Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications

Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications Kitap pdf indir

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Sitenin güncellenmesi nedeniyle, güncelleme tamamlanana kadar indirme işlemi geçici olarak durdurulacaktır. [email protected]

Michael Goodchild bir coğrafyacı ve coğrafi bilgi bilimi (GIS) alanında öncüdür. 24 Şubat 1944'te İngiltere'nin Surrey kentinde doğdu ve coğrafya alanında doktora derecesini 1969'da Bristol Üniversitesi'nden aldı.

Goodchild, CBS, mekansal analiz ve uzaktan algılama üzerine yaptığı araştırmalarla tanınmaktadır. 15'in üzerinde kitap ve 500'den fazla makalenin yazarlığını veya yazarlığını üstlendi ve coğrafya ve GIS alanına katkılarından dolayı çok sayıda ödül aldı.

Akademik çalışmalarına ek olarak, Goodchild, "Geographical Analysis" dergisinin editörlüğü ve Ulusal Coğrafi Bilgi ve Analiz Merkezi'nin (NCGIA) kurucu başkanı olarak görev yapmak da dahil olmak üzere CBS ile ilgili çeşitli organizasyon ve girişimlerde yer almıştır. Birleşik Devletler.

Goodchild şu anda California Üniversitesi, Santa Barbara'da fahri coğrafya profesörüdür ve araştırma ve öğretimde aktif olmaya devam etmektedir.

Kitabın Tanımı

Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications kitap pdf oku ve indir Michael Goodchild

" Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications" is a book authored by Michael Goodchild that explores the issue of spatial uncertainty in ecological research and its implications for remote sensing and GIS applications. The book is a comprehensive guide to the latest methods and techniques for dealing with spatial uncertainty in ecology, with a focus on how these methods can be used in conjunction with remote sensing and GIS technologies.

The book starts by introducing the concept of spatial uncertainty and its relevance to ecological research. It then goes on to discuss the different sources of spatial uncertainty, including errors in data collection, processing, and analysis. The book also explores the different types of spatial uncertainty, including positional uncertainty, attribute uncertainty, and temporal uncertainty.

One of the key strengths of the book is its focus on the practical applications of spatial uncertainty in ecological research. The book provides a detailed overview of the different methods and techniques that can be used to quantify and model spatial uncertainty, including Monte Carlo simulation, fuzzy logic, and Bayesian networks. The book also includes a range of case studies that demonstrate how these methods can be applied in practice.

In addition to its focus on spatial uncertainty, the book also explores the latest developments in remote sensing and GIS technologies and their applications in ecology. The book provides a comprehensive overview of the different types of remote sensing data that are available, including satellite imagery, airborne lidar, and ground-based sensors. It also explores the latest advances in GIS software and how these can be used to integrate different types of spatial data.

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