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Bathymetry Time Series Using High Spatial Resolution Satellite Images

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and water ecosystem complexity.


Introduction
The issues of hydro-sedimentary processes in lagoons, estuaries, and enclosed bays are important in terms of coastal management, because they are generally characterized by a strong human presence that results in the release of contaminants and large quantities of nutrients into the ecosystem [1]. There are many methodologies to study the nutrients in ecosystems; one of them, possibly the most used, is the three-dimensional (3D) numerical model.
In the Mar Menor lagoon, ROMS has been used to evaluate the water renewal conditions, and a time series spanning a period longer than one year (between 2010 and 2012) provides a record of the seasonal variability of the lagoon hydrodynamics, which was used to validate the hydrodynamic model implemented [24]. SHYFEM has been used to compare the water exchange and mixing in 10

Study Area
The Mar Menor is a hypersaline lagoon with a surface area of 135.76 km 2 , a volume of about 0.65 × 10 9 m 3 , and a maximum depth of 7 m-located in the SE of the Iberian Peninsula, between the parallels 37 • 38 and 37 • 50 North latitude and the meridians 0 • 43 and 0 • 57 West longitude. There are five open channels or "golas" connecting the Mar Menor lagoon and the Mediterranean Sea. These can be seen in Figure 1c. The Encañizadas area is located at the north end of La Manga, on the southern edge of the Salinas de San Pedro Regional Park, and is made up of a group of small islets, surrounded by large flooded areas crossed by a network of shallow channels. Due to its morphology, it experiences periodic waterlogging related to tidal flows and changes in atmospheric pressure; historically, its topography and hydrology have been modified for the conditioning of fishing apparatus, known as "Encañizada". Currently, there are three open inlets (El Ventorrillo, La Torre, and El Charco) and one channel closed by a floodgate since 1980 (New); the Estacio channel was an ancient "Encañizada" drained for the construction of the port of Tomas Maestre in 1973 and is currently the deepest (5 m; Figure 1d); and the Marchamalo channel was an old artificial "Encañizada" that never worked due to its tendency to fill with sediments ( Figure 1e) [76]. Currently, it is a navigable but has a shallow channel (1 m).
The Mar Menor lagoon was created by a sequence of consecutive oscillations of the sea level that occurred in the Quaternary. It is located at the bottom of a river basin bordered by mountains that enclose the Campo de Cartagena, a vast plain of 1350 km 2 with a low inclination to the SE. The contribution of continental water is made up of six watercourses, which are dry most of the year and contribute to the natural process of filling the Mar Menor lagoon [77]. In relation to this, the most outstanding geomorphological elements determining the dynamics of the lagoon are the sand barrier, continuous shore, islands and volcanic outcrops, and underwater area of the Mar Menor lagoon [77,78].
The erosion factors are mainly natural driving forces-winds, storms, waves, and a rise in sea level. The sand barrier was created by marine currents and the effect of the wind and waves. This effect is the reason why the Encañizada gola bottom is moving and changing [25,79]. The exchange between Mediterranean and lagoon waters can be affected because of changes in the inlet's geomorphology, and these changes can affect the biological productivity, the species richness, and the complexity of the lagoon communities [80][81][82], and, therefore, affecting the environmental and economic balance of this area. Precise knowledge of the spatio-temporal evolution of the opening of this golas is very useful to improve the results of the hydrodynamic models that are being implemented for the Mar Menor lagoon and its connection with the Mediterranean Sea. According to the work of the Technical University of Cartagena (UPCT) [24], the "El Estacio" channel is the most important in the regulation of the water exchange of the Mar Menor lagoon, since it accounted for 60% of the total annual volume interchanged at that time (2010-2011), while the "Encañizadas" channel contributed 33% and the "Marchamalo" channel the remaining 7%. However, the Encañizadas can account for up to the 80% if the net balance is considered [25]. These percentages have significant seasonal fluctuations depending on the sand deposits caused by the storms in the area and the maintenance work that is carried out regularly on the golas. The water renewal rate of the volume of the Mar Menor lagoon has been calculated as 318 days [27], although this can be very variable depending on the weather conditions and freshwater inputs due to runoff or groundwater discharge [83].
Water 2020, 12, x FOR PEER REVIEW 4 of 29 the complexity of the lagoon communities [80][81][82], and, therefore, affecting the environmental and economic balance of this area. Precise knowledge of the spatio-temporal evolution of the opening of this golas is very useful to improve the results of the hydrodynamic models that are being implemented for the Mar Menor lagoon and its connection with the Mediterranean Sea. According to the work of the Technical University of Cartagena (UPCT) [24], the "El Estacio" channel is the most important in the regulation of the water exchange of the Mar Menor lagoon, since it accounted for 60% of the total annual volume interchanged at that time (2010-2011), while the "Encañizadas" channel contributed 33% and the "Marchamalo" channel the remaining 7%. However, the Encañizadas can account for up to the 80% if the net balance is considered [25]. These percentages have significant seasonal fluctuations depending on the sand deposits caused by the storms in the area and the maintenance work that is carried out regularly on the golas. The water renewal rate of the volume of the Mar Menor lagoon has been calculated as 318 days [27], although this can be very variable depending on the weather conditions and freshwater inputs due to runoff or groundwater discharge [83].

