Hyperspectral analysis of chlorophyll content and photosynthetic capacity of coral reef substrates

Few studies have assessed the biophysical properties controlling reflection and absorption of light in coral reef environments and their relationships with quantitative measures of reef health and productivity. The present article examines the relationship between spectral reflectance, photosynthetic capacity, and chlorophyll a from common coral reef substrates. Reflectance readings of several targets (massive corals Montipora sp., n=49, and Porites sp., n=80; macroalgae Chlorodesmis sp., n=24; and sediment interspersed with benthic microalgae, n=35) were obtained in situ on Heron Reef, southern Great Barrier Reef (23 degrees 27'S, 151 degrees 55'E). Measurements of photosynthetic capacity and chlorophyll content were acquired simultaneously. Linear correlations were examined between spectral reflectance at all wavelengths and both photosynthetic capacity and pigment content (Chl a). Reflectance plots for all targets exhibited an absorption feature centered at 675 nm, and spectral reflectance at this wavelength decreased with increasing Chl a levels. The strength of this correlation varied between features, being highest for Porites sp. and lowest for sediment, highlighting the complexities of coral reef environments and the difficulties associated with relating spectral reflectance to biophysical properties. Photosynthetic capacity did not exhibit statistically significant correlations to spectral reflectance or absorption at any wavelength. Our results demonstrate the capabilities and difficulties associated with field scale hyperspectral data for measuring select biophysical properties of coral reefs and the need for assessment of the capabilities of airborne and satellite imaging sensors for similar purposes

Mapping olive varieties and within-field spatial variability using high resolution QuickBird imagery

[Abstract]: The growth of the Australian olive (Olea europaea L.) industry requires support from research to ensure its profitability and sustainability. To contribute to this goal, our project tested the ability of remote sensing imagery to map olive groves and their attributes. Specifically, this study aimed to: (a) discriminate olives varieties; and to (b) detect and interpret within-field spatial variability. Using high spatial resolution (2.8m) QuickBird multispectral imagery acquired over Yallamundi (southeast Queensland) on 24 December 2003, both visual interpretation and statistical (divergence) measures were employed to discriminate olive varieties. Similarly, the detection and interpretation of within-field spatial variability was conducted on enhanced false colour composite imagery, and confirmed by the use of statistical methods. Results showed that the two olive varieties (i.e. Kalamata and Frantoio) can be visually differentiated and mapped on the enhanced image based on texture. The spectral signature plots showed little difference in the mean spectral reflectance values, indicating that the two varieties have a very low spectral separability. In terms of within-field spatial variability, the presence or absence of Rhodes grass (Chloris gayana) was detected using visual interpretation, corroborated by the results of quantitative statistical measures. Spatial variability in soil properties, caused by the presence of a patch of sandy soil, was also detected visually. Finally, the “imprint” of former cover-type or land-use prior to olive plantation establishment in 1998 was identified. More work is being done to develop image classification techniques for mapping within-field spatial variability in olive varieties, biomass and condition using hyperspectral image data, as well as interpreting the cause of observed variability

Spatial heterogeneity of air-sea energy fluxes over a coral reef-Heron Reef, Australia

The thermal environment of a coral reef is moderated by complex interactions of air-sea heat and moisture fluxes, local to synoptic-scale weather and reef hydrodynamics. Measurements of air-sea energy fluxes over coral reefs are essential to understanding the reef-atmosphere processes that underpin coral reef environmental conditions such as water temperature, cloud, precipitation, and local winds (such as during coral bleaching events). Such measurements over coral reefs have been rare, however, and the spatial heterogeneity of surface-atmosphere energy exchanges due to the different geomorphic and biological zones on coral reefs has not been captured. Accordingly, the heterogeneity of coral reefs with regard to substrate, benthic communities, and hydrodynamic processes has not been considered in the characterization of the surface radiation budget and energy balance of coral reefs. Here, the first concurrent in situ eddy covariance measurements of the surface energy balance and radiation transfers over different geomorphic zones of a coral reef are presented. Results showed differences in radiation transfers and sensible and latent heat fluxes over the reef, with higher Bowen ratios over the shallow reef flat zone. The energy flux divergence between sites increased with wind speed and during unstable, southeasterly trade winds with the net flux of heat being positive and negative over different geomorphic zones. The surface drag coefficient at measurement height ranged from 1 x 10(-3) to 2.5 x 10(-3), with no significant difference between sites. Results confirm that spatial variation in radiation and air-reef-water surface heat and moisture fluxes occurs across a lagoonal platform reef in response to local meteorological conditions, hydrodynamics, and benthic-substrate cover

Estimating aboveground woody biomass change in Kalahari woodland: combining field, radar, and optical data sets

