sensor radiances into subsurface irradiance reflectance values. These reflectance values were comparable to in situ reflectance spectra measured during the Hyperion overpass, except at longer wavelengths (beyond 700 nm), where reflectance values were contaminated by severe atmospheric adjacency effects. Chlorophyll-a and tripton concentrations were retrieved by inverting two Hyperion bands selected using a sensitivity analysis applied to the bio-optical model. The sensitivity analysis indicated that the assessment of coloured dissolved organic matter was not achievable in this study due to the limited coloured dissolved organic matter concentration range of the lake, resulting in reflectance differences below the environmental measurement noise of Hyperion. The chlorophyll-a and tripton image-products were compared to in situ data collected during the Hyperion overpass, both by traditional sampling techniques (8 points) and by continuous flow-through systems (32 km). For chlorophyll-a the correlation coefficient between in situ point stations and Hyperion-inferred concentrations was 0.77 (data range from 1.30 to 2.16 mg m(-3)). The Hyperion-derived chlorophyll-a concentrations also match most of the flow-through transect data. For tripton, the validation was constrained by variable re-suspension phenomena. The correlation coefficient between in situ point stations and Hyperion-derived concentrations increased from 0.48 to 0.75 (data range from 0.95 to 2.13 g m(-3)) if the sampling data from the re-suspension zone was avoided. The comparison of Hyperionderived tripton concentrations and flow-through transect data exhibited a similar mismatch. The results of this research suggest further studies to address compatibilities of validation methods for water body features with a high rate of change, and to reduce the contamination by atmospheric adjacency effects on Hyperion data at longer wavelengths in Alpine environment. The transferability of the presented method to other sensors and the ability to assess water quality independent from in situ water quality data, suggest that management relevant applications for Lake Garda (and other subalpine lakes) could be supported by remote sensing.

  • 10.
    Gålfalk, Magnus
    et al.
    Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences.
    Bastviken, David
    Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences.
    Approaches for hyperspectral remote flux quantification andvisualization of GHGs in the environment2017In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 191, 81-94 p.Article in journal (Refereed)
    Abstract [en]

    Methane (CH4) and nitrous oxide (N2O) are two very potent greenhouse gases, with highly heterogeneous distributionsin both space and time. Mapping hot-spots and source areas, and measuring fluxes in different environmentshas so far not been possible on a local scale using direct measurements. We have developed amethod for simultaneous mapping of methane (CH4) and nitrous oxide (N2O), also including water vapor(H2O), using ground-based remote sensing on a landscape-sized scale by utilizing Imaging Fourier TransformSpectrometers (IFTS) with high spectral resolution and imaging rates. The approach uses calculated libraries oftransmission spectra at the spectroscopic resolutions of the IFTS, based on the HITRAN database of spectroscopiclines and our own line-by-line radiative transfer model (LBLRTM). For each species, 1024 spectra have beenmade, resulting in 10243 combinations of column densities. Using an adaptive grid, solutions are found foreach line of sight at a spectral resolution of up to 0.25 cm−1 using the full spectral region of the detector. Themodeling ismulti-layered, calculating temperatures of the background, air, and any additional gas layers, also accountingfor reflected cold sky. Background distances can bemapped fromthe amount of water vapor in each lineof sight. The described approach can be used to identify sources, quantify gas distributions, and to calculate fluxes.Visualizations can produce gas distribution images, as well as air motion videos, which are used to map fluxesusing the same data set, without the need for additional instruments for wind measurements.

  • 11. Gålfalk, Magnus
    et al.
    Olofsson, Göran
    Stockholm University, Faculty of Science, Department of Astronomy.
    Bastviken, David
    Approaches for hyperspectral remote flux quantification and visualization of GHGs in the environment2017In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 191, 81-94 p.Article in journal (Refereed)
    Abstract [en]

