Discriminating small wooded elements in rural landscape from aerial photography: a hybrid pixel/object-based analysis approach

While small, fragmented wooded elements do not represent a large surface area in agricultural landscape, their role in the sustainability of ecological processes is recognized widely. Unfortunately, landscape ecology studies suffer from the lack of methods for automatic detection of these elements. We propose a hybrid approach using both aerial photographs and ancillary data of coarser resolution to automatically discriminate small wooded elements. First, a spectral and textural analysis is performed to identify all the planted-tree areas in the digital photograph. Secondly, an object-orientated spatial analysis using the two data sources and including a multi-resolution segmentation is applied to distinguish between large and small woods, copses, hedgerows and scattered trees. The results show the usefulness of the hybrid approach and the prospects for future ecological applications

Forty-four years of land use changes in a Sardinian cork oak agro-silvopastoral system: a qualitative analysis

The island of Sardinia is the biggest producer of natural cork in Italy. In this study, cork oak cover change is investigated in a typical agro-silvopastoral system where the main activities are cereal fodder and wheat cultivation, sheep rearing and cork exploitation. The research method is based on the comparison of two land use maps produced by photo-interpretation of digitised aerial photographs taken in 1954 and 1998, combined with interviews with local farmers, field surveys, and data collected from literature, administrative documentation and decadal censuses (at council level). The results show that the cork oak woodland surface decreased (-29%). It was substituted by other forest, ploughed land, and mixed grassland and shrubland. Apart from the transformation of the cork oak woodland to other forest, other changes have happened probably because of an increase in agricultural and pastoral activities as described by the documental material available for the same area

The usefulness of thermal infrared and related imagery in the evaluation of agricultural resources. An exploratory study, volume I Final report

Multispectral imagery for aerial inventory and analysis of cultivated crop resource

A preliminary training guide for utilizing high-altitude, color-infrared photography in compiling soil maps

Instruction for acquiring and analytically processing small-scale color-infrared photography to perform a soil resources inventory over forests of the southern U.S. is provided. Planning the project; acquiring aerial photography, materials, equipment and supplemental data; and preparing the photography for analysis are discussed. The procedures for preparing ancillary and primary component overlays are discussed. The use of correlation charts and dichotomous keys for mountain landforms, water regime, and vegetation is explained

Investigation of natural environment by space means. Geobotany, Geomorphology, soil sciences, agricultural lands, landscape study

Reports given by Soviet specialists at a meeting of Socialist countries on remote sensing of the earth using aerospace methods are presented

Development of analysis techniques for the use of aerial photography in the monitoring of intertidal mussel beds and oyster beds

This project aimed at improving the analysis techniques of aerial photography for mussel bed recognition and mapping. In this project two techniques were tested; recognition and mapping by human eye and recognition and mapping by automatic detection software. The detection with the human eye was tested in two ways. The first test considered recognition of mussel beds in an area were contours of the previous year were available. The second test concerned a blind recognition test without any knowledge on previous locations of mussel beds

Segmentation and classification of individual tree crowns

By segmentation and classification of individual tree crowns in high spatial resolution aerial images, information about the forest can be automatically extracted. Segmentation is about finding the individual tree crowns and giving each of them a unique label. Classification, on the other hand, is about recognising the species of the tree. The information of each individual tree in the forest increases the knowledge about the forest which can be useful for managements, biodiversity assessment, etc. Different algorithms for segmenting individual tree crowns are presented and also compared to each other in order to find their strengths and weaknesses. All segmentation algorithms developed in this thesis focus on preserving the shape of the tree crown. Regions, representing the segmented tree crowns, grow according to certain rules from seed points. One method starts from many regions for each tree crown and searches for the region that fits the tree crown best. The other methods start from a set of seed points, representing the locations of the tree crowns, to create the regions. The segmentation result varies from 73 to 95 % correctly segmented visual tree crowns depending on the type of forest and the method. The former value is for a naturally generated mixed forest and the latter for a non-mixed forest. The classification method presented uses shape information of the segments and colour information of the corresponding tree crown in order to decide the species. The classification method classifies 77 % of the visual trees correctly in a naturally generated mixed forest, but on a forest stand level the classification is over 90 %