Plant growth monitoring and potential drought risk assessment by means of Earth observation data

Richter, K.; Rischbeck, Pablo; Eitzinger, Josef; Schneider, Werner; Suppan, Franz; Weihs, Philipp

doi:10.1080/01431160802036268

Cited by 13 publications

(11 citation statements)

References 36 publications

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“…This leads to the topic of the transferability of model results: PROSAIL has been used in an international context and for many different climate zones, vegetation types, soil characteristics, under various agricultural management conditions and with different ground, airborne, and satellite remote sensor types. To give just an insight into the variety of studies and sites with specific characteristics, the geographic locations of PROSAIL studies were as follows: several studies were carried out in large European agricultural regions, such as the Marchfeld area in Austria [161] or Lower Bavaria in Germany [38,96], characterized by temperate continental climate (Climate classification after Koeppen [162]). The Barrax site in Spain, which is situated in a cold semi-arid climate zone, was probably one of the most exploited test sites worldwide [65,76,87,90,159,[163][164][165].…”

Section: Geographic Locationsmentioning

confidence: 99%

Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

et al. 2018

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Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultural crop monitoring. Evaluation was carried out using a systematic literature review of 281 scientific publications with regard to their (i) spectral exploitation, (ii) vegetation type analyzed, (iii) variables retrieved, and (iv) choice of retrieval methods. From the analysis, current trends were derived, and problems identified and discussed. Our analysis clearly shows that the PROSAIL model is well suited for the analysis of imaging spectrometer data from future satellite missions and that the model should be integrated in appropriate software tools that are being developed in this context for agricultural applications. The review supports the decision of potential users to employ PROSAIL for their specific data analysis and provides guidelines for choosing between the diverse retrieval techniques.

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Section: Geographic Locationsmentioning

confidence: 99%

Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

et al. 2018

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“…In their study, Richter et al (2008a) analysed the change of the spectral signal (from 0.4 to 2.5 µm) of a fluvisol soil with varying volumetric SWC (for details of the experiment, see Richter et al 2008a). We used three bare soil spectra with different levels of SWC from this experiment: soil a with low SWC (θ v = 0.017), soil b with high SWC (θ v = 0.27) and soil ref with medium SWC (θ v = 0.05), representing the reference.…”

Section: Canopy and Soil Reflectance Modellingmentioning

confidence: 98%

“…Atzberger et al 2003, Richter et al 2008a) is introduced into PROSAIL, i.e. multiplied with the soil spectrum.…”

Section: Canopy and Soil Reflectance Modellingmentioning

confidence: 99%

“…Data of a soil reflectance experiment carried out by Richter et al (2008a) in the framework of the Crop Drought Stress Monitoring by Remote Sensing (DROSMON) project of the University of Natural Resources and Life Sciences, Vienna, were used to demonstrate the 'natural behaviour' of the factor. In their study, Richter et al (2008a) analysed the change of the spectral signal (from 0.4 to 2.5 µm) of a fluvisol soil with varying volumetric SWC (for details of the experiment, see Richter et al 2008a).…”

Section: Canopy and Soil Reflectance Modellingmentioning

confidence: 99%

“…The coupled canopy bidirectional reflectance (SAILH) (Verhoef 1984, 1985, Kuusk 1991 and leaf optical properties (PROSPECT) (Jacquemoud and Baret 1990) models ('PROSAIL'), for instance, satisfy this requirement. PROSAIL has been widely used for canopy reflectance modelling and applications, amongst others, by Atzberger (2004), Combal et al (2002), Darvishzadeh et al (2008), Koetz et al (2005), Richter et al (2008aRichter et al ( ,b, 2009) and Weiss et al (2000). The model does not directly calculate the soil reflectance and requires a soil spectrum as input.…”

Section: Introductionmentioning

confidence: 98%

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Evaluation of near-surface soil water status through the inversion of soil–canopy radiative transfer models in the reflective optical domain

Richter

Vuolo²,

D’Urso

et al. 2012

International Journal of Remote Sensing

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Knowledge of the spatial and temporal variability of surface soil water content (SWC) is important to understand the linkage between hydrological, ecological and geological processes in a region. Optical Earth observation (EO) data offer the pos-\ud sibility to retrieve surface soil water information, since an overall decrease of soil reﬂectance corresponds to increasing SWC. Sensitivity analysis of the combined leaf (PROSPECT) and canopy (SAILH) reﬂectance models (PROSAIL) to soil reﬂectance variations was carried out, and remote sensing and ground data from different experimental agricultural sites (ESA Spectra Barrax Campaigns (SPARC) 2004, ESA Airborne SAR and Optic Campaigns (AgriSAR) 2006 and participatory multi-level EO-assisted tools for irrigation water management and agricultural\ud decision-support (PLEIADeS) 2007) were exploited. A simple look-up table (LUT) inversion technique was implemented to estimate canopy and soil variables. High negative relationships (r = − 0.87) between the soil reﬂectance factor of the model\ud and the measured SWC were found for several crop types and different locations exhibiting a low fractional vegetation cover (fCover). Even though quantiﬁcation of SWC is difﬁcult, the method could be useful to obtain relative SWC information,\ud especially before the start and at the beginning of the growing season. Furthermore, the physically based estimation approach offers the possibility of getting information about soil and canopy characteristics concurrently from optical EO data. The methodology presented in this article may also represent a suitable complement in the retrieval of SWC from active microwave

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Early warning systems development for agricultural drought assessment in Nigeria

Adedeji

Olusola

James

et al. 2020

Environ Monit Assess

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Plant growth monitoring and potential drought risk assessment by means of Earth observation data

Cited by 13 publications

References 36 publications

Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

Evaluation of near-surface soil water status through the inversion of soil–canopy radiative transfer models in the reflective optical domain

Early warning systems development for agricultural drought assessment in Nigeria

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