Implementation of species distribution models in Google Earth Engine

Google Earth Engine (GEE) is a free Web‐based spatial analysis platform that requires only a web browser and an Internet connection to programmatically access and analyse data from its multi‐petabyte catalog of regularly updated satellite imagery (e.g. MODIS, Landsat, Sentinel) and other geospatial datasets. The high computing capacity of GEE can make computationally demanding analyses more accessible to researchers and practitioners, especially those with limited access to advanced computational resources. Here, we present a workflow in GEE to fit species distribution models, offering direct access to a multi‐petabyte catalog of raster products to obtain estimates of habitat suitability.

• Publication year

  2022

• Venue

  Diversity and Distributions: A journal of biological invasions and biodiversity

• Publication date

  2022-02-11

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1111/ddi.13491
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling

  2021influential reference
• A standard protocol for reporting species distribution models

  2020cited by this paper
• Modelling species presence-only data with random forests

  2020cited by this paper
• rgee: An R package for interacting with Google Earth Engine

  2020cited by this paper
• Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

  2020cited by this paper
• The area under the precision‐recall curve as a performance metric for rare binary events

  2019cited by this paper
• Species distribution modelling to support forest management. A literature review

  2019cited by this paper
• Habitat metrics based on multi‐temporal Landsat imagery for mapping large mammal habitat

  2019cited by this paper
• Standards for distribution models in biodiversity assessments

  2019cited by this paper
• Ensemble species distribution modelling with transformed suitability values

  2018influential reference
• Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance

  2018influential reference
• blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

  2018cited by this paper
• Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

  2017cited by this paper
• First Experiences with Google Earth Engine

  2017influential reference
• Better together: Integrating and fusing multispectral and radar satellite imagery to inform biodiversity monitoring, ecological research and conservation science

  2017cited by this paper
• Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

  2017cited by this paper
• Habitat Suitability and Distribution Models: With Applications in R

  2017influential reference
• Google Earth Engine: Planetary-scale geospatial analysis for everyone

  2017influential reference
• Wallace: A flexible platform for reproducible modeling of species niches and distributions built for community expansion

  2017cited by this paper
• Opening the black box: an open-source release of Maxent

  2017cited by this paper
• From science to action: Principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making.

  2016cited by this paper
• High-resolution mapping of global surface water and its long-term changes

  2016cited by this paper
• On the selection of thresholds for predicting species occurrence with presence‐only data

  2015cited by this paper
• Point process models for presence‐only analysis

  2015cited by this paper
• New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

  2014influential reference
• Spatial filtering to reduce sampling bias can improve the performance of ecological niche models

  2014cited by this paper
• Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

  2014cited by this paper
• R: A language and environment for statistical computing.

  2014cited by this paper
• Modelling avian biodiversity using raw, unclassified satellite imagery

  2014cited by this paper
• Satellite remote sensing for applied ecologists: opportunities and challenges

  2014cited by this paper
• High-Resolution Global Maps of 21st-Century Forest Cover Change

  2013cited by this paper
• Achieving Conservation Science that Bridges the Knowledge–Action Boundary

  2013cited by this paper
• The problem of pattern and scale in ecology: what have we learned in 20 years?

  2013cited by this paper
• Novel Three-Step Pseudo-Absence Selection Technique for Improved Species Distribution Modelling

  2013cited by this paper
• Species distribution modelling for the people: unclassified landsat TM imagery predicts bird occurrence at fine resolutions

  2013cited by this paper
• Handbook of the mammals of the world : vol. 3 : primates

  2013influential reference
• Selecting pseudo‐absences for species distribution models: how, where and how many?

  2012cited by this paper
• Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling

  2012cited by this paper
• Integrating biodiversity distribution knowledge: toward a global map of life.

  2012cited by this paper
• Predictive species and habitat modeling in landscape ecology : concepts and applications

  2011influential reference
• Improving species distribution models for climate change studies: variable selection and scale

  2011cited by this paper
• Modeling Species Distribution and Change Using Random Forest

  2011influential reference
• New trends in species distribution modelling

  2010cited by this paper
• Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data.

