Comparison of estimates using record statistics from Weibull model: Bayesian and non-Bayesian approaches

This paper develops a Bayesian analysis in the context of record statistics values from the two-parameter Weibull distribution. The ML and the Bayes estimates based on record values are derived for the two unknown parameters and some survival time parameters e.g. reliability and hazard functions. The Bayes estimates are obtained based on a conjugate prior for the scale parameter and a discrete prior for the shape parameter of this model. This is done with respect to both symmetric loss function (squared error loss), and asymmetric loss function (linear-exponential (LINEX)) loss function. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study. A practical example consisting of real record values using the data from an accelerated test on insulating fluid reported by Nelson was used for illustration and comparison. Finally, Bayesian predictive density function, which is necessary to obtain bounds for predictive interval of future record is derived and discussed using a numerical example. The results may be of interest in a situation where only record values are stored.     

Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: Influence of spatial pattern and vegetation type

An algorithm for burned area mapping in Africa based on classification trees was developed using SPOT-VEGETATION (VGT) imagery. The derived 1 km spatial resolution burned area maps were compared with 30 m spatial resolution maps obtained with 13 Landsat ETM+ scenes, through linear regression analysis. The procedure quantifies the bias in burned area estimation present in the low spatial resolution burned area map. Good correspondence was observed for seven sites, with values of the coefficient of determination (R²) ranging from 0.787 to 0.983. Poorer agreement was observed in four sites (R² values between 0.257 and 0.417), and intermediate values of R² (0.670 and 0.613) were obtained for two sites. The observed variation in the level of agreement between the Landsat and VGT estimates of area burned results from differences in the spatial pattern and size distribution of burns in the different fire regimes encompassed by our analysis. Small and fragmented burned areas result in large underestimation at 1 km spatial resolution. When large and compact burned areas dominate the landscape, VGT estimates of burned area are accurate, although in certain situations there is some overestimation. Accuracy of VGT burned area estimates also depends on vegetation type. Results showed that in forest ecosystems VGT maps underestimate substantially the amount of burned area. The most accurate estimates were obtained for woodlands and grasslands. An overall linear regression fitted with the data from the 13 comparison sites revealed that there is a strong relationship between VGT and Landsat estimates of burned area, with a value of R² of 0.754 and a slope of 0.803. Our findings indicate that burned area mapping based on 1 km spatial resolution VGT data provides adequate regional information.     

Assessing the accuracy of satellite derived global and national urban maps in Kenya

Ninety percent of projected global urbanization will be concentrated in low income countries. This will have considerable environmental, economic and public health implications for those populations. Objective and efficient methods of delineating urban extent are a cross-sectoral need complicated by a diversity of urban definition rubrics world-wide. Large-area maps of urban extents are becoming increasingly available in the public domain, as are a wide-range of medium spatial resolution satellite imagery. Here we describe the extension of a methodology based on Landsat ETM and Radarsat imagery to the production of a human settlement map of Kenya. This map was then compared with five satellite imagery-derived, global maps of urban extent at Kenya national-level, against an expert opinion coverage for accuracy assessment. The results showed the map produced using medium spatial resolution satellite imagery was of comparable accuracy to the expert opinion coverage. The five global urban maps exhibited a range of inaccuracies, emphasising that care should be taken with use of these maps at national and sub-national scale.     

Comparison of multitemporal compositing methods for burnt area detection in Southeast Asian conditions

This study investigated the usability of different multitemporal compositing methods for burnt area detection purposes in the humid tropical conditions of insular Southeast Asia, characterised by persisting cloud cover, varying fire‐induced spectral changes and large amount of small burn scars. Six monthly composites of the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance images (MOD09) were built using six different algorithms. The performance and usability of the compositing algorithms were evaluated using three criteria: separability between burnt and unburnt areas, homogeneity and average sensor zenith angle. Maximum surface temperature method (band 31, 11.0 µm) produced the most homogeneous composites with preference to close‐to‐nadir observations. However, these composites showed unexpectedly low separability between burnt and unburnt areas, mainly due to low spatial resolution of band 31 (1000 m). Overall, taking into account the performance of the compositing methods and the large amount of small burnt areas in insular Southeast Asia, a minimum NIR (band 2, 0.86 µm) method, combined with pre‐compositing cloud and cloud shadow removal, was seen as the most suitable compositing method for burnt area detection in this region. Its strengths were 250 m spatial resolution in pixel selection and high burnt/unburnt separability combined with reasonably good performance on homogeneity and average sensor zenith angle.     

