4 results for Aryal, Jagannath

  • On the usefulness of very high resolution IKONOS satellite imagery for vegetation mapping

    Mathieu, Renaud; Aryal, Jagannath; Beck, K; Shanahan, D (2004-11)

    Conference item
    University of Otago

    Only the abstract was published in the proceedings. There is no full text.

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  • Predictive habitat modelling to estimate petrel breeding colony sizes: Sooty shearwaters (Puffinus griseus) and mottled petrels (Pterodroma inexpectata) on Whenua Hou Island

    Scott, Darren; Moller, Henrik; Fletcher, David; Newman, Jamie; Aryal, Jagannath; Bragg, Corey; Charleton, Kristin (2009)

    Journal article
    University of Otago

    Between 2001 and 2006, we systematically sampled the entire coast of Whenua Hou, a rugged offshore island in southern New Zealand, to estimate the population densities of sooty shearwaters (Puffinus griseus) and mottled petrels (Pterodroma inexpectata) by counting the entrances of breeding burrows. A two‐step regression modelling process using binomial errors was used to predict the presence of a colony, and a normal general linear model was used to predict the density of entrances within colonies. Aerial photography, GIS and a Digital Elevation Model were used to extract relevant habitat and location variables, and a combination of both regression models was used to predict the density of breeding burrows within each 5.32 m2 pixel on the island. This complex GIS and habitat prediction modelling approach gave population estimates very similar to a more traditional simple area extrapolation method and gave no improvement in precision. However, correction for the slope of the land increased our simple area estimates of population size by 11%. We estimate populations of sooty shearwater and mottled petrel breeding pairs at 173 000 (162 000–190 000) and 160 000 (123 000–197 000) respectively. Based on this number of breeding pairs, we calculate that Whenua Hou supports a total population of 868 000 (554 000–1 270 000) sooty shearwaters. Our estimate of the total mottled petrel population 202 000 pairs (162 000–242 000) is comparable with the only published estimate, but could be an underestimate because mottled petrels are sometimes found in large burrows. More research for robust estimation of population trends is needed to assess the conservation status of mottled petrels.

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  • Object-oriented classification and Ikonos multispectral imagery for mapping vegetation communities in urban areas

    Mathieu, Renaud; Aryal, Jagannath (2005-11)

    Conference paper
    University of Otago

    The management of vegetated areas by urban planners relies on detailed and updated knowledge of their nature and distribution. Manual photo-interpretation of aerial photographs is efficient, but is time consuming. Image segmentation and object-oriented classifications provide a tool to automatically delineate and label vegetation units. Object-oriented techniques were tested with a very high-resolution multispectral Ikonos image to produce fine scale maps of vegetation communities in Dunedin (New Zealand). The Ikonos image was orthorectified and a first classification produced a map with 4 strata: industrial/commercial (with amenity pastures and tree groups), residential (with amenity pastures and private gardens), vegetation (with other vegetation classes), and water. A hierarchical network of image objects was built to extract vegetation patches of various sizes such as small private gardens and larger exotic plantations. The classification of the image objects was performed using the nearest neighbour (NN) method. Thirteen variables were considered to build the NN feature space, including mean object spectral value and standard deviation for each spectral band, and object compactness. The vegetation map was validated using an independent dataset collected in the field. The original classification scheme included 17 vegetation categories, of which ten were successfully discriminated: forests, exotic plantations, tree groups, exotic scrubs, mixed scrubs, native scrubs, pastures, amenity grasslands, rough grasslands, private gardens. Classes of ecological interest characterized by various canopy densities could not be discriminated (e.g. low and high density gardens, shrublands and scrubs). Vegetation patches smaller than 0.05 ha were efficiently extracted within the city. The overall classification accuracy was 92% and the kappa coefficient was 0.89 (i.e. 89% more accurate than a random classification). Object-oriented techniques and Ikonos imagery proved to be a promising technique to produce GISready vegetation map.

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  • Optimisation of a buyer’s sourcing strategy in the mixed auction/direct supply of New Zealand wool

    Aryal, Jagannath

    Lincoln University

    The New Zealand Wool Industry (NZWI) contributes over a billion dollars a year to NZ gross output. However, this industry is at a crossroads and the incumbent practitioners are looking for ways to increase the value of the New Zealand wool clip. The value of the industry to the economy is directly related to the price which buyers are prepared to pay for wool, primarily as a result of the marketing approaches used, physical parameters of wool as well as intra and inter-fibre competition. The inflation adjusted price has steadily decreased over recent years and understanding of its dynamics is a fundamental problem for the stakeholders. Among the stakeholders, buyers / exporters, heavily involved in the process of price formation currently face a real time problem of sourcing strong wool from two parallel but different marketing systems operated simultaneously – auction and direct supply. The underlying mathematics which governs the decision making of buyers on the price dynamics in these sourcing options is poorly understood. This study developed system models for price formation in both auction and direct supply sourcing and an associated optimization model for the buyer / exporter of the New Zealand wool clip. All three of these models were original and none appear to have been described previously. It is hoped that these three models will be of quite general utility and also be useful therefore for other agricultural commodities that are traded simultaneously via auction and direct supply. The average price for a given wool type, which is the output from this new modelling exercise is precisely what is required as input data for solving the minimization problem in wool blending models.

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