Influence of soil surface roughness on soil bidirectional reflectance

The non-Lambertian behaviour of soil surfaces depends on its roughness at micro-scale and larger scales, as well as on the incident angle of the direct solar beam on the surface. A geometrical model, taking into account the diffuse as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is used in the paper to describe the influence of soil surface roughness, caused by soil aggregates or soil clods, on the soil bidirectional reflectance distribution. A rough soil surface in the model is simulated by equalsized opaque spheroids lying on a horizontal surface. The model was tested in outdoor conditions on artificially formed soil surfaces made of two spectrally different soil materials: a mineral loam, and a loam with high organic matter content. The spectral data were measured by a field radiometer in the three SPOT (HRV) bands. The model predicts that at specific illumination conditions, soils surfaces with the highest roughness, expressed by the minimum distances between soil aggregates, can show lower variation of reflectance in the view zenith angle function than soil surfaces of a lower roughness.     

Estimating aerodynamic resistance of rough surfaces using angular reflectance

Current wind erosion and dust emission models neglect the heterogeneous nature of surface roughness and its geometric anisotropic effect on aerodynamic resistance, and over-estimate the erodible area by assuming it is not covered by roughness elements. We address these shortfalls with a new model which estimates aerodynamic roughness length (z₀) using angular reflectance of a rough surface. The new model is proportional to the frontal area index, directional, and represents the geometric anisotropy of z₀. The model explained most of the variation in two sets of wind tunnel measurements of aerodynamic roughness lengths (z₀). Field estimates of z₀ for varying wind directions were similar to predictions made by the new model. The model was used to estimate the erodible area exposed to abrasion by saltating particles. Vertically integrated horizontal flux (F_h) was calculated using the area not covered by non-erodible hemispheres; the approach embodied in dust emission models. Under the same model conditions, F_h estimated using the new model was up to 85% smaller than that using the conventional area not covered. These F_h simulations imply that wind erosion and dust emission models without geometric anisotropic sheltering of the surface, may considerably over-estimate F_h and hence the amount of dust emission. The new model provides a straightforward method to estimate aerodynamic resistance with the potential to improve the accuracy of wind erosion and dust emission models, a measure that can be retrieved using bi-directional reflectance models from angular satellite sensors, and an alternative to notoriously unreliable field estimates of z₀ and their extrapolations across landform scales.     

A hemispherical–directional reflectance model as a tool for understanding image distinctions between cultivated and uncultivated bare surfaces

This paper discusses a model to predict the normalized hemispherical–directional reflectance function for soil or rocky surfaces of a given roughness under conditions of outdoor illumination. These surfaces are simulated by geometrical shapes similar to beads merging into each other, characterized by three parameters. In addition, the shape of the surface is characterized by the directivity factor D_R, expressing the differences between the maximum and the minimum deviations of its height, calculated along all possible directions. The surface is illuminated by a hemispherical light source created by a number of point sources of given light intensities. The light energy is scattered from the surface, in accordance the quasi-Lambertian function. The distribution of the surface reflectance, as viewed from all the possible directions, can be described for all the possible illumination conditions expressed by the solar zenith and the horizontal angles for a given hemisphere light distribution of a definite optical thickness. This represents the hemispherical–directional reflectance distribution function, HDRDF, of the surface. The HDRDF function is normalized to the nadir viewpoint and visualized for a given illumination condition. The model assumes that the HDRDF of a surface contains information about the directivity of the surface shape, as described by the directivity factor of the surface hemispherical–directional reflectance function D_HDRDF. This factor, expressing the asymmetry of the HDRDF with respect to the solar principal plane (SPP), is strongly correlated with the D_R. The use of both factors, the D_R and D_HDRDF, enables us to understand the distinctions between soil surface images with height irregularities of directional character that create a furrow microrelief, and irregularities spread non-directly, randomly, depending on whether the soil has been cultivated or not. The model was tested on directional reflectance data measured in the visible, the near and the middle infrared spectra for cultivated surface with furrows, as well as for three uncultivated desert loess and rocky surfaces situated in Israel.     

