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Advanced technologies and big data have brought new visions and methods to urban planning research. Based on the Baidu heat map and POI data of two typical days (a weekend day and a workday) in 2018, this paper analyses the spatial and temporal aggregation patterns of crowds in the urban centre of Wuhan using ArcGIS. Aggregation patterns are defined by the intensity of population activities and the places where crowds gather. In terms of time, the daily change of population aggregation intensity is studied by counting the heat value of 24 moments captured throughout the day. The results show that on rest days, people prefer to travel around noon and in the afternoon, reaching the highest peak of the day around 15:00, while on workdays, residents' activities are affected by commuting, with obvious 'morning rush hours' and 'evening rush hours'. Firstly, the spatial correlation between the density of POI distribution and the degree of population aggregation has been studied by the spatial coupling relationship between the Baidu heat map and POI data. Secondly, the index of correlation between the aggregation of different POIs and population (ICPP) are mentioned to analyse the purposes and the degrees of aggregation during weekend and workday rush hours. Based on the ICPP, we analyse activities from three aspects: the different ICPPs between the workday and the weekend; the different ICPPs between the morning, afternoon and evening; and the different ICPPs among different POIs.

Volunteered geographic information (VGI) has great potential to reveal spatial and temporal dynamics of geographic phenomena. However, a variety of potential biases in VGI are recognized, many of which root from volunteer data contribution activities. Examining patterns in volunteer data contribution activities helps understand the biases. Using eBird as a case study, this study investigates spatial and temporal patterns in data contribution activities of eBird contributors. eBird sampling efforts are biased in space and time. Most sampling efforts are concentrated in areas of denser populations and/or better accessibility, with the most intensively sampled areas being in proximity to big cities in developed regions of the world. Reported bird species are also spatially biased towards areas where more sampling efforts occur. Temporally, eBird sampling efforts and reported bird species are increasing over the years, with significant monthly fluctuations and notably more data reported on weekends. Such trends are driven by the expansion of eBird and characteristics of bird species and observers. The fitness of use of VGI should be assessed in the context of applications by examining spatial, temporal and other biases. Action may need to be taken to account for the biases so that robust inferences can be made from VGI observations.

The study determined water temperature trends of rivers in Poland in the period 1971&ndash, 2015, and also their spatial and temporal patterns. The analysis covered daily water temperature of 53 rivers recorded at 94 water gauge stations and air temperature at 43 meteorological stations. Average monthly, annual, seasonal and maximum annual tendencies of temperature change were calculated using the Mann&ndash, Kendall (M&ndash, K) test. Regional patterns of water temperature change were determined on the basis of Ward&rsquo, s hierarchical grouping for 16 correlation coefficients of average annual water temperature in successive 30-year sub-periods of the multi-annual period of 1971&ndash, 2015. Moreover, regularities in monthly temperature trends in the annual cycle were identified using 12 monthly values obtained from the M&ndash, K Z test. The majority of average annual air and water temperature series demonstrate statistically significant positive trends. In three seasons: spring, summer and autumn, upward tendencies of temperature were detected at 70%&ndash, 90% of the investigated water gauges. In 82% of the analysed rivers, similarity to the tendencies of change of monthly air temperature was concluded, with the climatic factor being recognised as of decisive importance for the changes in water thermal characteristics of the majority of rivers in Poland. In the winter months, positive trends of temperature were considerably weaker and in general statistically insignificant. On a regional scale, rivers with a quasi-natural thermal regime experienced temperature increases from April to November. In the other cases, different directions of change in river water temperature (RWT) were attributed to various forms of human impact. It was also found that for the majority of rivers the average annual water temperature in the analysed 30-year sub-periods displayed upward trends, statistically significant or close to the significance threshold. Stronger trends were observed in the periods after 1980, while a different nature of water temperature change was detected only in a couple of mountainous rivers or rivers transformed by human impact. In the beginning of the analysed period (1971&ndash, 2015), the average annual water temperature of these rivers displayed positive and statistically significant trends, while after 1980 the trends were negative. The detected regularities and spatial patterns of water temperature change in rivers with a quasi-natural regime revealed a strong influence of climate on the modification of their thermal regime features. Rivers characterised by a clearly different nature of temperature change, both in terms of the direction of the tendencies observed and their statistical significance, were distinguished by alterations of water thermal characteristics caused by human activity. The results obtained may be useful in optimising the management of aquatic ecosystems, for which water temperature is a significant indicator of the ongoing environmental changes.

The main objective of this work was to evaluate technologies that have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture yield and for support to decision making by the farmers. Three types of sensors were evaluated: an electromagnetic induction sensor, an active optical sensor and a capacitance probe. The results are relevant for the selection of the adequate sensing system for each particular application and to open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions and rainfall patterns, characteristic of the Mediterranean region.

