Optimal management of water and land resources is based on process-based eco-hydrological models (Kutilek and Nielsen, 1994), which have been increasingly used to solve several scientific and practical problems, such as retrieving soil moisture status and water infiltration patterns, assessing vegetation stress and drought conditions, controlling the spray of pesticides, monitoring potential landslides, evaluating post-fire damages and related restoration practices. The reliability of numerical simulations in critical zone (CZ) processes depends on an accurate parameterization of the soil hydrological behavior that is traditionally assessed using direct measurement methods. Nevertheless, for studies devoted to relatively large spatial scales, direct methods are hampered by the time and costs required for field activities and laboratory analyses. To circumvent somehow these limitations, pedotransfer functions (PTFs) were proposed to estimate the soil hydraulic properties. Basically, a PTF exploits the knowledge of readily available or easily measurable basic information on soil physical and chemical properties to infer the soil water retention and hydraulic conductivity functions. In this chapter, the methods for mapping physical, chemical, and other key properties of the soil will be discussed jointly with a presentation of recently developed proxy tools for monitoring soil-vegetation characteristics through unmanned aerial systems (UASs). Multi- or hyper-spectral sensors installed on a UAS enable field-scale spectral measurements to be performed even at centimeter-scale thus allowing the prediction of soil properties at unprecedented grid resolution. Exploiting the high potential offered by UAS-based multi-spectral imaging, a new family of soil transfer functions, here called spectral transfer functions (STFs), is proposed to estimate the soil hydraulic properties from spectral measurements. The input and/or output data of the PTF/STF mandate the use of advanced interpolation techniques to reliably obtain the soil hydraulic behavior in a study area for modeling purposes. Spatial interpolation is an important task for running distributed hydrological models over relatively large areas. Therefore, a key component of this chapter is devoted to the issues of scale, spatial variability, and geostatistical mapping of soil characteristics.

Mapping soil properties for unmanned aerial system-based environmental monitoring.

Romano Nunzio
Primo
Writing – Review & Editing
;
Nasta Paolo
Ultimo
Writing – Review & Editing
2023

Abstract

Optimal management of water and land resources is based on process-based eco-hydrological models (Kutilek and Nielsen, 1994), which have been increasingly used to solve several scientific and practical problems, such as retrieving soil moisture status and water infiltration patterns, assessing vegetation stress and drought conditions, controlling the spray of pesticides, monitoring potential landslides, evaluating post-fire damages and related restoration practices. The reliability of numerical simulations in critical zone (CZ) processes depends on an accurate parameterization of the soil hydrological behavior that is traditionally assessed using direct measurement methods. Nevertheless, for studies devoted to relatively large spatial scales, direct methods are hampered by the time and costs required for field activities and laboratory analyses. To circumvent somehow these limitations, pedotransfer functions (PTFs) were proposed to estimate the soil hydraulic properties. Basically, a PTF exploits the knowledge of readily available or easily measurable basic information on soil physical and chemical properties to infer the soil water retention and hydraulic conductivity functions. In this chapter, the methods for mapping physical, chemical, and other key properties of the soil will be discussed jointly with a presentation of recently developed proxy tools for monitoring soil-vegetation characteristics through unmanned aerial systems (UASs). Multi- or hyper-spectral sensors installed on a UAS enable field-scale spectral measurements to be performed even at centimeter-scale thus allowing the prediction of soil properties at unprecedented grid resolution. Exploiting the high potential offered by UAS-based multi-spectral imaging, a new family of soil transfer functions, here called spectral transfer functions (STFs), is proposed to estimate the soil hydraulic properties from spectral measurements. The input and/or output data of the PTF/STF mandate the use of advanced interpolation techniques to reliably obtain the soil hydraulic behavior in a study area for modeling purposes. Spatial interpolation is an important task for running distributed hydrological models over relatively large areas. Therefore, a key component of this chapter is devoted to the issues of scale, spatial variability, and geostatistical mapping of soil characteristics.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/907619
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact