Evaluation of decadal land degradation dynamics in old coal-mines of Central India

The present study attempts to understand land use dynamics in an area subjected to opencast and underground coal mining for the last few decades in Kotma Coalmines of Anuppur district in Madhya Pradesh, India through geospatial techniques. Land Use and Land Cover (LULC) change detection analysis was performed digitally classifying Landsat 5 (2001) as well as Landsat 8 (2020) satellite data using maximum likelihood algorithm. Results revealed that area under Dense native vegetation decreased drastically (13.74 sq. km) with the gradual and consistent expansion in the activities of coal mines which showed the highest increase in area over time (15.84 sq. km). Bivariate regression analysis showed the positive empirical relationships between vegetation indices and soil physico-chemical parameters. Studies suggested soil and vegetation is degraded over the large mining areas consistently over a long time period. Despite the continuous reforestation activities on mined areas, the decline area under dense vegetation and sparse vegetation over the twenty-year time-scale indicates that the reclamation activities are still in its’ infancy. Land Degradation Vulnerability Index (LDVI) map was generated to understand the extent of decadal land degradation trends and it shows that 8.60 % of the area is highly vulnerable to degradation. The LDI inputs will help the planners to develop alternate strategies to tackle vulnerability zones for safe mining. Monthly estimation of various meteorological parameters was also recorded to generate heat plots for the period 2001-2020. The study concludes that monitoring and assessment of fragile ecosystems are indispensable for holistic environmental management.

Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang

Time-series normalized difference vegetation index (NDVI) is commonly used to conduct vegetation dynamics, which is an important research topic. However, few studies have focused on the relationship between vegetation type and NDVI changes. We investigated changes in vegetation in Xinjiang using linear regression of time-series MOD13Q1 NDVI data from 2001 to 2020. MCD12Q1 vegetation type data from 2001 to 2019 were used to analyze transformations among different vegetation types, and the relationship between the transformation of vegetation type and NDVI was analyzed. Approximately 63.29% of the vegetation showed no significant changes. In the vegetation-changed area, approximately 93.88% and 6.12% of the vegetation showed a significant increase and decrease in NDVI, respectively. Approximately 43,382.82 km2 of sparse vegetation and 25,915.44 km2 of grassland were transformed into grassland and cropland, respectively. Moreover, 17.4% of the area with transformed vegetation showed a significant increase in NDVI, whereas 14.61% showed a decrease in NDVI. Furthermore, in areas with NDVI increased, the mean NDVI slopes of pixels in which sparse vegetation transferred to cropland, sparse vegetation transferred to grassland, and grassland transferred to cropland were 9.8 and 3.2 times that of sparse vegetation, and 1.97 times that of grassland, respectively. In areas with decreased NDVI, the mean NDVI slopes of pixels in which cropland transferred to sparse vegetation, grassland transferred to sparse vegetation were 1.75 and 1.36 times that of sparse vegetation, respectively. The combination of vegetation type transformation NDVI time-series can assist in comprehensively understanding the vegetation change characteristics.

Land use and land cover changes in the Lower Neretva Region from 1990 to 2020

Changes in land use and land cover are the result of complex interactions between humans and their environment. This study examines land use and land cover changes in the Lower Neretva Region between 1990 and 2020. Political and economic changes in the early 1990s resulted in changes in the landscape, both directly and indirectly. Multispectral image processing was used to create thematic maps of land use and land cover for 1990, 2005, and 2020. Satellite images from Landsat 5, Landsat 7 and Landsat 8 were the main source of data. Land use and land cover structure was assessed using a hybrid approach, combining unsupervised and manual (visual) classification methods. An assessment of classification accuracy was carried out using a confusion matrix and kappa coefficient. According to the results of the study, the percentage of built-up areas increased by almost 33%. Agricultural land and forests and grasslands also increased, while the proportion of swamps and sparse vegetation areas decreased.

