Variation In Vegetation Density Research Articles

Numerical Simulations of Impact River Morphology Evolution Mechanism Under the Influence of Floodplain Vegetation

Shallow floodplains play a crucial role in river basins by providing essential ecological, hydrological, and geomorphic functions. During floods, intricate hydrodynamic conditions arise as flow exits and re-enters the river channel, interacting with the shallow vegetation. The influence and mechanism of shoal vegetation on channel hydrodynamics, bed topography, and sediment transport remain poorly understood. This study employs numerical simulations to address this gap, focusing on the Xiaolangdi–Taochengpu river section downstream of the Yellow River. Sinusoidal-derived curves are applied to represent the meandering river channel to simulate the river’s evolutionary process at a true scale. The study simulated the conditions of bare and vegetated shallow areas using rigid water-supported vegetation with the same diameter but varying spacing. The riverbed substrate was composed of non-cohesive sand and gravel. The analysis examined alterations in in-channel sediments, bed morphology, and bed heterogeneity in relation to variations in vegetation density. Findings indicated a positive correlation between vegetation density and bed heterogeneity, implying that the ecological complexity of river habitats can be enhanced under natural hydrological conditions in shallow plain vegetation and riparian diffuse flow. Therefore, for biological river restoration, vegetation planting in shallow plain regions can provide greater effectiveness.

The effect of vegetation index on the land surface temperature in South Badung Regency, Bali Province

The land surface temperature (LST) is a crucial component of the earth’s energy balance system. The temperature differences between the earth’s surface and the atmosphere are reflected in LST. Conversion of land, including vegetated land, may result in changes to LST. Using the vegetation index approach—NDVI and EVI—this study seeks to ascertain how variations in vegetation density impact LST. Using Landsat 7 ETM+ satellite imagery from 2003 and Landsat 8 OLI-TIRS from 2015 and 2020, this research combines remote sensing technologies and GIS to get vegetation density and LST values, which were then subjected to field verification and spatiotemporal analysis. According to the study’s findings, variations in vegetation density and soil surface temperature have an inverse or opposing relationship. The study’s findings suggest that variations in vegetation density and soil surface temperature have an opposing or inverse connection. In South Badung Regency, places with low vegetation density vary more in proximity to metropolitan areas, resulting in higher soil surface temperatures. These findings suggest that several additional factors, including population density and size, land use, urban planning, rainfall, and season, influence variations in land surface temperature in South Badung Regency.

Global vegetation, moisture, thermal and climate interactions intensify compound extreme events

Compound extreme events, encompassing drought, vegetation stress, wildfire severity, and heatwave intensity (CDVWHS), pose significant threats to societal, environmental, and health systems. Understanding the intricate relationships governing CDVWHS evolution and their interaction with climate teleconnections is crucial for effective climate adaptation strategies. This study leverages remote sensing, reanalysis data, and climate models to analyze CDVWHS during historical (1982–2014), near-future (2028–2060), and far-future (2068–2100) periods under two Shared Socioeconomic Pathways (SSP; 245 and 585). Our results show that reduced vegetation health, unfavorable temperature conditions, and low moisture conditions have negligible effects on vegetation density. However, they worsen the intensity of heatwaves and increase the risk of wildfires. Wildfires can persist when thermal conditions are poor despite favorable moisture levels. For example, despite adequate moisture availability, we link the 2012 Siberian wildfire in the Ob basin to anomalous negative thermal conditions and concurrent unfavorable thermal-moisture conditions. In contrast, the Amazon experiences extreme and exceptional drought associated with unfavorable moisture conditions in the same year. A comparative analysis of Siberian and North American fires reveals distinct burned area anomalies due to variations in vegetation density and wildfire fuel. The North American fires have lower positive anomalies in burned areas because of negative anomalous vegetation density, which reduced the amount of wildfire fuel. Furthermore, we examine basin-specific variability in climate teleconnections related to compound CDVWHS, revealing the primary modes of variability and evolution of CDVWHS through climate teleconnection patterns. Moreover, a substantial increase in the magnitude of heatwave severity emerges between the near and far future under SSP 585. This study underscores the urgency for targeted actions to enhance ecosystem resilience and safeguard vulnerable communities from CDVWHS impacts. Identifying CDVWHS hotspots and comprehending their complex relationships with environmental factors are essential for developing effective adaptation strategies in a changing climate.

