Technical note. Illustration of the influence of shadowing on high latitude information derived from satellite imagery

Two separate types of contamination by shadowing have been identified following an analysis of two Thematic Mapper scenes from the Arctic. The well-established effect of orographic shadowing is particularly important for cryospheric surfaces. Cirrus clouds, often very difficult to identify by automated techniques, also cast shadows which decrease the radiances detected from snow and ice surfaces. These effects are illustrated here in relation to snow mapping algorithms.     

Adapting a global stratified random sample for regional estimation of forest cover change derived from satellite imagery

A desirable feature of a global sampling design for estimating forest cover change based on satellite imagery is the ability to adapt the design to obtain precise regional estimates, where a region may be a country, state, province, or conservation area. A sampling design stratified by an auxiliary variable correlated with forest cover change has this adaptability. A global stratified random sample can be augmented by additional sample units within a region selected by the same stratified protocol and the resulting sample constitutes a stratified random sample of the region. Stratified sampling allows increasing the sample size in a region by a few to many additional sample units. The additional sample units can be effectively allocated to strata to reduce the standard errors of the regional estimates, even though these strata were not initially constructed for the objective of regional estimation. A complete coverage map of deforestation within the Brazilian Legal Amazon (BLA) is used as a population to evaluate precision of regional estimates obtained by augmenting a global stratified random sample. The standard errors of the regional estimates for the BLA and states within the BLA obtained from the augmented stratified design were generally smaller than those attained by simple random sampling and systematic sampling.     

Recent elevation changes of Svalbard glaciers derived from ICESat laser altimetry

We have tested three methods for estimating 2003-2008 elevation changes of Svalbard glaciers from multi-temporal ICESat laser altimetry: (a) linear interpolation of crossover points between ascending and descending tracks, (b) projection of near repeat-tracks onto common locations using Digital Elevation Models (DEMs), and (c) least-squares fitting of rigid planes to segments of repeat-track data assuming a constant elevation change rate. The two repeat-track methods yield similar results and compare well to the more accurate, but sparsely sampled, crossover points. Most glacier regions in Svalbard have experienced low-elevation thinning combined with high-elevation balance or thickening during 2003-2008. The geodetic mass balance (excluding calving front retreat or advance) of Svalbard's 34,600 km² glaciers is estimated to be −4.3 ± 1.4 Gt y⁻¹, corresponding to an area-averaged water equivalent (w.e.) balance of −0.12 ± 0.04 m w.e. y⁻¹. The largest ice losses have occurred in the west and south, while northeastern Spitsbergen and the Austfonna ice cap have gained mass. Winter and summer elevation changes derived from the same methods indicate that the spatial gradient in mass balance is mainly due to a larger summer season thinning in the west and the south than in the northeast. Our findings are consistent with in-situ mass balance measurements from the same period, confirming that repeat-track satellite altimetry can be a valuable tool for monitoring short term elevation changes of Arctic glaciers.     

Extraction of bajadas from digital elevation models and satellite imagery

A methodology was designed for the extraction of bajadas from the 15 min US Geological Survey digital elevation models and Landsat Thematic Mapper imagery. The method was demonstrated for the Death Valley-California where progressive eastward tilting has enabled the west-side fans to coalesce and form bajadas. First, the drainage that crossed the uplands and the bajadas was extracted from the DEM. The drainage pixels were successively grown by checking the surrounding pixels on the basis of their gradient. It was concluded that for gradient in the interval [2°,11°] the upslope bajadas border was segmented. In order to eliminate the drainage pixels that belonged to the uplands, the drainage pixels were subtracted. Then, the isolated small 8-connected foreground pixels were identified and subtracted too. Finally, region growing was performed again to the remaining pixels with the same growing criterion. Isolated 8-connected background pixels, representing almost flat regions inside bajadas, were identified and merged to the segmented pixels. At the end, by taking into account the spectral response in the satellite image, the downslope border of bajadas was segmented. The extracted polygon was in agreement with the information depicted on (a) the US Geological Survey topographic map of scale 1:100,000 and (b) the satellite image and (c) the polygon classified manually by a photo-interpreter.     

