Analysis Of Spatial Variability Research Articles

Analysis of Spatial and Temporal Variability of Global Wetlands during the Last 20 Years Using GlobeLand30 Data

Knowing the distributions and changes in global wetlands and their conversion to other land cover types could facilitate our understanding of wetland development, causes of variations, and decision-making for restoration and protection. This study aimed to comprehensively analyze the changes in wetland distributions at global, continental, typical regional, and national scales and the conversions between wetlands and other land cover types in the last 20 years. This study used GlobeLand30 (GL30) data with a 30 m resolution for the years 2000, 2010, and 2020. The main findings of this study are as follows: (1) the area of wetlands continued to increase globally from 2000 to 2020, with a total increase of approximately 4%. Wetland changes from 2010 to 2020 were more significant than those from 2000 to 2010. The regions with significant wetland changes were mainly in the north middle- and high-latitude, and the equatorial middle- and low-latitude, and Oceania and North America were the continents with the highest increase and decrease, respectively; (2) the major conversion of wetlands was mainly natural land cover types, including forest, grassland, water, and tundra, and there were minor conversions due to human activities, including the conversion of wetlands to cropland (~4600 km2) and artificial land (~3400 km2); (3) from 2000 to 2020, the increase in global wetlands was uneven, while the decrease was nearly even at a national scale. Australia had the highest increase due to the conversions from grass, bare land, and water, and Canada had the highest decrease due to the conversion into tundra and forest. The analysis results could more comprehensively characterize the distributions and changes of global wetlands, which may provide basic information and knowledge for related research work and policymaking.

A case study of a real-time internet of things system for site-specific potato crop management in El-Salhia Area-Egypt

The site-specific management is the technology that considers the natural variability within the same field of factors related to crop growth to improve its management practices such that the agricultural treatments are varied for field's small production zones saving resources and environment, and improving crop quality and size. Since site-specific decisions are not far from the Fourth Industrial Revolution and the concept of processes automation, this work addresses improving the process of spatial variability analysis and thus supporting management decisions by developing a system—entitled EGYPADS—based on the Internet of Things and its enabling technologies. EGYPADS automates data collection, zones delineation according to their land suitability evaluation, and maps generation. The paper addresses a case study of potato crop in a specific area in Egypt, El-Salhia, in which eighty-five sites were chosen as main dataset for the modeling process during different stages of crop growth. Three management zones were recognized of the selected field based on the differentiation in their land suitability characteristics, representing about 5%, 65%, and 30% of the total area, respectively. The structure, screens, and services of EGYPADS are described in this paper. EGYPADS offered services include: management zones delineation using absolute and virtual coordinates, Land Suitability Assessment (LSA), data entry from field in real-time as well as from excel sheets, saving maps in suitable format for variable rate application, real-time and historical data processing, centralized management, and flexible formulation of events and related actions. The implementation of EGYPADS was verified. The system dynamically produces non-contiguous isobands, each representing a specific range of parameter values, and can be properly exported for use by other programs or smart machinery. It was proven that EGYPADS supports more than one land with different geometry, area, location, and number of nodes. EGYPADS was compared with the traditional LSA method, and was found to produce similar management zones.

Temporal and spatial variation analysis of habitat quality on the PLUS-InVEST model for Ebinur Lake Basin, China

The improvement of habitat quality is of great significance to biodiversity conservation. Irrational development activities lead to the degradation of habitat quality and loss of biodiversity, especially in arid inland areas where the ecological environment is fragile. In this study, the InVEST model is used to evaluate the habitat quality and degradation degree of the Ebinur Lake Basin from 1990 to 2020, while the PLUS model is used to predict the land use change in the Ebinur Lake Basin under various scenarios. Combined with the results of ecological zoning planning, the spatial distribution of land use and habitat quality under the inertia development (ID) and ecological protection (EP) scenarios in 2030 were compared and analyzed, and the optimal scenario was selected. The following four conclusions are drawn: (1) From 1990 to 2020, cultivated land, grassland, and construction land significantly increased, while forest land, water bodies, and unused land significantly decreased. (2) The habitat quality of the watershed showed an increasing trend followed by a decreasing trend. The area proportion of high habitat quality has always exceeded 50 % of the total area of the watershed with a high level of habitat quality. (3) Furthermore, combined with habitat quality and the human footprint index (HFI), ecological zoning planning for the basin was conducted. The three ecological zones were divided into key protected areas, key restoration areas, and moderate development zones, with area proportions of 53.69 %, 29.37 %, and 16.93 %, respectively. (4) By comparing habitat quality under the ID scenario and the EP scenario in 2030, we found that the area of high habitat quality increased by 2730.06 km2 under the EP scenario, which improved the overall level of habitat quality, and was more conducive to the ecological security protection of the basin. The results of this study may benefit the analysis of the temporal and spatial variation characteristics of habitat quality in the Ebinur Lake Basin and provide a reference for the improvement of habitat quality in the inland arid region.