    Methane (CH4) and nitrous oxide (N2O) are two very potent greenhouse gases, with highly heterogeneous distributions in both space and time. Mapping hot-spots and source areas, and measuring fluxes in different environments has so far not been possible on a local scale using direct measurements. We have developed a method for simultaneous mapping of methane (CH4) and nitrous oxide (N2O), also including water vapor (H2O), using ground-based remote sensing on a landscape-sized scale by utilizing Imaging Fourier Transform Spectrometers (IFTS) with high spectral resolution and imaging rates. The approach uses calculated libraries of transmission spectra at the spectroscopic resolutions of the IFTS, based on the HITRAN database of spectroscopic lines and our own line-by-line radiative transfer model (LBLRTM). For each species, 1024 spectra have been made, resulting in 10243 combinations of column densities. Using an adaptive grid, solutions are found for each line of sight at a spectral resolution of up to 0.25 cm(-1) using the full spectral region of the detector. The modeling is multi-layered, calculating temperatures of the background, air, and any additional gas layers, also accounting for reflected cold sky. Background distances can be mapped from the amount of water vapor in each line of sight. The described approach can be used to identify sources, quantify gas distributions, and to calculate fluxes. Visualizations can produce gas distribution images, as well as air motion videos, which are used to map fluxes using the same data set, without the need for additional instruments for wind measurements.

  • 12.
    Harvey, E. Therese
    et al.
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
    Kratzer, Susanne
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
    Philipson, Petra
    Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 158, 417-430 p.Article in journal (Refereed)
    Abstract [en]

    The coastal zones are the most inhabited areas of the world and are therefore strongly affected by humans, leading to undesirable environmental changes that may alter the ecosystems, such as eutrophication. In order to evaluate changes in the environment an effective water quality monitoring system for the coastal zones must be in place. The chlorophyll-a concentration is commonly used as a proxy for phytoplankton biomass and as indicator for eutrophication and it can be retrieved from ocean colour remote sensing data. Several operational monitoring systems based on remote sensing are in place to monitor the open sea and, to some extent, the coastal zones. However, evaluations of coastal monitoring systems based on satellite data are scarce. This paper compares the chlorophyll-a concentrations retrieved from an operational satellite system based on MERIS (Medium Resolution Imaging Spectrophotometer) data with ship-based monitoring for the productive seasons in 2008 and 2010, in a coastal area in the Baltic Sea. The comparisons showed that the satellite-based monitoring system is reliable and that the estimations of chlorophyll-a concentration are comparable to in situ measurements in terms of accuracy and quantitative retrieval. A very strong correlation was found between measurements from satellite-derived chlorophyll-a compared to in situ measurements taken close in time (0-3 days), with RMSE of 64% and a MNB of 17%. The comparison of the monthly means showed improved RMSE and a MNB of only 8%. Furthermore, this study shows that MERIS is better at capturing spatial dynamics and the extent of phytoplankton blooms than ship-based monitoring, since it has a synoptic view and higher temporal resolution. Satellite-based monitoring also increases the frequency of chlorophyll-a observations considerably, where the degree of improvement is dependent on the sampling frequency of the respective monitoring programme. Our results show that ocean colour remote sensing can, when combined with field sampling, provide an improved basis for more effective monitoring and management of the coastal zone. These results are important for eutrophication assessment and status classifications of water basins and can be applied to a larger extent within national and international agreements considering the coastal zones, e.g. the European Commission's Water Framework Directive.

  • 13. Jonsson, A. M.
    et al.
    Eklundh, L.
    Hellstrom, M.
    Bärring, Lars
    SMHI, Research Department, Climate research - Rossby Centre.
    Jonsson, P.
    Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology2010In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 114, no 11, 2719-2730 p.Article in journal (Refereed)
    Abstract [en]

    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.

  • 14.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Johansson, Erik
    SMHI, Research Department, Atmospheric remote sensing.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Advancing the uncertainty characterisation of cloud masking in passive satellite imagery: Probabilistic formulations for NOAA AVHRR data2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 158, 126-139 p.Article in journal (Refereed)
    Abstract [en]