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.     

Comparison of land surface temperatures derived from satellite observations with ground truth during FIFE

Surface temperatures of the FIFE (First ISLSCP Field Experiment) experimental area derived from thermal infrared radiances recorded from different satellite platforms at different scales were compared with reference observations by means of infrared thermometers at ground stations distributed over the area. FIFE was conducted during late spring, summer and fall over an area of 15 km by 15 km in a hilly tall-grass prairie region in northeastern Kansas. The data available for this purpose were produced by AVHRR and TOVS instruments aboard NOAA-9 and NOAA-10, the TM instrument aboard Landsat-5 and VISSR instrument aboard GOES-7. The scales covered by these instruments span a wide range, namely between hundreds of metres (Landsat TM) and hundreds of kilometres (TOVS). The data are analysed both with and without the application of an atmospheric correction.     

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We spatially aggregated 30 m datasets to coarser spatial resolutions (90, 150, 210, 270, 510 and 990 m) and produced estimates of forest proportion for each spatial resolution using both model‐ and design‐based approaches. Average‐based aggregation had no effect on per‐image estimates of forest proportion; image variability decreased with increasing spatial resolution and local variability peaked between 210 and 270 m. Majority‐based aggregation resulted in overestimation of forest land in a heavily forested landscape and underestimation of forest land in a sparsely forested landscape, with both trends following a natural log distribution. Of the spatial resolutions tested, 30 m was superior for obtaining estimates using model‐based approaches. However, standard errors of design‐based inventory estimates of forest proportion were smallest when accompanying stratification maps which were aggregated to between 90 and 150 m spatial resolutions and strata thresholds were optimized by study area. These results suggest that spatially aggregating existing 30 m land cover datasets can provide NFIs with gains in precision of their estimates of forest land area, while reducing image storage size and processing times; land cover datasets derived from coarser spatial resolution sensors may provide similar benefits.     

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.     

Regional evaporation estimates from flux tower and MODIS satellite data

Two models were evaluated for their ability to estimate land surface evaporation at 16-day intervals using MODIS remote sensing data and surface meteorology as inputs. The first was the aerodynamic resistance-surface energy balance model, and the second was the Penman-Monteith (P-M) equation, where the required surface conductance is estimated from remotely-sensed leaf area index. The models were tested using 3 years of evaporation and meteorological measurements from two contrasting Australian ecosystems, a cool temperate, evergreen Eucalyptus forest and a wet/dry, tropical savanna. The aerodynamic resistance-surface energy balance approach failed because small errors in the radiative surface temperature translate into large errors in sensible heat, and hence into estimates of evaporation. The P-M model adequately estimated the magnitude and seasonal variation in evaporation in both ecosystems (RMSE = 27 W m^− 2, R² = 0.74), demonstrating the validity of the proposed surface conductance algorithm. This, and the ability to constrain evaporation estimates via the energy balance, demonstrates the superiority of the P-M equation over the surface temperature-based model. There was no degradation in the performance of the P-M model when gridded meteorological data at coarser spatial (0.05°) and temporal (daily) resolution were substituted for locally-measured inputs.The P-M approach was used to generate a monthly evaporation climatology for Australia from 2001 to 2004 to demonstrate the potential of this approach for monitoring land surface evaporation and constructing monthly water budgets from 1-km to continental spatial scales.     

Fraction images derived from Terra Modis data for mapping burnt areas in Brazilian Amazonia

The objective of this paper is to present a method for mapping burnt areas in Brazilian Amazonia using Terra MODIS data. The proposed approach is based on image segmentation of the shade fraction images derived from MODIS, using a non‐supervised classification algorithm followed by an image editing procedure for minimizing misclassifications. Acre State, the focus of this study, is located in the western region of Brazilian Amazonia and undergoing tropical deforestation. The extended dry season in 2005 affected this region creating conditions for extensive forest fires in addition to fires associated with deforestation and land management. The high temporal resolution of MODIS provides information for studying the resulting burnt areas. Landsat 5 TM images and field observations were also used as ground data for supporting and validating the MODIS results. Multitemporal analysis with MODIS showed that about 6500 km² of land surface were burnt in Acre State. Of this, 3700 km² corresponded to the previously deforested areas and 2800 km² corresponded to areas of standing forests. This type of information and its timely availability are critical for regional and global environmental studies. The results showed that daily MODIS sensor data are useful sources of information for mapping burnt areas, and the proposed method can be used in an operational project in Brazilian Amazonia.     

