SENSITIVITY OF ASAR AP DATA TO WHEAT CROP PARAMETERS

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1 SENSITIVITY OF ASAR AP DATA TO WHEAT CROP PARAMETERS Francesco Mattia, Laura Dente, Giuseppe Satalino, and Thuy Le Toan Istituto di Studi sui Sistemi Intelligenti per l Automazione, ISSIA-CNR, via Amendola /D, 76 Bari, Italy Centre d Etudes Spatiales de la Biosphere, CNRS-CNES-Univ. P. Sabatier, Toulouse, France ABSTRACT This paper illustrates some results obtained in the frame of an experimental campaign carried out on several wheat fields of the Matera (Italy) site, from February to June. During this period, EN- VISAT ASAR data, at alternating polarization mode and at different incidence angles, were acquired on the area roughly every week. Ground data such as soil moisture content, wheat biomass, LAI etc., were also collected during the wheat growing seasons. The paper focuses on the relationship between HH/VV ASAR backscatter at high incidence angle and wheat fresh biomass as well as LAI. Observations show a strong correlation between HH/VV ASAR backscatter at about and LAI from tillering to heading stage. In addition, the HH/VV-LAI relationship has been found quite robust with respect to inter-field and inter-year variability. Conversely, the HH/VVfresh wheat biomass relationship has been found not reliable over wheat fields with significant presence of weeds. No significant differences in the HH/VV-LAI relationship between wheat and oat crops has been found. These observations indicate that, at least over the same agricultural area, it should be possible to design, implement and assess a retrieval algorithm to estimate LAI of cereal fields from ASAR AP data at high incidence angles. Key words: ASAR alternating polarization; ground data, wheat biomass; leaf area index.. INTRODUCTION Recent experimental studies, which simulated the ENVISAT ASAR system acquisitions (Mattia et al., ; Brown et al., ), have found that the HH/VV backscatter ratio at incidence angle is strongly related to above-ground wheat biomass during the whole crop growing season. For instance, in Figure it is plotted the HH/VV backscatter at and the wheat total fresh biomass, measured during the growing season on one field of the Matera (Italy) site (Mattia et al., ). The wheat phenological stage is also reported. Radar data were acquired by a C-band ground based scatterometer. Additionally, at high incidence angles, the HH/VV backscatter was found almost insensitive to soil moisture changes thus encouraging its use as robust indicator of wheat biomass. The physical phenomenon underlying the sensitivity of HH/VV backscatter to wheat biomass is the differential attenuation of horizontally and vertically polarized electromagnetic waves that propagate through a medium with vertical structure, such as wheat canopy (Picard et al., ; Bracaglia et al., 99). HH/VV (db) at tillering HH/VV, Biomass, stem elongation heading 7 7 ripening,,, Total Fresh Biomass (Kg/m ) Figure. Temporal behavior of HH/VV backscatter at incidence and wheat total fresh biomass measured on Matera site during the campaign. These observations confirm past experimental studies (Le Toan et al., 98) then suggest a great deal of potential of ASAR data to retrieve biophysical parameters over vegetated fields. However, they were still carried out on a limited number of fields and needed to be validated by ASAR data at larger scale. In this context, an experimental study on the Matera site has been started in February. The overall objective of this experiment, is to investigate the new potential of the ASAR system to retrieve bio-physical parameters of agricultural fields. To achieve this objective in situ measurements have been carried out from February to June. During the wheat growing seasons (i.e. from February to June), fresh Proc. of the Envisat & ERS Symposium, Salzburg, Austria 6- September (ESA SP-7, April )