Genetic population structure and demographic history of the endemic fish Paralichthys olivaceus of the Northwest Pacific Ocean.

The Northwest Pacific marginal waters comprising the South China Sea, East China Sea, Yellow Sea, and the Sea of Japan have unique geomorphic features. The Japanese flounder Paralichthys olivaceus, which is endemic to the Northwest Pacific, has high nutritional, economic, and ecological value. To allow the examination of the demographic history and population structure of the most common P. olivaceus species range over the five marginal seas (East China Sea, Yellow Sea, Bohai Sea, Northwest Pacific Ocean, and the Sea of Japan), the mitochondrial DNA control region of 91 individuals from six populations in China was sequenced. These sequences were combined with 233 sequences from four populations distributed in the Northwestern Pacific Ocean for analysis. Higher levels of nucleotide diversity (0.032 ± 0.016) and haplotype diversity (0.996 ± 0.001) were observed. The peripheral Fuqing population in the East China Sea had the relatively lowest genetic diversity and highest differentiation. Furthermore, when the results of the isolation by distance test, spatial analysis of molecular variation and geographic barrier analysis are also considered, there is a clear need to prioritize resource conservation and enhancement measures in this area. The phylogenetic trees, structure assignment test, and haplotypes network revealed no significant differences in the genealogical structure among ten populations. Mismatch distribution analysis, Bayesian skyline plots, and neutrality tests suggested that P. olivaceus experienced population expansion during the Pleistocene. Ocean currents and climate change play important roles in shaping the geographical distribution and genetic population structure of P. olivaceus.

Geospatial Analysis of Spatial Variability of Groundwater Quality Using Ordinary Kriging: A Case Study of Dungarpur Tehsil, Rajasthan, India

Groundwater is one the major sources of natural water being exploited excessively for various uses in India.
 Thus, it is very essential to monitor the spatial and temporal variability of groundwater quality. Geo-Statistical Interpolation using GIS has been considered as the best and most advanced method for the interpolation and prediction studies of groundwater pollution and quality, and is adopted universally. In this paper, ordinary Kriging with logarithmic data transformation has been used to interpolate and predict the spatial variation of groundwater quality parameters - EC, TDS, pH, Na+, Ca2+, Bi-Carbonate, Fluoride, Chloride, Sulphate and Nitrate using data pertaining to 48 well locations in the Dungarpur tehsil. Data was transformed and normalized using Logarithmic Transformation Method and Semivariograms were drawn and analyzed for selecting the suitable model. The best Semivariogram model was obtained based upon cross validation and on the lesser RMSE criterion and Coefficient of Determination. The results show that the best semivariogram model based on RMSE varied for each water quality parameter. For log transformed data Exponential model was found suitable for EC, TDS, Na+, TH etc.; Spherical model for Ca2+ ; Chloride Gaussian Model for Chloride. For original or raw for non-transformed data Exponential Model was found suitable for Fluoride, Sulphate and Nitrate; and Gaussian Model for pH and Bi-Carbonates.

Spatial variability of the productive capacity of teak (Tectona grandis Linn F.) plantations in the eastern Amazonia

Application of geostatistics in mapping the productive capacity of forest stands is an important tool to guide decision making regarding precision silviculture. In this study, we investigated the productive capacity of teak clonal plantations and its spatial dependence, making the site mapping possible. We also investigated the influence of soil chemical attributes on productive potential. We used dominant height, age and geographic coordinates data from plots during five evaluations in clonal teak plantations of different ages. We performed the classification of the forest sites by the guide-curve method. The principal components analysis was used to group the forest stands according to soil chemical attributes (available P and exchangeable K, Na and Mg). The spatial variability analysis of productive capacity was carried out through geoestatistics. The results show that the productive capacity has spatial dependence. The exponential model has provided the best estimates of dominant height, revealing that 69.2% of the mapped area was from medium and 30.8% from high productive capacity. The multivariate analysis showed that soil fertility has influenced the productive capacity, discerning the most productive sites, in agreement with the soil quality. The geostatistical technique was efficient to estimate the productive capacity in unsampled areas, revealing sites with different productive potentials and their response to edaphic factors. This may assist in the efficient management of planting, when establishing silvicultural actions in specific locations, which are identified in the planted area maps, reducing the management costs.

