1.

Record Nr.

UNINA9910456472103321

Autore

Simms Andrew

Titolo

Ecological debt [[electronic resource] ] : global warming and the wealth of nations / / Andrew Simms

Pubbl/distr/stampa

London, : Pluto Press, 2009

ISBN

1-78371-059-4

1-84964-377-6

Edizione

[2nd ed.]

Descrizione fisica

1 online resource (336 p.)

Disciplina

333.7

Soggetti

Environmental economics

Environmental protection - Citizen participation

Consumption (Economics) - Environmental aspects

Global warming

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di bibliografia

Includes bibliographical references (p. 190-204) and index.

Sommario/riassunto

--New edition of this highly acclaimed guide-- 'Creative and compelling.' Guardian'Essential reading.' Head of the IPCC 'A new phrase has entered the language.' Anita RoddickThis is the second edition of Andrew Simms's highly regarded guide to ecological



2.

Record Nr.

UNINA9910789490203321

Titolo

Remote sensing of protected lands [[electronic resource] /] / edited by Yeqiao Wang

Pubbl/distr/stampa

Boca Raton, : CRC Press, c2012

ISBN

0-429-10567-3

1-4398-4188-8

Descrizione fisica

1 online resource (613 p.)

Collana

Taylor & Francis series in remote sensing applications

Altri autori (Persone)

WangYeqiao

Disciplina

333.73/160285

333.73160285

Soggetti

Protected areas - Remote sensing

Remote sensing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Front Cover; Contents; Series Foreword; Preface; Acknowledgments; Editor; Contributors; Chapter 2 - Remote Sensing for Inventory and Monitoring of U.S. National Parks; Chapter 3 - Monitoring Landscape Dynamics of National Parks in the Western United States; Chapter 4 - Forest Dynamics within and around Olympic National Park Assessed Using Time-Series Landsat Observations; Chapter 13 - Integration of Remote Sensing and In Situ Ecology for the Design and Evaluation of Marine-Protected Areas: Examples from Tropical and Temperate Ecosystems

Chapter 14 - Remote Sensing Assessment of Wildfire Impact and Simulation Modeling of Short-Term Post-Fire Vegetation Recovery within the Dixie National ForestChapter 15 - Satellite-Observed Endorheic Lake Dynamics across the Tibetan Plateau between Circa 1976 and 2000; Chapter 16 - Multisensor Remote Sensing of Forest Dynamics in Central Siberia; Chapter 17 - Remote Sensing and Modeling for Assessment of Complex Amur (Siberian) Tiger and Amur (Far Eastern) Leopard Habitats in the Russian Far East; Chapter 18 - The Influence of Realistic Vegetation Phenology on Regional Climate Modeling

Chapter 19 - Monitoring Natural Hazards in Protected Lands Using Interferometric Synthetic Aperture RadarChapter 20 - Characterizing



Biophysical Properties in Protected Tropical Forests with Synergistic Use of Optical and SAR Imagery; Chapter 22 - Monitoring and Forecasting Climate Impacts on Ecosystem Dynamics in Protected Areas Using the Terrestrial Observation and Prediction System; Chapter 23 - Geospatial Decision Models for Management of Protected Wetlands; Back Cover

Sommario/riassunto

National parks, wildlife refuges and sanctuaries, natural reserves, conservation areas, frontier lands, and marine-protected areas are increasingly recognized as essential providers of ecosystem services and biological resources. As debates about climate change and sustainability intensify, protected areas become more important as indicators of ecosystem conditions in particular environments or in comparison with adjacent environments. The first book of its kind, Remote Sensing of Protected Lands showcases state-of-the-art remote sensing applications for the i

3.

Record Nr.

UNINA9910299284403321

Titolo

Human and Machine Learning : Visible, Explainable, Trustworthy and Transparent / / edited by Jianlong Zhou, Fang Chen

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018

ISBN

3-319-90403-5

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XXIII, 482 p. 140 illus., 114 illus. in color.)

Collana

Human–Computer Interaction Series, , 2524-4477

Disciplina

006.31

Soggetti

User interfaces (Computer systems)

Human-computer interaction

Artificial intelligence

Pattern recognition systems

User Interfaces and Human Computer Interaction

Artificial Intelligence

Automated Pattern Recognition

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Nota di contenuto

Part I Transparency in Machine Learning -- Part II Visual Explanation of Machine Learning Process -- Part III Algorithmic Explanation of Machine Learning Models -- Part IV User Cognitive Responses in ML-Based Decision Making -- Part V Human and Evaluation of Machine Learning -- Part VI Domain Knowledge in Transparent Machine Learning Applications.

Sommario/riassunto

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.