Development and validation of a technique for merging satellite derived aerosol optical depth from SeaWiFS and MODIS

Merging time series of satellite derived aerosol products from independent missions can support aerosol science by combining in a consistent way temporally overlapping data sets and by increasing data coverage. A merging technique applied to satellite aerosol optical depth τ_a is presented and tested with SeaWiFS and MODIS-Aqua data. The technique relies on least squares fitting of the available τ_a spectra onto a linear or second-order polynomial relation between log-transformed τ_a and wavelengths. First, the sensor specific products are compared with field observations collected by a sun-photometer installed on the Acqua Alta Oceanographic Tower in the northern Adriatic Sea. Mean absolute percentage differences are approximately 21% at 412 and 443 nm, and increase with wavelength, with large overestimates in the red and near-infrared bands. The mean absolute differences are typically 0.04. When inter-compared, the 2 satellite products agree well, with mean absolute percentage differences lower than 20% at all wavelengths and little bias. The results of the comparison of the merger outputs with the field data are well in line with the validation results of the sensor specific products, and are comparable for the various merging procedures. The benefits of merging in terms of data coverage are briefly illustrated for the Mediterranean basin.     

Atmospheric correction of optical imagery from MODIS and Reanalysis atmospheric products

In this paper we analyze the differences obtained in the atmospheric correction of optical imagery covering bands located in the Visible and Near Infra-Red (VNIR), Short-Wave Infra-Red (SWIR) and Themal-Infrared (TIR) spectral regions when atmospheric profiles extracted from different sources are used. In particular, three sensors were used, Compact High Resolution Imaging Spectrometer (CHRIS), Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) and Landsat5 Thematic Mapper (TM), whereas four atmospheric profiles sources were considered: i) local soundings launched near the sensor overpass time, ii) Moderate Resolution Radiometer (MODIS) atmospheric profiles product (MOD07), iii) Atmospheric Correction Parameter Calculator (ACPC) generated by the National Center for Environmental Prediction (NCEP) and iv) Modified Atmospheric Profiles from Reanalysis Information (MAPRI), which includes data from NCEP and National Center of Atmospheric Research (NCAR) Reanalysis project but interpolated to 34 atmospheric levels and resampled to 0.5° × 0.5°. MODIS aerosol product (MOD04) was also used to extract Aerosol Optical Thickness (AOT) values at 550 nm. Analysis was performed for three test dates (12th July 2003, 18th July 2004 and 13th July 2005) over an agricultural area in Spain. Results showed that air temperature vertical profiles were similar for the four sources, whereas dew point temperature profiles showed significant differences at some particular levels. Atmospheric profiles were used as input to MODTRAN4 radiative transfer code in order to compute atmospheric parameters involved in atmospheric correction, with the aim of retrieving surface reflectances in the case of VNIR and SWIR regions, and Land Surface Temperature (LST) in the case of the TIR region. For the VNIR and SWIR region, significant differences depending on the atmospheric profile used were not found, particularly in the Visible region in which the AOT content is the main parameter involved in the atmospheric correction. In the case of TIR, differences depending on the atmospheric profile used were appreciable, since in this case the main parameter involved in the atmospheric correction is the water vapor content, which depends on the vertical profile. In terms of LST retrieval from ASTER data (2004 test case), all profiles provided satisfactory results compared to the ones obtained when using a local sounding, with errors of 0.3 K for ACPC and MAPRI cases and 0.7 K for MOD07. When retrieving LST from TM data (2005 test case), errors for MOD07 and MAPRI were 0.6 and 0.9 K respectively, whereas ACPC provided an error of 2 K. The results presented in this paper show that the different atmospheric profile sources are useful for accurate atmospheric correction when local soundings are not available. In particular, MOD07 product provides atmospheric information at the highest spatial resolution, 5 km, although its use is limited from 2000 to present, whereas MAPRI provides historical information from 1970 to present, but at lower spatial resolution.     

Remote sensing of vegetation water content from equivalent water thickness using satellite imagery

Vegetation water content (VWC) is one of the most important parameters for the successful retrieval of soil moisture content from microwave data. Normalized Difference Infrared Index (NDII) is a widely-used index to remotely sense Equivalent Water Thickness (EWT) of leaves and canopies; however, the amount of water in the foliage is a small part of total VWC. Sites of corn (Zea mays), soybean (Glycine max), and deciduous hardwood woodlands were sampled to estimate EWT and VWC during the Soil Moisture Experiment 2005 (SMEX05) near Ames, Iowa, USA. Using a time series of Landsat 5 Thematic Mapper, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Wide Field Sensor (AWiFS) imagery, NDII was related to EWT with R² of 0.85; there were no significant differences among land-cover types. Furthermore, EWT was linearly related to VWC with R² of 0.87 for corn and 0.48 for soybeans, with a significantly larger slope for corn. The 2005 land-cover classification product from the USDA National Agricultural Statistics Service had an overall accuracy of 92% and was used to spatially distribute VWC over the landscape. SMEX05 VWC versus NDII regressions were compared with the regressions from the Soil Moisture Experiment 2002 (SMEX02), which was conducted in the same study area. No significant difference was found between years for corn (P = 0.13), whereas there was a significant difference for soybean (P = 0.04). Allometric relationships relate the size of one part of a plant to the sizes of other parts, and may be the result from the requirements of structural support or material transport. Relationships between NDII and VWC are indirect, NDII is related to canopy EWT, which in turn is allometrically related to VWC.     