    Two alternative methods for probabilistic cloud masking of images from the Advanced Very High Resolution Radiometer (AVHRR) sensor have been examined. Both methods are based on Bayesian theory and were trained using data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. Results were evaluated by comparing to independent CALIPSO-CALIOP observations and to a one-year ground-based cloud dataset composed from five different remote sensing systems over the observation site in Cabauw in the Netherlands. In addition, results were compared to two different cloud masks; one derived from the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor and one from the Climate Monitoring Satellite Application Facility Clouds (CMSAF), Albedo and Radiation dataset from AVHRR data (CLARA-A1). It was demonstrated that the probabilistic methods compare well with the referenced satellite datasets and for daytime conditions they provide even better performance than the reference methods. Among the two probabilistic approaches, it was found that the formulation based on a Naive Bayesian formulation (denoted PPS-Prob Naive) performed clearly superior to the formulation based on a linear summation of conditional cloud probabilities (denoted PPS-Prob SPARC) for daytime conditions. For the study based on the observations over the Cabauw site, the overall daytime Kuipers Skill Score for PPS-Prob Naive was 0.84, for PPS-Prob SPARC 0.79, for CLARA-A1 0.74 and for SEVIRI 0.66. Corresponding results for night-time conditions were less favourable for the probabilistic formulations (Kuipers Skill Score 0.74 for PPS-Prob Naive, 0.68 for PPS-Prob SPARC, 0.80 for CLARA-A1 and 0.79 for SEVIRI) but still relatively close to the reference dataset The Cabauw distribution of cloudiness occurrences in different octa categories was reproduced very closely by all methods, including the probabilistic formulations. Results based on Cabauw observations were also largely in good agreement with results deduced from comparisons with the CALIPSO-CALIOP cloud mask. The PPS-Prob Naive approach will be implemented in an upcoming version of the Polar Platform System (PPS) cloud software issued by the EUMETSAT Nowcasting Satellite Application Facility (NWC SAF). It will also be used in the second release of the CMSAF CLARA cloud climate data record based on historic AVHRR GAC data (to be denoted CIARA-A2). (C) 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-SA license

  • 15.
    Kratzer, Susanne
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK). Stockholm University, Faculty of Science, Department of Systems Ecology.
    Brockmann, Carsten
    Moore, Gerald
    Using MERIS full resolution data to monitor coastal waters: A case study from Himmerfjärden, a fjord-like bay in the northwestern Baltic Sea2008In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 112, no 5, 2284-2300 p.Article in journal (Refereed)
    Abstract [en]

    In this paper we investigate if MERIS full resolution (FR) data (300 m) is sufficient to monitor changes in optical constituents in Himmerfjärden, a fjord-like, north– south facing bay of about 30 km length and 4 km width. The MERIS FR products were derived using a coastal processor (FUB Case-2 Plug-In). We also compared the performance between FUB and standard processor (MEGS 7.4), using reduced resolution (RR) data (1 km resolution) from the open Baltic Sea, and compared the products to sea-truthing data. The optical variables measured for seatruthing

    were chlorophyll, suspended particulate matter (SPM), as well as coloured dissolved organic matter (CDOM, also termed yellow substances), and the spectral diffuse attenuation coefficient, K d (490). The comparison of the RR data to the sea-truthing data showed that, in the open Baltic Sea, the MERIS standard processor overestimated chlorophyll by about 59%, and SPM by about 28%, and underestimated yellow substance by about 81%, whereas the FUB processor underestimated SPM by about 60%, CDOM by about 78%, and chlorophyll a by about 56%.

    The FUB processor showed a relatively high precision for all optical components (standard deviation: 6– 18%), whereas the precision for the MEGS 7.4 was rather low (standard deviation: 43– 73%), except for CDOM (standard deviation: 13%). The analysis of the FR data showed that all FR level 2 water products derived from MERIS followed a polynomial decline in concentration when moving off-shore. The distribution of chlorophyll and SPM was best described by a 2nd order polynomial, and the distribution of CDOM by a 3rd order polynomial, verifying the

    diffusional model described in Kratzer and Tett [Kratzer, S. and Tett, P. (in press). Using bio-optics to investigate the extent of coastal waters— a Swedish case study. Hydrobiologia.]. A new K d (490) and Secchi depth algorithm based on MERIS channel 3 (490 nm) and channel 6 (620 nm) each was derived from radiometric sea-truthing data (TACCS, Satlantic). Applying the K d (490) algorithm to the MERIS FR data over Himmerfjärden, and comparing to sea-truthing data the results showed a strong correlation (r =0.94). When comparing the FR data to the seatruthing

    data CDOM and K d (490) showed a low accuracy, but a high precision with a rather constant off-set. In summary, one may state that the precision of MERIS data improves by applying the FUB Case-2 processor and the accuracy improves with improved spatial resolution for chlorophyll and SPM. Furthermore, the FUB processor can be used off-the-shelf for open Baltic Sea monitoring, provided one corrects for the respective off-set from sea-truthing data which is most likely caused by an inaccuracy in the atmospheric correction. Additionally, the FR data can

    be used to derive CDOM, K d (490) and Secchi depth in Himmmerfjärden if one corrects for the respective off-set. We will need to perform more comparisons between sea-truthing and MERIS FR data before the new K d (490) algorithm can be made operational, including also scenes from other times of year. In order to provide a level 2 product that can be used reliably by the Baltic Sea user community, our recommendation to ESA is to include the spectral attenuation coefficient as a MERIS standard product.