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing ground plots whose coordinates are obtained from Global Positioning System (GPS) receivers that are calibrated to the same geographic coordinate system, and then matching ground plots to image pixels containing the centers of the ground plots. Errors in rectification and GPS coordinates cause observations of ground attributes to be associated with spectral values of incorrect pixels which, in turn, introduces classification errors into the resulting maps. The most important finding of the study is that for common magnitudes of rectification and GPS errors, as many as half the ground plots may be assigned to incorrect pixels. The effects on areal estimates obtained by aggregating class predictions for individual pixels are deviation of the estimates from their true values, erroneous confidence intervals, and incorrect inferences. Results are reported in detail for both probability-based (design-based) and model-based approaches to inference for proportion forest area using maps constructed from Landsat imagery, forest inventory plot observations and a logistic regression model.     

Improving delay estimates derived from least-square algorithms and Padé approximations

It is shown that an on-line estimate of the unknown delay using the Padé approximation can be improved substantially. Based on an initial on-line estimate, a sequence of the estimates of delay is then constructed, which converges to the true delay.     

Evaluation of RADARSAT-1 data for identification of burnt areas in Southern Europe

This study presents the combined analysis of RADARSAT products of different spatial resolutions acquired under different incidence angles for mapping burnt scars on forested areas of Central Portugal. Prior to the SAR data analysis, a number of pre-processing procedures were carried out. Noise was eliminated by adaptive texture preserving filtering. A specific algorithm for the geocoding of SAR images, based on a range-Doppler approach, enabled precise geocoding of the SAR data by means of a single very accurate ground control point. A novel incidence-angle-normalization for SAR imagery was applied to analyze the backscatter coefficient to a given incidence angles. Further, a backscatter coefficient analysis was performed according to the slope on forested areas and fire disturbed areas. A qualitative and quantitative investigation of the backscattering as related to the slope angle and time changes was performed. As a result of this analysis, the scenes that allowed maximizing the discrimination of burnt areas were selected as the input for the neural network classification. The investigation on the effect of the SAR incidence angle in burnt area discrimination determined that low incidence angles are required for discriminating burnt areas in hilly regions. It was also demonstrated that topography influences the level of discrimination of burnt areas since areas affected by forest fires on face-slopes presents higher backscatter coefficient than those back-slopes. Therefore, SAR data can play a significant role for burnt area mapping in Europe in those areas where optical data cannot be used due to persistent cloud cover.     

Surface motion of mountain glaciers derived from satellite optical imagery

A complete and detailed map of the ice-velocity field on mountain glaciers is obtained by cross-correlating SPOT5 optical images. This approach offers an alternative to SAR interferometry, because no present or planned RADAR satellite mission provides data with a temporal separation short enough to derive the displacements of glaciers. The methodology presented in this study does not require ground control points (GCPs). The key step is a precise relative orientation of the two images obtained by adjusting the stereo model of one “slave”' image assuming that the other “master” image is well georeferenced. It is performed with numerous precisely-located homologous points extracted automatically. The strong ablation occurring during summer time on the glaciers requires a correction to obtain unbiased displacements. The accuracy of our measurement is assessed based on a comparison with nearly simultaneous differential GPS surveys performed on two glaciers of the Mont Blanc area (Alps). If the images have similar incidence angles and correlate well, the accuracy is on the order of 0.5 m, or 1/5 of the pixel size. Similar results are also obtained without GCPs. An acceleration event, observed in early August for the Mer de Glace glacier, is interpreted in term of an increase in basal sliding. Our methodology, applied to SPOT5 images, can potentially be used to derive the displacements of the Earth's surface caused by landslides, earthquakes, and volcanoes.     

