Low Sensitivity Areas Research Articles

Targeted Microperimetry Grids for Focal Lesions in Intermediate AMD: PINNACLE Study Report 7.

The purpose of this study was to evaluate the feasibility and utility of optical coherence tomography (OCT)-based, targeted microperimetry grids in assessing focal lesions in intermediate age-related macular degeneration (iAMD). The multicenter, prospective PINNACLE study enrolled 395 patients with iAMD aged 55 to 90 years across 12 international sites. Participants underwent imaging, including OCT and microperimetry, every 4 to 12 months over 3 years. Deep learning algorithms detected focal lesions and changes in OCT images, including drusen regression, EZ/IZ loss with hypertransmission, and subretinal fluid, guiding 5-point microperimetry targeted to lesion locations. Data were analyzed using linear mixed models to estimate differences between retinal sensitivity measured by the 5-point focal grids and sensitivity interpolated from the 24-point standard grids. The final analysis included 93 eyes from 83 patients, assessing 605 of the 5-point targeted grids and standard grids across 235 focal lesions. The Pearson correlation between focally measured sensitivity and interpolated sensitivity was 0.76. However, interpolation from the standard grid could be erroneous, especially in central regions of lesions characterized by EZ/IZ loss with hypertransmission and subretinal fluid. Interpolation errors increased with distance to the nearest measurement point (slope = 2.20 dB per degree, 95% confidence interval [CI] = 1.52 to 2.87). A significant negative relationship was found between interpolation errors and retinal sensitivity, with the highest errors in areas of low sensitivity. Lesion size significantly impacted interpolation errors for EZ/IZ loss with hypertransmission (slope = -19.41 dB/mm², 95% CI = -29.63 to -9.18). Targeted grids improved the detection and understanding of how focal retinal changes affect visual function in patients with iAMD, supporting the development of therapeutic interventions.

Dynamic Spatiotemporal Land Use Evolution in China’s Plateau Lake Basins in Response to Landscape Ecological Sensitivity

Ecological sensitivity measures an ecosystem’s reaction and restoration difficulty to exogenous disturbances. Regional ecological and environmental challenges can be identified using ecological sensitivity evaluation. The regional characteristics and environmental challenges of plateau lakes were quantified to create four assessment indexes: landform, natural conditions, human activities, and ecological security. Eleven ecologically sensitive characteristics were chosen. We evaluated the landscape ecological sensitivity of the Erhai Lake Basin, China, using ArcGIS and the analytical hierarchy process (AHP). The results showed that the Erhai Lake Basin was mostly forest from 1990 to 2020 and that the dynamic land-use attitude increased and then reduced. The cultivated land became mostly woods and grassland. The largest building area was tied to reverting farms to woods and urban construction. The highest weight was from single-factor ecologically sensitive vegetation covering, followed by river systems and roadways, and lowest was from landslides and collapses. The ecologically sensitive areas with more vegetation and a greater distance from roads and woodland are harder to recover from harm. According to the thorough sensitivity analysis, the study region’s high sensitivity area is 1102.36 km2 (26.16%) and the higher sensitivity area is 1177.10 km2 (27.93%). The ecological sensitivity increases from neighborhoods to nature reserves. High-sensitivity areas were in hilly woods and grasslands with few people. The low-sensitivity area was around water and homes. The dynamic stability of the area ecological environment influenced ecological sensitivity. This study aims to provide sustainable land use solutions for the Erhai Lake Basin and a scientific basis for managing and protecting ecologically vulnerable areas.

Identification of ecological functional zoning and its influencing factors in the Sihu Lake Basin, China