基于TVDI河北省干热风同期土壤湿度监测研究

干热风是高温低湿型的灾害性天气。河北省是干热风易发地区,进行干热风易发期土壤湿度监测研究,对于评估干热风的影响与危害具有重要意义。选用2010年河北省干热风同期5~6月Terra/MODIS8期地表反射率产品MOD09A1和地表温度(LST)产品MOD11A2,通过构建LST\|EVI特征空间,得到温度植被干旱指数(TVDI)反映的河北省各时段的土壤湿度空间分布图。另外分析TVDI值与对应气象站点降水数据变化的趋势关系和二者的定量相关关系,发现降水数据变化与TVDI有较显著的负相关性,通过α=0.05显著性检验。基于研究结果可快速有效地反映研究区土壤湿度等级与空间分布变化状况,与及时更新的气象数据(风速、气温、降水等)相结合,在根据已有指标监测到干热风发生的基础上,评估干热风的影响与危害。     

A model to predict land susceptibility to wind erosion in western Queensland,Australia

This paper describes the development and validation of the Australian Land Erodibility Model (AUSLEM), designed to predict land susceptibility to wind erosion in western Queensland, Australia. The model operates at a 5 × 5 km spatial resolution on a daily time-step with inputs of grass and tree cover, soil moisture, soil texture and surficial stone cover. The system was implemented to predict land erodibility, i.e. susceptibility to wind erosion, for the period 1980–1990. Model performance was evaluated using cross-correlation analyses to compare trajectories of mean annual land erodibility at selected locations with trends in wind speed and observational records of dust events and a Dust Storm Index (DSI). The validation was conducted at four spatial length scales from 25 to 150 km using windows to represent potential dust source areas centered on and positioned around eight meteorological stations within the study area. The predicted land erodibility had strong correlations with dust-event frequencies at half of the stations. Poor correlations at the other stations were linked to the inability of the model to account for temporal changes in soil erodibility, and comparing trends in the land erodibility of regions with dust events whose source areas lie outside the regions of interest. The model agreement with dust-event frequency trends was found to vary across spatial scales and was highly dependent on land type characteristics around the stations and on the types of dust events used for validation.     

Geometrical modelling of soil bidirectional reflectance incorporating specular effects

A geometrical model, taking into account the diffuse, as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is discussed here. The model computes the bidirectional, reflectance of soils illuminated by a single source. A rough soil surface is simulated by equal-sized spheroids regularly spaced on a horizontal surface. The model was tested using soil bidirectional reflectance data obtained in laboratory conditions by Jacquemoud et al in 1992. Two parameters describing soil surface geometry were used for modelling the soil relalive reflectance in laboratory conditions: the relative distance (d/ a) between spheroids (relative to their horizontal radii ( a )and the shape of spheroids (b/ a) ( as proportion of their vertical (b) to horizontal radii (a)) The simulation of reflectance for soil surfaces of pebbles and sand, containing simple dense particles with rounded edges, can be carried out using the d/ a and b/ a ratios which nearly described their aclual geometry. The reflectance of more geometrically complicated soil surfaces, such as clay and peat with irregular secondary porous aggregates, can be simulated by surfaces of effective geometry of vertically elongated spheroids.     

土壤全氮含量与碳氮比的高光谱反射估测影响因素研究

基于土壤高光谱反射特征可以实现土壤全氮(TN)含量与碳氮比(C∶N)等土壤属性的快速、无损测定,但其估测模型受土壤颗粒粒径水平与光谱指数(预处理)等因素影响。通过研磨准备2、0.25和0.15 mm共3个水平颗粒粒径的土样,分析了原始(RAW)及多次散射校正MSC(Multiple Scattering Correction)、一阶微分FD(First Derivative)、连续统去除CR(Continuum Removal)等预处理的土壤反射光谱与TN含量、碳氮比变化之间的关系,发现土壤研磨可以提高反射光谱对TN含量变化的响应,而FD、CR与MSC等光谱预处理能够明显缩小不同颗粒粒径水平土样的光谱反射-TN含量、碳氮比相关性差异。结果表明:0.25 mm颗粒粒径土样的FD预处理光谱在2 250 nm和2 280 nm处分别与TN含量、碳氮比变化存在最大相关,但最大相关单波段线性回归模型的TN含量、碳氮比估测精度不如全波段光谱PLSR模型。其中,0.25 mm土样RAW光谱全波段PLSR模型估测TN含量的表现最佳(RPD=3.49,R²=0.92,RMSEP=0.1 g/kg);而碳氮比的估测结果并不十分理想,其最优估测模型(0.25 mm土样FD预处理的全波段PLSR模型)的RPD仅为1.21,可能与土样的碳氮比变化范围较小有关,在以后的研究中可以尝试采集更多的样本数量或土壤类型,使训练样本具有较大的变量范围,以取得较好的估测效果。     