A longitudinal functional connectivity comprehensive index for multi-sluice flood control system in plain urban river networks

• Dynamic quantification of hydrological function connectivity in complex river network is solved. • A new quantitative indicator of longitudinal functional connectivity is established. • The Longitudinal Functional Connectivity Comprehensive Index of Changzhou city is obtained. In the process of urbanization development, human activities have a great impact on rivers because of social and economic demands, which directly or indirectly lead to changes in the structure and function of river networks, thus making hydrological patterns tend to be chaotic and ecological environment deteriorates. In order to clarify the hydrological connectivity change mechanism of plain urban river network, the main urban area of Changzhou was taken as the study area, the Longitudinal Functional Connectivity Comprehensive Index (LFCCI) was defined. The results of temporal and spatial variation analysis of LFCCI in the study area showed that the average LFCCI in the main urban area was 1.34. Among them, the average LFCCI in flood season (May to August) were higher than those in non-flood season, the maximum and minimum values of LFCCI were 1.7 (May) and 0.63 (December) respectively, indicating that the scheduling of stations in flood season was more complex. Meanwhile, the average LFCCI of Jiuli station was the highest (2.95) and Wujin station was the lowest (0.30). However, further analysis showed that Weicun, Zaogang and Xiaohe sluices were important stations that affect the LFCCI in the study area. The evaluation method solved the problem of hydrological connectivity evaluation under the background of complex dispatching rules, and it provided important technical support for river network connection project and water environment improvement.

Study on the Scale Effect of Spatial Variation in Soil Salinity Based on Geostatistics: A Case Study of Yingdaya River Irrigation Area

Soil salinization seriously restricts the development of agricultural economies in arid and semi-arid areas. Mastering the spatial variability characteristics of multi-scale soil salt in irrigated areas is of great significance for the improvement and utilization of saline soil and agricultural production. The middle and lower reaches of the Yingdaya River were selected as the study area, and the irrigation area was divided into three scales: the L scale (irrigation area), the M scale (township level) and the S scale (village level). A total of 131 data sets were obtained through field investigations and sampling, and the spatial variability characteristics and scale effects of the soil salt in multi-scale irrigated areas were analyzed using classical statistics, geostatistics and nested model methods. The results showed that the average soil salinities at the L, M and S scales were 1.664%, 0.263% and 0.217%, respectively, and the coefficients of variation were 2.564, 1.312 and 0.866, respectively. The soil salinities at different scales exhibited moderate spatial correlation and anisotropic characteristics, through which, the maximum variation directions for L and M were 113° and 139°, respectively, and the maximum variation direction of the S scale was 86°. The spatial distribution of the soil salinity is affected by the scale effect, but the accuracy of spatial estimations can be effectively improved by using a multi-scale nested model for interpolation. The high-value areas of soil salt in the irrigation areas were distributed in the southeastern regions of the study area, and weakened in small areas around the high-value areas. The influence of each influencing factor on the soil salinization at different scales also differed. Except for the slope, the correlations between other influencing factors and the soil salt content gradually decreased with decreases in the scale. This study provides a concise summary of the spatial variation analysis of soil characteristic variables, and also provides a scientific basis for the formulation and implementation of salinization control programs.