2 biomass, leaf are index (LAI) and canopy structure parameters have been measured roughly every two weeks. While, during the whole campaign period, soil moisture content has been gathered, coinciding with multi-angular ASAR acquisitions, roughly every week. This paper focuses on the relationship between HH/VV ASAR backscatter at approximately incidence angle and wheat fresh biomass as well as LAI. In the next section, the overall experiment is briefly described. Then the ground data as well as the methodology adopted for each measurement are summarized. Subsequently the sensitivity of ASAR data to wheat crop parameters is illustrated. Finally some conclusions and future work are drawn.. MEASUREMENT CAMPAIGN km A B Figure. Map of fields selected over the Matera site. Fields reported in yellow and in green were quantitatively and qualitatively monitored, respectively. Field A and Field B have been selected for the analysis. The experimental site is an area of approximately 9x9 Km located close to Matera, Basilicate region, in the south of Italy. The Province of Matera with its communities extends all the way to the Ionian Sea (Figure ). Its topography is mainly characterized by hills (-6 m high) alternating with relatively flat valleys. The average temperatures range between 6.6 C in January (i.e. the coldest month) and.8 C in July (i.e. the hottest month). The Matera site is a predominantly agricultural area mainly devoted to wheat cultivation. According to the local crop management scheduling, durum wheat (i.e. Triticum durum Desf.) is usually sown between November and the end of December and harvested at mid June. From July to October fields are not cultivated. MATERA Figure. Map of South Italy. Over this area, ten fields, with size ranging between and ha, have been selected. Five of these fields have been quantitatively monitored from February to June. While qualitative information concerning surface status, phenological stage, harvesting date, etc. has been recorded on the remaining five fields. On Figure, the location of the selected fields is reported. In yellow and green are indicated the fields quantitatively and qualitatively monitored, respectively. For the purposes of this paper, it is worth mentioning that over the Matera site, there are two main categories of wheat fields: a) fields on which no fertilization and no herbicide treatments are applied b) fields which undergo fertilization and herbicide treatments Out of the ten fields selected in this study, three fall in the category a) while seven in the category b). For the subsequent analysis, two fields, well representing these two typical categories, have been selected: Field A (category a) and Field B (category b). Their location is reported in Figure. Over a relatively small portion of Field A was also conducted the simulation experiment with ground based scatterometer in (Mattia et al., ). Due to the unusually adverse weather conditions faced in the autumn and to the drought of spring, many wheat fields were sown late and, at the beginning of spring, several of these fields were in so bad conditions that farmers decided to leave them as fallow or re-plough and re-sow them with gram. In our case, out of ten selected fields one was re-sown with gram while two were left as fallow. In, eight fields where sown with wheat, one was fallow and one was sown with oat. The latter (denominated Field C) was quantitatively monitored in order to understand whether the temporal behavior of its HH/VV backscatter ratio is significantly different from that of wheat. In fact, from a structural point of view, oat is similar to wheat, at least until heading. The main differences consist of the fact that oat canopy is higher and denser. Additionally oat is usually sown before wheat and it is harvested when it is still green, i.e. usually in April on the Matera site. Field C was fertilized and treated with herbicide.

3 Table. Number and the status of fields quantitatively monitored in and. Field status wheat oat fallow/gram () - - () - () total 6 (9) () Table. Ground data acquired during the and experiment. Soil measurements grav. and vol. soil moisture cont. m long roughness profiles soil texture Agronomic measurements phenological stage fresh/dry weight of stems/m fresh/dry weight of leaves/m fresh/dry weight of ears/m Leaf area index (LAI) Canopy structure plant density (plants/m ) row spacing stems per plant leaves per stem stem diameter/length leaf length/width/thickness In Table, the number and the status of fields quantitatively monitored in and is summarized. In brackets the number of qualitatively monitored fields is reported too. In particular, Field A was fallow in and it was sown with wheat in. Field B was sown with wheat both in and in. While Field C was sown with wheat in and with oat in... Ground data Table lists the ground data gathered in and. Canopy structure measurements were mainly concentrated in and will not be further described in this paper. Soil roughness profiles were acquired roughly at the beginning of the growing seasons (i.e. in March and December ). A m long needle-like profiler (Figure ) was employed to measure soil roughness along directions parallel and perpendicular with respect to the row directions. Gravimetric and volumetric