A quantitative understanding of the hydro-environmental factors that influence the occurrence of agricultural drought events would enable more strategic climate change adaptation and drought ...management plans. Practical drought hazard mapping remains challenging due to possible exclusion of the most pertinent drought drivers, and to the use of inadequate predictive models that cannot describe drought adequately. This research aims to develop new approaches to map agricultural drought hazard with state-of-the-art machine learning models, including classification and regression trees (CART), boosted regression trees (BRT), random forests (RF), multivariate adaptive regression splines (MARS), flexible discriminant analysis (FDA) and support vector machines (SVM). Hydro-environmental datasets were used to calculate the relative departure of soil moisture (RDSM) for eight severe droughts for drought-prone southeast Queensland, Australia, over the period 1994–2013. RDSM was then used to generate an agricultural drought inventory map. Eight hydro-environmental factors were used as potential predictors of drought. The goodness-of-fit and predictive performance of all models were evaluated using different threshold-dependent and threshold-independent methods, including the true skill statistic (TSS), Efficiency (E), F-score, and the area under the receiver operating characteristic curve (AUC-ROC). The RF model (AUC-ROC = 97.7%, TSS = 0.873, E = 0.929, F-score = 0.898) yielded the highest accuracy, while the FDA model (with AUC-ROC = 73.9%, TSS = 0.424, E = 0.719, F-score = 0.512) showed the worst performance. The plant available water holding capacity (PAWC), mean annual precipitation, and clay content were the most important variables to be used for predicting the agricultural drought. About 21.2% of the area is in high or very high drought risk classes, and therefore, warrant drought and environmental protection policies. Importantly, the models do not require data on the precipitation anomaly for any given drought year; the spatial patterns in AGH were consistent for all drought events, despite very different spatial patterns in precipitation anomaly among events. Such machine-learning approaches are able to construct an overall risk map, thus assisting in the adoption of a robust drought contingency planning measure not only for this area, but also, in other regions where drought presents a pressing challenge, including its influence on key practical dimensions of social, environmental and economic sustainability.
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•Spatial and temporal machine learning approaches proposed for drought risk mapping.•Performance of six machine learning models is compared.•MARS and RF are suitable machine learning models for spatial risk mapping•Approximately 26% of the study area is at high or very high drought risk.•New approach considers hydro-geo-environmental factors for drought risk policy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ
To develop solar energy as a primary source of electricity supply in China, it is imperative to also develop an overall and complete solar energy potential analysis. Such an analysis technique would ...be a substantial contribution to solar power generation development both nationally and regionally. This study analyzes the spatial and temporal distribution of solar energy in China and estimates the solar energy potential from three aspects: geography, technology, and economy. The results of this research showed that the solar energy resource in China is substantially rich and stable, but also has notable spatial heterogeneity. A potential estimation indicated that Xinjiang Province was the most optimal site for large-scale photovoltaic station construction, displaying the highest values for all three potentials. It was also found that solar energy potential in western China is greater, while the eastern region is less suitable for solar photovoltaic development. These results can provide support for the large-scale development and utilization of solar energy resources in the future.
•Chinese solar energy resources are stable and has notable spatial heterogeneity.•Northwestern China was with higher potential than the east.•Xinjiang Province was the most optimal option for PV station operation.•Land use remained critical for large-scale PV generation.
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The objective of this work is to analyze wave packet propagation in weakly nonlinear acoustic metamaterials and reveal the interior nonlinear wave mechanism through spectro-spatial analysis. The ...spectro-spatial analysis is based on full-scale transient analysis of the finite system, by which dispersion curves are generated from the transmitted waves and also verified by the perturbation method (the L-P method). We found that the spectro-spatial analysis can provide detailed information about the solitary wave in short-wavelength region which cannot be captured by the L-P method. It is also found that the optical wave modes in the nonlinear metamaterial are sensitive to the parameters of the nonlinear constitutive relation. Specifically, a significant frequency shift phenomenon is found in the middle-wavelength region of the optical wave branch, which makes this frequency region behave like a band gap for transient waves. This special frequency shift is then used to design a direction-biased waveguide device, and its efficiency is shown by numerical simulations.
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The coronavirus pandemic is causing a huge impact around the world. Its real magnitude presents very important regional differences, which are appreciable in the number of infected and victims in the ...different countries. The outbreak of the pandemic and the ignorance of the virus mean that, even today, there are many unknowns about essential aspects related to it. In this sense, geographic knowledge can help answer many questions from the territorial analysis of the data. The objective of this article will be to analyze the behavior of the coronavirus pandemic within the Spanish region of Galicia. The authors of this study propose a multiscale analysis that allows deciphering the most common propagation patterns. For this, we have high spatial resolution data that has been provided by the competent authority under confidentiality. The results of this work allow us to represent and interpret the territorial impact of the pandemic, understanding its behavior as far as possible, allowing future dynamics to be predicted.