Generation of high-resolution East Antarctic landfast sea-ice maps from cloud-free MODIS satellite composite imagery

A method to generate high spatio-temporal resolution maps of landfast sea ice from cloud-free MODIS composite imagery is presented. Visible (summertime) and thermal infrared (wintertime) cloud-free 20-day MODIS composite images are used as the basis for these maps, augmented by AMSR-E ASI sea-ice concentration composite images (when MODIS composite image quality is insufficient). The success of this technique is dependent upon efficient cloud removal during the compositing process. Example wintertime maximum (~ 374,000 km²) and summertime minimum (~ 112,000 km²) fast-ice maps for the entire East Antarctic coast are presented. The summertime minimum map provides the first high-resolution indication of multi-year fast-ice extent, which may be used to help assess changes in Antarctic sea-ice volume. The 2σ errors in fast-ice extent are estimated to be ± 2.98% when ≥ 90% of the fast-ice pixels in a 20-day period are classified using the MODIS composite, or ± 8.76 otherwise (when augmenting AMSR-E or the previous/next MODIS composite image is used to classify > 10% of the fast ice). Imperfect composite image quality, caused by persistent cloud, inaccurate cloud masking or a highly dynamic fast-ice edge, was the biggest impediment to automating the fast-ice detection procedure.     

Improved estimation of aerosol optical depth from MODIS imagery over land surfaces

Estimation of aerosol loadings is of great importance to the studies on global climate changes. The current Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol estimation algorithm over land is based on the “dark-object” approach, which works only over densely vegetated (“dark”) surfaces. In this study, we develop a new aerosol estimation algorithm that uses the temporal signatures from a sequence of MODIS imagery over land surfaces, particularly “bright” surfaces. The estimated aerosol optical depth is validated by Aerosol Robotic Network (AERONET) measurements. Case studies indicate that this algorithm can retrieve aerosol optical depths reasonably well from the winter MODIS imagery at seven sites: four sites in the greater Washington, DC area, USA; Beijing City, China; Banizoumbou, Niger, Africa; and Bratts Lake, Canada. The MODIS aerosol estimation algorithm over land (MOD04), however, does not perform well over these non-vegetated surfaces. This new algorithm has the potential to be used for other satellite images that have similar temporal resolutions.     

Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery

The surface bidirectional reflectance distribution function (BRDF) contains valuable information on canopy physiognomy for desert grassland and grass-shrub transition communities. This information may be accessed by inverting a BRDF model against sets of observations, which encompass important variations in viewing and illumination angles. This paper shows that structural canopy attributes can be derived through inversion of the Simple Geometric Model (SGM) of the BRDF developed in this paper. It is difficult to sample BRDF features from the ground because of the discontinuous nature of the canopies and long intrinsic length scales in remotely sensed spectral measures (>10 m). A multispectral digital camera was therefore used to derive spatial multiangular reflectance data sets from the air and the SGM was validated against and inverted with these. It was also validated using 3-D radiosity simulations driven with maps of field-measured plant dimensions. The interpretation of the retrieved parameter maps (shrub density, shrub width and canopy height) reveals variations in canopy structure within desert grassland and grassland-shrubland transition communities, which are clearly related to structural and optical features in high resolution panchromatic and vegetation index images. To our knowledge, this paper reports on the first attempts to acquire structural canopy attributes of desert landscapes using multiple view angle data at scales less than 1 km. The results point to further opportunities to exploit multiangular data from spaceborne sensors such as the Multiangle Imaging SpectroRadiometer (MISR) and the Compact High Resolution Imaging Spectrometer (CHRIS) on the NASA Terra and European Space Agency's PROBA satellites, respectively.     

