Gis And Remote Sensing Applications In Biogeography And Ecology

In recent years, the conservation of tropical forests has received worldwide publicity whereas effective forest management, particularly for timber extraction, has attracted little attention and gained some notoriety. The overall aim of the present paper was to examine how environmental micro-variation in the Chiquibul Forest Reserve of Belize can influence species distribution and thereby inform management strategy. The paper deals first with the background to forest management in Belize, then considers the methodology used in the present study and fin~~ly assesses the preliminary results. The specific objectives are: (1) to assess the effects of changing scale on the variability of selected individual soil properties in forest plots within the same vegetation class; and (2) to examine the variation in soil properties and tree species distribution, and to integrate environmental and ecological data over a range of scales. BACKGROUND Whereas the global and regional distribution of tropical forests is broadly governed by climatic and altitudinal variation, individual forest tracts need to consider a range of other, locally important factors to explain species distribution and change. With very high species diversity, tropical forests present a major challenge in the attempt to unravel controlling factors in distribution and growth (Swaine et aI. 1987). Research that attempts to explain diversity has looked at species distribution according to a range of factors, with a general recognition that soil fertility plays a significant if ill defined role (Swaine 1996).

This is one of the first books to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research, and thus delivers the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences by way of spatial data. After describing the uses of such data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis.

Particularly about forests in the USA.

In an age of unprecedented proliferation of data from disparate sources the urgency is to create efficient methodologies that can optimise data combinations and at the same time solve increasingly complex application problems. Integration of GIS and Remote Sensing explores the tremendous potential that lies along the interface between GIS and remote sensing for activating interoperable databases and instigating information interchange. It concentrates on the rigorous and meticulous aspects of analytical data matching and thematic compatibility - the true roots of all branches of GIS/remote sensing applications. However closer harmonization is tempered by numerous technical and institutional issues, including scale incompatibility, measurement disparities, and the inescapable notion that data from GIS and remote sensing essentially represent diametrically opposing conceptual views of reality. The first part of the book defines and characterises GIS and remote sensing and presents the reader with an awareness of the many scale, taxonomical and analytical problems when attempting integration. The second part of the book moves on to demonstrate the benefits and costs of integration across a number of human and environmental applications. This book is an invaluable reference for students and professionals dealing not only with GIS and remote sensing, but also computer science, civil engineering, environmental science and urban planning within the academic, governmental and commercial/business sectors.

This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS. Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided. This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.