Medium-resolution Data Research Articles

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels.

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing.

Data mining of metal ion environments present in protein structures

Analysis of metal–protein interaction distances, coordination numbers, B-factors (displacement parameters), and occupancies of metal-binding sites in protein structures determined by X-ray crystallography and deposited in the PDB shows many unusual values and unexpected correlations. By measuring the frequency of each amino acid in metal ion-binding sites, the positive or negative preferences of each residue for each type of cation were identified. Our approach may be used for fast identification of metal-binding structural motifs that cannot be identified on the basis of sequence similarity alone. The analysis compares data derived separately from high and medium-resolution structures from the PDB with those from very high-resolution small-molecule structures in the Cambridge Structural Database (CSD). For high-resolution protein structures, the distribution of metal–protein or metal–water interaction distances agrees quite well with data from CSD, but the distribution is unrealistically wide for medium (2.0–2.5 Å) resolution data. Our analysis of cation B-factors versus average B-factors of atoms in the cation environment reveals substantial numbers of structures contain either an incorrect metal ion assignment or an unusual coordination pattern. Correlation between data resolution and completeness of the metal coordination spheres is also found.

Timing of erosion and satellite data: A multi-resolution approach to soil erosion risk mapping

Erosion reduces soil productivity and causes negative downstream impacts. Erosion processes occur on areas with erodible soils and sloping terrain when high-intensity rainfall coincides with limited vegetation cover. Timing of erosion events has implications on the selection of satellite imagery, used to describe spatial patterns of protective vegetation cover. This study proposes a method for erosion risk mapping with multi-temporal and multi-resolution satellite data. The specific objectives of the study are: (1) to determine when during the year erosion risk is highest using coarse-resolution data, and (2) to assess the optimal timing of available medium-resolution images to spatially represent vegetation cover during the high erosion risk period. Analyses were performed for a 100-km2 pasture area in the Brazilian Cerrados. The first objective was studied by qualitatively comparing three-hourly TRMM rainfall estimates with MODIS NDVI time series for one full year (August 2002–August 2003). November and December were identified as the months with highest erosion risk. The second objective was examined with a time series of six available ASTER images acquired in the same year. Persistent cloud cover limited image acquisition during high erosion risk periods. For each ASTER image the NDVI was calculated and classified into five equally sized classes. Low NDVI was related to high erosion risk and vice versa. A DEM was used to set approximately flat zones to very low erosion risk. The six resulting risk maps were compared with erosion features, visually interpreted from a fine-resolution QuickBird image. Results from the October ASTER image gave highest accuracy (84%), showing that erosion risk mapping in the Brazilian Cerrados can best be performed with images acquired shortly before the first erosion events. The presented approach that uses coarse-resolution temporal data for determining erosion periods and medium-resolution data for effective erosion risk mapping is fast and straightforward. It shows good potential for successful application in other areas with high spatial and temporal variability of vegetation cover.

Poyang Hu (Jiangxi Province, P. R. of China) Area Variations between January 2004 and June 2006 Using ENVISAT Low and Medium Resolution Time Series

Poyang Hu, one of the most regularly flooded areas in China, can be considered as a key hydrological element in flood control and reduction within the middle Changjiang basin. This area was selected as a major test site of the Flood DRAGON Project, part of the MOST-ESA DRAGON Programme. Over two and half years, water extent was monitored based on sixty-four ENVISAT low and medium resolution ASAR and MERIS FR images. It's the first time that such an amount of ENVISAT data was used in monitoring inland lake water extent variations. This original integration approach involves: lake surface variation analysis, yearly submersion time estimation, and a spatial recognition of three major hydrological sub-systems. The results highlight the great potential of ENVISAT, and more largely Earth Observation Medium Resolution data, for large inland water body monitoring and management. This approach can be applied worldwide in the context of global climate change.

Signature extension through space for northern landcover classification: A comparison of radiometric correction methods

