Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions

Indirect optical measurement techniques enable efficient and non-destructive estimation of plant area index (PAI). However, because they cannot distinguish between foliage and other canopy elements, corrections are needed to determine leaf area index (LAI), which is typically the property of interest. In this study, we investigate near-infrared digital hemispherical photography (DHP) as a means of estimating and correcting for woody material. Using data collected at a deciduous broadleaf forest site, we show that near-infrared DHP could successfully estimate effective wood area index (WAIe) and wood area index (WAI) during leaf-on conditions, providing similar mean values (WAIe = 0.88, WAI = 1.53) to those determined from visible DHP during leaf-off conditions (WAIe = 0.87, WAI = 1.38). This information was used to correct estimates of effective PAI (PAIe) and PAI, enabling effective LAI (LAIe) and LAI to be derived with low RMSD (0.33 for LAIe and 0.76 for LAI), NRMSD (12% for LAIe and 19% for LAI), and bias (−0.01 for LAIe and −0.16 for LAI). Not correcting for woody material led to overestimation of LAIe by 31% on average and 46% in the worst observed case, and the degree of overestimation was further enlarged for LAI (42% on average and 61% in the worst observed case). In agreement with previous studies, the effects of clumping and woody area were found to be partly compensatory. On average, PAIe provided a reasonable approximation of LAI without correction, though overestimation of 52% and underestimation of 20% occurred at the lowest and highest LAI values, respectively. Compared to WAIe and WAI measurement using leaf-off visible DHP, near-infrared DHP offers two crucial advantages: i) data collection can be conducted at the same time as leaf-on PAIe and PAI measurements, and ii) it is likely that the approach could provide an indirect WAIe and WAI measurement option for evergreen species

Ancillary Data Uncertainties within the SeaDAS Uncertainty Budget for Ocean Colour Retrievals

Atmospheric corrections introduce uncertainties in bottom-of-atmosphere Ocean Colour (OC) products. In this paper, we analyse the uncertainty budget of the SeaDAS atmospheric correction algorithm. A metrological approach is followed, where each of the error sources are identified in an uncertainty tree diagram and briefly discussed. Atmospheric correction algorithms depend on ancillary variables (such as meteorological properties and column densities of gases), yet the uncertainties in these variables were not studied previously in detail. To analyse these uncertainties for the first time, the spread in the ERA5 ensemble is used as an estimate for the uncertainty in the ancillary data, which is then propagated to uncertainties in remote sensing reflectances using a Monte Carlo approach and the SeaDAS atmospheric correction algorithm. In an example data set, wind speed and relative humidity are found to be the main contributors (among the ancillary parameters) to the remote sensing reflectance uncertainties

WISECARE+:Results of a European study of a nursing intervention for the management of chemotherapy-related symptoms

While the use of chemotherapy has significantly improved survival rates, the symptoms associated with chemotherapy remain a major burden for patients. Preventing or appropriately managing side effects significantly improves patients’ functional status and quality of life, ultimately leading to greater patient acceptance of chemotherapy. However, symptom assessment and management are fraught with difficulties such as poor patient recall, retrospective assessment conducted by clinicians and lack of appropriate, clinically relevant and patient friendly symptom assessment and management tools. Furthermore the differences between clinician and patient perceptions of stresses and distress during chemotherapy are well recognised. This study aimed to evaluate the impact of a nursing intervention incorporating structured symptom assessment and management, facilitated by information technology, on chemotherapy-related symptoms, nausea, vomiting, fatigue and mucositis. This pan-European study, involved 8 clinical sites from Belgium, Denmark, England, Ireland and Scotland. Adults (n ¼ 249)receiving first line chemotherapy for breast, lung, ovarian or colorectal cancer, osteosarcoma, acute myeloid leukaemia (AML), acute lymphoblastic leukaemia (ALL) or lymphoma were recruited to the study. Patients completed daily symptom assessment questionnaires for 14 days following consecutive cycles of chemotherapy. Symptom outcomes were compared before and after the introduction of the intervention with positive impact on patients’ experiences of nausea, vomiting and oral problems. Fatigue was not significantly improved