F. Mark Danson

Factors affecting the remotely sensed response of coniferous forest plantations

Remote sensing of forest biophysical properties has concentrated upon forest sites with a wide range of green vegetation amount and thereby leaf area index and canopy cover. However, coniferous forest plantations, an important forest type in Europe, are managed to maintain a large amount of green vegetation with little spatial variation. Therefore, the strength of the remotely sensed signal will, it is hypothesized, be determined more by the structure of this forest than by its cover. Airborne Thematic Mapper (ATM) and SPOT-1 HRV data were used to determine the effects of this structural variation on the remotely sensed response of a coniferous forest plantation in the United Kingdom. Red and near infrared radiance were strongly and negatively correlated with a range of structural properties and with the age of the stands but weakly correlated with canopy cover. A composite variable, related to the volume of the canopy, accounted for over 75% of the variation in near infrared radiance. A simple model that related forest structural variables to the remotely sensed response was used to understand and explain this response from a coniferous forest plantation.

Landscape composition and spatial prediction of alveolar echinococcosis in Southern Ningxia, China

Background Alveolar echinococcosis (AE) presents a serious public health challenge within China. Mass screening ultrasound surveys can detect pre-symptomatic AE, but targeting areas identified from hospital records is inefficient regarding AE. Prediction of undetected or emerging hotspots would increase detection rates. Voles and lemmings of the subfamily Arvicolinae are important intermediate hosts in sylvatic transmission systems. Their populations reach high densities in productive grasslands where food and cover are abundant. Habitat availability is thought to affect arvicoline population dynamic patterns and definitive host–intermediate host interactions. Arvicoline habitat correlates with AE prevalence in Western Europe and southern Gansu Province, China. Methods and Findings Xiji County, Ningxia Hui Autonomous Region, borders southern Gansu. The aims of this study were to map AE prevalence across Xiji and test arvicoline habitat as a predictor. Land cover was mapped using remotely sensed (Landsat) imagery. Infection status of 3,205 individuals screened in 2002–2003 was related, using generalised additive mixed models, to covariates: gender; farming; ethnicity; dog ownership; water source; and areal cover of mountain pasture and lowland pasture. A Markov random field modelled additional spatial variation and uncertainty. Mountain pasture and lowland pasture were associated with below and above average AE prevalence, respectively. Conclusions Low values of the normalised difference vegetation index indicated sub-optimality of lowland pasture for grassland arvicolines. Unlike other known endemic areas, grassland arvicolines probably did not provide the principal reservoir for Echinococcus multilocularis in Xiji. This result is consistent with recent small mammal surveys reporting low arvicoline densities and high densities of hamsters, pikas and jerboas, all suitable intermediate hosts for E. multilocularis, in reforested lowland pasture. The risk of re-emergence is discussed. We recommend extending monitoring to: southern Haiyuan County, where predicted prevalence was high; southern Xiji County, where prediction uncertainty was high; and monitoring small mammal community dynamics and the infection status of dogs.

Candidate high spectral resolution infrared indices for crop cover

Abstract The sensitivity of near-infrared/red ratio vegetation indices to soil reflectance and plant color result in ambiguous interpretation of plant condition and productivity. Measurements of the reflectance of crop canopies were made at high spectral resolution to investigate candidate vegetation indices, in the near- and middle-infrared (800–2500 nm), for their ability to umambiguously estimate foliage cover independently of the extraneous effects of variations in canopy color and soil background brightness. Reflectances were measured with an IRIS spectroradiometer over plots of sugar beet (Beta vulgaris L.) sown on different denss and at different densities to produce a wide range in canopy cover. Vegetation color was varied by infecting selected plots with sugar beet yellows virus. Soil brightness was varied by placing trays of peat between the plant rows. Selected narrow-band near- and middle-infrared reflectances were tested for their relationship with canopy cover and their sensitivity to variations in canopy color and soil brightness. The relationship between canopy cover and traditional near-infrared/red ratio indices was f to be sensitive to both canopy color and soil brightness. Most infrared indices were insensitive to the effects of canopy color, but those showing the highest correlations with cover tended to be significantly influenced by soil brightness. The most promising NIR reflectances were those beyond the range (760–900 nm) of near-infrared reflectance detected by current space-borne systems, such as Landsat TM and SPOT HRV.

Terrestrial laser scanning to estimate plot-level forest canopy fuel properties

This paper evaluates the potential of a terrestrial laser scanner (TLS) to characterize forest canopy fuel characteristics at plot level. Several canopy properties, namely canopy height, canopy cover, canopy base height and fuel strata gap were estimated. Different approaches were tested to avoid the effect of canopy shadowing on canopy height estimation caused by deployment of the TLS below the canopy. Estimation of canopy height using a grid approach provided a coefficient of determination of R2 = 0.81 and an RMSE of 2.47 m. A similar RMSE was obtained using the 99th percentile of the height distribution of the highest points, representing the 1% of the data, although the coefficient of determination was lower (R2 = 0.70). Canopy cover (CC) was estimated as a function of the occupied cells of a grid superimposed upon the TLS point clouds. It was found that CC estimates were dependent on the cell size selected, with 3 cm being the optimum resolution for this study. The effect of the zenith view angle on CC estimates was also analyzed. A simple method was developed to estimate canopy base height from the vegetation vertical profiles derived from an occupied/non-occupied voxels approach. Canopy base height was estimated with an RMSE of 3.09 m and an R2 = 0.86. Terrestrial laser scanning also provides a unique opportunity to estimate the fuel strata gap (FSG), which has not been previously derived from remotely sensed data. The FSG was also derived from the vegetation vertical profile with an RMSE of 1.53 m and an R2 = 0.87.