Uncertainty estimates for the FAPAR operational products derived from MERIS — Impact of top-of-atmosphere radiance uncertainties and validation with field data

This paper discusses the accuracy of the operational Medium Resolution Imaging Spectrometer (MERIS) Level 2 land product which corresponds to the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). The FAPAR value is estimated from daily MERIS spectral measurements acquired at the top-of-atmosphere, using a physically based approach. The products are operationally available at the reduced spatial resolution, i.e. 1.2 km, and can be computed at the full spatial resolution, i.e. at 300 m, from the top-of-atmosphere MERIS data by using the same algorithm. The quality assessment of the MERIS FAPAR products capitalizes on the availability of five years of data acquired globally. The actual validation exercise is performed in two steps including, first, an analysis of the accuracy of the FAPAR algorithm itself with respect to the spectral measurements uncertainties and, second, with a direct comparison of the FAPAR time series against ground-based estimations as well as similar FAPAR products derived from other optical sensor data. The results indicate that the impact of top-of-atmosphere radiance uncertainties on the operational MERIS FAPAR products accuracy is expected to be at about 5-10% and the agreement with the ground-based estimates over different canopy types is achieved within ± 0.1.     

Ozone dynamics over Greece as derived from satellite and! in situ measurements

A comprehensive analysis of the records of surface ozone available for Athens, Greece ( 38° N, 24° E) for the periods 1901–1940 and 1987–1990 is presented. Both records are analysed to explore the intraseasonal fluctuations and the harmonic components of surface ozone and also compared to other historical surface ozone records. The variation in surface ozone concentration during rainfall is also investigated, using the hourly measurements of the surface ozone concentration obtained by a network of four stations within the Greater Athens area. The results indicate that, during rainfall events which are associated with the passing of a cold front, an important decrease of the surface ozone concentration is observed. Daily measurements of surface ozone and NO_x, from five stations in the Greater Athens Basin overthe period 1986–1990 are also used in order to examine the main features of basin-wide 0₃-HC-NO_x relations. A simple regression model between the surface ozone concentration and the temperature at the 850 hPa level, which was first tested in Los Angeles, gave satisfactory results in reproducing the mean monthly ozone variation in Athens, when coefficients extracted from local data were used in the regression equation. A series of vertical ozone soundings over Athens has been also performed in order to explore the tropospheric ozone variations and to examine further the transport that occurs at the 700hPa level with advection from the north-western sector. The relevant results are discussed. The existing uncertainties concerning the stratosphere-troposphere exchange of ozone which mainly occurs during midlatitude tropopause folding as well as during cut-off low events are also discussed. The examination of the role of the atmospheric circulation in the lower stratosphere in relation to the laminated structure of ozone is also attempted. The data collected during the balloon ascents have been compared with those during the balloon descents. Both profiles are compared with the total ozone measurements derived from the TOMS on the Nimbus-7 satellite and the Dobson spectrophotometer. The data collected for the vertical distribution of ozone and temperature have been compared with the satellite-derived reference models which provide the monthly latitudinal variations of vertical structure of both ozone and temperature. We have also used total ozone measurements obtained with a Dobson spectrophotometer ( No. 118) which has been instituted in Athens from 1989 in order to examine the consistency of data from TOMS with the corresponding Dobson data on a daily basis. Furthermore monthly mean total ozone data were first estimated for the entire period and were then Fourier analysed to obtain the amplitude, phase and percentage contribution to the total variance of the first, second and third harmonics.     

Surface temperature and albedo relationships in Senegal derived from NOAA-7 satellite data

Ground temperature and albedo values were studied in a semiarid, sub-Saharan region of Africa, Senegal, for various days in the period of September 1981 to October 1982. The albedo and ground temperature were found to be positively correlated; i.e., regions of high albedo were regions of high ground temperature, and regions of low albedo were regions of low ground temperature. Highest values of ground temperature and albedo were found in a region characterized by sparse vegetation and in the dry season. Lowest values of ground temperature and albedo were found in regions characterized by dense vegetation and in the wet season. These results suggest that regions of high albedo in the sub-Saharan region of west Africa are regions of high ground temperature. Mechanisms for increasing the ground temperature under high albedo conditions are discussed. The increased ground temperature will increase the long wave radiation emitted to the atmosphere and the sensible heat flux at the surface. Therefore, there can be a net heat gain in the local atmosphere which will result in a general rising motion. These results are in contrast to those proposed by Charney (1975), who suggested that an increased albedo in semidesert regions will cause a net radiation loss, contributing to net cooling, sinking, and drying of the air aloft.     

