Multi-year simulation of Mediterranean forest transpiration by the integration of NOAA-AVHRR and ancillary data

The estimation of transpiration fluxes through wide vegetated land surfaces is of great importance for the proper planning and management of environmental resources, particularly in areas where water is a main limiting factor during at least part of the growing cycle. While remotely sensed techniques cannot directly measure these fluxes, they can provide useful information on vegetation variables such as Leaf Area Index (LAI), which are functionally related to the mentioned processes. The aims of the present work were: (a) to illustrate the use of multi-temporal LAI profiles derived from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI) data as input for a biogeochemical model (Forest-BGC) which simulates the main processes of forest vegetation (transpiration and photosynthesis); and (b) to analyse the sensitivity of the calibrated model to its main driving variables (meteorological data and NDVI-derived LAI profiles) in order to assess their relative importance for operational transpiration monitoring. In particular, the model was applied to two oak stands in the Tuscany Region (central Italy), which are representative of Mediterranean forests and for which a calibration phase had already been performed. Simulations were carried out for a 15-year period (1986–2000) using as inputs daily meteorological data and NDVI-derived monthly LAI profiles. The sensitivity of the model to both input types was then assessed through other model runs with fixed values of the two variables. The results of these experiments indicated that the remotely sensed LAI estimates are the main determinant of simulated transpirations, especially during the Mediterranean arid season (summer) when water resources are the primary limiting factor for vegetation development.     

Comparison of four line-based positional assessment methods by means of synthetic data

Positional accuracy of spatial data can be assessed by means of line-based methods. In this work we develop an analysis of the following four methods: Hausdorff Distance, Mean Distance, Single Buffer Overlay and Double Buffer Overlay, using a set of 12 synthetic cases. The synthetic cases incorporate specific shape features for bias, random errors and outliers which correspond to simplified versions of real world possibilities. The use of synthetic cases helps us to understand the basic behavioral differences between the methods. Numerical results for the positional accuracy estimations are different between methods and cases due to the different concepts of distance involved and the specific configurations of each case. When the method results in a function, patterns related to different types of errors can be detected in this function. The length-inclusion level of each method is revealed as the base criterion for comparison. The Single Buffer Overlay Method offers the more general solution because it includes the others’ results.     

On the use of ancillary data by applying the concepts of the theory of evidence to remote sensing digital image classification

In this study we investigate a new approach to implement concepts developed by the ‘theory of evidence’ to remote sensing digital image classification. In the proposed approach, auxiliary variables are structured as layers in a Geographical Information System (GIS)-like format to produce layers of belief and plausibility. Thresholds are applied to the layers of belief and plausibility to detect errors of commission and omission, respectively on the thematic image. The thresholds are estimated as functions of the user's and producer's accuracy. Preliminary tests were performed over an area covered by natural forest with Araucaria, showing some promising results.     

Iterative sound synthesis by means of cross-coupled digital oscillators

Abstract

Musicians have long been interested in using iterative processes to aid the composition of musical forms (macrostructure) and to synthesize sounds (microstructure). This paper introduces a new sound synthesis method exploring the non-linear behaviour of two iterative cross-coupled digital oscillators. It begins with a brief introduction to iterative systems followed by background information on previous attempts at using them for synthesizing sounds (e.g. feedback frequency and amplitude modulations). Next, it introduces our synthesis method and briefly explains how it has been implemented in a system for real-time composition and performance. The paper concludes with a discussion on how the system has been put into practice to compose and perform a number of works.     

