Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

Abstract

Abstract:A new procedure is proposed for estimating actual basal crop coefficients from vegetation indices (Kcb VI) considering a density coefficient (Kd) and a crop coefficient for bare soil. Kd is computed using the fraction of ground cover by vegetation (fc VI), which is also estimated from vegetation indices derived from remote sensing. A combined approach for estimating actual crop coefficients from vegetation indices (Kc VI) is also proposed by integrating the Kcb VI with the soil evaporation coefficient (Ke) derived from the soil water balance model SIMDualKc. Results for maize, barley and an olive orchard have shown that the approaches for estimating both fc VI and Kcb VI compared well with results obtained using the SIMDualKc model after calibration with ground observation data. For the crops studied, the correlation coefficients relative to comparing the actual Kcb VI and Kc VI with actual Kcb and Kc obtained with SIMDualKc were larger than 0.73 and 0.71, respectively. The corresponding regression coefficients were close to 1.0. The methodology herein presented and discussed allowed for obtaining information for the whole crop season, including periods when vegetation cover is incomplete, as the initial and development stages. Results show that the proposed methods are adequate for supporting irrigation management. OPEN ACCESSRemote Sens. 2015, 7 2374

Assessing Olive Evapotranspiration Partitioning from Soil Water Balance and Radiometric Soil and Canopy Temperatures

“…The data plots visually indicate that the model produces transpiration estimates close to observed data for the calibration year 2013, with no conspicuous patterns of deviations for the validation year 2014. Related goodness of fit and error indicators presented in Table 3 allow one to assume that SIMDualKc model performed well in capturing the characteristics of our intensive olive orchard of incomplete cover (≤300 trees ha −1 ), as it did for a super-intensive orchard (≥1500 trees ha −1 ) in the region, reported in [17,18]. 2014 observed (T sf ) and estimated transpiration data (T SDual ) were compared ( Figure 2) to validate the model.…”

“…, and a total of 500.8 mm for the year (298.6 mm for T SDual ). The SIMDualKc approach to dual K c for olives with incomplete ground cover takes into account the fraction of soil surface wetted by irrigation and exposed to radiation [12,19,46], hence reflected in the values of E sSDual [17,18].…”

Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices

“…In the last decades, spectral reflectance data have increasingly been used in the study of vegetation due to the strong relationship between the spectral properties of vegetation and several biophysical and biochemical attributes of vegetation, e.g., vegetation fraction, leaf pigments content, canopy water content, crop coefficients, and crop evapotranspiration (e.g., [12][13][14][15][16][17]). The corresponding spectral reflectance data are often used in the form of spectral indices, which are mathematical combinations of two or more spectral bands selected to describe the biophysical parameters of interest [18].…”

Remote Sensing for Crop Water Management: from Experiments to User-Driven Services

“…For these reason, some of these approaches have been integrated into a classical soil water balance, like that described in FAO56 [6], demonstrating good performance for the assessment of irrigation water requirements [117,131]. The literature is prolific in soil water balance models, with different degree of realism and complexity, but the approaches based on remote sensing data are generally based on relatively simple models [116] because these approaches have a clear inclination for the operational applications at large scales.…”