Qualitative estimation of camera motion parameters from the linear composition of optical flow

In this paper, we propose a new method for estimating camera motion parameters based on optical flow models. Camera motion parameters are generated using linear combinations of optical flow models. The proposed method first creates these optical flow models, and then linear decompositions are performed on the input optical flows calculated from adjacent images in the video sequence, which are used to estimate the coefficients of each optical flow model. These coefficients are then applied to the parameters used to create each optical flow model, and the camera motion parameters implied in the adjacent images can be estimated through a linear composition of the weighted parameters.We demonstrated that the proposed method estimates the camera motion parameters accurately and at a low computational cost as well as robust to noise residing in the video sequence being analyzed.     

Assessment of apparent and inherent optical properties derived from SeaWiFS with field data

The knowledge of the absorption and scattering characteristics of the ocean supports diverse applications for studying biological and physical processes of marine ecosystems. The determination of the related inherent optical properties from remote sensing is addressed for a site located in the northern Adriatic Sea using coincident SeaWiFS images and field measurements. The proposed methodology first combines regional algorithms to determine the spectra of irradiance reflectance and diffuse attenuation coefficient from the normalized water leaving radiance by accounting for the bidirectional structure of the light field. These spectra are then used as inputs to an inverse model that yields the absorption, scattering, and backscattering coefficients of seawater (considered without the contribution of pure water). The uncertainties associated with the different steps in the sequence of calculations are quantified and discussed. Specifically, the analysis of 48 match-ups comparing in situ irradiance reflectance with that derived from remote sensing water leaving radiance shows mean absolute differences below 20% between 490 and 555 nm and approximately 30% at 443 and 670 nm. Lower discrepancies are obtained if more stringent criteria for the selection of match-ups are implemented (12-15% and 20-22%, respectively). The results obtained with 42 match-ups show a reasonable agreement for the absorption coefficient from 412 to 490 nm (approximately 35%), the scattering coefficient from 443 to 555 nm (approximately 30%), and the attenuation coefficient in the spectral range 412-555 nm (approximately 30%). Based on 17 match-ups, the comparison for the backscattering coefficient gives mean absolute differences in the range of 31-53%. The comparison between field and derived scattering properties suggests that the particulate scattering phase function inherent to the inverse model is not appropriate for the site considered. Finally, in the framework of the selected inversion scheme, uncertainties associated with the satellite derived irradiance reflectance in the blue and the determination of K_d at 490 nm through an empirical band ratio algorithm appear as the elements where improvements would be particularly needed to derive high quality spectra of inherent optical properties.     

Accuracy assessment using sub-pixel fractional error matrices of global land cover products derived from satellite data

Information on land cover distribution at regional and global scales has become fundamental for studying global changes affecting ecological and climatic systems. The remote sensing community has responded to this increased interest by improving data quality and methodologies for extracting land cover information. However, in addition to the advantages provided by satellite products, certain limitations exist that need to be objectively quantified and clearly communicated to users so that they can make informed decisions on whether and how land cover products should be used. Accuracy assessment is the procedure used to quantify product quality. Some aspects of accuracy assessment for evaluating four global land cover maps over Canada are discussed in this paper. Attempts are made to quantify limiting factors resulting from the coarse spatial resolution of data used for generating land cover information at regional and global levels. Sub-pixel fractional error matrices are introduced as a more appropriate way for assessing the accuracy of mixed pixels. For classification with coarse spatial resolution data, limitations of the classification method produce a maximum achievable accuracy defined as the average percent fraction of dominant land cover of all pixels in the mapped area. Relationships among spatial resolution, landscape heterogeneity and thematic resolution were studied and reported. Other factors that can affect accuracy, such as misregistration and legend conversion, are also discussed.     

Optimized extraction of daily bio-optical time series derived from MODIS/Aqua imagery for Lake Tanganyika, Africa

Lake Tanganyika is one of the world's great freshwater ecosystems. In recent decades its hydrodynamic characteristics have undergone important changes that have had consequences on the lake's primary productivity. The establishment of a long-term Ocean Color dataset for Lake Tanganyika is a fundamental tool for understanding and monitoring these changes. We developed an approach to create a regionally calibrated dataset of chlorophyll-a concentrations (CHL) and attenuation coefficients at 490 nm (K490) for the period from July 2002 to December 2006 using daily calibrated radiances retrieved from the MODIS-Aqua sensor. Standard MODIS Aqua Ocean Color products were found to not provide a suitable calibration for high altitude lakes such as the Lake Tanganyika. An optimization of the extraction process and the validation of the dataset were performed with independent sets of in situ measurements. Our results show that for the geographical, atmospheric and optical conditions of Lake Tanganyika: (i) a coastal aerosol model set with high relative humidity (90%) provides a suitable atmospheric correction; (ii) a significant correlation between in situ data and CHL estimates using the MODIS specific OC3 algorithm is possible; and (iii) K490 estimates provide a good level of significance. The resulting validated time series of bio-optical properties provides a fundamental information base for the study of phytoplankton and primary production dynamics and interannual trends. A comparison between surface chlorophyll-a concentrations estimated from field monitoring and from the MODIS based dataset shows that remote sensing allows improved detection of surface blooms in Lake Tanganyika.     

