利用AMTIS数据反演植被和土壤温度

遥感陆面温度 (LST)是目前遥感界面临的重要课题 ,组分温度反演则为LST反演的主攻目标。如果混合像元组分间的温度及发射率存在明显差别 ,就可以从多角度热辐射亮度变化中分离出组分温度的信息。在热辐射矩阵模型的基础上 ,讨论了确定可反演参数和反演组分温度的方法 ,并以AMTIS多角度热红外图像为数据源 ,在进行几何和大气纠正后 ,尝试利用矩阵反演方法分解混合像元中的植被和土壤温度。误差分析表明土壤温度反演结果较好 ,但植被温度的反演精度不高     

复种指数遥感监测方法

复种指数是反映水土光与自然资源利用程度的指标 ,其实质是沿时间序列 ,反映某一种植制度对耕地的利用程度。联系复种指数与时间序列NDVI曲线的纽带是农作物年内的循环规律。时间序列的NDVI值蕴涵着植被的生长和枯萎的年循环节律 ,经时间序列谐函数分析法 (HarmonicAnalysisofTimeSeries ,HANTS)重构的NDVI曲线 ,可以准确地反映农作物的出苗、拔节、抽穗、收获等物理过程。因此 ,根据时间序列的NDVI曲线的周期性 ,可以反向捕捉到耕地农作物动态的信息 ,进而得到耕地的复种指数。本文依据上述原理 ,提出复种指数遥感监测的方法 ,然后用 1999年至 2 0 0 2年 4年的VGT(SPOT4卫星vegetation数据 )旬合成NDVI时间序列数据集提取了复种指数 ,并利用地面样区观测结果和统计数据进行检验 ,取得很高的精度。     

泰国水稻种植面积月变化的遥感监测

介绍了光学和微波遥感影像相结合进行泰国水稻种植面积监测方法。泰国雨季雨量充足 ,气温适合 ,同一时间耕地上水稻的物候多样 ,每月水稻种植面积都发生变化。利用旱季的TM影像 ,获得耕地信息。同时利用TM影像覆盖的雷达区域进行非耕地去除 ,进行非监督分类 ,提取反映水稻种植不同生长期的雷达影像后向反射系数特征 ,建立各种类型的分类模型 ,采用监督分类的方法对全景雷达数据进行水稻种植情况调查 ,并分别予以识别和统计 ,反映研究区水稻月种植情况。分类结果通过类别检验和面积量算检验进行精度评价和分析。     

The analysis of SPOT-5 characteristics on land cover Classification

<正>KnowledgeaboutlandcoverandlandusehasbecomeincreasinglyimportantastheNationplanstoovercometheproblemsofuncontrolleddevelopment,deterioratingenvironmentalquality,lossofprimeagriculturallandsetc.Landuseandlandcoverdataareneededintheanalysisofenvironmentalprocessesandproblemstoknowiflivingconditionsandstandardsaretobeimprovedormaintainedatcurrentlevels.     

Seasonal and inter-annual relationships between vegetation and climate in central New Mexico, USA

Linear correlations between seasonal and inter-annual measures of meteorological variables and normalized difference vegetation index (NDVI) are calculated at six nearby yet distinct vegetation communities in semi-arid New Mexico, USA Monsoon season (June–September) precipitation shows considerable positive correlation with NDVI values from the contemporaneous summer, following spring, and following summer. Non-monsoon precipitation (October–May), temperature, and wind display both positive and negative correlations with NDVI values. These meteorological variables influence NDVI variability at different seasons and time lags. Thus vegetation responds to short-term climate variability in complex ways and serves as a source of memory for the climate system.     

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.     

The causes and environmental effects of land use conversion during agricultural restructuring in Northeast China

During the last decade of the 20th century, extensive conversion in agricultural land use took place in Northeast China. The goal of this study is to ascertain its spatial distribution and regional differentiation, determine its causes, and analyze its environmental impact. Especially we attempt to elucidate how institutional constraints have facilitated the change at a time of agrarian restructuring when newly emerging free market was hybridized with the former planned economy. Information on six categories of land use was mapped from interpretation of Landsat TM images recorded in 1990, 1995 and 2000. Most of land use changes took place during the first half of the decade, coinciding with abrupt and chaotic changes in government directives. Farmland was changed mainly to woodland, water body and built-up areas while woodland and grassland were converted chiefly to farmland. Spatially, the change from farmland to woodland was restricted to the west of the study area. The change from grassland to farmland took place in the grazing and farming interlocked west. These chaotic and occasionally conflicting changes were largely caused by lack of stability and consistency in agricultural land use policies promulgated. They have exerted adverse impacts on the local environment, including land degradation, increased flooding, and modified climate regime.     

Sequence of faulting and deformation during the 2000 eruptions of the Usu Volcano, Hokkaido, Japan—interpretation and image analyses of aerial photographs

Significant faulting and deformation of the ground surface has been rarely known during volcanic eruptions. Usu Volcano, Hokkaido, Japan, is a unique example of deformation due to felsic magma intrusion. Usu Volcano has a history of such types of eruptions as phreatic, pumice eruption (Plinian type), pyroclastic flowing and lava doming since 1663. On March 31, 2000, phreatomagmatic to phreatic eruptions took place after 23 years of dormancy in the western piedmont, followed by explosions on the western flank of Usu Volcano. They were associated with significant deformation including faulting and uplift. The eruptions and deformation were continuing up to the end of May 2000.We identified the faulting using total nine sets of aerial photographs taken from before the eruption (March 31, 2000) to more than 1 year (April 27, 2001) after the end of the activity, and traced deformation processes through image processing using aerial photographs. We found that some of the new faults and the associated phreatic eruptions were related to old faults formed during the 1977–1981 eruptive episode.The image processing has revealed that the surface deformation is coincident with the area of faulting forming small grabens and the phreatic explosion vents. However, the faulting and main explosive eruptions did not take place in the highest uplift area, but along the margin. This suggests that the faulting and explosive activities were affected by small feeder channels diverging from the main magma body which caused the highest uplift.     

Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool

Contamination of groundwater has become a major concern in recent years. Since testing of water quality of all domestic and irrigation wells within large watersheds is not economically feasible, one frequently used monitoring strategy is to develop contamination potential maps of groundwater, and then prioritize those wells located in the potentially highly contaminated areas for testing of contaminants. However, generation of contamination potential maps based on groundwater sensitivity and vulnerability is not an easy task due inherent uncertainty. Therefore, the overall goal of this research is to improve the methodology for the generation of contamination potential maps by using detailed landuse/pesticide and soil structure information in conjunction with selected parameters from the DRASTIC model. The specific objectives of this study are (i) to incorporate GIS, GPS, remote sensing and the fuzzy rule-based model to generate groundwater sensitivity maps, and (ii) compare the results of our new methodologies with the modified DRASTIC Index (DI) and field water quality data. In this study, three different models were developed (viz. DI_fuzz, VI_fuzz and VI_{fuzz_ped}) and were compared to the DI. Once the preliminary fuzzy logic-based (DI_fuzz) was generated using selected parameters from DI, the methodology was further refined through VI_fuzz and VI_{fuzz_ped} models that incorporated landuse/pesticide application and soil structure information, respectively. This study was conducted in Woodruff County of the Mississippi Delta region of Arkansas. Water quality data for 55 wells were used to evaluate the contamination potential maps. The sensitivity map generated by VI_{fuzz_ped} with soil structure showed significantly better coincidence results when compared with the field data.     

Advances in lunar science from the Clementine mission: A decadal perspective

The Clementine spacecraft orbited the Moon and acquired science data for 10 weeks in the Spring of 1994. During this time it collected global 11-band multispectral images and near global altimetry. Select areas of the Moon were imaged at 25 m/pixel in visible light and 60 m/pixel in thermal wavelengths. From these datasets a new paradigm for the evolution of the lunar crust emerged. The Moon is no longer viewed as a two-terrane planet, the Apollo samples were found not to represent the lunar crust as a whole, and the complexity of lunar crustal stratigraphy was further revealed. More than ten years later the Clementine datasets continue to significantly advance lunar science and will continue to do so as new measurements are returned from planned missions such as Chandrayaan, SELENE, and Lunar Reconnaissance Orbiter. This paper highlights the scientific research conducted over the last decade using Clementine data and summarizes the influence of Clementine on our understanding of the Moon.