The effect of post-wildfire management practices on vegetation recovery: Insights from the Sapadere fire, Antalya, Türkiye

Post-wildfire management actions mainly targeting the removal of salvage logs and burned trees is a common but controversial practice. Although it aims to regain some of the natural and economic value of a forest, it also requires disturbing burned areas, which may have some negative consequences affecting, for instance, the carbon cycle, soil erosion, and vegetation cover. Observations from different geographic settings contribute to this scientific debate, and yet, the spatiotemporal evolution of the post-fire road network developed as part of fire management practices and its influence on vegetation recovery has been rarely examined. Specifically, we still lack observations from Türkiye, though wildfires are a common event. This research examined the evolution of the vegetation cover in relation to post-fire road constructions and the resultant debris materials in areas affected by the 2017 Sapadere fire in Antalya, Türkiye. We used multi-sensor, multi-temporal optical satellite data and monitored the variation in both vegetation cover and road network from the pre-to post-fire periods between 2014 and 2021. Our results showed that fire management practices almost doubled the road network in the post-fire period, from 487 km to 900 km. Overall, 7% of the burned area was affected by these practices. As a result, vegetation cover in those areas shows only ∼50% recovery, whereas undisturbed areas exhibit ∼100% recovery 5 years after the event. Notably, such spatiotemporal analysis carried out for different burned areas would provide a better insight into the most suitable post-fire management practices. Our findings, in particular, show that the current practices need to be revisited as they cause a delay in vegetation recovery

Efficiency analysis of solar farms by UAV-based thermal monitoring

Solar energy is a rapidly growing industry, and the performance analysis and maintenance of solar farms are crucial for ensuring their photovoltaics efficiency and longevity. In this context, many solar farms are established and it is crucial for energy producers to operate these farms efficiently. However, control of solar degradation panels locally takes time and control procedures are a challenge for the producers particularly for large farms. In recent years, the use of unmanned aerial vehicles equipped with thermal imaging sensors has emerged as a promising technique for monitoring solar farms. Herein, degradation inspection and efficiency analyses of the solar panels can be effectively conducted by mapping thermal orthomosaic data. In this study, thermal images were obtained for orthomosaic data production by conducting photogrammetric flights with a real time kinematic enabled unmanned aerial vehicles on a solar farm. The solar panels were divided into segments by the segmentation process and photovoltaics efficiency was calculated for each panel based on solar energy. The photovoltaics efficiency was monitored to vary at most 1.22 % throughout the day with the maximum efficiency reaching 18.25 % in the afternoon, and the minimum efficiency dipping to 17.03 % midday. Close efficiency values were acquired in the morning and afternoon with a difference not exceeding 0.12 %. As such, the damage conditions of panels can be identified by designating the ones with the lowest efficiency. Thus it can be deduced that rapid, cost effective and feasible assessment of solar farms may be possible by unmanned aerial vehicle-based thermal monitoring while bringing forth more sensitive future predictions

Regional distribution and characteristics of major badland landscapes in Turkey

Badlands are extremely rugged, outstanding landscapes that can be seen in all ice-free climate regions over erosion-susceptible unconsolidated materials, and they have drawn attention with their spectacular and iconic forms. Unlike nearly all badlands researches conducted at the experimental site and watershed scale, so far, the broader-scale evaluation has been neglected in the analysis of badland distribution, characteristics, and dynamics. Our study provides an integrative new insight into badland landscapes by investigating the distribution, characteristics and controlling factors of Turkish badlands on a broad, regional scale. We inventoried Turkish badlands using aerial imagery and studied their distribution using K-means clustering, an unsupervised machine learning algorithm, based on a set of major conditional geo-environmental factors that control the regional distribution and characteristics of badlands, including tectonics, lithology, topography, climate, and vegetation. Here, we identified, a total of 4494 km2 of badland areas which are non-uniformly distributed across Turkey, substantially clustered in the Central Anatolian Plateau (CAP). According to our regional analyses, we have determined a total of five badland regions comprising three major types classified as Semi-arid, Mediterranean, and Montane (humid), together with two transitional types in-between the Semi-arid and Montane badland regions. Our results indicate that temperature seasonality (0.83), mean annual precipitation (0.83), and precipitation seasonality (0.76) are predominantly assigned to the badlands clusters. The clastic rocks are revealed as the most crucial and inevitable factor for the development of Turkish badlands, which are represented in a wide geologic time-scale (Cretaceous to Quaternary) and diverse lithological units (i.e., lacustrine, volcaniclastics, and terrestrial). Neogene and Paleogene terrestrial clastics (77 %) constitute the majority of the lithologic settings of these badland landscapes. The active and complex tectonic history of Turkey has portrayed the fundamental frame of the identified badland regions, by providing a susceptible environment (i.e., development of sedimentary basins) and promoting badland development through successive base-level changes. Furthermore, tectonically-modulated (i.e., formation of orogenic belts, and uplifting of CAP) climate dynamics outline the distribution pattern and differentiation of the regional characteristics of badlands in Turkey. Overall, our regional-scale approach to badland mapping and regional synthesis may decipher not only the tectonic and climatic conditions of the identified badlands regions, but it may also contribute to the implementation of future effective strategies for the detection and mapping of erosion susceptible and high sediment flux areas in very broad spatial contexts of similar unexplored territories.The authors are thankful to editor Arnaud Temme and three anonymous reviewers for their useful and constructive comments. This study is supported by the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not indicate that the content of the publication is approved in a scientific sense by TUBITAK. MMH is a Serra Hunter fellow funded by the Generalitat the Catalunya (UB-LE-9055). The authors thank to Orkan Ozcan, Ali Mohammadi, Serdar Yeşilyurt, Cihan Yıldız, Onur Altınay, and Tunahan Aykut for their support during the fieldworks.Peer reviewe