  2009cited by this paper
• Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models

  2009cited by this paper
• BIOMOD – a platform for ensemble forecasting of species distributions

  2009cited by this paper
• Can remote sensing of land cover improve species distribution modelling?

  2008cited by this paper
• Effects of sample size on the performance of species distribution models

  2008cited by this paper
• Assessing the effects of pseudo-absences on predictive distribution model performance

  2008cited by this paper
• AUC: a misleading measure of the performance of predictive distribution models

  2008cited by this paper
• Can remote sensing of land cover improve species distribution modelling ?

  2008cited by this paper
• A working guide to boosted regression trees.

  2008cited by this paper
• Maximum entropy modeling of species geographic distributions

  2006cited by this paper
• Predicting species distribution: offering more than simple habitat models.

  2005cited by this paper
• Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.1276 VERY HIGH RESOLUTION INTERPOLATED CLIMATE SURFACES FOR GLOBAL LAND AREAS

  2005cited by this paper
• Presence-absence versus presence-only modelling methods for predicting bird habitat suitability

  2004cited by this paper
• Predictive habitat distribution models in ecology

  2000cited by this paper
• Shuttle Radar Topography Mission

  2000cited by this paper
• A review of methods for the assessment of prediction errors in conservation presence/absence models

  1997cited by this paper
• Effects of forest patch size on nesting success of wood thrushes

  1995cited by this paper

• Coupling Remote Sensing and Artificial Intelligence: Mapping Hydrological Variables with GEE and Predicting Surface-water Extent with Neural Networks

  2026cites this paper
• Validating habitat suitability assessments with post‐translocation animal movement data

  2025cites this paper
• Potential fence density in central and Western North America and implications for Bison (Bison bison) restoration

  2025cites this paper
• ViitGEE: an open-source tool for visual image interpretation and reference data collection in google earth engine

  2025cites this paper
• A generalized modeling framework for spatially extensive species abundance prediction and population estimation

  2025cites this paper
• Using Bi-Temporal Lidar to Evaluate Canopy Structure and Ecotone Influence on Landsat Vegetation Index Trends Within a Boreal Wetland Complex

  2025cites this paper
• Modeling the Wildlife–Livestock Interface of Cattle Fever Ticks in the Southern United States

  2025cites this paper
• Effectiveness of temporal matching in ecological niche models: Insights for a low‐dispersing species

  2025cites this paper
• Predicting Climate Change Impacts on Sub-Tropical Fruit Suitability Using MaxEnt: A Regional Study from Southern Türkiye

  2025cites this paper
• Striking yet destructive: The potential expansion of pompom weed (Campuloclinium macrocephalum (Less.) DC.)) in South Africa

  2025cites this paper
• Global range extension of bioclimatic zone of Bruguiera hainesii C.G.Rogers 1919 (Rhizophoraceae)

  2025cites this paper
• Systematic review and bibliometric analysis of innovative approaches to soil fertility assessment and mapping: trends and techniques

  2025cites this paper
• Choosing blocks for spatial cross-validation: lessons from a marine remote sensing case study

  2025cites this paper
• Advances in Landslide Detection through Google Earth Engine: A Comprehensive Review

  2025cites this paper
• Species distribution model performance improves when habitat characterizations are centered on detected individuals instead of observers

  2025cites this paper
• Rapid Declines in Southern Sierra Nevada Fisher Habitat Driven by Drought and Wildfire

  2025cites this paper
• An entire-process MaxEnt framework for habitat suitability modeling on Google Earth Engine: A case study of the oriental white stork in eastern mainland China.

  2025cites this paper
• Range-wide assessment of habitat suitability for jaguars using multiscale species distribution modelling

  2025cites this paper
• Dual niche modeling with GEE and SHAP for predicting habitat shifts of Haloxylon ammodendron and Cistanche deserticola under climate change

  2025cites this paper
• IDENTIFY SUITABLE AREAS FOR PEANUT CULTIVATION IN OSMANIYE PROVINCE THROUGH THE AHP METHOD

  2025cites this paper
• The Potential Geographic Distribution of Bactrocera minax and Bactrocera tsuneonis (Diptera: Tephritidae) in China