Rational delineation of ecological functional areas and clarification of their driving factors are of significance for maintaining regional ecosystem stability. We assessed six ecosystem services of Sihu Lake Basin located in Jianghan Plain using InVEST and RUSLE models and recreational scoring methods. By using K-means clustering, we identified the ecosystem service bundles, and delineated the ecological functional areas in combination with ecological sensitivity and ecosystem service bundles. The dominant driving factors of different ecological functional areas were analyzed by Geodetector. The results showed that the spatial distributions of habitat quality and carbon sequestration services were similar, with high values being mainly concentrated in Changhu Lake Basin and Honghu Lake Basin. However, the spatial distributions of crop production and soil conservation services were different, with high-value areas concentrated in the northwest area with mountains. The high values of water production service were mainly concentrated in the eastern part of Honghu Lake Basin, while the high-value areas of ecological recreation service were mainly concentrated in the northwest area and the southern part of Honghu Lake Basin. The Sihu Lake Basin could be classified into crop production bundle, habitat quality bundle, and urban living bundle according to cluster analysis. The low ecological sensitivity areas accounted for 59.0% of the Sihu Lake Basin. We classified the study area into ecological restoration areas, ecological conservation areas, ecological transition areas, ecological development areas, and comprehensive use areas by combination of ecological sensitivity and ecosystem service bundles. The geodetector results indicated that the driving factors of each ecological function zone were significantly different. The natural factors significantly influenced the ecological restoration zone, while the normalized vegetation index and population density were the main influencing factors in the ecological conservation zone and the ecological development zone, respectively. Land use type was the main influencing factor in the ecological transition zone and the comprehensive use zone. The results could provide important support for coordinated regional social development and environmental protection.

Assessment of the desertification sensitivity of Northwestern El Minya Governorate, Egypt using MEDALUS model

Assessment of the desertification sensitivity of Northwestern El Minya Governorate, Egypt using MEDALUS model

Production of Environmental Sensitivity Maps for Desertification in Southern Marshes of Iraq

The arid and semi-arid regions have faced critical desertification problems in the last decades. This phenomenon is caused either by human actions or natural circumstances. The study aims to identify the sensitive areas of desertification in the marshlands of southern Iraq using the Environmental Sensitivity Areas Index (ESAI) for desertification. The study area is located between longitudes (46.1° to 48.1° E) and latitude (29.55° to 32.55° N), which includes parts of the governorates of Al-Amarah, Al-Basara and Al-Nasiriyah in southern Iraq with an area of about 27,989 km2. Satellite image processing for the Landsat OLI sensor of 2021 was adopted to characterize the general appearance of the interest area. Arc Gis ver.10.7 programs were used to analyze different data and produce the Desertification Sensitivity Index (DSI) and maps for the parameters for evaluating southern marshes’ desertification. Nine parameters are grouped into three orderly indices concerning the behaviour of desertification, and weighting factors are assigned in each index. This study found that the study area highly sensitive to desertification represents (10781.14 km2 of the total area) about 38.52% of the study area. The area sensitive to desertification covers about 38.42%, about 10752.92 km2 of the total area. Areas of low sensitivity to desertification appear throughout the marshes, representing 23.06%, about 6454.67 km2 of the total area. The result shows that the area is suffering from reduced water supplies and the human destruction of natural grazing areas for urban expansion or cultivation of seasonal crops.

Mapping the sensitivity of land degradation in the Ouergha catchment (Morocco) using the MEDALUS approach

Soil degradation is a global phenomenon affecting the productivity of agricultural land. Due to the low vegetation cover and the aggressive climate, Morocco presents a significant case of soil degradation through erosion and desertification. The Ouergha catchment is highly vulnerable to this scourge. The objective of this study was to assess the sensitivity of land to degradation in the Ouergha catchment area. The MEDALUS approach, widely used in the Mediterranean region, was used to assess the sensitivity of soils to degradation/desertification. This approach integrates four indicators that strongly influence this phenomenon (climate, soil, vegetation and human pressure). The results show that more than half of the study area has a medium sensitivity of land to degradation. The critical areas represent 16.2% and correspond to bare land characterized by steep slopes and absence of vegetation. Low sensitivity areas occupy a limited proportion of 21.9% and correspond to wet summits and conserved forest areas. Climate change could lead to a further increase in areas susceptible to degradation.