The Tibetan Plateau is one of the most vulnerable areas to extreme precipitation. In recent decades, water cycles have accelerated, and the temporal and spatial characteristics of extreme precipitation have undergone dramatic changes across the Tibetan Plateau, especially in its various ecosystems. However, there are few studies that considered the variation of extreme precipitation in various ecosystems, and the impact of El Ni&ntilde, o-Southern Oscillation (ENSO), and few researchers have made a quantitative analysis between them. In this study, we analyzed the spatial and temporal pattern of 10 extreme precipitation indices across the Tibetan Plateau (including its four main ecosystems: Forest, alpine meadow, alpine steppe, and desert steppe) based on daily precipitation from 76 meteorological stations over the past 30 years. We used the linear least squares method and Pearson correlation coefficient to examine variation magnitudes of 10 extreme precipitation indices and correlation. Temporal pattern indicated that consecutive wet days (CWD) had a slightly decreasing trend (slope = &minus, 0.006), consecutive dry days (CDD), simple daily intensity (SDII), and extreme wet day precipitation (R99) displayed significant increasing trends, while the trends of other indices were not significant. For spatial patterns, the increasing trends of nine extreme precipitation indices (excluding CDD) occurred in the southwestern, middle and northern regions of the Tibetan Plateau, decreasing trends were distributed in the southeastern region, while the spatial pattern of CDD showed the opposite distribution. As to the four different ecosystems, the number of moderate precipitation days (R10mm), number of heavy precipitation days (R20mm), wet day precipitation (PRCPTOT), and very wet day precipitation (R95) in forest ecosystems showed decreasing trends, but CDD exhibited a significant increasing trend (slope = 0.625, P &lt, 0.05). In the other three ecosystems, all extreme precipitation indices generally exhibited increasing trends, except for CWD in alpine meadow (slope = &minus, 0.001) and desert steppe (slope = &minus, 0.005). Furthermore, the crossover wavelet transform indicated that the ENSO had a 4-year resonance cycle with R95, SDII, R20mm, and CWD. These results provided additional evidence that ENSO play an important remote driver for extreme precipitation variation in the Tibetan Plateau.

Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May–October, February–April and November–January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (CODMn), 5-day biochemical oxygen demand (BOD5), NH4+–N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.

In an agricultural county like China, agricultural fertilizers are the source of ammonia (NH3) emissions. However, the spatial variability in NH3 emissions is large, and the associated uncertainties affect the reliability of total NH3 emission estimates. In this study, an inventory is presented for NH3 emissions from China's agricultural fertilizer application at the city-level, and on a 1 × 1 km grid for croplands in 2010. We present NH3 emissions by source, the temporal and spatial patterns, and the associated uncertainties. The inventory is based on high-resolution activity data, regional emission factors (EFs) and related parameters that are derived from local studies. We compare our emissions estimates with previous inventories from EDGAR and other studies. The total NH3 emissions from China's agricultural fertilizer is 10.7 (8.9–12.3) TgNH3·yr−1. Livestock manure spreading contributes 47.5% to the total emissions, and synthetic fertilizer use by 41.9%. Rural excrement (5.0%) and cake fertilizer (5.5%) are relatively small sources. The spatial pattern of NH3 emissions from China's agricultural fertilizer were primarily concentrated in the North China Plain, the Songliao Plain, the Huaihe River Basin, the Middle-Lower Yangtze Plain, the Pearl River Delta Plain, the Sichuan Basin, the Tarim basin and the Leizhou Peninsula. Approximately 50% of the emissions are from only 76 cities. Our temporal analysis reveals a clear seasonal pattern in NH3 emissions: highest and lowest emissions are calculated for summer and winter, accounting for 42% and 14% of the total emissions, respectively. Peak emissions are calculated for July (1.7 TgNH3·yr−1) and lowest emissions for January (0.5 TgNH3·yr−1). The emissions are correlated with temperature, planting time and cultivation practices.

This paper reviews the patterns observed in the diversity and structure of the macrofauna benthic community under the influence of fish farming. First, we explain the effects of organic enrichment on the sediment and the consequences for the inhabiting communities. We describe the diversity trends in spatial and temporal gradients affected by fish farming and compare them with those described by the Pearson and Rosenberg model. We found that in general terms, the trends of diversity and other community parameters followed the Pearson and Rosenberg model but they can vary to some extent due to sediment local characteristics or to secondary disturbances. We also show the different mechanisms by which wild fish can affect macrofauna diversity patterns under fish farming influence. In addition, we comment the importance of the macrofauna diversity in the ecosystem functions and propose some guidelines to measure functional diversity related to relevant processes at ecosystem level. We propose more research efforts in the main topics commented in this review to improve management strategies to guarantee a good status of the diversity and ecosystem functioning of sediments influenced by fish farming.

We suggest an ethno-biological approach to analyze the cultural and social drivers of hunting activities and assess sustainability in villages near Makokou, northeast Gabon, based on interviews with hunters, participatory mapping of hunting territories, and daily records of offtakes for 1 yr. Hunting in villages of northeast Gabon is practiced for both local consumption and cash income to cover basic family expenses. There appears to be no clear tendency to abandon subsistence hunting for commercial hunting as in other regions of Africa. Cultural and socioeconomic factors explain the temporal and spatial variation in hunting activities. Hunting increases in the dry season during circumcision ceremonies, when it is practiced mainly at > 10 km from villages, and decreases during the rainy season because most hunters are occupied by other economic activities. Degraded forest such as secondary regrowth supplies 20% of the animals killed and the greatest diversity of species at short distances from villages. Mature forest supplies the species with the greatest commercial value, e.g., red river hog ( Potamochoerus porcus), and is the preferred source of meat for traditional ceremonies. In the last 15 yr, hunting patterns have changed rapidly, mainly because of the spread of gun hunting, which had serious implications for the nature of offtakes. Our results suggest that there is potential to allow hunting for resistant species such as blue duiker (Cephalophus monticola) and African brush-tailed porcupine ( Atherurus africanus). Other species such as red river hog and small diurnal monkeys require more attention. Specific management systems could be discussed in participatory hunting management plans to identify possible solutions to maintain the population levels of the more critical species.