Breaking new ground in mapping human settlements from space – The Global Urban Footprint

Power-Law Distributions in Empirical Data

Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009) · SIAM Review · doi:10.1137/070710111 · Cited by 8,019

Global food demand and the sustainable intensification of agriculture

Tilman, D., Balzer, C., Hill, J., & Befort, B. L. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1116437108 · Cited by 7,692

Global Change and the Ecology of Cities

Grimm, N., Faeth, S., Golubiewski, N., Redman, C., Wu, J., Bai, X.-M., & Briggs, J. (2008) · Science · doi:10.1126/science.1150195 · Cited by 6,789

Power-law distributions in empirical data

Clauset, A. J., Shalizi, C. R., & Newman, M. E. J. (2018) · Figshare · doi:10.1184/r1/6586835.v1 · Cited by 6,710

World Urbanization Prospects: The 1996 Revision

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A Meta-Analysis of Global Urban Land Expansion

Seto, K. C., Fragkias, M., Güneralp, B., & Reilly, M. K. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023777 · Cited by 2,406

Global land cover mapping at 30 m resolution: A POK-based operational approach

Chen, J., Chen, J., Liao, A., Cao, X., Chen, L., Chen, X., He, C., Han, G., Shu, P., Lu, M., et al. (2014) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2014.09.002 · Cited by 2,120

World Urbanization Prospects: an alternative to the UN model of projection compatible with the mobility transition theory

Bocquier, P. (2005) · Demographic Research · doi:10.4054/demres.2005.12.9 · Cited by 1,746

TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry

Krieger, G., Moreira, A., Fiedler, H., Hajnsek, I., Werner, M. U., Younis, M., & Zink, M. (2007) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2007.900693 · Cited by 1,690

Human behavior and the principle of least effort.

indicated, N. A. (1949) · Journal of Consulting Psychology · doi:10.1037/h0052803 · Cited by 1,610

Polarimetric and Multitemporal Information Extracted from Sentinel-1 Sar Data to Map Buildings

Chini, M., Pelich, R., Hostache, R., Matgen, P., & López-Martínez, C. (2018) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2018.8518607 · Cited by 4

Leveraging ALOS-2 PALSAR-2 for Mapping Built-Up Areas and Assessing Their Vertical Component

Corbane, C., Kato, S., Iwao, K., Sabo, F., Politis, P., Pesaresi, M., & Kemper, T. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3036345 · Cited by 4

An urban ecology primer for Montevideo: Heat island in a Latin American social-ecological context

Orlando, L., & Berazategui, M. (2024) · Urban Climate · doi:10.1016/j.uclim.2024.102091 · Cited by 5

Assessment of the Impacts of Image Signal-to-Noise Ratios in Impervious Surface Mapping

Xian, G., Shi, H., Anderson, C., & Wu, Z. (2019) · Remote Sensing · doi:10.3390/rs11222603 · Cited by 4

Time series enable the characterization of small‐scale vegetation dynamics that influence fine‐scale animal behavior – an example from white storks' foraging behavior

Standfuß, I., Geiß, C., Nathan, R., Rotics, S., Scacco, M., Kerr, G., & Taubenböck, H. (2022) · Remote Sensing in Ecology and Conservation · doi:10.1002/rse2.251 · Cited by 4

Urban scale climate change adaptation through smart technologies

Bazazzadeh, H., Pourahmadi, B., Pilechiha, P., Safaei, S. S. H., & Berardi, U. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-85552-5.00011-7 · Cited by 4

How do disease control measures impact spatial predictions of schistosomiasis and hookworm? The example of predicting school-based prevalence before and after preventive chemotherapy in Ghana

Kulinkina, A. V., Farnham, A., Biritwum, N., Utzinger, J., & Walz, Y. (2023) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0011424 · Cited by 4

WORLD HERITAGE MAPPING IN A STANDARD-BASED STRUCTURED GEOGRAPHICAL INFORMATION SYSTEM

Valese, M., Noardo, F., & Roders, A. P. (2020) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xliii-b4-2020-81-2020 · Cited by 4

