Lichens and mosses moisture content assessment through high‐spectral resolution remote sensing technology: a case study of the Hudson Bay Lowlands,Canada

Assessing moisture contents of lichens and mosses using ground‐based high‐spectral resolution spectrometers offers immense opportunities for a comprehensive monitoring of peatland moisture status by satellite/airborne imagery. This study investigates the impact of various moisture conditions of common subarctic lichen and moss species upon the spectral signatures obtained. The lichens are Cladina stellaris and Cladina rangiferina, and the mosses are Dicranum elongatum and Tomenthypnum nitens. Reflectance and moisture content measurements of these species were made in a laboratory setting, while maintaining the natural moisture conditions of the samples; once the moisture and spectral measurements were complete, the samples were returned to the field and placed in their natural setting, continuously receiving moisture from precipitation and groundwater and losing water through evaporation and drainage. Changes in reflectance of the visible to shortwave infrared (SWIR) range (400–2500 nm) at various moisture contents were examined, as well as the potential of current spectral reflectance indices to evaluate the plants' moisture contents was examined. Results indicate that the SWIR region is useful in identifying variations in plants moisture conditions, while the unique spectral signatures of the lichens and mosses in the visible and near‐infrared range suggest that these species may be detected by satellite and airborne imagery. Of current spectral indices, the normalized difference infrared index (NDII) was most successful in identifying the above plants' moisture content (details are discussed in the paper). Future study should focus on the development of improved moisture content spectral indices, as well as upscaling reflectance data and spectral indices. Copyright © 2010 John Wiley & Sons, Ltd.     

Spectral reflectance measurements of estuarine waters

Shapes and variations of reflectance spectra in estuarine water were investigated for the purpose of monitoring chlorophyll in situ by optical means. A survey undertaken in an estuarine environment, using reflectance measurements between 400 and 850 nm with a full-width half maximum (FWHM) of about 2 nm, revealed that the first derivative in the neighbourhood of the chlorophyll absorption band shows a defined spectral region which can be used to estimate chlorophyll concentrations. Correlation between chlorophyll and the first derivative was found to be low, but a good relationship exists between the ratio of the reflectance R680/R670 and chlorophyll concentrations. Based on dissolved organic carbon measurements, it is assumed that chromophoric dissolved organic compounds mask the absorption band of chlorophyll in the blue part of the spectrum, resulting in a low correlation coefficient in that spectral range. Therefore, the use of the red bands is an alternative for measuring photosynthetic pigments in coastal water at longer wavelengths. Results presented here demonstrate that the spectral locations of bands in the visible are not adequate and that hyperspectral data are required for positioning the very narrow bands for measuring chlorophyll at longer wavelengths.     

查干湖冰封期光谱特征及影响因素

湖冰光谱特征是湖冰遥感反演的物理基础,是研究湖冰光学特性和空间分布的理论依据。本文以查干湖为例,使用ASD Field Spec 4便携式地物光谱仪采集冰封期不同类型湖冰、积雪和水体光谱,利用Savitzky-Golay滤波法和包络线去除法分析白冰、灰冰、黑冰、雪冰、积雪和水体的反射光谱特征,探索气泡对湖冰反射光谱特征的影响。积雪和雪冰、白冰和灰冰、黑冰和水体的反射特征随着波长的变化特征基本一致,冰的反射率介于积雪和水体之间,其中白冰的反射率高于灰冰和黑冰,在包络线去除结果中,黑冰和水体在440 nm吸收谷处的吸收面积为5.184和10.878、吸收深度为0.052和0.106,雪、雪冰、白冰、灰冰在800和1030 nm吸收谷处的吸收面积和吸收深度的变化表现为雪<雪冰<灰冰<白冰。气泡是影响湖冰光谱特征的重要因素,气泡使白冰反射率减小和黑冰反射率增大,并且气泡使得白冰在800/1030nm和黑冰在440 nm处的吸收面积和吸收深度减小,其中气泡大小和疏密程度的不同会导致湖冰反射率的影响程度存在差异。同时,本文选取时间同步的Landsat 8 OLI遥感影像,在完成辐...     

