Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning

Nehir Uyar; Azize Uyar

doi:10.51489/tuzal.1909286

Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning

Abstract

Forests play a vital role in carbon sequestration, biodiversity conservation, and climate regulation. However, changing environmental conditions, including variations in precipitation, temperature, and soil properties, significantly impact tree physiology and forest dynamics. This study aims to evaluate the potential of machine learning models in predicting canopy height, a key indicator of forest structure, using remote sensing data. Four models Random Forest, Support Vector Machine, and Gradient Boosting Trees (GBT) were tested under multiple scenarios incorporating Sentinel-2, Landsat 8, and Landsat 9 imagery. Predictor variables included Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), precipitation, land surface temperature (LST), soil moisture, population density, elevation, slope, aspect, albedo, and CO concentration. The study area, located south of Shaver Lake in Fresno, California, represents a dynamic forest ecosystem vulnerable to climatic variability. Results indicate that RF and GBT models achieved the highest predictive accuracy (R² = 0.66 and 0.63, respectively) with Sentinel-2 data, while CART and SVM performed less effectively, especially with Landsat 9 data. These findings emphasize the importance of selecting appropriate remote sensing datasets for tree physiology assessments. Future research should explore multi-source data fusion and advanced hybrid modeling approaches to improve forest monitoring and sustainable management.

Keywords

References

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Details

Primary Language

English

Subjects

Photogrammetry and Remote Sensing, Remote Sensing

Journal Section

Research Article

Authors

Nehir Uyar ^*
0000-0003-3358-3145
Türkiye

Azize Uyar
0000-0003-2625-3690
Türkiye

Publication Date

July 3, 2026

Submission Date

March 26, 2026

Acceptance Date

May 25, 2026

Published in Issue

Year 2026 Volume: 8

DOI

https://doi.org/10.51489/tuzal.1909286

IZ

https://izlik.org/JA58CY75PB

Cite

RIS / Bibtex

APA

Uyar, N., & Uyar, A. (2026). Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning. Turkish Journal of Remote Sensing, 8. https://doi.org/10.51489/tuzal.1909286

AMA

1.Uyar N, Uyar A. Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning. TJRS. 2026;8. doi:10.51489/tuzal.1909286

Chicago

Uyar, Nehir, and Azize Uyar. 2026. “Linking Climate Variability to Forest Canopy Structure Using Multi-Sensor Remote Sensing and Machine Learning”. Turkish Journal of Remote Sensing 8 (July). https://doi.org/10.51489/tuzal.1909286.

EndNote

Uyar N, Uyar A (July 1, 2026) Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning. Turkish Journal of Remote Sensing 8

IEEE

[1]N. Uyar and A. Uyar, “Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning”, TJRS, vol. 8, July 2026, doi: 10.51489/tuzal.1909286.

ISNAD

Uyar, Nehir - Uyar, Azize. “Linking Climate Variability to Forest Canopy Structure Using Multi-Sensor Remote Sensing and Machine Learning”. Turkish Journal of Remote Sensing 8 (July 1, 2026). https://doi.org/10.51489/tuzal.1909286.

JAMA

1.Uyar N, Uyar A. Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning. TJRS. 2026;8. doi:10.51489/tuzal.1909286.

MLA

Uyar, Nehir, and Azize Uyar. “Linking Climate Variability to Forest Canopy Structure Using Multi-Sensor Remote Sensing and Machine Learning”. Turkish Journal of Remote Sensing, vol. 8, July 2026, doi:10.51489/tuzal.1909286.

Vancouver

1.Nehir Uyar, Azize Uyar. Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning. TJRS. 2026 Jul. 1;8. doi:10.51489/tuzal.1909286

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Editors are committed to maintaining the confidentiality of all submitted materials. Manuscripts, reviewer reports, and all related communication are treated as confidential documents and are shared only with individuals directly involved in the editorial and peer review process.
Editors must ensure the confidentiality of all submitted manuscripts and must not upload manuscript content to AI tools or platforms. All editorial decisions must be based solely on human judgment.
The editorial team ensures that the peer review process is conducted objectively and without bias. In cases where conflicts of interest arise, appropriate measures are taken, including reassignment of editorial responsibility.
Editors are also responsible for overseeing ethical compliance throughout the publication process. In cases of suspected misconduct such as plagiarism, data fabrication, falsification, duplicate publication, or inappropriate authorship editors follow the guidelines and flowcharts provided by COPE. Depending on the nature and severity of the issue, the editorial office may request clarification from authors, suspend the review process, reject the manuscript, or initiate post-publication actions such as corrections or retractions.
The Editor-in-Chief holds the final authority in all editorial decisions and ensures that the journal’s policies are implemented consistently and transparently.