In Situ Depth Data Points Obtained Using an Unmanned Surface Vehicle (USV)
The Murcia Institute of Agri-Food Research and Development (IMIDA) is working with two types of USV, developed with different aims: An Unmanned Surface Water Vehicle (USWV) to study bathymetry in shallow water, and a Remotely Operated Underwater Vehicle (ROV) to study water quality and the lagoon bottom.
These drones are based on ArduPilot or ArduPilotMega (APM). The latter is an autopilot of free code used in the control of several types of drones, such as unmanned helicopters, unmanned aircraft, and unmanned aquatic vehicles. In recent years, more and more unmanned automatic data acquisition equipment has been applied to ocean observation, and the USWV is one example. Due to its high degree of automation and flexibility, it can be applied to the surveying and mapping of water depth. The Massachusetts Institute of Technology has developed a prototype ARTEMIS [84]; it is a small unmanned sounding vessel used in water-depth measurement. This idea has been

In Situ Depth Data Points Obtained Using an Unmanned Surface Vehicle (USV)
The Murcia Institute of Agri-Food Research and Development (IMIDA) is working with two types of USV, developed with different aims: An Unmanned Surface Water Vehicle (USWV) to study bathymetry in shallow water, and a Remotely Operated Underwater Vehicle (ROV) to study water quality and the lagoon bottom.
These drones are based on ArduPilot or ArduPilotMega (APM). The latter is an autopilot of free code used in the control of several types of drones, such as unmanned helicopters, unmanned aircraft, and unmanned aquatic vehicles. In recent years, more and more unmanned automatic data acquisition equipment has been applied to ocean observation, and the USWV is one example. Due to its high Water 2020, 12, 531 5 of 28 degree of automation and flexibility, it can be applied to the surveying and mapping of water depth. The Massachusetts Institute of Technology has developed a prototype ARTEMIS [84]; it is a small unmanned sounding vessel used in water-depth measurement. This idea has been developed into different types of small unmanned ships, boats, or catamarans [85][86][87], such as the IMIDA06 USV [88] used in this study ( Figure 2).
Water 2020, 12, x FOR PEER REVIEW 5 of 29 developed into different types of small unmanned ships, boats, or catamarans [85][86][87], such as the IMIDA06 USV [88] used in this study ( Figure 2). The drones were used to perform the bathymetric work in five coastal areas of the Mar Menor lagoon and in the three channels of communication with the Mediterranean Sea ( Figure 3). Special attention was given to the Encañizadas channel, where seven bathymetries have been performed in the last 10 years by different Spanish organizations (Table 1)

