Magaly Koch

Using automated supervised methods with satellite and aerial imageries for liquefaction mapping is a promising step in providing detailed and region-scale maps of liquefaction extent immediately after an earthquake. The accuracy of these methods depends on the quantity and quality of training samples and the number of available spectral bands. Digitizing a large number of high-quality training samples from an event may not be feasible in the desired timeframe for rapid response as the training pixels for each class should be typical and accurately represent the spectral diversity of that specific class. To perform automated classification for liquefaction detection, we need to understand how to build the optimal and accurate training dataset. Using multispectral optical imagery from the 22 February, 2011 Christchurch earthquake, we investigate the effects of quantity of high-quality training pixel samples as well as the number of spectral bands on the performance of a pixel-based parametric supervised maximum likelihood classifier for liquefaction detection. We find that the liquefaction surface effects are bimodal in terms of spectral signature and therefore, should be classified as either wet liquefaction or dry liquefaction. This is due to the difference in water content between these two modes. Using 5-fold cross-validation method, we evaluate performance of the classifier on datasets with different pixel sizes of 50, 100, 500, 2000, and 4000. Also, the effect of adding spectral information was investigated by adding once only the near infrared (NIR) band to the visible red, green, and blue (RGB) bands and the other time using all available 8 spectral bands of the World-View 2 satellite imagery. We find that the classifier has high accuracies (75%-95%) when using the 2000 pixels-size dataset that includes the RGB+NIR spectral bands and therefore, increasing to 4000 pixels-size dataset and/or eight spectral bands may not be worth the required time and cost. We also investigate accuracies of the classifier when using aerial imagery with same number of training pixels and either RGB or RGB+NIR bands and find that the classifier accuracies are higher when using satellite imagery with same number of training pixels and spectral information. The classifier identifies dry liquefaction with higher user accuracy than wet liquefaction across all evaluated scenarios. To improve classification performance for wet liquefaction detection, we also investigate adding geospatial information of building footprints to improve classification performance. We find that using a building footprint mask to remove them from the classification process, increases wet liquefaction user accuracy by roughly 10%.

Spectroradiometric soil surveys (field radiometry) are a valuable technique for soil classification and properties estimation. Field radiometry combines -in a relatively easy-to-use procedure- a fast, accurate and non-destructive sampling method. A wide range of soil properties have been quantitatively estimated with field or laboratory radiometry. In addition, field radiometry is a basic stage in remote sensing studies. It allows the up-scaling process of soil, vegetation or water parameters from the ground level to the airborne or spaceborne sensors level. Field radiometry plays a crucial role in training and validation stages of quantitative remote sensing. A complex problem in remote sensing appears when several components are mixed within a pixel and the resulting pixel's spectrum is a combination of the individual components. This work assess the effect of vegetation in soil properties estimation with linear regression models. Field spectra were taken from soil-vegetation ...

Abstract Climate change and increasing urbanization have intensified scientific interest in understanding the impact of vegetation cover on human health. While the elderly population (persons 65+y.o.) continues to grow, environmental determinants for asthma in this group remain poorly understood. Using spatial and time series analysis we investigated the effect of vegetation cover as measured by the Normalized Difference Vegetation Index (NDVI) on asthma hospitalization rates (AHR)(ICD-9 codes 493.0-9) among Medicare recipients in seven northeastern United States. We considered potential confounders, including income, land cover category, seasonal influenza activity, and population density, classified as urban, suburban, and rural. Time-series analysis identified seasonal patterns in elderly asthma hospitalizations as counter-phase with NDVI: when vegetation vigor increases, AHR decreases (R 2 =0.59, p=0.001). Winter peaks of influenza correlated with an increase in AHR (R 2 =0.43, ...

Groundwater recharge potential and flow regime along the western desert of Egypt are still not well understood. Thus, the present work aims at integrating different levels of hydrological information that can be derived from space- and ground-based sensors to explore renewable groundwater aquifers west of Aswan City. This area is covered by a thin sheet of desert sand and has most probably been affected by the geo-structural settings that shaped the eastern Nile Kom Ombo basin. The thermal bands of ASTER images were used to calculate the Land Surface Temperature (LST), which revealed straight zones of low thermal anomalies, extending parallel and diagonally to the present River Nile. These detected low thermal anomaly zones most probably represent buried channels within the study area. Moreover, images from the low frequency ALOS/PALSAR L-band radar sensor have been used to penetrate the desert sand and delineate the subsurface structures in the area. The existence of such space-bor...