2. Responsibilities of Authors

Authors submitting manuscripts to the Turkish Journal of Remote Sensing (TJRS) are expected to adhere to the highest standards of academic integrity and ethical research practices.
Authors must ensure that their submissions are original and have not been published previously or submitted to another journal simultaneously. All sources, including data, figures, and previously published work, must be properly cited. Any form of plagiarism, including self-plagiarism, is strictly prohibited.
The research presented in the manuscript must be reported accurately, clearly, and transparently. Authors are responsible for ensuring that the methods, data, analyses, and results are presented in a way that allows verification and reproducibility. Fabrication, falsification, or selective reporting of data is considered a serious ethical violation.
Authors must disclose any financial, institutional, or personal relationships that could be perceived as influencing the results or interpretation of their work. If no conflict of interest exists, this must be explicitly stated.
For studies involving human participants or animals, authors are required to obtain approval from relevant ethics committees and to comply with international ethical standards, including the Declaration of Helsinki. Information regarding ethical approval (committee name, approval number, and date) must be clearly stated in the manuscript.
Authors are expected to follow best practices in data management. When requested, authors should provide access to raw data, supplementary materials, or methodological details necessary for verification of the study.
During the peer review process, authors must respond to reviewer and editor comments in a timely, respectful, and scientifically justified manner. All revisions should be clearly explained and documented.
If authors identify a significant error or ethical issue in their published work, they are obligated to inform the editorial office promptly and cooperate in the correction or retraction process.

3. Authorship Criteria and Changes Policy

Authorship in the Turkish Journal of Remote Sensing (TJRS) is limited to individuals who have made a substantial intellectual contribution to the research and the preparation of the manuscript.
To qualify as an author, each contributor should have participated in at least one or more of the following stages: the conception or design of the study, data collection, data analysis and interpretation, drafting the manuscript, or critically revising it for important intellectual content. All authors must approve the final version of the manuscript and agree to its submission and publication.
Individuals who have contributed to the study but do not meet the criteria for authorship such as technical support, data collection assistance, or general supervision should be acknowledged appropriately in the acknowledgements section.
Unethical authorship practices, including guest (gift) authorship, ghost authorship, or inappropriate changes in the order of authors, are strictly prohibited. All authors share collective responsibility for the accuracy, integrity, and originality of the work.
In cases of authorship disputes, the editorial office may request detailed explanations and supporting documentation. If necessary, the matter may be referred to the relevant institutions in accordance with international ethical guidelines.

Changes in Authorship

Authors are strongly encouraged to carefully determine the authorship and the order of authors prior to submission and to provide the final and complete author list at the time of initial submission.
Any request for the addition, removal, or rearrangement of author names should be made before the manuscript is accepted and will only be considered with the approval of the Editorial Office.
To request a change in authorship, the corresponding author must submit:
(a) a clear justification explaining the reason for the requested change, and
(b) written confirmation (e.g., e-mail or signed letter) from all listed authors indicating their agreement with the proposed modification.
In cases involving the addition or removal of an author, confirmation must also be obtained from the author being added or removed.
The journal reserves the right to decline authorship changes that do not comply with these requirements.