Evaluation of Geological Disaster Sensitivity in Shuicheng District Based on the WOE-RF Model

To improve the prevention and control of geological disasters in Shuicheng District, 10 environmental factors—slope, slope direction, curvature, NDVI, stratum lithology, distance from fault, distance from river system, annual average rainfall, distance from road and land use—were selected as evaluation indicators by integrating factors such as landform, basic geology, hydrometeorology and engineering activities. Based on the weight of evidence, random forest, support vector machine and BP neural network algorithms were introduced to build WOE-RF, WOE-SVM and WOE-BPNN models. The sensitivity of Shuicheng District to geological disasters was evaluated using the GIS platform, and the region was divided into areas of extremely high, high, medium, low and extremely low sensitivity to geological disasters. By comparing and analyzing the ROC curve and the distribution law of the sensitivity index, the AUC evaluation accuracy of the WOE-RF, WOE-SVM and WOE-BPNN models was 0.836, 0.807 and 0.753, respectively; the WOE-RF model was shown to be the most effective. In the WOE-RF model, the extremely high-, high-, medium-, low- and extremely low-sensitivity areas accounted for 15.9%, 16.9%, 19.3%, 21.0% and 26.9% of the study area, respectively. The extremely high- and high-sensitivity areas are mainly concentrated in areas with large slopes, broken rock masses, river systems and intensive human engineering activity. These research results are consistent with the actual situation and can provide a reference for the prevention and control of geological disasters in this and similar mountainous areas.

Ozone profiles without blind area retrieved from MAX-DOAS measurements and comprehensive validation with multi-platform observations

Tropospheric ozone (O 3 ) profiles, especially within the boundary layer, are essential for studying the vertical, temporal, spatial variations, as well as the formation sensitivity and regional transport of O 3 . However, it is rare to find continuous tropospheric O 3 profiles with high temporal and spatial resolutions without blind areas using current remote sensing technologies, with issues such as low near-surface sensitivity or systematic blind areas from satellite and LiDAR observations, respectively, being encountered. In this study, multi-source data including stratospheric O 3 profiles from external datasets and local monthly dependent a priori profiles were fused in the retrieval algorithm, then vertical O 3 profiles from the near-surface to the free troposphere were retrieved from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. With the aim of deriving a set of best practice recommendations for applying a profile inversion algorithm to long-term observations, we comprehensively investigated the influence of various settings on profile retrieval, with emphasis on the selection of a Fraunhofer reference spectrum and appropriate a priori profiles in the upper troposphere. These recommendations are essential for applying the algorithm to real long-term measurements. In this study, tropospheric O 3 profiles were retrieved for operational MAX-DOAS observations in Beijing, and the results, especially for the boundary layer, were evaluated in detail with respect to well-established independent O 3 datasets, including one-year ozonesonde profiles and tower-based in-situ measurements at different altitudes. A good level of agreement was found for both near-surface and elevated-altitude results, and the MAX-DOAS O 3 profiles were able to reproduce the vertical distributions measured by ozonesonde. However, MAX-DOAS measurements are less sensitive to the upper troposphere and converge to the a priori profile, and the smoothing effect induced by the optimal estimation method makes it difficult to reproduce steep vertical gradients in real atmosphere. • Developing a novel remote sensing algorithm for O 3 profiles without blind area. • Capturing O 3 near-surface and vertical distributions as indicated by validations. • Deriving best practice recommendations for applying inversion algorithm. • Indicating stable algorithm performance between different instruments' measurements.

Study on cooperative constraint zoning of water environment.

This study comprehensively considers two elements of water environmental sensitivity and pressure using the combination of qualitative analysis and quantitative calculation. And it puts forward the water environmental collaborative constraint zoning method and focuses on the construction of the water environmental collaborative constraint zoning evaluation index system using the fuzzy optimization programming model to determine the index weight. This study takes the Liaohe River Basin in Liaoning Province as a study area through two-dimensional quadrant analysis of water environmental sensitivity and pressure; it is divided into four types of areas: high-pressure and high-sensitivity area (HP-HS area), high-pressure and low-sensitivity area (HP-LS area), low-pressure and high-sensitivity area (LP-HS area) and low-pressure and low-sensitivity area (LP-LS area), respectively. The results show that the proportion of HP-HS area is 28.4%, the proportion of HP-LS area is 10.1%, the proportion of LP-HS area is 22.2% and the proportion of LP-LS area is 39.3%, respectively. The evaluation results are in line with the actual situation of the Liaohe River Basin in Liaoning Province. According to the results of different zoning, this research puts forward the optimization and adjustment scheme of industrial layout to achieve the comprehensive and coordinated sustainable development of population, economy, society, and environment in the study area. The research results also have been applied to the formulation of '14th Five-Year Plan' for water ecological environment protection of key river basins in Liaoning Province.