Identifying Urban Areas By Combining Data From The Ground And From Outer Space: An Application To India

Galdo, V., Li, Y., & Rama, M. (2018) · World Bank, Washington, DC eBooks · doi:10.1596/1813-9450-8628 · Cited by 4

Contemporary Remote Sensing Tools for Integrated Assessment and Conservation Planning of Ice-free AntarcticaPreprint

Patricio-Valerio, L., Shaw, J. D. S., González, F., Robinson, S. A., & Helmstedt, K. J. (2022) · doi:10.31223/x5ds7q · Cited by 3

A 1 km datasets for urban–suburban–rural–natural continuous gradient landscapes in Southwest China

Fang, J., Zhang, S., Deng, W. P., & Zhang, H. (2025) · Scientific Data · doi:10.1038/s41597-025-06266-0 · Cited by 4

Advancing hybrid spatial dynamic modeling for urban sustainable transitions

Zhang, H., & Cai, Z. (2026) · Discover Cities · doi:10.1007/s44327-026-00220-4 · Cited by 3

Les villes et le climat : Bâtiments et urbanisme

Viguié, V. (2020) · Comptes Rendus Géoscience · doi:10.5802/crgeos.19 · Cited by 3

Detecting and Analyzing the Increase of High-Rising Buildings to Monitor the Dynamic of the Xiong’an New Area

Li, L., Zhu, J., Gao, L., Cheng, G., & Zhang, B. (2020) · Sustainability · doi:10.3390/su12114355 · Cited by 3

Development of the information retrieval system to analyze the dynamics of the formation of settlements network

Lisetskii, F., Ilyashenko, S., & Buryak, Z. A. (2021) · InterCarto InterGIS · doi:10.35595/2414-9179-2021-4-27-202-217 · Cited by 3

Influence of the Mosaicking Algorithm on Sentinel-1 Land Cover Classification Over Rough Terrain

Borlaf-Mena, I., Badea, O. N., & Tanase, M. A. (2021) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss47720.2021.9553648 · Cited by 3

Mapping of urban landuse and landcover with multiple sensors : Joining close and remote sensing with deep learning

Srivastava, S. (2020) · doi:10.18174/509667 · Cited by 3

Building Risk‐Informed Communities

McClain, S. N., Kruczkiewicz, A., Ndugwa, R. P., Braneon, C. V., Bader, D., Bazo, J., & Owen, M. (2022) · Geophysical monograph · doi:10.1002/9781119536789.ch7 · Cited by 3

Climate Hazards in Latin American Cities:Understanding the Role of the Social and Built Environments and Barriers to Adaptation ActionPreprint

Slovic, A. D., Indvik, K., Martins, L. S., Kephart, J. L., Swanson, S., Quistberg, D. A., Moran, M. R., Bakhtsiyarava, M., Zavaleta-Cortijo, C., Gouveia, N., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4484848 · Cited by 3

GlobalBuildingMap — Unveiling the mystery of global buildings

Zhu, X. X., Li, Q., Shi, Y., Wang, Y., Stewart, A. J., Prexl, J., & Zhang, F. (2026) · Scientific Data · doi:10.1038/s41597-026-06578-9 · Cited by 12

A Review of Urban Building Extraction From Synthetic Aperture Radar Imagery Based on Deep Learning

Wu, F., Gong, L., Zhang, W., Wang, C., Zhang, H., & Wang, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3593955 · Cited by 2

Fine-Grained 3D Building Reconstruction and Floor Height Estimation from Ultra-High-Resolution TomoSAR Data Using Geometric Constraints

Chen, H., Liu, W., Chen, Q., Cui, L., & Xing, M. (2026) · Remote Sensing · doi:10.3390/rs18071073 · Cited by 2

