Vegetation Moisture Content Research Articles

Establishment of empirical relations between fuel moisture content and the normalised difference vegetation index

The object of the present research is to establish empirical relations between the Fuel Moisture Content (FMC) and the Normalised Difference Vegetation Index (NDVI) in pasture samples. The study area was the Carillanca Experimental Centre belonging to the Institute ofAgriculture and Livestock Research (Instituto de Investigaciones Agropecuarias - INIA), Araucania Region, Chile. The study period ran from November 2011 to January 2012, in order to determine the variation in vegetation moisture content from spring, when plant cover is most vigorous, to summer when it declines to a minimum due to the summer drought. The application of a linear adjustment model produced correlation coefficients higher than 0.6.

Vegetation moisture content model based on principal component analysis

In this paper,hyperspectral remote sensing technology was applied to the quantitative study of the relationship between the reflectance spectra of vegetation and vegetation moisture content,and reliable data were obtained for the study of vegetation water content as one of the "Eco-water"information parameters.Sensitive bands were extracted by relevance analysis and stepwise regression of the reflectance spectra and the moisture content of palm leaves collected in the sampling points.In avoidance of the interaction of sensitive bands,the relationship between principal constituents and moisture content was identified as a transition in the first place by extracting principal constituents using principal component analysis,the regression equation of every principal component and standard variables was established,the equation of regression between every standard variable and original variables was also established and,finally,the model of the relationship between vegetation moisture content and reflectance spectra was obtained from translating the transition model.The results showed that the reflectance spectra of palm leaves had significant correlation with vegetation water content at 454 nm,668 nm,1 466 nm,1 664 nm and 1 924 nm,and that the relative correlation between the predicted values obtained in the niche model and the monitoring values was 0.92,with the root mean square error being 0.06.

The potential of dual-wavelength laser scanning for estimating vegetation moisture content

Vegetation moisture content is an important early indicator of forest drought stress, disease and fire risk. Existing remote sensing techniques to measure biochemical properties of vegetation, such as Equivalent Water Thickness (EWT), are limited by an inability to differentiate canopy and understorey properties and are influenced by variations in canopy structure. By providing a range-resolved estimate of reflectance, laser scanner measurements have the potential to overcome these limitations. Dual-wavelength laser scanning can provide an active measurement of reflectance from which spectral indices can be derived that are insensitive to range, incidence angle and scattering area of the target within the laser beam, factors that make exploiting single-wavelength laser scanner intensity data difficult.This study demonstrates the potential of dual-wavelength laser scanning for measurement of leaf biochemical properties, through determining the relationship between a laser-scanner-derived spectral index, using near infrared (1063nm) and middle infrared (1545nm) wavelengths, and the EWT of individual leaves. The suitability and sensitivity of the index is tested using a leaf optical properties model (PROSPECT-5) and the method is tested experimentally under laboratory conditions using the Salford Advanced Laser Canopy Analyser. A strong relationship (R2=0.8, RMSE=0.0069gcm−2) was found between a normalised ratio of the two wavelengths and measured EWT of leaf samples. The relationship corresponds well to that predicted by modelling. However, the experimental data also revealed significant spatial variability in the index value across individual leaves, suggesting heterogeneity in moisture distribution at within-leaf scales. The study suggests significant potential for using dual-wavelength and multispectral laser scanning for measuring vegetation biochemical properties.

Impact factors of soil wind erosion in the center of Taklimakan Desert

The development and progress of soil wind erosion are influenced by the factors of climate, terrain, soil and vegetation, etc. This paper, taking Tazhong region, a town in the centre of the Taklimakan Desert, as an example and using comparative and quantitative methods, discussed the effects of climate, surface roughness (including vegetation cover) and surface soil properties on soil wind erosion. The results showed that the climate factor index C of annual wind erosion is 28.3, while the maximum of C is 13.9 in summer and it is only 0.7 in winter. The value of C has a very good exponential relationship with the wind speed. In Tazhong region, the surface roughness height is relatively small with a mean of 6.32 × 10 −5 m, which is in favor of soil wind erosion. The wind erosion is further enhanced by its sandy soil types, soil par- ticle size, lacking of vegetation and low soil moisture content. The present situation of soil wind erosion is the result of concurrent effects of climate, vegetation and surface soil properties.

