Pascal Sirguey

Improving MODIS Spatial Resolution for Snow Mapping Using Wavelet Fusion and ARSIS Concept

We propose to fuse the high spatial content of two 250-m spectral bands of the moderate resolution imaging spectroradiometer (MODIS) into its five 500-m bands using wavelet-based multiresolution analysis. Our objective was to test the effectiveness of this technique to increase the accuracy of snow mapping in mountainous environments. To assess the performance of this approach, we took advantage of the simultaneity between the advanced spaceborne thermal emission and reflection radiometer (ASTER) and MODIS sensors. With a 15-m spatial resolution, the ASTER sensor provided reference snow maps, which were then compared to MODIS-derived snow maps. The benefit of the method was assessed through the investigation of various metrics, which showed an improvement from 3% to 20%. Therefore, the enhanced snow map is of great benefit for environmental and hydrological applications in steep terrain.

A digital rock density map of New Zealand

Digital geological maps of New Zealand (QMAP) are combined with 9256 samples with rock density measurements from the national rock catalogue PETLAB and supplementary geological sources to generate a first digital density model of New Zealand. This digital density model will be used to compile a new geoid model for New Zealand. The geological map GIS dataset contains 123 unique main rock types spread over more than 1800 mapping units. Through these main rock types, rock densities from measurements in the PETLAB database and other sources have been assigned to geological mapping units. A mean surface rock density of 2440kg/m^3 for New Zealand is obtained from the analysis of the derived digital density model. The lower North Island mean of 2336kg/m^3 reflects the predominance of relatively young, weakly consolidated sedimentary rock, tephra, and ignimbrite compared to the South Islands 2514kg/m^3 mean where igneous intrusions and metamorphosed sedimentary rocks including schist and gneiss are more common. All of these values are significantly lower than the mean density of the upper continental crust that is commonly adopted in geological, geophysical, and geodetic applications (2670kg/m^3) and typically attributed to the crystalline and granitic rock formations. The lighter density has implications for the calculation of the geoid surface and gravimetric reductions through New Zealand.

Performance and Accuracy of Lightweight and Low-Cost GPS Data Loggers According to Antenna Positions, Fix Intervals, Habitats and Animal Movements.

Recently developed low-cost Global Positioning System (GPS) data loggers are promising tools for wildlife research because of their affordability for low-budget projects and ability to simultaneously track a greater number of individuals compared with expensive built-in wildlife GPS. However, the reliability of these devices must be carefully examined because they were not developed to track wildlife. This study aimed to assess the performance and accuracy of commercially available GPS data loggers for the first time using the same methods applied to test built-in wildlife GPS. The effects of antenna position, fix interval and habitat on the fix-success rate (FSR) and location error (LE) of CatLog data loggers were investigated in stationary tests, whereas the effects of animal movements on these errors were investigated in motion tests. The units operated well and presented consistent performance and accuracy over time in stationary tests, and the FSR was good for all antenna positions and fix intervals. However, the LE was affected by the GPS antenna and fix interval. Furthermore, completely or partially obstructed habitats reduced the FSR by up to 80% in households and increased the LE. Movement across habitats had no effect on the FSR, whereas forest habitat influenced the LE. Finally, the mean FSR (0.90 ± 0.26) and LE (15.4 ± 10.1 m) values from low-cost GPS data loggers were comparable to those of built-in wildlife GPS collars (71.6% of fixes with LE < 10 m for motion tests), thus confirming their suitability for use in wildlife studies.

Measuring body length of male sperm whales from their clicks: The relationship between inter-pulse intervals and photogrammetrically measured lengths

Sperm whales (Physeter macrocephalus) emit short, broadband clicks which often include multiple pulses. The time interval between these pulses [inter-pulse interval (IPI)] represents the two-way time for a pulse to travel between the air sacs located at either end of the sperm whales head. The IPI therefore, is a proxy of head length which, using an allometric relationship, can be used to estimate total body length. Previous studies relating IPI to an independent measure of length have relied on very small sample sizes and manual techniques for measuring IPI. Sound recordings and digital stereo photogrammetric measurements of 21 individuals were made off Kaikoura, New Zealand, and, in addition, archived recordings of whales measured with a previous photogrammetric system were reanalyzed to obtain a total sample size of 33 individuals. IPIs were measured automatically via cepstral analysis implemented via a software plug-in for pamguard, an open-source software package for passive acoustic monitoring. IPI measurements were highly consistent within individuals (mean CV=0.63%). The new regression relationship relating IPI (I) and total length (T) was found to be T=1.258I+5.736 (r(2)=0.77, p<0.001). This new regression provides a better fit than previous studies of large (> 11 m) sperm whales.

Simple correction of multiple reflection effects in rugged terrain

Operational correction of optical satellite sensor imagery usually models radiation reflected from surrounding terrain with a first‐order reflection function. In rugged areas and snowy environments, the trapping of radiation between adjacent slopes can make such an approximation inadequate, leading to underestimation of the amount of irradiance, and overestimation of the ground reflectance. It is shown that a multiple reflection model, based on mean parameters computed from the terrain neighbourhood, converges to a simple correction factor. Comparison between first‐order and multiple reflection models shows that the reflectance of snow targets, in very rugged terrain, may be overestimated by up to 30% if disregarding multiple reflections. This potentially explains saturated values obtained from topographic correction algorithms which only use a first‐order terrain function, e.g. ATCOR3, and demonstrates that correction for multiple reflections should be implemented in specific environments.

