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The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape

Yıl 2025, Cilt: 8 Sayı: 1, 188 - 200, 31.12.2025

Öz

Unmanned Aerial Vehicles (UAVs) are transforming both landscape planning and smart farming by delivering high-resolution, flexible, and cost-effective spatial data. This paper synthesizes current applications of UAVs in ecological monitoring, land-use planning, and precision agriculture, emphasizing their role in bridging farm-level management with regional planning goals. Drawing from recent advances in sensors, machine learning, and participatory approaches, the paper integrates a field-based case study from Adana, Türkiye, where UAV multispectral and thermal imagery were employed in wheat fields under controlled irrigation and nitrogen regimes. This Mediterranean example demonstrates how UAV-based monitoring can provide empirical evidence for linking farm-level diagnostics to landscape-scale resilience planning. The study concludes with methodological and governance insights for embedding UAV workflows into climate-resilient land-use systems.

Etik Beyan

The authors wish to acknowledge the financial support by the European Union’s ERASMUS+ Program under the Grant Number 2023-1-DE01-KA220-HED-000166720 (Smart Farming).

Destekleyen Kurum

European Union ERASMUS+ Program

Proje Numarası

ERASMUS+ 2023-1-DE01-KA220-HED-000166720

Teşekkür

The authors wish to acknowledge the financial support by the European Union’s ERASMUS+ Program under the Grant Number 2023-1-DE01-KA220-HED-000166720 (Smart Farming).

