The development of an object-oriented classification model for operational burned area mapping on the Mediterranean island of Thasos using Landsat TM images

ABSTRACT: Multispectral classification, one of the most commonly used methods for mapping burned areas, is based on the spectral properties of different classes of interest and employs special algorithms designed to perform various types of spectral analysis. However, the use of these classifications has been repeatedly reported to create confusion between burned areas and nonvegetation categories, especially water bodies and shaded areas. As a result of the aforementioned, spectral based classification methods cannot be used operationally for the mapping of burned areas from satellite images. On the other hand, object-oriented image classification, which is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values, shape and texture. Sophisticated classification, incorporating contextual and semantic information, can be performed by utilizing not only image object attributes but also the relationship between networked image objects. In this study the synergy of all these features allowed us to address image analysis tasks that, up till now, have not been possible. The aim of this work was to develop an object-oriented classification model for operational burned area mapping on the Mediterranean island of Thasos using LANDSAT TM images. An objectoriented specified model was used to map burned areas in two different Mediterranean areas after the LANDSAT TM images had been radiometrically, geometrically and topographically corrected. The combination of the object-oriented approach and the multispectral resolution data of LANDSAT TM showed very promising results in burned area mapping and in discriminating between burned and the other classes of confusion

Investigation of aggregation effects in vegetation condition monitoring at a national scale

Abstract Monitoring vegetation condition is an important issue in the Mediterranean region, in terms of both securing food and preventing fires. Vegetation indices (VIs), mathematical transformations of reflectance bands, have played an important role in vegetation monitoring, as they depict the abundance and health of vegetation. Instead of storing raster VI maps, aggregated statistics can be derived and used in long-term monitoring. The aggregation schemes (zonations) used in Greece are the forest service units, the fire service units and the administrative units. The purpose of this work was to explore the effect of the Modifiable Areal Unit Problem (MAUP) in vegetation condition monitoring at the above mentioned aggregation schemes using 16day Normalized Difference Vegetation Index (NDVI) composites acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor. The effects of aggregation in the context of MAUP were examined by analyzing variance, from which the among polygon variation (objects' heterogeneity) and the within polygon variation (pixels' homogeneity) was derived. Significant differences in objects' heterogeneity were observed when aggregating at the three aggregation schemes, therefore there is a MAUP effect in monitoring vegetation condition on a nationwide scale in Greece with NDVI. Monitoring using the fire service units has significantly higher pixels' homogeneity, therefore there is indication that it is the most appropriate for monitoring vegetation condition on a nationwide scale in Greece with NDVI. Results were consistent between the two major types of vegetation, natural and agricultural. According to the statistical validation, conclusions based on the examined years (2003 and 2004) are justified

Accuracy of the Triple Test Versus Colposcopy for the Diagnosis of Premalignant and Malignant Cervical Lesions

Background: Despite the World Health Organization (WHO) recommendations concerning the use of alternative tests for the detection of cervical cancer precursor lesions in low-income countries, the accuracy of these tests is a debated issue. In the present study we compare the diagnostic accuracy of the triple test with that of colposcopy for the diagnosis of premalignant and malignant cervical lesions. Methods: A cross-sectional study was performed in 328 women referred to the gynecology clinic at Shahid Sadoughi Hospital, affiliated to Yazd University of Medical Sciences (SSUMS), Yazd, Iran, from March 2016 to June 2018. As the first step, a Pap smear was obtained from all participants. Visual inspection with acetic acid (VIA) and Lugol�s iodine (VILI) was performed in accordance with the known protocol. A colposcopy was then conducted in all participants, biopsy samples were obtained, and histological features studied. Finally, the results were compared by statistical analysis. Results: The age range of the participants was 30 - 50 years. Of 328 women, 60 (18.3 ) were postmenopausal. Two-hundred and five patients (62.5 ) had an abnormal Pap smear, 165 (50.3 ) had abnormal results on colposcopy, and 141 (43 ) had abnormal histopathology reports. The VIA was positive in 129 patients (39.3 ) and the VILI in 177 (54 ). The results of the triple test were reported to be positive in 205 cases (51.52 ). The sensitivity of the triple test in the detection of premalignant and malignant cervical lesions was 78.7 and 69 , respectively. The sensitivity and specificity of colposcopy in the detection of premalignant and malignant cervical lesions was 80.1 and 72.2 , respectively. The diagnostic accuracy of the triple test and colposcopy in the detection of premalignant and malignant cervical lesions was 73 versus 75 . Conclusion: Since the results of the study showed that the diagnostic accuracy of the triple test is equivalent that of colposcopy, the former may be used in low-income countries and areas lacking access to colposcopy. © 2020. All rights reserved

Influence of the second stage of labor on maternal and neonatal outcomes in vaginal births after caesarean section: a multicenter study in Germany