Dynamic simulation and visualisation of coastal erosion

A key requirement for effective coastal zone management is good knowledge and prediction of land erosion rates due to encroachment of the sea. However, in addition to demarcation of the hazard through modelling and mapping, a policy of risk mitigation necessitates significant attention should also be addressed to communicating the transient behaviour of the predictions and associated uncertainty. With climate change and sea level rise implying that historical rates of change may not be a reliable guide for the future, enhanced visualisation of the evolving coastline has the potential to improve awareness of this changing risk. This visual content is developed by linking scientific modelling with the transformation of digital elevation models, and then using GIS to integrate other spatiotemporal content. The resulting high-resolution visualisations may meet demands from decision-makers for tools to communicate scientific results more effectively, due to their realism and apparent authenticity. Nevertheless they can also produces a tension with the underlying scientific content because of the necessary extrapolation of extra detail, and the lack of established procedures to communicate the resulting uncertainty in the visualisation. Coastal managers also have concerns about releasing the visualisations to the general public. These issues are explored through analysis of future cliff erosion in Norfolk on the eastern coast of Great Britain.     

Classification of Mediterranean vegetation by TM and ancillary data for the evaluation of fire risk

Mediterranean vegetation is strongly subjected to the risk of wildfires, which can become a major cause of land degradation. The knowledge of the spatial variations of this risk is essential, therefore, for forest resource management. Relying on the fact that different vegetation types can be associated with different risk levels, a classification approach based on the use of Landsat Thematic Mapper (TM) scenes is currently proposed for the generation of maps related to fire risk. Hard and fuzzy classifications were tested for this purpose on Elba island (central Italy), taking into account the effects of the use of scenes from different periods (spring and summer) and of ancillary data. The fire risk images obtained were evaluated by comparison with the fire events that occurred on the island during the last decade. The results show that, while the acquisition period has only minor effects, classification accuracy is strongly dependent on the inclusion of ancillary data. Moreover, the fuzzy approach better exploits the information of the integrated datasets, producing maps which are temporally stable and highly indicative of the fire risk in the study area.     

Improving digital image watermarking by means of optimal channel selection

Supporting safe and resilient authentication and integrity of digital images is of critical importance in a time of enormous creation and sharing of these contents. This paper presents an improved digital image watermarking model based on a coefficient quantization technique that intelligently encodes the owner’s information for each color channel to improve imperceptibility and robustness of the hidden information. Concretely, a novel color channel selection mechanism automatically selects the optimal HL4 and LH4 wavelet coefficient blocks for embedding binary bits by adjusting block differences, calculated between LH and HL coefficients of the host image. The channel selection aims to minimize the visual difference between the original image and the embedded image. On the other hand, the strength of the watermark is controlled by a factor to achieve an acceptable tradeoff between robustness and imperceptibility. The arrangement of the watermark pixels before shuffling and the channel into which each pixel is embedded is ciphered in an associated key. This key is utterly required to recover the original watermark, which is extracted through an adaptive clustering thresholding mechanism based on the Otsu’s algorithm. Benchmark results prove the model to support imperceptible watermarking as well as high robustness against common attacks in image processing, including geometric, non-geometric transformations, and lossy JPEG compression. The proposed method enhances more than 4 dB in the watermarked image quality and significantly reduces Bit Error Rate in the comparison of state-of-the-art approaches.     

An assessment of the realism of digital human manikins used for simulation in ergonomics

In this study, the accuracy of the joint centres of the manikins generated by RAMSIS and Human Builder (HB), two digital human modelling (DHM) systems widely used in industry for virtual ergonomics simulation, was investigated. Eighteen variously sized females and males were generated from external anthropometric dimensions and six joint centres (knee, hip and four spine joints) were compared with their anatomic locations obtained from the three-dimensional reconstructed bones from a low-dose X-ray system. Both RAMSIS and HB could correctly reproduce external anthropometric dimensions, while the estimation of internal joint centres location presented an average error of 27.6 mm for HB and 38.3 mm for RAMSIS. Differences between both manikins showed that a more realistic kinematic linkage led to better accuracy in joint location. This study opens the way to further research on the relationship between the external body geometry and internal skeleton in order to improve the realism of the internal skeleton of DHMs, especially for a biomechanical analysis requiring information of joint load and muscle force estimation.

Practitioner summary: This study assessed two digital human modelling (DHM) systems widely used in industry for virtual ergonomics. Results support the need of a more realistic human modelling, especially for a biomechanical analysis and a standardisation of DHMs.     

