Development of new spectral reflectance indices for the detection of lichens and mosses moisture content in 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 the lichens Cladina stellaris and Cladina rangiferina, and the mosses Dicranum elongatum and Tomenthypnum nitens on the spectral signatures obtained. 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. Previously, we correlated the present spectral indices with the moisture contents of the above species, whereas the current study developed new species‐specific indices to improve the detection of the plants' moisture contents. The relationship between the plants' moisture content and the water table position was examined as well. It was found that the lichens are not responsive to variations in the water table position, whereas the mosses, specifically D. elongatum, are quite sensitive to changes in the water table position. Thus, the use of the mosses spectral indices may contribute to an indirect evaluation of the water table position. Overall, the results suggest that the unique spectral signatures of the above species can be detected by satellite and airborne imagery, whereas the mosses, can be used as indicators of peatlands moisture status. Copyright © 2010 John Wiley & Sons, Ltd.     

Unsaturated hydraulic properties of xerophilous mosses: towards implementation of moss covered soils in hydrological models

Evaporation from mosses and lichens can form a major component of the water balance, especially in ecosystems where mosses and lichens often grow abundantly, such as tundra, deserts and bogs. To facilitate moss representation in hydrological models, we parameterized the unsaturated hydraulic properties of mosses and lichens such that the capillary water flow through moss and lichen material during evaporation could be assessed. We derived the Mualem‐van Genuchten parameters of the drying retention and the hydraulic conductivity functions of four xerophilous moss species and one lichen species. The shape parameters of the retention functions (2.17 < n < 2.35 and 0.08 < α < 0.13 cm^?1) ranged between values that are typical for sandy loam and loamy sand. The shapes of the hydraulic conductivity functions of moss and lichen species diverged from those of mineral soils, because of strong negative pore‐connectivity parameters (?2.840 < l < ?2.175) and low hydraulic conductivities at slightly negative pressure heads (0.016 < K₀ < 0.280 cm/d). These K₀ values are surprisingly low, considering that mosses are very porous. However, during evaporation, large pores and voids were air filled and did not participate in capillary water flow. Small K₀ values cause mosses and lichens to be conservative with water during wet conditions, thus tempering evaporation compared to mineral soils. On the other hand, under dry conditions, mosses and lichens are able to maintain a moisture supply from the soil, leading to a higher evaporation rate than mineral soils. Hence, the modulating effect of mosses on evaporation possibly differs between wet and dry climates. Copyright © 2013 John Wiley & Sons, Ltd.     

An assessment of water reserve changes in Salt Lake,Turkey, through multi‐temporal Landsat imagery and real‐time ground surveys

This paper focuses mainly on the investigation of water reserve changes in Salt Lake, Turkey, using remote‐sensing data. The study is performed in two stages: (1) correlation analysis for real‐time ground and satellite data and (2) assessment of water reserve changes using multi‐temporal Landsat imagery. First, correlation analysis is conducted to investigate the relationship between digital data from Landsat‐5 TM and spectral (in situ) measurements collected using a field spectroradiometer on the same day and time. A radiometric correction procedure, including conversions from digital numbers to radiance and from radiance to at‐satellite reflectance, is executed to make satellite data comparable to in situ measurements. This procedure show that simultaneous ground and satellite remote‐sensing data are highly correlated (0·84 > R² > 97) and the near‐infrared region (for this study TM4‐Landsat‐5 TM, band 4) is the best spectral range to distinguish salt and water on the satellite data for the multi‐temporal analysis of the water reserve in Salt Lake. It also shows that the use of shortwave infrared band(s) will result in confusion for the determination of the water reserve in this water‐covered study area. In a second and last phase, the water reserve change in the lake is examined using multi‐temporal Landsat imagery collected in 1990, 2001 and 2005. The remotely sensed, sampled and treated data show that the water reserve in the lake has decreased markedly between 1990 and 2005 due to drought and uncontrolled water usage. It is suggested that the use of water supplies around Salt Lake should be controlled and that the lake should regularly be monitored by up‐to‐date remote‐sensing data (at least annually) for better management of water resources. Copyright © 2007 John Wiley & Sons, Ltd.     