Visualizing soil surfaces and crop residues

A test case for visualizing field and laboratory data pertaining to soil erosion and infiltration is examined. Several visualization techniques were used to derive image data from an experiment in which the effect of a sequence of five rainfalls on a laboratory-formed soil surface was measured. The base data are millimeter-resolution elevation models generated using a laser-scanning device. The surfaces generated by the laser scanner are visualized as perspective views. Changes in the soil surface with cumulative rainfall are examined by visualizing differences between successive laser-scanned surfaces. The modeling of straw coverage, which can influence infiltration, overland flow, and erosion, using a random process model is discussed     

黄河流域甘肃片土壤侵蚀遥感普查的初步分析

以TM影像为主要信息源,借助GIS(地理信息系统)软件ARC/INFO作技术支撑,对黄河流域甘肃片土壤侵蚀现状进行普查。通过提取影响土壤侵蚀主导因子并综合分析确定甘肃片土壤侵蚀类型、分布及强度。     

Evaluation of two empirical wind erosion models in arid and semi-arid regions of China and the USA

Wind erosion models are important tools for assessing soil erodibility and identifying management practices to control erosion. The Agricultural Policy/Environmental eXtender (APEX) model and Revised Wind Erosion Equation (RWEQ) were tested using data collected from the Tarim Basin of China and Columbia Plateau of the United States of America. Adequate performance in simulating soil loss was achieved using the original APEX model and RWEQ in respectively a cotton field and desert-oasis ecotone in the Tarim Basin and winter wheat - summer fallow (WW-SF) field in the Columbia Plateau. We calibrated the APEX model and RWEQ to improve performance because both models have many empirical parameters. After calibration, both models adequately simulated soil loss from all land use types except the RWEQ from the red date orchard in the Tarim Basin. Inadequate performance of the calibrated RWEQ in the red date orchard was likely due to underestimating maximum mass transport.     

城市混合像元分解中土壤与不透水面纯像元选取方法的对比研究——以厦门为例

近年来混合像元分解在城市地表组分监测与分析中的应用逐渐成为城市遥感的一个热点。纯像元的选取是混合像元分解过程中的重点和关键所在。以沿海城市厦门为研究对象,根据不同的土壤和不透水面纯像元选取规则,使用2组12种不同的纯像元选取方法对2007年1月8日TM影像进行混合像元分解,对分解结果的模型适宜度进行了比较,并使用2006年12月25日SPOT5高分辨率影像对分解结果的精度进行了比较和评估。结果表明:混合像元分解在纯像元选取时,S端元选取兼顾低反射率裸土和高反射率裸露基岩的纯像元可以整体提高分解的模型适宜度和分解精度;适度提高I分量纯像元中高反射率纯像元的比例有助于改善整体尤其是S、W分量的分解效果。     

民勤县红崖山风蚀监测站监测成果分析

民勤县红崖山风蚀监测站是甘肃省两个风蚀监测点之一,为准确掌握区域水土流失强度、发生发展规律、动态变化趋势等情况,本文以现有监测技术为基础,利用全自动气象观测仪、测钎、布袋式集沙仪、降尘缸等设备,通过地面观测法、测钎法、降尘缸法等,对监测站的降水量、蒸发量、风速、风向、土壤含水率、风蚀厚度、降尘量、输沙率等要素数据进行定期监测,并分析得出：每年第二季度风蚀厚度最大,这与大风天气发生频次、风速大小有直接关系。而且采取麦草方格网沙障措施可有效降低风蚀厚度,水土流失治理效果明显。通过对该监测站风蚀情况监测,为今后民勤县开展水土流失防治工作提供重要的基础支撑。     