4. Responsibilities of Reviewers

Reviewers play a fundamental role in ensuring the scientific quality, integrity, and credibility of the Turkish Journal of Remote Sensing (TJRS). They are expected to contribute to the peer review process in an objective, constructive, and timely manner.
Reviewers should accept review invitations only if the manuscript falls within their area of expertise and if they can complete the evaluation within the specified time frame. If a reviewer identifies a potential conflict of interest such as personal, professional, or financial relationships with the authors they must decline the review and inform the editorial office.
All manuscripts under review must be treated as strictly confidential documents. Reviewers must not share, distribute, or use any part of the manuscript for personal advantage or research purposes prior to publication.
Reviewers must treat all manuscripts as confidential and must not upload manuscript content to AI tools or platforms. Peer review reports must be based solely on the reviewer’s own expertise and independent judgment. (see the journal's AI use and authorship policy).
Reviewer reports should be based on scientific reasoning and should provide clear, constructive, and evidence-based feedback aimed at improving the quality of the manuscript. Personal criticism or inappropriate language directed at the authors is not acceptable.
Reviewers are also expected to identify relevant published work that has not been cited by the authors and to alert the editorial office to any substantial similarity, potential plagiarism, data inconsistency, or ethical concerns they detect during the evaluation process.
The review process should be conducted independently and ethically, without any attempt to influence the editorial decision inappropriately.

5. Peer Review Process

The Turkish Journal of Remote Sensing (TJRS) implements a double-blind peer review system to ensure the objectivity, fairness, and scientific quality of all published manuscripts.
In this system, the identities of both authors and reviewers are concealed throughout the evaluation process in order to eliminate potential bias and ensure impartial assessment. Manuscripts that successfully pass the editorial preliminary evaluation are assigned to at least two independent reviewers who are experts in the relevant field.
Reviewers evaluate manuscripts based on criteria such as originality, scientific contribution, methodological rigor, clarity of presentation, and relevance to the scope of the journal. Based on the reviewers’ reports, manuscripts may be accepted, rejected, or returned to the authors for minor or major revisions.
In cases where reviewer opinions differ significantly, the editor may, when deemed necessary, assign an additional reviewer to ensure a balanced and fair evaluation. The final decision is made by the Editor-in-Chief, taking into account the reviewers' reports and the manuscript's overall scientific merit.
All stages of the peer review process are conducted in accordance with international ethical standards, ensuring confidentiality, transparency, and accountability.
For a detailed description of all stages of the evaluation workflow, please refer to the journal’s “Review Process” page.

6. Evaluation Process (Editorial Screening)

All manuscripts submitted to TJRS undergo an initial editorial screening prior to the peer review process. This preliminary evaluation is conducted to ensure that submissions meet the journal’s basic requirements and are suitable for further review.
During this stage, manuscripts are assessed in terms of their compliance with the journal’s aims and scope, scientific relevance, originality, and adherence to submission and formatting guidelines. In addition, key elements such as anonymization, ethical declarations, conflict of interest statements, and required documentation (e.g., ethics committee approval, copyright forms) are checked.
The editorial office may also conduct an initial similarity screening using plagiarism detection tools at this stage. Manuscripts that do not meet the journal’s standards or fail to comply with ethical and technical requirements may be returned to the authors for correction or rejected without being sent for peer review.
Only manuscripts that successfully pass this preliminary evaluation are forwarded to the double-blind peer review process.

7. Plagiarism and Similarity Policy

All manuscripts submitted to the Turkish Journal of Remote Sensing (TJRS) are screened using recognized plagiarism detection software such as Turnitin, intihal.net and/or iThenticate prior to peer review.
The journal adopts a maximum similarity threshold of 25%, excluding references, methodological standard expressions, and properly cited quotations. However, the editorial office evaluates not only the similarity percentage but also the context, source, and nature of the overlap.
Manuscripts found to contain plagiarism, excessive similarity, improper citation, or text recycling may be returned to the authors for revision or rejected outright. The final decision regarding similarity evaluation rests with the editorial office.

8. Research Misconduct and Ethical Violations

TJRS strictly prohibits all forms of scientific misconduct and unethical practices. These include, but are not limited to:

Plagiarism
Data fabrication (making up data)
Data falsification (manipulating research data or results)
Duplicate or redundant publication
Salami slicing (inappropriate division of research findings)
Unethical authorship practices
Peer review manipulation

In cases of suspected misconduct, the editorial office follows internationally accepted procedures and the guidelines provided by COPE. Depending on the severity of the issue, the journal may request clarification, reject the manuscript, notify relevant institutions, or initiate correction or retraction procedures after publication.

9. Conflict of Interest Policy

All authors, reviewers, and editors are required to disclose any financial, institutional, or personal relationships that could influence the research or its evaluation process.
Conflicts of interest may include funding sources, consultancy roles, employment relationships, personal connections, or any situation that may compromise objectivity.
If no conflict of interest exists, this must be explicitly stated in the manuscript.
Failure to disclose a conflict of interest may result in rejection of the manuscript or post-publication actions such as correction or retraction.

10. Data Transparency and Verification

TJRS supports scientific transparency and encourages authors to make their research data, code, and supporting materials publicly available whenever possible to foster open science.
While public data sharing is encouraged, authors must be prepared to provide access to the raw data and methodological details if requested by the editorial office for verification purposes during the peer-review process.
If data sharing is not possible due to ethical, legal, or confidentiality constraints, authors must clearly state these reasons in the "Data Availability" section of their manuscript.
Authors should select the most appropriate statement based on their data accessibility. Examples include:

>> “The data presented in this study are available on request from the corresponding author.”

>> “The data associated with this study are not publicly available due to privacy, institutional, or technical restrictions.”

>> “The data presented in this study are available in [Name of Repository] at [URL/DOI].”

11. Ethical Compliance, Legal Requirements and Human/Animal Research Ethics

The Turkish Journal of Remote Sensing (TJRS) requires that all submitted studies comply with applicable ethical standards, legal regulations, and internationally accepted research ethics principles.
For studies involving human participants or animals, authors must obtain approval from a relevant ethics committee prior to data collection. The name of the ethics committee, approval date, and approval number must be clearly stated in the manuscript. In studies involving human participants, informed consent must be obtained, and participants’ rights, privacy, and dignity must be protected. For animal studies, internationally accepted standards of humane treatment must be followed.
Manuscripts that require ethics committee approval but fail to provide the necessary documentation will not be considered for evaluation. In cases where ethical approval is not required, authors must provide a clear justification. Detailed requirements are provided on the journal’s Ethics Committee Approval page.
TJRS places great importance on the protection of personal data and confidentiality. Authors must ensure that personal data used in research are processed in accordance with applicable data protection regulations and ethical standards. Identifiable personal information must not be disclosed without explicit consent, and confidentiality must be maintained throughout the research and publication process.
The journal also respects intellectual property rights and expects authors to comply with copyright regulations. Authors are responsible for obtaining all necessary permissions for the use of third-party materials, including figures, tables, images, datasets, and scales. Any legal or ethical responsibility arising from copyright violations belongs solely to the authors.

12. Policy on the Use of Artificial Intelligence

TJRS regulates the use of artificial intelligence tools in accordance with international ethical standards. Artificial intelligence tools cannot be listed as authors and may only be used for limited and transparent purposes such as language editing or technical assistance. Authors are required to disclose the use of AI tools and remain fully responsible for all content generated or modified with their assistance. Detailed guidelines are provided in the journal’s Artificial Intelligence Policy.

13. Correction, Retraction, and Post-Publication Policy

The Turkish Journal of Remote Sensing (TJRS) is committed to preserving the accuracy, integrity, and reliability of the scientific record. In cases where errors, ethical concerns, or potential misconduct are identified after publication, the journal takes appropriate actions in accordance with international publication ethics standards and the guidelines of the Committee on Publication Ethics (COPE).
If minor errors that do not affect the overall conclusions of the study are identified, a correction (erratum or corrigendum) may be issued and linked to the original article.
In cases involving serious ethical violations or significant errors that invalidate the findings, the journal may initiate a retraction process. Retracted articles remain accessible in the journal archive but are clearly marked to ensure transparency and maintain the integrity of the scholarly record.
When necessary, the journal may also publish an expression of concern while an investigation is ongoing.
Authors are expected to inform the editorial office promptly if they identify errors or ethical issues in their published work. Requests for correction or retraction may also be submitted by authors, reviewers, or readers.
Detailed procedures regarding article retraction and withdrawal are available on the journal’s dedicated Correction, Retraction and Withdrawal Policy page.

14. Open Access Policy

The Turkish Journal of Remote Sensing (TJRS) adopts a fully open access publishing model, ensuring that all published content is freely available to readers without any subscription fees or access barriers.
The journal supports the principles of the Budapest Open Access Initiative (BOAI) and promotes the unrestricted dissemination of scientific knowledge. All articles published in TJRS can be accessed, read, downloaded, and shared without limitation, provided that appropriate attribution is given.
Detailed information regarding the journal’s open access practices is available on the Open Access Policy page.