Avaliação dos níveis de NO2 atmosféricos em corredores de transporte público

Quintanilha, W. F. L., Maia, M. L., Bertoncini, B. V., Ribeiro, J. P., Cassiano, D. R., Sousa, F. W., & do Nascimento, R. F. (2021) · Transportes · doi:10.14295/transportes.v29i4.2508 · Cited by 2

A Cross-Angle Propagation Network for Built-Up Area Extraction by Fusing Spatial–Spectral-Angular Features From the ZY-3 Multiview Satellite Imagery: Dataset and Analysis of China’s 41 Major Cities

Zuo, R., Huang, X., Li, J., & Pan, X. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3453868 · Cited by 2

Evaluating How Land-Use Changes Affect the Ecosystem Services Provided by Urban Parks and Green Spaces

Emmanuel, O., & Eraky, A. (2025) · Journal of parks · doi:10.3390/jop1010004 · Cited by 2

New Prospects in Analysing Big Data from Space - The Urban Thematic Exploitation Platform

Esch, T., Asamer, H., Bachofer, F., Balhar, J., Boettcher, M., Boissier, E., Hirner, A., Mathot, E., Marconcini, M., Metz-Marconcini, A., et al. (2018) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2018.8517493 · Cited by 2

Surface Heterogeneity-Involved Estimation of Sample Size for Accuracy Assessment of Land Cover Product from Satellite Imagery

Ren, H., Cai, G., & Du, M. (2019) · Sensors · doi:10.3390/s19204430 · Cited by 2

HIGH-RESOLUTION URBAN MAPPING BY FUSION OF SAR AND OPTICAL DATA

Petrushevsky, N., Manzoni, M., & Guarnieri, A. M. (2021) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xliii-b3-2021-273-2021 · Cited by 2

Modeling of population distribution in space and time to support disaster risk management

Freire, S. (2020) · doi:10.3990/1.9789036549998 · Cited by 2

Global Thematic Land Use Cover Datasets Characterizing Artificial Covers

García-Álvarez, D., Hinojosa, J. L., & Pérez, F. J. J. (2022) · Springer eBooks · doi:10.1007/978-3-030-90998-7_21 · Cited by 2

Earth observation data for assessing global urbanization-sustainability nexuses

Tian, Y. (2023) · doi:10.18174/629718 · Cited by 1

Detecting Inequalities from Earth Observation–Derived Global Societal Variables

Ehrlich, D., Pesaresi, M., Kemper, T., Schiavina, M., Freire, S., & Melchiorri, M. (2024) · Remote sensing and digital image processing · doi:10.1007/978-3-031-49183-2_3 · Cited by 1

Urbanization, Economic Development, and Environmental Quality: Insights from Urban Growth and NO2 Pollution in Megacities

Erbertseder, T., Gilardi, L., Esch, T., & Taubenböck, H. (2025) · Joint Urban Remote Sensing Event (JURSE) · doi:10.1109/jurse60372.2025.11076023 · Cited by 1

Urban Expansion, Climate Vulnerability, and Transportation Resilience: Insights for Sustainable Development

Arifai, A. M., & Arsyad, M. (2025) · Advance Sustainable Science Engineering and Technology · doi:10.26877/asset.v7i3.1495 · Cited by 1

Development and implementation of a passive surveillance system for Aedes albopictus in Emilia-Romagna, Italy

Blaha, M., Albieri, A., Angelini, P., Antolini, G., Bonannella, C., Laurini, F., Rosà, R., & Re, D. D. (2026) · Ecological Informatics · doi:10.1016/j.ecoinf.2026.103718 · Cited by 2

Multimodal Deep Learning Framework for Profiling Socio-Economic Indicators and Public Health Determinants in Urban Environments

Dufitimana, E., Bizimana, J. P., Uwayezu, E., Gahungu, P., & Mugisha, E. (2026) · Urban Science · doi:10.3390/urbansci10040177 · Cited by 3

How can technological innovation enable carbon reduction in energy systems from a multi-level perspective? evidence from chengdu-chongqing urban agglomeration in China