Effect of surface roughness,wavelength, illumination,and viewing zenith angles on soil surface BRDF using an imaging BRDF approach

Compared to non-imaging instruments, imaging spectrometers (ISs) can provide detailed information to investigate the influence of scene components on the bidirectional reflectance distribution function (BRDF) of a mixed target. The research reported in this article investigated soil surface reflectance changes as a function of scene components (i.e. illuminated pixels and shaded pixels), illumination and viewing zenith angles, and wavelength. Image-based BRDF data of both rough and smooth soil surfaces were acquired in a laboratory setting at three different illumination zenith angles and at four different viewing zenith angles over the full 360° azimuth range, at an interval of 20°, using a Specim V10E IS (Specim, Spectral Imaging Ltd., Oulu, Finland) mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5). The BRDF of the smooth soil surface was dominated by illuminated pixels, whereas the shaded pixels were a larger component of the BRDF of the rough soil surface. As the illumination zenith angle was changed from 60° to 45° and then to 30°, the shadowing effect decreased, regardless of the soil surface. Soil surface reflectance was generally higher at the backscattering view zenith angles and decreased continuously to forward scattering view zenith angles in the light principal plane, regardless of the wavelength, due to the Specim V10E IS seeing more illuminated pixels in the backscattering angles than in the forward scattering angles. Higher soil surface reflectance was observed at higher illumination and viewing zenith angle combinations. For both soil surface roughness categories, the BRDF exhibited a greater range of values in the near-infrared than at the visible wavelengths. This research enhances our understanding of soil BRDF for various soil roughness and illumination conditions.     

土壤可蚀性(K)值图编制方法的初步研究

介绍了利用土壤普查图件和剖面理化分析的成果资料，编制土壤可蚀性(K)值图的方法，沙及求取剖面点K值的查图表法、图斑分并与图斑K值的确定原则和编制程序等。应用上述方法，完成了我国第一张地区级K值图，效果良好。经分析，与公式算法比，查图表法的K值精度为85.45%;与径流小区实测值比，用K值图上相应K值监测的土攘年流失量的精度为86.0%.。该法既有更新水土流失调查方法的科学意义和指导流失治理的实
用价值，也值得进一步深入研究。     

NOAA AVHRR land surface albedo algorithm development

The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 mu m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 mu m) and near-IR (0.7-1.3 mu m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.     

The modified Beckmann-Kirchhoff scattering theory for rough surface analysis

This paper focusses on how reflectance models based on scattering theory and reported in the physics literature can be used for making estimates of surface roughness parameters using reflectance measurements obtained with a digital camera. We commence by reviewing the Beckmann-Kirchhoff (B-K) scatter theory, and the recent modification to it by Vernold and Harvey. We show how this model can be used to estimate surface roughness parameters for dielectric surfaces using pixel brightness measurements. Using the roughness parameter measurements we compare the model with reflectance measurements from the CUReT database. This comparison shows that the Vernold-Harvey modification of the B-K model gives a better fit to data than the Oren-Nayar model for certain types of rough surface.     

Wavelet-based detection of clods on a soil surface

One of the aims of the tillage operation is to produce a specific range of clod sizes, suitable for plant emergence. Due to its cloddy structure, a tilled soil surface has its own roughness, which is connected also with soil water content and erosion phenomena. The comprehension and modeling of surface runoff and erosion require that the micro-topography of the soil surface is well estimated. Therefore, the present paper focuses on the soil surface analysis and characterization. An original method consisting in detecting the individual clods or large aggregates on a 3D digital elevation model (DEM) of the soil surface is introduced. A multiresolution decomposition of the surface is performed by wavelet transform. Then a supervised local maxima extraction is performed on the different sub surfaces and a last process makes the validation of the extractions and the merging of the different scales. The method of detection was evaluated with the help of a soil scientist on a controlled surface made in the laboratory as well as on real seedbed and ploughed surfaces, made by tillage operations in an agricultural field. The identifications of the clods are in good agreement, with an overall sensitivity of 84% and a specificity of 94%. The false positive or false negative detections may have several causes. Some very nearby clods may have been smoothed together in the approximation process. Other clods may be embedded into another peace of the surface relief such as another bigger clod or a part of the furrow. At last, the low levels of decomposition are dependent on the resolution and the measurement noise of the DEM. Therefore, some borders of clods may be difficult to determine. The wavelet-based detection method seems to be suitable for soil surfaces described by 2 or 3 levels of approximation such as seedbeds.     

