Magaly Koch

Multisensor approach to determine changes of wetland characteristics in semiarid environments (central Spain)

Saline wetlands in the semiarid environment of Central Spain are fragile and highly dynamic ecosystems that are affected by degradation processes as a result of anthropological influences. An increase in agricultural production has led to the development of large-scale irrigation schemes with overexploitation of groundwater, and with consequent effects on the complex hydrology and associated land use. In this work, data from field, hyperspectral airborne, and multispectral satellite sensors are used in order to determine changes of wetland characteristics over time. The spectra of surface components (soil, vegetation, and salt crusts) were selected from the hyperspectral data and identified as endmembers using a site-specific spectral library. The spectral information contained in these endmembers was extrapolated to a temporal series of broadband multispectral imagery on which spectral unmixing analysis was performed in order to detect changes in the wetland over time. Results showed that the selected wetland components have undergone important changes in both their total area as well as their spatial distribution. These changes are mainly associated with the anthropogenic impact; however, natural influences due to seasonal fluctuations may coincide with the overall changes, although this in general is difficult to determine. Water regulation and agricultural practices directly influence the salinity of the soils and therefore the nature of the hygrophytic vegetation.

A spectral library for a semi-arid wetland and its application to studies of wetland degradation using hyperspectral and multispectral data

Semi-arid wetland areas in Central Spain are especially sensitive ecosystems and are considered to be one of the most important areas for the migration and wintering of waterfowl in Europe. Many of these wetland areas are saline or sub saline and are subjected to natural (seasonal) as well as human induced changes. Factors causing changes that significantly alter or modify the ecological function of these wetlands are considered to be degradation processes. The use of hyperspectral and multispectral data together with ground spectra and field studies has a great potential for monitoring wetland conditions. In this work spectral and analytical information concerning soil, vegetation and land use, contained in a site specific spectral library, is linked with the spectral characteristics of components from an anthropogenic influenced wetland area in La Mancha Alta. This information forms the basis for determining and selecting end members from hyperspectral data (DAIS 7915), which are then extrapolated to lower spatial and spectral resolution multispectral Landsat ETM+ and TM data. A spectral unmixing is carried out to obtain a multitemporal analysis for evaluating wetland degradation. Results show that the approach is successful in determining rapid surface change due to anthropogenic influences. Spectral unmixing results present an increase of salt-affected soil and a redistribution of saline pasture. This is further supported with a post classification change detection assessment and ground data confirm that principal causes are changes in wetland use together with water regulation of the Cigüela river.

Lineament mapping for groundwater resource assessment: A comparison of digital Synthetic Aperture Radar (SAR) imagery and stereoscopic Large Format Camera (LFC) photographs in the Red Sea Hills, Sudan

Abstract The results of a comparative investigation of lineament mapping from stereoscopic Large Format Camera (LFC) photographs and from SIR-C L- and C-band Synthetic Aperture Radar (SAR) data are described. The lineament patterns are used to test a model developed by Koch (1993) of groundwater flow in the arid Red Sea Hills area of Sudan. Initial results show that the LFC imagery is most useful for mapping detailed fracture patterns while the combination of the L- and C-bands of the SIR-C Synthetic Aperture Radar is helpful in the location of major deep-seated fracture zones. The lineament patterns derived from LFC and SIR-C show strong N-S and E-W orientations, which correspond to the current tectonic configuration of the Red Sea rift system. The longer E-W trending features may be important from a regional hydro-geological point of view, whereas the shorter features are significant in that they interconnect the major faults.

An evaluation of Landsat TM spectral data and SAR-derived textural information for lithological discrimination in the Red Sea Hills, Sudan

Abstract The effectiveness of spectral and textural information in the identification of surface rock types in an arid region, the Red Sea Hills of Sudan, is evaluated using spectral information from the six Landsat TM optical bands and textural features derived from Shuttle Imaging Radar-C (SIR-C) C-band HH polarization data. An initial classification is derived from Landsat TM data alone using three classification algorithms, Gaussian maximum likelihood, a multi-layer feed-forward neural network and a Kohonen self-organizing feature map (SOM), to generate lithological maps, with classification accuracy being measured using a confusion matrix approach. The feed-forward neural net produced the highest overall classification accuracy of 57 per cent and was, therefore, selected for the second experiment, in which texture measures from SIR-C C-band HH-polarized synthetic aperture radar (SAR) data are added to selected TM spectral features. Four methods of measuring texture are employed, based on the Fourier ...

