Jelle G. Ferwerda

Estimating tropical pasture quality at canopy level using band depth analysis with continuum removal in the visible domain

Pasture quality, expressed as a percentage of total digestible nutrients (nitrogen, potassium, phosphorous, calcium and magnesium), is a major factor determining the grazing patterns of wildlife and livestock. Existing rangeland monitoring techniques seldom reflect the nutritive quality of the pastures and are consequently of limited value in explaining animal distribution. Techniques that can estimate pasture quality on a large scale are therefore critical in understanding and explaining wildlife and livestock distribution. We present the results of a greenhouse experiment designed to estimate the concentrations of nitrogen, potassium, phosphorous, calcium, magnesium and non‐detergent fibre (NDF), using the reflectance of a tropical grass (Cenchrus ciliaris) canopy. Canopy spectral measurements were taken under controlled laboratory conditions using a GER 3700 spectroradiometer. We tested the utility of using the band depth analysis methodology in the visible region (where water absorption is less effective) to estimate foliar chemistry in fresh canopies. Continuum removal was applied to the visible absorption feature centred at 670 nm, and band depth ratios (BDRs) were calculated. Stepwise linear regression was used to select wavelengths from calculated BDRs that were highly correlated with foliar chemistry in a randomly selected training dataset. The resulting regression models were used to predict foliar chemistry in a test dataset. Results indicate that stepwise regression on bands calculated from continuum‐removed reflectance spectra could predict foliar nutrient concentration with high accuracy. The correlations were highest for magnesium and nitrogen (R 2 = 0.77 and 0.73 respectively, using the normalized band depth index (NBDI)) between the measured and estimated biochemicals—a satisfactory result in estimating foliar chemistry in fresh standing pastures. With the advent of new sensors such as Hymap and MERIS, these results lay the basis for developing algorithms to rapidly estimate and ultimately map pasture quality in tropical rangelands.

Nitrogen detection with hyperspectral normalized ratio indices across multiple plant species

The main focus of recent studies relating vegetation leaf chemistry with remotely sensed data is the prediction of chlorophyll and nitrogen content using indices based on a combination of bands from the red and infrared wavelengths. The use of high spectral resolution data offers the opportunity to select the optimal wavebands for predicting plant chemical properties. In order to test the optimal band combinations for predicting nitrogen content, normalized ratio indices were calculated for all wavebands between 350 and 2200 nm for five different species. The correlation between these indices and the nitrogen content of the samples was calculated and compared between species. The results show a strong correlation between individual normalized ratio indices and the nitrogen content for different species. The spectral regions that are most effective for predicting nitrogen content are, for each individual species, different from the normalized difference vegetation index (NDVI) spectral region. By combining the areas of maximum correlation it was possible to determine the optimal spectral regions for predicting leaf nitrogen content across species. In a cross‐species situation, normalized ratio indices using the combination of reflectance at 1770 nm and at 693 nm may give the best relation to nitrogen content for individual species.

Satellite-based monitoring of tropical seagrass vegetation: current techniques and future developments

Decline of seagrasses has been documented in many parts of the world. Reduction in water clarity, through increased turbidity and increased nutrient concentrations, is considered to be the primary cause of seagrass loss. Recent studies have indicated the need for new methods that will enable early detection of decline in seagrass extent and productivity, over large areas. In this review of current literature on coastal remote sensing, we examine the ability of remote sensing to serve as an information provider for seagrass monitoring. Remote sensing offers the potential to map the extent of seagrass cover and monitor changes in these with high accuracy for shallow waters. The accuracy of mapping seagrasses in deeper waters is unclear. Recent advances in sensor technology and radiometric transfer modelling have resulted in the ability to map suspended sediment, sea surface temperature and below-surface irradiance. It is therefore potentially possible to monitor the factors that cause the decline in seagrass status. When the latest products in remote sensing are linked to seagrass production models, it may serve as an early-warning system for seagrass decline and ultimately allow a better management of these susceptible ecosystems.

The Function of Remote Sensing in Support of Environmental Policy

Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently little academic interest in the societal contribution of environmental remote sensing. This is because none of the more than 300 peer reviewed papers described actual policy support. This paper describes and discusses the potential, actual support, and limitations of earth observation with respect to supporting the various stages of environmental policy development. Examples are given of the use of remote sensing in problem identification and policy formulation, policy implementation, and policy control and evaluation. While initially, remote sensing contributed primarily to the identification of environmental problems and policy implementation, more recently, interest expanded to applications in policy control and evaluation. The paper concludes that the potential of earth observation to control and evaluate, and thus assess the efficiency and effectiveness of policy, offers the possibility of strengthening governance.