Kaynakça

  • Agrawal, J., & Arafat, M.Y. (2024). Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture. Drones, 8(11), 664.
  • Aliloo, J., Abbasi, M., et al. (2024). Dos and Don'ts of Using Drone Technology in The Crop Fields. Technology in Society, 76, 102165.
  • Alves, A.K.S., et al. (2024). High-Throughput Phenotyping in Soybean Using UAV-Based RGB Imagery. Scientific Reports, 14, 12845.
  • Anam, I., et al. (2024). UAV and AI For Crop Protection: A Systematic Review. Current Plant Biology, 15, 100327.
  • Anderson, K., & Gaston, K.J. (2025). Drones in Ecology: Ten Years Back And Forth. Bioscience, 75(8), 664–676.
  • Araújo-Paredes, C., et al. (2022). Assessment of Crop Water Stress Index Using Aerial Thermal Imagery. Plants, 11(5), 652.
  • Barathkumar, R., Selvanayaki, R., et al. (2024). Impact of Drone Technology on Agriculture: Farmers' Perception Analysis. Plant Science Today, 11, 13–20.
  • Barbosa, B.D.S., Ferraz, G., et al. (2021). Application of RGB Images Obtained By UAV in Coffee Farming. Remote Sensing, 13(12), 2456.
  • Barbosa, M.J.R., Moreira, M., et al. (2022). Uavs To Monitor And Manage Sugarcane: Integrative Review. Agronomy, 12(3), 563.
  • Bazrafkan, A., et al. (2025). Optimizing UAS–Satellite Fusion Strategies For Precision Agriculture. Frontiers in Remote Sensing, 6, 1524531.
  • Berger, C., et al. (2022). Assessing Green Infrastructure Benefits With Uavs in Urban Environments. Urban Forestry & Urban Greening, 68, 127492.
  • Bongomin, O., et al. (2024). UAV Image Acquisition and Processing For High-Throughput Phenotyping. The Plant Phenome Journal, 7, E20034.
  • Canicatti, M., & Vallone, M. (2024). Drones in Vegetable Crops: A Systematic Literature Review. Smart Agricultural Technology, 7, 100219.
  • Cook, K. (2017). An Evaluation Of UAV Photogrammetry For Monitoring Riverbank Erosion. Earth Surface Processes And Landforms, 42(6), 1125–1135.
  • Daniels, L., et al. (2023). Evaluating Radiometric Calibration Methods For UAV Multispectral imagery. Remote Sensing, 15(12), 2975.
  • Delavarpour, N., et al. (2023). A Review of UAV Sprayer Technology: State of The Art And Challenges. Transactions of The ASABE, 66(3), 851–866.
  • Didan, K., et al. (2023). UAS Multispectral Calibration With MAPR Reflectance Panels. U.S. Department of Energy Report.
  • Dong, H., et al. (2024). Review of UAV-Based Approaches For Water Stress Detection in Crops. Agricultural Water Management, 304, 108763.
  • Eltner, A., et al. (2016). Image-Based Surface Reconstruction in Geomorphometry Merits, Limits And Developments. Earth Surface Dynamics, 4, 359–389.
  • Farid, A., Mouhoub, R., et al. (2024). Multi-UAV Weed Spraying. Robotics, Computer Vision And Intelligent Systems, 2077, 210–224.
  • Fathololoumi, S., Vasava, V., et al. (2025). Reducing Corn Yield Prediction Uncertainty Through Multi-Scale Integration of Ground, Drone, And Satellite Data. Precision Agriculture, 26(5), 1123–1142.
  • Fernández-Guisuraga, J.M., Et al. (2020). Assessing Post-Fire Vegetation Recovery Using UAV-Derived Multispectral Imagery. Ecological Indicators, 113, 106243.
  • Franklin, S.E., & Ahmed, O.S. (2018). Deciduous Tree Species Classification Using Object-Based Analysis And UAV Imagery. International Journal of Remote Sensing, 39(15–16), 5039–5061.
  • Gheorghe, G.V., Dumitru, C., et al. (2024). Advancing Precision Agriculture With Uavs: Innovations in Fertilization. Inmateh Agricultural Engineering, 74(3), 1057–1072.
  • Greco, C., Gaglio, M., et al. (2025). Smart Farming Technologies For Sustainable Agriculture: A Case Study of A Mediterranean Aromatic Farm. Agriculture, 15(8), 963.
  • Greco, C., Gaglio, M., et al. (2025). Monitoring Moringa Oleifera İn The Mediterranean Area Using Uavs. Agriculture, 15(13), 1405. Guebsi, R., et al. (2024). Drones İn Precision Agriculture: A Comprehensive Review. Drones, 8(11), 686.
  • Haskins, C., et al. (2021). UAV Monitoring Of Tidal Marsh Restoration. Ecological Engineering, 161, 106140.
  • Hnida, Y., Mahraz, M., et al. (2025). Multi-Scale Detection Of Olive Tree Crowns in UAV Orthophotos Using Deep Learning. Smart Agricultural Technology, 12, 100451.
  • Hu, Y., & Minner, J. (2023). UAV-Based 3D Modeling For Urban Green Infrastructure Planning. Landscape And Urban Planning, 236, 104795.
  • Jiao, L., et al. (2024). UAV-Assisted Restoration Monitoring in Grassland Ecosystems. Ecological Indicators, 155, 110278.
  • Jones, T.G., et al. (2022). UAV Monitoring of Riparian Buffers For Water Quality Protection. Environmental Monitoring And Assessment, 194, 334.
  • Kamarulzaman, A.M.M., et al. (2023). UAV İmplementations in Urban Planning: A Systematic Review. Remote Sensing, 15(11), 2845.
  • Kartal, A., et al. (2025). Optimizing Spray Technology For Drone-Based Pesticide Application. Crop Protection, 174, 106231.
  • Kleinschroth, F., et al. (2022). Drone Imagery As Boundary Objects For Collaborative Land Management. Agricultural Systems, 198, 103384.
  • Lacerda, L.N., et al. (2022). Assessment Of Water Stress in Cotton Using Thermal UAV Imagery. Current Plant Biology, 29, 100238.
  • Lucieer, A., et al. (2014). Detecting Landslide Displacements Using UAV Photogrammetry And DSM Differencing. Remote Sensing of Environment, 147, 189–197.
  • Mazzia, V., Comba, L., Khaliq, A., et al. (2020). UAV And Satellite Data Fusion For Precision Agriculture. Computers And Electronics in Agriculture, 178, 105784.
  • Muhmad Kamarulzaman, A., et al. (2023). UAV Implementations in Urban Planning And Related Fields. Remote Sensing, 15(11), 2845.
  • Narziari, R., et al. (2025). A Critical Review of Uavs For Sustainable Agriculture Aligned With Sdgs. Discover Agriculture, 1, 55.
  • Panthakkan, A., et al. (2025). RGB Vegetation İndices For UAV Monitoring of Date Palm. Agronomy, 15(2), 456.
  • Pretto, A., et al. (2019). Aerial-Ground Robotics For Precision Farming: The FLOURISH Project. IEEE Robotics And Automation Letters, 4(3), 2242–2249.
  • Robinson, J.M., et al. (2022). Existing and Emerging Uses of Drones in Restoration Ecology. Methods in Ecology And Evolution, 13(12), 2617–2636.
  • Sestraș, P., et al. (2025). Land Surveying With UAV Photogrammetry And Lidar For DFM Optimization. Automation in Construction, 161, 105223.
  • Singh, A., Kumar, P., et al. (2024). UAV-Enabled Irrigation Scheduling and Variable-Rate Irrigation. Agricultural Water Management, 299, 108753.
  • Shao, Y., et al. (2021). Uavs and Urban Green Roof Assessment. Landscape And Urban Planning, 214, 104171.
  • Stöcker, C., et al. (2015). UAV-Based Mapping of Soil Erosion in Agricultural Landscapes. Remote Sensing, 7(5), 5243–5277.
  • Sun, Z., et al. (2021). Uavs As Remote Sensing Platforms in Plant Ecology: A Review. Journal of Plant Ecology, 14(6), 1003–1023.
  • Swaminathan, V., et al. (2024a). UAV-Based Downwelling Light Sensor Correction. The Plant Phenome Journal, 7, E20031.
  • Swaminathan, V., et al. (2024b). Radiometric Exposure Effects On UAV Imagery. The Plant Phenome Journal, 7, E20032.
  • Tanaka, T.S.T., et al. (2024). UAV-Based Crop Phenotyping: A Review of Sensors And Workflows. Drones, 8(7), 422.
  • Torresan, C., et al. (2020). UAV For Biodiversity Monitoring And Habitat Mapping: A Review. International Journal Of Remote Sensing, 41(7), 2377–2401.
  • Török, P., et al. (2021). Monitoring of Ecological Restoration Outcomes Using Uavs. Restoration Ecology, 29(5), E13390.
  • Tsouros, D.C., et al. (2019). UAV-Based Applications For Precision Agriculture: A Review. Information Processing in Agriculture, 6(2), 120–143.
  • Van Iersel, W., et al. (2023). UAV Monitoring Of Coastal Dune Stabilization. Ecological Engineering, 190, 106671.
  • Villarreal, S., et al. (2025). Uavs For Ecological Monitoring And Land-Use Change Detection: A Synthesis. Landscape And Urban Planning, 250, 105855.
  • Wallace, L., et al. (2016). Assessment Of Forest Structure Using UAV Lidar. Remote Sensing, 8(8), 649.
  • Wang, Y., et al. (2024). Multispectral Radiometric Correction For UAV Imagery. ISPRS Journal of Photogrammetry And Remote Sensing, 206, 50–63.
  • Yadav, M., et al. (2024). UAV-Enabled Irrigation Scheduling For Precision Agriculture. Agricultural Water Management, 299, 108753.
  • Yewle, A.D., et al. (2025). Multimodal Ensemble Fusion For Rice Yield Prediction From UAV And Field Data. Heliyon, 11(2), E24215.
  • Zhang, S., et al. (2025). UAV Multispectral İmagery For Crop Monitoring: A Review. Current Plant Biology, 36, 100410.
  • Zhu, H., et al. (2024). Deep Learning For UAV-Based Agricultural Monitoring. Frontiers in Plant Science, 15, 1185429.