  • 16.
    Krishnaswamy, Jagdish
    et al.
    Stockholm University, Stockholm Resilience Centre.
    Bawa, Kamaijit S.
    Ganeshaiah, K. N.
    Kiran, M. C.
    Quantifying and mapping biodiversity and ecosystem services: Utility of a multi-season NDVI based Mahalanobis distance surrogate2009In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 113, no 4, 857-867 p.Article in journal (Refereed)
    Abstract [en]

    There is an urgent need for techniques to rapidly and periodically measure biodiversity and ecosystem services over large landscapes. Conventional vegetation classification and mapping approaches are based on discrete arbitrary classes which do not capture gradual changes in forest type (and corresponding biodiversity and ecosystem services values) from site to site. We developed a simple multi-date NDVI based Mahalanobis distance measure (called eco-climatic distance) that quantifies forest type variability across a moisture gradient for complex tropical forested landscapes on a single ecologically interpretable, continuous scale. This Mahalanobis distance, unlike other distance measures takes into account the variability in the reference class and shared information amongst bands as it is based on the covariance matrix, and therefore is most useful to summarize ecological distance of a pixel to a reference class in multi-band remotely sensed space In this study we successfully apply this measure as a surrogate for tree biodiversity and ecosystem services at two nested scales for the Western Chats Bio-diversity hotspot. Data from over 500 tree-plots and forest type maps was used to test the ability of this remotely sensed distance to be a surrogate for abundance based tree-species compositional turn-over and as a continuous measure of forest type and ecosystem services. Our results suggest a strong but scale dependant relationship between the remotely-sensed distance measure and floristic distance between plots. The multi-date NDVI distance measure emerges as very good quantitative surrogate for forest type and is a useful complement to existing forest classification systems. This surrogate quantifies forest type variability on a single, continuous quantitative scale and has important applications in conservation planning and mapping and monitoring of hydrologic and carbon storage and sequestration services.

  • 17.
    Kutser, Tiit
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    The possibility of using the Landsat image archive for monitoring long time trends in coloured dissolved organic matter concentration in lake waters2012In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 123, 334-338 p.Article in journal (Refereed)
    Abstract [en]

    Recent studies indicate that lakes are regulators of carbon cycling and climate. Therefore, it is important to know how the lake carbon content has changed over the last decades. In situ long time data series about the amount of dissolved organic carbon (DOC) in lakes are rare. The only potential way to study retrospectively the changes in lake carbon over the last decades is by means of remote sensing data provided there are sensors that can provide data about coloured dissolved organic matter (CDOM) in lakes over long periods. Landsat data archive contains images from 1984 to nowadays and covers the whole Earth. Although the sensors were not designed for remote sensing of aquatic environments it is still tempting to utilise the long data series. Landsat 4, Landsat 5 and Landsat 7 imagery available in free Landsat image archive was compared with time series of CDOM in situ data from 19 sampling stations available in the Swedish University of Natural Sciences lake monitoring database. There was no correlation between the image and in situ data when all the above mentioned data were used. Low radiometric resolution of the sensor, small size of many lakes (= large adjacency effects) and high concentration of CDOM (negligible water leaving radiation) could be the reasons. The results were more promising (R-2 = 0.62) when Lake Malaren stations were analysed separately. The lake is sufficiently large and with variable, but not extremely high. CDOM content. The Lake Malaren in situ data showed very different trends in CDOM concentrations in different basins of the lake over the last 45 years. Although the correlation between the image and in situ data was a bit low for accurate daily estimation of CDOM concentrations from Landsat data it could allow detecting general trends in lake CDOM content. Unfortunately, there is currently a gap in Landsat archive (for our study sites) between 1988 and 1998 which makes calculations of long time trends unreasonable for the time being. (C) 2012 Elsevier Inc. All rights reserved.