Vegetation and Soil Carbon under Various Forest Management Types: Case of Karang Sidemen Community Forest in Lombok, Eastern Indonesia

The condition of community-managed forest areas varies according to biophysics characteristics and management activities. This study aims to investigate the condition of vegetation and soil carbon stocks of various types of forest management by the community in Karang Sidemen Village, Lombok, Indonesia. In the study area, it was found 4 types of landuse management, namely; dense forest-like vegetation (Tp1), moderate vegetation with intensive (Tp2) and less intensive (Tp3) under-stand cultivation, and sparse vegetation resembling dryland agriculture (Tp4). Vegetation condition was analyzed based on satellite derived NDVI index and field observation. Sentinel satellite images for 2015 and 2019, with a resolution of 10x10 m was used. Field data collection was carried out in August 2019. It was made 5 sample plots of 20x20 m for each management type. Vegetation data with diameter (D) ≥ 20 cm, 10 cm ≤D< 20 cm, 2 cm ≤D< 10 cm and D< 2 cm were collected from plots of 20x20 m, subplots 10x10 m, 5x5 m and 2x2 m, respectively. Soil samples were taken diagonally on a 20x20 m plot, at a depth of 0-5 cm, 5-10 cm, 10-20 cm and 20-30 cm. The results showed that the NDVI derived vegetation index for 2015 and 2019 images showed different patterns for the four types of management. The number of species for Tp1, Tp2, Tp3 and Tp4 were 9, 15, 9 and 8 species, respectively. The dominant species are generally from groups of plants providing economic benefits such as avocado (Persea americana), candlenut (Aleurites moluccana), cocoa (Theobroma cacao), coffee (Coffea canephora), jackfruit (Artocarpus heterophyllus), mangosteen (Garcinia mangostana) and guava (Psidium guajava). Soil carbon stocks of the four types of management at a depth of 0-5 cm, 5-10 cm, 10-20 cm and 20-30 cm were18.61-21.04 tons C/ha, 16.56-20.80 tons C/ha, 29.66-34.48 tons C/ha and 27.54 - 33.66 tons C/ha, respectively. The soil carbon stock of denser vegetation is higher than that of medium and sparse vegetation. Therefore, forest management with the community needs to maintain forest-like vegetation.

Was Australia a sink or source of CO₂ in 2015? Data assimilation using OCO-2 satellite measurements

In this study, we present the assimilation of data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data, version 9) to estimate the Australian carbon surface fluxes for the year 2015. To perform this estimation, we used both a regional-scale atmospheric transport–dispersion model and a four-dimensional variational assimilation scheme. Our results suggest that Australia was a carbon sink of −0.41 ± 0.08 PgC yr−1 compared to the prior estimate 0.09 ± 0.20 PgC yr−1 (excluding fossil fuel emissions). Most of the carbon uptake occurred in northern Australia over the savanna ecotype and in the western region over areas with sparse vegetation. Analysis of the enhanced vegetation index (EVI) suggests that the majority of the carbon uptake over the savanna ecosystem was due to an increase of vegetation productivity (positive EVI anomalies) amplified by an anomalous increase of rainfall in summer. Further from this, a slight increase of carbon uptake in Western Australia over areas with sparse vegetation (the largest ecosystem in Australia) was noted due to increased land productivity in the area caused by positive rainfall anomalies. The stronger carbon uptake estimate in this ecosystem was partially due to the land surface model (CABLE-BIOS3) underestimating the gross primary productivity of the ecosystem. To evaluate the accuracy of our carbon flux estimates from OCO-2 retrievals, we compare our posterior concentration fields against the column-averaged carbon retrievals from the Total Carbon Column Observing Network (TCCON) and ground-based in situ monitoring sites located around our domain. The validation analysis against TCCON shows that our system is able to reduce bias mainly in the summer season. Comparison with surface in situ observations was less successful, particularly over oceanic monitoring sites that are strongly affected by oceanic fluxes and subject to less freedom by the inversion. For stations located far from the coast, the comparison with in situ data was more variable, suggesting difficulties matching the column-integrated and surface data by the inversion, most likely linked to model vertical transport. Comparison of our fluxes against the OCO-2 model intercomparison (MIP) was encouraging. The annual carbon uptake estimated by our inversion falls within the ensemble of the OCO-2 MIP global inversions and presents a similar seasonal pattern.