Distinguishing forest types in restored tropical landscapes with UAV-borne LIDAR

Forest landscape restoration is a global priority to mitigate negative effects of climate change, conserve biodiversity, and ensure future sustainability of forests, with international pledges concentrated in tropical forest regions. To hold restoration efforts accountable and monitor their outcomes, traditional strategies for monitoring tree cover increase by field surveys are falling short, because they are labor-intensive and costly. Meanwhile remote sensing approaches have not been able to distinguish different forest types that result from utilizing different restoration approaches (conservation versus production focus). Unoccupied Aerial Vehicles (UAV) with light detection and ranging (LiDAR) sensors can observe forests` vertical and horizontal structural variation, which has the potential to distinguish forest types. In this study, we explored this potential of UAV-borne LiDAR to distinguish forest types in landscapes under restoration in southeastern Brazil by using a supervised classification method. The study area encompassed 150 forest plots with six forest types divided in two forest groups: conservation (remnant forests, natural regrowth, and active restoration plantings) and production (monoculture, mixed, and abandoned plantations) forests. UAV-borne LiDAR data was used to extract several Canopy Height Model (CHM), voxel, and point cloud statistic based metrics at a high resolution for analysis. Using a random forest classification model we could successfully classify conservation and production forests (90% accuracy). Classification of the entire set of six types was less accurate (62%) and the confusion matrix showed a divide between conservation and production types. Understory Leaf Area Index (LAI) and the variation in vegetation density in the upper half of the canopy were the most important classification metrics. In particular, LAI understory showed the most variation, and may help advance ecological understanding in restoration. The difference in classification success underlines the difficulty of distinguishing individual forest types that are very similar in management, regeneration dynamics, and structure. In a restoration context, we showed the ability of UAV-borne LiDAR to identify complex forest structures at a plot scale and identify groups and types widely distributed across different restored landscapes with medium to high accuracy. Future research may explore a fusion of UAV-borne LiDAR with optical sensors, and include successional stages in the analyses to further characterize and distinguish forest types and their contributions to landscape restoration.

Spatial distribution vegetation density, land surface temperature, and land surface moisture of Banda Aceh, Indonesia after 17years of tsunami: a multitemporal analysis approaches.

Although some studies on vegetation cover in relation to the land surface temperature (LST) and land surface moisture (LSM) have been carried out, but not yet been investigated in relation to the pre-disaster and after-tsunami disasters. This paper investigates the spatial extent of vegetation cover density, land surface temperature, and land surface moisture of Banda Aceh from 2000 to 2020 to represent the pre-disaster phase, during the disaster, post-disaster, rehabilitation, and reconstruction stages, and current conditions using remote sensing data. NDVI, LST, and NDMI indexes were utilized, and the mapping process of multitemporal images of Banda Aceh was carried out. The results show that after the tsunami, the distribution of vegetation density varies, tending to decrease for densely vegetated areas before increasing more than 5years later. For medium categories, the vegetation density increased by 22% in 2020 and almost 26% in 2015. Meanwhile, dense vegetation grew by 19% and 13%, respectively, according to data for 2015 and 2020. In a similar outlook, the increasing vegetation density has demonstrated that the LST across Banda Aceh is dominated by 27-30°C, with 2005 data occupying the coldest area. The city's moderate moisture content covered 85.43% of its surface. The low to medium vegetation density, LST, and LSM indexes from 2000 to 2010 is shown by overlaying a combination of three spatial extent indexes. It is shown that Banda Aceh's medium-to-high density, medium LSM, and medium-to-high LST spatially. Banda Aceh's dynamic changes in vegetation, LST, and LSM over the past two decades have been proven in this research; the Banda Aceh's spatial variation in vegetation density, LST, and LSM is influenced by the tsunami.

Machine Learning Regression for RF Path Loss Estimation Over Grass Vegetation in IoWSN Monitoring Infrastructure

This proposal examines the effect of grass vegetation elevation and density on path loss between sensors deployed in an IoT-enabled wireless sensor network (IoWSN) crop monitoring infrastructures. Observations via real-time measurement campaigns at different node heights and vegetation depths revealed that the sensor deployment made using free-space or tree vegetation based path loss model (PLM) experiences network disconnectivity due to variations in vegetation density in a cropping cycle. An empirical PLM is formulated to identify signal strength at different development phases of paddy and sugarcane medium grass vegetation. For this, the 2.4 GHz RF path loss coefficient (PLC) is estimated using data collected through measurement campaign over combinations of sensor height and vegetation density. Further, the formulated PLC is used to train multiple regression model to develop a generic PLM for all medium grass vegetation. Improvements in coverage and connectivity have been validated through proof of concept.