Maps that accurately quantify aboveground vegetation biomass (AGB) are essential for ecosystem monitoring and conservation. Throughout Namibia, four vegetation change processes are widespread, namely, deforestation, woodland degradation, the encroachment of the herbaceous and grassy layers by woody strata (woody thickening), and woodland regrowth. All of these vegetation change processes affect a range of key ecosystem services, yet their spatial and temporal dynamics and contributions to AGB change remain poorly understood. This study quantifies AGB associated with the different vegetation change processes over an 8-year period, for a region of Kalahari woodland savannah in northern Namibia. Using data from 101 forest inventory plots collected during two field campaigns (2014–2015), we model AGB as a function of the Advanced Land Observing Satellite Phased Array L-band synthetic aperture radar (PALSAR and PALSAR-2) and dry season Landsat vegetation index composites, for two periods (2007 and 2015). Differences in AGB between 2007 and 2015 were assessed and validated using independent data, and changes in AGB for the main vegetation processes are quantified for the whole study area (75,501 km2). We find that woodland degradation and woody thickening contributed a change in AGB of −14.3 and 2.5 Tg over 14% and 3.5% of the study area, respectively. Deforestation and regrowth contributed a smaller portion of AGB change, i.e. −1.9 and 0.2 Tg over 1.3% and 0.2% of the study area, respectively

Mapping decadal land cover changes in the woodlands of north eastern Namibia from 1975 to 2014 using the Landsat satellite archived data

Woodlands and savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to subsistence and intensive agriculture or urbanized. This study investigates changes in land cover over four administrative regions of North Eastern Namibia within the Kalahari woodland savannah biome, covering a total of 107,994 km2. Land cover is mapped using multi-sensor Landsat imagery at decadal intervals from 1975 to 2014, with a post-classification change detection method. The dominant change observed was a reduction in the area of woodland savannah due to the expansion of agriculture, primarily in the form of small-scale cereal and pastoral production. More specifically, woodland savannah area decreased from 90% of the study area in 1975 to 83% in 2004, and then increased to 86% in 2014, while agricultural land increased from 6% to 12% between 1975 and 2014. We assess land cover changes in relation to towns, villages, rivers and roads and find most changes occurred in proximity to these. In addition, we find that most land cover changes occur within land designated as communally held, followed by state protected land. With widespread changes occurring across the African continent, this study provides important data for understanding drivers of change in the region and their impacts on the distribution of woodland savannahs

Development of process trees for object-oriented change detection in riparian environments from high spatial resolution multi-spectral images

The objectives of this research were to: (1) develop rule sets in Definiens Developer 7® for mapping and monitoring riparian zone land-cover classes within two QuickBird images; and (2) compare the results of four object-oriented and pixel-based change detection approaches. Two QuickBird images, atmospherically corrected to at-surface reflectance, were captured in May and August 2007 for a savanna woodlands area along Mimosa Creek in Central Queensland, Australia. In-situ vegetation structural measurements and LiDAR data, obtained on 28 May - 5 June and 15 July 2007 respectively, were used for calibration and validation. A sequential segmentation routine was applied to enable segmentation of large image datasets. An Isodata unsupervised classification was used for pixel-based classification and rule sets were developed for object-oriented classification of the following land-cover classes: streambed; riparian vegetation; bare ground; rangelands; and woodlands. Four object-oriented and pixel-based change detection routines were applied to the image data: post-classification comparison; image differencing; image regression; and the tasselled cap transformation. The object-oriented classification results showed that object- and class-related features and membership functions could be standardized in the rule sets for classifying the two QuickBird images. Results from the different change detection approaches indicated that post-classification comparison and image differencing produced more accurate results, especially when used together. All four change detection approaches were suited to object-oriented analysis. Advantages of the object-oriented change detection routines included: (1) no need for post-change detection filtering and smoothing; (2) less impact of slight geometric offsets between image datasets; and (3) the ability to include context relationships to improve change detection results

Tracking the rapid loss of tidal wetlands in the Yellow Sea

In the Yellow Sea region of East Asia, tidal wetlands are the frontline ecosystem protecting a coastal population of more than 60 million people from storms and sea-level rise. However, unprecedented coastal development has led to growing concern about the status of these ecosystems. We developed a remote-sensing method to assess change over ∼4000 km of the Yellow Sea coastline and discovered extensive losses of the region's principal coastal ecosystem - tidal flats - associated with urban, industrial, and agricultural land reclamations. Our analysis revealed that 28% of tidal flats existing in the 1980s had disappeared by the late 2000s (1.2% annually). Moreover, reference to historical maps suggests that up to 65% of tidal flats were lost over the past five decades. With the region forecast to be a global hotspot of urban expansion, development of the Yellow Sea coastline should pursue a course that minimizes the loss of remaining coastal ecosystems