Desertification Extraction Based on a Microwave Backscattering Contribution Decomposition Model at the Dry Bottom of the Aral Sea

The fine particles produced during the desertification process provide a rich material source for sand and dust activities. Accurately locating the desertified areas is a prerequisite for human intervention in sand and dust activities. In arid and semi-arid regions, due to very sparse vegetation coverage, the microwave surface scattering model is very suitable for describing the variation of topsoil property during the process of desertification. However, the microwave backscattering coefficient (MBC) trend of the soil during the desertification process is still unclear now. Moreover, the MBC of a resolution unit usually involves the contribution of soil and vegetation. These problems seriously limit the application of microwave remote sensing technology in desertification identification. In this paper, we studied the soil MBC change trend during the desertification process and proposed a microwave backscattering contribution decomposition (MBCD) model to estimate the soil MBC of a resolution unit. Furthermore, a simple microwave backscattering threshold (SMSBT) model was established to describe the severity of desertification. The MBCD and SMSBT models were verified qualitatively through landscape photos of sampling points from a field survey in November 2018. The results showed that the MBC would gradually decline with the deepening degree of desertification. The MBCD model and the corresponding least squares method can be used to estimate the soil MBC accurately, and the SMSBT model can accurately distinguish different degrees of desertification. The results of desertification classification showed that more than 68% of the dry bottom of the Aral Sea is suffering from different degrees of desertification.

Detection of “Legbreaker” Antipersonnel Landmines by Analysis of Aerial Thermographic Images of the Soil

An automatic detection methodology for “legbreaker” Antipersonnel Landmines (APL) was developed based on digital image processing techniques and pattern recognition, applied to thermal images acquired by means of an Unmanned Aerial Vehicle (UAV) equipped with a thermal camera. The images were acquired from the inspection of a natural terrain with sparse vegetation and under uncontrolled conditions, in which prototypes of “legbreaker” APL were buried at different depths. Remarkable results were obtained using a Multilayer Perceptron (MLP) classifier, reaching a 97.1% success rate in detecting areas with the presence of these artifacts.

Umzug einer Galapagos-Riesenschildkröte aus dem Zoologischen Garten in die Zoologische Sammlung

Galápagos-Riesenschildkröten sind ausschließlich auf dem Galápagos-Archipel im Pazifischen Ozean zu finden. Dort leben sie sowohl in regennassen Regionen als auch in Gebieten mit spärlicher Vegetation. Sie sind tagaktiv und wandern vom Hochland zu ihren Eiablageplätzen in wärmeren Küstengebieten. Sie können ein sehr hohes Alter erreichen, in der Regel werden sie 50–80 Jahre alt. Im Jahr 2020 verzeichnete das Europäische Zuchtbuch für Galápagos-Riesenschildkröten 108 Tiere in 23 Zoos und Einrichtungen. In Europa wird diese Art in 12 Zoos gezeigt, darunter in Rostock und Hoyerswerda. Im Jahr 2012 wurden im Rostocker Zoo fünf Tiere gehalten, die alle aus dem Zoo Zürich kamen. Im Juni 2019 wurde eine der fünf Schildkröten, Elvida, tot in ihrem Gehege aufgefunden. Elvida wurde zur Sektion an das Leibniz-Institut für Zoo- und Wildtierforschung in Berlin übergeben. Danach wurde sie im Museum für Naturkunde Berlin präpariert. Die Präparation erfolgte mit einem Imprägnierverfahren, bei dem das Wasser der Zellen durch Polyethylenglykol (PEG) ersetzt wird. Seit Dezember 2020 ist das Exponat der Galápagos-Riesenschildkröte Elvida Teil der Zoologischen Sammlung der Universität Rostock, wo es den Studierenden für Lehrzwecke zur Verfügung steht und Teil der Ausstellung ist. Relocation of a Galapagos giant tortoise from the Zoological Garden to the Zoological Collection Abstract: Galápagos giant tortoises are found exclusively on the Galápagos archipelago in the Pacific Ocean. There they live both in rain-wet regions and in areas with sparse vegetation. They are diurnal and migrate from the highlands to their egg-laying sites in warmer coastal areas. They can reach a very old age, usually they live 50–80 years. In 2020, the European Studbook for Galápagos giant tortoises listed 108 animals in 23 zoos and institutions. In Europe, this species is kept in 12 zoos, including Rostock and Hoyerswerda. Five individuals were kept at Rostock Zoo in 2012, all of which came from Zurich Zoo. In June 2019, one of the five tortoises, Elvida, was found dead in her enclosure. Elvida was handed over to the Leibniz Institute for Zoo and Wildlife Research in Berlin for dissection. After finishing the dissection, it was prepared at the Museum für Naturkunde Berlin. The preparation was carried out with an impregnation procedure in which the water of the cells is replaced by polyethylene glycol (PEG). Since December 2020, the exhibit of the Galápagos giant tortoise Elvida has been part of the Zoological Collection of the University of Rostock, where it is available to students for teaching purposes and is part of the exhibition.

