###### Abstract  
Recently, spatial organization in salt marshes was shown to contain vital information on system resilience. However, in salt marshes, it remains poorly understood what shaping processes regulate spatial patterns in soil or vegetation properties that can be detected in the surface reflectance signal. In this case study we compared the effect on surface reflectance of four major shaping processes: Flooding duration, wave forcing, competition, and creek formation. We applied the ProSail model to a pioneering salt marsh species (_Spartina anglica_) to identify through which vegetation and soil properties these processes affected reflectance, and used in situ reflectance data at the leaf and canopy scale and satellite data on the canopy scale to identify the spatial patterns in the biophysical characteristics of this salt marsh pioneer in spring. Our results suggest that the spatial patterns in the pioneer zone of the studied salt marsh are mainly caused by the effect of flood duration. Flood duration explained over three times as much of the variation in canopy properties as wave forcing, competition, or creek influence. It particularly affects spatial patterns through canopy properties, especially the leaf area index, while leaf characteristics appear to have a relatively minor effect on reflectance. ProSail; salt marsh; Spartina; reflectance; spatial patterns; flood duration 20191151103390/rs110505110390/rs11050  
become visible as spatial patterns. This will increase our general understanding of ecosystems and improve our ability to monitor their stability. Spatial patterns can be defined as a pattern in the spatial distribution of a variable, in this study we focus on vegetation reflectance, and hence with spatial pattern we mean the spatial distribution of similarities and dissimilarities of vegetation reflectance. In general, two types of vegetation based spatial pattern studies can be distinguished: i) Studies focusing on the effect of an (often abiotic) parameter on vegetation zonation (i.e., zonation of different plant species) and ii) studies focusing on how vegetation properties affect spatial patterning (i.e., patterns in a single species). In the first case, the focus was generally on the effect of a single parameter (e.g., nutrient composition, salinity, or competition) on vegetation zonation. Here, the spatial pattern changes as a result of changes in composition of the species. In the second case, studies can focus on the effect of changing vegetation properties on spatial patterns, for example, the effect of drought, and the corresponding low water content in plants [6; 7; 8] or changes in biomass in response to salinity [9; 10]. This changes the appearance of plants, which changes the spatial pattern. Our study falls in the second category as we are interested in the vegetation properties that are affected by biotic and abiotic processes. In this study, we focus on the spatial variation of biophysical properties of a single species, and do not look at vegetation zonation. To understand the stability of services provided by ecosystems and the resilience of such a system, using spatial patterns, analyses have to be performed at a large spatial scale, which is made feasible with remote sensing [11]. Satellite data offer a sufficient spatial scale and synoptic coverage that cannot easily be obtained through field observations [11]. The effects of vegetation properties on optical reflectance on a scale that affects satellite data, and hence affects spatial patterns, are traditionally studied in two different ways: Either through vegetation indices (VI's) linked through correlation with physical properties or through physical models [12]. Vegetation indices are widely used, whereas physical models are most often used in agriculture. A VI is generally directly related to in situ biophysical properties or environmental properties, and is influenced by biophysical properties of the canopy and leaves.