Microwave Sensors for Soil Moisture Detection: An Application toward Healthy Date Palm

Soil moisture is an important key parameter in the earth ecosystem that has an impact on both landscape and atmospheric conditions. Moreover, sudden changes to soil moisture due to environmental conditions result in degradation to food plants and, thus, may consequently affect food yields. This chapter aims to investigate numerically an application for crops health through soil moisture detection using microwave-based sensors. The numerical studies are carried out using full-wave electromagnetic simulations. More emphasis on the numerical setup of microwave antennas with customized modeled soil layer is presented

Index of Soil Moisture Using Raw Landsat Image Digital Count Data in Texas High Plains

The growth and yield of crops in the arid and semi-arid regions of the world is driven by the amount of soil moisture available to the crop through rainfall and irrigation. Various methods have been developed for quantifying the soil moisture status of agricultural crops. Recent technological advances in remote sensing have shown that soil moisture can be measured with a variety of remote sensing techniques, each with its own strengths and weaknesses. In this study, building on of the strengths of multispectral satellite imagery, a new approach is suggested for estimating soil moisture content. A soil moisture index, the Perpendicular Soil Moisture Index (PSMI), is proposed; it is evaluated using raw image digital count (DC) data in the red, near-infrared, and thermal infrared spectral bands. To test this approach, soil moisture was measured in 18 agricultural fields in the semi-arid Texas High Plains over two years and compared to corresponding PSMI values determined from Landsat image data. These results showed that PSMI was strongly correlated (R2 = 0.79) with observed soil moisture. It was further demonstrated that maps of PSMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region. While further study is needed to determine the exact relationship between PSMI and soil moisture in larger areas with different climates, this study suggests that PSMI is a good indicator of soil moisture and has potential for operationally monitoring soil moisture conditions at the field to regional scales

Põhjapoolkera soode põhjaveetaseme seire täiendamine optiliste ja termiliste satelliidiandmete abil

Väitekirja elektrooniline versioon ei sisalda publikatsiooneSood on märgalad, kuhu taimede mittetäieliku lagunemise tõttu on talletunud palju turvast, , mis sisaldab suurt kogust süsinikku. Turvas on moodustunud aastatuhandete jooksul niisketes tingimustes. Inimtegevuse surve ning globaalne kliima soojenemine on põhjustanud soode kuivenemise ning seetõttu talletunud süsiniku lendumist kasvuhoonegaaside (KHG), peamiselt süsihappegaasina (CO2), mis põhjustab omakorda kliima soojenemist. Ka teised KHG-d, metaan ja naerugaas, lenduvad soodest ja nendegi puhul on olulisimaks teguriks põhjaveetaseme langus. Seetõttu on täpsem teadmine soode põhjaveetaseme muutustest olulise tähtsusega Maa kliima muutumise ennustamisel. Käesolev väitekiri annab ülevaate uuringutest, mille välitööde osa tehti Eestis Endla looduskaitsealal Männikjärve ja Linnusaare rabades, võrdlevad analüüsid aga sarnaste soodega Soomes, Rootsis, Kanadas ja USA-s. Töö peamiseks eesmärgiks oli täiendada Põhjapoolkera soode põhjaveetaseme sattelliidi-põhist kaugseiret, mille alusel hinnati tulemuste olulisust, võrreldes seda soodes tehtud kohapealsete mõõtmistega. Esmakordselt näidati, et kasutatud optiliste ja termiliste spektrite signaalid, mis on turba veesisalduse ja rohelise (kasvuperioodi) taimkatte määramise seisukohast kõige tundlikumad, , iseloomustavad usaldusväärselt soode põhjaveetaset. Täiendava uuringuga taimkatte mõjust seosele leiti vastav niiskusindeks ja selle kõige usaldusväärsemad kohad (pikslid) soodes, mis omakorda võimaldas üldistada tulemust kogu soo ulatuses. Algselt Eesti soodes välja töötatud metoodika õigustas ennast ka teistes soodes nii Euroopas kui ka Põhja-Ameerikas ning seda soovitatakse kasutada edasistes uuringutes.Peatlands are a type of wetlands, which have accumulated huge quantities of carbon as a plant matter. The accumulation of this carbon occurred in water-logged conditions and took thousands of years. Global climate change can lead to the drying of peatlands and, thus, the release of accumulated carbon in the form of greenhouse gas – carbon dioxide (CO2). Releasing CO2 into the atmosphere will amplify global climate change. Therefore, knowledge of water table depth in peatlands is essential for predicting future Earth climate. In this thesis, we present results of our four articles integrated together and they share one general aim – to improve the estimation of water table depth in Northern Hemisphere peatlands using remotely sensed information in thermal and optical spectra. We evaluated the usefulness of this information to detect the temporal and spatial changes in water table depth based on in-situ data collected in peatlands. Particularly, we used signals sensitive to moisture and green vegetation, and utilized them in several indices that indicate soil moisture conditions. In this thesis, we have determined, for the first time, that used in our study moisture index based on optical data has a strong temporal relationship with in-situ measured water table depth in peatlands. Moreover, we discussed the impact of vegetation cover on that relationship and suggested a method for selecting the most informative pixels of moisture index. In conclusion, we suggest the future perspectives of using optical-based moisture index together with challenges it might have.https://www.ester.ee/record=b536954

Surface Soil Moisture Retrievals from Remote Sensing:Current Status, Products & Future Trends

Advances in Earth Observation (EO) technology, particularly over the last two decades, have shown that soil moisture content (SMC) can be measured to some degree or other by all regions of the electromagnetic spectrum, and a variety of techniques have been proposed to facilitate this purpose. In this review we provide a synthesis of the efforts made during the last 20 years or so towards the estimation of surface SMC exploiting EO imagery, with a particular emphasis on retrievals from microwave sensors. Rather than replicating previous overview works, we provide a comprehensive and critical exploration of all the major approaches employed for retrieving SMC in a range of different global ecosystems. In this framework, we consider the newest techniques developed within optical and thermal infrared remote sensing, active and passive microwave domains, as well as assimilation or synergistic approaches. Future trends and prospects of EO for the accurate determination of SMC from space are subject to key challenges, some of which are identified and discussed within. It is evident from this review that there is potential for more accurate estimation of SMC exploiting EO technology, particularly so, by exploring the use of synergistic approaches between a variety of EO instruments. Given the importance of SMC in Earth’s land surface interactions and to a large range of applications, one can appreciate that its accurate estimation is critical in addressing key scientific and practical challenges in today’s world such as food security, sustainable planning and management of water resources. The launch of new, more sophisticated satellites strengthens the development of innovative research approaches and scientific inventions that will result in a range of pioneering and ground-breaking advancements in the retrievals of soil moisture from space

Surface Soil Water Content Estimation from Thermal Remote Sensing based on the Temporal Variation of Land Surface Temperature

Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness Index—TRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges

Surface Soil Water Content Estimation from Thermal Remote Sensing based on the Temporal Variation of Land Surface Temperature

Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness IndexTRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second GenerationSpinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R-2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R-2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges