Improving the potential of pixel-based supervised classification in the absence of quality ground truth data

The accuracy of classified results is often measured in comparison with reference or “ground truth” information. However, in inaccessible or remote natural areas, sufficient ground truth data may not be cost-effectively acquirable. In such cases investigative measures towards the optimisation of the classification process may be required. The goal of this paper was to describe the impact of various parameters when applying a supervised Maximum Likelihood Classifier (MLC) to SPOT 5 image analysis in a remote savanna biome. Pair separation indicators and probability thresholds were used to analyse the effect of training area size and heterogeneity as well as band combinations and the use of vegetation indices. It was found that adding probability thresholds to the classification may provide a measure of suitability regarding training area characteristics and band combinations. The analysis illustrated that finding a balance between training area size and heterogeneity may be fundamental to achieving an optimum classified result.Furthermore, results indicated that the addition of vegetation index values introduced as additional image bands could potentially improve classified products and that threshold outcomes could be used to illustrate confidence levels when mapping classified results

Improving the potential of pixel-based supervised classification in the absence of quality ground truth data

The accuracy of classified results is often measured in comparison with reference or “ground truth” information. However, in inaccessible or remote natural areas, sufficient ground truth data may not be cost-effectively acquirable. In such cases investigative measures towards the optimisation of the classification process may be required. The goal of this paper was to describe the impact of various parameters when applying a supervised Maximum Likelihood Classifier (MLC) to SPOT 5 image analysis in a remote savanna biome. Pair separation indicators and probability thresholds were used to analyse the effect of training area size and heterogeneity as well as band combinations and the use of vegetation indices. It was found that adding probability thresholds to the classification may provide a measure of suitability regarding training area characteristics and band combinations. The analysis illustrated that finding a balance between training area size and heterogeneity may be fundamental to achieving an optimum classified result. Furthermore, results indicated that the addition of vegetation index values introduced as additional image bands could potentially improve classified products and that threshold outcomes could be used to illustrate confidence levels when mapping classified results.http://www.sajg.org.za/index.php/sajgam2016Centre for Geoinformation ScienceGeography, Geoinformatics and Meteorolog

Remote sensing of peanut cropping areas and modelling of their future geographic distribution and disease risks

Peanut or groundnut (Arachis hypogaea L), one of the most important oil seed crops, faces several challenges due to climate change. The unfavourable climate in Australia, as a result of high climate variability, could easily affect peanut production. For example, the incidence of drought stress will increase the likelihood of one of the major problems in the peanut industry, i.e. aflatoxin. In addition, if the climate changes as projected, shifts in geographic distribution of peanut crops and the associated diseases are inevitable. In view of these concerns, this study set the following objectives: 1) to assess the effectiveness of PROBA-V imagery in mapping peanut crops; 2) to study the effects of climate change on the future geographic distribution of peanut crops in Australia; and 3) to examine the effects of climate change on the future distribution of aflatoxin in peanut crops, and to locate high risk areas of aflatoxin in the future areas of peanut crop production. In this study, the area of peanut crop mapping was the South Burnett region in Queensland, while the area of future geographic distribution of peanut crops and aflatoxin covered the entire continent of Australia. To address the first objective, the peanut crop areas were mapped using time-series PROBA-V NDVI by stacking time-series imagery and generating the phenological parameter imagery. Three classification algorithms were used: maximum likelihood classification (MLC), spectral angle mapper (SAM), and minimum distance classification (Min). The results reveal that the overall accuracy of mapping using time-series imagery outweighed phenological parameter imagery, although both datasets performed very well in mapping peanut crops. MLC application in the time-series imagery dataset produced the best result, i.e. overall accuracy of 92.75%, with producer and user accuracy of each class ≥ 78.79%. Specifically for peanut crops, all the algorithms tested produced satisfactory results (≥75.95% of producer and user accuracy), except for the producer accuracy of Min algorithm. Overall, PROBA-V imagery can provide satisfactory results in mapping peanut crops in the study area. For the second objective, the effects of climate change in the potential future geographic distribution of peanut crops in Australia for 2030, 2050, 2070, and 2100 were studied using the CLIMEX program (a Species Distribution Model) under Global Climate Models (GCMs) of CSIRO-Mk3.0 and MIROC-H. The results show an increase in unsuitable areas for peanut cultivation in Australia throughout the projection years for the two GCMs. However, the CSIRO-Mk3 projection of unsuitable areas for 2100 was higher (76% of Australian land) than MIROC-H projection (48% of Australian land). Both GCMs agreed that some current peanut cultivation areas will become unsuitable in the future, while only limited areas will still remain suitable for peanut cultivation. The present study confirms the effects of climate change on the suitability of peanut growing areas in the future. In the third objective, the impacts of climate change on future aflatoxin distribution in Australia and the high risk areas of aflatoxin incidence in the projected future distribution of peanut crops were examined. The projected future distribution of aflatoxin for 2030, 2050, 2070, and 2100 was also modelled using CLIMEX under CSIRO-Mk3.0 and MIROC-H GCMs. The results demonstrated that only a small portion of the Australian continent will be optimal/suitable for aflatoxin persistence, due to the incidence of heat and dry stresses. The map overlay results between the future projections of aflatoxin and peanut crops resulted in small areas of low aflatoxin risk in the future projected areas of peanut crops. It is projected that most of the current peanut cultivation areas will have a high aflatoxin risk, while others will no longer be favourable for peanut cultivation in the future. This study has clearly demonstrated the ability of PROBA-V satellite imagery in mapping peanut crops. It has also demonstrated that climate change incidence will affect the suitability areas of future geographical distribution of peanut crops and the associated aflatoxin disease. This study provides strategic information on current peanut growing areas, future suitable areas for peanut crops in Australia, and future high risk areas of aflatoxin incidence. This information will provide valuable contributions to the long-term planning of peanut cultivation in the country

