Ecological Dynamics and Human Impact Assessment of a Small Mangrove Forest in the Northern Persian Gulf: A Multidimensional Approach Using Satellite-derived, Drone- based, and Field-measured Data

doi:10.21203/rs.3.rs-4868552/v1

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Ecological Dynamics and Human Impact Assessment of a Small Mangrove Forest in the Northern Persian Gulf: A Multidimensional Approach Using Satellite-derived, Drone- based, and Field-measured Data

https://doi.org/10.21203/rs.3.rs-4868552/v1

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The ecological dynamics of Mangroves of Dayyer City (MDC) in the northern Persian Gulf were assessed. This study employs satellite-based data, drone-based photography, and field measurements/observations to assess changes in mangrove areas, investigate human-made structures affecting the MDC. Satellite imagery from Google Earth, spanning from 2011 to 2022, reveals fluctuations in the MDC area, with notable afforestation efforts until 2018, followed by rapid degradation. The mangrove forest, initially covering ~ 2.2 ha in 2011, expanded to 3.2 ha by 2015 due to mangrove planting efforts. However, subsequent years witnessed a decline, with the area diminishing to 1.7 ha by June 2022. Human-made structures, specifically a nonstandard road and its relevant bridge construction in 2018, are identified as the main potential cause of mangrove degradation by obstructing freshwater flow from upper areas. Drone-based observations conducted on March 2023, provided a detailed map revealing that ~ 44% of healthy mangroves are damaged. However, field measurements performed on November 2023, revealed higher salinity levels at MDC stations than at other adjacent mangrove areas (Nayband and Melgonzeh). The principal component analysis (PCA) showed that the first two principal components explained a significant portion (99.7%) of the variability in the environmental data. Specifically, the first principal component represented variations in water temperature, accounting for 93.2% of the observed environmental variability. On the other hand, the second principal component was associated with salinity and dissolved oxygen concentrations, explaining 6.5% of the observed variability. This multidimensional approach enhances our understanding of the complex interactions influencing mangrove ecosystems.

Coastal Ecosystems

Coastal Management

Anthropogenic Effects

Google Earth

Dayyer City

Drone

Mangroves are a taxonomically varied group of halophytic (salt-tolerant) shrubs and trees that occur in the space between high and low tides on tropical and subtropical shorelines, a harsh and highly dynamic environment that presents exceptional challenges to the species that inhabit them (Hogarth 2015; Primavera et al. 2018; Spalding et al. 2010; Tomlinson 2016). Mangrove forests are unique ecosystems that occur in the intertidal zones of tropical and subtropical coastlines. Mangrove forests are unique coastal ecosystems that depend on a delicate balance of freshwater and seawater to sustain their health and biodiversity. The influx of freshwater is crucial for reducing salinity levels and providing essential nutrients, while seawater delivers vital minerals and supports tidal flushing, which helps prevent the buildup of toxins. The mechanism by which seawater and freshwater water interact in mangrove ecosystems is complex and involves several factors. One of the key mechanisms by which seawater and freshwater interact in mangrove ecosystems is through the process of tidal inundation (Wolanski et al., 1992). Tidal inundation occurs when seawater flows into mangrove forests during high tides and then recedes during low tides, leaving behind a mixture of seawater and fresh water (Kumbier et al., 2021). This process helps to maintain the salinity levels of the mangrove ecosystem within a range that is tolerable for the growth and survival of mangrove species. Another important mechanism is the exchange of water between the mangrove ecosystem and surrounding freshwater sources, such as creeks, rivers and streams (Bunt et al., 1982). In some cases, freshwater inputs may be the dominant source of water for mangrove ecosystems, while in other cases, seawater may be the dominant source. The balance between freshwater and seawater inputs is critical for maintaining the salinity levels of mangrove ecosystems (Santini et al., 2015).

Generally, mangrove forests worldwide are decreasing at an increasing rate of one to two percent per year, particularly in developing countries, which host 90% of the world's mangrove forests (Duke et al., 2007). Almost one-third of the world's mangrove forests have vanished between 1950 and 2000 (Alongi, 2002). It is estimated that annual mangrove forest loss averaged 0.26–0.66% globally between 2000 and 2012 (Hamilton and Casey, 2016). Studies indicate that these forests respond quickly to short-term environmental changes; thus, in the short term, in addition to being highly vulnerable, they also possess great potential for growth and expansion given suitable environmental conditions or direct and indirect human interventions. For instance, some countries, such as Puerto Rico, Guinea, Bangladesh, Australia, and India, have experienced little change in the extent of mangroves or even witnessed their expansion (FAO 2007; De Boer 2002).

