ABSTRACT:This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

No abstract

Nonwood forest products potentially provide many economic, social and environmental benefits in Turkey. Increasing public demand for nonwood forest products has led to the development of spatial planning and updating of existing plans. In order to ensure the sustainable management of nonwood forest products, their trends and spatial distributions by time can be estimated by using land use/land cover change detection approach. The Linden is one of the most important nonwood forest products in Turkey and the most widespread distribution of linden is located in the province of Bursa. In this study, it was aimed to determine the spatiotemporal changes of one of the world's largest linden forests in Yeniköy Forestry Enterprise Chief within the border of Bursa Forestry Regional Directorate. Change detection analysis was applied to Landsat 5 TM image and Landsat 8 OLI/TIRS image captured in August 2008 and in July 2017, respectively. The spatiotemporal change detection was implemented on these two images by using various digital image processing techniques (pre-processing, classification, postprocessing, and change detection) through ERDAS Imagine 2015, ArcGIS 10.5, and ENVI 5.3 program. The supervised classification, applied on both images using ERDAS Imagine 2015 program, revealed that there were six significant land use/land cover types in the study area; linden, other deciduous trees, wetlands, swamp, sand, and other lands (settlements, agriculture, open areas). The results indicated that there was increase in the areas of wetlands, sand, and other lands, while the area of linden forest, other deciduous trees, and swamp decreased from 2008 to 2017. According to the accuracy assessment results, the classification processes applied on 2008 and 2017 images provided overall accuracy of 84.38% and 82.81%, respectively. It is determined that some of the linden forests have been converted into residential areas and farmlands to grow crops.

Özet Ülkemiz; zengin bitki örtüsü, farklı iklim ve coğrafik özellikleri ile arıcılığa son derece elverişli bir ortam oluşturmaktadır. Türkiye bulunduğu coğrafya, iklim koşulları ve bitki örtüsü ile ideal bir arıcılık bölgesidir. İstatistiklere bakıldığında ise Türkiye gerek arıcılıkla uğraşanlar gerekse kovan varlığı bakımından üst sıralarda olmasına rağmen bal, propolis, arı sütü gibi üretilen arı ürünleri bakımından birçok ülkeden geride bulunmaktadır. Bursa ili içerisinde 2013-2016 yılları arasında toplamda 725,3 hektar alanda 5 adet Bal Ormanı kurulmuş olup yapılan çalışmalar sonucunda 2016 yılından itibaren bu sayı 17 olmuştur. Bu çalışmamızda, Bursa Orman Bölge Müdürlüğü sınırları içerisinde bulunan bazı odunsu türlerle kurulabilecek Bal Ormanlarının, Coğrafi Bilgi Sistemleri (CBS) ve Uzaktan Algılama (UA) teknolojileri kullanılarak belirlenmesi ve yörede kurulacak bal ormanları ile bölgesel ve ulusal bağlamda elde edilecek gelirin tahmin edilmesi amaçlanmıştır. Alanların belirlenmesinde gerekli olan kriterlere Bal Ormanı Eylem Planından erişilmiştir. Yapılan analizler sonucunda odunsu türler bazında Bursa Orman Bölge Müdürlüğü sınırları içerisinde bal ormanına konu olabilecek alanlar belirlenmiştir.

630*38:625.7/.8]:582.685.4(560 Bursa) Road networks within the forested areas are essential structure to access forests for various purposes such as management, protection, regeneration, harvesting, and recreation etc. However, if roads are not planned properly, they may result in serious impacts on forest ecosystems including degradation and fragmentation of habitats. On the other hand, light availability along the road edge increases which reflects the diversity and amount of plant species. In the study, it was aimed to investigate the rod edge effect on tree growing by measuring the basal area increment along road network located within the linden stands. The study area was selected from Karacabey province of Bursa where linden has the largest distribution in Turkey. In the field study stage, four sample trees were selected from 5-meter-wide stripes at the road edge and from control zone which is about 50 meters away from the road edge. Measurements were repeated for 6 sample road sections with 500 meters length along 3 km-long road located in the middle of linden stands. Since the stand characteristics were mostly uniform and did not vary significantly along the sample road, stand structures such as tree ages, stand density, canopy, etc. were not   evaluated in this study. During the data collection, the diameter at breast height (DBH) was measured for the sample trees located in the specified zones. Then, statistical analysis was conducted to indicate whether there is a difference in basal area increments between the trees at road edge and the trees located in control zone.  According to the results, increasing the distance from the road edge resulted in reduction in the average basal area values. There was a statistically significant difference between basal area values for trees at road edge and the trees located in control zone.