  • 18.
    Kutser, Tiit
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    Alikas, Krista
    Kothawala, Dolly N.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    Kohler, Stephan J.
    Impact of iron associated to organic matter on remote sensing estimates of lake carbon content2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 156, 109-116 p.Article in journal (Refereed)
    Abstract [en]

    There is a strong need to develop remote sensing methods for mapping lake carbon content on regional to global scales. The use of in situ methods is impractical for monitoring lake water quality over large geographical areas, which is a fundamental requirement to understand the true role of lakes in the global carbon cycle. The coloured component of dissolved organic carbon (DOC), called CDOM, absorbs light strongly in the blue part of the visible spectrum and can be used as a proxy for mapping lake DOC with remote sensing. However, iron associated to organic matter can cause extra browning of waters. Consequently, the remote sensing signal we interpret as DOC may partially be attributed to the presence of iron associated to organic matter, potentially hampering our ability to estimate carbon concentrations. A thorough analysis of biogeochemical parameters was carried out on Lake Malaren on August 23, 2010, and a MERIS full resolution image was acquired simultaneously. MERIS standard, Case 2 Regional, and Boreal processors were used to calculate remote sensing products, which were compared with different lake water characteristics. The carbon to iron ratio was different from the rest of the lake in one of the basins. MERIS standard and Case 2 Regional processors were sensitive to this difference as the correlation between MERIS CDOM product and DOC was low (R-2 = 0.43) for all sampling stations and increased to 0.92 when the one basin was excluded. The Boreal Lakes processor results were less disturbed by the different carbon-iron ratios found in one basin and produced reasonably good results (R-2 = 0.65). We found MERIS products (e.g. total absorption) that provided good correlation (R-2 = 0.80) with DOC-specific absorbance at 254 nm, called SUVA, which is a metric commonly used to assess drinking water treatability. However, none of the MERIS products were suitable for mapping the total organic carbon in Lake Malaren.MERIS total suspended matter product was a good (R-2 = 0.73) proxy for particulate iron, meaning that the particulate iron content in Malaren can be mapped from space. (C) 2014 Elsevier Inc. All rights reserved.

  • 19.
    Kutser, Tiit
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    Verpoorter, Charles
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    Paavel, Birgot
    Tranvik, Lars J.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Limnology.
    Estimating lake carbon fractions from remote sensing data2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 157, 138-146 p.Article in journal (Refereed)
    Abstract [en]

    Issues like monitoring lake water quality, studying the role of lakes in the global carbon cycle or the response of lakes to global change require data more frequently and/or over much larger areas than the in situ water quality monitoring networks can provide. The aim of our study was to investigate whether it is feasible to estimate different lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO(2)) from space using sensors like OLCI on future Sentinel 3. In situ measurements were carried out in eight measuring stations in two Swedish lakes within 2 days of MERIS overpass. The results suggest that the MERIS CDOM product was not suitable for estimating CDOM in lakes Malaren and Tamnaren and was not a good proxy for mapping lake DOC and TOC from space. However, a simple green to red band ratio and some other MERIS products like the total absorption coefficient, turbidity index, suspended matter and chlorophyll-a were correlated with different carbon fractions and could potentially be used as proxies to map these lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO2) from space. (C) 2014 Elsevier Inc All rights reserved.

  • 20.
    Michelson, Daniel
    et al.
    SMHI, Core Services.
    Liljeberg, B M
    Pilesjo, P
    Comparison of algorithms for classifying Swedish landcover using Landsat TM and ERS-1 SAR data2000In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 71, no 1, 1-15 p.Article in journal (Refereed)
    Abstract [en]

    Sixteen landcover classes in a representative Swedish environment were analyzed and classified using one Landsat TM scene and seven ERS-1 SARPRI images acquired during 1993. Spectral and backscattering signature separabilities are analyzed using the Jeffries-Matusita distance measure to determine which combinations of channels/images contained the most information. Maximum likelihood, sequential maximum a posteriori (SMAP, a Bayesian image segmentation algorithm), and back propagation neural network classification algorithms were applied and their performances evaluated. Results of the separability analyses indicated that the multitemporal SAR data contained more separable landcover information than did the multispectral TM data; the highest separabilities were achieved when the TM and SAR data were combined. Classification accuracy evaluation results indicate that the SMAP algorithm out-performed the maximum likelihood algorithm which, in turn, outperformed the neural network algorithm. The best KAPPA values, using combined data, were 0.495 for SMAP, 0.0445 for maximum likelihood, and 0.432 for neural network. Corresponding overall accuracy values were 57.1%, 52.4%, and 51.2%, respectively. A comparison between lumped crop area statistics with areal sums calculated from the classified satellite data gave the highest correspondence where the SMAP algorithm was used, followed by the maximum likelihood and neural network algorithms. Based on our application, we can therefore confirm the value of a multisource optical/SAR approach for analyzing landcover and the improvements to classification achieved using the SMAP algorithm. (C)Elsevier Science Inc., 2000.