A critical analysis of the international standards for research and conservation of pleistocene sites: the future of the global heritage of human evolution

On the basis of a critical revision of the application of the criteria that justify the Outstanding Universal Value over time, this work discusses and identifies the need for a specific chapter in 2the Operational Guidelines of the Convention related to Pleistocene sites and properties related to non-sedentary populations. The International community at UNESCO, guided by the most advanced research and conservation knowledge, should set up specific rules and categories for inscription and standards for the integrated preservation of Pleistocene sites. These pages illustrate how to channel the process to pass from Pleistocene knowledge to a Pleistocene heritage, and how to avoid the useless distinction between the arrays of heritages: immovable, movable, intangible, documentary or molecular when defining the very nature of a site related to our early past as humans. Finally, my dissertation invites the research and conservation communities to merge practices and to set up a collaborative dialogue in the interest of our long-term cultural evolution. This dissertation conceives the origins of our remotest cultural diversity as a human capital, which can guide our species on its journey through the enormous challenges toward climate change and artificial intelligence

IKUWA6. Shared Heritage

Celebrating the theme ‘Shared heritage’, IKUWA6 (the 6th International Congress for Underwater Archaeology), was the first such major conference to be held in the Asia-Pacific region, and the first IKUWA meeting hosted outside Europe since the organisation’s inception in Germany in the 1990s. A primary objective of holding IKUWA6 in Australia was to give greater voice to practitioners and emerging researchers across the Asia and Pacific regions who are often not well represented in northern hemisphere scientific gatherings of this scale; and, to focus on the areas of overlap in our mutual heritage, techniques and technology. Drawing together peer-reviewed presentations by delegates from across the world who converged in Fremantle in 2016 to participate, this volume covers a stimulating diversity of themes and niche topics of value to maritime archaeology practitioners, researchers, students, historians and museum professionals across the world

WEED INFESTATION OF WINTER WHEAT IN DIFFERENT TILLAGE SYSTEMS AND LEVEL OF NITROGEN IN TOP DRESSING

Growing technology, especially tillage and fertilization of economically important crop species such as wheat, plays a very important role in weed control. Successful weed control in the crop in turn significantly affects the formation of grain yield, both in quantity and quality. The aim of this paper was to investigate the influence of sustainable (mulch - and no- tillage) and conventional farming system on weed infestation of winter wheat. Basic fertilization was uniform (600 kg/ha NPK 15:15:15) while weed infestation differences between three levels of nitrogen fertilization in top dressing (0, 60 and 120 kg/ha) were examined. The variety Pobeda, selected at the Institute of Field and Vegetable Crops in Novi Sad, served as the object of investigation. The examination was performed at "Radmilovac" on the experimental school property of the Faculty of Agriculture in Zemun within the four- crop rotation (maize-winter wheat-spring barley + red clover-red clover) on leached chernozem soil type in a two-year period. The system of conventional tillage showed the highest efficiency in the weed control (number of weed species and number of weed plants per species) of the two conservation systems. The next is the system of mulch tillage, which may be of interest for practice, while the system of no tillage had the lowest efficiency in the control of weeds, especially perennials. Increasing the amount of nitrogen in the top dressing reduces weeds in all tillage systems, mainly due to the stronger competitiveness of winter wheat. The highest fresh biomass of weeds was measured in the no-tillage system (especially in the second year of investigation) due to the significantly higher presence of perennial broadleaf weeds