Chen, J., Zeng, Q., & Qin, G. (2026) · Energy · doi:10.1016/j.energy.2026.141104 · Cited by 1

Climate dynamics and air quality interactions: Machine learning analysis of diurnal temperature range drivers in three major Bangladesh cities

Rony, M. R. H., Guo, S., Rahman, M. Z., Lohani, S. P., Mang, H., Wen, W., & Cheng, S. (2026) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2026.148556 · Cited by 1

Influence of new residential construction varying in housing density on bird species, human tolerance guilds, and communities

DeLap, J. H., Marzluff, J. M., & Converse, S. J. (2026) · Scientific Reports · doi:10.1038/s41598-026-54885-3 · Cited by 1

Multi-spectral and multi-temporal settlement footprint-derived pixel-level analytical approach to the evolution of building morphology in the Haldia urban-industrial region, India

Das, B., & Prasad, J. V. D. (2026) · Evolving Earth · doi:10.1016/j.eve.2026.100146 · Cited by 1

New Enabling Technologies to Observe and Characterize Urban Environments with Big Data from Space - The Urban Thematic Exploitation Platform

Palacios‐Lopez, D., Marconcini, M., Zeidler, J., Balhar, J., Boettcher, M., Boissier, E., Mathot, E., Svatoň, V., & Esch, T. (2018) · elib (German Aerospace Center) · Cited by 1

Monitoring the evolution of drought conditions over Africa

Ebobenow, J., & Arreyndip, N. A. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/958/1/012004 · Cited by 1

Capella Space X-Band Synthetic Aperture Radar (Sar) Data Applied to Environmental and Humanitarian Use Cases in Earth Observation with A Focus on Urban Footprint Mapping

Mattingly, K., & De, S. (2022) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss46834.2022.9884439 · Cited by 1

Impact of Drive Days and No-DriveDays on Atmospheric Carbon Monoxide (CO) concentration

Relton, C., Mary, A. D. C., Rayappan, T., Mary, M. S., Mookkaiyaraj, R., & Ganesan, G. (2025) · Current World Environment · doi:10.12944/cwe.19.3.23 · Cited by 1

A randomized transformation for data processing on quantum computers

Zollner, J. M., & Werner, M. (2025) · Quantum Machine Intelligence · doi:10.1007/s42484-025-00250-y · Cited by 1

Urban Land Use Efficiency in the United States: Assessing UN 2030 Sustainable Development Goals

Ishrak, M. F., Mathews, A. J., Newberry, J. L., & Yu, W. (2026) · Geographies · doi:10.3390/geographies6010021 · Cited by 1

New Opportunities for Urban Land Governance by Exploiting Big Data from Earth Observation

Esch, T., Adam, F., Bachofer, F., Boudinaud, L., Hirner, A., Geßner, U., Knauer, K., Metz-Marconcini, A., Marconcini, M., Üreyen, S., et al. (2018) · elib (German Aerospace Center) · Cited by 1

Mapping impact of urbanization in Shahat-Cyrene (Libya) using a big SAR data approach of change detection with COSMO-SkyMed time series

Tapete, D., & Cigna, F. (2020) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/509/1/012056 · Cited by 1

Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm

Karalasingham, S., Deo, R. C., & Prasad, R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817772-3.00010-0 · Cited by 1

Estimating Time of Urbanization with Moderate-Resolution Sensors

Silván-Cárdenas, J. L., Tapia-McClung, R., Valdiviezo-N., J. C., & Salazar-Garibay, A. (2022) · The Professional Geographer · doi:10.1080/00330124.2022.2125882 · Cited by 1

Deciphering the many maps of the Xingu – an assessment of land cover classifications at multiple scalesPreprint

Kalácska, M., Arroyo‐Mora, J. P., Lucanus, O., de Sousa, L. M., Pereira, T. D. S., & Vieira, T. B. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.23.887588 · Cited by 1