Unified optical flow field approach to motion analysis from a sequence of stereo images

In this paper a new approach to motion analysis from stereo image sequences using unified temporal and spatial optical flow field (UOFF) is reported. That is, based on a four-frame rectangular model and the associated six UOFF field quantities, a set of equations is derived from which both position and velocity can be determined. It does not require feature extraction and correspondence establishment, which are known to be difficult, and only partial solutions suitable for simplistic situations have been developed. Furthermore, it is capable of detecting multiple moving objects even when partial occlusion occurs, and is potentially suitable for nonrigid motion analysis. Unlike the current existing techniques for motion analysis from stereo imagery, the recovered motion by using this new approach is for a whole continuous field instead of only for some features. It is a purely optical flow approach. Two experiments are presented to demonstrate the feasibility of the approach.     

Large-scale monitoring of coppice forest clearcuts by multitemporal very high resolution satellite imagery. A case study from central Italy

Reliable assessment of forest resource stock, productivity and harvesting is a commonly agreed objective of environmental monitoring programs. Distinctively, the assessment of wood harvesting has become even more relevant to evaluate the sustainability of forest management and to quantify forest carbon budget. This paper presents the development and testing of procedures for assessing forest harvesting in coppice forests by very high resolution (VHR) satellite imagery. The study area is located in central Italy over approximately 34,000 km². A set of SPOT5 HRG multispectral images was acquired for the study years (2002-2007). Official administrative statistics of coppice clearcuts were also acquired. More than 9500 clearcuts were mapped and dated by on-screen interpretation of the SPOT5 images. In a subset of the study area various methods for semi-automatic clearcut mapping were tested by pixel- and object-oriented approaches. The following results are presented: (i) clearcut map developed by visual interpretation of the SPOT5 images resulted in high thematic (overall accuracy of 0.99) and geometric (root mean square error of clearcut boundary delineation of 5.3 m) reliability; (ii) object-oriented approach achieved significantly better accuracy than pixel-based methods for semi-automatic classification of the coppice clearcuts; (iii) comparison between mapped clearcut area and official forest harvesting statistics proved a significant underestimation by the latter (65% of the total mapped clearcut area). A sample-based procedure exploiting VHR satellite imagery is finally proposed to correct the official statistics of coppice clearcuts.     

Inter-comparison study of water level estimates derived from hydrodynamic-hydrologic model and satellite altimetry for a complex deltaic environment

Riverine deltas are hydrologically one of the most active terrestrial bodies supporting an intricate network of rivers, a highly unsteady flow regime, high agricultural productivity and large population centers. Understanding the complex hydrology of riverine deltas is challenging due to the paucity of conventional ground-based measurements on river water levels and flows that result in large spatial and temporal sampling gaps. One way to bridge this sampling issue is to employ hydrodynamic models in combination with remotely-sensed water level elevation data from satellite altimetry in a data assimilation framework. However, a good understanding of the performance of models and altimetry is required beforehand. Using Bangladesh as an example of a complex delta, an inter-comparison study was therefore performed for water level estimates derived from the two methods: 1) satellite altimetry and 2) hydrodynamic-hydrologic modeling framework. The Envisat mission was selected for satellite altimetry-based water level data. For the modeling framework, a calibrated 1-D hydrodynamic model, HEC-RAS, was set up for the major rivers of Bangladesh using in-situ river bathymetry, gaged stream flow and water level data. Envisat water level estimates were generally found to be exceeded by the model-based values by 0.20 m and 1.90 m for Monsoon and dry seasons, respectively. In general, the average RMSE between Envisat and modeled estimates is more than 2.0 m. The closest agreement with altimetry was observed during the high flow Monsoon season over the Brahmaputra river. Envisat estimates are found to disagree most with model-based estimates for small to medium-sized river basins that are mountainous and flashy. This inter-comparison study provides preliminary guidance on the relative weights to assign for each type of estimate when designing a data assimilation scheme for optimal water level prediction in ungaged basins.