A.A. Van de Griend

On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces

Abstract The spatial variation of both the thermal emissivity (8–14/mu;m) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-infrared radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0·94. This empirical relationship is of potential use for energy balance studies using thermal infrared remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Retrieving near-surface soil moisture from microwave radiometric observations: current status and future plans

Abstract Surface soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Passive microwave remotely sensed data have great potential for providing estimates of soil moisture with good temporal repetition on a daily basis and on a regional scale (∼10 km). However, the effects of vegetation cover, soil temperature, snow cover, topography, and soil surface roughness also play a significant role in the microwave emission from the surface. Different soil moisture retrieval approaches have been developed to account for the various parameters contributing to the surface microwave emission. Four main types of algorithms can be roughly distinguished depending on the way vegetation and temperature effects are accounted for. These algorithms are based on (i) land cover classification maps, (ii) ancillary remote sensing indexes, and (iii) two-parameter or (iv) three-parameter retrievals (in this case, soil moisture, vegetation optical depth, and effective surface temperature are retrieved simultaneously from the microwave observations). Methods (iii) and (iv) are based on multiconfiguration observations, in terms of frequency, polarization, or view angle. They appear to be very promising as very few ancillary information are required in the retrieval process. This paper reviews these various methods for retrieving surface soil moisture from microwave radiometric systems. The discussion highlights key issues that will have to be addressed in the near future to secure operational use of the proposed retrieval approaches.

Energy, Water and Carbon Exchange in a Boreal Forest Landscape - NOPEX Experiences

The role of the land surface in controlling climate is still underestimated and access to information from the boreal-forest zone is instrumental to improve this situation. This motivated the organ ...

On the Relationship between Thermodynamic Surface Temperatures and High Frequency (37 GHz) Vertical Polarization Brightness Temperatures under Semi-arid Conditions.

A method to estimate surface temperature from high-frequency microwave observations is presented. Microwave brightness temperature is a function of the emissivity and the physical temperature of the emitting layer, and therefore possesses a strong physical basis for the estimation of surface temperature. Field observations have shown that maximum and minimum daily air temperatures are strongly related to daytime (1200h) and night-time (2400h) surface temperature. Field measurements of surface temperature are also compared to METEOSAT thermal observations. Long-term daily maximum and minimum air temperatures are then used to derive datasets of daytime and night-time surface temperatures. The results indicate that 37 GHz vertical polarization brightness temperature provides a reasonable estimate of spatially averaged surface temperature. This approach could provide a useful tool for climate modelling, land surface processes investigations, and other energy balance applications by providing consistent and independent long-term estimates of daily global surface temperature.

Microwave vegetation optical depth and inverse modelling of soil emissivity using Nimbus/SMMR satellite observations

SummaryA radiative transfer model has been used to determine the large scale effective 6.6 GHz and 37 GHz optical depths of the vegetation cover. Knowledge of the vegetation optical depth is important for satellite-based large scale soil moisture monitoring using microwave radiometry. The study is based on actual observed large scale surface soil moisture data and observed dual polarization 6.6 and 37 GHz Nimbus/SMMR brightness temperatures over a 3-year period. The derived optical depths have been compared with microwave polarization differences and polarization ratios in both frequencies and with Normalized Difference Vegetation Index (NDVI) values from NOAA/AVHRR. A synergistic approach to derive surface soil emissivity from satellite observed brightness temperatures by inverse modelling is described. This approach improves the relationship between satellite derived surface emissivity and large scale top soil moisture fromR2=0.45 (no correction for vegetation) toR2=0.72 (after correction for vegetation). This study also confirms the relationship between the microwave-based MPDI and NDVI earlier described and explained in the literature.

Partial area hydrology and remote sensing

Abstract The partial-area concept is one of several basic concepts in modelling hydrologic processes which are related to the fast components of runoff production. However, there are several reasons why this concept has not been applied in practical hydrology. The main reasons are related to the temporal and spatial variability of these contributing areas, which make their identification and characterization extremely difficult. Until now, this identification has only been realized by detailed field surveys, of which the laborous procedures impede a break-through of partial-area hydrology into the practice of hydrologic modelling. Remote sensing has developed into a most promising technique for regional analysis of both small- and large-scale hydrological systems. After a review of the concepts of partial-area hydrology and processes involved, the potentialities of remote sensing for partial-area hydrology are discussed for the various bands of the electromagnetic (E.M.) spectrum. The spatial and temporal aspects of remote sensing form a potential source of new information which has not been used to any degree. It is concluded that optimum use of the remotely sensed data requires a change in hydrological modelling, and appropriate adaption of models.

NOPEX—a northern hemisphere climate processes land surface experiment

The interface between land surfaces and the atmosphere is a key area in climate research, where lack of basic knowledge prevents us from reducing the considerable uncertainties about predicted chan ...

Daily surface moisture model for large area semiarid land application with limited climate data

Abstract Evapotranspiration and surface soil moisture are seldom monitored on a routine basis like other climatic parameters, and consequently must be modelled from whatever data one may have available. A simple daily model is presented, which uses a modified Priestley-Taylor concept, whereby the α term is dynamic, and dependent on the available surface moisture. The relationship between α and the surface moisture is a result of the drying character of the soil, and very much a function of whether the surface is bare or vegetation-covered. Also, the soil heat flux is shown to be an important parameter which should not be neglected, and may also be estimated from the surface moisture.

Determination of microwave vegetation optical depth and single scattering albedo from large scale soil moisture and Nimbus/SMMR satellite observations

Abstract The single scattering albedo and optical depth of typical savanna vegetation in Botswana (Africa) have been determined by inverse modelling using satellite observed microwave signatures and surface soil moisture. Soil emissivity was modelled using a multi-layer radiative transfer model. The study is based on large scale surface moisture data and Nimbus/SMMR 6·6 GHz and 37 GHz dual polarized brightness temperatures over a 3-year period. As compared to the optical depths, the derived single scattering albedos displayed only minor seasonal variations, whereas the values fit well within the range reported in the literature from laboratory and field experiments. Both 6·6 and 37 GHz optical depths were found to be significantly related to NDVI-values derived from NOAA/AVHRR.

Measurement and spatial variation of thermal infrared surface emissivity in a savanna environment

Knowledge of the surface thermal emissivity is necessary for the application of thermal infrared remote sensing, which forms the basis for water and surface energy balance monitoring from space. Thermal emissivity was measured in the wavelength band 8–14 μm for a series of representative surfaces within a natural bush-savanna environment intermixed with cultivated fields in Botswana. The measurements were performed with an emissivity box, which may be constructed with different dimensions to meet the general requirements of the user. The device is well-suited for bare soil, grass, and other types of soil and low-vegetation cover combinations. The measured emissivity varied between 0.914 for bare soil (loamy sand) and 0.986 for a surface completely covered with savanna shrub (Euclea undulata). Calculations are based on the measurements of the radiative surface temperature of three different reflecting configurations of the box. Repetitive estimates of the emissivity were found to be very reproducible for the same surface types and showed the large spatial variability of surface emissivity within the study area. This paper describes the emissivity box together with other versions of the box concept found in the literature, and it describes the operation and calibration procedure as well as the results and consequences of the emissivity measurements for the application of thermal infrared remote sensing.