UAV RGB,thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust

Biocrusts (topsoil communities formed by mosses, lichens, bacteria, fungi, algae, and cyanobacteria) are a key biotic component of dryland ecosystems. Whilst climate patterns control the distribution of biocrusts in drylands worldwide, terrain and soil attributes can influence biocrust distribution at landscape scale. Multi-source unmanned aerial vehicle (UAV) imagery was used to map and study biocrust ecology in a typical dryland ecosystem in central Spain. Red, green and blue (RGB) imagery was processed using structure-from-motion techniques to map terrain attributes related to microclimate and terrain stability. Multispectral imagery was used to produce accurate maps (accuracy > 80%) of dryland ecosystem components (vegetation, bare soil and biocrust composition). Finally, thermal infrared (TIR) and multispectral imagery was used to calculate the apparent thermal inertia (ATI) of soil and to evaluate how ATI was related to soil moisture (r² = 0.83). The relationship between soil properties and UAV-derived variables was first evaluated at the field plot level. Then, the maps obtained were used to explore the relationship between biocrusts and terrain attributes at ecosystem level through a redundancy analysis. The most significant variables that explain biocrust distribution are: ATI (34.4% of variance, F = 130.75; p < 0.001), Elevation (25.8%, F = 97.6; p < 0.001), and potential solar incoming radiation (PSIR) (52.9%, F = 200.1; p < 0.001). Differences were found between areas dominated by lichens and mosses. Lichen-dominated biocrusts were associated with areas with high slopes and low values of ATI, with soil characterized by a higher amount of soluble salts, and lower amount of organic carbon, total phosphorus (P_tot) and total nitrogen (N_tot). Biocrust-forming mosses dominated lower and moister areas, characterized by gentler slopes and higher values of ATI with soils with higher contents of organic carbon, P_tot and N_tot. This study shows the potential to use UAVs to improve our understanding of drylands and to evaluate the control that the terrain has on biocrust distribution.     

Deployment of an unmanned aerial system to assist in mapping an intermittent stream

Recent growth in the capabilities of unmanned aerial vehicles and systems (UASs) as airborne platforms for collecting environmental data has been very rapid. There are now ample examples in the literature of UASs being deployed to map fine‐scale vegetation, glacial, soil and atmospheric conditions. The purported advantages of UASs are their ability to collect spatial data at lower cost, lower risk, higher resolution and higher frequency than ground surveys or satellite platforms. In this specific study, whether or not obtaining high‐resolution UAS imagery was advantageous for identifying an intermittent stream network was determined by comparing it with coarse‐scale satellite imagery collected for the same purpose. It was also determined if the UAS imagery could be an improvement to Global Positioning System acquired ground‐truth points for classifying an intermittent stream network across the same large‐scale satellite image. The UAS‐acquired and satellite‐acquired imageries were derived from a visible spectrum camera capable of 2‐cm resolution and multispectral SPOT‐5 with 10‐m resolution, respectively. The SPOT‐5 imagery with its relatively coarse resolution could not always detect the narrow intermittent stream, which was well resolved in the UAS imagery. When a classified UAS image was applied as a training area for the SPOT‐5 image, the identification of the stream network and accuracy of the satellite imagery classification did not necessarily improve. UASs have the potential to revolutionize hydrological research the same way that geographic information systems did three decades ago. A final goal of the paper is to provide insight into the advantages and disadvantages of deploying a UAS for this kind of research. © 2015 Her Majesty the Queen in Right of Canada. Hydrological Processes. © 2015 John Wiley & Sons, Ltd.     

Preliminary spectral characterization of snow in a high altitude tropical glacier and potential effects of impurities in snow on albedo of tropical glaciers

This paper presents some preliminary measurements of snow spectral reflectance on the tropical Bolivian Zongo glacier. Measurements show a correct agreement with theoretical spectral albedo of pure snow in the near infrared region, but lower values in the visible region (by 10–20%) probably due to aerosols contained in snow. Impurity contents ranged from 10 to 100 ppmw in one‐week‐old snow collected from the Zongo glacier, but measurements are scarce. Large amounts of snowfall partly compensate the proximity of dust sources in mid‐latitude glaciers, whereas on outer‐tropical glaciers precipitations are not abundant and are very seasonal, and sources of aerosols are proximate. Copyright © 2007 John Wiley & Sons, Ltd.     

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.     

