Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA - or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance of ‘grey’ literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA methods are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.

Object based image analysis for remote sensing

Climate change 2014 - Synthesis Report

This paper deals with several aspects of the assessment of hazard and risk of landsliding. In recent years the interest in this topic has increased greatly and there are many technical papers dealing with this subject in the literature. This article presents a summary review and a classification of the main approaches that have been developed world-wide. The first step is the subdivision between qualitative and quantitative methods. The first group is mainly based on the site-specific experience of experts with the susceptibility/hazard determined directly in the field or by combining different index maps. The approaches of the second group are formally more rigorous. It is possible to distinguish between statistical analyses (bivariate or multivariate) and deterministic methods that involve the analysis of specific sites or slopes based on geo-engineering models. Such analyses can be deterministic or probabilistic. Among the quantitative methods discussed is the Neural Networks approach which has only recently been applied to engineering geology problems. Finally several considerations concerning the concept of acceptable risk and risk management are presented.

Landslide hazard assessment: summary review and new perspectives

https://ro.uow.edu.au/cgi/viewcontent.cgi?article=5754&context=engpapers

Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning

https://www.ecorisq.org/docs/foreco183.pdf

Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification

Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM

Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping

https://pure.uva.nl/ws/files/2250898/125305_AppGeography_Aguirre_et_al_2012.pdf

Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico

https://pure.uva.nl/ws/files/3804251/41638_Gustavvsson_et_al_Mapping_System.pdf

Arie C. Seijmonsbergen

Papers

Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification

Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM

Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping

Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico

A new symbol-and-GIS based detailed geomorphological mapping system: Renewal of a scientific discipline for understanding landscape development