Land degradation and erosion risk mapping by fusion of spectrally-based information and digital geomorphometric attributes

The Guadalentin basin, located in the SE of Spain, has a semiarid climate and presents typical characteristics of Mediterranean landscapes vulnerable to land degradation processes and desertification risks. In such an environment, when the vegetation cover is low, the signal received by satellites is dominated by the spectral properties of soils. Changes in these properties can be interpreted in terms of varying soil surface conditions. These optical changes underline the major modifications affecting soil surface under land degradation processes. The present research uses remote sensing techniques to characterise land degradation based on two approaches: spectral mixture analysis and a set of indices describing the spectrum shape. It also presents an integrated approach for evaluating ecosystem vulnerability to land degradation, through the combined analysis of spectrally-derived land units and geomorphometric units. Specific objectives consist of evaluating the potential of extending the indices describing the spectrum shape to the short-wave infrared region, and of identifying landscape units according to their sensitivity to land degradation. Our results demonstrate that the spatial distribution of regional patterns of land degradation can be reliably mapped by using both indices describing the spectrum shape and spectral unmixing. The latter holds great potential for operational mapping of soil conditions and erosion features from optical images. Moreover, landscape-unit analysis shows that DEM (Digital Elevation Model) variables combined with spectral information are very useful for land degradation assessment. This approach allowed us to segment the landscape into different units according to their lithology and vegetation characteristics, as well as their susceptibility to water erosion.     

Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data

An operational crop yield model was developed by introducing realtime satellite imagery into a Geographical Information System (GIS) and the Crop Specific Water Balance (CSWB) model of the Food and Agriculture Organization (FAO). Input databases were developed with three different resolutions; agro-ecological zone (AEZ) polygons, 7.6 km and 1.1 km pixels; from archived satellite data commonly used by Early Warning Systems (EWS) to simulate maize yield and production in Kenya from 1989 to 1997. Simulated production results from the GIS-based CSWB model were compared to historical maize production reports from two Government of Kenya (GoK) agencies. The coefficients of determination (r ²) between the model and GoK district reports ranged from 0.86 to 0.89. The results indicated the 7.6 km pixel-by-pixel analysis was the most favorable method due to the Rainfall Estimate (RFE) input data having the same resolution. The GIS-based CSWB model developed by this study could also be easily expanded for use in other countries, extended for other crops, and improved in the future as satellite technologies improve.     

Accuracy assessment of automatically derived digital elevation models from aster data in mountainous terrain

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite was designed to generate along‐track stereo images. The data are available at low cost, providing a feasible opportunity for generating digital elevation models (DEMs) in areas where little or no elevation data are yet available. This study evaluates the accuracy of DEMs extracted from ASTER data covering mountainous terrain. For an assessment of the achieved accuracies in the Andean study site, comparisons were made to similar topographical conditions in Switzerland, where reference data were available. All raw DEMs were filtered and interpolated by the post‐processing tools included with PCI Geomatica, the software package used. After carefully checking the DEM quality, further post‐processing was undertaken to eliminate obvious artefacts such as peaks and sinks. Accuracy was tested by comparing the DEMs in the Swiss Alps to three reference models. The achieved results of the generated DEMs are promising, considering the extreme terrain. Given accurate and well‐distributed ground control points (GCPs), it is possible to generate DEMs with a root mean square (RMS) error between 15?m and 20?m in hilly terrain and about 30?m in mountainous terrain. The DEMs are very accurate in nearly flat regions and on smooth slopes with southern expositions: errors are generally within ±10?m in those cases. Larger errors do appear in forested, snow covered or shady areas and at steep cliffs and deep valleys with extreme errors of a few hundred metres. The evaluation showed that the quality of the DEMs is sufficient for enabling atmospheric, topographic and geometric correction to various satellite datasets and for deriving additional products.     