Time-lapse adaptive inversion on resistivity monitoring data with Lp norm regularization and cross-time weight

Time-lapse electrical resistivity tomography (ERT) can describe the dynamic processes occurring underground and has been widely employed in the fields of hydrology, environmental management, and engineering. The time-lapse inversion method is based on the space- and time-dimension regularization technique as it considers complementary information about more than one time interval and reduces the potential causes of the geophysical data inversion of the artifact. However, the L2 norm inversions smear out the models and cannot distinguish between the resistivity interfaces. Moreover, the determination of the two optimal regularization parameters for time-lapse inversion remains challenging, and the fixed-time regularization parameter smooths out the low-sensitivity area and inhibits the real variation on the target body of the deep region. To overcome this problem, we propose a time-lapse ERT inversion method of adaptively imaging the time-lapse model and focusing on the resistivity variation on the time dimension. This method is based on the Lp norm regularization provided by the M-estimator and uses the adaptive regularization parameters based on the model roughness and data misfit. In addition, a cross-time matrix improving the sensitivity in the deep region of model space is added to the time regularization term. We present two synthetic examples and a field dataset to validate the method. Numerical simulation and field dataset inversion results revealed that the proposed time-lapse inversion strategy can avoid the excessive smoothness caused by the low sensitivity in the model deep region and can thus enhance the response from the true ground variation to improve the accuracy of the inversion results. Owing to the adaptive regularization parameters that can preserve the dynamic balance between the objective function components, the inversion iteration progress can remain stable and can maintain the trend toward convergence.

Targeted implementation of cool roofs for equitable urban adaptation to extreme heat

Cities are facing the twin pressures of greenhouse gas driven climatic warming and locally induced urban heating. These pressures are threatening populations that are sensitive to extreme heat due to sociodemographic factors including economic means. Heat-reducing infrastructure adaptation measures such as reflective "cool" materials can reduce urban temperatures. Here we examine the needs-based equity implications associated with heat-reducing cool roofing in Maricopa County, Arizona through application of high-resolution urban-atmospheric simulations. We simulate heatwave conditions and evaluate the air temperature reduction arising from uniform cool roof implementation (i.e., the entire urbanized county), and contrast results against simulated cooling impacts of needs-based targeted cool roof implementation in sociodemographically heat sensitive areas. We find that installing cool roofs uniformly, rather than in a targeted fashion, provides on average 0.66°C reduction in the highest heat sensitivity area and 0.39°C temperature reduction in the lowest heat sensitivity area due in part to a higher roof area density in the heat sensitive area. Targeting cool roof implementation yields 0.45°C cooling in the most sensitive areas compared to 0.22°C cooling in the least sensitive areas, meaning that needs-based targeted cool roofs in high sensitivity areas provide more relief than cool roofs targeted at low sensitivity areas, thus providing more cooling where it is most needed. Needs-based targeted implementation has the dual benefits of concurrently producing more than twice as much cooling and reducing heat exposure for the largest absolute number of individuals in the densely populated, highly heat sensitive areas. Targeting cool roof implementation to high heat sensitivity areas, however, does not achieve thermally equal temperatures in Maricopa County because the high sensitivity areas were substantially warmer than low sensitivity areas prior to implementation. This study illustrates the utility of a new "Targeted Urban Heat Adaptation" (TUHA) framework to assess needs-based equity implications of heat-reducing strategies and underscores its importance by examining the impacts of cooling interventions across sociodemographically heterogeneous urban environments.

NPK in treated wastewater irrigation: Regional scale indices to minimize environmental pollution and optimize crop nutritional supply