A bootstrap procedure to select hyperspectral wavebands related to tannin content

Detection of hydrocarbons in plants with hyperspectral remote sensing is hampered by overlapping absorption pits, while the ‘optimal’ wavebands for detecting some surface characteristics (e.g. chlorophyll, lignin, tannin) may shift. We combined a phased regression with a bootstrap procedure to find wavebands related to the tannin content of fresh leaves, and compared the bands thus identified with the reflectance spectra of pure quebracho tannin. For both reflectance and derivative spectra, bands were identified that can be linked to known absorption features (1471, 1640, 1710, 2175 nm) or fall within the absorption regions identified from a reflectance curve of pure quebracho tannin. We also confirmed a previously reported link between tannin content and the derivative spectra around 800 nm. The study shows that by combining bootstrapping with phased regression it is possible to determine wavebands of which the reflectance is influenced by tannin.

Inducing condensed tannin production in Colophospermum mopane : absence of response to soil N and P fertility and physical damage

The effects of available soil N and P and the effect of simulated browsing (leave removal) on foliar condensed tannin (CT) concentration were tested on young Colophospermum mopane (J. Kirk ex Benth) J. Leonard (Mopane) plants. Although clear differences in growth occurred between different levels of soil N, no differences in foliar CT concentration were found. Changes in available soil P and physical damage did not affect the plant growth or chemical composition. The complete absence of response of CT concentration to physical damage and soil nutrients may be related to the age of the trees in this study. It is proposed that existing theories on the interaction between soil properties and carbon based defences in trees are expanded, to include the potential responses of young trees to different soil nutrient levels.

Differences in regeneration between hurricane damaged and clear-cut mangrove stands 25 years after clearing

The effect of human disturbance on mangrove forest may be substantially different from the effects of natural disturbances. This paper describes differences in vegetation composition and structure of five vegetation types in two mangrove areas near Darwin, Australia, 25 years after disturbance. The vegetation in clear-felled forest showed more adult Avicennia marina than in the hurricane-affected forest, and a virtual absence of A. marina juveniles and saplings. This indicates that A. marina will be replaced by other species in the canopy, showing a multi-phase vegetation development in mangrove forest after human disturbance. The mechanism of disturbance and the conditions after clearing therefore affects the vegetation composition for at least 25 years after this disturbance took place.

Continuous wavelet transformations for hyperspectral feature detection

A novel method for the analysis of spectra and detection of absorption features in hyperspectral signatures is proposed, based on the ability of wavelet transformations to enhance absorption features. Field spectra of wheat grown on different levels of available nitrogen were collected, and compared to the foliar nitrogen content. The spectra were assessed both as absolute reflectances and recalculated into derivative spectra, and their respective wavelet transformed signals. Wavelet transformed signals, transformed using the Daubechies 5 motherwavelet at scaling level 32, performed consistently better than reflectance or derivative spectra when tested in a bootstrapped phased regression against nitrogen.

Resource Distribution and Dynamics: mapping herbivore resources

The distribution of food is an important predictor for the distribution and density of herbivores in an ecosystem. Determining the distribution and densities of resource quantity and quality in space and time is therefore a crucial step towards understanding the spatial arrangement of herbivores. In recent years remote sensing has become the tool of choice for producing high spatial-resolution impressions of the variability of the landscape, and in particular land cover. Remote sensing is slowly moving away from mapping the surface into discrete land-cover classes. More and more, it is now used to produce highly accurate probability maps of presence, depicting the percentage of individual pixels covered with a certain surface element. This more closely represents the continuous nature of natural phenomena. Recent studies have indicated that it is possible to measure the chemical composition of foliage too. Recently a case study in Kruger National Park confirmed that it is possible to measure nitrogen concentration and phenolic compound levels in grass and trees accurately, with a spatial resolution of 4 meters. This opens doors for new lines of research, where the distribution of herbivores can be linked to the actual resource distribution

Soil N and P affected reflectance signatures of individual colophospermum mopane leaves

Reflectance and derivative spectra of greenhouse‐grown mopane (Colophospermum mopane) were analyzed to investigate whether the interactive effect of soil phosphorus and nitrogen treatments on plant‐chemical composition can be detected using non‐destructive techniques. Reflectance spectra were affected by changes in soil nitrogen. Derivative spectra showed significant differences as a result of nitrogen and phosphorus treatment. Several spectral bands that showed different spectral signatures between soil treatments also showed significant correlation to condensed tannin, phosphorus and nitrogen concentration in mopane leaves. This shows the potential to detect the effect of soil properties on the plants physiology with hyperspectral remote sensing.