Ergonomic assessment of handle design by means of electromyography and subjective rating

Stress and strain during manual tool handling not only depend on factors such as weight to be handled, but are also determined by the design of the man-machine interface. In this study, three different handles of electric hedge-clippers were analysed; the results of a comparative investigation into the physiological cost demanded by the use of the different handles are discussed. Muscular strain was measured via surface electromyography in laboratory experiments with nine male subjects. The results showed significant differences in physiological cost depending on both work height and the handles' shape. Systematic differences in muscular strain between the utilized tools were found, despite the fact that all clippers were compensated with respect to weight and location of the centre of gravity. One of the handle designs enabled working under varying conditions (work height and direction) at a reduced level of muscular strain of the right arm. Results from the physiological evaluation were partly supported by the working persons' own subjective experience. The results of this investigation show that further ergonomic tool and handle design is necessary.     

基于需求驱动的数字化校园数据架构研究与设计

近年来,在数字化校园建设中,以数据服务为核心,为不同角色提供人性化信息服务,以及为学校发展提供决策支持的需求应运而生.而单一的统一数据库在应用系统和业务规模扩大时其应用查询效率较低,为此设计出一种新的数字化校园数据架构,将数据交换库与共享数据库分离,使数据存放更为有效,从而提高查询效率.从理论上和技术上对新的数据架构进行了可行性分析.新的数据架构能够较好地满足数字化校园建设中的新需求.     

Numerical simulation of flows over vacuometers by means of the Monte-Carlo method of direct statistical simulation

An upper atmosphere probe is considered. For the atmosphere parameters, a reconstruction method using the density data by a vacuometer located behind a wire screen is constructed. In the context of the Monte-Carlo method of direct statistical simulation, we propose a simplified simulation algorithm for the interactions of a molecule with the wire screen treated as a semipermeable membrane. To obtain a relationship between the transmitter reading and the parameters of the undisturbed atmosphere, we numerically simulate the flow over the transmitter.     

An assessment of shuttle radar topography mission digital elevation data for studies of volcano morphology

The Shuttle Radar Topography Mission has provided high spatial resolution digital topographic data for most of Earth's volcanoes. Although these data were acquired with a nominal spatial resolution of 30 m, such data are only available for volcanoes located within the U.S.A. and its Territories. For the overwhelming majority of Earth's volcanoes not contained within this subset, DEMs are available in the form of a re-sampled 90 m product. This has prompted us to perform an assessment of the extent to which volcano-morphologic information present in the raw 30 m SRTM product is retained in the degraded 90 m product. To this end, we have (a) applied a simple metric, the so called dissection index (di), to summarize the shapes of volcanic edifices as encoded in a DEM and (b) using this metric, evaluated the extent to which this topographic information is lost as the spatial resolution of the data is reduced. Calculating di as a function of elevation (a di profile) allows us to quantitatively summarize the morphology of a volcano. Our results indicate that although the re-sampling of the 30 m SRTM data obviously results in a loss of morphological information, this loss is not catastrophic. Analysis of a group of six Alaskan volcanoes indicates that differences in di profiles calculated from the 30 m SRTM product are largely preserved in the 90 m product. This analysis of resolution effects on the preservation of topographic information has implications for research that relies on understanding volcanoes through the analysis of topographic datasets of similar spatial resolutions produced by other remote sensing techniques (e.g., repeat-pass interferometric SAR; optical stereometry).     

Twitter data analysis by means of Strong Flipping Generalized Itemsets

Twitter data has recently been considered to perform a large variety of advanced analysis. Analysis of Twitter data imposes new challenges because the data distribution is intrinsically sparse, due to a large number of messages post every day by using a wide vocabulary. Aimed at addressing this issue, generalized itemsets – sets of items at different abstraction levels – can be effectively mined and used to discover interesting multiple-level correlations among data supplied with taxonomies. Each generalized itemset is characterized by a correlation type (positive, negative, or null) according to the strength of the correlation among its items.This paper presents a novel data mining approach to supporting different and interesting targeted analysis – topic trend analysis, context-aware service profiling – by analyzing Twitter posts. We aim at discovering contrasting situations by means of generalized itemsets. Specifically, we focus on comparing itemsets discovered at different abstraction levels and we select large subsets of specific (descendant) itemsets that show correlation type changes with respect to their common ancestor. To this aim, a novel kind of pattern, namely the Strong Flipping Generalized Itemset (SFGI), is extracted from Twitter messages and contextual information supplied with taxonomy hierarchies. Each SFGI consists of a frequent generalized itemset X and the set of its descendants showing a correlation type change with respect to X.Experiments performed on both real and synthetic datasets demonstrate the effectiveness of the proposed approach in discovering interesting and hidden knowledge from Twitter data.     

