放牧对退化草地近地面辐射的影响

随着环境变化,草原地表状态也会改变,尤其是近地面能量收支过程变化更明显。为深入理解半干旱草原地表辐射能量平衡过程对放牧的响应特征,利用内蒙古正镶白旗典型退化草原2020年生长季（6—10月）的辐射通量观测资料,对比分析了禁牧、放牧草地太阳总辐射、地表反射辐射、大气长波辐射、地表长波辐射、净辐射以及地表反照率的日变化和生长季变化规律的差异。结果表明：在生长季,太阳总辐射随着时间推进逐月递减;禁牧区的地表反射辐射总体小于放牧区;各月大气长波辐射日变化幅度很小,处于130—370 W·m^-2;禁牧、放牧条件下地表长波辐射存在明显的季节变化规律,但是二者之间的差异甚微。内蒙古典型退化草原生长季近地面辐射通量有显著单峰型日变化特征。禁牧、放牧草地地表反照率都呈现“U”型日变化规律。生长季放牧草地的反照率明显高于禁牧草地。在禁牧区,辐射分量（地表反射辐射、大气长波辐射）和植被指数（归一化差异植被指数）对净辐射的影响是正向极显著的;而地表反照率和另一辐射分量（地表长波辐射）对净辐射有显著的负向作用。在放牧区,地表反射辐射和大气长波辐射对净辐射有极显著的正向作用;而地表反照率和地表长波辐射对净辐射的作用则是负向显著的。植被状况是影响内蒙古典型退化草原近地表辐射能量收支过程的首要因子。     

Comparing recent geopotential models in Andalusia (Southern Spain)

This work focuses on the comparison between satellite-only and combined Global Geopotential Models (GGMs) derived from the CHAMP and GRACE satellite missions with land gravity anomalies, geoid undulations provided by the gravimetric geoid ANDALUSGeoid2002 and GPS/levelling geoid undulations in Andalusia in order to find the GGM that best fits this area in order to be used in a further geoid computation. The results show that the EIGEN-CG01C model or the combined models GGM02C/EIGEN-CG01C and ITG-CHAMP01E/EIGEN-CG01C should be used.     

Dynamic characteristics of a base isolated building from ambient vibration measurements and low level earthquake shaking

Ambient vibration tests were conducted on a base-isolated apartment building in Takamatsu, Japan, to determine the mode shapes and the associated natural frequencies and damping ratios at very low levels of excitation. The latest developments in signal analysis for modal decomposition are used to analyze the ambient response data. A finite element model of the building and isolators was calibrated and refined using the experimental results from the ambient vibration tests. This model was then used to simulate the recorded response of the building under excitation from a small earthquake. The finite element model, calibrated by ambient vibration data and the low level of earthquake shaking, provides the starting point for modelling the non-linear response of the building when subjected to strong shaking.     

Evaluation of 2-m temperature and precipitation products of the Climate Forecast System version 2 over Iran

Using a continuous multi-decadal simulations over the period 1981–2010, subseasonal to seasonal simulations of the Climate Forecast System version 2 (CFSv2) over Iran against the Climatic Research Unit (CRU) dataset are evaluated. CFSv2 shows cold biases over northern hillsides of the Alborz Mountains with the Mediterranean climate and warm biases over northern regions of the Persian Gulf and the Oman Sea with a dry climate. Magnitude of the model bias for 2-m temperature over different regions of Iran varies by season, with the least bias in temperate seasons of spring and autumn, and the largest bias in summer. The model bias decreases as temporal averaging period increases from seasonal to annual. The forecast generally produces dry and wet biases over dry and wet regions of Iran, respectively. In general, 2-m temperature over Iran is better captured than precipitation, but the prediction skill of precipitation is generally high over western Iran. Averaged over Iran, observations indicated that 2-m temperature has been gradually increasing during the studied period, with a rate of approximately 0.5 °C per decade, and the upward trend is well simulated by CFSv2. Averaged over Iran, both observations and simulation results indicated that precipitation has been decreasing in spring, with averaged decreasing trends of 0.8 mm (observed) and 1.7 mm (simulated) per season each year during the period 1981–2010. Observations indicated that the maximum increasing trend of 2-m temperature has occurred over western Iran (nearly 0.7 °C per decade), while the maximum decreasing trend of annual precipitation has occurred over western and parts of southern Iran (nearly 45 to 50 mm per decade).     

Sea-floor sediment distribution in the Gulf of Mexico

Carbonate content, smear-slide analysis and diffuse reflectance spectrophotometry were utilized to determine modern sediment composition and distribution throughout the Gulf of Mexico. In all, 186 core top and grab samples distributed throughout the Gulf were analyzed. Reflectance spectra were taken from thick smear slides from the near ultraviolet, through the visible, and into the near infrared. The first derivatives of the percent reflectance data were subjected to factor analysis producing factors that grouped covarying first-derivative wavelengths. Factors were interpreted by comparison to first-derivative curves for known sediment components and minerals. Interpretation was aided by the mapping of both calcium carbonate content and smear-slide sediment classes. The most easily interpreted factor solution was produced by analyzing only the visible region of the spectrum and extracting seven factors which explained 98% of the cumulative variance. These factors, in order of their relative importance, are interpreted as (1) marl and calcareous clay, (2) glauconite, (3) kaolinite, (4) organic matter, (5) phosphorite, (6) hematite, and (7) goethite. Some factor maps are consistent with known sources of fluvial sediment input; for example, kaolinite is deposited off rivers draining the southeastern US. Other factor maps are related to the origin of the material in the factor, glauconite, for example, being confined to low sedimentation regions of the outer shelf. The most unusual observation concerns the distribution of hematite, which appears to be transported from the rivers of south Texas, primarily the Rio Grande, across the shelf then eastward downslope along the base of the Sigsbee Escarpment. This eastward transport seems to be explainable only by transport in bottom currents flowing along the base of the Sigsbee Escarpment.     