  2025cites this paper
• Human footprint and rainfall shape Masai giraffe's habitat suitability and connectivity in a multiple‐use landscape

  2024cites this paper
• GEE_xtract: High-quality remote sensing data preparation and extraction for multiple spatio-temporal ecological scaling

  2024cites this paper
• Mapping the potential distribution of Asian elephants: Implications for conservation and human-elephant conflict mitigation in South and Southeast Asia

  2024cites this paper
• Predicting the Potential Geographic Distribution of Invasive Freshwater Apple Snail Pomacea canaliculate (Lamarck, 1819) under Climate Change Based on Biomod2

  2024cites this paper
• Google Earth Engine: empowering developing countries with large-scale geospatial data analysis—a comprehensive review

  2024cites this paper
• SUITABLE HABITAT AREA ANALYSIS AND NICHE ASSESSMENT OF THE INVASIVE EMERALD ASH BORER (AGRILUS PLANIPENNIS) IN NATIVE AND INVASIVE RANGES

  2024cites this paper
• Predictive ecological niche model for Cinnamomumparthenoxylon (Jack) Meisn. (Lauraceae) from Last Glacial Maximum to future in Vietnam

  2024cites this paper
• Land-cover change in Cuba and implications for the area of distribution of a specialist’s host-plant

  2024cites this paper
• Modeling Habitat Suitability and Current Distribution of the Relicted Maghreb Magpie (Pica mauritanica)

  2024cites this paper
• Analysis of the distribution of Astragalus membranaceus var. mongholicus in Inner Mongolia under climate change using the GEE platform

  2024cites this paper
• Impact of Climate Change on Distribution of Suitable Niches for Black Locust (Robinia pseudoacacia L.) Plantation in China

  2024cites this paper
• Active remote sensing data and dispersal processes improve predictions for an invasive aquatic plant during a climatic extreme in Great Lakes coastal wetlands.

  2024cites this paper
• Advancing studies on global biocrust distribution

  2024cites this paper
• Functional group analyses of herpetofauna in South Korea using a large dataset

  2023cites this paper
• What is going on within google earth engine? A systematic review and meta-analysis

  2023cites this paper
• Generación de Superficies de Interpolación de la Variable Temperatura en la Provincia de Chimborazo en Periodo 2010- 2020

  2023cites this paper
• The Effects of Anthropogenic Disturbances on the Spatiotemporal Patterns of Medium–Large Mammals in Tropical Volcanic Landscapes

  2023influential citation
• Beyond protected areas: The importance of mixed‐use landscapes for the conservation of Sumatran elephants (Elephas maximus sumatranus)

  2023cites this paper
• Demographic collapse threatens the long-term persistence of Andean condors in the northern Andes

  2023cites this paper
• Combining species distribution models and moderate resolution satellite information to guide conservation programs for reticulated giraffe

  2023cites this paper
• Wildlife habitat association over a twelve-year period (2008-2020) in the Greater Mahale Ecosystem, western Tanzania

  2023cites this paper
• Google Earth Engine for archaeologists: An updated look at the progress and promise of remotely sensed big data

  2023cites this paper
• Machine learning approach to detect Land Use Land Cover (LULC) change in Chure region of Sarlahi district, Nepal

  2023cites this paper
• Ecological Niche Models using MaxEnt in Google Earth Engine: Evaluation, guidelines and recommendations

  2023cites this paper
• Machine learning-based prediction of sand and dust storm sources in arid Central Asia

  2023cites this paper
• Using habitat suitability models for multiscale forensic geolocation analysis

  2023cites this paper
• Identifying stable and overlapping habitats for a predator (common leopard) and prey species (Himalayan grey goral & Himalayan grey langur) in northern Pakistan

  2023cites this paper
• Conservation of rare and cryptic species: Challenges of uncertainty and opportunities for progress

  2022cites this paper
• Assessing multitemporal calibration for species distribution models

  2022cites this paper
• Google Earth Engine and machine learning for Earth monitoring

  2022cites this paper
• T OWARDS SCALABLE DEEP SPECIES DISTRIBUTION MODELLING USING GLOBAL REMOTE SENSING

  year unknowncites this paper