Treated wastewater (TWW) is increasingly used for agricultural irrigation, and often contains higher concentrations of the major plant nutrients N, P, and K than freshwater, reducing the need for agricultural fertilization. However, excessive inputs of nutrients to cropping systems can be harmful to crops and the environment. The present study developed and employed six novel indices to assess the sustainability of TWW-irrigation and spatio-temporal trends in NPK loads to TWW-irrigated fields. Three indices relate to regional analysis of TWW-irrigation sustainability: the 'Environmental sustainability' index measures the TWW compliance with environmental irrigation standards; a 'Nutritional sustainability' index assesses whether the TWW satisfy crop fertilization requirements; a 'Basin nutrient surplus' index measures deviations of N or P loads to river basins from allowed levels. Three additional indices assess the environmental impact, potential loss of nutrients and fit of a given TWW for fertilization recommendations. We employed these indices to analyze a decade-long high spatio-temporal resolution data of TWW quality from Israel on a basin scale, for six TWW-irrigated plantation crops. The results reveal that in high-sensitivity hydrological areas, TWW is generally above the environmental standard for N and P; the TWW with lowest nutrient content is irrigated in low-sensitivity areas, leading to a reduced potential for utilization of nutrients in TWW. While the N irrigation standard (25mgL-1) does not exceed the nutritional requirements of most analyzed crops, the P standard (5mgL-1) results in excess fertilization for all analyzed crops. Therefore, environmental and nutritional sustainability of TWW-irrigation can be increased by diverting high-quality TWW to high-sensitivity areas and vice versa. Furthermore, development of local environmental standards will allow maximizing TWW NPK utilization in low-sensitivity areas, increasing nutritional sustainability. The indices presented in this study provide a tool to help maximize the nutritional benefits of TWW while minimizing its environmental impact.

Detection method of karst features around tunnel construction by multi-resistivity data-fusion pseudo-3D-imaging based on the PCA approach

Abstract During tunnel construction, large groundwater influx poses serious safety hazards. To ensure construction safety, effective measures such as early warning, grouting, and framework support are needed to counteract potential water hazards. It is also critical to clarify the spatial location and size of the water-bearing geological structures before construction to avoid catastrophe. Electrical resistivity tomography (ERT) operates at a high resolution and is sensitive to low-resistivity targets such as water. Thus, it has strong application potential for the detection of karst geomorphology around tunnel construction. However, the use of a single-ERT method may not be sufficient to accurately locate the spatial distribution of karst features. Therefore, it is necessary to carry out multiple-ERT data fusion to generate a comprehensive interpretation of karst geohazards. According to the spatial distribution of different karst caves, we established four geoelectric models for numerical simulation based on the method of principal component analysis. Studies have shown that data fusion is superior to conventional comparative analysis of geophysical data results and creates a more accurate comprehensive description of the same target. For example, inversion data fusion improves poor imaging of the cross-hole ERT near the borehole and reduces the distribution of pseudo-anomalies near the electrode. In this study, the vertical resolution of the surface ERT, and the horizontal resolution of the cross-hole ERT were both improved, while the imaging ability of the borehole-surface ERT in the peripheral low-sensitivity area was enhanced. Moreover, a three-dimensional (3D) conversion method of two-dimensional (2D) detection data in the tunnel environment was employed. An interpolation 3D-imaging of the 2D detection data was carried out, rendering the interpretation of the results more intuitive and comprehensive. Finally, we applied this method in the Daba Tunnel Water Governance Project in Hunan Province, China, and demonstrated that it could overcome the limitations of the single-ERT survey. We were able to accurately delineate the distribution range of the main water-rich bodies around the tunnel. Our findings provide key guidance for the successful implementation of tunnel water-inrush treatment.

Land degradation sensitivity assessment and convergence analysis in Korla of Xinjiang, China

Land degradation has a major impact on environmental and socio-economic sustainability. Scientific methods are necessary to monitor the risk of land degradation. In this study, the environmental sensitive area index (ESAI) was utilized to assess land degradation sensitivity and convergence analysis in Korla, a typical oasis city in Xinjiang of China, which is located on the northeast border of the Tarim Basin. A total of 18 indicators depicting soil, climate, vegetation, and management qualities were used to illustrate spatial-temporal patterns of land degradation sensitivity from 1994 to 2018. We investigated the causes of spatial convergence and divergence based on the Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. The results show that the branch of the Tianshan Mountains and oasis plain had a low sensitivity to land degradation, while the Tarim Basin had a high risk of land degradation. More than two-thirds of the study area can be categorized as “critical” sensitivity classes. The largest percentage (32.6%) of fragile classes was observed for 2006. There was no significant change in insensitive or low-sensitivity areas, which accounted for less than 0.4% of the entire observation period. The ESAI of the four time periods (1994–1998, 1998–2006, 2006–2010, and 2010–2018) formed a series of convergence patterns. The convergence patterns of 1994–1998 and 1998–2006 can be explained by the government’s efforts to “Returning Farmland to Forests” and other governance projects. In 2006–2010, the construction of afforested work intensified, but industrial development and human activities affected the convergence pattern. The pattern of convergence in most regions between 2010 and 2018 can be attributed to the government’s implementation of a series of key ecological protection projects, which led to a decrease in sensitivity to land degradation. The results of this study altogether suggest that the ESAI convergence analysis is an effective early warning method for land degradation sensitivity.

