Pakistan has experienced significant urbanization, characterized by rapid urban population growth and unplanned urban expansion, making it the most urbanized country in South Asia. This study focuses on Lahore, the secondlargest megacity of Pakistan, and evaluates land cover changes over the last three decades (1990-2020). It also analyzes the relationship between urban green landscapes and unregulated urban expansion. The study reveals significant changes in the ecology of Lahore’s urban landscape using Landsat imagery, including Landsat 5 TM, Landsat 8 OLI, and a 30m spatial resolution, along with population data from the Pakistan Bureau of Statistics. In particular, the study reveals a decline in urban green spaces and a significant expansion of urban built-up areas in Lahore. The annual urban area expansion rates were 24.2 km2 (1990- 2000), 12.1 km2 (2000-2010), and 26.4 km2 (2010-2020), while vegetation cover decreased 33.45 km2 (1990-2000), 20 km2 (2000-2010) in the first two decades but slightly increased from 2010 to 2020 at an annual rate of 14.17 km2. As a result, there is a serious concern about the rapid decline of green space in Lahore. It is recommended that the administrative authorities follow the World Health Organization’s guidelines regarding the need for green spaces. This study contributes to achieving the United Nations’ Sustainable Development Goal 11th, indicator 11.3.1, and provides guidelines for conserving natural, social, and economic resources in the face of rapid urbanization.

The volcanoes of Kamchatka are a World Heritage Site. They are of aesthetic, conservation, and scientific value; therefore, they must be protected from negative anthropogenic influences. However, according to the recent assessment by the International Union for Conservation of Nature, this site inspires significant concern. A similar viewpoint was also expressed in the local press. A part of the site, Avachinsky Pass, inspires a particular concern. This is a place between the volcanoes Koryaksky and Avachinsky. An excessive number of visitors was considered the main threat because it resulted in the trampling of soil and the extirpation of threatened animals. We performed a survey of the Avachinsky Pass aiming to estimate its state. Based on aerial pictures and observation we composed a scheme of habitats over the area around Avachinsky Pass revealing the disturbed plots of land. Moreover, we registered vertebrates considering them as biological indicators. It became clear that tourism has a significant impact on the state of the Avachinsky Pass, but the affected area is relatively small. Despite a large number of visitors, the survey revealed high biodiversity. We registered 19 species of birds and 9 species of mammals. Among them, black-capped marmots are especially informative as they have a settled way of life; they do occur on the Pass. The absence of grazing and logging contributes to the conservation of elfin forests and other plant communities on the slopes making the object resistant to anthropogenic impacts. Off-road vehicles pose the biggest threat to bare-ground revegetation.

Imagery obtained from unmanned aerial vehicle (UAV) is widely used for land surface modelling. Recent research prove that digital elevation models (DEMs) created from UAV imagery are characterized by a high rate of accuracy and reliability. Most of these studies are focused on assessing absolute elevation accuracy of the UAV DEMs, but the accuracy of relative elevations (i.e., accuracy of reproducing of local elevation differences within DEM) also should be considered. In this paper, we focus on the precision of replicating relative elevations in DEMs derived from imagery captured via UAVs without precise coordinate reference. To evaluate this accuracy, we use datasets of aerial images processed in two different methods: one with on-board coordinates obtained from a GNSS receiver, and the other based on precise coordinates calculated with the Post-Processing Kinematic (PPK) method. The sites selected for assessment are not look like each other in terms of terrain and forest cover characteristics to track the difference of modelling in the divergent areas. Constructed DEMs were compared with reference fragments of global DEMs by the statistical indices for the difference fields. The findings indicate that the absence of an accurate coordinate reference does not have a substantial impact on the precision of reproducing relative elevations in the DEM. This makes it possible to use UAV materials without precise coordinate reference for modelling in most geographical studies, where the error of terrain steepness values of 0.9° can be considered acceptable.

Forest and land fires are disasters that often occur in Indonesia which affects neighbouring countries. The burned area can be observed using remote sensing. Synthetic aperture radar (SAR) sensor data is advantageous since it can penetrate clouds and smoke. However, image analysis of SAR data differs from optical data, which is based on properties such as intensity, texture, and polarimetric feature. This research aims to propose a method to detect burned areas from the extracted feature of Sentinel-1 data. The features were classified using the Convolutional Neural Network (CNN) classifier. To find the best input features, several classification schemes were tested, including intensity and polarimetric features by applying the Boxcar speckle filter and the Gray Level Co-occurrence Matrix (GLCM) texture feature without using the Boxcar speckle filter. Additionally, this research investigates the significance of a window size parameter for each scheme. The results show the highest overall accuracy achieved 84% using CNN classification utilizing the GLCM texture features and without conducting the Boxcar speckle filter on the window size of 17×17 pixels when tested on the part region of Pulang Pisau Regency and Kapuas Regency, Central Kalimantan in 2019. The total burned area was 76,098.6 ha. The use of GLCM texture features without conducting the Boxcar speckle filter as input classification performs better than using intensity and polarimetric features that undergo the Boxcar speckle filter. Combining intensity and polarimetric features with performing the Boxcar speckle filter improves better classification performance over utilizing them separately. Furthermore, the selection of window size also contributes to improve the model performance.