15. Copyright and Licensing Policy

The Turkish Journal of Remote Sensing (TJRS) respects the intellectual property rights of authors while supporting the wide dissemination of scientific knowledge.
Authors retain the copyright of their work and grant the journal the right of first publication. All published content is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license, which permits sharing, distribution, adaptation, and reuse of the material for any purpose, including commercial use, provided that appropriate credit is given and derivative works are distributed under the same license.
Authors are responsible for the originality of their work and for obtaining all necessary permissions for the use of third-party materials.
Further details regarding open access, copyright, licensing, and author agreements are provided on the Licenses and Copyright Policy pages.

16. Publication Fee Policy

The Turkish Journal of Remote Sensing (TJRS) does not charge any fees for manuscript submission, evaluation, or publication processes.
There are no article processing charges (APCs), submission fees, or publication fees at any stage of the editorial and publication process.
All accepted articles are published free of charge as part of the journal’s commitment to supporting open and accessible scientific communication.

17. Publication Period of Journal

Turkish Journal of Remote Sensing is a peer-reviewed journal published under a continuous publication model. Articles are published online individually upon acceptance and completion of the production process, without waiting for a scheduled issue, and are assigned to an annual volume.

18. Revenue, Advertising, and Direct Marketing Policy

The Turkish Journal of Remote Sensing (TJRS) is an independent, open-access, peer-reviewed journal. The journal does not charge any fees for submission, evaluation, or publication and does not generate revenue from authors or readers.
TJRS does not accept advertisements, and all editorial decisions are made independently based solely on academic merit.
The journal does not engage in misleading or aggressive direct marketing practices and ensures that all communications are conducted ethically and transparently.

19. Complaints and Appeals Policy

The Turkish Journal of Remote Sensing (TJRS) provides a transparent and fair mechanism for handling complaints and appeals related to editorial decisions, peer review processes, and ethical concerns.
Authors, reviewers, and readers may submit complaints or appeals regarding issues such as editorial decisions, delays in the review process, ethical concerns, or conflicts of interest.
All complaints and appeals must be submitted in writing to the Editorial Office via the journal’s official email address (tr.remotesensing@gmail.com) or directed to the Editor-in-Chief. Submissions must be supported by a clear justification and relevant evidence.
All complaints and appeals are evaluated objectively by the editorial office in accordance with international publication ethics standards and COPE guidelines. When necessary, the editorial board may seek additional opinions from reviewers, editorial board members, or relevant institutions.
The journal is committed to ensuring that all complaints and appeals are handled in a fair, transparent, and timely manner.

Editor-in-Chief

Osman ORHAN

Climate Change-Impact and Adaptation, Geospatial Information Systems and Geospatial Data Modelling, Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning, Geological Sciences and Engineering, Geographic Information Systems, Remote Sensing

Co-Editors

Ahmet Tarık TORUN

Engineering, Geospatial Information Systems and Geospatial Data Modelling, Photogrametry, Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning, Geological Sciences and Engineering, Remote Sensing

RÇ

Resul ÇÖMERT

Photogrammetry and Remote Sensing

Mustafa ÜSTÜNER

Pattern Recognition, Photogrammetry and Remote Sensing, Remote Sensing

Editorial Board

Kaan KALKAN

Geomatic Engineering, Geospatial Information Systems and Geospatial Data Modelling, Photogrametry, Photogrammetry and Remote Sensing, Geographic Information Systems, Remote Sensing

Mehmet Ali DERELI

Geographical Information Systems (GIS) in Planning, Remote Sensing

Saygın ABDIKAN

Photogrammetry and Remote Sensing

BJ

Ben JARIHANI

Remote Sensing , Earth System Sciences

FC

Fabiana CALO

Photogrammetry and Remote Sensing, Natural Hazards

Aliihsan ŞEKERTEKIN

Geomatic Engineering, Photogrammetry and Remote Sensing

Muammer TÜN

Geographic Information Systems, Natural Hazards, Applied Geophysics

Alper ÇABUK

Ecology, Sustainability and Energy, Information Technologies in Architecture and Design, Design Instruments and Technology, Protection, Restoration and Repair in Buildings, Environment, Habitation and Products

