Person: GÜNDOĞDU, KEMAL SULHİ
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GÜNDOĞDU
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KEMAL SULHİ
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Publication Crop type classification using Sentinel 2A-derived Normalized Difference Red Edge Index (NDRE) and machine learning approach(Bursa Uludağ Üniversitesi, 2024-03-20) GÜNDOĞDU, KEMAL SULHİ; Bantchina, Benjamin Bere; Fen Bilimleri Enstitüsü; Biyosistem Mühendisliği Bölümü; 0000-0002-2593-426X; 0000-0002-5591-4788Satellite remote sensing (RS) enables the extraction of vital information on land cover and crop type. Land cover and crop type classification using RS data and machine learning (ML) techniques have recently gained considerable attention in the scientific community. This study aimed to enhance remote sensing research using high-resolution satellite imagery and a ML approach. To achieve this objective, ML algorithms were employed to demonstrate whether it was possible to accurately classify various crop types within agricultural areas using the Sentinel 2A-derived Normalized Difference Red Edge Index (NDRE). Five ML classifiers, namely Support Vector Machines (SVM), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP), were implemented using Python programming on Google Colaboratory. The target land cover classes included cereals, fallow, forage, fruits, grassland-pasture, legumes, maize, sugar beet, onion-garlic, sunflower, and watermelon-melon. The classification models exhibited strong performance, evidenced by their robust overall accuracy (OA). The RF model outperformed, with an OA rate of 95% and a Kappa score of 92%. It was followed by DT (88%), KNN (87%), SVM (85%), and MLP (82%). These findings showed the possibility of achieving high classification accuracy using NDRE from a few Sentinel 2A images. This study demonstrated the potential enhancement of the application of high-resolution satellite RS data and ML for crop type classification in regions that have received less attention in previous studies.Publication Adoption factors of irrigation systems whose projects are synchronized with land consolidation(Academic Publication Council, 2008-12-01) Yaslıoğlu, Erkan; Arıcı, İsmet; Kuşcu, Hayrettin; Gündoğdu, Kemal Sulhi; Aslan, S. Tülin Akkaya; Kirmikil, Müge; YASLIOĞLU, ERKAN; Arıcı, İsmet; KUŞÇU, HAYRETTİN; GÜNDOĞDU, KEMAL SULHİ; Aslan, S. Tülin Akkaya; KİRMİKİL, MÜGE; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0002-3865-7863; 0000-0001-9600-7685; 0000-0002-5591-4788; 0000-0001-5129-8642; AAH-4682-2021; N-9721-2013; ABW-2318-2022; ABE-6643-2020; AAH-2955-2021; ABI-4047-2020Agricultural land is fragmented in Turkey and in other Central European countries. Fragmented land prevents irrigation system efficiency to reach the desired level. In arid and semi-arid zones land consolidation offers opportunities for increased irrigation system efficiency.The objective of our study was to determine factors for adoption of irrigation system as related to land consolidation. The Logit regression model was used to analyse survey data. Villages on the Bursa-Karacabey Plain of Turkey, where land consolidation and irrigation system were planned, were used as study sites. Results show that supplying sufficient water in canals, ease of irrigation planning, reducing in water losses, ease of maintaining the irrigation and drainage system, and labour requirement significantly affected the adoption of irrigation systems.Publication Comparative analysis of the pysebal model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey(Selçuk Üniversitesi Yayınları, 2020-06-01) Sawadogo, Alidou; Tim, Hessels; Gündoğdu, Kemal Sulhi; Demir, Ali Osman; Ünlü, Mustafa; Zwart, Sander Jaap; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; DEMİR, ALİ OSMAN; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0002-5591-4788; 0000-0002-5091-1801; JLX-2232-2023; DXY-6494-2022; ABI-4047-2020Accurate estimation of evapotranspiration (ET) is an important factor in water management, especially in irrigated agriculture. Accurate irrigation scheduling requires accurate estimation of ET. The objective of this study was to estimate the actual evapotranspiration (ETa) by the pySEBAL model and to compare it with the actual evapotranspiration measured by the lysimeter method of soybean crop in Adana, Turkey. Five Landsat 5 Thematic Mapper (TM) images and weather data were used for this study to estimate actual evapotranspiration by the pySEBAL model. The results showed a good relationship between ETa estimated by the pySEBAL model and ETa measured by the lysimeter method, with an R-2 of 0.73, an RMSE of 0.51 mm.day(-1), an MBE of 0.04 mm.day(-1) and a Willmott's index of agreement (d) of 0.90. Based on this study, there is a good relationship between the actual evapotranspiration estimated by the pySEBAL model and the actual evapotranspiration measured by the lysimeter method. Consequently, ETa of soybean crop can be estimated with high accuracy by the pySEBAL model in Adana, Turkey.Publication Assessing the biophysical factors affecting irrigation performance in rice cultivation using remote sensing derived information(Elsevier, 2023-01-09) Sawadogo, Alidou; Dossou-Yovo, Elliott R.; Kouadio, Louis; Zwart, Sander