Evaluating the Sensitivity of Growing Degree Days as an Agro-Climatic Indicator of the Climate Change Impact: A Case Study of the Russian Far East

Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. Climatic regions with an extreme thermal range are a special case, as seasonal contrasts complicate the picture. Based on the above, the purpose of the paper is twofold. First, we review methods and indices used for the estimation of changes in the thermal component of the climate and demonstrate the usefulness of a sensitivity assessment methodology that gives some indication of the likely spatial extent of areas of high or low sensitivity to climate change and the size of the potential impact of that change, which is specifically beneficial in regions with high temperature extremes. Secondly, we constructed a composite indicator, called the Growing Degree Day Sensitivity Index (GDDSI) and defined as the percentage change in Growing Degree Day (GDD) for warming scenarios +1, +2 and +3 °C. GDDs were calculated for threshold base air temperatures of 0, 5, 10 and 15 °C, and a high-temperature limit of 30 °C. A GDD sensitivity analysis was applied to the thermally extreme climate of the Russian Far East. We analyzed the data of 50 weather stations across the study region over the period 1966–2017. The results show a strong GDDSI north-to-south gradient. In most cases, the sensitivity does not increase significantly as the warming rate increases. The higher the base threshold, the higher the sensitivity: GDDs with a threshold at 15 °C had the highest sensitivity in the far north of the study area where conditions are currently marginal for crop growth. The sensitivity analysis circumnavigates the difficulty of uncertainty in knowing what future climate to expect and informs planning decisions. The mapped results are useful for identifying areas of high sensitivity to climate change as well as the magnitude of the potential impact of that change.

ASSESSMENT AND MAPPING OF SOIL SENSITIVITY TO EROSION USING GIS IN MELLEGUE CATCHMENT, NORTHEAST OF ALGERIA

In Algeria, there is an urgent need for cartographic zones touched by erosion and also to target priority risk areas to improve the consistency of erosion prevention actions. Such a mapping must be able to display the areas at sensitivity to erosion and must take into account the developments to be undertaken. It is in this perspective that this study is carried out for (a) to map the sensitivity to erosion in the Mellegue catchment by relying on three factors of erosion namely topography, lithology and land use; and (b) to propose a management plan for vulnerable areas. This study is conducted using a Geographic Information System, which has allowed to characterize different areas of the study catchment and its sub-basins by producing a synthetic map of degrees of susceptibility to erosion.The results has shown that the basin has dominant areas of medium to high sensitivity to erosion, despite the existence of a considerable low sensitive area, corresponding to 47% of the basin area and observed mainly at the Meskiana sub-basin. The integration of the results into three levels of sub-basins has allowed identifying the most susceptible areas to erosion. This study provides sufficient data for a prioritization of the study basin according to their degree of erosion, making possible to the different actors, the management of the territory.

Strategic Environmental Impact Assessment for Onshore Windfarm Siting in Greece

The distance between theory and practice in the strategic environmental assessment (SEA) process is particularly noticeable. The development of an integrated, comprehensive and systematic approach guided by the related literature is considered to be an ideal condition for enhancing the value of SEA and increasing its effectiveness. The aim of the present paper was to develop a methodological approach of the most technical and critical stages of SEA for onshore wind farm (OWF) siting. The methodological framework included the proposal of the SEA objectives along with the indicators’ development, the identification of alternatives, the selection of a ‘most viable or sustainable’ alternative, the identification of potential impacts, their assessment, and finally, the proposal of a SEA monitoring system using both qualitative and quantitative methods, tools, and techniques. OWF siting within low and/or moderate sensitivity areas was considered as the most viable/sustainable alternative. SEA highlighted that OWF siting caused moderately to highly significant negative impacts on the thematic section of biodiversity and extremely significant positive impacts on the thematic sections of renewable energy sources, economy, and society. Although the proposed methodology was applied on SEA of OWF siting in Greece, it can be used universally to identify the impacts of OWF siting planning.