Peyzaj Planlamada İnsansız Hava Araçlarının (İHA) Kullanımı: Tarımsal Bir Peyzajda Akıllı Tarım Örneği

Yıl 2025, Cilt: 8 Sayı: 1, 188 - 200, 31.12.2025

Öz

İnsansız Hava Araçları (İHA’lar), yüksek çözünürlüklü, esnek ve maliyet etkin mekânsal veriler sağlayarak hem peyzaj planlamasını hem de akıllı tarımı dönüştürmektedir. Bu makale, İHA’ların ekolojik izleme, arazi kullanım planlaması ve hassas tarımdaki güncel uygulamalarını sentezlemekte; tarımsal uygulamalar ile bölgesel planlama hedefleri arasında köprü kurmadaki rollerini vurgulamaktadır. Sensör teknolojileri, makine öğrenmesi ve katılımcı yaklaşımlardaki son gelişmeleri vurgulayan bu çalışma, Adana (Türkiye)’da yürütülen ve kontrollü sulama ile azot uygulamaları altında buğday tarlalarında İHA tabanlı çok bantlı (multispektral) ve termal görüntülerin kullanıldığı saha temelli bir vaka çalışmasını bütüncül biçimde ele almaktadır. Bu Akdeniz örneği, İHA tabanlı izlemenin tarımsal alanlar düzeyindeki tanısal bulguların peyzaj ölçeğinde dirençlilik (dayanıklılık) planlamasıyla ilişkilendirilmesine ampirik kanıtlar sağlamak üzere bir örnek olarak seçilmiştir. Çalışma, İHA tabanlı iş akışlarının iklime dayanıklı arazi kullanım sistemlerine entegre edilmesine yönelik metodolojik ve yönetişimsel çıkarımlar ile sonuçlanmaktadır.