The global extent of mangrove forests is reportedly ~ 15.2 × 10⁶ ha distributed across 55 countries worldwide (Giri et al. 2011; Friess et al., 2019). In Asia, only 14 countries harbor substantial areas of these forests. Iran's mangroves rank 43rd globally and tenth in Asia in terms of area (Mahmoudi et al., 2022). Iran's mangroves constitute 0.2% of the mangroves in Asia and 0.08% of those in the world (Zahed et al. 2010; Hamzeh and Lahijani, 2022). The mangrove species in Iran include Avicennia marina (A. marina) (gray mangrove) and Rizophora mucronata (loop-root mangrove). Most of Iran's mangroves are located in marine national parks and protected areas, primarily along the gentler and calmer coasts of the western Strait of Hormuz. The mangrove habitats of Iran extend between the northern latitudes of 25 and 30 degrees, making them the northernmost border of mangrove forests globally and rendering them highly valuable. The mangrove forests in Bushehr Province in the vicinity of Nayband Bay, Dayyer City, and the village of Melgonzeh mark the last feasible growth areas of these forests. Of all the mangrove species described, only A. marina naturally occurs on the coasts of the Bushehr Province. These areas represent the ultimate climatic tolerance limits for mangrove shrubs and trees (Schile et al., 2017). These mangrove forests, the last distribution area of these rare habitats on the northern Persian Gulf, constitute the last global distribution range of mangroves on the northwestern shores of Asia. These habitats have lower biological productivity and biomass than mangroves in moist tropical regions globally and are more sensitive to climate change and human impacts (Ghobadi et al., 2055; Etemadi et al., 2018; Adame et al., 2021). Climate change, in addition to human impacts, can have irreversible effects on Iran's mangrove habitats, particularly in Bushehr Province, serving as an amplified stressor (Beni et al., 2021; Etemadi et al., 2021; Ghafarian et al., 2022).

While mangrove forests face multiple challenges, conservation efforts, community involvement, and sustainable management practices can help mitigate these threats and contribute to the preservation and restoration of these critical ecosystems. The regular assessment of mangrove ecosystems is crucial for conservation, sustainable management, and the well-being of both natural environments and the human communities that depend on them. In particular, helping an endangered mangrove ecosystem involves a combination of conservation efforts, community involvement, and sustainable practices. For instance, supporting conservation organizations, participating in mangrove planting programmes, educating the community, participating in clean-up events, monitoring and reporting illegal activities, and engaging with local authorities are some ways to contribute to the protection and restoration of endangered mangrove ecosystems.

Considering the aforementioned information regarding the significance of mangrove forests, especially those situated in the northern Persian Gulf, this study aimed to assess the factors contributing to the disappearance of a small mangrove forest located in Dayyer City in the northern Persian Gulf. To achieve this goal, various data sources have been compiled, including multitemporal satellite images (obtained from Google Earth), in situ field observations, and drone-based photography and mapping. Satellite imagery has been utilized to estimate variations in mangrove areas between 2011 and 2023 and to monitor the development of humanmade structures near the study area. Field observations and measurements, encompassing on-site photography and other methods, serve as evidence to uncover the reasons behind the destruction witnessed in the nominated mangrove ecosystem. Additionally, drone-based photography has facilitated the construction of an accurate, detailed map of mangroves, enabling an evaluation of their current health status. By correlating the gathered data with human-generated construction and activities, this research has highlighted the primary sources of destructive factors. Finally, several solutions have been proposed to address and mitigate the stressors impacting these affected mangrove ecosystems.