soil moisture content at -cm depth was measured using Kopechy rings (Figure ). In addition, IMKO TDR Figure. Needle-like profiler employed in the soil roughness measurements. Figure. Example of Kopechy ring collected on the Matera site. probes were used to estimate volumetric soil moisture values at 6cm and, for certain dates, at cm too. Figure 6 compares the temporal behavior of volumetric soil moisture content estimated on Field A in and. In this plot, as in other plots shown later, data acquired in have been included as reference values. As can be seen, soil conditions during spring time were significantly wetter in than in. Additionally, Figure 6 shows that during late spring there was an abrupt and consistent raising of soil moisture content (due to a few days of strong raining) while no abrupt change of soil moisture content was recorded in. Wheat water content was separately measured for stems, leaves and ears by drying the collected samples in an oven at 7 C for 8h. Typically, for each field, wheat samples were collected at four/six different locations, depending on the field size. Figure 7 shows the total fresh biomass estimated on Field A in and and on Field B in and. Since in Field A was fallow no estimate of wheat biomass is available. As can be seen, in average Field B presents higher total fresh biomass than Field A in. However, the significant presence of weeds on Field A (roughly % of wheat plants) implies that the measured wheat biomass is an underestimation of

4 Vol. soil moisture content (%) Field A Field A LAI,,, Field A - Field B Figure 6. Volumetric soil moisture values collected on Field A in and in. Figure 9. LAI values measured on Field A and Field B in. Total fresh biomass (Kg/m ),,, Field A - Field A - Field B - Field B Figure 7. Wheat total fresh biomass collected on Field A, in and, and on Field B, in and. the actual total above ground biomass present on that field. A better indicator of total above ground biomass is represented by LAI. In the Matera campaign, LAI was measured on fields using a portable probe, namely the AccuPAR linear PAR/LAI ceptometer (Figure 8). Figure 9 shows that the LAI values of Field A and Field B are quite similar, from tillering to heading (i.e. about ). This apparent inconsistence, with respect to what shown on Figure 7, can be in effect explained by the significant presence of weeds on Field A while they were almost absent on Field B. It is worth mentioning that wheat s weeds normally have vertical structure too... ASAR data The ASAR images exploited in the study have been obtained in the frame of ENVISAT AO 66. They consist of ten ASA APS P products at HH and VV polarizations. All the images were acquired for descending orbits and incident angle approximately equal to (i.e. swaths I and I6). Table reports dates, orbits and swaths of the acquired ASAR products. ASAR data were calibrated, co-registered and ground-projected using the GAMMA Remote Sensing Research and Consulting AG software package ( Table. ASAR data acquired on the Matera site at high incidence angles from February to June. DATE ORBIT SWATH 7// 8 9// /6/ // // // // 8// 9 6 7// 8 7 /6/ Figure 8. AccuPAR linear PAR/LAI ceptometer employed for LAI measurements. For each field the number of pixels averaged to calculate the σ depend on the swath. In the case of swath I and I6, they ranged between and. Figure shows the overall temporal behavior of HH/VV backscatter at about incidence angle for wheat fields monitored during on the Matera site. The wheat phenological stage is also reported on the plot. During January, fields were almost bare as can be inferred from the negative value of their HH/VV backscatter ratio. As can be seen in Figure, from the end of tillering (i.e. April) to ripening stage (i.e. June), the HH/VV backscatter follows

5 HH/VV at about (db) - - tillering stem elongation heading ripening Figure. Overall temporal behavior of HH/VV backscatter at about incidence for wheat fields on the Matera site during the growing season. the expected behavior of the fresh wheat biomass, at least qualitatively. However, for each date, a significant spread (between. and. db) among the HH/VV backscatter ratio of different fields can be noticed. In the next section, a quantitative analysis of the relationship between HH/VV backscatter at high incidence angles and fresh wheat biomass as well as LAI is carried out.. ANALYSIS In order to better understand how robust is the relationship between HH/VV backscatter and fresh wheat biomass (and/or LAI), with respect to disturbing factors such as variability of soil