巢湖浮游植物叶绿素含量与反射光谱特征的关系

利用高光谱地物光谱仪在巢湖进行了反射光谱测量和同步水质采样分析。在分析巢湖水体反射光谱特征的基础上,通过研究水体光谱反射率与叶绿素浓度之间的关系,利用反射率比值法和一阶微分法分别建立了叶绿素a的遥感定量模型。结果表明反射率比值R705nm/R680nm和690nm反射率的一阶微分均与叶绿素a浓度有较好的相关性,且用反射率比值法估算叶绿素a效果较好。     

Optimizing statistical classification accuracy of satellite remotely sensed imagery for supporting fast flood hydrological analysis

The aim of this study is to improve classification results of multispectral satellite imagery for supporting flood risk assessment analysis in a catchment area in Cyprus. For this purpose, precipitation and ground spectroradiometric data have been collected and analyzed with innovative statistical analysis methods. Samples of regolith and construction material were in situ collected and examined in the spectroscopy laboratory for their spectral response under consecutive different conditions of humidity. Moreover, reflectance values were extracted from the same targets using Landsat TM/ETM+ images, for drought and humid time periods, using archived meteorological data. The comparison of the results showed that spectral responses for all the specimens were less correlated in cases of substantial humidity, both in laboratory and satellite images. These results were validated with the application of different classification algorithms (ISODATA, maximum likelihood, object based, maximum entropy) to satellite images acquired during time period when precipitation phenomena had been recorded.     

The interpretation of visible band imagery of turbid shallow seas in terms of the distribution of suspended particulates

Visible band imagery from the Nimbus 7 Coastal Zone Colour Scanner (CZCS) and other satellite scanners indicates the occurrence of well-defined and persistent patterns of fine sediment concentration in the Irish Sea. The principal features of these distributions are related to variations in the intensity of tidal stirring with sharp transitions in the sub-surface reflectance occurring at frontal boundaries where there are abrupt changes in the vertical mixing regime. Observations of the suspended sediment concentration, both direct and by optical beam transmittance meter, have been used to demonstrate the correspondence between seston variations and changes in sub-surface reflectance as observed by satellite scanners.Radiometric measurements of sub-surface reflectance R are used to investigate the dependence of R (550 nm) on the concentration of suspended particulates Σ. The slope of the Σ- R relation is found to increase with the concentration of organic seston in a systematic way, a trend which is also apparent in an independent data set from the mouth of the Rhoˆne in the Mediterranean.These results may provide the basis for improved quantitative determination of seston from remotely sensed data if the mean level of organic seston concentration is known, or can be estimated from the spectral ratios in the reflectance data.     

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.     

Micro‐geomorphology determines community structure of biological soil crusts at small scales

Biological soil crusts (BSCs) are ubiquitous communities of diminutive organisms such as cyanobacteria, green algae, lichens, mosses and others associated closely with particles of surface soil, forming a cohesive thin horizontal layer. The ecological roles of BSCs affecting soil nutrient cycling, stability and hydrological processes, influencing the germination and establishment of vascular plants, and serving as habitats for numerous arthropods and microorganism have been well documented. We tested the hypothesis that micro‐geomorphological features determine the spatial distribution of BSCs by reallocating related abiotic resources at small‐ and medium‐scales in the Tengger Desert. Our results showed that higher soil pH and higher total potassium content in topsoil positively correlated with the colonization of cyanobacteria and algae in the earliest successional stages of BSCs, while increasing dust deposition onto the topsoil enhanced the development of lichen and mosses in the later stages of BSCs. Increasing soil moisture raised the proportion of mosses and lichen in BSCs, this will possibly change the ecological functions of BSCs, such as nitrogen‐fixation by cyanobacteria, due to the conversion from a complex to relative simple type of BSC. Micro‐geomorphology has created various habitats at a small‐scale affecting colonization and development of cryptogams. This paper considers the contribution of micro‐geomorphology to biodiversity in the extreme arid desert systems. Copyright © 2010 John Wiley & Sons, Ltd.     

