Identification of Spatial Clusters of COVID-19 in Yogyakarta using Moran’s Index

Various studies on the spreading pattern of COVID-19 were carried out because, every day, there are always new progresses from scientists about this virus, including its unique characteristics in each region with different geographical conditions. The objective of this research is to find the spatial distribution pattern of COVID-19 and to identify the climate parameters influencing it in the Yogyakarta. This study used Moran's Index in analyzing COVID-19 distribution pattern. The results of the analysis show that out of 5 regencies/cities in Yogyakarta, Sleman Regency has the highest average spread of COVID-19 or an average infection rate of 1.09, followed by Bantul with 0.75. Kulonprogo is the regency with the lowest number of cases. The result of Moran's index of 0.32 means that there are correlation between cases.The correlation between temperature and infection rate is R2 = 0.05, while the correlation between humidity and infection rate is R2 = 0.003. The spread of COVID-19 in Yogyakarta is more influenced by mobility or interactions between infected and uninfected individuals.

Indeks Pembangunan Berkelanjutan Lokal dan Sebaran Spasialnya di Kabupaten Mandailing Natal, Provinsi Sumatera Utara

The concept of sustainable development is very important to increase our quality of life. Measurement of development based on specific indicators is one of the approaches to describe sustainable development. At the local level, measuring sustainable development using specific indicators is still rare. Since each location has their own unique characteristics, measuring sustainability at the regional level could not always be applied locally. The availability of data at the village level strongly encourages the local measurement of sustainable development index. The economic, social, and environmental dimensions of Mandailing Natal Regency's development are still constrained. Using 21 variables that can reflect economic, social, and environmental aspects, this study aims to measure the sustainable development index at the local level. The Local Sustainable Development Index will be generated by analyzing these variables using the Factor Analysis (FA) method and Local Indicator of Spatial Autocorrelation (LISA) analysis. This index measurement is useful in considering the direction of location-based (spatial) development for decision makers at the local level and describe development sustainability. In general, IPBL economic value was in the medium category in 2011, and several villages in the low category were able to enhance their economic development sustainability in 2018. In the northwest, IPBL environment cluster type High-high (HH). In 2018, the percentage spatial distribution pattern of villages with the Low-low (LL) cluster type of IPBL economic and IPBL environment decreased. However, as can be seen from the spatial distribution pattern of IPBL social with cluster type LL, the percentage increased in 2018.

How soil abiotic factors affect the population fluctuation of Leitneria pugio (Acari: Mesostigmata: Halolaelapidae)

Abiotic factors, such as temperature, humidity, soil elements, along with biotic factors affect terrestrial arthropod communities. Since the application of agricultural fertilizers with the entrance of different elements causes changes in the soil physicochemical conditions, fertilizers may cause fluctuation in the population density of edaphic arthropods. Given this opinion, in this research, the effect of common fertilizers on the population fluctuation and distribution pattern of the predatory mite Leitneria pugio (Karg) was investigated. The experimental treatments were granular urea fertilizer with two doses (200 and 400 kg per ha), poultry manure, zinc sludge (to simulate the accumulation of zinc sulfate fertilizer in the soil), and control in five blocks. Humidity, pH, temperature, NO3– and NO2–, and elements (organic Carbon, K, Na, P, Fe, Cu, Pb, Cr, Cd, Ni, Zn, and As) of soil were measured, and their relationship with the predatory mite population was determined by Pearson correlation coefficient. Iwao's patchiness, Taylor's power law, and Morisita's coefficient of dispersion were used for determining the spatial distribution pattern of L. pugio. The spatial pattern of L. pugio was aggregated, and the highest population density of the predator was observed in December in zinc sludge and control treatments, and in May, in zinc sludge treatment, on the average 60, 35, and 110 per m2, respectively. The relationship between mite's population and Cu and Pb was significantly positive, and L. pugio had a significantly negative relationship with P, NO3– and soil temperature. Nevertheless, the application of different fertilizers did not affect the spatial distribution pattern of the predator.