建立面向区域农业可持续发展的空间决策支持系统的方法探讨

在解决诸如工业选址的空间问题时，空间决策支持系统避免了流行的商用ＧＩＳ软件在空间信息的分析评价，时空分布，预测和模拟以及决策等模型分析功能的不足，该文提出了建立ＳＤＳＳ的两种基本途径；一是利用现有ＧＩＳ与分析决策模型进行集成联结生成ＳＤＳＳ；另一种途径是自行开发具有空间数据管理和分析决策模型的一体化ＳＤＳＳ。     

风化及其它类荒漠漆表面层对高光谱分辨率遥感的影响（一）

由地表风化产生的表面覆被层的矿物质，其质地或与它的基岩矿物相似，或十分不同，虽然这类表面层的厚度仅有几微米到几毫米，但它们却完全控制了地面的反射光谱。与此相似，有些由风吹送的尘埃、胶结物或其它附着物在表面形成的外层也是影响遥感反射光谱的重要因素。这种由胶结物形成的表层往往是深色（甚至黑色）的，因为它们通常出现在干旱区，故常称为“荒漠漆”（“ｄｅｓｅｒｔｖａｒｎｉｓｈ”）。尽管这些暗色对我们的眼睛并无特别之处，但这类表面层（通常为粘土）在短波红外区（ＳＷＩＲ）具有低反射率的吸收特征，并能据此推断它们的矿物成分。因此，为了要在遥感图象和地面的实际“地质状况”之间建立联系，必须对裸露岩石表面特征具有良好的了解。由于不可能在野外总能找到“新鲜”的岩石表面，因此，人们必需能将“岩石内部”物质的光谱和它“上、下表面”的光谱区分开。本部分以美国加里福尼亚东部Ｗｈｉｔｅ－Ｉｎｙｏ山区高海拔地区早古生代白云质碳酸盐的风化表面为例，研究其岩石表面风化特征与海拔高度的关系。     

Modelling the spectral response of the desert tree Prosopis tamarugo to water stress

In this paper, we carried out a laboratory experiment to study changes in canopy reflectance of Tamarugo plants under controlled water stress. Tamarugo (Prosopis tamarugo Phil.) is an endemic and endangered tree species adapted to the hyper-arid conditions of the Atacama Desert, Northern Chile. Observed variation in reflectance during the day (due to leaf movements) as well as changes over the experimental period (due to water stress) were successfully modelled by using the Soil-Leaf-Canopy (SLC) radiative transfer model. Empirical canopy reflectance changes were mostly explained by the parameters leaf area index (LAI), leaf inclination distribution function (LIDF) and equivalent water thickness (EWT) as shown by the SLC simulations. Diurnal leaf movements observed in Tamarugo plants (as adaptation to decrease direct solar irradiation at the hottest time of the day) had an important effect on canopy reflectance and were explained by the LIDF parameter. The results suggest that remote sensing based assessment of this desert tree should consider LAI and canopy water content (CWC) as water stress indicators. Consequently, we tested fifteen different vegetation indices and spectral absorption features proposed in literature for detecting changes of LAI and CWC, considering the effect of LIDF variations. A sensitivity analysis was carried out using SLC simulations with a broad range of LAI, LIDF and EWT values. The Water Index was the most sensitive remote sensing feature for estimating CWC for values less than 0.036 g/cm², while the area under the curve for the spectral range 910–1070 nm was most sensitive for values higher than 0.036 g/cm². The red-edge chlorophyll index (CI_red-edge) performed the best for estimating LAI. Diurnal leaf movements had an effect on all remote sensing features tested, particularly on those for detecting changes in CWC.     

A laser scanning-based method for fast estimation of seismic-induced building deformations

Monitoring damaged buildings in an area where an earthquake has occurred requires the use of techniques which provide rapid and safe measurements even in emergency conditions. In particular, remote sensing techniques like terrestrial laser scanning (TLS) can satisfy these requirements, since they produce very dense point clouds in little time and also allow an accurate geometric modeling of observed buildings. Nevertheless, strong constraints on TLS data acquisition geometry, such as acquisition distance and incidence angles, typically characterize an area in seismic emergency conditions. In order to correctly interpret the data, it is necessary to estimate errors affecting TLS measurements in these critical conditions. A reliable estimation can be achieved by means of experiments and numerical simulations aimed at quantifying a realistic noise level, with emphasis on reduction of artifacts due to data acquisition, registration and modeling. This paper proposes a data analysis strategy in which TLS-based morphological maps computed as point-to-primitive differences are created. The method can be easily used for accurate surveying in emergency conditions. In order to demonstrate the proposed method in very diverse situations, it was applied to rapidly detect deformation traces in the San Giacomo Roncole Campanile (Modena), the Asinelli tower (Bologna) and the Cantalovo Church (Verona), three buildings damaged by the Mw 5.9 Emilia Romagna 2012 earthquake (Italy).     

Mapping deer habitat suitability using remote sensing and geographic information systems

This paper describes an effort to map the habitat for the Eastern Tehama Deer Herd located in Northern California. The range of this herd encompasses almost 600,000 hectares (1.5 million acres). Knowledge of the spatial distribution of suitable habitat is prerequisite to managing the deer herd. Remote sensing and GIS are appropriate tools for such an assessment. Remotely sensed data were used to map vegetation/land cover. These data along with elevation, aspect, slope, juxtaposition, and various buffer zones were input into a GIS and a model was used to produce a map of habitat suitability. The accuracy of the vegetation/land cover map was assessed and methods for validating the habitat suitability map are presented.