Near‐infrared spectroscopy of a hydroecological indicator: new tool for determining sustainable yield for Floridan aquifer system

Pond‐cypress (Taxodium ascendens Brong.) is a dominant canopy species in depressional wetlands of the south‐eastern Coastal Plain. Unsustainable withdrawals from the karst Floridan aquifer system have caused premature decline and death of pond‐cypress trees, presumably owing to altered hydroperiods (which alter the flow of water and nutrients in trees). There has been no scientifically based means to determine sustainable yield from this regional aquifer system or to detect early stages of physical/ecological damage associated with groundwater mining and aquifer storage and recovery (ASR, which also can alter natural hydroperiods). In this study, the relationship between visual symptoms (indicators) of stress or premature decline, and spectral reflectance was evaluated using dried, milled branch tips collected from natural stands of mature pond‐cypress. Depressional systems evaluated represented four of the six aquifer system subregions where subsurface perturbations from groundwater mining: (i) were presumed not to be occurring (reference wetlands); (ii) may be occurring but are not documented; and (iii) have been confirmed. Sampled trees were assigned to one of three stress classes (1, no/minimal; 2, moderate; 3, severe) based on the visual indicators. Partial least squares–linear discriminant analysis of second derivative spectral transformations in the visible/shortwave near‐infrared (NIR) region (400–1100 nm) and the NIR region (1100–2500 nm) was used to evaluate the samples in assigned classes. Class 1 samples were discriminated from combined class 2 and 3 samples in the NIR region with 100% and 97% accuracy for consecutive winter sample periods (before bud‐break). The percentage of correctly classified samples in this spectral region was lower (85%) for summer samples (full leaf‐out). Second‐derivative models for the NIR region developed from the winter data sets predicted assigned classes for alternate winter's samples with an accuracy of 97% and 100%. High correlation between spectral reflectance of dried, milled branch tips collected from mature pond‐cypress in winter and visual indicators of premature decline suggests in situ pond‐cypress are hydroecological indicators of anthropogenic subsurface hydroperiod perturbations. This approach provides objective means for early detection of unsustainable aquifer yield and adverse impacts from ASR activities in the south‐eastern Coastal Plain. Used in conjunction with hydrological monitoring and modelling, the hydroecological indicators should provide the means with which sustainable yield in the south‐eastern Coastal Plain can be achieved and maintained. Copyright © 2003 John Wiley & Sons, Ltd.     

On the potential of MetOp ASCAT‐derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg

In situ soil moisture data from the Bibeschbach experimental catchment in Luxembourg are used to evaluate relative surface soil moisture observed with the MetOp‐A Advanced Scatterometer (ASCAT). Filtered and bias‐corrected surface soil wetness indices (SWIs) derived from coarse‐resolution (25 km) C‐band scatterometer observations are shown to be highly correlated (r = 0.86) with catchment‐averaged soil moisture measured in the field. The combination of ASCAT and ENVISAT Advanced Synthetic Aperture Radar (ASAR) data sets yields high‐resolution (1 km) relative surface soil moisture that is equally well correlated with in situ measurements. It is concluded that for soil moisture monitoring applications at a catchment scale, the two soil moisture products are equivalent. The best correlation between the SWI derived from ASCAT and ASCAT‐ASAR with in situ soil moisture observations at ca. 5 cm depth is obtained with a characteristic time length parameter T equal to 288 h. These results suggest that satellite‐derived surface soil wetness may serve as proxy for soil storage that enables the monitoring of abrupt switches in river system dynamics to appear when an effective field capacity is exceeded and rapid subsurface stormflow is initiated. In catchments where soil moisture is the main controlling factor of rapid subsurface flow, MetOp ASCAT–derived SWI has the potential to monitor how a river system approaches a critical threshold. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluation of inundation areas resulting from the diversion of an extreme discharge towards the sea: case study in Tabasco,Mexico

This investigation comprises the hydraulic characterisation of a river located in the Mexican State of Tabasco, including the performance of its flood plain under the action of an extreme river discharge. This is done through the combination of a high‐quality validation dataset, remote sensing information, and a standard 2D numerical model. The dataset was collected during an intensive field campaign that took place in August 2009. In particular, in situ measurements of river discharge, bathymetry, water level, and velocities through a whole tidal cycle are employed along with multi‐spectral satellite imagery. The purpose of this study is twofold. Firstly, the integrated approach comprising the combination of a 2D hydrodynamic model, high‐quality in situ measurements and satellite imagery reduce the uncertainty in the model parameterisation and results. Secondly, it is shown that freely available sources of information, such as the Shuttle Radar Topographic Mission (SRTM) data can be processed and utilized in 2D hydraulic models. This is particularly important in countries where high‐resolution elevation data is not yet available. It is demonstrated that the selected approach is useful when the study of possible consequences in a flood plain induced by an extreme flood discharge are sought. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessing the potential of drone‐based thermal infrared imagery for quantifying river temperature heterogeneity

