G. Sepulcre-Cantó

Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery

This paper presents the results of estimation of leaf chlorophyll concentration through model inversion, from hyperspectral imagery of artificially treated orchard crops. The objectives were to examine model inversion robustness under changing viewing conditions, and the potential of multi‐angle hyperspectral data to improve accuracy of chlorophyll estimation. The results were compared with leaf chlorophyll measurements from laboratory analysis and field spectroscopy. Two state‐of‐the‐art canopy models were compared. The first is a turbid medium canopy reflectance model (MCRM) and the second is a 3D model (FLIGHT). Both were linked to the PROSPECT leaf model. A linear regression using a single band was also performed as a reference. The different techniques were able to detect nutrient deficiencies that caused stress from the hyperspectral data obtained from the airborne AHS sensor. However, quantitative chlorophyll retrieval was found largely dependent on viewing conditions for regression and the turbid medium model inversion. In contrast, the 3D model was successful for all observations. It offers a robust technique to extract chlorophyll quantitatively from airborne hyperspectral data. When multi‐angular data were combined, the results for both the turbid medium and 3D model increased. Final RMSE values of 5.8 µg cm−2 (MCRM) and 4.7 µg cm−2 (FLIGHT) were obtained for chlorophyll retrieval on canopy level.

Detecting crop irrigation status in orchard canopies with airborne and ASTER thermal imagery

This work provides a description of the research conducted to assess if ASTER satellite data enable the detection of the water status in orchard tree crops. Summer and winter TERRA-ASTER images were acquired over a study area of Seville in southern Spain over a 6-year period. 1076 olive orchards were monitored in this area, obtaining field location, area, tree density, and irrigation status information. Surface temperature images were obtained using the TES method and 0.5 m resolution panchromatic ortho-rectified imagery collected over the entire area to obtain vegetation cover. A comparison study of the temperature difference between orchards under different irrigation schemes is presented. Results in summer ASTER images showed differences between irrigated and rainfed orchard fields of 2 K, decreasing the differences to 0.5 K in ASTER winter images due to the lack of water stress condition. This methodology could be useful to detect the crop irrigation stratus operationally from ASTER satellite thermal imagery, with potential implications for evapotranspiration studies in non- homogeneous canopies.

Surface temperature in the context of FLuorescence EXplorer (FLEX) mission

It has been demonstrated that the spectrum of fluorescence emission is dependent on leaf temperature, thus there is a need for thermal information in order to interpret fluorescence signals. Temperature is also related to transpiration and stomata closure, which affects CO2 uptake and fluorescence. Therefore temperature measurements help to confirm the trends observed in fluorescence measurements. While fluorescence is immediately and uniquely related to photosynthesis, temperature provides additional information about plant status and instantaneous energy/water fluxes between plants and the atmosphere. The objective of this paper is to demonstrate the role of surface temperature in the context of FLuorescence EXplorer (FLEX) mission. To this end a database of land surface emissivity and temperature obtained from thermal radiometric measurements carried out in the framework of the Sen2FLEX (SENtinel-2 and FLuorescence Experiment) campaign has been used. These data were acquired in the agricultural site of Barrax (Spain) in June and July of 2005 simultaneously with airborne imagery acquired with Airborne Hyperspectral Scanner (AHS) and Compact Airborne Spectrographic Imager (CASI) sensors and data from the airborne fluorescence measuring instrument (AIRFLEX). As a result of these studies we have identified the optimal band configuration for the FLEX mission, that allows the estimation of land surface temperature with an accuracy lower than 1.5 K. To this end single-channel, split-window, and Temperature Emissivity Separation algorithms have been compared using a database of simulated brightness temperatures.

Estimation of evapotranspiration on discontinuous crop canopies using high resolution thermal imagery

Efficient water management in agriculture requires accurate estimation of the evapotranspiration (ET) of crops. This work presents the progress made on assessing the water status and ET estimation on discontinuous crop canopies where soil and shadow components affect the remote sensing imagery used. Two orchards used to conduct regulated deficit irrigation (RDI) experiments were monitored between 2004 and 2006 and at three different levels: i) near-field point thermal sensors monitoring single crowns continuously; ii) airborne level using high-resolution thermal and multispectral imagery collected at different times of day; and iii) satellite level using TERRA-ASTER and Quickbird for estimating surface temperature and multispectral imagery, respectively.

Stress detection in orchards with hyperspectral remote sensing data

A technique is presented for detecting vegetation crop nutrient stress from hyperspectral data. Experiments are conducted on peach trees. It is shown that nutrient deficiencies that caused stress could an be detected reliably on hyperspectral spectra. During an extensive field campaign, foliar and crown reflectance has been measured with a portable field spectroradiometer. Airborne hyperspectral imagery is acquired over the orchard with the AHS hyperspectral sensor. The multi-level approach (leaf level and top of canopy) enabled the assessment of vegetation indices and their relationship with pigment concentration at both leaf and canopy levels, showing the potential and limitations of hyperspectral remote sensing on the different levels. Stress on the peach orchard is was treated with iron chelates to recover from iron chlorosis conditions. Blocks of trees treated with iron chelates created a dynamic range of chlorophyll concentration as measured in leaves. A relationship is obtained between the measured spectra and estimated biochemical parameters via inversion of a linked directional homogeneous canopy reflectance model (ACRM) and the PROSPECT leaf model. Numerical model inversion was conducted by minimizing the difference between the measured reflectance samples and modeled values. An improved optimization method is presented. Results are compared with a simple linear regression analysis, linking chlorophyll to the reflectance measured at the leaf level and Top of Canopy (TOC). Optimal band regions and bandwidths are analyzed.