Etik Beyan

Yazarlar, Avrupa Birliği ERASMUS+ Programı kapsamında 2023-1-DE01-KA220-HED-000166720 (Smart Farming) hibe numarası ile sağlanan mali destek için teşekkür eder.

Destekleyen Kurum

Avrupa Birliği ERASMUS+ Programı

Proje Numarası

ERASMUS+ 2023-1-DE01-KA220-HED-000166720

Teşekkür

Yazarlar, Avrupa Birliği ERASMUS+ Programı kapsamında 2023-1-DE01-KA220-HED-000166720 (Smart Farming) hibe numarası ile sağlanan mali destek için teşekkür eder.

Kaynakça

  • Agrawal, J., & Arafat, M.Y. (2024). Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture. Drones, 8(11), 664.
  • Aliloo, J., Abbasi, M., et al. (2024). Dos and Don'ts of Using Drone Technology in The Crop Fields. Technology in Society, 76, 102165.
  • Alves, A.K.S., et al. (2024). High-Throughput Phenotyping in Soybean Using UAV-Based RGB Imagery. Scientific Reports, 14, 12845.
  • Anam, I., et al. (2024). UAV and AI For Crop Protection: A Systematic Review. Current Plant Biology, 15, 100327.
  • Anderson, K., & Gaston, K.J. (2025). Drones in Ecology: Ten Years Back And Forth. Bioscience, 75(8), 664–676.
  • Araújo-Paredes, C., et al. (2022). Assessment of Crop Water Stress Index Using Aerial Thermal Imagery. Plants, 11(5), 652.
  • Barathkumar, R., Selvanayaki, R., et al. (2024). Impact of Drone Technology on Agriculture: Farmers' Perception Analysis. Plant Science Today, 11, 13–20.
  • Barbosa, B.D.S., Ferraz, G., et al. (2021). Application of RGB Images Obtained By UAV in Coffee Farming. Remote Sensing, 13(12), 2456.
  • Barbosa, M.J.R., Moreira, M., et al. (2022). Uavs To Monitor And Manage Sugarcane: Integrative Review. Agronomy, 12(3), 563.
  • Bazrafkan, A., et al. (2025). Optimizing UAS–Satellite Fusion Strategies For Precision Agriculture. Frontiers in Remote Sensing, 6, 1524531.
  • Berger, C., et al. (2022). Assessing Green Infrastructure Benefits With Uavs in Urban Environments. Urban Forestry & Urban Greening, 68, 127492.
  • Bongomin, O., et al. (2024). UAV Image Acquisition and Processing For High-Throughput Phenotyping. The Plant Phenome Journal, 7, E20034.
  • Canicatti, M., & Vallone, M. (2024). Drones in Vegetable Crops: A Systematic Literature Review. Smart Agricultural Technology, 7, 100219.
  • Cook, K. (2017). An Evaluation Of UAV Photogrammetry For Monitoring Riverbank Erosion. Earth Surface Processes And Landforms, 42(6), 1125–1135.
  • Daniels, L., et al. (2023). Evaluating Radiometric Calibration Methods For UAV Multispectral imagery. Remote Sensing, 15(12), 2975.
  • Delavarpour, N., et al. (2023). A Review of UAV Sprayer Technology: State of The Art And Challenges. Transactions of The ASABE, 66(3), 851–866.
  • Didan, K., et al. (2023). UAS Multispectral Calibration With MAPR Reflectance Panels. U.S. Department of Energy Report.
  • Dong, H., et al. (2024). Review of UAV-Based Approaches For Water Stress Detection in Crops. Agricultural Water Management, 304, 108763.
  • Eltner, A., et al. (2016). Image-Based Surface Reconstruction in Geomorphometry Merits, Limits And Developments. Earth Surface Dynamics, 4, 359–389.
  • Farid, A., Mouhoub, R., et al. (2024). Multi-UAV Weed Spraying. Robotics, Computer Vision And Intelligent Systems, 2077, 210–224.
  • Fathololoumi, S., Vasava, V., et al. (2025). Reducing Corn Yield Prediction Uncertainty Through Multi-Scale Integration of Ground, Drone, And Satellite Data. Precision Agriculture, 26(5), 1123–1142.
  • Fernández-Guisuraga, J.M., Et al. (2020). Assessing Post-Fire Vegetation Recovery Using UAV-Derived Multispectral Imagery. Ecological Indicators, 113, 106243.
  • Franklin, S.E., & Ahmed, O.S. (2018). Deciduous Tree Species Classification Using Object-Based Analysis And UAV Imagery. International Journal of Remote Sensing, 39(15–16), 5039–5061.
  • Gheorghe, G.V., Dumitru, C., et al. (2024). Advancing Precision Agriculture With Uavs: Innovations in Fertilization. Inmateh Agricultural Engineering, 74(3), 1057–1072.
  • Greco, C., Gaglio, M., et al. (2025). Smart Farming Technologies For Sustainable Agriculture: A Case Study of A Mediterranean Aromatic Farm. Agriculture, 15(8), 963.
  • Greco, C., Gaglio, M., et al. (2025). Monitoring Moringa Oleifera İn The Mediterranean Area Using Uavs. Agriculture, 15(13), 1405. Guebsi, R., et al. (2024). Drones İn Precision Agriculture: A Comprehensive Review. Drones, 8(11), 686.
  • Haskins, C., et al. (2021). UAV Monitoring Of Tidal Marsh Restoration. Ecological Engineering, 161, 106140.
  • Hnida, Y., Mahraz, M., et al. (2025). Multi-Scale Detection Of Olive Tree Crowns in UAV Orthophotos Using Deep Learning. Smart Agricultural Technology, 12, 100451.
