相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Data investigation of installed and output power densities of onshore and offshore wind turbines worldwide
Peter Enevoldsen et al.
ENERGY FOR SUSTAINABLE DEVELOPMENT (2021)
Interactions of wind energy project siting, wind resource potential, and the evolution of the US power system
Trieu Mai et al.
ENERGY (2021)
Land use and turbine technology influences on wind potential in the United States
Anthony Lopez et al.
ENERGY (2021)
Wind power costs driven by innovation and experience with further reductions on the horizon
Philipp Beiter et al.
WILEY INTERDISCIPLINARY REVIEWS-ENERGY AND ENVIRONMENT (2021)
Expert elicitation survey predicts 37% to 49% declines in wind energy costs by 2050
Ryan Wiser et al.
NATURE ENERGY (2021)
Low-impact land use pathways to deep decarbonization of electricity
Grace C. Wu et al.
ENVIRONMENTAL RESEARCH LETTERS (2020)
Closing the gap between wind energy targets and implementation for emerging countries
Paolo Giani et al.
APPLIED ENERGY (2020)
Geospatial and techno-economic analysis of wind and solar resources in India
Ranjit Deshmukh et al.
RENEWABLE ENERGY (2019)
How much wind power potential does europe have? Examining european wind power potential with an enhanced socio-technical atlas
Peter Enevoldsen et al.
ENERGY POLICY (2019)
Visual Diagnosis of Tree Boosting Methods
Shixia Liu et al.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS (2018)
Effects of turbine technology and land use on wind power resource potential
Erkka Rinne et al.
NATURE ENERGY (2018)
The spatial extent of renewable and non-renewable power generation: A review and meta-analysis of power densities and their application in the US
John van Zalk et al.
ENERGY POLICY (2018)
A global map of travel time to cities to assess inequalities in accessibility in 2015
D. J. Weiss et al.
NATURE (2018)
Data Descriptor: HISDAC-US, historical settlement data compilation for the conterminous United States over 200 years
Stefan Leyk et al.
SCIENTIFIC DATA (2018)
Observation-based solar and wind power capacity factors and power densities
Lee M. Miller et al.
ENVIRONMENTAL RESEARCH LETTERS (2018)
Temporally-explicit and spatially-resolved global onshore wind energy potentials
Jonathan Bosch et al.
ENERGY (2017)
Google Earth Engine: Planetary-scale geospatial analysis for everyone
Noel Gorelick et al.
REMOTE SENSING OF ENVIRONMENT (2017)
Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea
Sunmin Lee et al.
GEOMATICS NATURAL HAZARDS & RISK (2017)
Understanding the life cycle surface land requirements of natural gas-fired electricity
Sarah M. Jordaan et al.
NATURE ENERGY (2017)
Modeling global Hammond landform regions from 250-m elevation data
Deniz Karagulle et al.
TRANSACTIONS IN GIS (2017)
100% Clean and Renewable Wind, Water, and Sunlight All-Sector Energy Roadmaps for 139 Countries of the World
Mark Z. Jacobson et al.
JOULE (2017)
Long-term implications of sustained wind power growth in the United States: Direct electric system impacts and costs
Eric Lantz et al.
APPLIED ENERGY (2016)
Long-term implications of sustained wind power growth in the United States: Potential benefits and secondary impacts
Ryan Wiser et al.
APPLIED ENERGY (2016)
Assessing different parameters estimation methods of Weibull distribution to compute wind power density
Kasra Mohammadi et al.
ENERGY CONVERSION AND MANAGEMENT (2016)
Global assessment of onshore wind power resources considering the distance to urban areas
Diego Silva Herran et al.
ENERGY POLICY (2016)
Do onshore and offshore wind farm development patterns differ?
Peter Enevoldsen et al.
ENERGY FOR SUSTAINABLE DEVELOPMENT (2016)
Energy Sprawl Is the Largest Driver of Land Use Change in United States
Anne M. Trainor et al.
PLOS ONE (2016)
The Wind Integration National Dataset (WIND) Toolkit
Caroline Draxl et al.
APPLIED ENERGY (2015)
Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods
Jie Zhang et al.
APPLIED ENERGY (2015)
Spatial convergent cross mapping to detect causal relationships from short time series
Adam Thomas Clark et al.
ECOLOGY (2015)
Incorporating Land-Use Requirements and Environmental Constraints in Low-Carbon Electricity Planning for California
Grace C. Wu et al.
ENVIRONMENTAL SCIENCE & TECHNOLOGY (2015)
Machine learning: Trends, perspectives, and prospects
M. I. Jordan et al.
SCIENCE (2015)
Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning
David M. Theobald et al.
PLOS ONE (2015)
A Review of Methodological Approaches for the Design and Optimization of Wind Farms
Jose F. Herbert-Acero et al.
ENERGIES (2014)
Land Cover and Topography Affect the Land Transformation Caused by Wind Facilities
Jay E. Diffendorfer et al.
PLOS ONE (2014)
Development and Applications of a Comprehensive Land Use Classification and Map for the US
David M. Theobald
PLOS ONE (2014)
Geographies of energy transition: Space, place and the low-carbon economy
Gavin Bridge et al.
ENERGY POLICY (2013)
Comparing the Ecological Impacts of Wind and Oil & Gas Development: A Landscape Scale Assessment
Nathan F. Jones et al.
PLOS ONE (2013)
Geophysical limits to global wind power
Kate Marvel et al.
NATURE CLIMATE CHANGE (2013)
Gradient boosting machines, a tutorial
Alexey Natekin et al.
FRONTIERS IN NEUROROBOTICS (2013)
Evaluation of Global Onshore Wind Energy Potential and Generation Costs
Yuyu Zhou et al.
ENVIRONMENTAL SCIENCE & TECHNOLOGY (2012)
GIS-based environmental assessment of wind energy systems for spatial planning: A case study from Western Turkey
Nazli Yonca Aydin et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2010)
Global potential for wind-generated electricity
Xi Lu et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2009)
A working guide to boosted regression trees
J. Elith et al.
JOURNAL OF ANIMAL ECOLOGY (2008)
Assessment of the global and regional geographical, technical and economic potential of onshore wind energy
M Hoogwijk et al.
ENERGY ECONOMICS (2004)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)