Ecotourism as a Forest Conservation Tool: An NDVI Analysis of the Sitakunda Botanical Garden and Ecopark in Chattogram, Bangladesh

Ecotourism, a sustainable form of tourism, is increasingly being viewed as a tool that can promote global biodiversity and forest conservation. This study explored the scope of ecotourism in forest conservation practices in the developing context by taking the Sitakunda Botanical Garden and Ecopark (SBGE), Bangladesh’s first ecopark established in 2000, as a case study. Using GIS and remote sensing technology, NDVI analysis revealed that, unlike the anticipated outcomes of the SBGE project, after a brief increase in vegetation coverage of 84.6% from 1995 to 2000, the vegetation coverage fell drastically from 2000 to 2015, wherein 33.4% of vegetation had been completely removed, and much of the dense and medium vegetation had been converted to sparse vegetation or other land uses. Anthropogenic activities, namely, unplanned urbanization, are suggested as the major contributors to this decline. From the period of 2015 to 2020, however, vegetation was seen to regenerate, potentially due to the decelerating urbanization or the possible manifestation of the ‘U’ shape relationship between the changes in vegetation and rates of urbanization. Sustainable land-use policies may help attain the targets of the project and lead the SBGE to emerge as a success story of the Bangladeshi ecotourism industry.

FEATURES OF THE FORMATION OF EXTREME EXOGENIC PROCESSES IN THE ALIBEK VALLEY (WESTERN CAUCASUS)

In the mountains, special types of geosystems are formed, whose origins are attributable to exogenic processes - debris flows, avalanches, landslides, etc. Since 2009, a regular survey of key objects and centers of heterogeneous extreme process development has been carried out for their identification and monitoring in the Central Caucasus (the Cherek- Balkarsky basin). To obtain a more complete picture of their course in the Northern Caucasus as a whole, and to track that cycle, the authors considered it expedient, beginning in 2021, to monitor also the Western Caucasus, the area of Teberda and Dombai. The article analyzes the results of expeditionary observations, as well as meteorological indicators that affect the course of extreme exogenic processes, their derivatives for 2020 and for the first eight months of 2021, from the Teberda and Terskol meteorological observatories.On the left side of the Alibek River valley, the predominant processes are talus and, to a lesser extent, avalanches. That side has a southern exposure and is arid relative to the right, northern one. On the one hand, moisture is insufficient for the successful formation of debris flows; on the other hand, sparse vegetation in the upper parts of the slope and the lower upper border of the forest do not inhibit exogenous processes.Air temperatures in Teberda are 4-5°C lower than in Balkaria. This contributes to the reduction of glacier melting, inhibiting exogenic processes. Higher moisture and the lack of grazing contribute to the formation of rich and dense vegetation, with a similar effect. This factor neutralizes the more active than in the Central Caucasus, frost weathering and high saltitudes, contributing to a higher rate of mobility of both water and debris.