conditions, of agricultural practice etc., it has been investigated in three cases: on the same field, it has been compared between different growing seasons (i.e. inter-year comparison); on the same year, it has been compared between different wheat fields (i.e. inter-field comparison); on the same year, it has been compared between one wheat and one oat field (i.e. inter-crop comparison) Figure shows the temporal behaviour of HH/VV backscatter (at approximately incidence) and total wheat fresh biomass on Field A in and (in radar data were obtained with the scatterometer). The agreement is quite good also in, notwithstanding that the biomass values are significantly lower than those measured in. This difference is essentially due to different meteorological conditions, which had an impact on soil moisture content (as reported in Figure 6) and to differences in the sowing dates. Whereas, the agricultural practice on field A, in terms of fertilization, herbicide treatment, plant density etc., did not significantly change between and. Figure is similar to Figure, but it refers to Field B. Data acquired in and are displayed. Unfortunately, during the wheat growing season, only two ASAR AP images at high incidence angles and HH and VV polarizations were acquired. Then we can say very little about the comparison reported in Figure. However, it seems there is no clear disagreement between the two years, at least. In summary, according to above observations concerning the inter-year comparison, the relationship between HH/VV and total fresh biomass is likely to remain valid in time, provided no changes in the agricultural practice happened. The next step has been to assess whether or not the relationship between HH/VV and fresh biomass is preserved between different wheat fields. To do so, their values, measured on Field A and Field B in, have been plotted in Figure. In blue are reported data referring to field B while in red those referring to field A. As can be seen, there is a very poor agreement in the case of Field A. In particular HH/VV overestimates its actual wheat biomass. This is not surprising because radar measurements are expected to be sensitive to total above ground biomass and, in the case of Field A, the consistent presence of weeds makes significant the difference between total wheat biomass and total above ground biomass. Since LAI is an estimator of total above ground biomass we should expect a better agreement between radar measurements and LAI. In effect, this is what we observe in Figure, which shows the HH/VV backscatter values on Field A and Field B together with the LAI values measured in. As can be seen, there is quite a good agreement between HH/VV and LAI both on Field A and Field B until heading. After heading the agreement is poor. In order to understand to what extend the relationship HH/VV-LAI is crop-type dependent, its behavior on the field sown with oat in (i.e. Field C) has been studied. It should be stressed that oat canopy structure is extremely similar to wheat, at least until heading. However, over the Matera area oat is sown before than wheat (i.e. typically in mid- October or beginning of November). As a consequence, the oat phenological cycle is anticipated with respect to that of wheat. In addition, oat is harvested shortly after heading (typically in April) much before than wheat. Furthermore, oat fields usually present higher values of LAI than wheat fields. Figure shows the HH/VV backscatter values on Field A and Field C together with the LAI values measured in. As can be seen, there is quite a good agreement between the HH/VV ratio and the LAI of the oat field until heading. After heading the agreement quickly deteriorates. As a final step, the study of the HH/VV-LAI relationship has been extended to all the seven fields quantitatively monitored between and. In Figure 6 the LAI values versus the HH/VV backscatter at approximately are shown. The