Satellite remote sensing procedures for glacial terrain analyses and hazard assessment in the Aoraki Mount Cook region, New Zealand

Abstract Hazards originating within glacial environments have received limited attention in New Zealand. In view of rapidly changing environmental conditions and the need for ongoing monitoring, overseas studies have recognised the importance of remote sensing procedures to support related hazard investigations. The initial goal for regional hazard studies is the identification of potential source areas on the basis of terrain analyses. Following a review of remotely sensed imagery and its application in glacial studies, several methods are applied here to map glacial ice, lakes, and debris accumulations in the Mount Cook region of New Zealand using freely available ASTER imagery. A new method for mapping turbid and clear water glacial lakes is presented, and the first application of a method for mapping debris accumulations at the regional scale appears promising for debris flow hazard investigations. Analyses of terrain changes reveal that a 20% expansion in lake area has continued over recent years, increasing the hazard potential from mass movement induced outburst flooding. A framework for the assessment of hazard potential in the region is introduced, requiring the integration of terrain analyses presented here with permafrost distribution modelling, geological mapping, and topographic analyses.

On the Importance of High-Resolution Time Series of Optical Imagery for Quantifying the Effects of Snow Cover Duration on Alpine Plant Habitat

We investigated snow cover dynamics using time series of moderate (MODIS) to high (SPOT-4/5, Landsat-8) spatial resolution satellite imagery in a 3700 km2 region of the southwestern French Alps. Our study was carried out in the context of the SPOT (Take 5) Experiment initiated by the Centre National d’Etudes Spatiales (CNES), with the aim of exploring the utility of high spatial and temporal resolution multispectral satellite imagery for snow cover mapping and applications in alpine ecology. Our three objectives were: (i) to validate remote sensing observations of first snow free day derived from the Normalized Difference Snow Index (NDSI) relative to ground-based measurements; (ii) to generate regional-scale maps of first snow free day and peak standing biomass derived from the Normalized Difference Vegetation Index (NDVI); and (iii) to examine the usefulness of these maps for habitat mapping of herbaceous vegetation communities above the tree line. Imagery showed strong agreement with ground-based measurements of snow melt-out date, although R2 was higher for SPOT and Landsat time series (0.92) than for MODIS (0.79). Uncertainty surrounding estimates of first snow free day was lower in the case of MODIS, however (±3 days as compared to ±9 days for SPOT and Landsat), emphasizing the importance of high temporal as well as high spatial resolution for capturing local differences in snow cover duration. The main floristic differences between plant communities were clearly visible in a two-dimensional habitat template defined by the first snow free day and NDVI at peak standing biomass, and these differences were accentuated when axes were derived from high spatial resolution imagery. Our work demonstrates the enhanced potential of high spatial and temporal resolution multispectral imagery for quantifying snow cover duration and plant phenology in temperate mountain regions, and opens new avenues to examine to what extent plant community diversity and functioning are controlled by snow cover duration.

Seven years of snow cover monitoring with MODIS to model catchment discharge in New Zealand

MODIS/TERRA was used to monitor the snowpack dynamics in the Waitaki catchment, New Zealand, from 2000 to 2007. Daily meteorological data (i.e., temperature and precipitation) and frequent observations of the snowpack were used with the Snowmelt Runoff Model (SRM) to simulate the daily discharge of the Ohau, Pukaki, and Tekapo catchments. The results obtained over these seven years brought considerable improvements in terms of modelling performances compared to previous efforts conducted in the region. It shed new light about the relative contribution of snowmelt to the discharge. The simulations also suggest that the severe drought of 2005 was largely mitigated by ice melt from glaciers in the Pukaki basin. A contribution of glacier melt much larger than normal is believed to have sustained the discharge to within 17% of the mean annual flow, although the precipitation was reduced by 34%.

Towards a vector agent modelling approach for remote sensing image classification

Object-based remote sensing image classification is known for its ability to elicit objects that correspond one-on-one with real-world objects. However, it is still subject to a two-stage linear segmentation and classification process and a limited ability to use geometry, class identity and neighbourhood information in that process. This paper explores the scope of intelligent vector agents (VAs), potentially unifying segmentation and classification, and, as implemented through the Geographic Automata System framework, explicitly modelling a set of vector objects with (1) elastic geometry, (2) states, (3) neighbourhoods and embedded rules connecting all three. A brief illustration involving geometry, geometry rules and states is presented.

Improved resolution for the detection of snow with MODIS using wavelet fusion

We propose to implement the ARSIS concept to fuse the high spatial content of the two 250 m spectral bands of MODIS into its five 500 m bands using wavelet based multi- resolution analysis. Our objective was to test the effectiveness of this technique to increase the accuracy of snow mapping in mountainous environments. To assess the performance of this approach, we took advantage of the simultaneity between ASTER and MODIS sensors, both on the TERRA platform. With a 15 m spatial resolution, the ASTER sensor provided reference snow maps that were then compared to MODIS derived snow maps. The benefit of the method was assessed through the investigation of various metrics. The enhanced snow map are therefore of great benefit for environmental and hydrological applications in steep terrain.