Testing the Application of Terrestrial Laser Scanning to Measure Forest Canopy Gap Fraction

Terrestrial laser scanners (TLS) have the potential to revolutionise measurement of the three-dimensional structure of vegetation canopies for applications in ecology, hydrology and climate change. This potential has been the subject of recent research that has attempted to measure forest biophysical variables from TLS data, and make comparisons with two-dimensional data from hemispherical photography. This research presents a systematic comparison between forest canopy gap fraction estimates derived from TLS measurements and hemispherical photography. The TLS datasets used in the research were obtained between April 2008 and March 2009 at Delamere Forest, Cheshire, UK. The analysis of canopy gap fraction estimates derived from TLS data highlighted the repeatability and consistency of the measurements in comparison with those from coincident hemispherical photographs. The comparison also showed that estimates computed considering only the number of hits and misses registered in the TLS datasets were consistently lower than those estimated from hemispherical photographs. To examine this difference, the potential information available in the intensity values recorded by TLS was investigated and a new method developed to estimate canopy gap fraction proposed. The new approach produced gap fractions closer to those estimated from hemispherical photography, but the research also highlighted the limitations of single return TLS data for this application.

Probability of cloud-free observation conditions across Great Britain estimated using MODIS cloud mask

Cloud cover is a major constraint on applications using optical remote sensing, particularly in temperate regions such as Great Britain (GB). This research explores the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask product to calculate cloud probability across GB. MODIS 1 km cloud mask data for 2005 were downloaded and processed to map cloud-free probabilities. The results indicate an average yearly cloud-free probability of 21.3%, with maximum and minimum monthly mean probabilities of 33.3% and 12.9% in November and March, respectively. Temporal and spatial variations in cloud-free frequencies are apparent. Northern and western regions are generally cloudier than those in the south. The results of this research indicate that cloud probabilities can be identified at a relatively high spatial resolution.

Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation

A new generation of multiwavelength lidars offers the potential to measure the structure and biochemistry of vegetation simultaneously, using range resolved spectral indices to overcome the confounding effects in passive optical measurements. However, the reflectance of leaves depends on the angle of incidence, and if this dependence varies between wavelengths, the resulting spectral indices will also vary with the angle of incidence, complicating their use in separating structural and biochemical effects in vegetation canopies. The Salford Advanced Laser Canopy Analyser (SALCA) dual-wavelength terrestrial laser scanner was used to measure the angular dependence of reflectance for a range of leaves at the wavelengths used by the new generation of multiwavelength lidars, 1063 and 1545 nm, as used by SALCA, DWEL, and the Optech Titan. The influence of the angle of incidence on the normalized difference index (NDI) of these wavelengths was also assessed. The reflectance at both wavelengths depended on the angle of incidence and could be well modelled as a cosine. The change in the NDI with the leaf angle of incidence was small compared with the observed difference in the NDI between fresh and dry leaves and between leaf and bark. Therefore, it is concluded that angular effects will not significantly impact leaf moisture retrievals or prevent leaf/bark separation for the wavelengths used in the new generation of 1063- and 1545-nm multiwavelength lidars.

Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks

ABSTRACT The Salford Advanced Laser Canopy Analyser (SALCA) is a unique dual-wavelength full-waveform terrestrial laser scanner (TLS) designed to measure forest canopies. This article has two principle objectives, first to present the detailed analysis of the radiometric properties of the SALCA instrument, and second, to propose a novel method to calibrate the recorded intensity to apparent reflectance using a neural network approach. The results demonstrate the complexity of the radiometric response to range, reflectance, and laser temperature and show that neural networks can accurately estimate apparent reflectance for both wavelengths (a root mean square error (RMSE) of 0.072 and 0.069 for the 1063 and 1545 nm wavelengths, respectively). The trained network can then be used to calibrate full hemispherical scans in a forest environment, providing new opportunities for quantitative data analysis.

Spectral and spatial information from a novel dual-wavelength full-waveform terrestrial laser scanner for forest ecology

The Salford Advanced Laser Canopy Analyser (SALCA) is an experimental terrestrial laser scanner designed and built specifically to measure the structural and biophysical properties of forest canopies. SALCA is a pulsed dual-wavelength instrument with co-aligned laser beams recording backscattered energy at 1063 and 1545 nm; it records full-waveform data by sampling the backscattered energy at 1 GHz giving a range resolution of 150 mm. The finest angular sampling resolution is 1 mrad and around 9 million waveforms are recorded over a hemisphere above the tripod-mounted scanner in around 110 min. Starting in 2010, data pre-processing and calibration approaches, data analysis and information extraction methods were developed and a wide range of field experiments conducted. The overall objective is to exploit the spatial, spectral and temporal characteristics of the data to produce ecologically useful information on forest and woodland canopies including leaf area index, plant area volume density and leaf biomass, and to explore the potential for tree species identification and classification. This paper outlines the key challenges in instrument development, highlights the potential applications for providing new data for forest ecology, and describes new avenues for exploring information-rich data from the next generation of terrestrial laser scanners instruments like SALCA.

Erratum to: Terrestrial Laser Scanning for Plot-Scale Forest Measurement

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