7,400 research outputs found
Database for: Excavations at Tall Jawa, Jordan: Volume 3, The Iron Age Pottery
No full textThis is a Microsoft Access database of imagery, drawings, and photos accompanying Excavations at Tall Jawa, Jordan: Volume 3, The Iron Age Pottery by P.M. Michèle Daviau. The text and database present a detailed typology of the Iron Age pottery excavated from 1989 to 1995. Together, they represent an in-depth analysis of the forming techniques employed to make each type of vessel from bowls to colanders, cooking pots to pithoi.
The digital archive is a work in progress by the author. The archive currently holds the collection for Excavation Field D. Upon completion, it will include seven collections, each one consisting of a database of diagnostic sherds and vessels as well as the images of these pots as .tiff files. Databases are related to excavation fields and are designed for meaningful searches: A, B, C-east, C-west, A-east (associated with C-west), D and E
Super-Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
No full textLandscape pattern represents a key variable in management and understanding of the environment, as well as driving many environmental models. Remote sensing can be used to provide information on the spatial pattern of land cover features, but analysis and classification of such imagery suffers from the problem of class mixing within pixels. Fuzzy classification techniques can estimate the class composition of image pixels. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques to provide an improved spatial representation of land cover targets larger than the size of a pixel have been developed, however, the mapping of sub-pixel scale land cover features has yet to be investigated. We recently described the application of a Hopfield neural network technique to super-resolution mapping of land cover features larger than a pixel (Tatem et al., 2000), using information of pixel composition determined from fuzzy classification, and (was but) now show how our approach can be extended in a new way (added) to predict the spatial pattern of sub-pixel scale features. The network converges to a minimum of an energy function defined as a goal and several constraints. Prior information on the typical spatial arrangement of the particular land cover types is incorporated into the energy function as a constraint. This produces a prediction of the spatial pattern of the land cover in question, at the sub-pixel scale. The technique is applied to synthetic and simulated Landsat TM imagery, and compared to results of an existing super-resolution target identification technique. Results show that the new approach (was Hopfield neural network) represents a simple, robust and efficient tool for super-resolution land cover pattern prediction from remotely sensed imagery
Geostatistical classification for remote sensing: an introduction
No full textTraditional spectral classification of remotely sensed images applied on a pixel-by-pixel basis ignores the potentially useful spatial information between the values of proximate pixels. For some 30 years the spatial information inherent in remotely sensed images has been employed, albeit by a limited number of researchers, to enhance spectral classification. This has been achieved primarily by filtering the original imagery to (i) derive texture ‘wavebands’ for subsequent use in classification or (ii) smooth the imagery prior to (or after) classification. Recently, the variogram has been used to represent formally the spatial dependence in remotely sensed images and used in texture classification in place of simple variance filters. However, the variogram has also been employed in soil survey as a smoothing function for unsupervised classification. In this review paper, various methods of incorporating spatial information into the classification of remotely sensed images are considered. The focus of the paper is on the variogram in classification both as a measure of texture and as a guide to choice of smoothing function. In the latter case, the paper focuses on the technique developed for soil survey and considers the modification that would be necessary for the remote sensing case. <br/
Earthquake-and-landslide events are associated with more fatalities than earthquakes alone
No full textNatural hazards are natural processes of the complex Earth system and may interact and affect each other. Often a single hazard can trigger a subsequent, different hazard, such as earthquakes triggering landslides. The effect of such cascading hazards has received relatively little attention in the literature. The majority of previous research has focused on single hazards in isolation, and even multi-hazard risk assessment currently does not account for the interaction between hazards, therefore ignoring potential amplification effects. Global earthquake-and-landslide fatality data were used to model cascading events to explore relationships between the number of fatalities during single and cascading events and covariates. A multivariate statistical approach was used to model the relationship between earthquake fatalities and several covariates. The covariates included earthquake magnitude, gross domestic product, slope, poverty, health, access to cities, exposed population to earthquake shaking, building strength and whether a landslide was triggered or not. Multivariate regression analysis showed the numbers of earthquake fatalities are significantly affected by whether a subsequent landslide is triggered or not
Quantitative and qualitative measurements of planned and unexpected change using remotely sensed imagery
No full text[Locomotive S 303 with 10/455 tons on 5 p.m. down Albury Express after passing Broadmeadows, Victoria, Melbourne, January 5, 1938] [picture] /
No full textPart of collection: Buckland collection of railway transport photographs.; Inscriptions: "S 303 (small tender) with 10/455 tons on 5 p.m. down Albury Express after passing Broadmeadows Jan 5, 1938"-- in ink on reverse.; Selected items are also available in an electronic version via the Internet at: http://nla.gov.au/nla.pic-vn3411329
Graduate recital, saxophone. Lewis, R., 1997
No full textRecorded during a live performance at Dalton Center Recital Hall, Western Michigan University, Kalamazoo, Michigan, February 4, 1997, 8:00 p.m., the 295th concert of the School of Music's 1996-1997 season.Robert Lewis, alto saxophone ; Tracy Cowden, piano ; 1st work with: Esin Boal, Mark Morris, violins ; Paul Krupiczewicz, viola ; Julia Karosas, cello ; Tracy Cowden, harpsichord.In partial fulfillment of the requirements of the Master of Music degree in saxophone performance, Western Michigan University, 1997.Information from performance program.Oboe concerto in D minor / Alessandro Marcello -- Concertina da camera / Jacques Ibert -- Distances within me / John Anthony Lennon -- Improvisation I for solo saxophone / Ryo Noda -- Oodles of Noodles / Jimmy Dorsey
Evacuation simulation modelling in the event of a near Earth object impact
No full textIf an Earth-threatening Near Earth Object (NEO) is detected, it is
important that decision makers, such as the United Nations together with nations at risk, decide how to approach such a natural hazard. Understanding the vulnerability, risk and resilience along the Path of Risk (PoR) is important in order to identify the most vulnerable areas and the dangers from the hazard, and when deciding how to mitigate such a natural hazard. This paper presents initial work in how a global vulnerability has been developed. This model has been applied to a case study to illustrate how it can be used as a measure in the context of NEO impact effects to identify areas at high risk such that evacuation should be considered. Initial studies in how to approach the evacuation modelling of these areas will also be discussed
A systematic review of landslide probability mapping using logistic regression
No full textLogistic regression studies which assess landslide susceptibility are widely available in the literature. However, a global review of these studies to synthesise and compare the results does not exist. There are currently no guidelines for the selection of covariates to be used in logistic regression analysis, and as such, the covariates selected vary widely between studies. An inventory of significant covariates associated with landsliding produced from the full set of such studies globally would be a useful aid to the selection of covariates in future logistic regression studies. Thus, studies using logistic regression for landslide susceptibility estimation published in the literature were collated, and a database was created of the significant factors affecting the generation of landslides. The database records the paper the data were taken from, the year of publication, the approximate longitude and latitude of the study area, the trigger method (where appropriate) and the most dominant type of landslides occurring in the study area. The significant and non-significant (at the 95 % confidence level) covariates were recorded, as well as their coefficient, statistical significance and unit of measurement. The most common statistically significant covariate used in landslide logistic regression was slope, followed by aspect. The significant covariates related to landsliding varied for earthquake-induced landslides compared to rainfall-induced landslides, and between landslide type. More importantly, the full range of covariates used was identified along with their frequencies of inclusion. The analysis showed that there needs to be more clarity and consistency in the methodology for selecting covariates for logistic regression analysis and in the metrics included when presenting the results. Several recommendations for future studies were given
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