NM

Nebiye MUSAOĞLU

Image Processing, Engineering, Photogrammetry and Remote Sensing

DA

Djamil AL-HALBOUNI

Photogrammetry and Remote Sensing, Numerical Modelling and Mechanical Characterisation, Remote Sensing , Earth System Sciences, Groundwater Hydrology, Electrical and Electromagnetic Methods in Geophysics, Applied Geophysics, Computational Modelling and Simulation in Earth Sciences

MH

Mahmud HAGHSHENAS HAGHIGHI

Remote Sensing , Earth and Space Science Informatics

GP

Giuseppe PULIGHE

Remote Sensing , Sustainable Agricultural Development, Agricultural Spatial Analysis and Modelling

YM

Yasser MAGHSOUDI

Remote Sensing , Earth and Space Science Informatics

Taşkın KAVZOĞLU

Neural Networks, Semi- and Unsupervised Learning, Machine Learning Algorithms, Extreme Learning Machines, Classification Algorithms, Remote Sensing

Sadra KARIMZADEH

Remote Sensing

Siti Aekbal SALLEH

Geospatial Information Systems and Geospatial Data Modelling, Geographical Information Systems (GIS) in Planning

DS

Dursun Zafer SEKER

Image Processing, Artificial Intelligence, Photogrametry, Geographical Information Systems (GIS) in Planning, Remote Sensing , Geoscience Data Visualisation, Geoinformatics (Other)

Aşır Yüksel KAYA

City in Human Geography, Environmental Geography, Environmental Impact Assessment, Turkish Human Geography, Urbanization Policies, Urban Geography in Regional Planning, Urban Morphology, Urban History, Geographical Information Systems (GIS) in Planning

OG

Omid GHORBANZADEH

Artificial Intelligence (Other), Geographic Information Systems, Remote Sensing

JC

João Pedro Leal Abalada De Matos CARVALHO

Electrical Engineering (Other), Photogrammetry and Remote Sensing

Müge ÜNAL

Climate Change Impacts and Adaptation (Other), Land Use and Environmental Planning, Landscape Planning

Senem TEKIN

Earthquake Engineering, Geological Sciences and Engineering, Applied Geology

Artur JANOWSKI

Computer Vision, Remote Sensing

Khalil VALIZADEH KAMRAN

Information Security Management, Geographical Information Systems (GIS) in Planning, Geographic Information Systems

MU

Murat UYSAL

Virtual and Mixed Reality, Geomatic Engineering, Photogrametry, Remote Sensing

Uğur AVDAN

Geomatic Engineering, Photogrametry, Geographical Information Systems (GIS) in Planning, Remote Sensing

EH

Emre HAVAZLI

Photogrammetry and Remote Sensing, Geodesy

Ahmet MERT

Wildlife and Habitat Management, Cartography and Digital Mapping, Forestry Sciences, Forest Biodiversity

Advisory Board

Caner ÖZDEMIR

Electrical Engineering, Engineering Electromagnetics, Signal Processing

YL

Yaohui LIU

Ecology (Other), Photogrammetry and Remote Sensing, Natural Hazards, Remote Sensing

SE

Semih EKERCIN

Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning

FY

Ferruh YILDIZ

Land Management, Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning

Fevzi KARSLI

Photogrametry, Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning

Cüneyt GÜLER

Photogrammetry and Remote Sensing, Hydrogeology, Geographic Information Systems, Watershed Management, Contaminant Hydrology, Surface Water Hydrology

Language Editor

ÖÖ

Özge ÖZGÜN

British and Irish Language, Literature and Culture

Layout Editor

Mehmet Özgür ÇELIK

Groundwater Quality Processes and Contaminated Land Assessment, Geomatic Engineering, Land Management, Geospatial Information Systems and Geospatial Data Modelling, Geographical Information Systems (GIS) in Planning, Groundwater Hydrology, Climate Change Processes, Sustainable Agricultural Development

Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning

Linking climate variability to forest canopy structure using multi-sensor remote sensing and machine learning

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