Surface velocity estimates of the North Indian Ocean from satellite gravity and altimeter missions

The circulation in the North Indian Ocean (NIO) is one of the most complex systems compared with other regions of global oceans, mostly due to its interactions with the monsoon winds. In recent years, our ability to measure the ocean’s mean dynamic topography (MDT) from space has improved immensely with the availability of satellite gravity measurements from Gravity Recovery and Climate Experiment (GRACE) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) missions. The present study uses data from GOCE and GRACE satellite gravity missions together with altimeter data in retrieving the geoid, satellite-only MDT, and surface velocities in the NIO. The study estimates geoid heights of the NIO from all five releases of the direct approach and the time-wise GOCE gravity data. The formal error associated with geoid heights at different resolutions is found to be the lowest for the latest release of direct approach GOCE data. In addition, a new satellite-only MDT is estimated from the direct approach GOCE geoid and the CNES_CLS11 mean sea surface. This MDT corrected to a 20-year time reference is used together with the newly reprocessed sea level anomaly data to estimate absolute dynamic topography and surface geostrophic velocities in the NIO. The total surface velocities computed from the Ekman and geostrophic velocity fields reproduce all major surface currents in the NIO, along with their seasonality. Furthermore, total surface velocity estimates computed here are validated using surface drifters and are found to be highly comparable (difference within ± 10 cm s^–1) with more than 170,000 individual surface drifter observations. Finally, the total velocities estimated here are used to examine the variability of the East India Coastal Current.     

Mesoscale surface current fields in the Baltic Sea derived from multi-sensor satellite data

We demonstrate the use of multi-sensor satellite images for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper by enhancing and combining image-processing techniques. The sequential satellite images were acquired by the Thematic Mapper (TM), the ERS-2 Synthetic Aperture Radar (SAR), the Wide-Field Scanner (WiFS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) during extensive cyanobacterial blooms in July 1997 and in July/August 1999. We also used a pair of Advanced SAR (ASAR) images from May 2005 showing imprints of singular oil spills in the Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface were taken as tracers for the local motion of the sea surface. Data from sensors working at different electromagnetic bands (e.g. TM and SAR) were used to apply high-speed feature-matching (cross-correlation) techniques for motion detection. The sufficiently short time lags between the multiple image acquisitions (from less than 1 h to approximately 1 day) and the high spatial coverage allowed for the calculation of optical flow (i.e. surface motion) fields, which include small-scale turbulent structures that are not resolved by operational numerical models. Our computed surface currents range from 4 to 35 cm s^?1 and are generally larger than those provided by the numerical models for the same dates and areas. We attribute this difference to local wind forcing, causing higher drift velocities at the very sea surface, which is seen from space, but which is not resolved by the numerical models.     

Accuracy assessment of fraction of vegetation cover and leaf area index estimates from pragmatic methods in a cropland area

The fraction of vegetation cover (FVC) and the leaf area index (LAI) are important parameters for many agronomic, ecological and meteorological applications. Several in‐situ and remote sensing techniques for estimating FVC and LAI have been developed in recent years. In this paper, the uncertainty of in‐situ FVC and LAI measurements was evaluated by comparing estimates from LAI‐2000 and digital hemispherical photography (DHP). The accuracy achieved with a spectral mixture analysis algorithm and two vegetation indices‐based methods was assessed using atmospherically corrected Landsat Thematic Mapper (TM) data over the Barrax cropland area where the European Space Agency (ESA) SENtinel‐2 and FLuorescence EXperiment (SEN2FLEX) field campaign was carried out in July 2005. The results indicate that LAI‐2000 and DHP performances are comparable, with uncertainties of 5% for FVC and 15% for effective LAI. The selected remote sensing methods are shown to be consistent, with a notable overall accuracy (root mean square error, RMSE) of 0.07 (10% in relative terms) for FVC and 0.8 (30%) for LAI. Similar bounds were found on upscaling in‐situ measurements with empirical transfer functions (TFs). These results suggest that the pragmatic methods considered applied at high resolution with minimum calibration data could be useful for mapping FVC and LAI in the study area, reducing in‐situ labour‐intensive characterization necessities for validation studies.