Northern landcover mapping for climate change and carbon modeling requires greater detail than what is available from coarse resolution data. Mapping landcover with medium resolution data from Landsat presents challenges due to differences in time and space between scene acquisitions required for full coverage. These differences cause landcover signatures to vary due to haze, solar geometry and phenology, among other factors. One way to circumvent this problem is to have an image interpreter classify each scene independently, however, this is not an optimal solution in the north due to a lack of spatially extensive reference data and resources required to label scenes individually. Another possible approach is to stabilize signatures in space and time so that they may be extracted from one scene and extended to others, thereby reducing the amount of reference data and user input required for mapping large areas. A radiometric normalization approach was developed that exploits the high temporal frequency with which coarse resolution data are acquired and the high spatial frequency of medium resolution data. The current paper compares this radiometric correction methodology with an established absolute calibration methodology for signature extension for landcover classification and explores factors that affect extension performance to recommend how and when signature extension can be applied. Overall, the new normalization method produced better extension and classification results than absolute calibration. Results also showed that extension performance was affected more by geographical distance than by differences in anniversary dates between acquisitions for the range of data examined. Geographical distance in the north–south direction leads to poorer extension performance than distance in the east–west direction due in part to differences in vegetation composition assigned the same class label in the latitudinal direction. While extension performance was somewhat variable and in some cases did not produce a best classification result by itself, it provided an initial best guess of landcover that can subsequently be refined by an expert image interpreter.

Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: Initial results from Tampa Bay, FL

Using Tampa Bay, FL as an example, we explored the potential for using MODIS medium-resolution bands (250- and 500-m data at 469-, 555-, and 645-nm) for estuarine monitoring. Field surveys during 21–22 October 2003 showed that Tampa Bay has Case-II waters, in that for the salinity range of 24–32 psu, (a) chlorophyll concentration (11 to 23 mg m −3), (b) colored dissolved organic matter (CDOM) absorption coefficient at 400 nm (0.9 to 2.5 m −1), and (c) total suspended sediment concentration (TSS: 2 to 11 mg L −1) often do not co-vary. CDOM is the only constituent that showed a linear, inverse relationship with surface salinity, although the slope of the relationship changed with location within the bay. The MODIS medium-resolution bands, although designed for land use, are 4–5 times more sensitive than Landsat-7/ETM+ data and are comparable to or higher than those of CZCS. Several approaches were used to derive synoptic maps of water constituents from concurrent MODIS medium-resolution data. We found that application of various atmospheric-correction algorithms yielded no significant differences, due primarily to uncertainties in the sensor radiometric calibration and other sensor artifacts. However, where each scene could be groundtruthed, simple regressions between in situ observations of constituents and at-sensor radiances provided reasonable synoptic maps. We address the need for improvements of sensor calibration/characterization, atmospheric correction, and bio-optical algorithms to make operational and quantitative use of these medium-resolution bands.

Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters

High concentrations of suspended particulate matter in coastal waters directly affect or govern numerous water column and benthic processes. The concentration of suspended sediments derived from bottom sediment resuspension or discharge of sediment-laden rivers is highly variable over a wide range of time and space scales. Although there has been considerable effort to use remotely sensed images to provide synoptic maps of suspended particulate matter, there are limited routine applications of this technology due in part to the low spatial resolution, long revisit period, or cost of most remotely sensed data. In contrast, near daily coverage of medium-resolution data is available from the Moderate-resolution Imaging Spectroradiometer (MODIS) Terra instrument without charge from several data distribution gateways. Equally important, several display and processing programs are available that operate on low cost computers. The utility of MODIS 250 m data for analyzing complex coastal waters was examined in the Northern Gulf of Mexico. Using simple processing procedures, MODIS images were used to map the concentration of Total Suspended Matter (TSM). A robust linear relationship was established between band 1 (620–670 nm) MODIS Terra 250 m data and in situ measurements of TSM ( r 2=0.89; n=52; MSE=4.74) acquired during six field campaigns. This study demonstrates that the moderately high resolution of MODIS 250 m data and the operating characteristics of the instrument provide data useful for examining the transport and fate of materials in coastal environments, particularly smaller bodies of water such as bays and estuaries.

Quantum chemistry can locally improve protein crystal structures.

We have re-refined the X-ray structure of the heme site in cytochrome c553, supplementing the crystallographic data with quantum chemical geometry optimizations, instead of the molecular mechanics force field used in standard crystallographic refinement. By comparing the resulting structure, obtained using medium-resolution data (170 pm), with an atomic-resolution structure (95 pm) of the same protein, we show that the inclusion of quantum chemical information into the refinement procedure improves the structure significantly. Thus, errors in the Fe-ligand distances are reduced from 3 to 32 pm in the low-resolution structure to 0-5 pm in the re-refined structure, one side-chain atom changes its conformation (a movement by 214 pm toward its position in the high-resolution structure), and the R factors are improved by up to 0.018. Thus, quantum refinement may be a powerful method to obtain an accurate structure for interesting parts of a protein.