In this study, the influence of climate change on land suitability for coffee cultivation in the Ecuadorian Amazon (EA) was investigated using five global circulation models (GCMs) in two different socioeconomic pathways (SSP126 and SSP585). Eleven physioedaphological factors were selected for the analysis and were combined with the most influential bioclimatic variables to model past, present and future suitable areas in five provinces of the EA. In assessing past suitability areas, key determinants varied based on land suitability levels. High suitability areas were primarily influenced by factors such as texture, organic matter content, soil fertility, soil depth, slope, and aspect, while pH, salinity, toxicity, drainage, and stoniness were more associated with moderate suitability areas. The present high suitability areas were influenced by texture, organic matter content, soil fertility, soil depth, and slope, whereas aspect, pH, salinity, toxicity, drainage, and stoniness were more prominent in modeling moderate areas. The ensemble estimation model projected distinct future scenarios for coffee cultivation; under the worst climate scenario (SSP585), Zamora Chinchipe and Morona Santiago, particularly in the east, face considerable unsuitability. Conversely, the more favorable scenario (SSP126) indicates high suitability across Pastaza, Orellana, and Sucumbios, with limited suitability in border areas adjacent to the Highland region. This study highlights the importance of implementing timely adaptation strategies to improve resilience to climate change impacts in the coffee sector.

The urban area is a spatial system that significantly impacts residents’ health risks. Despite the fact that urban areas house only 55% of the global population, they account for 95% of COVID-19 cases, highlighting the urgent need to understand the role of the urban environment in disease spread. This research explores the critical impact of urban form characteristics on public health risks, focusing primarily on the dynamics of COVID-19 transmission. The aim of the study study is to elucidate the spatial association between urban form elements such as connectivity, density, and heterogeneity and the incidence of COVID-19 cases, with a specific focus on Yogyakarta. Using global (OLS) and local (GWR) spatial regression models, we analyzed the relationship between these elements and COVID-19 prevalence at the neighborhood level rigorously. Our findings reveal a pronounced spatial correlation, particularly highlighting the significance of connectivity and heterogeneity. These factors explain over 95% of the variance in case numbers, while density shows no substantial link. This study’s originality lies in its hypothesis-driven examination of urban form impact on COVID-19 transmission, providing new insights into the spatial determinants of health risks in urban settings. Practical implications of our research are profound, providing evidencebased guidance for urban planning and disaster preparedness strategies to mitigate future health crises better. The study contributes valuable insights into designing healthier and more sustainable urban environments by providing a nuanced understanding of how the urban form influences the spread of disease.

Modern plants and surface soil δ13С values from 95 sites in the Baikal region were obtained for the first time and were used to establish relationships with regional environmental factors. Studied sites were distributed along the elevation gradient from 403 to 2315 m, which defined a strong landscape and climatic gradients encompassing mountain tundra, subalpine grasslands, mountain taiga, subtaiga, and steppe. δ13С values of soil organic matter (SOM) varied from –29.50 to –22.98‰. This result showed that the stable C isotopic composition of the surface soils was mainly determined by δ13С values of C3 plants (vary from –33.0 to –24.5‰) and C isotope fractionation during stabilization of plant-derived C into SOM. The δ13С values of modern plants and surface soils were negatively correlated with mean annual and growing season precipitation (p<0.05), confirming that precipitation is the primary factor determining SOM’s stable C isotopic composition in the Baikal region. A distinct increase in the δ13С values with decreasing mean annual and growing season precipitation was found with a slope of –0.42‰/100 mm and –0.97‰/100 mm, respectively. Temperature had no significant effect on the spatial distribution of SOM δ13С values at the regional scale but played an important role in the severe environments of mountain tundra (the coldest and wettest) and steppes (the warmest and driest). Such conditions strongly impacted SOM δ13С values by influencing plant species composition and soil microbiological activity. As a result, the organic matter of these soils is characterized by the highest δ13С values. The SOM of taiga soils formed under a favorable combination of temperature and precipitation was characterized by the lowest δ13С values

Paramo ecosystems are unique and are located in Ecuador, Colombia, and Venezuela. Although the Colombian government has made efforts for their preservation and sustainable use, several of the national paramos have experienced a change in their land cover as a result of climate variability, climate change, and the expansion of the agricultural and livestock frontiers. Changes in land cover can affect ecosystem integrity and its environmental services. Taking into account the regional importance of the Guachaneque paramo, it was analyzed whether its vegetation cover experiences any significant changes. This study was carried out by combining multi – temporal analysis of vegetation cover with climatic and statistical analyses. It was found that most land covers present a change mostly associated with human interventions (0.77–0.91). Climate variability and climate change also affect the landscape, but to a lesser extent (0.09–0.23). Water availability directly affects the expansion of all land covers, except paramo grassland, which indicates that an increase in rainfall associated with climate change will cause a contraction of this land cover. Currently, it is identified that anthropogenic pasture and crop surfaces replace the paramo grassland covers with an approximate change of 28.5 hectares per year. These results alert us to the need for monitoring and controlling the development of livestock and agricultural activities in order to preserve the integrity of the paramo landscape.