Satellite Data
The images used in this work were provided by Airbus (Table 2) and correspond to the Pleiades satellites successfully launched on 16 December 2011. These are two optical satellites: Pleiades-1A and Pleiades-1B. Their orbits are differentiated by a 180° separation and they work together to provide daily images from anywhere on the planet. The Pleiades sensors have a nominal swath width of 20 km at nadir and two spectral configurations ( Figure 4): a panchromatic configuration, with a spatial resolution of 0.5 m, and a multispectral configuration: visible (VI) and near infrared (NIR), both with a spatial resolution of 2 m.
The physical model used in this project (Appendix A) is based in the premise that the relationship between the water-leaving reflectance just above the surface R(0+,λ) and the water-leaving reflectance just below the surface R(0−,λ) is constant. The water-leaving reflectance just below the surface is a lineal combination reflectance from the water column and reflectance from the bottom. The water is clear; thus, the energy arrives from the bottom through the water column and the water column is homogenous [89]. The relationship between the water-leaving reflectance and the depth is z = m· + n where m and n do not vary with depth (they are constant when the properties of the water column and the bottom are constant, too), but RBlue and RGreen do vary [60,90], since they are the reflectances below the surface with bottom influence and the reflectance below the surface without bottom influence (that is, in deep water), respectively.

Satellite Data
The images used in this work were provided by Airbus (Table 2) and correspond to the Pleiades satellites successfully launched on 16 December 2011. These are two optical satellites: Pleiades-1A and Pleiades-1B. Their orbits are differentiated by a 180 • separation and they work together to provide daily images from anywhere on the planet. The Pleiades sensors have a nominal swath width of 20 km at nadir and two spectral configurations ( Figure 4): a panchromatic configuration, with a spatial resolution of 0.5 m, and a multispectral configuration: visible (VI) and near infrared (NIR), both with a spatial resolution of 2 m.
The physical model used in this project (Appendix A) is based in the premise that the relationship between the water-leaving reflectance just above the surface R(0+,λ) and the water-leaving reflectance just below the surface R(0−,λ) is constant. The water-leaving reflectance just below the surface is a lineal combination reflectance from the water column and reflectance from the bottom. The water is clear; thus, the energy arrives from the bottom through the water column and the water column is homogenous [89]. The relationship between the water-leaving reflectance and the depth is where m and n do not vary with depth (they are constant when the properties of the water column and the bottom are constant, too), but R Blue and R Green do vary [60,90], since they are the reflectances below the surface with bottom influence and the reflectance below the surface without bottom influence (that is, in deep water), respectively.    In this study, 22 Pleiades images-taken between 15 October 2012 and 5 December 2019-were used ( Table 2) ( Figure A1).

LiDAR Data
The airborne laser imaging detection and ranging (LiDAR) data correspond to the Spanish National

LiDAR Data
The airborne laser imaging detection and ranging (LiDAR) data correspond to the Spanish National Plan of Aerial Orthophotography (PNOA) of 2009 and 2016, of the Spanish National Geographic Institute (IGN). A model ALS50 (Leica Geosystems AG, Heerbrugg, Switzerland) was used, with a low point density (0.5 points/m 2 ) but completely covering the Mar Menor lagoon. A digital surface model (DSM) was obtained by triangulation at a spatial resolution of 2 m. The LiDAR data ( Figures 5 and 6) were processed with LAStools (Rapidlasso GmbH, Gilching, Germany) and ArcGiS 10.7 (ESRI, Redlands, CA, USA) software.     [14] in 2016 (no data for a depth < −3 m, blue line).