Evaluating Full Polarimetric C- and L-Band Data for Mapping Wetland Conditions in a Semi-Arid Environment in Central Spain

Semi-arid wetlands are very dynamic ecosystems as the different characteristics (areal extension, water depth and salinity, seasonal flooding, vegetation and fauna) that define them vary greatly in the short and long term. The objective of this work is to evaluate the contributions of Radarsat-2 (C-band) and ALOS PALSAR (L-band) full polarimetric data in characterizing and mapping wetland conditions in a semi-arid environment in Central Spain. The National Park of Las Tablas de Daimiel was selected as a test site because of on-going work in this wetland area which has produced ample information on the distribution of vegetation communities, soil types and wetland conditions obtained from spaceborne, airborne and ground based optical multispectral and hyperspectral sensors. The goal is to understand and evaluate the complementary information derived from multipolarized synthetic aperture radar (SAR) data not otherwise obtainable from optical sensors. Results suggest that the multipolarized SAR data enables a better separation of the vegetation structure and fragmentation than with the optical data. Optical sensors have the general advantage of improved spectral characterization of vegetation and soil types but are less effective in characterizing vegetation/soil morphology and detecting moisture conditions under dense canopies. Therefore, a combination of the radar and optical data can be very useful in assessing the wetland degradation status, so that appropriate measures can be designed for a sustainable management of the wetland. However, before such an integrated approach can be implemented, a thorough understanding of the type and nature of information derived from multi-frequency and multipolarized SAR data is needed.

Geological controls of land degradation as detected by remote sensing: A case study in Los Monegros, north-east Spain

The focus of the work reported in this paper is on the way in which land degradation processes affecting semi-arid Mediterranean environments are enhanced by the operation of external (human-induced) factors. A study of landscape change in the Los Monegros area of Aragon, north-east Spain, over the period 1984-1997 has been undertaken in order to evaluate the effects of the extension of irrigation on the expansion of arable agriculture, and to estimate the consequential effects on the landscape. Radiometrically-calibrated Landsat TM data were combined with ground-based observations (soil and geology maps, plus hydrogeological data) with the aim of analysing temporal change in land cover. A combination of remote sensing methods (linear spectral unmixing and principal components analysis) was used to determine the proportions of individual soil types. Change detection techniques were employed to pick out areas at risk from land degradation processes (increased soil erosion and soil salinization) and to explain the ways in which agricultural land-use practices interact with the geological and hydrogeological characteristics of the study area.

Textural and compositional characterization of Wadi Feiran deposits, Sinai Peninsula, Egypt, using Radarsat-1, PALSAR, SRTM and ETM+ data.

The present work aims at identifying favorable locations for groundwater resources harvesting and extraction along the Wadi Feiran basin, SW Sinai Peninsula, Egypt, in an effort to facilitate new development projects in this area. Landsat ETM+, Radarsat-1 and PALSAR images of Wadi Feiran basin were used in this work to perform multisource data fusion and texture analysis, in order to classify the wadi deposits based on grain size distribution and predominant rock composition as this information may lead to the location of new groundwater resources. An unsupervised classification was first performed on two sets of fused images (i.e., ETM+/Radarsat-1 and ETM+/PALSAR) resulting in five classes (hybrid classes) describing the main alluvial sediments in the wadi system. Some variations in the spatial distribution of individual classes were observed, due to the different spectral and spatial resolutions of Radarsat-1 (C-band, 12.5 m) and PALSAR (L-band, 6.25 m) data. Alluvial deposits are mixtures of parent rocks located further upstream often at a great distance. In order to classify the alluvial deposits in terms of individual rock types (endmembers), a spectral linear unmixing of the optical ETM+ image was performed. Subsequently, each class of the fused (hybrid) images was correlated with (1) individual rock type fractions (endmembers) obtained from spectrally unmixing the ETM+ image, (2) the geocoded and calibrated radar images (Radarsat-1 and PALSAR) and, (3) the slope map generated from the SRTM data. The goal was to determine predominant rock composition, mean backscatter and slope values for each of the five hybrid classes. Backscatter coefficient values extracted from both radar data (C- and L-band) were correlated and checked in the field, confirming that both wavelengths produced more or less similar textural classes that correspond to specific grain or fragment sizes of alluvial deposits. However, comparison of the spatial distribution of matching hybrid classes showed some variations due to the greater discrimination power of surface texture by Radarsat-1 C-band despite its lower spatial resolution. Furthermore, both hybrid classification results showed that regardless of elevation, areas that are covered by fine and moderate grains (fine sand to pebble) and are located along gentle terrains are favorable for groundwater recharge; while areas that are covered by very coarse grains (cobble to boulder) and are located along steep terrains are more likely to be affected by flash floods.