Competing effects of vegetation density on sedimentation in deltaic marshes

Marsh vegetation, a definitive component of delta ecosystems, has a strong effect on sediment retention and land-building, controlling both how much sediment can be delivered to and how much is retained by the marsh. An understanding of how vegetation influences these processes would improve the restoration and management of marshes. We use a random displacement model to simulate sediment transport, deposition, and resuspension within a marsh. As vegetation density increases, velocity declines, which reduces sediment supply to the marsh, but also reduces resuspension, which enhances sediment retention within the marsh. The competing trends of supply and retention produce a nonlinear relationship between sedimentation and vegetation density, such that an intermediate density yields the maximum sedimentation. Two patterns of sedimentation spatial distribution emerge in the simulation, and the exponential distribution only occurs when resuspension is absent. With resuspension, sediment is delivered farther into the marsh and in a uniform distribution. The model was validated with field observations of sedimentation response to seasonal variation in vegetation density observed in a marsh within the Mississippi River Delta.

Effect of varying wheatgrass density on resistance to overland flow

Vegetation cover plays an essential role in control of soil erosion in the Loess Plateau of China. The hydraulic resistance to overland flow under disturbed vegetation is critical in the study of water and soil conservation. A series of experiments on runoff hydraulics was conducted on exposed slopes and surfaces with grass cover. Wheatgrass patches with vegetation density ranging from 0.58% to 5.76% and inflows ranging from 5 to 40 L/min, incorporating slopes ranging from 4° to 12° were used in this study. A total of 264 groups of hydraulic runoff tests were conducted. The test results showed that, with increasing vegetation density, the flow pattern evolved from transient to turbulent flow. Both vegetation density and slope affected the Froude number (Fr). Vegetation density is an essential factor affecting flow resistance. On the premise of variation in vegetation density, the Kendall coefficient of Re and flow resistance exceeded 0.727, and the Spearman correlation coefficient exceeded 0.872. The total resistance of overland flow under vegetation cover can be divided into form resistance and grain resistance. With increased vegetation density, the proportion of form resistance of the total resistance increased from 95% to 99%. Vegetation was the main factor that constitutes flow resistance and controls soil erosion. These results are helpful for understanding the influence of vegetation community distribution on mechanisms of slope runoff and soil erosion.

Numerical study of hydrodynamic and salinity transport processes in the Pink Beach wetlands of the Liao River estuary, China

Abstract. Interaction studies of vegetation within flow environments are essential for the determination of bank protection, morphological characteristics and ecological conditions for wetlands. This paper uses the MIKE 21 hydrodynamic and salinity model to simulate the hydrodynamic characteristics and salinity transport processes in the Pink Beach wetlands of the Liao River estuary. The effect of wetland plants on tidal flow in wetland areas is represented by a varying Manning coefficient in the bottom friction term. Acquisition of the vegetation distribution is based on Landsat TM satellites by remote sensing techniques. Detailed comparisons between field observation and simulated results of water depth, salinity and tidal currents are presented in the vegetated domain of the Pink Beach wetlands. Satisfactory results were obtained from simulations of both flow characteristics and salinity concentration, with or without vegetation. A numerical experiment was conducted based on variations in vegetation density, and compared with the tidal currents in non-vegetated areas; the computed current speed decreased remarkably with an increase in vegetation density. The impact of vegetation on water depth and salinity was simulated, and the findings revealed that wetland vegetation has an insignificant effect on the water depth and salinity in this wetland domain. Several stations (from upstream to downstream) in the Pink Beach wetlands were selected to estimate the longitudinal variation of salinity under different river runoff conditions; the results showed that salinity concentration decreases with an increase in river runoff. This study can consequently help increase the understanding of favourable salinity conditions for particular vegetation growth in the Pink Beach wetlands of the Liao River estuary. The results also provide crucial guidance for related interaction studies of vegetation, flow and salinity in other wetland systems.