Ground-Based Data
During the field experiment, the IMIDA06 USV ( Figure 2) used a sounding AIRMAR (Airmar Technology Corporation, Milford, CT, USA), a bi-frequency of 50/200 kHz, 600 W of power, and a GNSS receiver that synchronously collected water depth and position data with high accuracy. The GNSS RTK receiver was a GPS-GALILEO-GLONASS type and the horizontal positioning (for a Real Time Kinematic, RTK, model) was connected to the sounding data to get good depth and position data. Bathymetry is defined as the depth from the bottom to the zero value. In Spain (Royal Decree 1071/2007 Spanish law), the zero value is the sea surface in Alicante city (Spain). The measuring range is 0.5 m to 100 m and the accuracy is ±10 mm. The GNSS receiver was an Emlid Reach RS model (Emlid Ltd., Hong Kong, China), the horizontal positioning accuracy (in the RTK model) was  In order to obtain a detailed bathymetry of the seabed of the Mar Menor lagoon, the IEO and IHM carried out a data collection campaign from 26 April to 13 June 2017. The objective of this was to conduct a bathymetric analysis of the interior of the Mar Menor lagoon (at depths > 3 m) and a characterization of the seabed ( Figure 6) with the GeoSwath 500 Plus interferometric probe (Kongsberg Gruppen ASA, Kongsberg, Norway), with lateral scan sonar registers by IEO [43].

Ground-Based Data
During the field experiment, the IMIDA06 USV ( Figure 2) used a sounding AIRMAR (Airmar Technology Corporation, Milford, CT, USA), a bi-frequency of 50/200 kHz, 600 W of power, and a GNSS receiver that synchronously collected water depth and position data with high accuracy. The GNSS RTK receiver was a GPS-GALILEO-GLONASS type and the horizontal positioning (for a Real Time Kinematic, RTK, model) was connected to the sounding data to get good depth and position data. Bathymetry is defined as the depth from the bottom to the zero value. In Spain (Royal Decree 1071/2007 Spanish law), the zero value is the sea surface in Alicante city (Spain). The measuring range is 0.5 m to 100 m and the accuracy is ±10 mm. The GNSS receiver was an Emlid Reach RS model (Emlid Ltd., Hong Kong, China), the horizontal positioning accuracy (in the RTK model) was about 10 mm, and the vertical positioning accuracy about 20 mm. The USV was developed by Inntelia (IPH Ltd., Huelva, Spain). Table 3 presents the specifications of USV components. In the bathymetries of the three golas of December 2019, a floating drone was used with an Echologger ECT400S (EofE Ultrasonics Ltd., Kyounggi-Do, Korea), acoustic frequency of 450 kHz, sampling frequency of 100 kHz, width of the conical beam 5 • (±3 dB), precision of 1 mm, a receiver and GNSS RTK antenna (GPS, GALILEO, and GLONASS), as well as lithium polymer battery power. It was controlled manually with a UHF Radio Modem system with 1 W of power (+30 dBm) for connection and data transmission. The coordinates of the ground control points (GCP) were acquired through a traditional technique, by means of a Leica-Geosystems Station TPS1200 (Leica Geosystems AG, Hauptsitz, Heerbrugg, Switzerland).

Pre-Processing
Firstly, all images available were checked on OneAtlas (Airbus DS Geo, Toulouse, France); secondly, the decoding was done (Figure 7). Each type of image was downloaded applying a specific pre-processing ( Table 2). The first step finished when all images had been pre-processed. In remote sensing imagery, atmospheric correction can remove the atmospheric influence (mainly caused by atmospheric molecules and light scattering particles) and illumination factors. The target reflectance spectrum after correction will be similar to the ground-measured spectra [90][91][92].

Pre-Processing
Firstly, all images available were checked on OneAtlas (Airbus DS Geo, Toulouse, France); secondly, the decoding was done (Figure 7). Each type of image was downloaded applying a specific pre-processing ( Table 2). The first step finished when all images had been pre-processed. In remote sensing imagery, atmospheric correction can remove the atmospheric influence (mainly caused by atmospheric molecules and light scattering particles) and illumination factors. The target reflectance spectrum after correction will be similar to the ground-measured spectra [90][91][92].

Water Area
The water mask was generated using the normalized difference water index (NDWI), using green and infrared bands [93] in each reflectance image. From Figure 7, if NDWI is higher than 0, the pixel is water and if NDWI is less than 0, it is not water. Each water mask was applied to its reflectance image and all reflectance water images were obtained.

Water Area
The water mask was generated using the normalized difference water index (NDWI), using green and infrared bands [93] in each reflectance image. From Figure 7, if NDWI is higher than 0, the pixel is water and if NDWI is less than 0, it is not water. Each water mask was applied to its reflectance image and all reflectance water images were obtained.