Analysis of Spatial Variability of Plough Layer Compaction by High-Power and No-Tillage Multifunction Units in Northeast China

In this study, we addressed the problem of the spatial variability of plough layer compaction by high-power and no-tillage multifunction units in the management of maize planting in the Great Northern Wilderness in China. A comprehensive field experiment involving high-power and no-tillage multifunction units for 165 acres of maize was conducted and analyzed using GIS. Firstly, the test area was divided into four areas, and points were set at equal horizontal distances to collect data on the compactness, water content, porosity and fatigue of the plough layer at different depths. Secondly, the GIS kriging difference method was used to analyze the impact of longitudinal compaction of the plough layer profile at each depth in different test areas. Thirdly, the GIS kriging difference method was used to analyze the lateral spatial distribution of plough layer compaction. Finally, the spatial longitudinal and transverse variabilities of the plough layer were summarized, and the effect of the high-power and no-tillage multifunction units on the physical ecology of the soil in the plough layer was investigated. The results show that the physical properties of the plough layer can be significantly affected by compaction after spreading in the middle tillage period. The surface soil was most affected, with the greatest change in compactness and porosity; the rate of change of soil compactness reached 143.49% and the rate of change of soil porosity reached 40.57%. With the increase in soil depth, the rate of change of soil compactness and porosity gradually decreased. The greatest variation in soil moisture content was found in the middle layer and reached a maximum of 13.78% at a depth of approximately 20 cm. The results of the spatial variability analysis show that the mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity of the tilled soil in the longitudinal space of each test area before compaction were approximately 15%, 19% and 20%, respectively; after compaction, the mean values were approximately 33%, 23% and 30%, respectively; the mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity change of the tilled soil were approximately 24%, 14% and 12%, respectively. The mean values of c0/(c0 + c) for the spatial semi-variance functions of compactness, water content and porosity of the soil at each depth in the lateral space before compaction were approximately 80%, 71% and 78%, respectively, and after compaction the mean values were approximately 40%, 23% and 24%, respectively, with the mean values of c0/(c0 + c) along the east–west direction being approximately 8%, 27% and 18%, and the mean values of c0/(c0 + c) along the north–south direction being approximately 9%, 0% and 20%. The results show that compaction by high-power and no-tillage multifunction units led to a decrease in the spatial variability of soil physical parameters at each depth of tillage in the black soil layer in the longitudinal space, while the spatial variability of the soil physical parameters at each depth of tillage in the black soil layer in the transverse space increased. Moreover, the degree of influence of compaction by high-power and no-tillage multifunction units on soil physical parameters was higher in both vertical and horizontal spaces. This study can provide a theoretical reference for the analysis of the impact of large units on the compaction of black soil layers from the perspective of GIS.

Biochemical properties of different species of seaweeds (Grateloupia) from the Indian coast and analysis of spatial variation in two selected species

Aim: The present study aimed to investigate the biochemical composition of five Grateloupia species and analysis of spatial variation in G. filicina and G. lithophila from the East and West coast of India. Methodology: Five Grateloupia species such as G. filicina, G. lithophila, G. catenata, G. orientalis and G. indica were collected from different states of India. Biochemical parameters like crude protein, total lipid, total ash, carbohydrates, total dietary fibre, chlorophyll, carotenoids, and total phenolic content were estimated to assess their nutritional values. Spatial variation for same parameters was also studied for G. filicina and G. lithophila. Results: It was observed that genus Grateloupia contained crude protein (12.4-16%), total lipid (0.61-1.47%), ash (11.49-18.03%), carbohydrate (5.17-17.21%), and total dietary fibre (54.08-66.16%) on a dry weight basis. Among all species, G. indica (16.00%) and G. filicina (15.48%) consisted of higher protein content. In contrast, G. orientalis (66.16%) and G. catenata (61.25%) had a maximum of total dietary fibre. The digestible energy obtained from Grateloupia was high, ranging from 85.93-141.29 kcal. Carotenoids (9.52-32.10 mg 100g-1) and total phenolic contents (TPC) (0.508-0.696 mg GAE g-1) represented the potential antioxidant activities of these Grateloupia species. Spatial variation in the biochemical composition of G. filicina and G. lithophila may be due to changes in the environmental factors. Interpretation: Biochemical compositions of these five species were similar to other edible Grateloupia species like G. turuturu and G. filicina. The results revealed that these species could be used for consumption purposes. Key words: Fibre, Grateloupia, Nutritional property, Phenols, Species, Spatial variation

High-resolution estimation of air pollutant emissions from vegetation burning in China (2000–2018)