Simple infrared techniques for measuring beach surface moisture

Knowledge of surface moisture on beaches is vital for aeolian process studies because moisture increases transport thresholds and limits mass flux. A number of beach surface moisture measurement techniques have been employed in the field, including sample extraction, commercial soil moisture sensors, and remote sensing techniques. Each method has significant limitations in the context of aeolian process studies. This study was designed to test infrared optic techniques for measuring beach surface moisture. A simple infrared sensor (narrow‐band radiometer) was developed to measure beach surface moisture content. The accuracy and practical usability of the narrow‐band radiometer were assessed in comparison to a commercial handheld spectroradiometer. Field calibrations conducted at Cape San Blas, Florida and Padre Island, Texas indicated that the narrow‐band radiometer performed quite well. The R² values exceeded 0·98 in each case, and the standard error averaged about 1% moisture content compared with gravimetric moisture contents determined from 1·5 mm deep surface scrapes. The performance of the two instruments was found to be comparable, with the narrow‐band radiometer slightly outperforming the spectroradiometer. In practical applications, the narrow‐band radiometer also has logistical advantages and is better suited to measure large numbers of points. Copyright © 2012 John Wiley & Sons, Ltd.     

乌梁素海沉水植物群落光谱特征及冠层水深影响分析

沉水植物对于改善富营养化水体和重建水生生态系统起着至关重要的作用.应用遥感技术可以实时、大面积监测沉水植物的分布和生长情况,而冠层水深直接影响沉水植物在湖泊、河流中的准确遥感解译.本研究基于实测光谱数据,分析了乌梁素海沉水植物光谱特征,并研究了冠层水深对乌梁素海沉水植物反射光谱的影响,建立了乌梁素海沉水植物冠层水深反演模型.结果表明:1)挺水植物在短波红外1662 nm和2223 nm附近分别有一个反射峰,这是挺水植物区别于沉水植物和漂浮藻类的重要波段; 0深度沉水植物(WDC=0)与漂浮藻类的光谱反射率非常接近,但是在绿波段(550～690 nm)有明显差异,因此,可以利用绿波段和短波红外波段的光谱特征来区分挺水植物、沉水植物和漂浮藻类.2)沉水植物群落的光谱反射率随冠层水深的增加而降低,在700～900 nm波段范围内变化最为明显,且在700～735 nm波段附近,沉水植物群落光谱反射率与冠层水深呈显著负相关.3)在建立的单波段/波段比沉水植物冠层水深反演模型中,波段比反演模型要优于单波段反演模型,波段比反演模型的决定系数R2 0.70,均方根误差13.70 cm,平均相对误差28%,反演精度较好,适用于10～60 cm沉水植物冠层水深的反演.4)利用波段响应函数,将实测光谱反射率积分到Landsat-8 OLI波段上,建立OLI了冠层水深反演模型,其中,波段比幂函数模型反演效果最好,R2为0.49,均方根误差为18.17 cm,平均相对误差40.05%.可用于精确大气校正后乌梁素海沉水植物冠层水深的反演.     

Remote sensing in hydrology

Remote sensing provides a means of observing hydrological state variables over large areas. The ones which we will consider in this paper are land surface temperature from thermal infrared data, surface soil moisture from passive microwave data, snow cover using both visible and microwave data, water quality using visible and near-infrared data and estimating landscape surface roughness using lidar. Methods for estimating the hydrometeorlogical fluxes, evapotranspiration and snowmelt runoff, using these state variables are also described.     

Aerosol optical depth retrieval by HJ-1/CCD supported by MODIS surface reflectance data

The high spatial resolution and temporal observation frequency of HJ-1/CCD make it suitable for aerosol monitoring. However, because of the lack of a shortwave infrared band, it is difficult to use HJ-1/CCD imagery to retrieve aerosol optical depth (AOD). We developed a new algorithm for HJ-1/CCD AOD retrieval by introducing MODIS surface reflectance outputs (MOD09) as support. In this algorithm HJ-1/CCD blue band surface reflectance was retrieved through MOD09 blue band surface reflectance by band matching of the two sensors. AOD at 550 nm was then generated through a pre-calculated look-up table for HJ-1/CCD. Eighteen HJ-1/CCD images covering the Jing-Jin-Tang (Beijing-Tianjin-Tangshan) region were used to retrieve AOD using the new algorithm, and the AODs were then validated using AERONET ground measurements in Beijing and Xianghe. The validation shows that compared with AERONET ground measurements, 27/29 AODs have error less than 0.1 in absolute value.     

NIR-red spectral space based new method for soil moisture monitoring

Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is de- veloped using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0―20 cm soil depths, correlation coef- ficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions.     

A mathematical model of soil moisture spatial distribution on the hill slopes of the Loess Plateau

Based on important factors that affect soil moisture spatial distribution, such as the slope gradients, land use, vegetation cover, and surface water diffusion characteristics together with field measurements of soil moisture data obtained from the surface soil under different land use structures, a soil moisture spatial distribution model was established. The diffusion degree coefficient of surface water for different vegetations was estimated from soil moisture values obtained from field measurements. The model can be solved using the finite unit method. The soil moisture spatial distribution on the hill slopes in the Loess Plateau were simulated by the model. A comparison of the simulated values with measurement data shows that the model is a good fit.     

Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models

Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ET_c) accurately is critical for improving irrigation system and basin water management. The use of remote sensing-based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near-infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.     

Multi-functional heat pulse probe measurements of coupled vadose zone flow and transport

Simultaneous measurement of coupled water, heat, and solute transport in unsaturated porous media is made possible with the multi-functional heat pulse probe (MFHPP). The probe combines a heat pulse technique for estimating soil heat properties, water flux, and water content with a Wenner array measurement of bulk soil electrical conductivity (EC_bulk). To evaluate the MFHPP, we conducted controlled steady-state flow experiments in a sand column for a wide range of water saturations, flow velocities, and solute concentrations. Flow and transport processes were monitored continuously using the MFHPP. Experimental data were analyzed by inverse modeling of simultaneous water, heat, and solute transport using an adapted HYDRUS-2D model. Various optimization scenarios yielded simultaneous estimation of thermal, solute, and hydraulic parameters and variables, including thermal conductivity, volumetric water content, water flux, and thermal and solute dispersivities. We conclude that the MFHPP holds great promise as an excellent instrument for the continuous monitoring and characterization of the vadose zone.     

Analysis of the spectral response of flourishing-withering vegetation changes based on ground spectral measurements

A structural mode was used to characterize vegetation composition at the plant leaf level and a flourishing-withering ratio was developed. The spectral responses of vegetation with different flourishing-withering ratios were analyzed, the change rates of the chlorophyll and moisture content indices of vegetation with different flourishing-withering ratios were compared, and correlations between the chlorophyll and moisture content indices were analyzed. The results reveal that leaves with an intermediate flourishing-withering ratio can increase the absorption signatures of vegetation and that band ranges of 570–700 nm and 1300–1540 nm can play a role in indicating changes in the flourishing-withering ratios of vegetation; NPQI, NPCI, R₆₉₅/R₄₂₀, R₆₉₅/R₇₆₀, R₇₅₀/R₇₀₀, the peak-value area of red selvedge, the red selvedge amplitude, the ratio between the red selvedge amplitude and the minimum amplitude, and the NDVI of vegetation change regularly with the change in flourishing-withering ratios, and these nine vegetation indices are highly related to the chlorophyll content. Vegetation indexes of NDWI and PRI are very sensitive to the flourishing-withering change in vegetation and are closely related to the moisture content, and the correlation coefficient is higher than 0.9. The derivative of the spectra is more effective in describing changes in the structural mode of vegetation with different flourishing-withering ratios, especially at band ranges of 552–628 nm and 630–686 nm, and it is more sensitive to the mixed flourishing-withering ratios of leaves rather than to the vegetation indices. The red selvedge position in the spectrum is highly related to the chlorophyll content and is not sensitive to changes in the structural mode of mixed flourishing-withering leaves. The red selvedge parameters are sensitive to changes in the flourishing-withering ratio at the peak-value area of the red selvedge amplitude and the ratio between the red selvedge amplitude and the minimum amplitude. The effect of a sand background on the spectrum of withering leaves is higher than that of flourishing leaves; the effect of a sand background increases with increasing proportions of withering leaves, the superposition effect of the sand background on mixed flourishing-withering leaves is about 7% at visible light bands of 400–700 nm and 1300–1540 nm, and is over 10% at the near infrared band range of 700–1300 nm.     

Aerosol optical depth retrieval by HJ-1/CCD supported by MODIS surface reflectance data

The high spatial resolution and temporal observation frequency of HJ-1/CCD make it suitable for aerosol monitoring. However, because of the lack of a shortwave infrared band, it is difficult to use HJ-1/CCD imagery to retrieve aerosol optical depth (AOD). We developed a new algorithm for HJ-1/CCD AOD retrieval by introducing MODIS surface reflectance outputs (MOD09) as support. In this algorithm HJ-1/CCD blue band surface reflectance was retrieved through MOD09 blue band surface reflectance by band matching of the two sensors. AOD at 550 nm was then generated through a pre-calculated look-up table for HJ-1/CCD. Eighteen HJ-1/CCD images covering the Jing-Jin-Tang (Beijing-Tianjin-Tangshan) region were used to retrieve AOD using the new algorithm, and the AODs were then validated using AERONET ground measurements in Beijing and Xianghe. The validation shows that compared with AERONET ground measurements, 27/29 AODs have error less than 0.1 in absolute value.