Sensitive ecosystems such as wetlands in a semi-arid environment of Central Spain are important indicators of environmental quality and biodiversity for an area dominated by human induced activities. These areas support an important ecological function for the variety of natural plant species as well as migrating and wintering waterfowl. The wetland areas are classified as saline and sub saline due

The National Park of Las Tablas de Daimiel in Central Spain is a wetland area of great value regarding biodiversity and wildlife habitat. This type of ecosystem is unique within a semi-arid climate and especially sensitive to degradation processes caused by growing pressure on natural resources (agricultural practices, groundwater depletion and land use change) as well as climatic changes. The objective of this work is to determine semi-arid wetland characteristics that are related to indicators of quality or degradation that represent the wetland state as a result of human-induced activities applying multi-angle Proba-1/CHRIS data. Data acquisitions were taken when the wetland area was under the influence of dry or wet conditions as a result of management practices intended to regulate the ecosystem habitat. The methodology is focused on obtaining wetland information related to wetland indicators (vegetation, water mass, soil and sediments). Endmembers are identified and a partial ...

ABSTRACT The assessment of flash flood potential of wadi (dry river) systems in arid lands is often difficult because of the lack of sufficiently long rainfall and discharge records of the infrequent and spatially variable rainfall events. Characterization of active wadi systems by remote sensing may offer an alternative solution. A methodology is presented to characterize the channel infill of wadi systems based on the soil composition, and the geomorphic and geologic properties of drainage basins. Spectral mixture modeling is performed on a Landsat TM image to identify the source material (endmembers) and source upland area of the alluvial infill. Endmembers are determined by two methods: (1) identifying pure image pixels, and (2) using spectral libraries representing main rock units of the drainage basin. Both methods are evaluated in terms of their ability to establish the relative contribution of upland source rocks to the overall alluvium composition in the lowland. The identification of wadi systems that are presently most active (high stream-power values) and efficient in transporting sediments to the basin outlet may enable identification of areas prone to flash floods.

ABSTRACT A desert plain in Egypt is being investigated to develop new techniques of multisensor data integration for groundwater exploration. A combination of multispectral, thermal and microwave data (ASTER and PALSAR) and supported by ground measurements (GPR, field spectroradiometry and magnetometry) were used to investigate surface sediment characteristics of the El-Gallaba Plain area, NW of Aswan. This desert plain once hosted an ancestral river system long before the Nile even existed. Nowadays the fluvial deposits are largely covered by Aeolian and gravelly sands and thus only detectible with radar and thermal images. Results show two broad strips of thermal cooling anomalies arranged in a linear fashion and diagonally crossing the alluvial basin. Spectral signatures collected along the linear land surface temperature (LST) anomalies show generally higher reflectance values (higher albedo) than the surrounding sediments. Both, the cooler LST and higher albedo, suggest that the surface sediments within the anomaly strips have lower emissivity values (low heat storage capacity). Furthermore, the homogeneity of these sediments was measured with a ground penetrating radar (GPR) using 250 & 100 MHz shielded antenna. The 12 GPR profiles across the LST anomalies confirmed that the near-surface sediments (up to 10 m depth) consist of thin horizontal layers of sandstone with very low gravel content. They show very different textural and compositional characteristics with respect to the surrounding areas suggesting a different depositional environment. Thus 12 magnetic profiles with 1.5 km average length were acquired across the LST anomalies to investigate deep seated structures. The results confirmed the existence of graben-like structures with a maximum depth to the basement of 150 m and shallower depths toward the edges of the LST anomalies. Consequently, these structurally controlled basins could be promising areas for ground water accumulation and exploration in the El-Gallaba Plain of the Western Desert in Egypt.

... Complutense 22 28040 Madrid, Spain thomas.schmid@ciemat.es ... The climate is semiarid Mediterranean and the topography is undulating with agricultural fields covering the plateau area as well as the Tajo river valley, which divides the plateau with steep escarpments. ...

... thomas.schmid@ciemat.es 2. Center for Remote Sensing, Boston University, Boston, MA, USA ... The topography is ondulating with agri-cultural influenced plateau areas, known as paramo, with a maximum height of 780 m above sea level (asl) and divided by the Tajo river basin ...