Monitoring land sensitivity to desertification in Central Asia: Convergence or divergence?

In Central Asia, desertification risk is one of the main environmental and socioeconomic issues; thus, monitoring land sensitivity to desertification is an extremely urgent issue. In this study, the combination of convergence patterns and desertification risk is advanced from a technical perspective. Furthermore, the environmentally sensitive area index (ESAI) method was first utilized to monitor the risk of desertification in Central Asia. In the study, the spatial and temporal patterns of desertification risk were illustrated from 1992 to 2015 using fourteen indicators, including vegetation, climate, soil and land management quality. The ESAI spatial convergence across administrative subdivisions was explored for three time intervals: 1992-2000, 2000-2008 and 2008-2015. The results indicated that nearly 13.66% of the study area fell into the critical risk of desertification from 1992 to 2008. However, the risk of desertification has improved since 2008, with critical classifications decreasing by 19.70% in 2015. According to the mutation year detection in the ESAI, 25.89% of the pixels with mutation years from 1992 to 2000 were identified, and this value was higher than that during the other time periods. The convergence analysis revealed that the desertification risk for 1992-2000 tended to diverge with a positive convergence coefficient of 0.13 and converge over the 2000-2008 and 2008-2015 time periods with negative convergence coefficients of -0.534 and -0.268, respectively. According to the spatial convergence analysis, we found that the divergence patterns in northern Central Asia from 1992 to 2000 resulted from the effects of the Soviet Union collapse: cropland abandonment in northern Kazakhstan and rangeland abandonment in Tajikistan, Kyrgyzstan and eastern Kazakhstan. In contrast, most areas from 2000 to 2008 experienced increased sensitivity to desertification with the convergence pattern caused by decreased precipitation, especially in northern Central Asia. However, convergence patterns were found in most regions for 2008-2015 with regard to augmented precipitation, which resulted in decreased sensitivity to desertification. Moreover, the low sensitivity areas were more likely to converge under increased precipitation. In this region, the findings of our study suggested that spatial convergence and divergence acted as related predictors of climate change and human activities, respectively. Thus, the ESAI convergence analysis was considered to provide an early warning of potential desertification.

Shared Excitation Based Nonlinear Ultrasound and Vibrothermography Testing for CFRP Barely Visible Impact Damage Inspection

Barely visible impact damage (BVID) is inevitable during either fabrication or lifetime of a carbon fiber reinforced plastic (CFRP) component. These flaws are usually difficult to be detected from the surface by visual inspection or machine vision based on a charge-coupled device or CMOS. In order to solve the problems of low efficiency, low sensitivity, and small detection area of the existing nondestructive testing (NDT) for BVID in CFRP, this paper proposes for the first time the integrated nonlinear ultrasound (NU) and vibrothermography (VT) NDT based on the shared excitation sources. The experimental system was built after introducing the principle of shared excitation based NU&VT NDT. The CFRP plates with 5, 15, and 25 J visible impact damage (VID) as well as 12 and 16 J BVID were tested using the integrated NU&VT. Experimental studies after signal processing have shown that all VID and BVID could be detected by the integrated NU&VT NDT, and the defection capability has a significant improvement after fast Fourier transform. The proposed method could provide a visualized and effective means for quality control and inspection of large-scaled and complex shape key components in manufacturing process and in service.

The study of urban landscape visual sensitivity assessments: a case study in the Zhongshan District of Dalian

ABSTRACTThis paper uses slope, distance,visual probability and remarkableness as evaluation indices to study urban landscape visual sensitivity in the Zhongshan District of Dalian. The results show that areas of high sensitivity account for 14.12% of the total area, these areas should be protected. Moderate sensitivity areas occupy 2.66%, urban landscape transformation should be carried out properly. Low-sensitivity areas accounted for only 0.74%, the utilization of vegetation and the construction of public facilities can be carried out in these areas. Areas classified as insensitive account for 82.48%, this is a potential zone where the urban landscape can be developed.