The current urbanization trend shows a large number of conurbated medium-sized cities growing and others that could be transformed into metropolises, especially in Latin America. This has led to disparities in the provision of urban services and amenities, as well as new territorial processes and spatial fragmentation. The objective of this study is to analyze the future changes in land use and land cover in the La Serena-Coquimbo conurbation, Coquimbo Region, Chile, under two different scenarios: Business-as-usual and Spatial Planning between 2020 and 2042. These different scenarios were simulated using the CLUMondo model based on the evolution of land use/cover between 1990-2020 in order to identify the main dynamics associated with urban growth in both cities. The simulation scenarios reflect how the urban area of the conurbation will expand towards the peri-urban area. In the first scenario, urban land shows an increase of 54%, and in the second one, 45% from 2020 to 2042, reinforcing the issues of the metropolization process in the conurbation, such as spatial segregation, infrastructure deficits, loss of ecosystems and natural landscapes, and fragmentation of rural areas. Spatially explicit models have proven to be a powerful tool for decision-makers tasked with projecting urban growth, particularly in conurbated cities undergoing metropolization.

Since the beginning of river valley civilizations, humans have sought to harness the potential of flowing waters. The monumental structures of dams have been instrumental in damming these flowing waters and providing a wide range of benefits to society, including irrigation, drinking water, and generating clean energy. The present paper reviews in detail the hydropower reservoirs (dams) and presents a broader depiction of the 3Ps associated with their profits, problems, and planning. A literature review pertaining to dam construction and their impacts has been undertaken to analyze various approaches involving studies on socio-economic and environmental indicators and sustainability/risk factors related to dams. Various online search engines have been used to identify the desired studies and research for review. The first section of the paper gives a detailed account of the contribution (i.e., profits) made by dams to the economic development of humanity. The second part presents the negative social and environmental impacts (i.e., problems) of dams. As the paper proceeds, numerous tools/models analyzed during the literature review are presented that can be used to mitigate the negative fallouts of these dams (i.e., planning). However, it has been found that all these methods provide fragmented information with no certainty regarding which essential aspects require more emphasis while planning for these superstructures. Thus, a basic uniform frame is suggested, showcasing the fundamental and most critical aspects to be considered while planning a dam structure, which are described according to the three phases of dam construction, i.e., pre-construction, construction, and post-construction phases. While presenting the 3Ps (profits, problems and planning) of dams and analyzing their pitfalls, the 3Is (innovative keys) are recommended, emphasizing innovative technologies, innovative planning, and innovative solutions, which are needed in making these dams more optimal, judicious, and sustainable.

Soil mapping of urban areas is required for solving many applied problems. However, its methodology is still under development. The lack of information about urban soils and the inconsistence of their classifications are the main difficulties, as well as the intricate soil cover patterns in cities and towns. The research was aimed to compile the soil map for the drainage basin of the small urban river Setun at a scale that could reflect its soil cover heterogeneity. Some new approaches to the differentiation of urban and semi-urban soils in accordance with recent ideas on their systematic and land use variants have been proposed. The concept of pedo-urbo-mosaics, which implements the soil cover pattern theory in relation to urbanized territory, has been used for delineating mapping units. The compilation methodology involved the use of open spatial data and GIS technologies. The subdivision of the basin into mapping units was performed using ©OpenStreetMap data and Yandex Maps Web mapping service. Spatial analysis in GIS allowed for mapping the territory with a moderate urbanization rate on a large scale, obtaining a more adequate and detailed spatial representation of the area than in the case of applying the traditional approach. The map, at a scale of 1:60,000 contains 16 natural/semi-natural soils and technogenic superficial formations, as well as 11 pedo-urbo-mosaics. The study may be of methodological interest as an experience in soil mapping of urbanized areas using GIS.

Understanding post-fire recovery and succession is crucial for determining the forest’s further reestablishment rate and development tendency, facilitating the restoration and protection of degraded forests, and planning post-fire forest management. The main aim of this study was to evaluate forest regeneration and reveal the tendency of plant succession after large-scale fire in the Tarvagatai Mountain range, Central Khangai, Mongolia. The monitoring study on post-fire plant succession and regeneration in the forbs-Rhytidium mosses pseudotaiga larch forests was conducted on permanent sample plots from 2007 to 2021 in the forest sites, which were damaged by severe fires in 1996 and 2002. Our results indicated that burned forest was regenerated sufficiently through the several serial stages of post-fire successions as fireweed (Chamaenerion angustifolium) community (up to 5 years after fire), fireweed-bonfire moss (Funaria hygrometrica) community (from 6 to 10 years), forbs community (11-16 years), grass-forbs young larch forest (17-25 years). Species numbers gradually increased with time in the forest affected by fires, whereas they rose drastically in the forest damaged by fire and livestock browsing due to the increase of ruderal species. In spite of the long recovery period, the post-fire similarity indexes of species composition and coenotic percentage compared with the control forest were relatively low, indicating a slow pre-fire vegetation recovery.