Vegetation burning in China contributes significantly to atmospheric pollution and climate change. However, most recent studies have focused on forest fires, ignoring grassland fires. Besides, there was a generally high uncertainty in the estimated fire emission because of missing small fire data and limited local vegetation data. This study employed high-resolution burned area data (GABAM, global annual burned area map) and land cover data to develop a high-resolution (30 m) emission inventory of vegetation burning in China in 2000, 2005, 2010, 2015, and 2018. Eleven pollutants were estimated, including CO, CH4, NOx, non-methane volatile organic carbon (NMVOC), SO2, NH3, PM2.5, PM10, organic carbon (OC), black carbon (BC), and CO2. The cumulative pollutant emissions from the temporal and spatial variation analyses of the burned area and emissions reached 1.21 × 105 Gg. Specifically, CO2 was the largest emission, with a mean annual emission of 2.25 × 104 Gg, accounting for 92.46% of the total emissions. CO was the second-largest emission, with a mean annual emission of 1.13 × 103 Gg. PM10 and PM2.5 emissions were also relatively high, with a mean annual emission of 200.5 and 140.3 Gg, respectively, with that of NMVOC (159.24 Gg) in between. The emissions of other pollutants, including OC, NOx, CH4, NH3, SO2, and BC, were relatively low. The South, Southwest, East, and Northeast of China contributed the most emissions. Shrubland contributed the most emissions for different vegetation types, followed by forest and grassland. Consequently, this study provides scientific evidence to support understanding the influence of fire on the local environment and policy on China’s air pollution control.

Analysis of Spatial and Temporal Variations of the Near-Surface Wind Regime and Their Influencing Factors in the Badain Jaran Desert, China

Wind regime is one of the main natural factors controlling the evolution and distribution of aeolian sand landforms, and sand drift potential (DP) is usually used to study the capacity of aeolian sand transport. The Badain Jaran Desert (BJD) is located where polar cold air frequently enters China. Based on wind data of eight nearby meteorological stations, this research is intended to explore the temporal variation and spatial distribution features of wind speed and DP using linear regression and cumulative anomaly method, and reveal the relationship between atmospheric circulation and wind speed with correlation analysis. We found that the wind speed and frequency of sand-blowing wind in the BJD decreased significantly during 1971–2016, and the wind speed obviously mutated in 1987. The regional wind speed change was affected by the Asian polar vortex, the northern hemisphere polar vortex and the Tibet Plateau circulation. The wind rose of the annual sand-blowing wind in this region was the “acute bimodal” type. Most of the annual wind directions clustered into the W-NW, and the prevailing wind direction was WNW. During 1971–2016, the annual DP, the resultant drift potential (RDP) and the directional variability (PDP/DP) in the desert showed an obvious downtrend, with a “cliff-like” decline in the 1980s and relative stable fluctuation thereafter. The BJD was under a low-energy wind environment with the acute bimodal wind regime. Wind speed, sand-blowing wind frequency and DP were high in the northeast and low in the southwest.

Large-scale spatial variability in loess landforms and their evolution, Luohe River Basin, Chinese Loess Plateau

Loess landform variability across large spatial extents needs to be analyzed to understand the formation and evolution of loess landscapes. This is becoming increasingly possible via the automated analysis of remotely-sensed data. Here, we quantify loess landforms using an object-based image analysis (OBIA) method and use this classification to describe the spatial variability of loess landforms. Quantitative indicators are used to drive the spatial variability analysis of loess landforms and explain their spatio-temporal evolution. Moreover, the hypsometric integral (HI) and topographic interpolation are employed to investigate soil erosion and development patterns of loess landscape. Results show that the OBIA method classified loess landforms to an accuracy of 88.7 %. The derived metrics in terms of the area, slope and complexity of landform shape allow the determination of the spatial structure of the loess landscapes. The HI value of the entire basin is 0.486, representing the mature stage of landform development, with relatively severe surface erosion. Correlation analysis of HI values and related indicators in the sub-basins shows that HI is poorly correlated with the area proportion of loess landform types and the total erosion volume in the basin but shows a relatively strong correlation with the volume of erosion per unit area.