2.1. Study area

The study area for this research is a small mangrove forest in the eastern area of Dayyer City (hereafter, MDC) located in the northern Persian Gulf (Fig. 1, a). Our on-site observations and other studies revealed that A. marina is the sole mangrove species in the MDC (Zahed et al., 2010). The predominance of this species in Iranian mangroves is due to its resilience to temperature and salinity variations in these regions (Zahed et al., 2010). These shrubs and trees are generally present in areas close to the coastline in the lower intertidal zone under the influence of tidal currents. The MDC occurs within the limits of Dayyer City and is only 811 m away from the nearest residential area, while no permanent river or creek flows into the MDC (Abedi and Jalili, 2016). However, Bardestan Creek, with a width of ~ 90 m and a length of ~ 45 km on the eastern side, is located 5.1 km away from this mangrove habitat (Abedi, 2015) (Fig. 1, b). Floods from upstream valleys, which flow during the rainy season, constitute the only route for freshwater to enter the MDC. These floodwaters also bring a certain amount of sediment into the MDC, leading to a reduction in the salinity or electrical conductivity (EC) of this mangrove habitat. Due to the geographic location of the MDC in the subtropical high-pressure zone, the climate of this habitat is characterized by extreme aridity, with ~ 200 mm of annual rainfall.

Figure 1

2.2. Collecting the data and information

2.2.1. Satellite-based data

The images extracted from Google Earth (GE) are the source of satellite-based data for this study. In this regard, the GE Pro version was used. 7.3.4.8642 was utilized to extract high-resolution true color composite (TCC) satellite images. Compared to the free version of GE, the GE Pro can increase the image resolution up to 8192×8192 pixels when saving images. This means that after zooming in on the desired area, it is possible to save a high-resolution TCC in the form of a jpg file. Moreover, there is a tool called "show historical imagery" that enables us to navigate between acquisition dates using a time slider, allowing us to view and save the TCC for various dates. It should be noted that the number of available data is limited and is related to the significance of the area. Notably, the high-resolution images that provide the data for GE became available after September 24, 1999, when the Ikonos satellite was launched. The spatial resolutions of Ikonos for the multispectral and panchromatic bands are 4 m and 1 m, respectively. This indicates that a pansharpened TCC with a 1-meter resolution can be generated from these data. However, after launching the QuickBird satellite on October 18, 2001, and Worldview-2 on October 8, 2009, the resolution increased to 0.6 m and 0.3 m, respectively. Particularly for the MDC area, the first available high-resolution image is from February 2011, and the most recent image is from June 2022 (as of the preparation of this paper). Based on the abovementioned information, since the main destructive human activities close to the MDC began in 2018, the necessary number of images with the highest spatial resolution (0.3 m) was available for extraction.

Accordingly, after downloading the necessary images, they must be georeferenced before they can be utilized for further analysis. For this purpose, Esri ArcGIS software was used to manually analyze the geo-registered images. In doing so, certain key points were selected on the images, and their coordinates were extracted from GE and subsequently entered into the software. To facilitate metric analysis of the subsequent steps, the metric coordinate system (UTM Zone-39) was chosen for both image extraction and georeferencing in ArcGIS. The affine polynomial transformation has been selected as the method because it is appropriate for cases where the input and output images have the same geometry. In this approach, a minimum of 6 points must be entered into the software. However, to improve the accuracy and precision of the geo-registered images, we used 10 reference points for all the images. Consequently, the georeferenced images were exported in the form of geotagged JPG files, which can be utilized for further analysis.

In the final step of the analysis of the satellite-based data, they were employed for monitoring and determining changes in mangroves in the MDC and for evaluating human activities close to the MDC. Since the spectral properties of healthy mangroves and damaged mangroves on TCC images are quite different, a simple classification procedure can be applied to differentiate them on the images. In this regard, the nearest neighborhood classifier in ArcGIS was used to classify the TCCs and, accordingly, to determine the mangrove areas on different dates.

2.2.2. Drone-based photography

Aerial photography has demonstrated its ability to precisely map coastal and nearshore habitats (Kabiri et al., 2014; Miraki et al., 2023). In this regard, the utilization of low-cost drones is one of the most common and accessible methods in these areas, where flights are typically safe and may yield precise and reliable results. The main purpose of utilizing drone in this research was to generate a precise thematic map from the mangroves of studied area. The drone was used to capture high-resolution images of the mangrove forest, allowing for detailed mapping of healthy and damaged mangrove areas. Assessing the extent of mangrove damage by analyzing the drone-captured images enabled us to quantify the percentage of healthy mangroves that were damaged. This quantitative assessment provided valuable insights into the severity of mangrove degradation in the MDC. Accordingly, on March 7, 2023, a flight was carried out in the MDC using a DJI™ Phantom 4 Pro drone. This consumer-grade drone is equipped with GPS/GLONASS for precise positioning and features a standard RGB camera capable of capturing geotagged photos at 20 megapixels (5472×3648 pixels) (additional details about the drone can be found at https://www.dji.com/global/support/product/phantom-4-pro).