Mapping eucalypt forest susceptible to dieback associated with bell miners ( Manorina melanophys) using laser scanning, SPOT 5 and ancillary topographical data

Mapping the location and extent of forest at risk from damaging agents or processes assists forest managers in prioritizing their planning and operational mitigation activities. In Australia, Bell Miner Associated Dieback (BMAD) refers to a form of canopy decline observed in eucalypt crowns occupied by colonies of bell miners ( Manorina melanophrys). High densities of bell miners are associated with decreased avian abundance and diversity and an increase in psyllid abundance on crown foliage. BMAD has recently been nominated as a key threatening process in New South Wales (NSW). Consequently, a modelling system for predicting bell miner distribution in coastal eucalypt forests of NSW has been developed. The presence or absence of bell miners was recorded in 130 plots located within a 12,800 ha catchment study area containing a range of eucalypt forest types. The modelling system was produced by integrating a machine learning software suite (WEKA), and the statistical software R within the geographic resources analysis support system (GRASS) geographical information system (GIS). The variable modelled was the binary variable: presence or absence of bell minors. Six modelling techniques (Logistic regression; generalised additive models; two tree-based ensemble classification algorithms, random forest and Adaboost and Neural Networks) were integrated with airborne laser scanning; SPOT 5 and topographic derived variables. Model evaluation and parameter selection were measured by three threshold dependent measures (sensitivity, specificity and kappa) and the threshold independent Receiver Operator Curve (ROC) analysis. The final presence and absence maps were obtained through maximisation of the kappa statistic and applied at a resolution of 10 m across the entire catchment study area. For this data set, the most accurate algorithm for predicting the distribution of bell miner colonies was random forest (kappa = 0.84; ROC area under curve = 0.97). Variables most commonly selected in the six models were the laser scanning metrics; coefficient of variation, skewness, and the 10th and 90th percentiles derived from the shape of the height frequency distribution which, in turn, is directly influenced by vertical structure of the forest. An image textural statistic based on the shortwave infrared (SWIR) band of SPOT 5 was also commonly selected by the models. The SWIR band is sensitive to vegetation and soil moisture content. These models predicted that forest stands with a sparse eucalypt canopy over a moist, dense understorey were susceptible to being colonised by bell miners and hence BMAD.

Modelling Soil Moisture Deficit and Moisture Content of Ground Vegetation: Progress Towards Development of a Fire Weather Index System Appropriate to the UK

Most of the wildfires in upland Britain occur in Spring, with the highest peak in April. However, the highest values of the Met Office Fire Severity Index (MOFSI, based on the Canadian Forest Fire Weather Index System) occur in the height of summer, thus successfully predicting extreme fire weather conditions, but failing to predict when the majority of real fires occur. Here we illustrate this discrepancy with data from the English Peak District, and present an alternative model which calculates a proposed shrub fire index (SFI) and compares it with randomly generated numbers to simulate fire occurrence. The major peaks in the SFI dynamics occur in spring, reflecting the effect of drought stress on shrubs caused by damaged leaf cuticles during winter and the lack of resources to alleviate the damage during the pre-green-up period. The model presented here shows a reasonable performance in reproducing the seasonal distribution of wild fire occurrence, and may therefore prove helpful for future development of a fire prediction system designed specifically for British conditions. An effective wildfire prediction system will have great value for increasing the preparedness of land managers, National Park Authority staff and the Fire and Rescue Services. A weather index that accurately predicts the fuel moisture content of the dominant shrubs will also be valuable to land managers who use prescribed fire for vegetation management.

Upscaling reflectance information of lichens and mosses using a singularity index: a case study of the Hudson Bay Lowlands, Canada

Abstract. Assessing moisture contents of lichens and mosses using ground-based high spectral resolution spectrometers (400–2500 nm) offers immense opportunities for a comprehensive monitoring of peatland moisture status by satellite/airborne imagery. This information may be valuable for present and future carbon balance modeling. Previous studies are based upon point measurements of vegetation moisture content and water table position, and therefore a detailed moisture status of entire northern peatlands is not available. Consequently, upscaling ground and remotely sensed data to the desired spatial resolutions is inevitable. This study continues our previous investigation of the impact of various moisture conditions of common sub-Arctic lichen and moss species (i.e., Cladina stellaris, Cladina rangiferina, Dicranum elongatum, and Tomenthypnum nitens) upon the spectral signatures obtained in the Hudson Bay Lowlands, Canada. Upscaling reflectance measurements of the above species were conducted in the field, and reflectance analysis using a singularity index was made, since this study serves as a basis for future aircraft/satellite research. An attempt to upscale current and new spectral reflectance indices developed in our previous studies was made as well. Our findings indicate that the spectral index C. rangiferina is to a lesser amount influenced by scale since it has a small R2 values between the log of the index and the log of the resolution, reduced slopes between the log of the index and the log of the resolution, and similar slopes between log reflectance and log resolution (α) of two wavelengths employed by the index. Future study should focus on concurrent monitoring of moisture variations in lichens and mosses both in situ and from satellite and airborne images, as well as analysis of fractal models in relations to the upscaling experiments.