  • 21.
    Mortin, Jonas
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Howell, Stephen E. L.
    Climate Research Division, Environment Canada.
    Wang, Libo
    Climate Research Division, Environment Canada.
    Derksen, Chris
    Climate Research Division, Environment Canada.
    Svensson, Gunilla
    Stockholm University, Faculty of Science, Department of Meteorology .
    Graversen, Rune G.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Schrøder, Thomas M.
    California Institute of Technology, USA.
    Extending the QuikSCAT record of seasonal melt–freeze transitions over Arctic sea ice using ASCAT2014In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 141, no 5, 214-230 p.Article in journal (Refereed)
    Abstract [en]

    The seasonal melt–freeze transitions are important to continuously monitor over Arctic sea ice in order to better understand Arctic climate variability. The Ku-band scatterometer QuikSCAT (13.4 GHz), widely used to retrieve pan-Arctic seasonal transitions, discontinued its decadal long record in 2009. In this study, we show that the C-band scatterometer ASCAT (5.3 GHz), in orbit since 2006 and with an anticipated lifetime through 2021, can be used to extend the QuikSCAT record of seasonal melt–freeze transitions. This is done by (1) comparing back- scatter measurements over multiyear and first-year ice, and by (2) retrieving seasonal transitions from resolution-enhanced ASCAT and QuikSCAT measurements and comparing the results with independent datasets. Despite operating in different frequencies, ASCAT and QuikSCAT respond similarly to surface transitions. However, QuikSCAT measurements respond slightly stronger to the early melt of first-year ice, making it less sensitive to sea-ice dynamics. To retrieve the transitions, we employed an improved edge-detector algorithm, which was iterated and constrained using sea-ice concentration data, efficiently alleviating unreasonable outliers. This gives melt–freeze transitions over all Arctic sea ice north of 60°N at a 4.45 km resolution during 1999–2009 and 2009–2012 for QuikSCAT and ASCAT, respectively. Using the sensor overlap period, we show that the retrieved transitions retrieved from the different instruments are largely consistent across all regions in the Arctic sea-ice domain, indicating a robust consistency.

  • 22. Olsson, Per-Ola
    et al.
    Lindström, Johan
    Eklundh, Lars
    Near real-time monitoring of insect induced defoliation in subalpine birch forests with MODIS derived NDVI2016In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 181, 42-53 p.Article in journal (Refereed)
    Abstract [en]

    Abstract Forestry and nature conservation can benefit from rapid on-line information on forest disturbances, such as insect attacks. This type of information would facilitate timely field studies and enable more rapid counter measures, as well as enable studies of the dynamics of an insect outbreak. In this study we developed a method based on MODIS derived NDVI for near real-time monitoring of insect induced forest defoliation in a subalpine birch forest in northern Sweden. The method is based on deviations from a seasonal trajectory of NDVI representing forest conditions without disturbances. A Kalman filter is applied to handle noise and satellite-derived NDVI observations of low quality, and cumulative sums (CUSUM) of the deviations from the seasonal trajectory representing undisturbed forests are used to detect disturbances. An annual offset of the seasonal trajectory is introduced in CUSUM to handle inter-annual variability in the start of season. Evaluation of the method showed that 74% of the defoliation was detected with a misclassification of undisturbed areas of 39% in MODIS pixels with at least 50% birch forest cover. The ability of the method to detect defoliation can be adjusted to fit the purpose of a study; with a higher threshold applied, 100% of the defoliation in the evaluation data was detected with 56% of the undisturbed areas misclassified as defoliated. The method also facilitates studies of the intra-seasonal temporal dynamics of an insect outbreak, which is a major advantage compared to methods that classifies pixels into undisturbed or defoliated for an entire season. Furthermore, the method can be extended to monitor within-season refoliation after an insect outbreak.