FEMME database: topologic and geometric information of macromolecules

FEMME (Feature Extraction in a Multi-resolution Macromolecular Environment: http://www.biocomp.cnb.uam.es/FEMME/) database version 1.0 is a new bioinformatics data resource that collects topologic and geometric information obtained from macromolecular structures solved by three-dimensional electron microscopy (3D-EM). Although the FEMME database is focused on medium resolution data, the methodology employed (based on the so-called α-shape theory) is applicable to atomic resolution data as well. The α-shape representation allows the automatic extraction of structural features from 3D-EM volumes and their subsequent characterisation. FEMME is being populated with 3D-EM data stored in the electron microscopy database EMD-DB ( http://www.ebi.ac.uk/msd/). However, and since the number of entries in EMD-DB is still relatively small, FEMME is also being populated in this initial phase with structural data from PDB and PQS databases ( http://www.rcsb.org/pdb/ and pqs.ebi.ac.uk/, respectively) whose resolution has been lowered accordingly. Each FEMME entry contains macromolecular geometry and topology information with a detailed description of its structural features. Moreover, FEMME data have facilitated the study and development of a method to retrieve macromolecular structures by their structural content based on the combined use of spin images and neural networks with encouraging results. Therefore, the FEMME database constitutes a powerful tool that provides a uniform and automatic way of analysing volumes coming from 3D-EM that will hopefully help the scientific community to perform wide structural comparisons.

A contextual approach to the mapping of burned areas in tropical Australian savannas using medium-resolution satellite data

Our objective was to develop and test a spectral‐spatial method to detect burned areas in savanna landscapes. The hypothesis tested was that the inclusion of spatial information (context) would better detect burning than do spectral-only tests. The spectral‐spatial measure used was the standard deviation (SD) of a near-infrared (NIR) channel for a 5 × 5 pixels window because this measure exhibits a spike on burning. This measure was compared with spectral-only tests in the Australian tropical savannas during the 2000 dry season (April‐November) using Système pour l'Observation de la Terre (SPOT) VEGETATION (VGT) data. Using a population of 23 burned areas, the superiority of the SD NIR signal was demonstrated and, using videography, the influences of surface factors on the SD NIR signal were examined. A large area (29 000 km2) comparison was made of the several burning detection tests, all referred to two manually interpreted datasets. Using the criterion of user accuracy, two spatial‐spectral tests outperformed two spectral-only tests. However, the largest common class of error was omission, indicating a failure of all tests to completely capture burned areas. This deficiency is not crippling, for it can be largely overcome by spatial filtering.

Modeling Shape and Topology of Low-Resolution Density Maps of Biological Macromolecules

In the present work we develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution, aiming at storing and querying them in a database framework. We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data. Connectivity among points is obtained with the use of the alpha shapes theory. This novel data representation has a number of interesting characteristics, such as 1) it allows us to automatically segment and quantify a number of important structural features from low-resolution maps, such as cavities and channels, opening the possibility of querying large collections of maps on the basis of these quantitative structural features; 2) it provides a compact representation in terms of size; 3) it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data; and 4) a general model of the geometry and topology of the macromolecule (as opposite to a spatially unrelated bunch of voxels) is easily obtained by the use of the alpha shapes theory.

ISO LWS Observations of Mars—Detection of Rotational Modulation in the Far Infrared

A series of far infrared (FIR) spectra of Mars between 43 and 196 μm was taken with the Long Wavelength Spectrometer (LWS) on board the European Space Agency's Infrared Space Observatory (ISO). Analysis of these medium-resolution data reveals a rotational modulation of the disk-averaged FIR brightness temperature. The observed variability of ±1.5% in the LWS wavelength range compares favorably with the predictions of a thermophysical model of the martian surface. A surface emissivity of ∼0.90 gives good agreement between the measured and the modeled brightness temperatures and leads to an improved estimate of the LWS photometric calibration uncertainty.

The effects of image scale on delineation of eroded lands using remote sensing data

Abstract With the development in sensor technology, in recent years, spaceborne multi-spectral data with improved spectral, radiometric spatial and temporal resolution are now available to the user community. Higher spatial resolution provides more details about the Earth's surface features, compared to medium or coarse spatial resolution data by virtue of smaller instantaneous field-of-view (IFOV) at a given wavelength. This study aims at bringing out the additional information on soil erosion that may accrue from the interpretation of large scale i.e., 1:50000 Landsat Thematic Mapper (TM) analogue data over what could be derived from 1:250 000 scale. Owing to improved discernibility of eroded lands at larger scale the pockets of eroded lands as small as 2.25 ha could be mapped at 1:50 000 scale as compared to 56.25 ha that is possible from 1:250 000 scale data. Besides, substantial refinement in the delineated boundaries of these lands have also been observed. The approach and results are discussed in d...