Spatial Variation of Vegetation Moisture Mapping Using Advanced Spaceborne Thermal Emission & Reflection Radiometer (ASTER) Data

Drought is a recurrent phenomenon in Jharkhand. It affects the livelihoods of the majority of its people, particularly tribals and dalits living in rural areas. Twelve of the 24 districts of the state, covering 43% of the total land area, are covered under the Drought Prone Areas Programme (DPAP). Hunger and starvation deaths are reported almost every year. Vegetation moisture content is one of the key parameters in drought monitoring, agricultural modelling and forest health mapping. In this paper the three different approaches is described using Advanced Spaceborne Thermal Emission & Reflection Radiometer (ASTER) data for measuring the vegetation moisture content in a part of Palamu Commissionaire of Jharkhand state, which is prone to severe drought. ASTER thermal data was used to calculate land surface temperature using Normalized Differential Vegetation Index (NDVI) emissivity correction method. Reflective bands are used to determine NDVI, Modified Soil Adjustment Vegetation Index (MSAVI) & Normalised Differential Water Index (NDWI). The three different vegetation moisture estimation methods namely MSAVI – LST (land surface temperature) feature space identification, NDWI & Vegetation Dryness Index (VDI) is applied to determine the vegetation moisture level. The results of three methods were classified and final moisture content map was produced. The result was validated using rainfall data of study area. This study indicates that by proper pre-processing of ASTER data, it can be used to estimate the land surface temperature and vegetation moisture content and can be used for drought prediction.

Ant species distribution along a topographic gradient in a "terra-firme" forest reserve in Central Amazonia

In Amazonia, topographical variations in soil and forest structure within "terra-firme" ecosystems are important factors correlated with terrestrial invertebrates' distribution. The objective of this work was to assess the effects of soil clay content and slope on ant species distribution over a 25 km² grid covering the natural topographic continuum. Using three complementary sampling methods (sardine baits, pitfall traps and litter samples extracted in Winkler sacks), 300 subsamples of each method were taken in 30 plots distributed over a wet tropical forest in the Ducke Reserve (Manaus, AM, Brazil). An amount of 26,814 individuals from 11 subfamilies, 54 genera, 85 species and 152 morphospecies was recorded (Pheidole represented 37% of all morphospecies). The genus Eurhopalothrix was registered for the first time for the reserve. Species number was not correlated with slope or clay content, except for the species sampled from litter. However, the Principal Coordinate Analysis indicated that the main pattern of species composition from pitfall and litter samples was related to clay content. Almost half of the species were found only in valleys or only on plateaus, which suggests that most of them are habitat specialists. In Central Amazonia, soil texture is usually correlated with vegetation structure and moisture content, creating different microhabitats, which probably account for the observed differences in ant community structure.

An analysis of spatiotemporal variations of soil and vegetation moisture from a 29‐year satellite‐derived data set over mainland Australia

The spatiotemporal behavior of soil and vegetation moisture over mainland Australia was analyzed using passive microwave observations by four satellites going back to late 1978. Differences in measurement specifications prevented merging the data directly. A continuous product was developed for Australia by scaling percentiles of the cumulative moisture distribution within each grid cell to the percentiles of a reference sensor. The coefficient of correlation and root‐mean‐square error between rescaled values and the reference generally suggest good agreement. Using the merged data product, a strong El Niño–Southern Oscillation signal in near‐surface hydrology across Australia was confirmed. Spatial patterns of trends in annual averages show that western and northwestern Australia have experienced an increase in vegetation moisture content, while the east and southeast experienced a decrease. Soil moisture showed a similar spatial pattern but with larger regions experiencing a decrease. This could be explained by decreasing rainfall and increasing potential evapotranspiration during the extended winter period (May–September). The results give us reasonable confidence in the time series of soil and vegetation moisture derived by the scaling method developed in this study. Development of a global data set along these lines should enable better estimation of hydrological variables and should increase understanding of the impacts of ocean circulations on terrestrial hydrology and vegetation dynamics.