6 6 data refer to the phenological period from tillering to heading. A simple power law (i.e. y = ax b ) is used to fit the data. As can be seen, there is very good correlation (R =.8) between measured and predicted LAI. The root mean square error is.. HH/VV (db) at about HH/VV - HH/VV - Biomass - Biomass -,,, Total Fresh Biomass (Kg/m) HH/VV (db) at about,,, -, HH/VV, Field A HH/VV, Field B Biomass, Field A Biomass, Field B -, 8 8,,,,,, Total Fresh biomass (Kg/m ) Figure. Temporal behavior of HH/VV backscatter at about incidence and wheat total fresh biomass measured on Field A and Field B in Figure. Temporal behavior of HH/VV backscatter at about incidence and wheat total fresh biomass measured on Field A in and in. HH/VV (db) at about,,, -, HH/VV, HH/VV, Biomass, Biomass,,,,,,, Total Fresh Biomass (Kg/m ) Figure. Temporal behavior of HH/VV backscatter at about incidence and LAI measured on Field A and Field B in. -, 7 7 Figure. Temporal behavior of HH/VV backscatter at about incidence and wheat total fresh biomass measured on Field B in and in.. DISCUSSION AND CONCLUSIONS In this study, the relationship between the HH/VV ASAR backscatter at high incidence angles and wheat crop parameters, such as fresh biomass and LAI, has been investigated. Data from an experimental campaign carried out over the Matera site from February to June have been analyzed. Observations show a strong correlation between HH/VV ASAR backscatter at and LAI of wheat fields from tillering to heading stage. In addition, the HH/VV-LAI relationship has been found quite robust with respect to inter-field and interyear variability. Conversely, the HH/VV-fresh wheat biomass relationship has been found not reliable over wheat fields with significant presence of weeds (i.e. fields neither fertilized nor treated with the herbicide). No significant differences in the HH/VV-LAI relationship between wheat and oat crops has been found. These observations indicate that, at least over the same agricultural area, it should be possible to design, implement and assess a retrieval algorithm to estimate LAI of cereal fields from ASAR AP data at high incidence angles. Future work will be dedicated to achieve this goal. At the same time it is important to quantify how useful can be this information, for instance, for an early yield prediction of cereal fields. To do so, the assimilation of LAI information retrieved from ASAR data into crop growth models should be pursued (see for instance (Dente et al., )). However, it is also worth mentioning some open problems which may hamper the future exploitation of aforementioned promising results. Firstly, the present analysis was concerned with a relatively small number of fields, which belong to a relatively homogeneous agricultural area. Whether or not the obtained HH/VV-LAI relationship remains valid over cereal fields having significantly different soil surfaces, plant density, etc. is not clear. Secondly, notwithstanding that the physical interpretation of the phenomenon underling the HH/VV-LAI relationship is relatively simple, theoretical modelling of this effect is still lacking (at least to the best of our knowledge). In particular, the role of soil conditions in the HH/VV-LAI relationship at high incidence angles needs to be further investigated through experimental and theoretical work. Finally, it should be

7 7 HH/VV at HH/VV, Field A HH/VV, Field C LAI, Field A LAI, Field C -, 8 8 heading Figure. Temporal behavior of HH/VV backscatter at about incidence and LAI measured on Field A and Field C in., R =.8 6,,,,,, LAI Dente L., Rinaldi M., Mattia F., Satalino G., On the Assimilation of C-band Radar Data into CERES- Wheat model, Proceedings IGARSS, IEEE Symposium, Le Toan T., Lopes A., and Huet M., On the relationships between radar backscattering coefficient and vegetation canopy characteristics, Proceddings IGARSS 8, ESA SP-, 6, 98 Mattia F., Le Toan T., Ghislain P., Posa F., D Alessio A., Notarnicola C., Gatti A.M., Rinaldi M., Satalino G., Pasquariello G., Multitemporal C-Band Radar Measurements on Wheat Fields, IEEE Trans. on Geoscience and Remote Sensing, vol., n. 7, -6, Picard G., Le Toan T., Mattia F., Understanding C- Band Radar Backscatter From Wheat Canopy Using a Multiple-Scattering Coherent Model, IEEE Trans. on Geoscience and Remote Sensing, vol., n. 7, 8-9,, Y =a X b LAI,, HH/VV (db) at about From tillering to heading Figure 6. LAI versus HH/VV backscatter at abaout measured over seven fields monitored on the Matera site during the growing seasons and. mentioned the fact that future ASAR AP acquisitions at high incidence angles will have small priority thus jeopardizing the future use of LAI retrieval algorithms based on the HH/VV feature. ACKNOWLEDGMENTS This work has been partly supported by ESA- ESTEC under contract n. 7//NL/JA and partly by ASI contract ASI/I/R/99/. REFERENCES Bracaglia M., Ferrazzoli P., Guerriero L. A., Fully polarimetric multiple scattering model for crops, REMOTE SENS ENVIRON, vol. n., 7-79, 99 Brown S.C.M., Quegan S., Morrison K., Bennett J.C., and Cookmartin G., High-Resolution Measurements of Scattering in Wheat CanopiesImplications for Crop Parameter Retrieval, IEEE Trans. on Geoscience and Remote Sensing, vol., n. 7, 6-6,