Water Depth Extraction Model
Reflectance water images near in time to the bathymetric data were chosen to get linear algorithms [90]. The operations between bands were performed using ENVI 4.8 software. The relationship between the raster data and the sounding data was processed with ArcMap 10.7. The m and n values of the model were obtained by EXCEL software, as well as the statistical study. The bathymetry derived from satellite data was compared with the bathymetric obtained from field data, and the normalized root mean square error (RMSE) was analyzed. The bathymetry on each date was calculated using a water depth extraction model, and the water amount was obtained by multiplying the pixel size by the bathymetry.

Integration of Altimetry Data for the Mar Menor Lagoon
The bathymetric datasets were integrated in an ArcGiS 10.7 geodatabase containing the LiDAR data of two years (2008 and 2016). Using all the data, a DEM was generated with a spatial resolution of 2 m, to perform the volume calculation for each isobath (m) and thus to compute the volume (m 3 ) of the Mar Menor lagoon. The volume between each isobath was calculated, starting at the deepest level and finishing at the isobath corresponding to the maximum level of the Mar Menor lagoon. The final result corresponds to the height-volume relationship that is the current capacity curve. The applied methodology is represented in the flowchart in Figure 8.

Integration of Altimetry Data for the Mar Menor Lagoon
The bathymetric datasets were integrated in an ArcGiS 10.7 geodatabase containing the LiDAR data of two years (2008 and 2016). Using all the data, a DEM was generated with a spatial resolution of 2 m, to perform the volume calculation for each isobath (m) and thus to compute the volume (m 3 ) of the Mar Menor lagoon. The volume between each isobath was calculated, starting at the deepest level and finishing at the isobath corresponding to the maximum level of the Mar Menor lagoon. The final result corresponds to the height-volume relationship that is the current capacity curve. The applied methodology is represented in the flowchart in Figure 8. The Digital Terrain Model (DTM) was derived by triangulation from the spatial resolutions of 1 m (Figure 9, Appendix A). Considering the vertex of the National Geodetic Network closest to each reservoir, the supporting points were taken with bi-frequency GPS. The datasets were processed with ArcGiS 10.7 (ESRI, Redlands, CA, USA) software. Subsequently, the points cloud with known X, Y, Z coordinates was calculated in the official terrestrial space reference system (ETRS89) and in the official vertical spatial reference system in Spain (EVRS89), based on the Earth Gravitational Model (EGM2008) of the National Geospatial-Intelligence Agency (NGA) EGM Development Team. Subsequently, a Triangular Irregular Network (TIN) mesh was generated using ArcGiS 10.7 (ESRI, Redlands, CA, USA) and this was used to calculate the volume of the Mar Menor lagoon. The Digital Terrain Model (DTM) was derived by triangulation from the spatial resolutions of 1 m (Figure 9, Appendix A). Considering the vertex of the National Geodetic Network closest to each reservoir, the supporting points were taken with bi-frequency GPS. The datasets were processed with ArcGiS 10.7 (ESRI, Redlands, CA, USA) software. Subsequently, the points cloud with known X, Y, Z coordinates was calculated in the official terrestrial space reference system (ETRS89) and in the official vertical spatial reference system in Spain (EVRS89), based on the Earth Gravitational Model (EGM2008) of the National Geospatial-Intelligence Agency (NGA) EGM Development Team. Subsequently, a Triangular Irregular Network (TIN) mesh was generated using ArcGiS 10.7 (ESRI, Redlands, CA, USA) and this was used to calculate the volume of the Mar Menor lagoon.

