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Assessing the quality of land is a very important step that precedes the planning of land use and taking management decisions; for example, in the agricultural field, it can be used to evaluate the suitability of the land for planting crops, determine the suitable irrigation system type, or adjust the agricultural inputs such as fertilizers and pesticides according to the requirements of each zone in the land. The spatial–temporal dynamic nature of land characteristics entails also updated evaluation process and updated management plan. The present paper tries to exploit the advances in information and communication technologies to develop a conceptual design of a dynamic system that accommodates the spatial–temporal dynamics of the agricultural soil characteristics to realize a land suitability assessment (LSA) based on a factor analysis method. The proposed design combines IoT technologies, web development, database, and digital mapping and tries to consolidate the system with other functionalities useful for decision support and suitable for different cases. The paper conducted a survey and made comparisons to select the best technologies that fit the current use case implementation and presents its reproducible conceptual modeling by developing the static and dynamic views through schemas, diagrams, message sequence charts, IoT messaging topic tree, pseudocode, etc. The functionality of the design was validated with a simple implementation of the system model. To our knowledge, there is no previous significant contribution that has addressed a LSA IoT use case. The proposed design automates the LSA process for more accurate decision-making, saving cost, time, and effort consumed in repeated field trips. It is characterized by flexibility and centralization in its offered services of spatial analysis, detection, visualizations, and status monitoring. The design also allows for remote control of field machinery. [ABSTRACT FROM AUTHOR]

Tourism networks are an important research part of tourism geography. Despite the significance of transportation in shaping tourism networks, current studies have mainly focused on the “daily behavior” of urban travel at the expense of tourism travel, which has been regarded as an “exceptional behavior”. To fill this gap, this study proposes a framework for exploring the spatial and temporal characteristics of urban tourism travel by taxi. We chose Shenzhen, a densely populated mega-city in China with abundant tourism resources, as a case study. First, we extracted tourist trips from taxi trajectories and used kernel density estimation to analyze the spatial aggregation characteristics of tourist trip origins. Second, we investigated the spatial dependence of tourist trips using local spatial autocorrelation analysis (Getis-Ord Gi*). Third, we explored the correlations between the tourist trip origins and urban geographic contextual factors (e.g., catering services and transportation facilities) using a geographically weighted regression model. The results show the following: (1) the trends between the coverage of tourist travel networks and the volume of tourist trips are similar; (2) the spatial interaction intensity of urban tourism has grouping and hierarchical characteristics; and (3) the spatial distribution of tourist trips by taxi is uneven and influenced by the distribution of urban morphology, tourism resources, and the preferences of taxi pick-up passengers. Our proposed framework and revealed spatial and temporal patterns have implications for urban tourism traffic planning, tourism product development, and tourist flow control in tourist attractions.

The change in land development intensity is an important perspective to reflect the variation in regional social and economic development and spatial differentiation. In this paper, spatial statistical analysis, Ordinary Least Squares (OLS), and Geographically weighted regression (GWR) methods are used to systematically analyse the spatial-temporal characteristics and driving forces of land development intensity for 131 spatial units in the western China from 2000 to 2015. The findings of the study are as follows: 1) The land development intensity in the western China has been increasing rapidly. From 2000 to 2015, land development intensity increased by 3.4 times on average. 2) The hotspot areas have shifted from central Inner Mongolia, northern Shaanxi and the Beibu Gulf of Guangxi to the Guanzhong Plain and the Chengdu-Chongqing urban agglomeration. The areas of cold spots were mainly concentrated in the Qinghai-Tibet Plateau, Yunnan, and Xinjiang. 3) Investment intensity and the natural environment have always been the main drivers of land development intensity in the western China. Investment played a powerful role in promoting land development intensity, while the natural and ecological environment distinctly constrained such development. The effect of the economic factors on land development intensity in the western China has changed, which is reflected in the driving factor of construction land development shifting from economic growth in 2000 to economic structure, especially industrial structure, in 2015. [ABSTRACT FROM AUTHOR]