褐潮土的光谱特性及用土壤反射率估算有机质含量的研究

本文通过ASDFR便携式光谱仪对132个风干土壤样品的光谱反射率进行了实验室测定。根据土样光谱反射率变化,获得了褐潮土土壤剖面的不同诊断层反射光谱特征。结果表明,在400～1200nm范围之间,土壤有机质含量与土壤光谱反射率有较好的相关性。利用导数光谱方法建立了预测土壤有机质含量的方程,提出了预测北京地区褐潮土有机质光谱的最佳波段。在波长447nm处采用反射率和A值(反射率倒数的对数)所建立的预测方程的预测精度较高。采用反射率的一阶微分建立的预测方程的最佳波段在516nm处。而A值一阶微分光谱在615nm处相关性最好。作为一项参考指标用光谱分析法评价土壤中有机质含量,以期对精准农业中土壤养分或肥力的预测具有一定的指导作用。     

A multilayer perceptron model for the correlation between satellite data and soil vulnerability in the Ferlo,Senegal

ABSTRACT

Soil erosion processes which contribute to desertification and land degradation, constitute major environmental and social issues for the coming decades. This is particularly true in arid areas where rural populations mostly depend on soil ability to support crop production. Assessment of soil erosion across large and quite diverse areas is very difficult but crucial for planning and management of the natural resources. The purpose of this paper is to investigate a prediction model for soil vulnerability to erosion based on the use of the information contained in satellite images. Based on neural networks models, the used approach in this paper aims at checking a correlation between the digital content of satellite images and soil vulnerability factors: erosivity (R), the soil erodibility (K), and the slope length and steepness (LS); vulnerability (V) as described in the RUSLE model. Significant results have been obtained for R and K factors. This promising pilot study was conducted in South Ferlo, Senegal, a region with Sahelian environmental characteristics.     

Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia

Soil loss causes environmental degradation and reduces agricultural productivity over large areas of the world. Here, we use the latest earth observation data and soil visible–near infrared (vis–NIR) spectroscopy to estimate the factors of the Revised Universal Soil Loss Equation (RUSLE) and to model soil loss by water erosion in Australia. We estimate rainfall erosivity (R) using the Tropical Rainfall Measuring Mission (TRMM); slope length and steepness (L and S) using a 3-arcsec Shuttle Radar Topography Mission (SRTM) digital elevation model; cover management (C) and control practice (P) using the national dynamic land cover dataset (DLCD) of Australia derived from the moderate-resolution imaging spectroradiometer (MODIS); and soil erodibility (K) using vis–NIR estimates of the contents of sand, silt, clay and organic carbon in Australian soil. We model K using a machine-learning algorithm with environmental predictors selected to best capture the factors that influence erodibility and produced a digital map of K. We use the derived RUSLE factors to estimate soil loss at 1-km resolution across the whole of Australia. We found that the potential gross average soil loss by water erosion in Australian is 1.86 t ha⁻¹ y⁻¹ (95% confidence intervals of 1.78 and 1.93 t ha⁻¹ y⁻¹), equivalent to a total of 1242 × 10⁶ tonnes of soil lost annually (95% confidence intervals of 1195 and 1293 t × 10⁶ y⁻¹). Our estimates of erosion are generally smaller than previous continental estimates using the RUSLE, but particularly in croplands, which might indicate that soil conservation practices effectively reduced erosion in Australia. However we also identify localized regions with large erosion in northern Australia and northeastern Queensland. Erosion in these areas carries sediments laden with nitrogen, phosphorus and pollutants from agricultural production into the sea, negatively affecting marine ecosystems. We used the best available data and our results provide better estimates compared to previous assessments. Our approach will be valuable for other large, sparsely sampled areas of the world where assessments of soil erosion are needed.