Functional Phenology of a Texas Post Oak Savanna from a CHRIS PROBA Time Series

Abstract

Remnant midwestern oak savannas in the USA have been altered by fire suppression and the encroachment of woody evergreen trees and shrubs. The Gus Engeling Wildlife Management Area (GEWMA) near Palestine, Texas represents a relatively intact southern example of thickening and evergreen encroachment in oak savannas. In this study, 18 images from the CHRIS/PROBA (Compact High-Resolution Imaging Spectrometer/Project for On-Board Autonomy) sensor were acquired between June 2009 and October 2010 and used to explore variation in canopy dynamics among deciduous and evergreen trees and shrubs, and savanna grassland in seasonal leaf-on and leaf-off conditions. Nadir CHRIS images from the 11 useable dates were processed to surface reflectance and a selection of vegetation indices (VIs) sensitive to pigments, photosynthetic efficiency, and canopy water content were calculated. An analysis of temporal VI phenology was undertaken using a fishnet polygon at 90 m resolution incorporating tree densities from a classified aerial photo and soil type polygons. The results showed that the major differences in spectral phenology were associated with deciduous tree density, the density of evergreen trees and shrubs—especially during deciduous leaf-off periods—broad vegetation types, and soil type interactions with elevation. The VIs were sensitive to high densities of evergreens during the leaf-off period and indicative of a photosynthetic advantage over deciduous trees. The largest differences in VI profiles were associated with high and low tree density, and soil types with the lowest and highest available soil water. The study showed how time series of hyperspectral data could be used to monitor the relative abundance and vigor of desirable and less desirable species in conservation lands.

Quantitative Analysis of the Research Trends and Areas in Grassland Remote Sensing: A Scientometrics Analysis of Web of Science from 1980 to 2020

“…[93], and used the overall coverage, NPP, biomass, etc., for aims such as determining grassland degradation [16] and estimating grass yield and rough protein content. Due to the wide application of high-resolution and hyperspectral remote sensing data, quantitative analysis of the spectral characteristics of different grassland species, and in-depth research on multitemporal monitoring of different vegetation indices [107][108][109][110], model parameters have been continuously optimized [11,12,14,20]. These parameters can be used to effectively identify different grassland types in the community, and determine the height, coverage, and area ratio of the grassland, thus providing complete monitoring of the succession processes of grassland communities.…”

Remote Sensing of Savannas and Woodlands: Editorial

“…These are followed by two articles on African environments that include a mix of savannas and woodlands and other vegetation [27,28]. The final two articles address functional ecological aspects of two different types of northern hemisphere oak savannas in North America [29] and Europe [30]. The group of four papers on South America span the ecotone from the heavily altered Mato Grosso forests in Amazonia through the savanna of the Cerrado to the dry forests of the Caatinga.…”

“…The two articles published here represent two major types: the perennial grass/oak savannas that stretched from southern Canada to northern Mexico between the grasslands and forests of North America; and the annual grass/oak savannas found, for example, in California and Spain. The paper by Hill et al [29] describes the use of a rare time series from the CHRIS hyperspectral sensor to explore functional phenology of the woody canopy in a conserved but degraded post oak savanna in Texas invaded with evergreen shrubs. The results of this study hint at the value of hyperspectral data in characterization of differences in canopy properties and species mixtures that are important in the evolution of disturbed remnant landscapes.…”

PhotonLabeler: An Inter-Disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data

“…Apart from the time the data was acquired, these differences a reflective of the different vegetation structure (sparse vs closed canopy) or phenological stages (leaf-on vs leaf-off) in the two sites. The data for the Zambia site was acquired in June, which is a leaf-off period for most deciduous forest in Zambia while Texas forests were in their leaf-off state at the time the data was acquired in April [21,22].…”