Diffusion-driven demographics -- Turing model as a concept for the emergence of sedentismPreprint

Friesen, J., Hartig, J., Henn, K., & Pelz, P. F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.05107 · Cited by 1

Commentary: A Road Map for Future Data-Driven Urban Planning and Environmental Health ResearchPreprint

Dyer, G. M. C., Khomenko, S., Adlakha, D., Anenberg, S. C., Angelova, J., Behnisch, M., Boeing, G., Chen, X., Cirach, M., de Hoogh, K., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4837798 · Cited by 1

Exploiting Earth observation data pools for urban analysis: the TEP URBAN project

Boettcher, M., Brito, F., Metz, A., Zeidler, J., Asamer, H., Mathot, E., Balhar, J., Heldens, W., Esch, T., Marconcini, M., et al. (2017) · Remote Sensing Technologies and Applications in Urban Environments · doi:10.1117/12.2299947

On the use of Global Urban Footprint to the Polish settlement vector database development

Brzezińska, M. (2019) · Geodezja i Kartografia · doi:10.24425/gac.2019.128466

Observing Changes Due To Urbanization And Anthropogenic Activities Across The Middle East And North Africa Using Cosmo-Skymed Background Mission And Bespoke Spotlight Time Series

Tapete, D., & Cigna, F. (2020) · IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) · doi:10.1109/m2garss47143.2020.9105293

The Dark Side of the Earth: Benchmarking Lighting Access for All Cities on Earth and the CityNet dataset

Albert, A., Strano, E., Kaur, J., & González, M. C. (2021) · The urban book series · doi:10.1007/978-3-030-71945-6_2

GANmapper: geographical content filling.Preprint

Wu, A. N., & Biljecki, F. (2021) · arXiv (Cornell University)

Examining Urban Built‐up Volume

Mathews, A. J., & Nghiem, S. V. (2021) · doi:10.1002/9781119625865.ch2

Maps highlight urban-rural differences in achieving Sustainable Development GoalsPreprint

Tian, Y., Tsendbazar, N., Leeuwen, E. S. V., & Herold, M. (2022) · Research Square · doi:10.21203/rs.3.rs-1208399/v1

Comment on essd-2022-92

(2022) · Earth system science data · doi:10.5194/essd-2022-92-rc2

Comment on essd-2022-92

(2022) · Earth system science data · doi:10.5194/essd-2022-92-rc1

Editorial

Hawken, S. (2021) · Environment and Urbanization Asia · doi:10.1177/0975425321997972

Comment on essd-2022-92

(2022) · Earth system science data · doi:10.5194/essd-2022-92-rc3

Modeling the changes of Paddy field to Residential in Pringsewu District, Indonesia

Miswar, D., Suyatna, A., Zakaria, W. A., Wahono, E. P., Yarmaidi, & Ardiyanti, D. (2022) · Ecology Environment and Conservation · doi:10.53550/eec.2022.v28i01s.061

Reply on RC2

Demuzere, M. (2022) · Earth system science data · doi:10.5194/essd-2022-92-ac2

Reply on RC1

Demuzere, M. (2022) · Earth system science data · doi:10.5194/essd-2022-92-ac1

Reply on RC3

Demuzere, M. (2022) · Earth system science data · doi:10.5194/essd-2022-92-ac3

A remote sensing perspective: mapping the human footprint in the Zambezi region of Namibia.