Several mobile-based applications are available for conducting planned and automated flights to capture mosaic photos using drones. In this research, Pix4Dcapture®, a free drone flight planning mobile app, was used to conduct the flight over the selected area. Its precision, reliability, flexibility, and feasibility allow for the arrangement of an automated flight by adjusting parameters such as flight altitude, image overlap, and area of interest. A polygon mission plan was created for the selected study area (Fig. 2), with the flight altitude set at 150 meters, resulting in a final ground sampling distance (GSD) of ~ 4 cm. This level of resolution enables the visual identification of objects 40×40 centimeters (10×GSD) in length in the photos, which is adequate for assessing the mangroves condition in the studied area (Kabiri, 2020). Considering the aforementioned details, an area of ~ 48 ha (600×800 meters), encompassing the entire MDC, was designated within the app for drone flight (Fig. 2). During a 16-minute flight, a total of 201 overlapping photos were captured from the area, from takeoff to the drone's landing.

Further processing began with the utilization of Agisoft™ Metashape Pro, a precise software package, to generate an orthophoto mosaic from the captured photos. Metashape offers five accuracy levels for photo alignment, with the highest level demanding more processing time. For this study, the highest accuracy level was selected due to the limited number of photos and confined area. A digital elevation model (DEM) was produced beforehand prior to the creation of the orthophoto mosaic. The final step involved the creation and exportation of the orthophoto mosaic in GeoTIFF format, encompassing geo-registration information for further analysis in ArcGIS software. Like in satellite-based data, the spectral differences between healthy and damaged mangroves in the mosaic prompted the utilization of the nearest neighborhood classifier in ArcGIS. This classification aided in estimating the areas occupied by both healthy and damaged mangroves within the mosaic.

Figure 2

2.2.3. Field observations/measurements and analysis

The main field measurements conducted for this study involved collecting temperature, salinity, and dissolved oxygen (DO) data using a HACH® portable multimeter (HQ40d) on November 24, 2023. Although the primary focus was on studying the MDC situation, we also gathered samples from the Nayband and Melgonzeh mangrove forests to compare the ecological conditions of these habitats with those of the MDC area (Fig. 3). These measurements were initially taken specifically for the MDC, allowing us to assess its current condition compared to its state before the onset of destructive humanmade activities. Additionally, field observations encompassed on-site visits and photography of the MDC and its surrounding areas, especially the affected mangroves.

The similarity matrices of the environmental variables were calculated as the normalized Euclidean distance. Variations in the ecological dataset were explored using principal component analysis (PCA). The primary goals of this analysis were to identify the main environmental gradients occurring during our study (Legendre and Legendre, 1998). The analyses were performed using the PRIMER v6 statistical package (Clarke and Gorley, 2006) and the PERMANOVA + PRIMER add-on package (Anderson et al., 2008).

Figure 3

3.1. The outputs of satellite-based data

The variation in the MDC area was determined as a primary output obtained from the analysis of satellite-based data. Figure 4 shows the MDC area for different years between 2011 and 2022. It should be noted that these areas are healthy, green, and nonaffected mangroves in the MDC. As shown in this figure, this area was ~ 2.2 ha in 2011 (Fig. 4a) and then increased to ~ 3.2 ha in 2015 (Fig. 4b). This increase was mostly due to the mangrove hand-planting programmes conducted by NGOs and local people and activists and, consequently, to the afforestation of MDC during these years (Mahmoudi and DanehKar, 2023). However, it seems that the afforestation plan was successful where the MDC area remained almost the same until 2018 (Fig. 4c). The area then decreased from ~ 3.1 ha in July 2018 (Fig. 4c) to ~ 2.4 ha in November 2018. This reduction was then amplified and continued until June 2022 (the last available satellite-based data on the date of preparation of this paper), when the area of nonaffected mangroves reached ~ 1.7 ha (Fig. 4d to 4i). For a better understanding of the procedure, the abovementioned variation in the MDC area is shown as a graph in Fig. 4j.