Results
The results show that multispectral optical imagery with very high spatial (i.e., 0.5 m) and temporal (in this study, 22 images) resolution is suitable for the tracking of water-level fluctuations of the Mar Menor golas and shallows at a fine scale. The results are a function of the different steps of the project; these are summarized as follows: IMIDA06 USV has been developed by IPH and IMIDA and has provided a good bathymetry map (for 13 March 2017), with a spatial resolution of 50 cm and an error equal to ±3 cm (Figure 9).
The results show that multispectral optical imagery with very high spatial (i.e., 0.5 m) and temporal (in this study, 22 images) resolution is suitable for the tracking of water-level fluctuations of the Mar Menor golas and shallows at a fine scale. The results are a function of the different steps of the project; these are summarized as follows: IMIDA06 USV has been developed by IPH and IMIDA and has provided a good bathymetry map (for 13 March 2017), with a spatial resolution of 50 cm and an error equal to ±3 cm (Figure 9). The NDWI values allow to evaluate the change of the water body and golas, as well as the annual movement of sediments and land area ( Figure 10, Appendix A). At the same time, the Water Depth Extraction Model [90] allows to obtain a bathymetric map from different satellite images and the parameters of this model (m and n). These parameters are not constant and depend on the water clarity ( Figure 11). At the same time, the Water Depth Extraction Model [90] allows to obtain a bathymetric map from different satellite images and the parameters of this model (m and n). These parameters are not constant and depend on the water clarity ( Figure 11). At the same time, the Water Depth Extraction Model [90] allows to obtain a bathymetric map from different satellite images and the parameters of this model (m and n). These parameters are not constant and depend on the water clarity ( Figure 11). The relationship between both methods showed a good fit. On one hand, the slope of the regression is close to 1 (0.84 in the case of low transparency and 1.02 with clear waters), indicating the accuracy of the satellite image estimations and field data. The RMSE was analyzed at three different dates ( Figure 12): one, five, and ten days of difference between the field data and the image.  The relationship between both methods showed a good fit. On one hand, the slope of the regression is close to 1 (0.84 in the case of low transparency and 1.02 with clear waters), indicating the accuracy of the satellite image estimations and field data. The RMSE was analyzed at three different dates ( Figure 12): one, five, and ten days of difference between the field data and the image.     The bathymetry, the barometric pressure, and the wind of the Mar Menor are responsible for the currents and therefore for the distribution of sediments in the lagoon. Therefore, an updated and high-resolution bathymetric characterization is especially important in order to know its evolution and its dynamics at different spatio-temporal scales. In addition, an accurate bathymetry is decisive to know the total volume of water in the lagoon and for hydrodynamic calculations, relevant to the determination of the water exchanges between Mar Menor and the Mediterranean Sea, through the The bathymetry, the barometric pressure, and the wind of the Mar Menor are responsible for the currents and therefore for the distribution of sediments in the lagoon. Therefore, an updated and high-resolution bathymetric characterization is especially important in order to know its evolution and its dynamics at different spatio-temporal scales. In addition, an accurate bathymetry is decisive to know the total volume of water in the lagoon and for hydrodynamic calculations, relevant to the determination of the water exchanges between Mar Menor and the Mediterranean Sea, through the three active golas. Mar Menor is a coastal lagoon with a high degree of hydrodynamic confinement and, as such, is the final recipient of all the transport processes that take place in the large (1350 km 2 ) watershed of Campo de Cartagena. The soil uses in the coastal area has undergone significant transformations in the last decade, which have contributed to the acceleration of these transport processes and, consequently, the bottom of the lagoon have experienced an increasing accumulation of sediments ( Figure 15        Mar Menor underwent a generalized silting up (an average of +18 cm) between 2008 and 2016, mainly the result of sediment contributions due to the very frequent extreme precipitation events [47].  [48] by applying the SQRT-ETmax cumulative distribution function.