Empirical modelling of surface fire behaviour in maritime pine stands

An experimental burning program took place in maritime pine (Pinus pinaster Ait.) stands in Portugal to increase the understanding of surface fire behaviour under mild weather. The spread rate and flame geometry of the forward and backward sections of a line-ignited fire front were measured in 94 plots 10–15 m wide. Measured head fire rate of spread, flame length and Byram’s fire intensity varied respectively in the intervals of 0.3–13.9 m min–1, 0.1–4.2 m and 30–3527 kW m–1. Fire behaviour was modelled through an empirical approach. Rate of forward fire spread was described as a function of surface wind speed, terrain slope, moisture content of fine dead surface fuel, and fuel height, while back fire spread rate was correlated with fuel moisture content and cover of understorey vegetation. Flame dimensions were related to Byram’s fire intensity but relationships with rate of spread and fine dead surface fuel load and moisture are preferred, particularly for the head fire. The equations are expected to be more reliable when wind speed and slope are less than 8 km h–1 and 15°, and when fuel moisture content is higher than 12%. The results offer a quantitative basis for prescribed fire management.

TRMM‐TMI satellite observed soil moisture and vegetation density (1998–2005) show strong connection with El Niño in eastern Australia

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMM/TMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1‐cm of soil (θ) and vegetation moisture content (via optical depth τ). The dominant temporal θ and τ patterns were strongly correlated to the El Niño Southern Oscillation Index (SOI) in spring (r2 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring θ and τ. Correlation analysis suggested that the regions most affected by El Niño are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 and clearly expressed in these satellite observations have a strong connection with El Niño.

Landscapes as gradients: The spatial structure of terrestrial ecosystem components in southern Ontario, Canada

The conventional view of the environment – consisting of discrete patches that repeat themselves across the landscape – has seldom been tested. Across a wide spatial scope in southern Ontario, Canada, we investigated the spatial structure of physical and biological features of the environment: vegetation communities, moisture, pH, and organic content of soil at local scales (10–1250 m), and mammalian communities, mean annual temperature and precipitation at regional scales (10–650 km). Spatial structure was quantified using log–log regression of variance ( V) with distance ( D), according to the power formula, V = aD z . All these ecosystem components exhibited gradients. Slopes ( z) of log–log regressions were positive (0.065 < z < 0.703) and were significantly steeper at the regional scale than the local scale. Variance appeared to increase without bound as distance between sampling locations increased. The results support the view of landscapes as continua and gradients. These patterns represent a challenge to the conventional view of how the natural environment is organised.

Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level

Fire danger models identify fuel moisture content (FMC) of live vegetation as a critical variable, since it affects fire ignition and propagation. FMC can be calculated by dividing equivalent water thickness (EWT) by dry matter content (DM). The optical properties spectra (PROSPECT) model was inverted to estimate EWT and DM separately using the Leaf Optical Properties Experiment (LOPEX) database, based on 490 measurements of leaf optical and biochemical properties. DM estimations were poor when leaf samples were fresh (r/sup 2/ = 0.38). Results of a sensitivity analysis conducted on the spectral response of samples demonstrated that water absorption masks the effects of DM on the spectral response. This causes a poor estimation of FMC (r/sup 2/ = 0.33), even though EWT estimation was good (r/sup 2/ = 0.94). However, DM of dry samples was accurately estimated (r/sup 2/ = 0.84), since no water was present. FMC estimation in fresh leaf material improved considerably (r/sup 2/ = 0.89) by accounting for DM in fresh samples (r/sup 2/ = 0.71), when a constant species-dependent DM value is used. A similar approach was taken on a canopy level by linking the PROSPECT leaf model with the Lillesaeter infinitive reflectance canopy model using data from laboratory measurements under controlled conditions. As expected, results indicate grater difficulty to estimate DM and FMC on a canopy level, although similar trends were observed. DM estimation improved from r/sup 2/ = 0.12 to r/sup 2/ = 0.39 when considering measurements of dry samples, which when used for FMC estimation, correlations increase from r/sup 2/ = 0.62 to r/sup 2/ = 0.81. Therefore, DM can be accurately estimated only when plant material is dry, and it is a necessary measurement in order to estimate FMC accurately. DM remains stable over annual time periods although lower values are expected during the drought season. However, time variations in DM are smaller than DM variations among species. Because there is also a decrease in water content with low EWT values during phenologically dormant periods, multitemporal data could be used to estimate FMC. Further research must be applied on real canopies to confirm these results.

