Urbanization and Long-Term Forest Dynamics in a Metropolitan Region of Southern Europe (1936–2018)

Although peri-urban landscapes in Southern Europe still preserve a relatively high level of biodiversity in relict natural places, urban expansion is progressively consuming agricultural land and, in some cases, forest cover. This phenomenon has (direct and indirect) environmental implications, both positive and negative. The present study contributes to clarifying the intrinsic nexus between long-term urban expansion and forest dynamics in a representative Mediterranean city based on diachronic land-use maps. We discuss some counterintuitive results of urbanization as far as forest expansion, wildfire risk, and biodiversity conservation are concerned. Forest dynamics were investigated at two time intervals (1936–1974 and 1974–2018) representing distinctive socioeconomic contexts in the Rome metropolitan area in Central Italy. Additionally, the spatial relationship between forest cover and urban growth was evaluated using settlement density as a target variable. All over the study area, forest cover grew moderately over time (from 18.3% to 19.9% in the total landscape), and decreased along the urban gradient (i.e., with settlement density) more rapidly in 2018 than in 1936. The diversification of forest types (Shannon H index) was higher in areas with medium-density settlements, indicating a tendency towards more heterogeneous and mixed structures in rural and peri-urban woods that undergo rising human pressure. The dominance of a given forest type (Simpson’s D index) was higher at high settlement density areas. Evenness (Pielou’s J index) was the highest at low settlement density areas. The long-term assessment of land-use dynamics in metropolitan fringes enriched with a spatially explicit analysis of forest types may inform regional planning and environmental conservation, which could delineate appropriate strategies for sustainable land management in Southern European cities.

Mitigasi Penyebaran Covid-19 Melalui Pemetaan Kepadatan Pemukiman, Mobilitas Penduduk dan Lingkungan Kelurahan Kadia Kota Kendari

Abstrak: Isu pandemi Covid-19 menjadi perhatian dunia dan sampai saat ini belum diprediksi kapan akan berakhir. Penyebaran Covid-19 merubah pola interaksi dalam kurun waktu yang cepat dan drastis karena adanya pemberlakukan pembatasan pergerakan dan kegiatan manusia. Kota Kendari termasuk daerah yang terdampak penyebaran Covid-19 dan salah satu kelurahan yang terdampak dengan status zona merah adalah kelurahan Kadia. Dalam mengantisipasi penyebaran Covid-19 di kelurahan Kadia, perlu dilakukan mitigasi melalui pemetaan kepadatan pemukiman, mobilitas penduduk dan lingkungan. Tujuan kegiatan ini adalah melakukan mitigasi penyebaran Covid-19 melalui pemetaan kepadatan pemukiman, mobilitas penduduk dan lingkungan kelurahan Kadia. Metode yang digunakan dalam penelitian ini adalah survey dan overlay peta. Hasil penelitian menunjukan kepadatan pemukiman di kelurahan Kadia pada tingkat yang tinggi (25-34) pada RW 002, RW 007 dan RW 008. Kepadatan penduduk di kelurahan Kadia yang tinggi pada (62-92) pada RW 001 RT 002, RW 002, RW 007 RT 001 dan 003, RW 008 RT 003, dan RW 009 RT 003. Tingkat mobilitas penduduk dikelurahan Kadia yang tinggi (90-174) pada RW 002 RT 002, RW 003 RT 001 dan 002, RW 004 RT001, 002 dan 003, RW 005 RT 001, RW 006 RT 001, dan RW 007. Secara spasial kondisi lingkungan kelurahan Kadia didominasi oleh lahan terbangun dengan jumlah penduduk sebanyak 7775 jiwa. Berdasarkan hasil pemetaan kepadatan pemukiman, kepadatan penduduk, mobilitas penduduk dan lingkungan maka mitigasi tingkat potensial penyebaran Covid-19 di kelurahan Kadia difokuskan pada titik potensial yang tinggi (RW 002) dan titik potensial yang sedang (RW 007). Beberapa langkah mitgasi penyebaran Covid-19 yang dilakukan adalah memasang poster mitigasi penerapan protokol kesehatan dengan memakai masker, selalu mencuci tangan dengan sabun dan menjaga jarak.Kata kunci : Mitigasi, Pandemi Covid-19, Pemetaan, Kelurahan Kadia Abstract: The issue of the Covid-19 pandemic has become a worldwide concern and until now it has not been predicted when it will end. The spread of Covid-19 changed the pattern of interaction in a fast and drastic period due to the imposition of restrictions on human movement and activities. Kendari City is one of the areas affected by the spread of Covid-19 and one of the ward affected by the red zone status is Kadia Ward. In anticipating the spread of Covid-19 in the Kadia sub-district, it is necessary to carry out mitigation through mapping the density of settlements, population mobility, and the environment. The purpose of this activity is to mitigate the spread of Covid-19 through mapping the density of settlements, population mobility, and the Kadia urban village environment. The method used in this research is survey and map overlay. The results showed that the density of settlements in the Kadia village was at a high level (25-34) in RW 002, RW 007, and RW 008. The population density in the Kadia ward was high at (62-92) in RW 001, RT 002, RW 002, RW. 007 RT 001 and 003, RW 008 RT 003, and RW 009 RT 003. The level of population mobility in Kadia kelurahan is high (90-174) in RW 002 RT 002, RW 003 RT 001 and 002, RW 004 RT 001, 002 and 003, RW 005,RT 001, RW 006, RT 001, and RW 007. Spatially, the environmental condition of the Kadia ward is dominated by built-up land with a population of 7775 people. Based on the results of mapping settlement density, population density, population mobility, and the environment, mitigation of the potential level of Covid-19 spread in the Kadia ward is focused on high potential points (RW 002) and medium potential points (RW 007). Some of the steps to mitigate the spread of Covid-19 were putting up a mitigation poster for the implementation of the health protocol by wearing a mask, always washing hands with soap, and keeping a distance.Keywords : Mitigation, Covid-19 Pandemic, Mapping, Kelurahan Kadia

