**1. Introduction**

Coastal salt marshes are dynamic ecosystems found at the interface between marine and terrestrial environments. These productive ecosystems play important roles in coastal resilience via a variety of ecosystem services, such as accreting sediments, sequestering carbon, and providing habitat for a rich range of biota [1,2]. However, as little as 10% of California's historical wetland cover remains today [3]. This decrease in wetland cover is likely to worsen with the potential increased frequency of disturbances that further reduce and degrade wetland cover, such as sea level rise, coastal erosion, deposition, and anthropogenic marine debris [4–6]. In Santa Barbara County, CA, a series of large debris flows known as the Montecito Debris Flows exemplify a large-scale depositional disturbance to both built and natural environments, including wetlands. The increasing frequency of events related to climate change, such as fires, hurricanes, and altered hydrology, will likely increase the potential for further debris flows, both locally and globally [7]. To mitigate the impacts of disturbance, management should include the effects of disturbances from debris flows in the understanding of marsh form and function. For instance, sediment deposition is a common and important process in many marshes, with deposition due to hurricanes frequently studied and found to provide sediment important for nutrient delivery and the ability to offset sea level rise [2,5]. In contrast, anthropogenic marine debris, such as fishing gear and wooden poles, has been found to damage plant tissues in marshes [4]; meanwhile, oiling has been found to temporarily increase shoreline loss of affected wetlands [8].

Debris flows are an episodic depositional disturbance event; however, there is little literature studying them in wetlands. Furthermore, many studies examining disturbance

**Citation:** Silva, G.D.; Roberts, D.A.; McFadden, J.P.; King, J.Y. Shifts in Salt Marsh Vegetation Landcover after Debris Flow Deposition. *Remote Sens.* **2022**, *14*, 2819. https://doi.org/ 10.3390/rs14122819

Academic Editor: Nicholas Murray

Received: 28 April 2022 Accepted: 7 June 2022 Published: 12 June 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

events in salt marshes have focused on the Gulf of Mexico and the east coast of the U.S. [4,5,8–11]. However, the disturbances that are common in those regions, such as hurricanes, are not common on the west coast of the U.S., where debris flows are more common. As such, the question of how the Montecito Debris Flows impacted the marsh is of interest. However, addressing this question with field methods is complicated by the fact that the unpredictability of the event meant that field data could not be collected prior to the event. Furthermore, a combination of manager-led mechanical dredging and inundation by exceptionally high tides, also known as king tides, removed sediment from the marsh and limited the ability to collect field data following the event. Remotely sensed data, however, were collected before and following the event and could be used to assess impacts of the debris flow on the marsh.

Remote sensing has been used for change detection, biomass estimation, and land cover classification in wetlands with a large range of applications [9,12]. Due to recent advances in sensor design and data analysis, remote sensing is becoming more practical for monitoring natural and anthropogenic changes in coastal systems [12]. Prior studies have recommended a variety of sensors (e.g., Landsat, imaging spectrometers, LiDAR, Planetscope, and drone data), techniques (e.g., maximum likelihood classification, Multiple Endmember Spectral Mixture Analysis (MESMA), reclassification, random forest, and postclassification change detection), and indices (e.g., normalized difference vegetation index) to monitor coastal wetland conditions [6,8,9,11,13–17]. Sensor and spectral vegetation index recommendations vary depending on the wetland type and the characteristics that are being assessed. Index recommendations are more dependent on the type of wetland being assessed.

Several approaches have been used to classify land cover in wetlands. One study implemented the use of fractional cover of different endmembers—spectra from pixels that are representative of a land cover, obtained by spectral mixture analysis (SMA) and MESMA [18]—in the classification of a marsh in the southern San Francisco Bay [12]. While both MESMA and SMA have challenges, MESMA was found to provide a more accurate representation of fractional cover, especially if 4- or 5-endmember models were used with more than one endmember per class [12]. Peterson et al. (2015) used MESMA on airborne visual/infra-red imaging spectrometer (AVIRIS) data to detect oil-impacted regions of coastal salt marsh in Barataria Bay, Louisiana with high accuracy of detecting oiled vs. nonoiled marshes (87.5% to 93.3%) [11]. Beland et al. (2017) used these maps and image change analysis to determine that oiling temporarily accelerated land loss in coastal marshes [8]. These studies highlight the effectiveness of MESMA as a technique for classifying wetland landcover and detecting areas affected by disturbance.

Other classification methods have also been used for tracking change. Tuxen et al. (2008) used NDVI to track vegetation colonization in Petaluma River Marsh after tidal restoration via post-classification change detection [19]. They concluded that NDVI can be used to discriminate vegetated and non-vegetated portions of marshes and is robust to human interpretations of NDVI [19]. Another study used Breaks For Seasonal and Trend (BFAST) and random forest classification on monthly NDVI products made from Landsat (5, 7, 8) and MODIS/Landsat fill-in images to perform change detection in forested wetlands with a classification accuracy of 92.96% and change detection accuracy of 87.8% [17]. Parihar et al. (2012) used maximum likelihood classification on Landsat MSS and TM data to track changes in the East Kolkata Wetlands in the absence of ground data, although the accuracy of this method was between 73.80% and 79.33% [14]. Im et al. (2008) showed that objectbased land cover classification with high accuracies (>90%) can be achieved with solely using a high point density LiDAR data [20].

In this study, we use random forest classification and change detection to assess how the Montecito Debris Flows impacted landcover in Carpinteria Salt Marsh Reserve. Our main objectives were: (1) classification of marsh landcover before and after the debris flows, (2) identification of what change in landcover had occurred and possible implications, (3) identification of important classification variables, and (4) assessment of how accurately random forest classification could map marsh landcover.

#### **2. Materials and Methods**

#### *2.1. Event and Site Description*

In December 2017, the Thomas Fire burned an area of 1140 km<sup>2</sup> in the Santa Ynez Mountains, making it the largest fire in California's history at the time [21,22]. Following the fire, the burned areas experienced an increased risk of debris flows, and, in early January 2018, a heavy rain event mobilized soils from the burn area and triggered a depositional event known as the Montecito Debris Flows [22]. The debris flows deposited approximately 680,000 m<sup>3</sup> of sediment across urban and natural areas along the Santa Barbara Coast [22]. In addition to at least 3 fatalities, 167 injuries, and 408 damaged homes, the Carpinteria Salt Marsh Reserve, an ecological study reserve operated by the University of California, received a large deposition of sediment.

Carpinteria Salt Marsh Reserve (CSMR), located in Carpinteria, CA (34.4012◦ N, 119.5379◦ W), is situated between California Highway 101, downtown Carpinteria, and the Pacific Ocean (Figure 1). The wetland is a heterogeneous landscape made up of 93 hectares of annual and perennial herbs and grasses, transitional upland habitat, water channels, and mud flats [6]. The plant community can be split into two main categories: mid marsh, primarily dominated by *Salicornia pacifica* (formerly *Salicornia virginica*, pickleweed), and high marsh, which is a mix of *Salicornia pacifica*, *Jaumea carnosa* (marsh jaumea), *Distichlis littoralis* (shore grass), *Arthrocnemum subterminale* (Parish's glasswort), *Frankenia salina* (alkali heath), and a few other less abundant species [6,23]. Water inputs come largely from tidal inundation and from water inlets in the eastern portion of the marsh that allow for input from further inland [24].

**Figure 1.** Carpinteria Salt Marsh Reserve with study extent outlined. Imagery courtesy of USDA National Agriculture Inventory Program.