J.; Traore, Farid; Gündoğdu, Kemal S.; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; DXY-6494-2022; ABI-4047-2020Identifying the biophysical factors that affect the performance of irrigated crops in semi-arid conditions is pivotal to the success of profitable and sustainable agriculture under variable climate conditions. In this study, soil physical and chemical variables and plots characteristics were used through linear mixed and random forest -based modeling to evaluate the determinants of actual evapotranspiration (ETa) and crop water productivity (CWP) in rice in the Kou Valley irrigated scheme in Burkina Faso. Multi-temporal Landsat images were used within the Python module for the Surface Energy Balance Algorithm for Land model to calculate rice ETa and CWP during the dry seasons of 2013 and 2014. Results showed noticeable spatial variations in PySEBAL-derived ETa and CWP in farmers' fields during the study period. The distance between plot and irrigation scheme inlet (DPSI), plot elevation, sand and silt contents, soil total nitrogen, soil extractable potassium and zinc were the main factors affecting variabilities in ETa and CWP in the farmers' fields, with DPSI being the top explanatory variable. There was generally a positive association, up to a given threshold, between ETa and DPSI, sand and silt contents and soil extractable zinc. For CWP the association patterns for the top six predictors were all non-monotonic; that is a mix of increasing and decreasing associations of a given predictor to either an increase or a decrease in CWP. Our results indicate that improving irrigated rice performance in the Kou Valley irrigation scheme would require growing more rice at lower altitudes (e.g. < 300 m above sea level) and closer to the scheme inlet, in conjunction with a good management of nutrients such as nitrogen and potassium through fertilization.Publication Determination of temporal and spatial changes of NDVI values on wheat planted plots(Kahramanmaraş Sütçü İmam Üniversitesi Rektörlüğü, 2018-01-01) Gündoğdu, Kemal Sulhi; GÜNDOĞDU, KEMAL SULHİ; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0002-5591-4788; ABI-4047-2020In agricultural production, generally the remote sensing techniques have begun to be used on follow-up of plant development in a widespread manner. Images taken from satellite, airplane and unmanned aerial vehicles provide facilities for the spatial follow-up of the plant's development in the field. For determination of the plant intensity and species, NDVI values is calculated as vegetation index by using images taken in the red and near infrared wavelength reflecting from the plants. In this study, it was aimed to determine the spatial and temporal change of NDVI values in Pehlivan wheat variety planted in farm of Agricultural Faculty, Uludag University during 2015-2016 production period. Landsat 8 images taken at different dates were used in the study. As a result of the plot-based evaluation, the vegetation index values in the parcel did not show a homogeneous distribution.Publication Estimating in-season actual evapotranspiration over a large-scale irrigation scheme in resource-limited conditions(Publ House Bulgarian, 2020-01-01) Sawadogo, Alidou; Gündoğdu, Kemal Sulhi; Traore, Farid; Kouadio, Louis; Hessels, Tim; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; Ziraat Fakültesi; Biyosistem Mühendisliği Bölümü; 0000-0002-7437-8415; 0000-0002-5591-4788; 0000-0002-7264-7220; ABI-4047-2020; DXY-6494-2022Reliable and readily available data on actual evapotranspiration (ETa) over large-scale areas throughout the crop growing season are critical for improved agricultural irrigation and water resource management. On-site data collection is costly, labour-intensive, and very challenging in resource-limited conditions. Thus, open-source satellite-based approaches might be adopted as cost-effective alternatives. In this study, the performance of a cost-effective and open source satellite-based approach for estimating ETa over a large-scale (1200 ha) irrigation system, the Kou Valley Irrigation Scheme (KVIS), in Burkina Faso was assessed. ETa values over the critical irrigation period during the 2014 dry season (January-April) were estimated using the Python module for Surface Energy Balance Algorithm for Land model (PySEBAL). Then, they were compared against the Water Productivity Open-access (FAO-WaPOR), and United States Geological Survey-Famine Early Warning Systems Network Operational Simplified Surface Energy Balance (USGS-FEWS NET's SSEBop) ETa over the same period at different temporal scales. Overall, ETa values were satisfactorily estimated throughout the crop growth season across the Kou Valley irrigation scheme using PySEBAL. They spatially varied depending on the soil type and crop, with daily values ranging from 4.09 mm day(-1) to 7.7 mm day(-1), for a seasonal average of 619 mm. The finer spatial resolution (30 m) of PySEBAL outputs allowed better estimations compared to the FAO-WaPOR and SSEBop-based approaches. Our findings help ascertain the use of the PySEBAL model in semi-arid environment in Burkina Faso, and could serve as a basis for developing strategies for improved irrigation water management in countries experiencing similar conditions such as Burkina Faso.