Spatiotemporal Evolution Characteristics of Urbanization in the Xiamen Special Economic Zone Based on Nighttime-Light Data from 1992 to 2020

In China and elsewhere, urban expansion is directly related to the important issues of social development, economic development, and the sustainable development of the ecological environment. Traditional statistical methods based on administrative regions lack geospatial information, which makes it difficult to analyze and explore in detail the development status and spatial differences of cities. In real time, nighttime light (NTL) remote sensing can reveal the spatial expansion change information of urban built-up areas (UB) on different scales, thus allowing for the analysis of urban spatial patterns and variations in urban development. Based on the long-time sequence NTL data from 1992 to 2020, this work studies the Xiamen Special Economic Zone by using the vegetation-water-adjusted NTL urban index (VWANUI) to extract the urban built-up areas and study the UB expansion patterns, the migration of the urban center of gravity, and intra-city differences. The result is a qualitative and quantitative temporal and spatial evaluation of Xiamen’s economic development characteristics. The results show that the UB of Xiamen expanded 349.219 km2 from 1995 to 2020, mainly concentrated in the period 2005–2020, during which time 79.44% of the expansion of the whole study period occurred. Throughout the study period, the urban center of gravity of Xiamen city shifts 8757.15 m to the northeast at the rate of 350.29 m/year in the direction of 74.88° (the urban center of gravity shifted from the inner island to the outer island). The total brightness of nighttime lights in Xiamen is gradually increasing, indicating that the level of urban economic development continuously improved over the measurement period, that human social activities have strengthened, and that the cross-island development strategy has produced certain results. These results provide data that describe urban development and policy formulation in Xiamen.

Multi-perspective analysis on rainfall-induced spatial response of soil suction in a vegetated soil

In this study, an intelligent monitoring platform is established for continuous quantification of soil, vegetation, and atmosphere parameters (e.g. soil suction, rainfall, tree canopy, air temperature, and wind speed) to provide an efficient dataset for modeling suction response through machine learning. Two characteristic parameters representing suction response during wetting processes, i.e. response time and mean reduction rate of suction, are formulated through multi-gene genetic programming (MGGP) using eight selected influential parameters including depth, initial soil suction, vegetation- and atmosphere-related parameters. An error standard–based performance evaluation indicated that MGGP has appreciable potential for model development when working with even fewer than 100 data. Global sensitivity analysis revealed the importance of tree canopy and mean wind speed to estimation of response time and indicated that initial soil suction and rainfall amount have an important effect on the estimated suction reduction rate during a wetting process. Uncertainty assessment indicated that the two MGGP models describing suction response after rainfall are reliable and robust under uncertain conditions. In-depth analysis of spatial variations in suction response validated the robustness of two obtained MGGP models in prediction of suction variation characteristics under natural conditions.

Analysis of Spatial and Vertical Variability of Environmental Parameters in a Greenhouse and Comparison of Carbon Dioxide Concentration in Two Different Types of Greenhouses

Analysis of Spatial and Vertical Variability of Environmental Parameters in a Greenhouse and Comparison of Carbon Dioxide Concentration in Two Different Types of Greenhouses

Assessing drivers of intra-seasonal grassland dynamics in a Kenyan savannah using digital repeat photography

Understanding grassland dynamics and their relationship to weather and grazing is critical for pastoralists whose livelihoods depend on grassland productivity. Studies investigating the impacts of climate and human factors on inter-seasonal grassland dynamics have focused mostly on changes to vegetation structure. Yet, quantifying the impact of these on the inter-seasonal dynamics of specific grassland communities is not known. This study uses digital repeat photography to examine how intra-seasonal grassland dynamics of different grassland communities are affected by precipitation, temperature, and grazing in a heterogeneous semi-arid savannah in Kenya. A low-cost digital repeat camera network allowed for fine-scale temporal and spatial variability analysis of grassland dynamics and grazing intensity. Over all grass communities, our results show precipitation driving mainly early-season and in some cases mid-season flushing, temperature driving end-of-season senescence, and grazing influencing mid-season declines. Yet, our study quantifies how these three drivers do not uniformly impact grassland species communities. Specifically, Cynodon and Cynodon/Bothriochloa communities are rapidly and positively associated with precipitation, where mid-season declines in Cynodon communities are associated with grazing and late-season declines in Cynodon/Bothriochloa communities are associated with temperature increases. Setaria communities, on the other hand, have weaker associations with the drivers, with limited positive associations with precipitation and grazing. Kunthii/Digitaria diverse communities had no association with the three drivers. Highly diverse mixed communities were associated with increased precipitation and temperature, as well as lower intensity grazing. Our research sheds light on the complex interactions between plants, animals, and weather. Furthermore, this study also demonstrates the potential of digital repeated photography to inform about fine-scale spatial and temporal patterns of semi-arid grassland vegetation and grazing, with the goal of assisting in the formulations of management practises that better capture the intra-annual variability of highly heterogeneous dryland systems.

