Seasonal inundation patterns in two large savanna floodplains of South America: the Llanos de Moxos (Bolivia) and the Llanos del Orinoco (Venezuela and Colombia)

Inundation patterns in two of the largest savanna floodplains of South America were studied by analysis of the 37‐GHz polarization difference observed by the Scanning Multichannel Microwave Radiometer (Nimbus‐7 satellite). Flooded area was estimated at monthly intervals for January 1979 through to August 1987 using mixing models that account for the major landscape units with distinctive microwave emission characteristics. Results are presented separately for five subregions in each of the two floodplain regions to show the spatial as well as temporal variability in inundation patterns. The total area inundated during the 9 years varied between 2069 and 78 460 km² in the Llanos de Moxos (also spelled as Mojos; median area, 23 383 km²) and 1278 and 105 454 km² in the Llanos del Orinoco (median, 25 374 km²), not including the open‐water area of permanent lakes and river channels. The correlation between flooded area and river stage was used to extend the inundation records over a 30‐year period in the Moxos (1967–97) and a 58‐year period (1927–85) in the Orinoco. Interannual variability in inundation is greater in the Moxos than the Orinoco. Comparison of these data, however, with a previously published analysis of the Pantanal wetland shows that inundation patterns in these two floodplain regions are not as variable across years as they are in the Pantanal. Copyright © 2004 John Wiley & Sons, Ltd.     

An investigation of sand–dust storm events and land surface characteristics in China using NOAA NDVI data

Observations from 560 weather stations in China show that sand–dust storms occur most frequently in April in north China. The region consists of Sub-dry Mid Temperate, Dry Mid Temperate, Sub-dry South Temperate and Dry South Temperate Zones and much of the land surface is desert or semi-desert: it is relatively dry with minimal rainfall and a high annual mean temperature. In most regions of China, the annual mean frequency of sand–dust events decreased sharply between 1980 and 1997 and then increased from 1997 to 2000. Statistical analyses demonstrate that the frequency of sand–dust storms correlates highly with wind speed, which in turn is strongly related to land surface features; on the other hand, a significant correlation between storm events and other atmospheric quantities such as precipitation and temperature was not observed. Accordingly, land surface cover characteristics (vegetation, snowfall and soil texture) may play a significant role in determining the occurrence of sand–dust storms in China. Analysis of Normalized Difference Vegetation Index derived from National Oceanic and Atmospheric Administration and Empirical Orthogonal Function show that since 1995 surface vegetation cover in large areas of Northern China has significantly deteriorated. Moreover, a high correlation is shown to exist among the annual occurrence of sand–dust storms, surface vegetation cover and snowfall. This suggests that the deterioration of surface vegetation cover may strongly influence the occurrence of sand–dust storms in China. Soils with coarse and medium textures are found to be more associated with sand–dust storms than other soils.     

Agricultural impacts on ecosystem functioning in temperate areas of North and South America

Land use has a large impact on ecosystem functioning, though evidences of these impacts at the regional scale are scarce. The objective of this paper was to analyze the impacts of agricultural land use on ecosystem functioning (radiation interception and carbon uptake) in temperate areas of North and South America. From land cover maps generated using high-resolution satellite images we selected sites dominated by row crops (RC), small grain crops (SG), pastures (PA), and rangelands (RA) in the Central Plains of USA and the Pampas of Argentina. These two regions share climatic characteristics and the agricultural conditions (crop types) are also very similar. Both areas were originally dominated by temperate grasslands. In these sites we extracted the temporal series of the normalized difference vegetation index (NDVI) from the NOAA satellites for the period 1989–1998 and calculated the mean seasonal NDVI curve for each site. Additionally, we calculated the mean annual NDVI, the maximum NDVI, the date of the year when the max NDVI was recorded and the interannual variability of these three attributes. We compared the mean values of each NDVI-derived attribute between land cover types and between continents. The NDVI seasonal patterns for each land cover type were roughly similar between the Central Plains and the Pampas during the growing season. The largest differences were observed during the winter and spring, when the NDVI of all land cover types in the Central Plains remained at lower values than in the Pampas. This was probably caused by the high annual thermal amplitude in the Central Plains that results in a much more restricted growing season. As a result of these differences in the shape of the NDVI curve, the mean annual NDVI in the Central Plains was lower than in the Pampas for all land cover types but the maximum NDVI did not differ importantly. In both regions, row crops delayed the date of the NDVI peak, small grain crops advanced it and pastures did not change it importantly, compared with rangelands. The interannual variability of the NDVI attributes was higher for small grains than for row crops in both regions. However, small grains crops were consistently more variable between years in the Central Plains than in the Pampas. The opposite occurred with pastures and rangelands, which were more variable in the Pampas than in the Central Plains. This paper confirms and generalizes previous findings that showed important imprints of land use on ecosystem functioning in temperate ecosystems. Our results support the idea that the changes in land cover that have occurred in the Central Plains and the Pampas leaded to similar changes in the way that ecosystems absorb solar radiation and in the patterns of carbon uptake.     