  • Hu, Y., & Minner, J. (2023). UAV-Based 3D Modeling For Urban Green Infrastructure Planning. Landscape And Urban Planning, 236, 104795.
  • Jiao, L., et al. (2024). UAV-Assisted Restoration Monitoring in Grassland Ecosystems. Ecological Indicators, 155, 110278.
  • Jones, T.G., et al. (2022). UAV Monitoring of Riparian Buffers For Water Quality Protection. Environmental Monitoring And Assessment, 194, 334.
  • Kamarulzaman, A.M.M., et al. (2023). UAV İmplementations in Urban Planning: A Systematic Review. Remote Sensing, 15(11), 2845.
  • Kartal, A., et al. (2025). Optimizing Spray Technology For Drone-Based Pesticide Application. Crop Protection, 174, 106231.
  • Kleinschroth, F., et al. (2022). Drone Imagery As Boundary Objects For Collaborative Land Management. Agricultural Systems, 198, 103384.
  • Lacerda, L.N., et al. (2022). Assessment Of Water Stress in Cotton Using Thermal UAV Imagery. Current Plant Biology, 29, 100238.
  • Lucieer, A., et al. (2014). Detecting Landslide Displacements Using UAV Photogrammetry And DSM Differencing. Remote Sensing of Environment, 147, 189–197.
  • Mazzia, V., Comba, L., Khaliq, A., et al. (2020). UAV And Satellite Data Fusion For Precision Agriculture. Computers And Electronics in Agriculture, 178, 105784.
  • Muhmad Kamarulzaman, A., et al. (2023). UAV Implementations in Urban Planning And Related Fields. Remote Sensing, 15(11), 2845.
  • Narziari, R., et al. (2025). A Critical Review of Uavs For Sustainable Agriculture Aligned With Sdgs. Discover Agriculture, 1, 55.
  • Panthakkan, A., et al. (2025). RGB Vegetation İndices For UAV Monitoring of Date Palm. Agronomy, 15(2), 456.
  • Pretto, A., et al. (2019). Aerial-Ground Robotics For Precision Farming: The FLOURISH Project. IEEE Robotics And Automation Letters, 4(3), 2242–2249.
  • Robinson, J.M., et al. (2022). Existing and Emerging Uses of Drones in Restoration Ecology. Methods in Ecology And Evolution, 13(12), 2617–2636.
  • Sestraș, P., et al. (2025). Land Surveying With UAV Photogrammetry And Lidar For DFM Optimization. Automation in Construction, 161, 105223.
  • Singh, A., Kumar, P., et al. (2024). UAV-Enabled Irrigation Scheduling and Variable-Rate Irrigation. Agricultural Water Management, 299, 108753.
  • Shao, Y., et al. (2021). Uavs and Urban Green Roof Assessment. Landscape And Urban Planning, 214, 104171.
  • Stöcker, C., et al. (2015). UAV-Based Mapping of Soil Erosion in Agricultural Landscapes. Remote Sensing, 7(5), 5243–5277.
  • Sun, Z., et al. (2021). Uavs As Remote Sensing Platforms in Plant Ecology: A Review. Journal of Plant Ecology, 14(6), 1003–1023.
  • Swaminathan, V., et al. (2024a). UAV-Based Downwelling Light Sensor Correction. The Plant Phenome Journal, 7, E20031.
  • Swaminathan, V., et al. (2024b). Radiometric Exposure Effects On UAV Imagery. The Plant Phenome Journal, 7, E20032.
  • Tanaka, T.S.T., et al. (2024). UAV-Based Crop Phenotyping: A Review of Sensors And Workflows. Drones, 8(7), 422.
  • Torresan, C., et al. (2020). UAV For Biodiversity Monitoring And Habitat Mapping: A Review. International Journal Of Remote Sensing, 41(7), 2377–2401.
  • Török, P., et al. (2021). Monitoring of Ecological Restoration Outcomes Using Uavs. Restoration Ecology, 29(5), E13390.
  • Tsouros, D.C., et al. (2019). UAV-Based Applications For Precision Agriculture: A Review. Information Processing in Agriculture, 6(2), 120–143.
  • Van Iersel, W., et al. (2023). UAV Monitoring Of Coastal Dune Stabilization. Ecological Engineering, 190, 106671.
  • Villarreal, S., et al. (2025). Uavs For Ecological Monitoring And Land-Use Change Detection: A Synthesis. Landscape And Urban Planning, 250, 105855.
  • Wallace, L., et al. (2016). Assessment Of Forest Structure Using UAV Lidar. Remote Sensing, 8(8), 649.
  • Wang, Y., et al. (2024). Multispectral Radiometric Correction For UAV Imagery. ISPRS Journal of Photogrammetry And Remote Sensing, 206, 50–63.
  • Yadav, M., et al. (2024). UAV-Enabled Irrigation Scheduling For Precision Agriculture. Agricultural Water Management, 299, 108753.
  • Yewle, A.D., et al. (2025). Multimodal Ensemble Fusion For Rice Yield Prediction From UAV And Field Data. Heliyon, 11(2), E24215.
  • Zhang, S., et al. (2025). UAV Multispectral İmagery For Crop Monitoring: A Review. Current Plant Biology, 36, 100410.
  • Zhu, H., et al. (2024). Deep Learning For UAV-Based Agricultural Monitoring. Frontiers in Plant Science, 15, 1185429.
Toplam 61 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yazılım Mühendisliği (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Hakan Alphan 0000-0003-1139-4087

