Spatiotemporal Change Detection of the Linden Forests in Bursa, Turkey

Year 2018, Volume: 4 Issue: 2, 50 - 55, 28.12.2018

Burhan Gencal , İnanç Taş , Abdullah Emin Akay

https://doi.org/10.33904/ejfe.495088

Cited By: 1

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, post-processing, 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.

Keywords

Spatiotemporal change detection, land use/land cover change, linden, classification

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