Albedo

Dobos, Endre

doi:10.1201/noe0849338304.ch15

Cited by 25 publications

(25 citation statements)

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“…One reason for the high performance of the predictive models for clay content and soil salinity is the high correlation between these two soil properties [54,59]. Furthermore, increasing soil salinity causes a strong decrease in soil albedo [26] registered by the sensor, and the high variation in clay content results in differences in the absorbance characteristics and, so, in the albedo [94]. Other factors contributing to the high performance of the models were the negligible influence of moisture content on the image spectra, because the image was selected in the early summer when soil was mostly dried, and a relatively uniform composition of clay minerals in the study area, with the dominance of montmorillonite [95,96], decreasing the influence of clay mineral type on the spectra variability.…”

Section: Modeling Soil Properties Using Mars and Plsr Methodsmentioning

confidence: 99%

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

2015

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Modeling and mapping of soil properties has been identified as key for effective land degradation management and mitigation. The ability to model and map soil properties at sufficient accuracy for a large agriculture area is demonstrated using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Soil samples were collected in the El-Tina Plain, Sinai, Egypt, concurrently with the acquisition of ASTER imagery, and measured for soil electrical conductivity (ECe), clay content and soil organic matter (OM). An ASTER image covering the study area was preprocessed, and two predictive models, multivariate adaptive regression splines (MARS) and the partial least squares regression (PLSR), were constructed based on the ASTER spectra. For all three soil properties, the results of MARS models were better than those of the respective PLSR models, with cross-validation estimated R

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Section: Modeling Soil Properties Using Mars and Plsr Methodsmentioning

confidence: 99%

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

2015

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“…The albedo values in the range of 0.05-0.15 refer to dark-colored, wet rough soils, as well as coniferous forests; 0.15-0.25 represent crops and natural vegetation, including deciduous forests; values between 0.35 and 0.4 relate to lightcolored, dry and smooth surfaces; and the extremely high values of 0.8-0.95 refer to fresh deep snow [3], [4]. On a regional scale, in the mid-latitudes, the albedo of the surface varies substantially between seasons.…”

Section: Introductionmentioning

confidence: 99%

Effects of Soil Surface Irregularities on the Diurnal Variation of Soil Broadband Blue-Sky Albedo

Cierniewski

Karnieli

Kaźmierowski

et al. 2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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This paper quantitatively explores, in terms of roughness indices, the effect of soil surface irregularities on the diurnal variation of the broadband blue-sky albedo of a large range of soil properties. Field studies were carried out on cultivated and uncultivated soil surfaces in Poland and Israel that vary in roughness and brightness. It was found that these irregularities, formed by different agricultural equipment and modified by rain or sprinkler irrigation, can be quantified by two roughness indices. Soil roughness not only affects the overall level of the diurnal variation of the albedo, but also affects the intensity of the diurnal increase from the solar zenith angle (µ ) at the local noon to about 75 80 . The roughness indices are variables that precisely determine only the albedo at the local solar noon of soils with the same color value. If the contents of soil organic carbon (SOC) and calcium carbonate are treated as the dominant variables, combined with one of the indices, these three variables together would significantly describe the albedo at the local solar noon of all soil surfaces. The soils, with their high irregularities, showed almost no rising values of albedo at a µ lower than 75 , while the smooth soil surfaces exhibited a gradual increase of the albedo at these angles. It is concluded that the roughness indices provide sufficient means to accurately describe the diurnal variation of the albedo of a wide range of surfaces, disregarding other soil properties.Index Terms-Diurnal albedo variation, field measurements, soil albedo, soils in Poland and Israel, soil surface roughness.

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“…The soil albedo is determined by particle size, mineral composition, moisture, organic matter content and surface roughness. Dobos (2003) adds that the surface of a subtle object is capable of reflecting greater radiation than a rough surface. Small albedo values in vegetated land cover are also caused by multilevel canopies that can absorb solar radiation at multiple levels of the canopy (Peng et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Land cover changes have been impacted to surface albedo values so that the ability of the earth's surface to absorb, reflect and forward the coming solar radiation also changes. The albedo value is influenced by the type and nature of surface radiation, atmospheric conditions, as well as the physical properties of surfaces such as colour, water content and surface roughness (Dobos, 2003). This results in changes in surface energy balance and heat capacity, thus affecting the spatial distribution of microclimate elements, such as surface temperatures.…”

Section: Introductionmentioning

confidence: 99%

Regional Heat Capacity and Surface Temperature Changes Due to  Oil Palm Plantation Development on 1994-2010 Based on Landsat-5 TM Satellite Data

Risdiyanto¹,

Aryani²,

Sujatnika³

2017

Preprint

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Regional heat capacity change is calculated from the ratio between the addition or subtraction of heat (ΔQ) with the increase or decrease in temperature (ΔT) region. The purpose of this study is to calculate the regional heat capacity change due to the changes of land cover composition with forest, shrubs, oil palm plantation and bare soil using Landsat-5 TM satellite data on 1994, 2000 and 2010. Total area that used on this study is 12971 ha. In 1994-2000, 4 % of forest area and 2% shrubs were increased, followed by additional of biomass forest 4.01 tons/ha and 2.83 tons/ha for shrubs. The increased of forest area and biomass (tons/ha) caused by forest and shrubs growth processing towards climax that added the canopy volume. So that, the regional heat capacity in 1994 amounted 19384 Data observation for 2000-2010 showed that forest area decreased by 66% due to forest's clearing into oil palm plantations (47%), shrubs (8%) and bare soil (11%). But, plant's biomass continue to increased, i.e 1.48 ton/ha for forest, 2.73 tons/ha for shrubs and 4.63 tons/ha for bare soil. Before 2000, there was no land cover by oil palm plantations, so the increasing rate from this land was the biggest than the three other lands, amounting to 122.29 tons/ha. Decreasing in the percentage of forest area does not cause a decrease in the heat capacity of the region. Intensive maintenance on oil plam plantation such as water management, fertilizer and planting space made it biomass productivity and ability to save the heat is greater than the forest. As the result, in 2010 regional heat capacity increased to 22508 MJC o-1 .

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Albedo

Cited by 25 publications

References 0 publications

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Effects of Soil Surface Irregularities on the Diurnal Variation of Soil Broadband Blue-Sky Albedo

Regional Heat Capacity and Surface Temperature Changes Due to  Oil Palm Plantation Development on 1994-2010 Based on Landsat-5 TM Satellite Data

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Albedo

Cited by 25 publications

References 0 publications

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Digital Mapping of Soil Properties Using Multivariate Statistical Analysis and ASTER Data in an Arid Region

Effects of Soil Surface Irregularities on the Diurnal Variation of Soil Broadband Blue-Sky Albedo

Regional Heat Capacity and Surface Temperature Changes Due to&nbsp; Oil Palm Plantation Development on 1994-2010 Based on Landsat-5 TM Satellite Data

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Regional Heat Capacity and Surface Temperature Changes Due to Oil Palm Plantation Development on 1994-2010 Based on Landsat-5 TM Satellite Data