Housing Market Activity is Associated with Disparities in Urban and Metropolitan Vegetation

In urban areas, the consistent and positive association between vegetation density and household income has been explained historically by either the capitalization of larger lawns and lower housing densities or landscaping and lifestyle districts that convey prestige. Yet cities with shrinking populations and rising land burdens often exhibit high vegetation density in declining neighborhoods. Because the observed associations do not directly address the causal connection between measures of social privilege and vegetation in urban landscapes, it is difficult to understand the forces that maintain them. Here, we compare patterns of household income with new measures derived from housing market data and other parcel-level sources—sale prices, tax foreclosures, new housing construction, demolitions, and the balance of construction and demolition. Our aim is to evaluate whether these spatially, temporally and semantically finer measures of neighborhood social conditions are better predictors of the distribution of urban vegetation. Furthermore, we examine how these relationships differ at two scales: within the City of Detroit and across the Detroit metropolitan area. We demonstrate, first, that linear relationships between income or home values and urban vegetation, though evident at broad metropolitan scales, do not explain recent variations in vegetation density within the City of Detroit. Second, we find that the real estate and demolition records demonstrate a stronger relationship with changes in vegetation density than corresponding changes in US Census measures like income, which suggests they hold at least as much interest for understanding how the relationships between biophysical changes and neighborhood change processes come about.

Effects of Vertical Variation in Vegetation Density on Wave Attenuation

AbstractA physical model experiment was used to investigate irregular wave attenuation through emergent vegetation with variations in stem heights. The experiment was conducted with six peak periods, six incident wave heights, and two schemes of vegetation. One scheme used uniform vegetation (constant stem height) and the other scheme approximated vegetation with larger biomass near the bottom and decreasing linearly to the surface, consistent with observed biomass patterns in the field. Although distributions were different, the total vertical projected area was kept constant between the two schemes. The cross shore variation of wave heights across the vegetation were measured, and losses due to sidewall and bottom friction effects were measured and removed from the wave attenuation in the vegetated cases to isolate the influence of vegetation. The normalized wave height attenuation for each case was fit to the decay equation to determine the difference of vegetation transmission coefficients Kv and damp...

Differential seed germination responses to the ratio of red to far-red light in temperate and tropical species

Variation in vegetation density creates a range of red to far-red ratios of irradiance (R:FR) potentially permitting fine-scale discrimination of light conditions for seed germination. However, remarkably few studies have explored whether R:FR responses of germination vary among species that differ in distribution and life-history traits. In this study, we explored the relationships between R:FR requirements and four species characteristics: seed mass, latitudinal distribution (tropical vs. temperate), seed dormancy (dormant vs. nondormant), and plant growth form (woody vs. nonwoody). We obtained data on germination response to R:FR of 62 species from published literature and added new data for ten species from aseasonal tropical forests in Borneo. First, we analyzed whether species characteristics influenced overall light dependency of germination using phylo- genetic logistic regression. We found that seed mass had a strong negative effect on light dependency, but that the seed mass at which tropical taxa had a 50 % probability of light dependency was 40 times that of temperate taxa. For light-dependent species, we found that the threshold R:FR that stimulates 50 % of maximum germination (R:FR50) was also related to seed mass and latitudinal distribution. In agreement with an earlier study, we found that for temperate taxa, the R:FR50 was significantly negatively correlated with seed mass. In contrast, for 22 tropical taxa, we found a significant positive correlation. These oppos- ing relationships suggest contrasting selection pres- sures on germination responses of tropical taxa (mostly trees) and temperate herbaceous plants, and which are likely related to differences in seed longev- ity, seed burial rates, and reproductive output.

The effect of plant density on epiphytic macroinvertebrates associated with a submerged macrophyte, Lagarosiphon ilicifolius Obermeyer, in Lake Kariba, Zimbabwe

The effect of variations in the density of a submerged macrophyte, Lagarosiphon ilicifolius, on epiphytic macroinvertebrate community structure in the shallow waters of a sheltered bay of Lake Kariba were investigated. The body size class distributions of a mayfly, Cloeon (Ephemeroptera: Baetidae), and the damselfly family, Coenagrionidae, were also assessed with respect to variation in vegetation density. Macroinvertebrates were sampled from low-, moderate- and high-density beds of L. ilicifolius. There were no significant differences in individual taxon and total macroinvertebrate abundances, macroinvertebrate richness and diversity with respect to vegetation density. In all three density categories the functional feeding group (FFG) composition was dominated by collector-gatherers and collector-filterers. The abundance of the two FFGs did not change significantly within each, as well as among, the three vegetation-density categories (ANOVA, p > 0.05). The largest size class of Cloeon occurred only in high-density beds, whereas the largest coenagrionid individuals were obtained from low- and moderate-density beds and were absent from high-density beds. The results suggest that variation in the density of Lagarosiphon does not affect epiphytic macroinvertebrate community structure, but does affect body-size distributions of macroinvertebrate taxa, probably by affecting predator-prey interactions.