The relation between Normalized Difference Vegetation Index and vegetation moisture content at three grassland locations in Victoria, Australia

The supposition that, for most practical purposes, a single, generic, widely applicable relation exists between Normalized Difference Vegetation Index (NDVI) and grassland vegetation moisture content is tested. An experiment is described in which the vegetation moisture content at three Victorian grassland sites of varying composition is measured over the course of a complete curing episode. For each site, corresponding satellite radiation measurements are used to extract surface reflectances corrected for atmospheric and view-angle effects, and NDVI values based on these. On relating NDVI so obtained to the field measurements of vegetation moisture expressed in terms of a parameter commonly employed in assessing grassland fire risk, namely Fuel Moisture Content (FMC), separate relations for each site are clearly identified. When the relation appropriate to each site is used to derive FMC for that site, accurate estimates are obtained. Accuracy decreases markedly if the relation appropriate to one site is used to derive estimates of FMC at the other sites. When FMC values are transformed to another commonly employed parameter of grassland vegetation moisture content, namely Grassland Curing Index (GCI), the loss of accuracy becomes much greater. More accurate estimates of GCI are obtained using a direct relation between NDVI and GCI.

Foliar moisture content of Pacific Northwest vegetation and its relation to wildland fire behavior

Foliar moisture was monitored for five conifers and associated understory vegetation in Pacific Northwest forests. Decline in foliar moisture of new foliage occurred over the dry season, while less variation was evident in older foliage. Late season foliar moisture ranged from 130 to 170%. In riparian–upland comparisons, largest differences were found for understory vegetation, with less variation evident for overstory trees. Minimum foliar moisture values of 100–120% are appropriate to use in crown fire risk assessment for the Pacific Northwest.

Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications

The Global Vegetation Moisture Index (GVMI) was developed to retrieve vegetation water content from local to global scale rapidly and reliably using SPOT-VEGETATION data. This paper validates the GVMI with field measurements of vegetation water content measured over four different ecosystems in Senegal. Two of the sites show exact concordance between GVMI-derived and field-measured water content. The remaining two sites show differences in value but provide identical evolution over time. Comparison between ecosystems illustrates that GVMI-derived water content is consistent with field measurements of water content expressed as a quantity of water per unit area. Additional study shows that GVMI is not related to the vegetation moisture content expressed as a percentage of water per quantity of biomass. Comparison between the GVMI and NDVI methods also illustrates that the NDVI provides different information (vegetation greenness), which is not directly related to the quantity of water in the vegetation. Potential applications of the new GVMI are also discussed.

Study on forest fire danger model with remote sensing based on GIS

Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real-time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the cobination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.

DEVELOPMENT AND VALIDATION OF A MICROWAVE RADIOMETER ALGORITHM FOR LAND SURFACE HYDROLOGY

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability Esspecially, soil moisture, surface temperature and vegetation are the key parameters which should be observed in the global scale. In this paper, an algorithm for these land surface hydrological parameters has been developed by introducing two indices, Soil Wetness Index and Polarization Index which are calculated from a microwave radiative-transfer equation. The algorithm was applied to the air-borne and satellite sensors and validated by using the ground data. The estimated soil moisture, surface temperature and water content of vegetation corresponded reasonably to the observed ones.

Seasonality of carbon emissions from biomass burning in a Zambian savanna

Seasonal trends in carbon emissions from savanna fires in Western Province, Zambia, were investigated in the early dry season (early June to early August) 1996. The objective was to determine the effect of fuel moisture content on combustion factors and modified combustion efficiency (the ratio of the molar concentration of CO2released to the molar concentration of CO and CO2). Early dry season biomass burning may emit fewer emission products of complete combustion (CO2) and more products of incomplete combustion (e.g., CO). Thirteen experimental sites were burned between June and August 1996, six in a miombo woodland and seven in a dambo grassland. Fires were lit in each ecosystem as the fuels dried so as to monitor changes in fire behavior as the dry season progressed. Total fuel loading ranged from 1884 kg ha−1to 3314 kg ha−1in the dambo and 8953 kg ha−1to 13233 kg ha−1in the miombo. Moisture content of green grass decreased from 127% to 69% in the dambo and from 119% to 33% in the miombo through the length of the study. Combustion factors (CF, the percentage of fuel consumed) increased from 44% to 98% in the dambo. CF values for the miombo increased from 1% to 47%. Fire line intensity increased from 288 kW m−1to 5271 kW m−1in the dambo and from 25 kW m−1to 5274 kW m−1in the miombo. Results indicate that combustion factors and combustion efficiency values follow seasonal trends correlating to metrics of vegetation moisture content, which may alter the type and quantity of carbon emissions. Incorporation of seasonal dynamics of the fire regime should be included in global estimates of carbon flux in the subtropics and in the amount of products of incomplete combustion per unit area burned.