Figure 4

To monitor and investigate the reasons for this degradation in the MDC area after July 2018, other satellite-based data were produced in this study to detect and investigate human-made structures in the area around the MDC. Figure 5 illustrates these activities on 6 dates between July 2018 and June 2022. As shown in this figure, there was no noticeable activity in human-made construction around the MDC in July 2018 (Fig. 5a); thus, the first step of these kinds of activities was observed in the image for September 2018 (Fig. 5b and 5c). This means that the construction of a bridge started between the abovementioned dates to implement a road for access to the shrimp farming area that was constructed later. Our field observations showed that after the construction of this bridge, the flow of freshwater from the upper area to the MDC was blocked, after which the degradation of mangroves started. This phenomenon is visible in Fig. 5e, where sediments are observable behind the constructed bridge; i.e., the path of freshwater is blocked by construction. Figure 5f also shows this blocking where it seems that seawater (which comes up due to the tide) could not cross the constructed bridge. Moreover, this figure shows that the shrimp farming area was developed in March 2021, when it did not exist in December 2020. It should be mentioned that thus far, there is no convincing evidence that the construction of this shrimp farm has a direct impact on the MDC area (because it has not yet been fully launched), but the destructive influence of nonstandard roads and their relevant bridges on this area is undeniable.

Figure 5

3.2. The results of drone-based photography

The main output of drone-based observations in the MDC is a precise topologic and thematic map of mangroves (healthy and damaged) and other surrounding features and habitats (Fig. 6a). This map provides detailed information about the current situation of mangrove shrubs and trees in the MDC. As shown in Fig. 6a, unfortunately, a large number of mangroves were completely or partially damaged. For a better understanding of the amount of remaining healthy shrubs and trees, Fig. 6b shows the canopies that covered an area of ~ 18070 m². This means that, when comparing the optimum situation of healthy mangroves before destructive human activities begin, ~ 44% of them are damaged. As shown in Fig. 6a, most of the damaged mangroves occurred in areas distant from the adjacent wetland where sufficient freshwater could not be received due to decreased water input resulting from the construction of the aforementioned roads and bridges.

Figure 6

3.3. The results of field observations and measurements

Three main environmental factors, namely, wide seasonal variation in temperature, high seawater salinity, and DO conditions, were measured in the present study. The measured environmental parameters at the six aforementioned stations are shown in Table 1. As shown in this table, the amount of salinity at both stations located in the MDC was greater than that at the stations in the Melgonzeh and Nayband.

Principal component analysis (PCA) revealed comparable ranges of environmental conditions among the sampled stations (Fig. 7). The first two principal components in the PCA explained 99.7% of the variability in the environmental data. The PCA revealed a gradient (PCA axis 1, 93.2% of the observed environmental variability) related to the water temperature. The independent second PCA axis gradient (PCA axis 2, 6.5% of observed environmental variability) was associated with salinity and dissolved oxygen (DO) concentrations. The salinity was negatively related to the DO concentration along this axis. The results of this study showed that the environmental conditions at the sampled stations were comparable between the mangrove habitats. Based on the measurements and PCA results, the mangrove regions were separated according to their environmental parameters.

It seems that human impacts and construction around mangrove forests, especially roads and access roads, have prevented the passage of freshwater during the rainy season and increased the salinity of the water in these habitats compared to those in other sampled habitats. High evaporation rates also result in extreme salinity in MDCs. The MDC has suffered negative impacts due to structures interfering with natural sedimentation processes and water circulation or depleting freshwater resources (Khan and Kumar 2009; Lokier et al. 2018; Paleologos et al. 2019). High salinity is known to have significant impacts on the growth and structure of mangroves, often resulting in stunted ‘dwarf’ trees and shrubs; thus, A. marina in the MDC rarely exceeds 4–6 m (Embabi 1993; Moore et al. 2014), while it can reach 14 m in tropical environments.