Climate change is altering river temperature regimes, modifying the dynamics of temperature‐sensitive fishes. The ability to map river temperature is therefore important for understanding the impacts of future warming. Thermal infrared (TIR) remote sensing has proven effective for river temperature mapping, but TIR surveys of rivers remain expensive. Recent drone‐based TIR systems present a potential solution to this problem. However, information regarding the utility of these miniaturised systems for surveying rivers is limited. Here, we present the results of several drone‐based TIR surveys conducted with a view to understanding their suitability for characterising river temperature heterogeneity. We find that drone‐based TIR data are able to clearly reveal the location and extent of discrete thermal inputs to rivers, but thermal imagery suffers from temperature drift‐induced bias, which prevents the extraction of accurate temperature data. Statistical analysis of the causes of this drift reveals that drone flight characteristics and environmental conditions at the time of acquisition explain ~66% of the variance in TIR sensor drift. These results shed important light on the factors influencing drone‐based TIR data quality and suggest that further technological development is required to enable the extraction of robust river temperature data. Nonetheless, this technology represents a promising approach for augmenting in situ sensor capabilities and improved quantification of advective inputs to rivers at intermediate spatial scales between point measurements and “conventional” airborne or satellite remote sensing.     

An automated algorithm for river ice monitoring over the Susquehanna River using the MODIS data

Reliable and prompt information on river ice condition and extent is needed to make accurate hydrological forecasts to predict ice jams breakups and issue timely flood warnings. This study presents a technique to detect and monitor river ice using observations from the MODIS instrument onboard the Terra satellite. The technique incorporates a threshold‐based decision tree image classification algorithm to process MODIS data and to determine the extent of ice. To differentiate between ice‐covered and ice‐free pixels within the riverbed, the algorithm combines observations in the visible and near‐infrared spectral bands. The developed technique presents the core of the MODIS‐based river ice mapping system, which has been developed to support National Oceanic and Atmospheric Administration NWS's operations. The system has been tested over the Susquehanna River in northeastern USA, where ice jam events leading to spring floods are a frequent occurrence. The automated algorithm generates three products: daily ice maps, weekly composite ice maps and running cloud‐free composite ice maps. The performance of the system was evaluated over nine winter seasons. The analysis of the derived products has revealed their good agreement with the aerial photography and with in situ observations‐based ice charts. The probability of ice detection determined from the comparison of the product with the high‐resolution Landsat imagery was equal to 91%. A consistent inverse relationship was found between the river discharge and the ice extent. The correlation between the discharge and the ice extent as determined from the weekly composite product reached 0.75. The developed CREST River Ice Observation System has been implemented at National Oceanic and Atmospheric Administration–Cooperative Remote Sensing Science and Technology Center as an operational Web tool allowing end users and forecasters to assess ice conditions on the river. Copyright © 2012 John Wiley & Sons, Ltd.     

A method for canopy water content estimation for highly vegetated surfaces-shortwave infrared perpendicular water stress index

In this paper, a new method for canopy water content (FMC) estimation for highly vegetated surfaces- shortwave infrared perpendicular water stress index (SPSI) is developed using NIR, SWIR wavelengths of Enhanced Thematic Mapper Plus (ETM ) on the basis of spectral features and distribution of surface targets with different water conditions in NIR-SWIR spectral space. The developed method is further explored with radiative transfer simulations using PROSPECT, Lillesaeter, SailH and 6S. It is evident from the results of validation derived from satellite synchronous field measurements that SPSI is highly correlated with FMC, coefficient of determination (R squared) and root mean square error are 0.79 and 26.41%. The paper concludes that SPSI has a potential in vegetation water content estimation in terms of FMC.     

Relating Hyperspectral Airborne Data to Ground Measurements in a Complex and Discontinuous Canopy

The work described in this paper is aimed at validating hyperspectral airborne reflectance data collected during the Regional Experiments For Land-atmosphere EXchanges (REFLEX) campaign. Ground reflectance data measured in a vineyard were compared with airborne reflectance data. A sampling strategy and subsequent ground data processing had to be devised so as to capture a representative spectral sample of this complex crop. A linear model between airborne and ground data was tried and statistically tested. Results reveal a sound correspondence between ground and airborne reflectance data (R2 > 0.97), validating the atmospheric correction of the latter.