  • 23. Pierson, Donald C.
    et al.
    Kratzer, Susanne
    Strombeck, Niklas
    Håkansson, Bertil
    SMHI, Core Services.
    Relationship between the attenuation of downwelling irradiance at 490 nm with the attenuation of PAR (400 nm-700 nm) in the Baltic Sea2008In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 112, no 3, 668-680 p.Article in journal (Refereed)
    Abstract [en]

    The vertical attenuation coefficient of diffuse downwelling irradiance at 490 nm (K-d 490) is a parameter that we routinely derive from SeaWiFS images of the Baltic Sea. Here, through model simulations, we examine the relationship between Kd(490), and the vertical attenuation coefficient of PAR (Kd PAR), as this later coefficient determines the light available for aquatic photosynthesis. A simple semi-analytical model is used to predict Kd(490) and Kd(PAR), as a function of the concentrations of chlorophyll, colored dissolved organic material (CDOM), suspended inorganic, and suspended organic particulate material. A series of model simulations based on variations in these optically significant constituents over a range realistic for the Baltic Sea, are used to define the relationship between the two attenuation coefficients. K-d(PAR) = 0.6677K(d)(490)(0.6763). This relationship was verified, using data collected independently from the data set used to derive model coefficients, and appears robust when applied to the Baltic Sea. Comparison to other studies and model sensitivity analyses suggest that the relationship will be dependent on relatively large regional variations in CDOM absorption. A relationship between K-d(490) and Secchi disk depth was also developed and verified. This relationship while useful was more uncertain. The uncertainty was related to a greater influence of scattering on Secchi disk depth estimates and the corresponding parameterization of scattering in our model. (C) 2007 Elsevier Inc. All rights reserved.

  • 24.
    Pierson, Donald C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Evolution, Limnology.
    Kratzer, Susanne
    Strömbeck, Niklas
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Evolution, Limnology.
    Hakansson, Bertil
    Relationship between the attenuation of downwelling irradiance at 490 nm with the attenuation of PAR (400 nm-700 nm) in the Baltic Sea2008In: Remote Sensing of Environment, ISSN 0034-4257, Vol. 112, no 3, 668-680 p.Article in journal (Refereed)
    Abstract [en]

    The vertical attenuation coefficient of diffuse downwelling irradiance at 490 nm (K-d 490) is a parameter that we routinely derive from SeaWiFS images of the Baltic Sea. Here, through model simulations, we examine the relationship between Kd(490), and the vertical attenuation coefficient of PAR (Kd PAR), as this later coefficient determines the light available for aquatic photosynthesis. A simple semi-analytical model is used to predict Kd(490) and Kd(PAR), as a function of the concentrations of chlorophyll, colored dissolved organic material (CDOM), suspended inorganic, and suspended organic particulate material. A series of model simulations based on variations in these optically significant constituents over a range realistic for the Baltic Sea, are used to define the relationship between the two attenuation coefficients. K-d(PAR) = 0.6677K(d)(490)(0.6763). This relationship was verified, using data collected independently from the data set used to derive model coefficients, and appears robust when applied to the Baltic Sea. Comparison to other studies and model sensitivity analyses suggest that the relationship will be dependent on relatively large regional variations in CDOM absorption. A relationship between K-d(490) and Secchi disk depth was also developed and verified. This relationship while useful was more uncertain. The uncertainty was related to a greater influence of scattering on Secchi disk depth estimates and the corresponding parameterization of scattering in our model.

  • 25. Rees, W G
    et al.
    Tutubalina, O V
    Golubeva, E I
    Reflectance spectra of subarctic lichens between 400 and 2400 nm2004In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 90, no 3, 281-292 p.Article in journal (Refereed)
    Abstract [en]

    We present hyperspectral reflectance measurements for a number of common crustose and fruticose lichens from subarctic Sweden, and describe their common spectral features and principal differences. We confirm previous work that showed the spectrum beyond the water absorption at 1940 urn to be particularly characteristic of crustose lichens, and some previous work on the effect of drying fruticose lichens on their reflectance spectra. We discuss the implications of our data for optimal techniques for discriminating between different lichen species. (C) 2004 Elsevier Inc. All rights reserved.

  • 26. Santoro, Maurizio
    et al.
    Beaudoin, Andre
    Beer, Christian
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
    Cartus, Oliver
    Fransson, Johan B. S.
    Hall, Ronald J.
    Pathe, Carsten
    Schmullius, Christiane
    Schepaschenko, Dmitry
    Shvidenko, Anatoly
    Thurner, Martin
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry. Max-Planck Institute for Biogeochemistry, Germany.
    Wegmueller, Urs
    Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 168, 316-334 p.Article in journal (Refereed)
    Abstract [en]

    This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10 degrees N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01 degrees were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (<30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (>300 m(3)/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%).

