An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data

Accurate high-resolution soil moisture data are needed for a range of agricultural and hydrologic activities. To improve the spatial resolution of ∼ 40 km resolution passive microwave-derived soil moisture, a methodology based on 1 km resolution MODIS (MODerate resolution Imaging Spectroradiometer) red, near-infrared and thermal-infrared data has been implemented at 4 km resolution. The three components of that method are (i) fractional vegetation cover, (ii) soil evaporative efficiency (defined as the ratio of actual to potential evaporation) and (iii) a downscaling relationship. In this paper, 36 different disaggregation algorithms are built from 3 fractional vegetation cover formulations, 3 soil evaporative efficiency models, and 4 downscaling relationships. All algorithms differ with regard to the representation of the nonlinear relationship between microwave-derived soil moisture and optical-derived soil evaporative efficiency. Airborne L-band data collected over an Australian agricultural area are used to both generate ∼ 40 km resolution microwave pixels and verify disaggregation results at 4 km resolution. Among the 36 disaggregation algorithms, one is identified as being more robust (insensitive to soil, vegetation and atmospheric variables) than the others with a mean slope between MODIS-disaggregated and L-band derived soil moisture of 0.94. The robustness of that algorithm is notably assessed by comparing the disaggregation results obtained using composited (averaged) Terra and Aqua MODIS data, and using data from Terra and Aqua separately. The error on disaggregated soil moisture is systematically reduced by compositing daily Terra and Aqua data with an error of 0.012 vol./vol.     

Effects of soil composition and mineralogy on remote sensing of crop residue cover

The management of crop residues (non-photosynthetic vegetation) in agricultural fields influences soil erosion and soil carbon sequestration. Remote sensing methods can efficiently assess crop residue cover and related tillage intensity over many fields in a region. Although the reflectance spectra of soils and crop residues are often similar in the visible, near infrared, and the lower part of the shortwave infrared (400-1900 nm) wavelength region, specific diagnostic chemical absorption features are evident in the upper shortwave infrared (1900-2500 nm) region. Two reflectance band height indices used for estimating residue cover are the Cellulose Absorption Index (CAI) and the Lignin-Cellulose Absorption (LCA) index, both of which use reflectances in the upper shortwave infrared (SWIR). Soil mineralogy and composition will affect soil spectral properties and may limit the usefulness of these spectral indices in certain areas. Our objectives were to (1) identify minerals and soil components with absorption features in the 2000 nm to 2400 nm wavelength region that would affect CAI and LCA and (2) assess their potential impact on remote sensing estimates of crop residue cover. Most common soil minerals had CAI values ≤ 0.5, whereas crop residues were always > 0.5, allowing for good contrast between soils and residues. However, a number of common soil minerals had LCA values > 0.5, and, in some cases, the mineral LCA values were greater than those of the crop residues, which could limit the effectiveness of LCA for residue cover estimation. The LCA of some dry residues and live corn canopies were similar in value, unlike CAI. Thus, the Normalized Difference Vegetation Index (NDVI) or similar method should be used to separate out green vegetation pixels. Mineral groups, such as garnets and chlorites, often have wide ranges of CAI and LCA values, and thus, mineralogical analyses often do not identify individual mineral species required for precise CAI estimation. However, these methods are still useful for identifying mineral soils requiring additional scrutiny. Future advanced multi- and hyperspectral remote sensing platforms should include CAI bands to allow for crop residue cover estimation.     

A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors

A sequential model is developed to disaggregate microwave-derived soil moisture from 40 km to 4 km resolution using MODIS (Moderate Imaging Spectroradiometer) data and subsequently from 4 km to 500 m resolution using ASTER (Advanced Scanning Thermal Emission and Reflection Radiometer) data. The 1 km resolution airborne data collected during the three-week National Airborne Field Experiment 2006 (NAFE'06) are used to simulate the 40 km pixels, and a thermal-based disaggregation algorithm is applied using 1 km resolution MODIS and 100 m resolution ASTER data. The downscaled soil moisture data are subsequently evaluated using a combination of airborne and in situ soil moisture measurements. A key step in the procedure is to identify an optimal downscaling resolution in terms of disaggregation accuracy and sub-pixel soil moisture variability. Very consistent optimal downscaling resolutions are obtained for MODIS aboard Terra, MODIS aboard Aqua and ASTER, which are 4 to 5 times the thermal sensor resolution. The root mean square error between the 500 m resolution sequentially disaggregated and ground-measured soil moisture is 0.062 vol./vol. with a bias of − 0.045 vol./vol. and values ranging from 0.08 to 0.40 vol./vol.     

Effects of soil moisture and water depth on ERS SAR backscatter measurements from an Alaskan wetland complex

We conducted a preliminary investigation of the response of ERS C-band SAR backscatter to variations in soil moisture and surface inundation in wetlands of interior Alaska. Data were collected from 5 wetlands over a three-week period in 2007. Results showed a positive correlation between backscatter and soil moisture in sites dominated by herbaceous vegetation cover (r = 0.74, p < 0.04). ERS SAR backscatter was negatively correlated to water depth in all open (non-forested) wetlands when water table levels were more than 6 cm above the wetland surface (r = − 0.82, p < 0.001). There was no relationship between backscatter and soil moisture in the forested (black spruce-dominated) wetland site. Our preliminary results show that ERS SAR data can be used to monitor variations in hydrologic conditions in high northern latitude wetlands (including peatlands), particularly sites with sparse tree cover.     

