Our Common Ground, 2005-2

Iowa Department of Natural Resources fact sheet on water.

Our Common Ground, 2005-3

Iowa Department of Natural Resources fact sheet on IGS Rock library

Our Common Ground, 2005-3

Iowa Department of Natural Resources fact sheet on IGS Rock library

Our Common Ground, 2006-2

Iowa Department of Natural Resources fact sheet on exploring the mid-continent rift.

Our Common Ground, 2005-4

Iowa Department of Natural Resources fact sheet on Geographic Information Systems.

Our Common Ground, 2006-1

Using LiDAR to Scan Iowa from Aircraft

Retention half times in the skeleton of plutonium and 90Sr from above-ground nuclear tests: a retrospective study of the Swiss population.

Plutonium and (90)Sr are considered to be among the most radiotoxic nuclides produced by the nuclear fission process. In spite of numerous studies on mammals and humans there is still no general agreement on the retention half time of both radionuclides in the skeleton in the general population. Here we determined plutonium and (90)Sr in human vertebrae in individuals deceased between 1960 and 2004 in Switzerland. Plutonium was measured by sensitive SF-ICP-MS techniques and (90)Sr by radiometric methods. We compared our results to the ones obtained for other environmental compartments to reveal the retention half time of NBT fallout (239)Pu and (90)Sr in trabecular bones of the Swiss population. Results show that plutonium has a retention half time of 40+/-14 years. In contrast (90)Sr has a shorter retention half time of 13.5+/-1.0 years. Moreover (90)Sr retention half time in vertebrae is shown to be linked to the retention half time in food and other environmental compartments. These findings demonstrate that the renewal of the vertebrae through calcium homeostatic control is faster for (90)Sr excretion than for plutonium excretion. The precise determination of the retention half time of plutonium in the skeleton will improve the biokinetic model of plutonium metabolism in humans.

Estimativa do teor de água no solo utilizando dados de radar de abertura sintética

Em virtude da crescente demanda mundial por alimentos, um monitoramento eficaz e em larga escala da umidade do solo constitui fator de grande importância para a previsão de safras. Este trabalho teve por objetivo apresentar uma técnica para o cálculo do teor de água no solo, utilizando modelos preditivos de umidade do solo, baseados em dados de radar de abertura sintética (SAR). Foram utilizados dados do SAR a bordo do JERS-1 ("Japanese Earth Resources Satellite") e dois modelos empíricos. O primeiro relaciona o coeficiente de retroespalhamento com a permissividade complexa (modelo de Dubois), e o segundo relaciona a permissividade complexa com o teor de água do solo e algumas de suas características físico-hídricas, tais como percentagem de areia e argila (modelo de Hallikainen). Inicialmente, os dados do SAR/JERS-1 foram calibrados e, por meio do modelo de Dubois, foram calculados os valores de permissividade complexa. Para tanto, foi necessário inserir níveis estimados de rugosidade do solo. A partir destes resultados, utilizou-se o modelo de Hallikainen para calcular a umidade volumétrica. A análise geral dos resultados indica que a técnica de estimação de umidade do solo a partir de imagens de radar de abertura sintética, utilizada neste estudo, mostrou-se física e matematicamente exeqüível. No entanto, apresentou uma precisão moderada, não sendo ainda recomendada para o uso operacional no mapeamento de umidade do solo. A análise dos resultados revelou também que a precisão dos dados é bastante influenciada pela precisão dos valores de rugosidade introduzidos.

Estimation of surface roughness in a semiarid region from C-band ERS-1 synthetic aperture radar data

In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

A methodology for the classification of convective structures using meteorological radar: Application to heavy rainfall events on the Mediterranean coast of the Iberian Peninsula

During the period 1996-2000, forty-three heavy rainfall events have been detected in the Internal Basins of Catalonia (Northeastern of Spain). Most of these events caused floods and serious damage. This high number leads to the need for a methodology to classify them, on the basis of their surface rainfall distribution, their internal organization and their physical features. The aim of this paper is to show a methodology to analyze systematically the convective structures responsible of those heavy rainfall events on the basis of the information supplied by the meteorological radar. The proposed methodology is as follows. Firstly, the rainfall intensity and the surface rainfall pattern are analyzed on the basis of the raingauge data. Secondly, the convective structures at the lowest level are identified and characterized by using a 2-D algorithm, and the convective cells are identified by using a 3-D procedure that looks for the reflectivity cores in every radar volume. Thirdly, the convective cells (3-D) are associated with the 2-D structures (convective rainfall areas). This methodology has been applied to the 43 heavy rainfall events using the meteorological radar located near Barcelona and the SAIH automatic raingauge network.