Mapping Arctic tundra vegetation types using digital SPOT/HRV-XS data A preliminary assessment

Abstract

Multispectral (XS) image data recorded by the High Resolution Visible (HRV) sensor aboard the SPOT-1 satellite are being evaluated for the mapping of Arctic tundra vegetation in the Arctic Foothill Province of Alaska. This research is part of a current ecosystems study that requires an efficient means for mapping vegetation types over large areas. Conventional spectral-based image classification techniques were applied to SPOT/HRV-XS data from a single date. The unique characteristics of the vegetation cover (mainly tussock tundra) and illumination conditions of the location necessitated a detailed examination of classification approaches that have generally been applied in mid-latitude studies. Preliminary results suggest that areal estimates of Arctic tundra vegetation types can be made accurately (±2·5 per cent per category), but maps generated by classifying spectral features of SPOT/HRV-XS data alone arc unsuitably accurate (56 per cent). This is partly due to the high occurrence of relatively small vegetation parcels, determined by measuring the characteristic lengths of vegetation parcels from a ‘ground reference’ map covering the same area as the SPOT/HRV-XS subscene.     

Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data

The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by solving the IEM with two unknowns is a classic example of under-determination and is at the core of the problems associated with the use of radar imagery coupled with IEM-like models. This study offers a solution strategy to this problem by the use of multi-angle radar images, and thus provides estimates of roughness and soil moisture without the use of ancillary field data. Results showed that radar images can provide estimates of surface soil moisture at the watershed scale with good accuracy. Results at the field scale were less accurate, likely due to the influence of image speckle. Results also showed that subsurface roughness caused by rock fragments in the study sites caused error in conventional applications of IEM based on field measurements, but was minimized by using the multi-angle approach.     

Statistical evaluation and verification of digital simulation models

In most instances, designers of digital simulation models ignore the statistical design and the statistical implications associated with these models. Most ignore the problem because of the added difficulties related to autocorrelated data. Fishman and Kiviat of the RAND Corporation [33] suggested the use of spectral analysis as a technique for evaluating the significance of statistics emanating from a simulation model, comparing model output with “real-world” data for model verification and comparing model outputs for two or more policy change evaluations. The authors have developed this concept into a synthesized model and verified the model through a spectral analysis on data derived from the Logistics Composite Model (LCOM). LCOM was developed jointly by the RAND Corporation and the Air Force Logistics Command for the purpose of simulating aircraft flight and base support processes in response to mission requirements. Some forty statistics were evaluated through spectral analysis for confidence limits. Further, certain policy changes regarding inventory re-order were implemented and a spectral analysis was performed to judge whether or not the separate results were statistically different.     

A computer program for the simulation of landform erosion

A computer implementation of a stochastic model describing changes in a landform during lithologically controlled erosion is described. The model is a Markov chain in two dimensions where the noise component depends upon the underlying lithologies. A surface at any elevation above the present level can be reconstructed according to the characteristics of any of four generally accepted geomorphic theories. Erosion then proceeds until the desired reduction in elevation is achieved. The resulting surface then can be compared to an expected surface, such as the present one, and a measure of fit obtained. About 4096 geomorphically significant option combinations are available, including: isostatic adjustment to erosion, epeirogenic uplift, treatment of the landform parameters as random variables, and criteria for ending the simulation. A technique for validation based upon the random topology model of R. L. Shreve is included. An example covering about 5000 km² in the central Appalachians is described.