Occurrence patterns of crop-foraging sika deer distribution in an agriculture-forest landscape revealed by nitrogen stable isotopes

Conflicts arising from the consumption of anthropogenic foods by wildlife are increasing worldwide. Conventional tools for evaluating the spatial distribution pattern of large terrestrial mammals that consume anthropogenic foods have various limitations, despite their importance in management to mitigate conflicts. In this study, we examined the spatial distribution pattern of crop-foraging sika deer by performing nitrogen stable isotope analyses of bone collagen. We evaluated whether crop-foraging deer lived closer to agricultural crop fields during the winter and spring, when crop production decreases. We found that female deer in proximity to agricultural crop fields during the winter and spring were more likely to be crop-foraging individuals. Furthermore, the likelihood of crop consumption by females decreased by half as the distance to agricultural crop fields increased to 10 km and fell to essentially zero at a distance of approximately 40 km. We did not detect a significant trend in the spatial distribution of crop-foraging male deer. The findings of spatial distribution patterns of crop-foraging female deer will be useful for the establishment of management areas, such as zonation, for efficient removal of them.

Seasonal Monitoring Of Chlorophyll-A With Landsat 8 Oli In The Madura Strait, Pasuruan, East Java, Indonesia

Chlorophyll-a (Chl-a) is a type of pigment is most common and predominant in all oxygen-evolving photosynthetic organisms such as higher plants, red and green algae. The concentrations of high chlorophyll-a (Chl-a) in coastal waters tend to be lower offshore due to land through river water runoff. The Madura Strait is one of the Indonesian basins that is widely used for fisheries activity, which directly impacts and puts quite high pressure on the aquatic resources. In addition, the development of urban areas and changes of land use in the hinterland areas of East Java Province due to increasing population are also intensive. The objectives of this research were: (1) to map the distribution of chlorophyll-a, its concentration and dynamics in the Madura Strait near the Pasuruan coastal area using remote sensing for both dry and rainy seasons, (2) figure out the influence of rivers or other oceanographic factors that may occur, and (3) calculate the accuracy of the estimation compared to the field data. The Landsat 8 OLI imagery was used to determine the concentration of Chl-a and analyze its seasonal spatial distribution pattern. The results show that (1) spatial distribution of chlorophyll-a (Chl-a), its concentration and dynamics in the Madura Strait waters near the Pasuruan coastal area varies between dry and rainy months or seasons, (2) input from rivers, waves, tidal level, and eddy circulation constitute the oceanographic parameters that influence the spatial distribution pattern of chlorophyll-a (Chl-a) in the Madura Strait waters near the Pasuruan coastal area, and (3) validation of the estimated Chl-a concentrations from Landsat 8 OLI using field data has shown RMSE value of 0.49.

Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China

Sports tourism is an emerging tourism product. In the sports and tourism industry, resource mining is the foundation that provides positive significance for theoretical support. This study takes China’s sports tourism boutique projects as the study object, exploring its spatial distribution pattern through the average nearest neighbor index, kernel density, and spatial autocorrelation. On the strength of the wuli–shili–renli system approach, the entropy value method and geographic detector probe model are used to identify the driving factors affecting the spatial distribution pattern. Findings reveal the following: (1) From 2013 to 2014, the sports tourism resources in China present a distribution pattern with the Yangtze River Delta urban agglomeration as the high-density core area and the Guizhou–Guangxi border area and the western Hubei ecological circle as the sub-density core areas. (2) From 2014 to 2018, China’s sports tourism boutique projects increased by 381, and the regional differences among various provinces tended to converge. The high-density core area remained unchanged. The sub-density cores are now the Yunqian border area of the Karst Plateau, the Qinglong border area of the Qilian Mountains, and the Jinji border area of the Taihang Mountains, shaping the distribution trends of “depending on the city, near the scenery” and “large concentration, small dispersion”. (3) The proportion of provincial sports tourism development classified as being in the coordinated stage is 61.29%. (4) The explanatory power of the factors affecting the spatial layout in descending order is natural resource endowment, sports resource endowment, transportation capacity, industrial support and guidance, market cultivation and development, people’s living standards, software and hardware services, and economic benefit effects. The explanatory power of the interaction of two different factors is higher than that of the single factor.