A model for simulating the performance and irrigation of green stormwater facilities at residential scales in semiarid and Mediterranean regions

Impervious areas change hydrological processes, reducing infiltration and evapotranspiration, and increasing direct runoff. Stormwater practices using green infrastructure are implemented locally to control runoff and preserve the hydrological cycle. Applying these techniques in semiarid and Mediterranean regions requires accounting for aspects related to the maintenance of green areas. This study develops the Integrated Hydrological Model at Residential Scale, a continuous model for representing the performance and irrigation of green stormwater facilities at residential scales. Among other relevant process, the model simulates evaporation from bare soil and redistribution between soil layers. Different components of the model were tested using laboratory and numerical experiments, and then an application to a case study and a sensitivity analysis were carried out. The model identifies significant differences in the performance of a rain garden with different vegetation, climate and irrigation practices and provides good insight for the maintenance needs of green infrastructure for runoff control.     

AMSR-E卫星反演土壤湿度与ECWMF,NECP再分析土壤湿度比较分析

土壤湿度是气象学、气候学研究领域的重要环境因子和过程参数。AMSR-E可提供全球范围的较长时序的卫星反演土壤湿度产品,将ECWMF和NECP再分析资料与AMSR-E土壤湿度产品进行时空比较,在评价三者一致性的同时对AMSR-E土壤湿度进行检验,并进一步使用站点观测资料(土壤湿度、降水量)对中国区域的AMSR-E、ECWMF以及NECP土壤湿度进行检验。结果表明：全球及中国区域AMSR-E、ECWMF与NECP土壤湿度空间分布特征一致性较好,但与ECWMF、NCEP相比AMSR-E土壤湿度在数值上明显偏小,尤其当AMSR-E土壤湿度数值较小时,与另两者的差距较大;三者土壤湿度均与降水量有较好的对应关系,比较而言,ECWMF和NECP土壤湿度与降水量的对应关系更好;与站点土壤湿度相比,ECWMF和NECP土壤湿度偏大,AMSR-E土壤湿度偏小,全国范围内2009年159个站点统计结果显示:ECWMF、NECP与站点的均方根误差(0.107、0.124)小于AMSR-E的均方根误差(0.127)。     

Comparing three methods for modeling the uncertainty in knowledge discovery from area-class soil maps

Knowledge discovery has been demonstrated as an effective approach to extracting knowledge from existing data sources for soil classification and mapping. Soils are spatial entities with fuzzy boundaries. Our study focuses on the uncertainty associated with class assignments when classifying such entities. We first present a framework of knowledge representation for categorizing spatial entities with fuzzy boundaries. Three knowledge discovery methods are discussed next for extracting knowledge from data sources. The methods were designed to maintain information for modeling the uncertainties associated with class assignments when using the extracted knowledge for classification. In a case study of knowledge discovery from an area-class soil map, all three methods were able to extract knowledge embedded in the map to classify soils at accuracies comparable to that of the original map. The methods were also able to capture membership gradations and helped to identify transitional zones and areas of potential problems on the source map when measures of uncertainties were mapped. Among the three methods compared, a fuzzy decision tree approach demonstrated the best performance in modeling the transitions between soil prototypes.     

长期施用含氮化肥对大豆生育及养分吸收的影响

从1984年起,在沈阳农业大学棕壤上没有氮化肥长期定位试验。结果表明,长期施用含氯化肥在大豆整个生育期内可促进株高、茎粗、根系等地上部及地下部的生长,氯对大豆氮、磷养分的吸收无明显影响,对钾的吸收有 促进作用。     

江西省土壤可溶态稀土元素含量和分布规律的研究

对江西 1 1种母质发育的有代表性的水稻土、旱作地、自然土壤 ,61个剖面 ,4 1 2个土样的可溶态稀土元素分析测定 ,统计结果表明 :江西土壤稀土元素的强度因素处于较高水平 ,平均值为 1 9 0mg/kg ,有 4 2 80 %的样点处于丰富级 ;有由南向北 ,由东向西逐渐降低的趋势 .其含量最高的地区是赣南由花岗岩、泥质岩、第四纪红粘土、酸性紫色土、碳质岩类风化物等母质发育的土壤 ,较低的为赣西北由石英岩 ,第三纪红砂岩、石灰岩、下蜀系黄土等母质发育的土壤 ;在土壤剖面分布中 ,旱作地表层低于底层 ,水稻土表层有生物富集作用高于底层 ;影响土壤中可溶态稀土元素含量的主要因子有 :成土母质 ,气候条件 (温度 ,降水量 ) ,土壤 pH ,土壤质地和耕作类型     

黑龙江省西部草地土壤无机磷的形态

本文通过牧场试验,探讨了黑龙江省西部草地土壤无机磷形态,结果表明,四种草地土壤均以Ｃａ－Ｐ为主,约占无机磷总量的６０％左右,Ｏ－Ｐ含量少于Ｆｅ－Ｐ和Ａｌ－Ｐ．草甸黑钙土无机磷总量最高,Ｃａ２－Ｐ、Ｃａ８－Ｐ和Ａｌ－Ｐ都是草甸黑钙土重要的贮磷库;草甸风沙土无机磷总量最低,但Ｃａ８－Ｐ含量相对较高;草甸碱土无机磷总量、Ｃａ２－Ｐ和Ａｌ－Ｐ含量显著高于碱化草甸土．向草甸碱土和碱化草甸土施磷酸二铵能显著增加土壤无机磷的总量,尤其显著提高土壤中Ｃａ８－Ｐ和Ａｌ－Ｐ含量．