Función de ajuste de la atenuación de una señal de microondas para estimar el contenido de humedad de suelos

p.203-206Se aplicó un modelo de regresión múltiple sobre la base de mediciones de contenido de humedad realizadas a partir de la atenuación de una señal de microondas en suelos de distintas texturas y contenido hídrico. Del análisis de la función de ajuste, surge que los porcentajes de arena y materia orgánica no son factores relevantes. A partir de estas conclusiones se elaboró un diseño experimental factorial con tres factores (humedad, porcentajes de arcilla y limo) y dos niveles. De esta forma se redujo el número de pruebas y se realizó un estudio de las interacciones. Se compararon los resultados de ambos métodos para distintos valores de humedad y textura. Se observó buena correspondencia en el campo del diseño experimental

Savannah land cover characterisation: a quality assessment using Sentinel 1/2, Landsat, PALSAR and PlanetScope

The importance of savannahs worldwide has been widely acknowledged and documented. They are important ecosystems that are found on almost half of the African continent and a fifth of the Earth’s surface. They consist of varying densities of grasses and woody vegetation and,due to their complexity, they have been centre stage for a number of land system science debates, such as, equilibrium dynamics, land degradation and desertification, or their contribution to the global carbon cycle, to name but a few. Their significance is directly linked to the numerous recent efforts to map and monitor their land cover as accurately as possible, most commonly by employing Earth observation technologies. A recent case study by Symeonakis et al. (2018), carried out in a southern African savannah covering an area of ~44,000km2, tested the performance of different combinations of Landsat- and PALSAR-based metrics from the dry and wet seasons. They concluded that the combination of multi-sensor and multi-season data provides the best results when mapping the main land cover types of woody vegetation, grasses, crops and urban/bare. Here, we take this work further by testing the performance of 15 similar models, this time based on a combination of Sentinel-1 and Sentinel-2 metrics from the dry and wet season, using the same study area, training and validation samples (extracted from 0.5 m RGB aerial photography). Our results corroborate the findings of the previous study: the combination of the Sentinel optical and C-band radar data from both seasons yielded the most accurate land cover Random Forests classifications: overall accuracy of 87%, overall k: 0.83. Very high user’s and producer’s accuracies were also found, especially for the woody class (User’s: 93%; Producer’s: 93%), which is of primary concern in these savannah environments, due to its relevance to the land degradation processes that are dominant in the region: bush encroachment, overexploitation for fuelwood and deforestation. Similar to the Landsat/PALSAR study, the models based on SAR data only, were less accurate than the optical models. As anticipated, the L-band PALSAR data used in the previous study performed better in mapping the woody cover than their C-band counterparts, since L-band radiation is able to penetrate through the canopy layer and reach the woody stems and branches more efficiently. However, and interestingly, the Landsat-PALSAR study generally outperformed the Sentinel1/2 study, e.g. reporting the same omission but a 5% lower commission error for the woody class (estimated from the all-parameter model). Additionally, we tested a novel land cover configuration mapping accuracy approach using PlanetScope 3m-pixel data, with the view to assessing the quality of the mapping of landscape configuration (e.g. number of crop paddocks) and not only its composition (e.g. crop vs other cover). For five test areas of 170 km2 each, we performed object-based classifications of the PlanetScope imagery (two images per test area, one from the dry and one from the wet season). The results were less promising than those achieved for land cover composition: as an example, in one of our areas of focus, we determined 30 crop paddocks, 28 of which were of the circular centre pivot type ranging from 0.06 to 0.75 km2. For the same area, we mapped a significantly larger number of paddocks with the Sentinel 2 data, most of which were of the rectangular-shaped type. This discrepancy was attributed to the spectral similarity between the crop and grass land cover types, as well as the averaging effect of the lower spatial resolution of the Sentinel. Our findings, however, suggesting a multi-sensor and multi-seasonal approach, are an important addition to the emerging literature and can be used to guide efforts for achieving a highly accurate savannah land cover characterisation. Future work will investigate the use of the PlanetScope object-based classifications as training of the coarser-resolution models (e.g. Seninel 1- and 2-based metrics), not only for improving the mapping of land cover configuration, but also for mapping fractional cover, e.g. % woody vegetation

Subjective scar assessment scales in orthopaedic surgery and determinants of patient satisfaction: a systematic review.