Bird species richness and diversity at montane Important Bird Area (IBA) sites in south-eastern Nigeria

SummaryThe mountains of south-eastern Nigeria are a western extension of the Cameroon mountain range, which is classified as an endemic bird area (EBA). Unlike its eastern extension in Cameroon, most of the ornithological surveys in the western extension of the Cameroon highlands in Nigeria have produced only limited checklists and inventories. There is a clear need for quantitative baseline data so that conservation problems can be identified. Twenty line transects covering a total transect length of 28.8 km were used to survey five sites (Afi Mountain Wildlife Sanctuary, Oban Division and Okwangwo Division of Cross River National Park, Sankwala Mountains and Mbe Mountains) in the westernmost extension of the Cameroon Mountains EBA in south-eastern Nigeria. Vegetation measurements were taken to control for the potential confounding effect of variation in vegetation density and structure on detectability of birds between sites. The 193 bird species recorded in Afi, 158 in Sankwala, 124 in Oban, 100 in Mbe and 73 in Okwangwo Division included most of the Cameroon highlands restricted range species. The results show that the mountains of south-eastern Nigeria are important parts of the Cameroon EBA, particularly Afi Mountain Wildlife Sanctuary. However these sites are threatened by fire and livestock grazing on the hilltops, shifting agriculture on the hillsides and lowlands, and logging for timber in some parts, as well as wildlife hunting for bushmeat.

Assessing the ecological application of lasergrammetric techniques to measure fine-scale vegetation structure

In the study of habitat use by animals, it is important to sample vegetation structure or the degree of cover at different heights or in vegetation strata. Commonly-used techniques to estimate vegetation cover (e.g. point height intercept) are time-consuming and can be especially subjective in tall forest environments. We investigated the application of a Terrestrial Laser Scanner (TLS) to quantify forest structure, in terms of evenness and functional diversity. We also explored the suitability of the developed lasergrammetric technique (LGT) in the monitoring of nest site preferences of translocated populations of New Zealand endemic birds, the South Island saddleback ( Philesturnus carunculatus) and the New Zealand robin ( Petroica australis). At an acquisition rate of up to 6000 points per second and with an estimated error of less than 2 cm, the LGT technique utilises terrestrial scanners that allow collection and processing of field data rapidly and precisely. Further, LGT is able to account for small structural elements such as minor branches, leaves and vine stems. The derived measures (mean height of canopy (MCH), indices of structural evenness ( E var) and functional diversity ( FD var)) can quantified vertical variations in vegetation density but appeared highly dependent on the vertical scale of measurement. When applied to an ecological case study, results suggested that the LGT method provides complementary quantitative estimates to summary methods when assessing vegetation structure for micro-scale studies. However, further validations of the LGT accuracy are needed more specifically in relation to density of obstructing vegetation and when used in the measuring of small vegetative objects and total biomass estimates. The development of new software packages that easily convert large amounts of three-dimensional data collected using laser scanners, into a form ready for biostatistical analysis, also is strongly encouraged.

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR is sensitive to the variation in vegetation density. At the same time SAR is also sensitive to other target properties such as canopy structure, canopy moisture, soil moisture and surface roughness of the underlying soil. However, the sensitivity of SAR backscatter to the vegetation density depends upon the frequency, polarization and angle of incidence at which the SAR is operated. This paper provides comparative evaluation of the sensitivity of multi‐frequency and multi‐polarized SAR backscatter to the plant density of Prosopis juliflora, a thorny plant. Monitoring of P. juliflora is of importance as the state forest department introduced it to arrest the spread of desert. In carrying out this study, data from the SIR‐C/X‐SAR mission over parts of Gujarat, India, have been used. In the present study, the variation of multi‐frequency (L and C) and multi‐polarized (HH, VV and VH) SAR backscatter with plant density has been studied. The results clearly indicate that cross‐polarized SAR backscatter at longer wavelength is the appropriate choice for the quantitative retrieval of plant density.