Background: The American College of Obstetricians and Gynecologists (ACOG) introduced a new standard of care in 2014, extending the duration of the second stage of labor in order to reduce caesarean delivery (CD) rates and its severe complications. The aim of the present study is to evaluate success rates of trial of labor after caesarean section (TOLAC), as well as maternal and neonatal outcomes after the establishment of the recent guidelines. Methods: A retrospective study was performed at two large departments in Germany from January 2008 to January 2018. Patients undergoing TOLAC were divided into two groups. Group I (958 patients) was constituted before the establishment of the current guidelines, and Group II (588 patients) after the establishment of the guidelines. A subgroup analysis was performed to compare neonatal outcomes after successful TOLAC and operative vaginal delivery with those after failed TOLAC and secondary CD. Results: The success rate of vaginal births after cesarean section (VBAC) fell from 66.4 in Group I to 55.8 in Group II (p < 0.001). The median duration of the second stage of labor was statistically significantly longer in Group II than in Group I (79.3 ± 61.9 vs. 69.3 ± 58.2 min) for patients without previous vaginal birth. The incidence of operative vaginal delivery decreased from Group I to Group II (9.6 vs. 6.8). The incidence of third- and fourth-degree perineal lacerations, blood loss and emergency CD were similar in the two groups. Concerning the neonatal outcome, our groups did not differ significantly in regard of rates of umbilical artery cord pH < 7.1 (p = 0.108), the 5-min Apgar scores below 7 (p = 0.224) and intubation (p = 0.547). However, the transfer rates to the neonatal care unit were significantly higher in Group II than in Group I (p < 0.001). Neonatal outcomes did not differ significantly in the subgroup analysis. Conclusion: Extending the second stage of labor does not necessarily result in more vaginal births after TOLAC. Maternal and neonatal outcomes were similar in both groups. Further studies will be needed to evaluate the role of operative vaginal delivery and the duration of the second stage of labor in TOLAC. © 2021, The Author(s)

Earth Observation for Forestry Applications in Cyprus

This paper presents an overview of how space-based and earth observation techniques can be used for forestry applications in Cyprus. Indeed, an example of how the Department of Forests in Cyprus can further promote the importance of using remote sensing techniques in Cyprus. Examples are shown of how mapping of burned areas is performed using remote sensing data (Landsat ETM, Sentinel) as well of how post-fire management is implemented. Examples of the Solea fire event occurred in Cyprus is presented. Finally, remote sensing is also used for risk assessment study for developing fire hazard index. Ground spectro-radiometric measurements are also used in combination with remote sensing imagery and burned severity measures to develop a simple, fast, accurate and reliable methodology for the assessment of the burn severity levels on a forest fire scar in Cyprus forests. The need to develop a national observatory of forests using earth observation and GIS is highlighted

A classification of water erosion models according to their geospatial characteristics

In this article, an extensive inventory in the literature of water erosion modelling from a geospatial point of view is conducted. Concepts of scale, spatiality and complexity are explored and clarified in a theoretical background. Use of Geographic Information Systems (GIS) is pointed out as facilitating data mixing and model rescaling and thus increasing complexity in data-method relations. Spatial scale, temporal scale and spatial methodologies are addressed as the most determining geospatial properties underlying water erosion modelling. Setting these properties as classification criteria, 82 water erosion models are identified and classified into eight categories. As a result, a complete overview of water erosion models becomes available in a single table. The biggest share of the models is found in the category of the mechanistic pathway-type event-based models for watershed to landscape scales. In parallel, geospatial innovations that could be considered as milestones in water erosion modelling are highlighted and discussed. An alphabetical list of all models is also listed in the Appendix. For manipulating scale efficiently, two promising spatial theories are suggested for further exploitation in the future such as hierarchy theory and fractals theory. Regarding erosion applications, uncertainty analysis within GIS is considered to be necessary for further improving performance of erosion models.JRC.H.5-Land Resources Managemen

Monthly soil erosion monitoring based on remotely sensed biophysical parameters: a case study in Strymonas river basin towards a functional pan-European service

Currently, many soil erosion studies at local, regional, national or continental scale use models based on the USLE-family approaches. Applications of these models pay little attention to seasonal changes, despite evidence in the literature which suggests that erosion risk may change rapidly according to intra-annual rainfall figures and vegetation phenology. This paper emphasises the aspect of seasonality in soil erosion mapping by using month-step rainfall erosivity data and biophysical time series data derived from remote-sensing. The latter, together with other existing pan-European geo-databases sets the basis for a functional pan-European service for soil erosion monitoring at a scale of 1:500,000. This potential service has led to the establishment of a new modelling approach (called the G2 model) based on the inheritance of USLE-family models. The G2 model proposes innovative techniques for the estimation of vegetation and protection factors. The model has been applied in a 14,500 km2 study area in SE Europe covering a major part of the basin of the cross-border river, Strymonas. Model results were verified with erosion and sedimentation figures from previous research. The study confirmed that monthly erosion mapping would identify the critical months and would allow erosion figures to be linked to specific land uses.JRC.H.5-Land Resources Managemen

Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

This study investigates the effectiveness of combining multispectral very high resolution (VHR) and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM). The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements

Identifying a suitable combination of classification technique and bandwidth(s) for burned area mapping in tallgrass prairie with MODIS imagery

Prescribed fire is crucial to the ecology and maintenance of tallgrass prairie, and its application affects a variety of human and natural systems. Consequently, maps showing the location and extent of these fires are critical to managing tallgrass prairies in a manner that balances the needs of all stakeholders. Satellite-based optical remote sensing can provide the necessary input for this mapping, but it requires the development mapping methods that are specific to tallgrass prairie. In this research, we devise and test a suitable mapping method by comparing the efficacy of seven combinations of bands and indices from the MODIS sensor using both pixel and object-based classification methods. Due to the relatively small size of many prescribed fires in tallgrass prairie, scenarios based on the 250 m spatial resolution red and NIR bands outperformed those based on the coarser 500 m spatial resolution bands, and a combination of both red and NIR performed better than each 250 m band individually. Object-based classification offered no improvement over the pixel-based classification, and performed poorer in some cases. Our results suggest that mapping burned areas in tallgrass prairie should be done at a minimum of 250 m spatial resolution, should used a pixel-based classification technique, and should use a combination of red and NIR