Abstract
Soil moisture (SM) plays a key role in many environmental processes and has a high spatial and temporal variability. Collecting sample SM data through field surveys (e.g., for validation of remote sensing-derived products) can be very expensive and time consuming if a study area is large, and producing accurate SM maps from the sample point data is a difficult task as well. In this study, geospatial processing techniques are used to combine several geo-environmental layers relevant to SM (soil, geology, rainfall, land cover, etc.) into a land unit area (LUA) map, which delineates regions with relatively homogeneous geological/geomorphological, land use/land cover, and climate characteristics. This LUA map is used to guide the collection of sample SM data in the field, and the field data is finally spatially interpolated to create a wall-to-wall map of SM in the study area (Garmsar, Iran). The main goal of this research is to create a SM map in an arid area, using a land unit area (LUA) approach to obtain the most appropriate sample locations for collecting SM field data. Several environmental GIS layers, which have an impact on SM, were combined to generate a LUA map, and then field surveying was done in each class of the LUA map. A SM map was produced based on LUA, remote sensing data indexes, and spatial interpolation of the field survey sample data. The several interpolation methods (inverse distance weighting, kriging, and co-kriging) were evaluated for generating SM maps from the sample data. The produced maps were compared to each other and validated using ground truth data. The results show that the LUA approach is a reasonable method to create the homogenous field to introduce a representative sample for field soil surveying. The geostatistical SM map achieved adequate accuracy; however, trend analysis and distribution of the soil sample point locations within the LUA types should be further investigated to achieve even better results. Co-kriging produced the most accurate SM map of the study area.
Highlights
Soil moisture (SM) has a significant impact on environmental processes and water resource management
Whereas precise field soil sampling is an essential step to obtain accurate SM measurements [15,16,17], geographical information systems (GIS) provides a variety of useful tools for geo-environmental monitoring, mapping and evaluation, and spatial analysis to explore the spatial relationships between physical phenomena such as soil type, geology, and land cover to help the produce land unit area (LUA) maps [18,19,20,21,22]
It was found that the technique to produce the land unit area (LUA) from geospatial databases of environmental parameters was effective for the selection of soil sampling and, for SM mapping
Summary
Soil moisture (SM) has a significant impact on environmental processes and water resource management. Soil sampling design and the locations of samples points are very important, and is one of the other challenges in SM studies For overcoming these two major challenges, geospatial databases in GIS and spatial interpolation techniques are powerful tools. Whereas precise field soil sampling is an essential step to obtain accurate SM measurements [15,16,17], GIS provides a variety of useful tools for geo-environmental monitoring, mapping and evaluation, and spatial analysis to explore the spatial relationships between physical phenomena such as soil type, geology, and land cover to help the produce land unit area (LUA) maps [18,19,20,21,22]. We applied GIS tools for advanced analysis of geospatial data for creating the LUA map as a homogenous field area to guide soil sampling [29,30]. TThhee bbeenneeffiitt ooff tthhee LLUUAA aapppprrooaacchh iiss tthhaatt iitt ccoonnssiiddeerrss mmaannyy ooff tthhee vvaarriiaabblleess wwhhiicchh aaffffeeccttSSMMssppaattiiaallvvaarriiaabbiilliittyy
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