Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.

Horticulture is a widespread activity in family farming in the Transamazonian region—Pará, with emphasis on production aimed at the family’s own consumption. The lettuce cultivar Vanda (Lactuca sativa L.) represents a significant part of this production, which prioritizes the use of internal labor. The main objective of this work was to evaluate the development of lettuce CV Vanda grown in beds using organic compost and chemical fertilization (NPK). The criteria considered to evaluate this performance were: Root system development, plant height and total fresh mass production. The best averages in relation to root development occurred in the plots cultivated with organic compost in the proportion of 5 kg/m², due to its characteristics as a fertilizer and soil conditioner. The cultivation with the use of NPK provided the best averages in relation to the production of total fresh mass and plant height, results that were mainly attributed to the extra supply of nitrogen in the covering fertilization, which consisted in the addition of 10 g urea per square meter via soil. Statistical analysis showed no statistically significant difference regarding plant height for both treatments. And in relation to root development, the difference was statistically significant.

In order to promote the application of noise map in high-speed railway noise management, the high-speed railway noise map drawing technology based on the combination of noise prediction model and geographic information system (GIS) is studied. Firstly, according to the distribution characteristics of noise sources and line structure characteristics of high-speed railway, the prediction model of multi equivalent sound sources and the calculation method of sound barrier insertion loss of high-speed railway are optimized; secondly, a three-dimensional geographic information model of a high-speed railway is built in GIS software, and the railway noise prediction technology based on the model is developed again; then, the noise of discrete nodes is calculated, and the continuous noise distribution map is drawn by spatial interpolation. The research results show that the comparison error between the noise map of a high-speed railway drawn by this technology and the measured results is less than 1 dB (A), which verifies the accuracy and practicality of the high-speed railway noise map, and can be used as a reference for the railway noise management department to formulate noise control countermeasures.

The purpose of this article is to determine the equitability of airport and university allocations throughout Ethiopian regional states based on the number of airports and institutions per 1 million people. According to the sample, the majority of respondents believed that university allocation in Ethiopia is equitable. In contrast, the majority of respondents who were asked about airports stated that there is an uneven distribution of airports across Ethiopia’s regional states. Hence, both interviewees and focus group discussants stated that there is a lack of equitable distribution of universities and airports across Ethiopia’s regional states. This paper contributes a lesson on how to create a comprehensive set of determining factors for equitable infrastructure allocation. It also provides a methodological improvement for assessing infrastructure equity and other broader implications across Ethiopian regional states.

Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.