Discussion
The deployment of an IMIDA06 USV is an example of how the free disposition of research findings can stimulate scientific advances, with the contribution of anyone, anywhere in the world. The images and their distribution are low-cost, which has allowed the development of new prototypes that, in turn, will be surpassed by novel work. Now it is necessary to take advantage of the developments from the recent years and make them useful to the community. In this sense, the IMIDA06 USV, as a source of field data, has allowed the development of a satellite image tracking system that is able to provide valuable data that helps solve environmental, social, and economic problems.
The Mar Menor lagoon and its area of influence is a complex and dynamic environmental, economic, and social system [94]; therefore, distinct types of information are necessary for its good management. The use of 3D numerical models represents a solution to obtain data and predict situations in the short term. However, model inputs condition the results and, therefore, special attention should be paid to their accuracy and precision; e.g., the initial conditionals (Xo, Yo, Zo) have to be precise enough. Remote sensing provides information on large coastal water bodies, such as the Mar Menor lagoon, besides providing good precision for Xo and Yo. However, knowing the depth, even in the shallowest waters, requires transparent waters that allow the sunlight to reach and be reflected by the bottom.
The initial idea was to use an unmanned aerial vehicle or unscrewed aerial vehicle (UAV), but in this area the use of a UAV is prohibited due to military activities. However, it is possible to use high spatial resolution satellite images to obtain a real-time bathymetry with an acceptable error that can be applied in different fields, such as scientific research, technology, and management.
At the same time, the idea was to select several places where very high spatial resolution bathymetric data could be obtained, using an aquatic drone, and then relate this data to the high spatial resolution images from satellites.
During this work, different water situations were induced by CoLs. This allowed producing distinct equations according to the transparency of the water, and a good adjustment with an acceptable RMSE was obtained. The methodology was improved by introducing a new step, since after calculating the relationship between LnBlue and LnGreen, the analysis of the ratio values is necessary for choosing the appropriate algorithm.
The changes in the depth of the lagoon depend mainly on the sediment loads mainly transported by runoff during flash-flood events, which deposit soil and other particles on the bottom. This contribution can reach 1863 t yr −1 [95]. Contributions from the Mediterranean or exchanges through the inlets have not been studied in depth, but there is evidence that they can be significant throughout the recent history of the Mar Menor lagoon, especially during extreme storm events [96]. Sedimentation rates have changed during the evolution of the Mar Menor lagoon linked to human uses in the drainage basin, and have increased with time, from 30 mm/century before the Middle Age to more than 30 cm/century in the 20th century, particularly due to deforestation and agricultural practices [97]. To the best of our knowledge, no work had been done that allowed to know the recent changes and the spatial variability of the sedimentation rates in the lagoon.
In the present work, the lowest RMSE value obtained was 0.179 m and increased over time; in 2017 it was 0.186 m and after the CoLs of 2019 there was a random movement and deposition of sand according to the RMSE value.
In the Encañizada gola the deposition of sand meant that the channel, through which water enters and leaves the Mar Menor lagoon, has gradually closed over time ( Figure 16). In the Marchamalo and Estacio golas the deposition of sand meant that the channels were shallower compared to the last bathymetry carried out by the UPCT, in 2011 ( Figure 17). bottom. This contribution can reach 1863 t yr −1 [95]. Contributions from the Mediterranean or exchanges through the inlets have not been studied in depth, but there is evidence that they can be significant throughout the recent history of the Mar Menor lagoon, especially during extreme storm events [96]. Sedimentation rates have changed during the evolution of the Mar Menor lagoon linked to human uses in the drainage basin, and have increased with time, from 30 mm/century before the Middle Age to more than 30 cm/century in the 20th century, particularly due to deforestation and agricultural practices [97]. To the best of our knowledge, no work had been done that allowed to know the recent changes and the spatial variability of the sedimentation rates in the lagoon.
In the present work, the lowest RMSE value obtained was 0.179 m and increased over time; in 2017 it was 0.186 m and after the CoLs of 2019 there was a random movement and deposition of sand according to the RMSE value.
In the Encañizada gola the deposition of sand meant that the channel, through which water enters and leaves the Mar Menor lagoon, has gradually closed over time ( Figure 16). In the Marchamalo and Estacio golas the deposition of sand meant that the channels were shallower compared to the last bathymetry carried out by the UPCT, in 2011 ( Figure 17). It was demonstrated that multispectral images are enough to obtain a precise bathymetry in shallow water. In this case, the shallow water is defined by the fact that the sunlight reaches the bottom of the lagoon. It was possible because, as shown in the bathymetric map, the maximum depth in the Mar Menor lagoon is 7 m; however, a depth of 4 m is presented in the photic zone, and this is the depth of the lagoon that it has been determined using optical sensors from different movements and of increases or decreases in the amount of water in the gola. These models will provide the stakeholders enough information to be able to take decisions about the area with the aim of enhancing its conservation and the use of its resources. If the studies had been limited to the Encañizadas gola alone, the sight of the importance of the other golas and the movement of water through them, between the Mediterranean Sea and the Mar Menor lagoon, would not have been known. Therefore, increasing knowledge of the movement of the sand in all the golas is fundamental for the area, in both economic and environmental terms (Figures A1,A3). It was demonstrated that multispectral images are enough to obtain a precise bathymetry in shallow water. In this case, the shallow water is defined by the fact that the sunlight reaches the bottom of the lagoon. It was possible because, as shown in the bathymetric map, the maximum depth in the Mar Menor lagoon is 7 m; however, a depth of 4 m is presented in the photic zone, and this is the depth of the lagoon that it has been determined using optical sensors from different platforms: satellite, aircraft, or UAV.
The hyper-high spatial resolution of the sensor allows to obtain enough spatial detail, while the high resolution provides a temporal vision to observe details of the influence of the tides. Since the acquisition of the images is always at the same time and in the same place, the variation in the amount of water can only be due to movement of sand or movement of water.
The generated maps provide much information for the management of such a complicated area, but the most important thing is not only the information itself, but that it can be generated in quasi real time, allowing stakeholders to have accurate data in a short time for decision making. The depth model allows the use of images, obtained by aerial drones, of very high spatial resolution (18 cm) or the ones that the stakeholder prefers, since the resolution depends on the drone flight height; it can even reach 3 cm. As the gola is a small area, the stakeholder could have the bathymetric map a few hours after the flight. The low cost of obtaining spatial information from an area with great dynamism between water and land will allow the development of predictive models of soil movements and of increases or decreases in the amount of water in the gola. These models will provide the stakeholders enough information to be able to take decisions about the area with the aim of enhancing its conservation and the use of its resources. If the studies had been limited to the Encañizadas gola alone (Supplementary Materials S2), the sight of the importance of the other golas and the movement of water through them, between the Mediterranean Sea and the Mar Menor lagoon, would not have been known. Therefore, increasing knowledge of the movement of the sand in all the golas is fundamental for the area, in both economic and environmental terms ( Figures A1 and A3).