  • 27. Stengel, M.
    et al.
    Mieruch, S.
    Jerg, M.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Scheirer, Ronald
    SMHI, Research Department, Atmospheric remote sensing.
    Maddux, B.
    Meirink, J. F.
    Poulsen, C.
    Siddans, R.
    Walther, A.
    Hollmann, R.
    The Clouds Climate Change Initiative: Assessment of state-of-the-art cloud property retrieval schemes applied to AVHRR heritage measurements2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 162, 363-379 p.Article in journal (Refereed)
    Abstract [en]

    Cloud property retrievals from 3 decades of the Advanced Very High Resolution Radiometer (AVHRR) measurements provide a unique opportunity for a long-term analysis of clouds. In this study, the accuracy of AVHRR-derived cloud properties cloud mask, cloud-top height, cloud phase and cloud liquid water path is assessed using three state-of-the-art retrieval schemes. In addition, the same retrieval schemes are applied to the AVHRR heritage channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) to create AVHRR-like retrievals with higher spatial resolution and based on presumably more accurate spectral calibration. The cloud property retrievals were collocated and inter-compared with observations from CloudSat, CALIPSO and AMSR-E The resulting comparison exhibited good agreement in general. The schemes provide correct cloud detection in 82 to 90% of all cloudy cases. With correct identification of clear-sky in 61 to 85% of all clear areas, the schemes are slightly biased towards cloudy conditions. The evaluation of the cloud phase classification shows correct identification of liquid clouds in 61 to 97% and a correct identification of ice clouds in 68 to 95%, demonstrating a large variability among the schemes. Cloud-top height (CTH) retrievals were of relatively similar quality with standard deviations ranging from 2.1 km to 2.7 km. Significant negative biases in these retrievals are found in particular for cirrus clouds. The biases decrease if optical depth thresholds are applied to determine the reference CTH measure. Cloud liquid water path (LWP) is also retrieved well with relative low standard deviations (20 to 28 g/m(2)), negative bias and high correlations. Cloud ice water path (IWP) retrievals of AVHRR and MODIS exhibit a relative high uncertainty with standard deviations between 800 and 1400 g/m2, which in relative terms exceed 100% when normalized with the mean IWP. However, the global histogram distributions of IWP were similar to the reference dataset MODIS retrievals are for most comparisons of slightly better quality than AVHRR-based retrievals. Additionally, the choice of different near-infrared channels, 3.7 mu M as opposed to 1.6 mu m, can have a significant impact on the retrieval quality, most pronounced for IWP, with better accuracy for the 1.6 mu m channel setup. This study presents a novel assessment of the quality of cloud properties derived from AVHRR channels, which quantifies the accuracy of the considered retrievals based on common approaches and validation data. Furthermore, it assesses the capabilities of AVHRR-like spectral information for retrieving cloud properties in the light of generating climate data records of cloud properties from three decades of AVHRR measurements. (C) 2013 Elsevier Inc. All rights reserved.

  • 28. Sterckx, S.
    et al.
    Knaeps, S.
    Kratzer, Susanne
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
    Ruddick, K.
    SIMilarity Environment Correction (SIMEC) applied to MERIS data over inland and coastal waters2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 157, 96-110 p.Article in journal (Refereed)
    Abstract [en]

    The launch of several new satellites such as Sentinel-2, Sentinel-3, HyspIRI, EnMAP and PRISMA in the very near future, opens new perspectives for the inland and coastal water community. The monitoring of the water quality closer to the coast, within estuaries or small lakes with satellite data will become feasible. However for these inland and nearshore coastal waters, adjacency effects may hamper the correct retrieval of water quality parameters from remotely sensed imagery. Here, we present a sensor-generic adjacency pre-processing method, SIMilarity Environment Correction (SIMEC). The correction algorithm estimates the contribution of the background radiance based on the correspondence with the Near-INfrared (NIR) similarity spectrum. The performance of SIMEC was tested on MERIS FR images both above highly reflecting waters with high SPM loads, as well as dark lake waters with high CDOM absorption. The results show that SIMEC has a positive or neutral effect on the normalized remote sensing reflectance above optically-complex waters, retrieved with the MERIS MEGS or UR processor.

1 - 28 of 28
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