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Full-Text Articles in Life Sciences
Artificial Intelligence As An Alternative Modelling Strategy For Reliable Height-Diameter Predictions Of Mixed-Oaks Species, Maria J. Diamantopoulou, Ramazan Özçeli̇k, Burak Koparan, Onur Alkan
Artificial Intelligence As An Alternative Modelling Strategy For Reliable Height-Diameter Predictions Of Mixed-Oaks Species, Maria J. Diamantopoulou, Ramazan Özçeli̇k, Burak Koparan, Onur Alkan
Turkish Journal of Agriculture and Forestry
Forest management and sustainable timber production rely on forest measurements that include tree height. However, the fieldwork needed for tree height measurements is time-consuming, and several times, hard to obtain. The solution to this problem is the construction of reliable height-diameter (h-d) models that can provide accurate tree height predictions. To this direction, a modified Gompertz model that included dominant height and diameter at breast height was used to predict tree height. In order to investigate the most promising modelling method, six alternative approaches were evaluated; these involved both regression and artificial intelligence techniques and produced the (i) …
The Potential Of Göktürk 2 Satellite Images For Mapping Burnt Forest Areas, Murat Kuruca, Di̇lek Küçük Matci, Uğur Avdan
The Potential Of Göktürk 2 Satellite Images For Mapping Burnt Forest Areas, Murat Kuruca, Di̇lek Küçük Matci, Uğur Avdan
Turkish Journal of Agriculture and Forestry
Using remotely sensed data to identify burnt forest areas produces fast, economical, and highly accurate results. Accordingly, in this study we investigate the capabilities of Göktürk-2, Turkey's national satellite, for mapping burnt forest areas. We compare our results with those obtained from Landsat-8 and Worldview-2 satellite images, which are frequently used for mapping burnt areas. The capabilities of the satellites are compared, in terms of detecting burnt forest areas, using support vector machine (SVM) and rotation forest (RF) classification, which are advanced methods. According to the results of the accuracy analysis, SVM classification gives similar kappa statistics and overall accuracy …
A Smart Agricultural Application: Automated Detection Of Diseases In Vine Leaves Usinghybrid Deep Learning, Ahmet Alkan, Muhammed Usame Abdullah, Hanadi̇ Omai̇sh Abdullah, Muhammed Assaf, Huiyu Zhou
A Smart Agricultural Application: Automated Detection Of Diseases In Vine Leaves Usinghybrid Deep Learning, Ahmet Alkan, Muhammed Usame Abdullah, Hanadi̇ Omai̇sh Abdullah, Muhammed Assaf, Huiyu Zhou
Turkish Journal of Agriculture and Forestry
This paper reports a study which utilizes deep learning for automated detection of the symptoms of diseases on vine leaves. Vine fruits or grapes are very important and have existed in Syria and surrounding areas (e.g., Turkey) for many years. Quality of vine fruits is also very important in grape production as it is consumed in these areas every day. The aim of this study is to improve diseasedetection accuracy in vine leaves and to develop a system to help Syrian and Turkish farmers and agricultural engineers to maintain the quality of grape production. In this study, over 1000 images …