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Peng Gong

Other affiliations: Keele University, Beijing Normal University, Nanjing University  ...read more
Bio: Peng Gong is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Land cover & Medicine. The author has an hindex of 95, co-authored 525 publications receiving 32283 citations. Previous affiliations of Peng Gong include Keele University & Beijing Normal University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors identify three categories of challenges that have to be addressed to maintain and enhance human health in the face of increasingly harmful environmental trends: conceptual and empathy failures (imagination challenges), such as an overreliance on gross domestic product as a measure of human progress, the failure to account for future health and environmental harms over present day gains, and the disproportionate eff ect of those harms on the poor and those in developing nations.

1,452 citations

Journal ArticleDOI
TL;DR: In this article, the first 30 m resolution global land cover maps using Landsat Thematic Mapper TM and enhanced thematic mapper plus ETM+ data were produced. And the authors used four classifiers that were freely available were employed, including the conventional maximum likelihood classifier MLC, J4.8 decision tree classifier, Random Forest RF classifier and support vector machine SVM classifier.
Abstract: We have produced the first 30 m resolution global land-cover maps using Landsat Thematic Mapper TM and Enhanced Thematic Mapper Plus ETM+ data. We have classified over 6600 scenes of Landsat TM data after 2006, and over 2300 scenes of Landsat TM and ETM+ data before 2006, all selected from the green season. These images cover most of the world's land surface except Antarctica and Greenland. Most of these images came from the United States Geological Survey in level L1T orthorectified. Four classifiers that were freely available were employed, including the conventional maximum likelihood classifier MLC, J4.8 decision tree classifier, Random Forest RF classifier and support vector machine SVM classifier. A total of 91,433 training samples were collected by traversing each scene and finding the most representative and homogeneous samples. A total of 38,664 test samples were collected at preset, fixed locations based on a globally systematic unaligned sampling strategy. Two software tools, Global Analyst and Global Mapper developed by extending the functionality of Google Earth, were used in developing the training and test sample databases by referencing the Moderate Resolution Imaging Spectroradiometer enhanced vegetation index MODIS EVI time series for 2010 and high resolution images from Google Earth. A unique land-cover classification system was developed that can be crosswalked to the existing United Nations Food and Agriculture Organization FAO land-cover classification system as well as the International Geosphere-Biosphere Programme IGBP system. Using the four classification algorithms, we obtained the initial set of global land-cover maps. The SVM produced the highest overall classification accuracy OCA of 64.9% assessed with our test samples, with RF 59.8%, J4.8 57.9%, and MLC 53.9% ranked from the second to the fourth. We also estimated the OCAs using a subset of our test samples 8629 each of which represented a homogeneous area greater than 500 m × 500 m. Using this subset, we found the OCA for the SVM to be 71.5%. As a consistent source for estimating the coverage of global land-cover types in the world, estimation from the test samples shows that only 6.90% of the world is planted for agricultural production. The total area of cropland is 11.51% if unplanted croplands are included. The forests, grasslands, and shrublands cover 28.35%, 13.37%, and 11.49% of the world, respectively. The impervious surface covers only 0.66% of the world. Inland waterbodies, barren lands, and snow and ice cover 3.56%, 16.51%, and 12.81% of the world, respectively.

1,212 citations

Journal ArticleDOI
TL;DR: To address the health challenges and maximise the benefits that accompany this rapid urbanisation, innovative health policies focused on the needs of migrants and research that could close knowledge gaps on urban population exposures are needed.

930 citations

Journal ArticleDOI
Nick Watts1, Markus Amann2, Nigel W. Arnell3, Sonja Ayeb-Karlsson4, Jessica Beagley1, Kristine Belesova5, Maxwell T. Boykoff6, Peter Byass7, Wenjia Cai8, Diarmid Campbell-Lendrum9, Stuart Capstick10, Jonathan Chambers11, Samantha Coleman1, Carole Dalin1, Meaghan Daly12, Niheer Dasandi13, Shouro Dasgupta, Michael Davies1, Claudia Di Napoli3, Paula Dominguez-Salas5, Paul Drummond1, Robert Dubrow14, Kristie L. Ebi15, Matthew J. Eckelman16, Paul Ekins1, Luis E. Escobar17, Lucien Georgeson18, Su Golder19, Delia Grace20, Hilary Graham12, Paul Haggar10, Ian Hamilton1, Stella M. Hartinger21, Jeremy J. Hess15, Shih Che Hsu1, Nick Hughes1, Slava Mikhaylov, Marcia P. Jimenez22, Ilan Kelman1, Harry Kennard1, Gregor Kiesewetter2, Patrick L. Kinney23, Tord Kjellstrom, Dominic Kniveton24, Pete Lampard19, Bruno Lemke25, Yang Liu26, Zhao Liu8, Melissa C. Lott27, Rachel Lowe5, Jaime Martinez-Urtaza28, Mark A. Maslin1, Lucy McAllister29, Alice McGushin1, Celia McMichael30, James Milner5, Maziar Moradi-Lakeh31, Karyn Morrissey32, Simon Munzert, Kris A. Murray5, Kris A. Murray33, Tara Neville9, Maria Nilsson7, Maquins Odhiambo Sewe7, Tadj Oreszczyn1, Matthias Otto25, Fereidoon Owfi, Olivia Pearman6, David Pencheon32, Ruth Quinn34, Mahnaz Rabbaniha, Elizabeth J. Z. Robinson3, Joacim Rocklöv7, Marina Romanello1, Jan C. Semenza35, Jodi D. Sherman14, Liuhua Shi, Marco Springmann18, Meisam Tabatabaei36, Jonathon Taylor, Joaquin Trinanes37, Joy Shumake-Guillemot, Bryan N. Vu26, Paul Wilkinson5, Matthew Winning1, Peng Gong8, Hugh Montgomery1, Anthony Costello1 
TL;DR: TRANSLATIONS For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.

886 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: 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

14,171 citations

Journal ArticleDOI
15 Nov 2013-Science
TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
Abstract: Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

7,890 citations

Journal ArticleDOI
01 May 1981
TL;DR: This chapter discusses Detecting Influential Observations and Outliers, a method for assessing Collinearity, and its applications in medicine and science.
Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

4,948 citations

Journal ArticleDOI
Haidong Wang1, Mohsen Naghavi1, Christine Allen1, Ryan M Barber1  +841 moreInstitutions (293)
TL;DR: The Global Burden of Disease 2015 Study provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015, finding several countries in sub-Saharan Africa had very large gains in life expectancy, rebounding from an era of exceedingly high loss of life due to HIV/AIDS.

4,804 citations