Comparison Quality of Interpolation Methods to Estimate Spatial Distribution of Soil Moisture Content

2020 ◽  
pp. 1-22
Author(s):  
Tülay Tunçay
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Interpolation Methods

Aboveground Biomass of Reaumuria soongorica Shrub Effect on Soil Moisture and Nutrient Spatial Distribution in Arid and Semi-Arid Region

2013 ◽  
Vol 726-731 ◽  
pp. 3803-3806
Author(s):  
Bing Ru Liu ◽  
Jun Long Yang
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Aboveground Biomass ◽  
Soil Moisture Content ◽  
Plant Biomass ◽  
Soil Layer ◽  
Soil Nutrient ◽  
Desert Plant ◽  
Important Species

In order to revel aboveground biomass of R. soongorica shrub effect on soil moisture and nutrients spatial distribution, and explore mechanism of the changes of soil moisture and nutrients, soil moisture content, pH, soil organic carbon (SOC) and total nitrogen (TN) at three soil layers (0-10cm,10-20cm, and 20-40cm) along five plant biomass gradients of R. soongorica were investigated. The results showed that soil moisture content increased with depth under the same plant biomass, and increased with plant biomass. Soil nutrient properties were evidently influenced with plant biomass, while decreased with depth. SOC and TN were highest in the top soil layer (0-10 cm), but TN of 10-20cm layer has no significant differences (P < 0.05). Moreover, soil nutrient contents were accumulated very slowly. These suggests that the requirement to soil organic matter is not so high and could be adapted well to the desert and barren soil, and the desert plant R. soongorica could be acted as an important species to restore vegetation and ameliorate the eco-environment.

Spatial distribution of soil moisture content within catchments and its modelling on the basis of topographic data

2003 ◽  
Vol 277 (1-2) ◽  
pp. 50-60 ◽  
Author(s):  
A.A. Svetlitchnyi ◽  
S.V. Plotnitskiy ◽  
O.Y. Stepovaya
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Topographic Data

scholarly journals Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 589 ◽  
Author(s):  
Shuai Huang ◽  
Jianli Ding ◽  
Jie Zou ◽  
Bohua Liu ◽  
Junyong Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Vegetation Cover ◽  
Soil Moisture Content ◽  
Surface Soil ◽  
Retrieval Model ◽  
Surface Soil Moisture ◽  
Microwave Scattering ◽  
Sparse Vegetation

Soil moisture is an important aspect of heat transfer process and energy exchange between land-atmosphere systems, and it is a key link to the surface and groundwater circulation and land carbon cycles. In this study, according to the characteristics of the study area, an advanced integral equation model was used for numerical simulation analysis to establish a database of surface microwave scattering characteristics under sparse vegetation cover. Thus, a soil moisture retrieval model suitable for arid area was constructed. The results were as follows: (1) The response of the backscattering coefficient to soil moisture and associated surface roughness is significantly and logarithmically correlated under different incidence angles and polarization modes, and, a database of microwave scattering characteristics of arid soil surface under sparse vegetation cover was established. (2) According to the Sentinel-1 radar system parameters, a model for retrieving spatial distribution information of soil moisture was constructed; the soil moisture content information was extracted, and the results were consistent with the spatial distribution characteristics of soil moisture in the same period in the research area. (3) For the 0–10 cm surface soil moisture, the correlation coefficient between the simulated value and the measured value reached 0.8488, which means that the developed retrieval model has applicability to derive surface soil moisture in the oasis region of arid regions. This study can provide method for real-time and large-scale detection of soil moisture content in arid areas.

scholarly journals Analysis of Spatial Distribution of Soil Moisture Content for Different Soil Layers in Mango Greenhouse

2019 ◽  
Vol 557 ◽  
pp. 012070
Author(s):  
F A Azizan ◽  
F N Mohamad Zalani ◽  
A Nagarajan ◽  
A A Aznan ◽  
R Ruslan
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Layers

scholarly journals Effects of Soil Moisture Content upon the Quality of Tuberous Roots of Sweet Potato

1936 ◽  
Vol 8 (4) ◽  
pp. 439-441
Author(s):  
Katsuhachi NAKAGAWA
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Sweet Potato ◽  
Soil Moisture Content ◽  
Tuberous Roots

Effect of the initial soil moisture content on the spatial distribution of the water retention

2008 ◽  
Vol 41 (10) ◽  
pp. 1098-1106 ◽  
Author(s):  
H. Merdun ◽  
R. Meral ◽  
A. Riza Demirkiran
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Moisture Content ◽  
Water Retention ◽  
Soil Moisture Content ◽  
Initial Soil Moisture ◽  
Initial Soil

Analysis on Soil Moisture Content in the Middle Reaches of the Yellow River

2011 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Run-chun LI ◽  
Xiu-zhi ZHANG ◽  
Li-hua WANG ◽  
Xin-yan LV ◽  
Yuan GAO
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Yellow River ◽  
The Yellow River

Analysis on Grey Correlation Degree of Soil Moisture Content under Different Land Use Types in Wind-Blown Sand Area

2010 ◽  
Vol 26 (6) ◽  
pp. 840-845
Author(s):  
Lin CHEN ◽  
Lei WANG ◽  
Qing-xia ZHANG ◽  
Nai-ping SONG
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Grey Correlation ◽  
Land Use Types ◽  
Correlation Degree ◽  
Grey Correlation Degree

Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Aslanidou ◽  
P. Smiris
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Moisture Distribution ◽  
Taxus Baccata ◽  
Mixed Stands ◽  
Potential Growth ◽  
North East ◽  
Soil Moisture Distribution

This  study deals with the soil moisture distribution and its effect on the  potential growth and    adaptation of the over-story species in north-east Chalkidiki. These  species are: Quercus    dalechampii Ten, Quercus  conferta Kit, Quercus  pubescens Willd, Castanea  sativa Mill, Fagus    moesiaca Maly-Domin and also Taxus baccata L. in mixed stands  with Fagus moesiaca.    Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content  of each sample    was measured in order to determine soil moisture distribution and its  contribution to the growth    of the forest species. The most important results are: i) available water  is influenced by the soil    depth. During the summer, at a soil depth of 10 cm a significant  restriction was observed. ii) the    large duration of the dry period in the deep soil layers has less adverse  effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out    at a soil depth of 40 cm iii) in the beginning of the growing season, the  soil moisture content is    greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew  stands, is 10-15 % in    the Q. pubescens  stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii    stands.

scholarly journals Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rehman S. Eon ◽  
Charles M. Bachmann
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Moisture Content ◽  
Layer Thickness ◽  
Soil Moisture Content ◽  
Hyperspectral Imagery ◽  
Barrier Island ◽  
Water Layer ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

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