Abstract
The Zagros forests in Western Iran are valuable ecosystems that have been seriously damaged by human interference (harvesting the wood and forest sub-products, converting the forests to the agricultural lands, and grazing) and natural events (drought events and fire). In this study, we generated accurate land cover (LC), and tree canopy cover percentage (TCC%) maps for the forests of Shirvan County, a part of Zagros forests in Western Iran using Sentinel-2, Google Earth, and field data for protective management. First, we assessed the accuracy of Google Earth data using 300 random field plots in 10 different land cover types. For land cover mapping, we evaluated the performance of four supervised classification algorithms (minimum distance (MD), Mahalanobis distance (MaD), neural network (NN), and support vector machine (SVM)). The accuracy of the land cover maps was assessed using a set of 150 stratified random plots in Google Earth. We mapped the forest canopy cover by using the normalized difference vegetation index (NDVI) map, and field plots. We calculated the Pearson correlation between the NDVI values and the TCC% (obtained from field plots). The linear regression between the NDVI values and the TCC% was used to obtain the predictive model of TCC% based on the NDVI. The results showed that Google Earth data yielded an overall accuracy of 94.4%. The SVM algorithm had the highest accuracy for the classification of Sentinel-2 data with an overall accuracy of 81.33% and a kappa index of 0.76. The results of the forest canopy cover analysis showed a Pearson correlation coefficient of 0.93 between the NDVI and TCC%, which is highly significant. The results also showed that the linear regression model is a good predictive model for TCC% estimation based on the NDVI (r2 = 0.864). The results can be used as a baseline for decision-makers to monitor land cover change in the region, whether produced by human activities or natural events and to establish measures for protective management of forests.
Highlights
Iran is a vast country with different types of climate and vegetation, a wide range of elevation, and varied geological formations, the combination of which led to having rich biological diversity [1] and numerous endemic species [2]
Providing a precise land cover map in Zagros forests would help the managers of the natural resources to find the answers to questions such as (1) how natural and human-made land covers are distributed in the Zagros forest, (2) how large the exact area of different land covers inside Zagros forests is, or (3) how human-made land covers interact with the natural land covers
This research presented an approach for mapping the land cover and tree canopy cover in western Zagros forests of Iran based on Sentinel-2, Google Earth, and field data
Summary
Iran is a vast country with different types of climate and vegetation, a wide range of elevation, and varied geological formations, the combination of which led to having rich biological diversity [1] and numerous endemic species [2]. The Zagros Mountain is not the most bio-diverse region in Iran, the Zagros oak forests are one of the most important natural ecosystems in Iran, that are 5500 years old [5,6,7,8]. Over the last 30 years, climate change, population growth, and the dependence of people’s livelihoods on these forests (by harvesting the wood and forest sub-products, converting forests to the agricultural lands, and grazing) have resulted in degradation of these natural ecosystems [9,10] These forests, especially in Ilam Province in Western Iran, have been damaged by climate change, droughts (especially in oak forests), fires and human interference through, for example, the dependence of the residents on these areas for the provision of wood for fuel and land for livestock, agriculture, and grazing [9,10,11,12]. Providing land cover and forest canopy cover maps in these forests will be the first step to protecting them and preventing further destruction [15]
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