Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model

Accurately estimating the spatial distribution of forest aboveground biomass (AGB) is important because of its carbon budget forms part of the global carbon cycle. This paper presented three methods for obtaining forest AGB based on a forest growth model, a Multiple-Forward-Mode (MFM) method and a stochastic gradient boosting (SGB) model. A Li-Strahler geometric-optical canopy reflectance model (GOMS) with the ZELIG forest growth model was run using HJ1B imagery to derive forest AGB. GOMS-ZELIG simulated data were used to train the SGB model and AGB estimation. The GOMS-ZELIG AGB estimation was evaluated for 24 field-measured data and compared against the GOMS-SGB model and GOMS-MFM biomass predictions from multispectral HJ1B data. The results show that the estimation accuracy of the GOMS-MFM model is slightly higher than that of the GOMS-SGB model. The GOMS-ZELIG and GOMS-MFM models are considerably more accurate at estimating forest AGB in arid and semiarid regions.     

Surface albedo from the geostationary Communication,Ocean and Meteorological Satellite (COMS)/Meteorological Imager (MI) observation system

The surface albedo is an essential climate variable that is considered in many applications used for predicting climate and understanding the mechanisms of climate change. In this study, surface albedo was estimated using a bidirectional reflectance distribution function model based on Communication, Ocean and Meteorological Satellite/Meteorological Imager data. Geostationary orbiting satellite data are suitable for a level 2 product like albedo, which requires a synthetic process to estimate. The authors modified established methods to consider the geometry of the solar-surface-sensor of COMS/MI. Of note, the viewing zenith angle term was removed from the kernel integration used for estimating spectral albedo. Finally, the spectral (narrow) albedo was converted into the broadband albedo with shortwave length (approximately 0.3–2.5 μm). This study determined conversion coefficients using only one spectral albedo of visible channel. The estimated albedo had a relatively high correlation with Satellite Pour l’Observation de la Terre/Vegetation and low unweighted error values specific for land types or times. The validation results show that estimated albedo has a root mean square error of 0.0134 at Jeju flux site that indicates accuracy similar to that of other satellite-based products.     

一种多角度观测系统几何精度的评估方法

多角度观测系统用于地面遥感实验中测量地物的双向反射特性。配合高光谱分辨率遥感卫星影像,可以反演得到地物的三维结构信息。多角度观测系统的几何精度直接影响到观测地物的范围及采集数据的准确性。对其进行评估,不仅为实验人员选择实验设备提供精度参数,而且有助于实验人员确定观测范围。以激光脚点最小包络圆半径作为评估参数,提供了一种评估多角度观测系统几何精度的方法;对自主研发的多角度观测系统的几何精度进行了计算与评估。对不同光谱仪视场下的理论观测范围与考虑系统几何精度后的实际观测范围进行了计算,并给出了参考。     

一种拓展的半物理时空融合算法及其初步应用

Landsat 5卫星较低的时间分辨率(16天)使得其很难获得大区域的、时相一致的清晰影像数据集。本文发展了一种基于半物理模型的时空融合算法-即乘性调制融合算法,并借助多时序的MODIS反射率数据来生成多时相的Landsat TM/ETM+反射率合成影像,经镶嵌后得到区域尺度的高时空分辨率地表反射率数据集(Landsat TM/ETM+)。本文利用吉林省2006年—2011年的Landsat 5 TM地表反射率数据以及500 m的MOD09A1反射率产品来生成3个时相的Landsat 5 TM反射率合成数据,从而获得研究区在上述时相下地表反射率数据的镶嵌图。初步分析表明,所生成的Landsat 5 TM反射率数据的光谱分布特征与MOD09A1反射率数据较为一致,且图像在整体上光谱特征的连续性较好。     

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.     

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.     

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.     

Mapping saltcedar (Tamarix ramosissima) and other riparian and agricultural vegetation in the Lower Colorado River region using multi-spectral Landsat TM imagery

Saltcedar (Tamarix ramosissima), an invasive shrub species, has successfully invaded large extents of several riparian zones in the western United States and northern Mexico. Mapping the distribution and abundance of saltcedar over these large areas through a multi-seasonal, cost-effective monitoring approach using satellite remote sensing is very essential. Ground truth surveys were conducted at 79 locations where the spectral reflectance measurements of vegetation, type of plant species, plant heights, soil samples and GPS co-ordinates were recorded. All the sampling was designed to coincide with the satellite overpass period. The Landsat TM colour-composite spectral ratio image (normalized difference vegetative index (NDVI), R _1,5 and R _1,7 as green, blue and red) can clearly identify and map the areas infested with saltcedar. The Landsat image analysis shows that these spectral ratios can be applied to multiple satellite overpasses for monitoring the seasonal progression of the saltcedar growth over time.     

Using hyperspectral reflectance data to assess biocontrol damage of giant salvinia

Field hyperspectral reflectance data were studied at 50 wavebands (10-nm bandwidth) over the 400- to 900-nm spectral range to determine their potential for distinguishing among giant salvinia (Salvinia molesta Mitchell) plants subjected to four population levels of salvinia weevils (Cyrtobagous salviniae Calder and Sands) to develop feeding damage to the plants. The four populations included a control with no insects and those with low, medium and high insect populations. The plants were studied in two experiments on each of two dates: 14 October 2010 and 21 July 2011. Two procedures were used to determine the optimum bands for discriminating among treatments: least significant difference (LSD) and stepwise discriminant analysis. The LSD comparison test results for both October and July experiments showed that generally the best bands for separating among treatments occurred in the green (505–595 nm), red (605–635 nm), red-near-infrared (NIR; 695–745 nm) edge and NIR (755–895 nm) regions where three to four treatments could be distinguished. Stepwise discriminant analysis identified four bands in the green, red and red-NIR edge to be significant to discriminate among the four treatments in Experiment 1 in October. For Experiment 2 in October, discriminant analysis identified five bands in the blue, green, red and NIR regions to be significant for distinguishing among the treatments. In Experiment 1 in July, five bands in the blue, green, red-NIR edge and NIR regions were found to be significant to discriminate among the treatments. For Experiment 2 in July, discriminant analysis identified four bands in the blue, green and red-NIR edge regions to be significant to discriminate among the treatments.