Temporal change detection in river courses and flood plains in an arid environment through satellite remote sensing

Temporal changes in ephemeral river courses and associated flood plains, which could not be detected by Landsat MSS due to its poor spatial resolution of 80m, have been identified and mapped within 10% accuracy by Landsat TM False colour composite because of its higher spectral and spatial resolution of 30 m. Over a period of 28 years (1958–86) the river courses widened upto 1.8 times through bank erosion due to the recurring flash floods. The flash floods have also caused morphological, soil fertility and landuse changes in the associated flood plains, which could also be monitored by the Landsat TM.     

Analysis of Interpolation Methods for Kinematic DGPS Control in Aerial Photogrammetry

Kinematic differential Global Positioning System (DGPS) positioning is routinely used in industry for directly observing an aircraft's position at each instant of photographic exposure during a photogammetric survey. A critical aspect of the subsequent data processing is estimation of the aircraft position at the exact time of exposure. GPS measurements are acquired at a uniform sampling rate, typically 1 Hz. The exposure times, however, do not generally coincide with these times. As a result, the exposure station positions must be interpolated from the adjacent GPS positions. This is typically done using a low-order polynomial, expressed as a function of time, for each coordinate dimension. However, trajectory perturbations induced by atmospheric turbulence can render such interpolation methods ineffective. This article will convey the results of an investigation into the use of several different interpolation models with airborne GPS data during straight, level flight. The fundamental task of time series reconstruction will first be addressed, in which several possible interpolation models are described. Two 10-Hz, airborne GPS data sets were collected to test the accuracy of each model. The error properties resulting from the application of each model to these data will be presented and analyzed in terms of time-domain statistics and frequency-domain characteristids. It will be demonstrated that interpolation error can be significantly reduced, especially in the height dimension, through judicious choice of an interpolator. ? 2000 John Wiley & Sons, Inc.     

The Integration of Cooperation Model and Genetic Algorithm

In the photogrammetry,some researchers have applied genetic algorithms in aerial image texture classification and reducing hyper-spectrum remote sensing data.Genetic algorithm can rapidly find the solutions which are close to the optimal solution.But it is not easy to find the optimal solution.In order to solve the problem,a cooperative evolution idea integrating genetic algorithm and ant colony algorithm is presented in this paper.On the basis of the advantages of ant colony algorithm,this paper proposes the method integrating genetic algorithms and ant colony algorithm to overcome the drawback of genetic algorithms.Moreover,the paper takes designing texture classification masks of aerial images as an example to illustrate the integration theory and procedures.     

Shape Similarity measures of Linear Entities

The essential of feature matching technology lies in how to measure the similarity of spatial entities.Among all the possible similarity measures,the shape similarity measure is one of the most important measures because it is easy to collect the necessary parameters and it is also well matched with the human intuition.In this paper a new shape similarity measure of linear entities based on the differences of direction change along each line is presented and its effectiveness is illustrated.     

Degradation of native wheat straw lignin by Streptomyces viridosporus T7A

Lignin is one of the major contributing factors toward the recalcitrance of lignocellulosic biomass. Understanding the process of lignin degradation in natural biological processes will provide useful information to develop novel biomass conversion technologies. Functional group changes in the lignin entities during the process may contribute to the cellulose degradation (utilization) by the microorganisms. In this study, compositional and advanced Fourier transform infrared, pyrolysis gas chromatography/mass spectrometry and ¹³C cross polarization/magic angle spinning nuclear magnetic resonance analysis were performed to explore the mechanism of biodegradation of wheat straw by Streptomyces viridosporus T7A. The results indicated that S. viridosporus T7A removed lignin and hemicelluloses as indicated by the increased carbohydrate/lignin ratio. Significant modification of carbonyl and methoxyl groups in the complex lignin structure was also evident. Most importantly, the quantitative results showed that lignin degradation was featured by deduction of guaiacyl unit. The results provide new insight for understanding lignin degradation by bacteria.     

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.     

Past,present and future vegetation-cloud feedbacks in the Amazon Basin

To begin exploring the underlying mechanisms that couple vegetation to cloud formation processes, we derive the lifting condensation level (LCL) to estimate cumulus cloud base height. Using a fully coupled land–ocean–atmosphere general circulation model (HadCM3LC), we investigate Amazonian forest feedbacks on cloud formation over three geological periods; modern-day (a.d. 1970–1990), the last glacial maximum (LGM; 21 kya), and under a future climate scenario (IS92a; a.d. 2070–2090). Results indicate that for both past and future climate scenarios, LCL is higher relative to modern-day. Statistical analyses indicate that the 800 m increase in LCL during the LGM is related primarily to the drier atmosphere promoted by lower tropical sea surface temperatures. In contrast, the predicted 1,000 m increase in LCL in the future scenario is the result of a large increase in surface temperature and reduced vegetation cover.