Land-Cover Phenologies and Their Relation to Climatic Variables in an Anthropogenically Impacted Mediterranean Coastal Area

Abstract: Mediterranean coastal areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor vegetation phenological variations. This study quantitatively describes Enhanced Vegetation Index (EVI) temporal changes for Mediterranean land-covers from the perspective of vegetation phenology and its relation with climate. A time series from 2001 to 2007 of the MODIS Enhanced Vegetation Index 16-day composite (MOD13Q1) was analyzed to extract anomalies (by calculating z-scores) and frequency domain components (by the Fourier Transform). Vegetation phenology analyses were developed for diverse land-covers for an area in south Alicante (Spain) providing a useful way to analyze and understand the phenology associated to those land-covers. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the

The Application of Predictive Modelling for Determining Bio-Environmental Factors Affecting the Distribution of Blackflies (Diptera: Simuliidae) in the Gilgel Gibe Watershed in Southwest Ethiopia

Blackflies are important macroinvertebrate groups from a public health as well as ecological point of view. Determining the biological and environmental factors favouring or inhibiting the existence of blackflies could facilitate biomonitoring of rivers as well as control of disease vectors. The combined use of different predictive modelling techniques is known to improve identification of presence/absence and abundance of taxa in a given habitat. This approach enables better identification of the suitable habitat conditions or environmental constraints of a given taxon. Simuliidae larvae are important biological indicators as they are abundant in tropical aquatic ecosystems. Some of the blackfly groups are also important disease vectors in poor tropical countries. Our investigations aim to establish a combination of models able to identify the environmental factors and macroinvertebrate organisms that are favourable or inhibiting blackfly larvae existence in aquatic ecosystems. The models developed using macroinvertebrate predictors showed better performance than those based on environmental predictors. The identified environmental and macroinvertebrate parameters can be used to determine the distribution of blackflies, which in turn can help control river blindness in endemic tropical places. Through a combination of modelling techniques, a reliable method has been developed that explains environmental and biological relationships with the target organism, and, thus, can serve as a decision support tool for ecological management strategies.

Remote Sensing Application for Water Quality Assessment in Lake Timsah, Suez Canal, Egypt

Lake Timsah lies along the middle section of Suez Canal in Egypt, and is the backbone of the tourism and fishing industry in Ismailia City, providing a significant portion to its income. In recent years, however, Lake Timsah has been subjected to significant environmental changes caused by various anthropogenic activities. Remote sensing and biological monitoring program were integrated for assessing its water quality. Sixteen sites were selected throughout the lake for in situ measurements and collecting water samples which were subsequently analysed. The analysed water parameters were regressed against calibrated radiance values extracted from a high resolution WorldView-2 image. The regression analysis resulted in six unique models with high determination coefficient (R 2 ) and probability (P) at 95% confidence level. These models were then applied to the WV-2 image to produce six unique water quality maps for the entire Lake Timsah. These maps were subsequently used to select the appropriate sites for collecting aquatic macro-invertebrates that serve as good bio-indicators for assessing the water quality of Lake Timsah. This collected biota was used to calculate the Hilsenhoff Biotic Index (HBI) which is an indirect measure of pollution tolerance. The HBI scores indicate the water quality of Lake Timsah ranged from poor to fairly poor. KeywordsWater Samples Analysis; Optical Satellite Data; Regression Analysis; Biotic Index; Water Evaluation; Lake Timsah Egypt