Table 1

The measured environmental parameters at six stations in the Melgonzeh, Dayyer, and Nayband mangrove habitats.
Station	Depth (m)	Temperature (^oC)	Salinity (psu)	Dissolved Oxygen (mg/l)
1M	0.50	23.50	39.80	6.30
2M	0.75	23.60	40.00	6.20
1D	0.50	24.10	40.50	6.33
2D	0.75	24.13	41.00	6.23
1N	0.50	22.26	39.33	5.86
2N	0.50	22.10	39.00	5.73

Figure 7

3.4. The pros and cons of applied approach

By integrating data from multiple sources (satellite, drone, field), this study offers a comprehensive understanding of the mangrove ecosystem, including changes over time, human impacts, and environmental parameters. The use of high-resolution satellite and drone imagery allows for detailed analysis and mapping of mangrove areas, including identifying healthy and damaged mangroves. moreover, conducting field measurements provides empirical data on environmental parameters such as temperature, salinity, and dissolved oxygen, enriching our analysis and supporting the findings. On the other hand, while the study spans from 2011 to 2022, the availability of high-resolution satellite imagery before 2001 is limited. Drone-based photography relies on flight planning, image capture, and processing, which may introduce biases or errors if not conducted rigorously. While field measurements provided valuable empirical data, the number of sampling stations and measurements may be limited. However, this study identifies human-made structures as a primary driver of mangrove degradation, other confounding factors (e.g., climate change and natural disturbances) may also influence mangrove dynamics. Considering and addressing these potential confounders could strengthen the interpretation of the results.

This study provides a comprehensive examination of the ecological dynamics of a unique mangrove forest near Dayyer City (MDC) in the northern Persian Gulf. Employing satellite-based data, drone-based photography, and field measurements/observations, we assessed changes in mangrove areas, investigated human-made structures affecting the MDC, and analyzed environmental parameters. The satellite imagery extracted from Google Earth between 2011 and 2022 revealed notable fluctuations in the MDC area, reflecting successful afforestation efforts until 2018 and rapid degradation after 2018, when human-made activities started. The construction of a nonstandard road and bridge in 2018 emerged as a significant factor contributing to mangrove degradation by obstructing freshwater flow from upper areas. Our drone-based observations in 2023 confirmed that, compared to the optimum situation of the MDC, ~ 44% of healthy mangroves were damaged. Field measurements revealed elevated salinity levels at the MDC stations compared to those at adjacent mangrove areas. Principal component analysis (PCA) also demonstrated differences in the environmental conditions of the MDC compared to those of the two habitats sampled (Nayband and Melgonzeh). This multidimensional approach enhances our understanding of the complex interactions influencing mangrove ecosystems, offering valuable insights for conservation and management strategies in the face of anthropogenic pressures.

In summary, our research highlights the critical need to address human-induced threats to mangrove ecosystems. The MDC's history of afforestation success followed by rapid degradation underscores the vulnerability of these ecosystems to human activities. The multidimensional approach adopted in this study provides a general perspective on the factors influencing mangrove health. Urgent conservation and management strategies are essential for mitigating the impact of anthropogenic pressures and ensuring the survival of mangrove ecosystems in the face of environmental challenges. This study serves as a foundation for future research and conservation efforts in the region, emphasizing the importance of preserving these vital coastal habitats.

Finding

This research was supported by the Pars Special Economic Energy Zone [contract no. 00-10-052] to E.A. and the Iran National Science Foundation [grant no. INSF-99031644] to K.K.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contribution

All authors contributed to the study conception and design. Field observations, data collection and analysis were performed by Keivan Kabiri and Ehsan Abedi. Remote sensing and drone-based analyses were conducted by Keivan Kabiri and PCA analyses were executed by Ehsan Abedi. The first draft of the manuscript was written by Keivan Kabiri and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Acknowledgement

The authors thank N. Ghasemi for his kind collaboration with the field observations in Dayyer City.

Data Availability

Data is provided within the manuscript or supplementary information files

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No competing interests reported.

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Ecological Dynamics and Human Impact Assessment of a Small Mangrove Forest in the Northern Persian Gulf: A Multidimensional Approach Using Satellite-derived, Drone- based, and Field-measured Data

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Version 1

Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Study area

2.2. Collecting the data and information

2.2.1. Satellite-based data

2.2.2. Drone-based photography

2.2.3. Field observations/measurements and analysis

3. Results and Discussion

3.1. The outputs of satellite-based data

3.2. The results of drone-based photography

3.3. The results of field observations and measurements

3.4. The pros and cons of applied approach

4. Conclusion and summary

Declarations

Finding

Competing Interests

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

Status:

Version 1