Analysis of the Spatial Distribution of Settlements of Red Wood Ants in the Baikal Region

Outbreaks of defoliating insects constantly emerge and spread in the heavily forested Baikal region. Biological control is the approach of choice in pest management, and red wood ants are used to control defoliating insects at their outbreak sites. The purpose of the present paper is to choose the forest plots with complexes of red wood ant nests in the Baikal region and to estimate the level of protection of these plots from defoliating insects using hybrid geoinformation system (GIS). The Institute for System Dynamics and Control Theory SB RAS geoportal (http://geos.icc.ru) is the hybrid GIS. During fieldwork, 101 nests of F. aquilonia Yarr. and 20 nests of F. lugubris Zett. were found. One hundred and two nests (88 F. aquilonia nests and 14 F. lugubris nests) formed nest complexes and were located on 18 forest plots. Two parameters were used to estimate protection level of forest plots from defoliating insects: the average number of nests per 1 hectare (settlement density) and the total area of dome bases of all anthills located on 1 hectare (power of the nest complex). The research revealed that only four forest plots (“Uzury”, “Khalgay”, “Onguren_2”, and “Onguren_3”), situated in the mountain taiga pine landscape, were protected from defoliating insects (settlement density ≥5 nests/ha and power of nest complex >6 m2/ha). Besides, the complex of nests in the “Onguren_2” forest plot can be a source for capture of filial nests. The “Arshan_2” forest plot, situated in the mountain taiga dark coniferous landscape of reduced development, had the lowest density of settlements of ants (less than two nests per hectare). The state-of-the-art hybrid GIS is a tool that can be used to quickly and efficiently discover and analyze the spatial distribution of settlements of red wood ants

GIS als Hilfsmittel zur Analyse räumlicher Strukturen im östlichen Sachsen und Thüringen des 10. und frühen 11. Jahrhunderts: Eine Königslandschaft neu betrachtet

For some time, the use of GIS in the context of medieval studies has been increasing. Aside from providing opportunities to visualise historical data in an uncomplicated way, GIS offers numerous tools such as viewshed, kernel density estimation or georeferencing, allowing new insights into historical contexts, which at the same time can reveal new avenues for research. This paper illustrates both the potential and difficulties of working with GIS on the analysis of spatial structures in early medieval Eastern Saxony and Thuringia. The main outcomes are a very high settlement density in the entire investigation area, with special concentrations in the eastern Harz foreland, the Hassegau, as well as a rapid and early expansion of the Harz Mountains.

Spatial features of settlement network within physical­geographical regions of the Prut upper basin

The territorial characteristics of settlement network per quantitative and settlement indicators within 35 physical and geographical areas of the upper basin of the Prut were analyzed: the number of settlements, settlement density and coefficient of uniformity of placing settlements. The regions of the insufficient development of the network of settlements and areas with their excessive were allocated. Key words: settlement network, physical, geographical area, settlement, settlement density.

Making time work: sampling floodplain artefact frequencies and populations

The expansion of large-scale excavation in Britain and parts of Continental Europe, funded by major development projects, has generated extensive new datasets. But what might we be losing when surfaces are routinely stripped by machines? Investigation by hand of ploughsoils and buried soils in the Fenlands of eastern England reveals high densities of artefacts and features that would often be destroyed or overlooked. These investigations throw new light on the concept of site sequences where features cut into underlying ground may give only a limited and misleading indication of the pattern and timing of prehistoric occupation. The consequential loss of data has a particular impact on estimates of settlement density and population numbers, which may have been much higher than many current estimates envisage.