ANALYSIS OF SURFACE SINK OF EXPLORATION VACANCY IN GOLD MINING AREA OF ZHAOYUAN CTIY BASED ON RS AND GIS

1 IN T R O D U C T IO NZhaoyuan C ity, located in northeast of ShandongProvince,iscalled "G old C ity"and itisone ofim portantgold production bases in C hina.The exploitation ofthegold broughtoutthe extensive vacantareas,leading tolarge-scale ground subsi…     

用单片机实现遥控器的红外发射

红外遥控在电子产品中有着越来越广泛的应用.介绍了用凌阳SPCE061A系列单片机实现电子产品的红外遥控发射.     

遥感影像构造地质解译过程中的逻辑形式与逻辑规律讨论

遥感图像是地表地物表征的集合，构成影像景观单元。遥感解译属于人脑意识活动的范畴，是利用表层信息由表及里、由此及彼的逻辑推理过程。探求因果联系的科学归纳法，探求等同关系的类比推理法，探求真实性的科学论证法是遥感解译过程中应遵循的思想方法。     

Optimal orbits for Mars atmosphere remote sensing

Most of the spacecrafts currently around Mars (or planned to reach Mars in the near future) use Sun-synchronous or near-polar orbits. Such orbits offer a very poor sampling of the diurnal cycle. Yet, sampling the diurnal cycle is of key importance to study Mars meteorology and climate. A comprehensive remote sensing data set should have been obtained by the end of the MRO mission, launched in 2005. For later windows, time-varying phenomena should be given the highest priority for remote sensing investigations. We present possible orbits for such missions which provide a rich spatial and temporal sampling with a relatively short repeat cycle (50 sols). After computation and determination of these orbits, said “optimal orbits”, we illustrate our results by tables of sampling and comparison with other orbits.     

The use of remotely sensed land cover to derive floodplain friction coefficients for flood inundation modelling

Remotely sensed land cover was used to generate spatially‐distributed friction coefficients for use in a two‐dimensional model of flood inundation. Such models are at the forefront of research into the prediction of river flooding. Standard practice, however, is to use single (static) friction coefficients on both the channel and floodplain, which are varied in a calibration procedure to provide a “best fit” to a known inundation extent. Spatially‐distributed friction provides a physically grounded estimate of friction that does not require fitting to a known inundation extent, but which can be fitted if desired. Remote sensing offers the opportunity to map these friction coefficients relatively straightforwardly and for low cost. Inundation was predicted using the LISFLOOD‐FP model for a reach on the River Nene, UK. Friction coefficients were produced from land cover predicted from Landsat TM imagery using both ML and fuzzy c‐means classifiction. The elevetion data used were from combined contour and differential global positioning system (GPS) elevation data. Predicted inundation using spatially‐distributed and static friction were compared. Spatially‐distributed friction had the greatest effect on the timing of flood inundation, but a small effect on predicted inundation extent. The results indicate that spatially‐distributed friction should be considered where the timing of initial flooding (e.g. for early warning) is important. Copyright © 2007 John Wiley & Sons, Ltd.     

AN AUTOMATIC PROCEDURE FOR ESTIMATING SPRING SMALL GRAINS ACREAGE FROM LANDSAT DATA

The development and testing of a computerized technique for utilizing multitemporal Landsat multispectral scanner data to estimate spring small grains acreage are described. The Kauth-Thomas green number transformation is applied to the data prior to application of the pixel-level standardized logic. Four years of data from the U.S. and Canada are used in testing. A comparison of the test results to those of the analyst-intensive procedures indicates a potential for increase in near-harvest estimation efficiency with little sacrifice in accuracy.     

APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO REMOTE SENSING*

Remote sensing is a geographic analysis tool capable of producing large quantities of data in the spectral, temporal and spatial domains. Techniques for automating the image analysis process would be advanced by the inclusion of artificial intelligence techniques in the design of image processing systems. The remote sensing application which show promise for successful implementation of artificial intelligence techniques are intelligent onboard processing, advanced database interrogation, and the automated analysis of multispectral imagery.