Analysis of sanitation and waterborne disease occurrence in Ondo State, Nigeria

Waterborne diseases (i.e., diarrhea, dracunculiasis, dysentery, typhoid fever, malaria, scabies, ringworm, cholera, hepatitis B, streptococci, and onchocerciasis) are linked to a significant disease burden worldwide. This work has thus established a relationship between access to improved sanitation, potable water supply, and waterborne disease occurrence in Ondo State, Nigeria, by analyzing the data sourced from the Federal Ministry of Water Resources, Federal Republic of Nigeria. The results showed that there was water scarcity (< 42% access) in the southern part of Ondo State. There was inadequate access to improved sanitation (< 30% access) in both the southern and northern parts of the State. Meanwhile, Southern Ondo State had the highest (> 320%) prevalence of waterborne diseases. There also existed a negatively moderate correlation: a substantial relationship between the access to a potable water supply (APW) (%) and the occurrence of waterborne diseases (WBD) (%) in Ondo State and between the occurrence of WBD (%) and improved sanitation (IS) (%) in the State. There existed a low correlation: definite but small relationship between the percentage of people with APW and the percentage of people with IS (%). This study has used the multiple linear regression model to develop a relationship equation using WBD as a dependent variable and APW and IS as independent variables. The first twelve elements (or LGAs) of Ondo State were used for modeling, while the last six were used to validate the results obtained. Equations generated were validated through residuals by observing the conditions of homoscedasticity, normality, and autocorrelation. The Nash–Sutcliffe efficiency was estimated to be about 80%. The spatial variability analysis was also done using inverse distance weighting. Therefore, it can be said that the modeled equation was quite good in predicting past and future waterborne diseases in Ondo State.

Estimation of B-Value Variation as Earthquake Precursor in Java Region with Maximum Likelihood Method

Java Island is one of the areas with a population density of 1,171 people/km2, which is relatively high compared to other regions in Indonesia. The tectonic setting of the Java region is affected by the interaction of tectonic plate subduction between the Indo-Australian Plate and the Eurasian Plate which moves at the rate of 67 mm/year. In addition, the presence of several active faults on Java Island also contributes to the tectonic setting. The implication of this setting is a relatively high level of potential earthquake events and some of them are destructive earthquakes. The estimation of b-value variations by using Gutenberg-Richter Equation plays an important role in estimating the occurrence of earthquakes. The aims of this study are to determine the role of spatial and temporal variations of b-value as earthquake precursors on Java Island. In this research, earthquakes analysis was carried out in the form of spatial and temporal variations of b-value from earthquake catalog data in 1900-2016 for the Java Island region. Based on the estimation of earthquake recurrence time for magnitude 6.5, 7, and 7.5, and also the analysis of spatial variation of b-value shows the areas with the potential for significant earthquakes in the west and eastern part of Java region. In addition, our result also obtains the existence of a seismic gap zone in the southern part of Central Java.

Analysis of Residential Function Spatial Variation of the City of Rwandz

One of the most fundamental human requirements is a place to live. Through a variety of architectural and socio-economic factors, this role became a significant function that cities provide and an essential feature that caught the interest of urban scholars. The paper aims to disclose the spatial variation of the characteristics of the Rwandz city's residential function by utilizing a questionnaire, statistical analysis, and GIS tools to classify the residences into areas within the city and evaluate and clarify the specific aspects of each region. Besides, using a suitability model to select the best residential locations in the city. The paper was separated into three major sections: the study area, methods, and results and discussion. The paper was able to classify Rwandz city into four residential regions: the old and dilapidated houses region, which occupies 10% of the total housing units; and the regions of medium-quality houses, good-quality houses, and layout houses, with percentages of 43.8%, 36%, and 10.2%, respectively. The paper tested the correlation between the criteria to determine the spatial relationships of the residential function, it found that the central parts of the city differ from the relatively newer periphery, in terms of residential characteristics. Through the suitability model, the highly suitable categories do not live up to acceptable levels, it occupies 7.3% of the city. In addition, the paper found that the levels of suitability do not match the reality of land values in many areas of the city.