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The classification of pollen grains using texture information in combination with shape features is presented in this paper. The surface texture of pollen is characterised by using Gabor trans- forms, the geometric shape is described by using moment invariants, and the pollen grains are clas- sifiedby anartificial neural network.In anexperiment with fivetypes of pollengrains, more than 97% of samples are correctly classified. Copyright ! 2004 John Wiley & Sons, Ltd.

This is the first of a series of papers on the theme of automated pollen analysis. The automation of pollen analysis could result in numerous advantages for the reconstruction of past environments, with larger data sets made practical, objectivity and fine resolution sampling. There are also applications in apiculture and medicine. Previous work on the classification of pollen using texture measures has been successful with small numbers of pollen taxa. However, as the number of pollen taxa to be identified increases, more features may be required to achieve a successful classi- fication. This paper describes the use of simple geometric measures to augment the texture measures. The feasibility of this new approach is tested using scanning electron microscope (SEM) images of 12 taxa of fresh pollen taken from reference material collected on Henderson Island, Polynesia. Pollen images were captured directly from a SEM connected to a PC. A threshold grey-level was set and binary images were then generated. Pollen edges were then located and the boundaries were traced using a chain coding system. A number of simple geometric variables were calculated directly from the chain code of the pollen and a variable selection procedure was used to choose the optimal subset to be used for classification. The efficiency of these variables was tested using a leave-one-out clas- sification procedure. The system successfully split the original 12 taxa sample into five sub-samples containing no more than six pollen taxa each. The further subdivision of echinate pollen types was then attempted with a subset of four pollen taxa. A set of difference codes was constructed for a range of displacements along the chain code. From these difference codes probability variables were cal- culated. A variable selection procedure was again used to choose the optimal subset of probabilities that may be used for classification. The efficiency of these variables was again tested using a leave- one-out classification procedure. The proportion of correctly classified pollen ranged from 81% to 100% depending on the subset of variables used. The best set of variables had an overall classification rate averaging at about 95%. This is comparable with the classification rates from the earlier texture analysis work for other types of pollen. Copyright 2004 John Wiley & Sons, Ltd.

The automation of palynology (the identification and counting of pollen grains and spores) will be a small step for image recognition, but a giant stride for palynology. Here we show the first successful automated identification, with 100% accuracy, of a realistic number of taxa. The technique used involves a neural network classifier applied to surface texture data from light micro- scope images. A further significance of the technique is that it could be adapted for the identification of a wide range of biological objects, both microscopic and macroscopic. Copyright 2004 John Wiley & Sons, Ltd.

Easter Island occupies an exceptionally isolated position in the south Pacific Ocean. It is entirely volcanic, and is famous for its giant statues. Late Quaternary sediments have been investigated in three craters: Rano Raraku, Rano Aroi and Rano Kao, giving a continuous record over the past 30 Ka. Pollen records indicate that the island was formerly forested. Palynological and sedimentological evidence suggests a Late Pleistocene climate slightly cooler and drier than the present. Deforestation by people occurred mainly between 1200 and 800 yr BP. This may have led to an ecological disaster and to the decline of the megalithic civilization. The depauperation of the present native flora owes more to human activity than to isolation.

Summary Two complementary pollen diagrams from Canna show a forest history similar to that found elsewhere in north-west Scotland, but the NAP values are unusually high. A late-glacial may possibly be present.