Introduction: Scar assessment tools can be utilized during the post-operative period to monitor scar progress. The primary aim of this systematic review was to evaluate current subjective scar assessment scales utilized in orthopaedic surgery. The secondary aim of this review was to identify determinants of patients’ satisfaction with their scars and to evaluate current measurement scales. Materials and methods: A systematic PRISMA compliant database search was conducted. Electronic databases, currently registered studies, conference proceedings and the reference lists of included studies were searched. There were no constraints based on language or publication status. A narrative synthesis provided a description and evaluation of scales utilized in orthopaedic surgery. Determinants of patient satisfaction were identified along with the scales used to measure satisfaction. Results: A total of 7066 records were screened in the initial search. Twenty-six articles satisfied the inclusion criteria, assessing 7130 patients. Six validated subjective scar scales were identified in the literature. These were the Vancouver Scar Scale, Patient and Observer Scar Assessment Scale, Manchester Scar Scale, Stony Brook Scar Evaluation Scale, Visual Analogue Scale and the Hollander Wound Evaluation Scale. Studies utilizing these scales to evaluate scars following orthopaedic procedures did so successfully. These were total hip arthroplasty, total knee arthroplasty and limb reconstruction. The scales demonstrated satisfactory validity. Functional outcomes such as restoration of movement ranked among patients’ highest concerns. Scar cosmesis was found to be amongst patients’ lowest priorities. Conclusions: Subjective scar assessment scales identified in the literature were not designed specifically for orthopaedic surgery. However, these were able to appropriately assess scars in the studies identified in this review. Current evidence suggests the effect of scar cosmesis on patient satisfaction with orthopaedic procedures is limited

Outcomes of hip fracture in centenarians : a systematic review and meta-analysis

Purpose: Outcomes of hip fractures in centenarians remain underreported owing to the small number of patients reaching 100 years of age. This review aimed to determine outcomes of hip fracture in centenarians and to identify the most common comorbidities among centenarians with hip fracture to better characterise this population. Methods: Published and unpublished literature databases, conference proceedings and the reference lists of included studies were searched to the 25th of January 2023. A random-effects meta-analysis was performed. Included studies were appraised using tools respective of study design. Results: Twenty-three studies (6970 centenarians) were included (retrospective period: 1990-2020). The evidence was largely moderate to low in quality. One-year mortality following a hip fracture was 53.8% (95% CI: 47.2% to 60.3%). Pooled complication rate following a hip fracture in centenarians was 50.5% (95% CI: 25.3% to 75.6%). Dementia (26.2%, 95% CI: 15.7% to 38.2%), hypertension (15.6%, 95% CI: 3.4% to 33.1%), and diabetes (5.5%, 95% CI: 1.9% to 10.7%) were the most common comorbidities among centenarians with hip fracture. Conclusion: Hip fractures in centenarians typically involve complex patient presentations with diverse comorbidities. However the current evidence-base is moderate to low in quality. Effective cross- discipline communication and intervention is suggested to promote treatment outcomes

Remote sensing and cropping practices: a review.

For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing), cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry), and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures). We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues.Made available in DSpace on 2018-01-31T23:57:48Z (GMT). No. of bitstreams: 1 2018001.pdf: 2502474 bytes, checksum: 56486e0a772111ad80472dd9f6791d76 (MD5) Previous issue date: 2018-01-24bitstream/item/171936/1/2018-001.pd

Synthetic Aperture Radar (SAR) image processing for operational space-based agriculture mapping

Few countries are using space-based Synthetic Aperture Radar (SAR) to operationally produce national-scale maps of their agricultural landscapes. For the past ten years, Canada has integrated C-band SAR with optical satellite data to map what crops are grown in every field, for the entire country. While the advantages of SAR are well understood, the barriers to its operational use include the lack of familiarity with SAR data by agricultural end-user agencies and the lack of a ‘blueprint’ on how to implement an operational SAR-based mapping system. This research reviewed order of operations for SAR data processing and how order choice affects processing time and classification outcomes. Additionally this research assessed the impact of speckle filtering by testing three filter types (adaptive, multi-temporal and multi-resolution) at varying window sizes for three study sites with different average field sizes. The Touzi multi-resolution filter achieved the highest overall classification accuracies for all three sites with varying window sizes, and with only a small (< 2%) difference in accuracy relative to the Gamma Maximum A Posteriori (MAP) adaptive filter which had similar window sizes across sites. As such, the assessment of order of operations for noise reduction and terrain correction was completed using the Gamma MAP adaptive filter. This research found there was no difference in classification accuracies regardless of whether noise reduction was applied before or after terrain correction. However, implementing the terrain correction as the first operation resulted in a 10 to 50% increase in processing time. This is an important consideration when designing and delivering operational systems, especially for large geographies like Canada where hundreds of SAR images are required. These findings will encourage country-wide, regional and global food monitoring initiatives to consider SAR sensors as an important source of data to operationally map agricultural production

SAR speckle filtering and agriculture field size: Development of sar data processing best practices for the JECAM SAR intercomparison experiment

Utilizing Synthetic Aperture Radar (SAR) sensors for crop inventory and condition monitoring offers many advantages, particularly the ability to collect data under cloudy conditions. The JECAM SAR Inter-Comparison Exper