Differentiation of plant age in grasses using remote sensing

Phenological or plant age classification across a landscape allows for examination of micro-topographical effects on plant growth, improvement in the accuracy of species discrimination, and will improve our understanding of the spatial variation in plant growth. In this paper six vegetation indices used in phenological studies (including the newly proposed PhIX index) were analysed for their ability to statistically differentiate grasses of different ages in the sequence of their development. Spectra of grasses of different ages were collected from a greenhouse study. These were used to determine if NDVI, NDWI, CAI, EVI, EVI2 and the newly proposed PhIX index could sequentially discriminate grasses of different ages, and subsequently classify grasses into their respective age category. The PhIX index was defined as: (AVNIRn+log(ASWIR2n))/(AVNIRn−log(ASWIR2n)), where AVNIRn and ASWIR2n are the respective normalised areas under the continuum removed reflectance curve within the VNIR (500–800 nm) and SWIR2 (2000–2210 nm) regions. The PhIX index was found to produce the highest phenological classification accuracy (Overall Accuracy: 79%, and Kappa Accuracy: 75%) and similar to the NDVI, EVI and EVI2 indices it statistically sequentially separates out the developmental age classes. Discrimination between seedling and dormant age classes and the adult and flowering classes was problematic for most of the tested indices. Combining information from the visible near infrared (VNIR) and shortwave infrared region (SWIR) region into a single phenological index captures the phenological changes associated with plant pigments and the ligno-cellulose absorption feature, providing a robust method to discriminate the age classes of grasses. This work provides a valuable contribution into mapping spatial variation and monitoring plant growth across savanna and grassland ecosystems.

► Discriminating between certain age classes problematic for most vegetation indices.
► Combining VNIR and SWIR region into an index creates robust phenological index.
► PhIX produces highest classification accuracy for discriminating all grass age classes.
► Important contribution to mapping spatial and temporal plant growth in savannas.