Broad Band X-Ray Telescope observations of NGC 4151 - Iron line diagnostics

The Fe K-alpha emission line is a potentially powerful diagnostic tool in the X-ray spectra of AGNs, however, this feature has previously been observed with relatively poor spectral resolution. The Broad Band X-Ray Telescope has provided us with the first high-quality, medium-resolution X-ray spectral data. We are able to constrain the width of the 6.4 keV Fe K-alpha line in NGC 4151 to be less than 160 eV FWHM (7,500 km/s), in contrast with former measurements of the line width. Also, we have limited information on the shape of the line profile. In addition to the strong narrow Fe K-alpha feature, we detect weaker broad residuals between 5-8 keV.

Search for TeV gamma-ray emission from Hercules X-1

Six years of observations of Hercules X-1 with the Whipple Observatory gamma-ray telescope have been subjected to a Fourier analysis to search for emission at the 0.8079 Hz neutron star frequency. Evidence for a signal is found at the 99.5 percent confidence level for data taken with the medium-resolution imaging camera with some indications of emission at frequencies blueshifted from the fundamental frequency. However, analysis of the high-resolution camera data base have failed to substantiate this effect. Selection of events on the basis of gamma-ray-like image parameters did not enhance the signal from the medium-resolution data nor produce any indication of a signal from the high-resolution data. The overall conclusion is that no statistically significant evidence for TeV gamma-ray emission was found in the Whipple Observatory data base when the 6 years of data are taken as a whole.

Refinement of tRNAfMet: how to combine stereochemical information with low- and medium-resolution data

Refinement of tRNA_f^Met: how to combine stereochemical information with low- and medium-resolution data

Investigation of clouds above snow surfaces utilizing radiation measurements obtained from the nimbus II satellite

Bidirectional reflectance of solar radiation as a function of scattering angles from snow and cloud surfaces is found to differ markedly. The variation of bidirectional reflectance with scattering angle depends on cloud thickness. Infrared temperature data obtained from the same region are used in conjunction with these observations to provide information on characteristics of clouds located above snow surfaces. Nimbus II Medium Resolution data from consecutive orbits over Greenland on 19 June 1966 are used to illustrate how such data provide information on clouds above snow surfaces.

Mitochondrial DNA from yeast “petite” mutants: Specific changes of buoyant density corresponding to different cytoplasmic mutations

Spatial resolution of environmental data may influence the results of habitat selection models. As high-resolution data are usually expensive, an assessment of their contribution to the reliability of habitat models is of interest for both researchers and managers. We evaluated how vegetation cover datasets of different spatial resolutions influence the inferences and predictive power of multi-scale habitat selection models for the endangered brown bear populations in the Cantabrian Range (NW Spain). We quantified the relative performance of three types of datasets: (i) coarse resolution data from Corine Land Cover (minimum mapping unit of 25 ha), (ii) medium resolution data from the Forest Map of Spain (minimum mapping unit of 2.25 ha and information on forest canopy cover and tree species present in each polygon), and (iii) high-resolution Lidar data (about 0.5 points/m2) providing a much finer information on forest canopy cover and height. Despite all the models performed well (AUC > 0.80), the predictive ability of multi-scale models significantly increased with spatial resolution, particularly when other predictors of habitat suitability (e.g. human pressure) were not used to indirectly filter out areas with a more degraded vegetation cover. The addition of fine grain information on forest structure (LiDAR) led to a better understanding of landscape use and a more accurate spatial representation of habitat suitability, even for a species with large spatial requirements as the brown bear, which will result in the development of more effective measures to assist endangered species conservation.

Meteorological satellite data: archiving and availability

The U. S. Weather Bureau makes copies of meteorological satellite data available to all as soon as feasible after acquisition. Archiving picture data has introduced new problems in controlling resolution and gray scale, which are quality factors not encountered in archiving digital weather data. Copies of satellite pictures are obtainable from the Weather Bureau's National Weather Records Center in 35 mm roll film format. Pictures from recent and future near-polar orbiting satellites are also obtainable as assemblages on 8½ × 11 inch sheet film. Catalogues of picture data from each satellite describe data available and assist in determining geographical location of pictures. TIROS medium-resolution radiation data are archived on digital magnetic tape, and are obtainable as tape copies, or in various printed formats. The Weather Bureau's TOS operational satellite system will begin in early 1966. Data processing procedures will be designed to satisfy operational needs, but all data will be archived in formats developed for TIROS or Nimbus, and with increased emphasis on digitized picture data.