Exploiting Differential Vegetation Phenology for Satellite-Based Mapping of Semiarid Grass Vegetation in the Southwestern United States and Northern Mexico

Abstract

Abstract:We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C 4 ) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI 2 ) data from Landsat to develop the NDPI, and MSAVI 2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI 2 and summer maximum MSAVI 2 ), and two simple, conventional VI metrics (summer average MSAVI 2 , summer maximum MSAVI 2 ). The NDPI in a scaled form (NDPI s ) performed best in predicting variation in perennial C 4 grass cover as estimated from landscape photographs at 92 sites (R 2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R 2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R 2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C 4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

Multi-Scale Phenology of Temperate Grasslands: Improving Monitoring and Management With Near-Surface Phenocams

“…Differentiating C 3 -dominant from C 4 -dominant grasslands has been a prominent theme in remote sensing research due to distinct C 3 /C 4 seasonal productivity patterns (Wang et al, 2013;Dye et al, 2016). Satellite data products characterize "land surface phenology" of vegetation types across landscape to global spatial scales (de Beurs and Henebry, 2004;Broich et al, 2015).…”

Woody Vegetation Die off and Regeneration in Response to Rainfall Variability in the West African Sahel

“…All values flagged as good quality between 8 October and 9 June were averaged for each dry season (i.e., lasting from October to June next calendar year). In this study, the mean dry season NDVI is representing the mean dry season green foliage mass of the woody vegetation [17][18][19].…”

Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data—Prolonged Above-Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel

“…However, indices frequently used to estimate vegetation dynamics, for example, the Normalized Difference Vegetation Index (NDVI) [43], typically fail to make a direct link between the remotely sensed observations and tree mortality/recovery. This happens mainly because NDVI estimates cannot differentiate between herbaceous and woody foliage production in drylands, as in those regions the grass layer is continuous and woody plants are sparse, resulting in NDVI values dominated by the grass layer dynamics [44,45]. New approaches based on phenology [16,46] rely on satellite sensors that do not cover the period of the Sahel droughts in the 1970s and 1980s (e.g., the Moderate Resolution Imaging Spectroradiometer, MODIS).…”