Conclusions
Once again, remote sensing was shown to be a tool, perhaps the most effective and cheapest one, for obtaining precise data. It may be used in 3D numerical models and in the management of the aquatic environment. It is necessary to remember that the Mar Menor lagoon is a dynamic ecosystem and the quantities of water and sand in each location within it are changing over time. Thus, although the bathymetric map generated throughout this work is the most up-to-date, it will be necessary to validate it from time to time due to the dynamic nature of the lagoon.
The results obtained show that the sedimentation processes occurring in the golas have produced a considerable reduction in their storage capacity, according the bathymetry. Although no significant changes have been detected in the current water renewal time in the lagoon compared to those estimated in the 1980s [25,27,83], the salinity has shown a tendency to approach the lower values of Mediterranean salinity rather than an increase [26]. It would be important to know how the observed changes can affect the capacity for water exchange between the Mar Menor lagoon and the Mediterranean Sea. In addition, climate change will negatively affect the frequency and intensity of natural hazards, such as extreme rainfall events in the area. Therefore, more frequent and severe flash flood events are expected for the contributing basins of the Mar Menor lagoon, which would affect their hydrodynamic [29] and sedimentation rates.
The bathymetries obtained from high-resolution satellite images, such as Pleiades, are demonstrated as very useful tools for complementing the bathymetries obtained with echo sounders in areas of shallow (<2 m) and clear water ( Figure A2). Consequently, the precision of the calculation of the water volume of the Mar Menor lagoon has improved over time with the incorporation of new, much more precise technologies, such as interferometric echo sounders. where Z is the depth and K d the downwelling diffuse attenuation coefficient.