Volkan Çatalkaya 0000-0002-8078-3548

Celaleddin Barutçular 0000-0003-3583-9191

Proje Numarası ERASMUS+ 2023-1-DE01-KA220-HED-000166720
Gönderilme Tarihi 14 Aralık 2025
Kabul Tarihi 30 Aralık 2025
Yayımlanma Tarihi 31 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 8 Sayı: 1

Kaynak Göster

APA Alphan, H., Çatalkaya, V., & Barutçular, C. (2025). The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape. GSI Journals Serie C: Advancements in Information Sciences and Technologies, 8(1), 188-200.
AMA Alphan H, Çatalkaya V, Barutçular C. The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape. aist. Aralık 2025;8(1):188-200.
Chicago Alphan, Hakan, Volkan Çatalkaya, ve Celaleddin Barutçular. “The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape”. GSI Journals Serie C: Advancements in Information Sciences and Technologies 8, sy. 1 (Aralık 2025): 188-200.
EndNote Alphan H, Çatalkaya V, Barutçular C (01 Aralık 2025) The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape. GSI Journals Serie C: Advancements in Information Sciences and Technologies 8 1 188–200.
IEEE H. Alphan, V. Çatalkaya, ve C. Barutçular, “The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape”, aist, c. 8, sy. 1, ss. 188–200, 2025.
ISNAD Alphan, Hakan vd. “The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape”. GSI Journals Serie C: Advancements in Information Sciences and Technologies 8/1 (Aralık2025), 188-200.
JAMA Alphan H, Çatalkaya V, Barutçular C. The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape. aist. 2025;8:188–200.
MLA Alphan, Hakan vd. “The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape”. GSI Journals Serie C: Advancements in Information Sciences and Technologies, c. 8, sy. 1, 2025, ss. 188-00.
Vancouver Alphan H, Çatalkaya V, Barutçular C. The Use of Unmanned Aerial Vehicles (UAVs) in Landscape Planning: The case of Smart Farming in an Agricultural Landscape. aist. 2025;8(1):188-200.