Introduction: Acute respiratory infection (ARI) is a health problem causing global morbidity and mortality in Indonesia, with 18.8 billion cases and more than six million deaths observed in 2016. ...Between 2013 and 2018, the diagnosis of ARI prevalence reportedly experienced a 10% decrease from 12.5-2.5%, within 10 provinces, including DKI Jakarta, Indonesia. Methods: This study aims to identify the spatial analysis of ARI events using an ecological method, based on the Air Pollution Standard Index (PSI) at DKI Jakarta between 2018 and 2019. Results and Discussion: Data analysis was performed by mapping case description through Quantum GIS, correlation assessment, as well as linear regression with SPSS scatter plot. Based on the bivariate analysis, the correlation assessment and linear regression of the ARI event with PM10 had positive regression in 2018 and 2019, at (R)0.649 and (R)0.0630, respectively. Conclusion: The highest PM10 values in Kelapa Gading and Cipayung districts increased the case of ARI fluctuations within two years. Therefore, the environmental health service office focused on the air quality evaluation and prevention control of ARI cases.
Green water is primarily associated with the appearance of annual plants and plays a significant role in biomass production in both arid and semi-arid ecosystems. Herein, we aim to estimate the ...optimal threshold for determining the presence or absence of annual plants and use them as an ecological indicator to assess potential green water areas in Kuwait as a case study. We integrate remote sensing techniques and MaxEnt modeling. The AUC for the annual plant distribution with all examined factors is 0.847, and the standard deviation is 0.050. The results demonstrated that potential locations with high levels of green water cover <20% of the country. The annual plant distribution was significantly correlated with several types of perennial plants, maximum temperature, precipitation, and sandy soils. It was also found that annual plants are controlled by the spring and winter temperature decline and the timing of precipitation occurrence, especially the pattern and amount of rainfall received in November. Sandy loam and loam soils were found to be ideal for annual plants, although land depressions and soil types are crucial factors in determining annual plant distribution. Additionally, annual plants enhanced the growth of several perennial communities. To reiterate, our study's model helped to comprehend the significance of annual plants as an ecological indicator in sustaining soil moisture over a prolonged period, as well as factors controlling the distribution of annual plants. The developed model and indicators could support decision-makers in determining appropriate locations with adequate levels of green water for revegetation planning in arid landscapes.
•The distribution of annual plants, suitable soils, and green water are significantly interconnected.•Machine learning techniques are useful for selecting suitable locations for revegetation.•Revegetation of native plants could help grazing pastures to enhance food security.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ
It is of very great significance to achieve accurate solution of equidistant points/equiratio line between two points at a large regional or global scale. At present, no effective method has been ...found for equidistant/equiratio line between two points on the Earth ellipsoid. In large scale space, the solution plane of equidistant/equiratio points between two points on the map cannot meet the requirements of high-precision space analysis, due to the existence of map projection deformation. The key to solving the above problems is to establish a method generating the equidistant/equiratio line based on solution to geodesic problem, and implement the entire calculation process on the Earth ellipsoid. Based on the Karney's direct and inverse formulas, the paper uses the pendulum method to design a cohesive method for calculating the equidistant/equiratio line between two points on the Earth ellipsoid. Several specific examples are selected for experimental verification, which proves that this algorithm can solve the problem of calculating equidistant/equiratio line of two points of different scale line in short distance, medium distance and long distance, and the precision of solving coordinate space is less than 0.00001 m, which can meet the requirements of long distance, wide range and high-precision spatial analysis.
•A unified and efficient algorithm to calculate the equidistant/equiratio line between two points on the Earth ellipsoid.•The calculation is completely processed on the earth ellipsoid, and it can completely get rid of the influence of map projection.•The results can meet the high-precision requirements of spatial analysis on the Earth ellipsoid.
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The need for the development of the riverside area in the central part of the city of Komsomolsk-on-Amur is considered. Current economic and socio-cultural factors influencing the functionalities and ...uses of the development are evaluated. A multifactorial spatial analysis was carried out to draw conclusions on the need to change the urban planning approach to the development of the Silinka River floodplain, including the improvement of transport accessibility of the Silinsky Park and revitalization of abandoned and ineffective industrial areas.
Spatial Determinants of Crime in Krakow, 2017-2021 The article presents a spatial analysis of selected types of crimes committed in Krakow in 2017-2021. Spatial data on crimes from the Police ...registers, the numbers of which were presented in tabular form, and data on the distribution of municipal monitoring were used for the research. The first step was to determine the type of spatial distribution of criminal offenses using the Nearest Neighbour Analysis method. As a result of determining the type of distribution as a clustered distribution, a detailed identification of the places of the highest concentration of criminal events in the city was initiated. For this purpose, the method of kernel density estimation showing the distribution of intensity of criminal events was used. Analyzes showed the highest concentration of violent crimes in Krakow in 2017-2021 in the city center, while crimes against property was evenly distributed throughout the city, with the exception of its suburbs. The last stage was a detailed spatial analysis of places defined as "hot spots" in terms of their functional and spatial conditions and situational conditions conducive to or hindering the commission of crimes there. The analysis was made on the basis of the local inspection of "hot spots". The obtained research results were compared to the criminological theories presented in the article and the results of research in this scope presented both in Poland and abroad.
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