     

Soil water content in southern England derived from a cosmic‐ray soil moisture observing system – COSMOS‐UK

Cosmic‐ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area‐averaged near‐surface (top 10–20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011–2014 and are the first such field‐scale measurements made in the UK. These four sites are prototype stations for a UK COsmic‐ray Soil Moisture Observing System, and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator 10‐cm soil moisture layer shows that these data can be used to test and diagnose model performance and indicate the potential for assimilation of these data into hydro‐meteorological models. The application of these large‐area soil water content measurements to evaluate remotely sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COsmic‐ray Soil Moisture Observing System network are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

A computer-based datalogging system used to investigate the infiltration process under natural rainfall conditions

The system described in this paper uses a commercial, portable computer to monitor rainfall, surface runoff, soil moisture potential, soil temperature, and water table levels. The system is designed as a permanent field instrument which reads 16 analogue and two digital channels. It offers 10-bit accuracy and records data on both magnetic tape and paper for greater security. The computer program is in Microsoft BASIC and can therefore be readily altered to change the measurement regime. Although designed to investigate the infiltration process the system is easily adapted to monitor other environmental processes.     

Identification of robust hyperspectral indices on forest leaf water content using PROSPECT simulated dataset and field reflectance measurements

In this study, we aim at finding efficient and robust hyperspectral indices for estimating forest leaf water content parameters (equivalent water thickness, EWT and fuel moisture content, FMC), which are useful for the understanding of terrestrial ecosystem functioning and evaluating fire risk. The most efficient hyperspectral indices have been identified (both on the context of index types and wavelength domains) using both a simulated dataset generated from the calibrated leaf reflectance model, PROSPECT, and datasets of field measured reflectance. Results indicate that high precision can be obtained using the type of vegetation index of two wavelength bands based on reflectance derivatives to estimate both parameters, with overall R² and RMSE of 0·60 ～ 0·75 and 0·0009 ～ 0·0012 g cm^?2 for EWT, 0·63 ～ 0·87 and 0·12 ～ 0·20 g g^?1 for FMC, respectively. The best indices identified in this study for vegetation water status in temperate deciduous forests were dSR (1510, 1560) for EWT and dSR (2110, 2260) for FMC, with widths of wavebands (Δλ) be variable up to 50 nm for both dSR indices. Despite the obvious discrepancies found in fit when applying the identified indices to different datasets, the indices identified in this study are applicable to various species (Dataset III), various phenological stages, different sites (Dataset I) and various leaf anatomies (Dataset II), and therefore suitable for an all inclusive wide range of application especially in temperate deciduous forests. Copyright © 2011 John Wiley & Sons, Ltd.     

The potential information in the temperature difference between shadow and sunlit of surfaces and a new way of retrieving the soil moisture

The thermal inertia and plant water stress index are often adopted to estimate soil moisture available for crops or plants. However, it is not very easy to obtain two temporal temperatures for thermal inertia model and air temperature for the plant water stress mode. Shadows of ground objects are often referred to noise on visible and near infrared remote sensing. But the difference of temperature between shadows and sunlit contains rich information concerning with heat-water status for soil. This paper presented a new way to excavate just by temperature difference usually between shadow and sunlit surface. Experiments validated the ideal. We can adopt thermal camera to measure the differences in the field measurements. However, we must use inversion based on multianglar thermal infrared remote sensing data in airborne and spaceborne. An inverting model was also presented by using Monte-Carlo and the least square method. Results show that this way is feasible.     

Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2–5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE³) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m³ m⁻³). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m³ m⁻³) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R² correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE³ study site.     

Effects of Soil Rhizosphere Aeration on the Root Growth and Water Absorption of Tomato

Soil rhizosphere aeration status is an important aspect of soil quality and soil ecology. The objective of the current study was to determine the appropriate moisture environment that facilitates rhizosphere soil aeration and ensures normal root respiration in tomato. In the potted experiment, five treatments of soil aeration were used (0.4, 0.8, 1.2, 1.6 ventilation volume of 50% porosity of soil, and no ventilation) under conditions of the different soil moisture upper limits. The effects of different rhizosphere soil aerations on the physiological indicators and water absorption of tomato were studied. Under the same soil moisture condition, plant growth and root vitality initially increased, and then decreased when the soil ventilation volume increased. The combination of soil moisture with 80% of field capacity and 0.8 ventilation volume with 50% soil porosity raised the chlorophyll content by 29.98% and the root vitality by 61.55%, as compared with the non‐ventilated treatment. Therefore, the appropriate volume of rhizosphere ventilation can effectively improve the capacity of water absorption in tomato. The result provides a new view about soil quality and soil ecology in terms of soil–root system.