Evaluation of MODIS Spectral Indices for Monitoring Hydrological Dynamics of a Small, Seasonally-Flooded Wetland in Southern Spain

Abstract

Monitoring spatio-temporal dynamics of hydrology in seasonally-flooded wetlands is important for water management and biodiversity conservation. Spectral data and derived indices from t he Moderate Resolution Imaging Spectroradiometer (MODIS) have been used for hydrological monitoring of large wetlands. However, comparable studies for small wetlands (<25 km 2) are lacking. Our aims are to examine whether MODIS-derived indices at 500-m spatial resolution can perform this task for small wetlands, and to compare the performance of various indices. First we evaluated if water levels are a good indicator for wetland inundation extent. A high correlation between water level and Landsatderived inundation extent was found (R 2 =0.957). Secondly, we compared 10 years of water level fluctuations with seven spectral indices at a 16-day interval. The Tasseled Cap brightness index (TCBI) had the highest correlation with water level for the complete time series including dry and wet years. Thirdly, we analyzed how these indices behave for areas with different inundation characteristics. Again TCBI showed a consistently accurate performance, which was independent of inundation frequency. We therefore conclude that TCBI is the best-suited index for monitoring of hydrological variability in small seasonally-flooded wetlands such as the Fuente de Piedra lake in southern Spain. We recommend testing this index further for other seasonally-flooded wetlands in semiarid areas.

Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing

“…This study tentatively confirms what previous studies have already revealed globally: that wetlands are declining in area and quality (McCarthy et al, 2007;Junk et al, 2013;Davidson, 2014;Gardner et al, 2015;Li et al, 2015). Although not conclusive, as the decline may be due to climatic variability and indeed in 2015 the region was severely affected by the El Niño-associated drought event (Rembold et al, 2016;FAO, 2016), the methodology managed to detect both seasonal variation (Figs 4 and 5) and also a trend showing deterioration.…”

“…These include; blue (459-479 nm), green (545-565 nm), red (620-670 nm), near infrared (841-876 nm), and shortwave infrared (SWIR1: 1 230-1 250 nm, SWIR2: 1 628-1 652 nm, SWIR3: 2 105-2 155 nm). The MODIS MCD43 500-m resolution reflectance datasets, which remove view-angle effects, mask cloud cover and reduce atmospheric contamination (Li et al, 2015), were used for this study.…”

“…Time-series spectral water indices were used to gauge the seasonal variations of wetland area, through the detection of surface wetness from multi-spectral imagery of the MODIS NDWI data (Li et al, 2015). The NDWI (Gao, 1996;McFeeters, 1996) follow the same logic as the NDVI, that is, a difference between two spectral bands divided by the sum of the two (Tucker, 1979 (McFeeters, 1996):…”

“…Besides these distinct landcover types, wetlands are also highly variable in spatial extent as the inundated area changes periodically, and often seasonally (Hess et al, 2015;Li et al, 2015). As a result of the landcover differences and spatial dynamics of wetlands, multispectral remote sensing potentially becomes an important time-and cost-effective tool to map and monitor wetlands, especially at fine and medium resolutions (Klemas, 2011;Li et al, 2015).…”

“…Most studies mapped wetland spatial extent using different methods and sensors, but few studied inundated area seasonal variations. Examples of previous studies on wetland inundated area seasonal variation include Ordoyne and Friedl (2008), Rebelo et al (2012) and Li et al (2015). However, these studies focused on single wetlands and did not cover all wetlands within a catchment.…”