Evaluation of the snow cover variation in the Canadian Regional Climate Model over eastern Canada using passive microwave satellite data

AbstractSnow cover from a 3 year (1992/93–1994/95) simulation of the Canadian Regional Climate Model (CRCM; operational version 3·5·3) driven by National Centers for Environmental Prediction analysis data over eastern Canada was evaluated using passive‐microwave‐derived snow cover information from the daily Special Sensor Microwave/Imager (SSM/I) data. The presence of snow on the ground was derived from 19 and 37 GHz normalized difference brightness temperature series to which a low‐pass filter was applied to remove day‐to‐day noise, and thresholding was also applied at different levels for taking into account the variation in vegetation density. The thresholds calibrated for four density classes with surface observations show a mean residual underestimation in the SSM/I number of days with snow cover during seasonal transition of −7 days. Compared with the SSM/I‐derived information, the CRCM was found to delay systematically the onset of the snow cover (typically 50 days late) and to ablate snow too quickly during the spring melt period (typically 30 days early). These systematic errors were attributed to the single‐layer force–restore representation of the soil–snow layer and contributed to snow cover extent underestimations in the order of 9% relative to the total area. Copyright © 2004 John Wiley & Sons, Ltd.

Human modification of the landscape and surface climate in the next fifty years

AbstractHuman modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land‐cover changes in response to demographic and economic activity. We use the land‐cover scenario as a surface boundary condition in a biophysically‐based land‐surface model coupled to a general circulation model for a 15‐years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land‐cover change relative to the sensitivity to decadal‐scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982–83) and high (1989–90) years to describe the seasonal phenology of the vegetation.In the past several centuries, large‐scale land‐cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land‐cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land‐cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land‐cover change is generally within the range induced by decadal‐scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics.

衛星データによる日平均気温推定のための基礎的研究 地上で測定した表面温度と日平均気温の関係について

Supplemental analyses using Landsat data were performed to study the possibility of estimating daily mean air temperature using surface temperature derived from satellite IR data. It is recognized that daily mean air temperature can be estimated relatively accurately from surface temperature. Also, studies of the basic relation between daily mean air temperature and surface temperature measured on the ground (over forest and soybean fields) were performed. The results are as follows: (1)When there is comparatively small variation in vegetation density (e.g. forest), the correlation coefficients between daily mean air temperature and the temperature of surfaces receiving sunshine are large. (2)The correlation tends to be better in the morning and evening, and worse at noon. (3)When there is comparatively large variation in vegetation density (e.g. soybean fields), the correlation coefficient between daily mean air temperature and surface temperature for clear days is comparatively large, but the correlations are small for fine days. (4)RMSE over forest or soybean fields for both clear days and fine days are large in spite of a large correlation coefficient. (5)The correlation coefficients and RMSE can be improved by multi-regression analysis between two-hour surface temperature and daily mean air temperature. (6)The mean time at which surface temperature was closest to daily mean air temperature was 8-9 a.m. in the morning and 4-6 p.m. in the evening for May to October over a forest.

Modeling biophysical controls on land surface temperature and reflectance in grasslands

The influence of soil moisture and vegetation density on land surface reflectance and temperature is investigated at a grassland site in northeastern Kansas. To do this, a forward model is developed and validated against measurements from a helicopter mounted multi-spectral sensor. Soil background reflectances are calculated as a function of soil type and moisture content and are incorporated into calculations of surface reflectance using a canopy radiative transfer model. Surface temperature is predicted using a two-layer framework that includes the effects of soil moisture on soil thermal properties. Variation in vegetation density is included in both models via the canopy leaf area index. Results from model simulations show good correlation between normalized values of modeled and observed surface spectral reflectance. Comparison of modeled vs. observed temperature data show that a relatively parsimonious set of variables (net radiation, air temperature, soil thermal properties, and leaf area index) may be used to model land surface temperature with good accuracy. These results support previous empirical and modeling studies suggesting that for land areas characterized by fractional vegetation cover, the slope of the relationship between spatially distributed NDVI and surface temperature measurements is diagnostic of mean soil moisture, while variation around the slope is indicative of local variation in soil moisture.