Weaver, A. (2021) · doi:10.18297/etd/3777

Comment on essd-2022-296

(2022) · Earth system science data · doi:10.5194/essd-2022-296-rc1

Comment on essd-2022-296

(2022) · Earth system science data · doi:10.5194/essd-2022-296-rc2

Research on the Theoretical Framework, Spatio-temporal Laws, and Driving Mechanism of Beautiful Human Settlements—A Case Study of the 14 Prefecture-Level Cities in Liaoning Province

Tian, S., Jin, B., Li, H., Li, X., & Yang, J. (2023) · Sustainability · doi:10.3390/su15021165

Earth Observation and Deep Learning for Sustainable Development: New Approaches To Facilitate Data-Informed Decision-Making

Fibæk, C. S. (2022) · VBN Forskningsportal (Aalborg Universitet) · doi:10.54337/aau510571430 · Cited by 1

Reply on RC1

Lamarche, C. (2023) · Earth system science data · doi:10.5194/essd-2022-296-ac1

Reply on RC2

Lamarche, C. (2023) · Earth system science data · doi:10.5194/essd-2022-296-ac2

Advancing large-scale analysis of human settlements and their dynamics

Li, M. (2023) · doi:10.5463/thesis.9

Archaeological Sites in Small Towns—A Sustainability Assessment of Northumberland County

Vaz, E. (2023) · doi:10.32920/24171444.v1

COVID-19 in Toronto: A Spatial Exploratory Analysis

Vaz, E. (2023) · doi:10.32920/24171438.v1

COVID-19 in Toronto: A Spatial Exploratory Analysis

Vaz, E. (2023) · doi:10.32920/24171438

Archaeological Sites in Small Towns—A Sustainability Assessment of Northumberland County

Vaz, E. (2023) · doi:10.32920/24171444

Cities and climate change: buildings and urban land use

Viguié, V. (2023) · Comptes Rendus Géoscience · doi:10.5802/crgeos.19-en

Benefits of Global Earth Observation Missions for Exposure Estimation and Earthquake Loss Modelling – Evidence from Santiago de Chile, ChilePreprint

Geiß, C., Priesmeier, P., Pelizari, P. A., Calderon, A. R. S., Schöepfer, E., Riedlinger, T., Vilar-Vega, M., María, H. S., Zapata, J. C. G., Pittore, M., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1475054/v1

Deep Transfer Model Based Local Climate Zone Classification Using SAR/Multispectral Images

Nawaz, A., Chen, J., & Yang, W. (2024) · International Conference on Computer Communication and Artificial Intelligence (CCAI) · doi:10.1109/ccai61966.2024.10603177

Probabilistic Fusion Framework Combining CNNs and Graphical Models for Multiresolution Satellite and UAV Image Classification

Pastorino, M., Moser, G., Guerra, F., Serpico, S. B., & Zerubia, J. B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78166-7_19

Sustainable Urban Green Spaces

Emmanuel, O., & Nukpezah, J. A. (2025) · Springer eBooks · doi:10.1007/978-3-319-31816-5_4478-1 · Cited by 1

Measuring urbanity: The role of proximity in urban places

Wolf, L. J., & Fox, S. (2025) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/23998083251334787

Flood Impact Assessment Maps - Chimanimani and Chipinge Districts, Zimbabwe

Intergovernmental Hydrological Programme (2025) · Dataset · doi:10.63253/u04ymlja

Additional file 6 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795188

Additional file 2 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795173

Additional file 1 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795170

Additional file 1 of Urban bat pups take after their mothers and are bolder and faster learners than rural pups

Harten, L. M., Gonceer, N., Handel, M., Dash, O., Fokidis, H. B., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.16584404

Additional file 3 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795176

Additional file 4 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795182

Additional file 1 of Modelling spatiotemporal trends in the frequency of genetic mutations conferring insecticide target-site resistance in African mosquito malaria vector species

Hancock, P. A., Lynd, A., Wiebe, A., Devine, M., Essandoh, J., Wat’senga, F., Manzambi, E. Z., Agossa, F. R., Donnelly, M. J., Weetman, D., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19173430

Additional file 7 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795191

Additional file 5 of Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Egert-Berg, K., Handel, M., Goldshtein, A., Eitan, O., Borissov, I. M., & Yovel, Y. (2021) · Figshare · doi:10.6084/m9.figshare.14795185

Land Cover Change Detection in Israel’s Dan Metropolis: Implications for Peri-Urban Ecohydrology and Climate ChangePreprint

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