Related references
Note: Only part of the references are listed.Validating two geospatial models of continental-scale environmental sound levels
Katrina Pedersen et al.
JASA EXPRESS LETTERS (2021)
Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models
Zhilu Chang et al.
REMOTE SENSING (2020)
Unsupervised learning approach in defining the similarity of catchments: Hydrological response unit based k-means clustering, a demonstration on Western Black Sea Region of Turkey
Ersin Aytac
INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH (2020)
Combining visual and noise characteristics of a neighborhood environment to model residential satisfaction: An application using GIS-based metrics
Samy Youssoufi et al.
LANDSCAPE AND URBAN PLANNING (2020)
Unsupervised K-Means Clustering Algorithm
Kristina P. Sinaga et al.
IEEE ACCESS (2020)
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Liang Han et al.
PLANT METHODS (2019)
Application of land-use regression models to estimate sound pressure levels and frequency components of road traffic noise in Taichung, Taiwan
Ta-Yuan Chang et al.
ENVIRONMENT INTERNATIONAL (2019)
Anthropogenic noise in US national parks - sources and spatial extent
Rachel T. Buxton et al.
FRONTIERS IN ECOLOGY AND THE ENVIRONMENT (2019)
GIS-based Analysis of Temporal Evolution of Rural Landscape: A Case Study in Southern Italy
Dina Statuto et al.
NATURAL RESOURCES RESEARCH (2019)
Estimating the Optimal Number of Clusters k in a Dataset Using Data Depth
Channamma Patil et al.
DATA SCIENCE AND ENGINEERING (2019)
Modeling anthropogenic noise propagation using the Sound Mapping Tools ArcGIS toolbox
Alexander C. Keyel et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2017)
Influential factors and spatiotemporal patterns of environmental sound levels in the contiguous United States
Daniel J. Mennitt et al.
NOISE CONTROL ENGINEERING JOURNAL (2016)
The Energy Footprint: How Oil, Natural Gas, and Wind Energy Affect Land for Biodiversity and the Flow of Ecosystem Services
Nathan F. Jones et al.
BIOSCIENCE (2015)
Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities
Inmaculada Aguilera et al.
JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY (2015)
Clustering of mineral prospectivity area as an unsupervised classification approach to explore copper deposit
Maysam Abedi et al.
ARABIAN JOURNAL OF GEOSCIENCES (2013)
Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area
George Grekousis et al.
CITIES (2013)
How and why environmental noise impacts animals: an integrative, mechanistic review
Caitlin R. Kight et al.
ECOLOGY LETTERS (2011)
Mapping Urban Environmental Noise: A Land Use Regression Method
Dan Xie et al.
ENVIRONMENTAL SCIENCE & TECHNOLOGY (2011)
Comparison of methods for land-use classification incorporating remote sensing and GIS inputs
Offer Rozenstein et al.
APPLIED GEOGRAPHY (2011)
Real Noise from the Urban Environment How Ambient Community Noise Affects Health and What Can Be Done About It
Anne Vernez Moudon
AMERICAN JOURNAL OF PREVENTIVE MEDICINE (2009)
Noise Pollution Changes Avian Communities and Species Interactions
Clinton D. Francis et al.
CURRENT BIOLOGY (2009)
Phylogenetic and ecological determinants of the neotropical dawn chorus
KS Berg et al.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES (2006)
Remote sensing and GIS in modeling visual landscape change: a case study of the northwestern and coast of Egypt
YA Ayad
LANDSCAPE AND URBAN PLANNING (2005)
Survey of clustering algorithms
R Xu et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2005)
Anthropogenic sounds differentially affect amphibian call rate
JWC Sun et al.
BIOLOGICAL CONSERVATION (2005)
Cicada acoustic communication: potential sound partitioning in a multispecies community from Mexico (Hemiptera : Cicadomorpha : Cicadidae)
J Sueur
BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY (2002)
Identifying brown bear habitat by a combined GIS and machine learning method
A Kobler et al.
ECOLOGICAL MODELLING (2000)
Share Paper