Abstract: A large‐scale mapping of gully density was carried out for the Middle Volga region of the Russian Plain (188 000 km2) based on the interpretation of aerial photographs (scale 1:17 000; surveys undertaken during 1956–1970). In addition, spatial‐temporal dynamic of gully density were assessed for some parts of the study area (the Udmurt Republic and the Mesha and Ulema River basins of Tatarstan), based on the interpretation of aerial photographs (survey 1986–1991) and high resolution satellite images (2012–2015). Information on factors potentially controlling gully formation and development were collected and a geographic information system (GIS) analysis was conducted. Results show the strong development of gullies in the study area over the 1956–1970 period with an average gully density of 0.21 km km−2. For the Udmurt region, we found that gully densities varied little in the period 1956–1986, during which the total active gully length reduced with only 2%. This period was characterized by low variable climatic conditions and a stable fraction of arable land with a relatively continuous crop rotation system. However, gully dynamics seems to have changed more strongly during recent decades. We found a strong (order of magnitude) reduction in active gully density for the period 2010–2015 as compared to 1986–1991. The main reason for this is likely the increasing winter air temperatures. This leads to a significant reduction in surface runoff during spring as a result of snowmelt. Nonetheless, in some regions (i.e. the Udmurt Republic in the taiga zone), the abandonment of arable land after 1991 likely plays a significant role. Likewise, a decline in the frequency of extreme rainfall events (> 50 mm) may have played a role. All of these factors contribute to a reduction of surface runoff to the gullies and their subsequent stabilization. © 2018 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Mangrove forests play an important role in absorbing carbon, filtering pollution, and protecting coastal residents from storms. However, mangrove forests are most susceptible to human interference and suffer more than one-third of losses globally. Therefore, quantifying their spatial-temporal changes and identifying their potential distributions are necessary for protection, restoration, and management. We first mapped and analysed the spatial-temporal changes in mangrove forests from 1993 to 2021 in the Xinying-Bay region (XYB), Hainan Province, China. Then, we predicted suitable habitats for mangrove forests by using the maximum entropy (MaxEnt) model based on mangrove distribution data for 2021 and related environmental data for the Circum-Xinying-Bay region (CXYB). The results show remarkable changes in mangrove forests in the XYB from 1993 to 2021, with the loss rate reaching 56 ha/y from 1998 to 2002. The MaxEnt model performs well, with the curve (AUC) extending beyond 0.9. Water quality and topography determined the distribution of mangrove forests, with the total contribution exceeding 65%. The six most important influential factors were salinity, DEM, precipitation in the driest quarter, pH, isothermality, and winter sea surface temperature. The area of mangroves highly suitable in the CXYB is approximately 3880 hm2 and is mainly located in the town of Xinzhou, the northeast area of the town of Mutang and the southwest area of the town of E'man. This suggests that areas prioritized for protection should include the northern and western areas of Xinzhou, northeastern areas of Mutang, and northern and western areas of E'man. These findings provide further understanding of mangrove distribution and can guide mangrove restoration and management. • Remarkable changes in mangrove forests in the XYB from 1993 to 2021. • Water quality and topography determined the distribution of mangrove forests. • The area of high mangrove forests restoration potential is approximately 2106 hm2. • A reasonable restoration strategy is the key to mangrove forests restoration. • More social groups should be encouraged to participate in the construction and management of mangrove forests. [ABSTRACT FROM AUTHOR]

GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalised Difference Vegetation Index) from 1982 to 2006 and MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI from 2001 to 2010 were blended to extract the grass coverage and analyze its spatial pattern. The response of grass coverage to climatic variations at annual and monthly time scales was analyzed. Grass coverage distribution had increased from northwest to southeast across China. During 1982-2010, the mean nationwide grass coverage was 34% but exhibited apparent spatial heterogeneity, being the highest (61.4%) in slope grasslands and the lowest (17.1%) in desert grasslands. There was a slight increase of the grass coverage with a rate of 0.17% per year. Increase in slope grasslands coverage was as high as 0.27% per year, while in the plain grasslands and meadows the grass coverage increase was the lowest (being 0.11% per year and 0.1% per year, respectively). Across China, the grass coverage with extremely significant increase (P<0.01) and significant increase (P<0.05) accounted for 46.03% and 11% of the total grassland area, respectively, while those with extremely significant and significant decrease accounted for only 4.1% and 3.24%, respectively. At the annual time scale, there are no significant correlations between grass coverage and annual mean temperature and precipitation. However, the grass coverage was somewhat affected by temperature in alpine and sub-alpine grassland, alpine and sub-alpine meadow, slope grassland and meadow, while grass coverage in desert grassland and plain grassland was more affected by precipitation. At the monthly time-scale, there are significant correlations between grass coverage with both temperature and precipitation, indicating that the grass coverage is more affected by seasonal fluctuations of hydrothermal conditions. Additionally, there is one-month time lag-effect between grass coverage and climate factors for each grassland types. [ABSTRACT FROM AUTHOR]

We report a harmonic hexagonal superlattice pattern in a dielectric barrier discharge in air/argon mixture at atmospheric pressure. The bifurcation scenario of harmonic hexagonal superlattice pattern with the applied voltage increasing is given. The phase diagram of the pattern types as a function of the applied voltage and the air-concentration is obtained. The hysteresis of pattern transitions at the up- ward and downward stage of the applied voltage is observed. The correlation measurements indicate that harmonic hexagonal superlattice pattern is an interleaving of two different transient sublattices. The spatial power spectrum demonstrates that harmonic hexagonal superlattice pattern has two separate wave vectors. Both small wave vector qh and big wave vector Kh, belong to the harmonic mode, and they obey a triad resonant interaction q¹h + q²h = Kh. [ABSTRACT FROM AUTHOR]

Tourism networks are an important research part of tourism geography. Despite the significance of transportation in shaping tourism networks, current studies have mainly focused on the "daily behavior" of urban travel at the expense of tourism travel, which has been regarded as an "exceptional behavior". To fill this gap, this study proposes a framework for exploring the spatial and temporal characteristics of urban tourism travel by taxi. We chose Shenzhen, a densely populated mega-city in China with abundant tourism resources, as a case study. First, we extracted tourist trips from taxi trajectories and used kernel density estimation to analyze the spatial aggregation characteristics of tourist trip origins. Second, we investigated the spatial dependence of tourist trips using local spatial autocorrelation analysis (Getis-Ord Gi*). Third, we explored the correlations between the tourist trip origins and urban geographic contextual factors (e.g., catering services and transportation facilities) using a geographically weighted regression model. The results show the following: (1) the trends between the coverage of tourist travel networks and the volume of tourist trips are similar; (2) the spatial interaction intensity of urban tourism has grouping and hierarchical characteristics; and (3) the spatial distribution of tourist trips by taxi is uneven and influenced by the distribution of urban morphology, tourism resources, and the preferences of taxi pick-up passengers. Our proposed framework and revealed spatial and temporal patterns have implications for urban tourism traffic planning, tourism product development, and tourist flow control in tourist attractions. [ABSTRACT FROM AUTHOR]