Changes In Vegetation Cover Research Articles

Soil erosion-based sub-watershed prioritization through coupling various crop management and erosivity scenarios using game theory

The soil erosion of the watershed is different in temporal and spatial scales due to complex climatic and environmental conditions and their dynamic state over time. Accordingly, it is necessary to prioritize sub-watersheds based on their dynamic conditions to reduce the destructive effects of soil erosion. However, this issue has to be sufficiently reported on the scale of the watershed. Towards that, a game theory-based prioritization approach was planned concerning changes in vegetation cover and rainfall in the Shazand Watershed of the Markazi Province, Iran. To achieve the purpose of the study, the amount of soil erosion was first estimated in different scenarios resulting from the changes in rainfall erosivity and vegetation cover using the RUSLE model. Next, pairwise comparisons between 24 sub-watersheds in all scenarios were made based on the sub-watersheds' ranks in soil erosion in each scenario. Considering all scenarios, the priority of the sub-watersheds was assessed using the Condorcet approach. The results showed that the mean soil erosion in the watershed ranged from 5.4 and 36 t ha−1 y−1 while applying various scenarios. It is worth mentioning that the prioritization results obtained from the Condorcet algorithm and the current soil erosion rate are highly similar. On the other hand, sub-watersheds 2 and 9 were selected as the first and last priority, providing an appropriate roadmap for managers and relevant departments to adopt appropriate soil erosion inhibition measures.

Identifying and Mapping the Spatial Factors That Control Soil Erosion Changes in the Yellow River Basin of China

The Yellow River Basin has been considered to have the most serious soil erosion in the world, and identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. This study used the Universal Soil Loss Equation (USLE) to estimate the spatial and temporal changes in soil erosion from 1985 to 2020 and analyzed the controlling factors. The results indicated that from 1985 to 2020, the average erosion modulus in the Yellow River Basin was 1160.97 t∙km−2∙yr−1, and the erosion modulus in the middle reach was significantly greater than in the lower and upper reaches. Changes in vegetation coverage, rainfall and land use controlled 38.95%, 40.87% and 9.21% of soil erosion changes, respectively. Among them, the area in which soil erosion was decreased due to increased vegetation coverage accounted for 70.77% of the area controlled by vegetation coverage, while the area in which soil erosion was increased due to increased rainfall accounted for 86.62% of the area controlled by rainfall. These results prove the effectiveness of vegetation restoration projects in controlling soil erosion in the Yellow River Basin, but more attention needs to be paid to the impact of rainfall on soil erosion in the future.

Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran.

Vegetation plays a crucial role in providing organic matter and regulating energy exchange on the Earth's surface. This study investigates the changes in vegetation cover, temperature, and precipitation in northeastern Iran during 2001-2020. MODIS-NDVI time series data and climatic data from 11 synoptic stations were utilized. The nonparametric Mann-Kendall method was employed to detect trends in vegetation cover and climatic variables. Additionally, the correlation between climatic parameters and vegetation was examined. Trend analysis revealed significant increases/decreases in vegetation cover in 32%/26% of the region, respectively. The increasing trend in vegetation cover was predominantly observed in highlands, suggesting that a warmer climate has enhanced the living conditions for plants in these regions. The vegetation trend map indicates an expansion of vegetation cover in the northern and central parts of Iran during the past 20years, whereas the southern and eastern portions experienced declines. The relationship between vegetation and elevation revealed that vegetation increased above 1,850m and decreased below 850m. Trend analysis showed no significant trend in precipitation data since the beginning of the twenty-first century, but an increasing trend in temperature was observed in 82% of the region's area, excluding the western strip. Correlation coefficients between temperature, precipitation, and vegetation indicated that declining temperatures are the limiting factors for vegetation in the highlands, while in lowland areas, the decrease in precipitation significantly diminishes vegetation growth.

PYROGENIC CHANGES OF BOG VEGETATION AND PEAT IN WESTERN SIBERIA

Wildfires are an important environmental factor which determines the carbon cycle intensity in mires. The article presents the assessment of the consequences of pyrogenic transformation and the current state of burntout mires in the taiga and forest-tundra zones of Western Siberia 6-8 years after the wildfire, with regard to their microhabitat heterogeneity. Field studies were conducted in 2022 on three mires (a total of 13 post-pyrogenic and pristine plots) and included a total-station survey of the surface, an assessment of the occurrence of species in the grass-dwarf shrub and moss-lichen tiers, sampling for laboratory analysis of the physical properties and botanical composition of peat. Sphagnum mosses, Polytrichum strictum, lichens and dwarf shrubs were considered as recovery indicator species. As a result of the study, it was found that the intensity of pyrogenic transformation is determined by the initial state of bog ecosystem and increases in a row: the hydro forestation site on the Bakchar raised bog - palsa - the Ust-Bakchar raised bog drained for peat extraction. At most of the studied plots, microdepressions were more susceptible to burnout, while hummocks were preserved or only partially burned out. The transformation of peat deposit properties extends beyond the layer directly exposed to burnout, and manifests itself in a decrease in water content, and an increase in ash content, bulk density and degree of humification. At the first stages of post-pyrogenic successions, similar patterns were revealed for the mires of taiga and forest-tundra zones, i.e. an intensive overgrowth with P. strictum. According to the results of the study, it was concluded that the hydroforestation site in the Bakchar bog could possibly restore the species composition of vegetation cover and resume peat accumulation. Irreversible changes in vegetation cover have occurred in the Ust-Bakchar bog, where the restoration of sphagnum mosses does not occur even 20 years after the fire.

EVALUATION OF VEGETATION COVER DYNAMICS IN A SUB-TROPICAL CLIMATE USING HIGH-RESOLUTION MULTISPECTRAL DATA FROM UAVS

The study of vegetation status is of great importance as it reveals environmental factors and their relationship with the availability of water resources, components that are relevant in the planning, drafting and execution of numerous civil engineering projects. Detecting changes in vegetation cover often requires data from space-based platforms, which may have limitations in terms of spatial or temporal resolution and high costs for acquiring high-resolution data. For relatively small areas, the use of Unmanned Aerial Vehicles (UAVs) provides a solution. These devices facilitate the acquisition of land cover information with high spatial and temporal resolution through the use of photographic cameras or specialized sensors. This research analyzes the vegetation status within a study area characterized by distinct climatic seasons (dry and humid) within a warm sub-tropical climate. The primary focus lies in detecting changes in vegetation cover and evaluating the overall state of the vegetation. To accomplish this objective, a multirotor UAV equipped with a multispectral camera that captures RED and NIR bands is deployed. Various vegetation indices based on distance and slope are applied to access the vegetation’s condition. The analysis of the results indicates that it is possible to evaluate the vegetation cover dynamics using the very high-resolution data obtained with the VANT approach (10 cm per pixel). Notably, the distance-based vegetation indices demonstrate superior efficacy in delineating the vegetation status and the stress induced by the scarcity of water resources during the transition between dry and humid seasons.

Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index (NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area. The current state of the oasis is influenced by both expansion and degradation factors. Therefore, it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources. This study used Landsat satellite images in 1987, 2002, and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis, applied multi-temporal Normalized Difference Vegetation Index (NDVI) data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis, and investigated the factors influencing these variation. This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021, with increase of NDVI values being higher than 0.10. In 2021, the highest NDVI value is generally above 0.70, while the lowest value remains largely unchanged. However, there is a remarkable increase in NDVI values between 0.20 and 0.30. The area of low NDVI values (0.00–0.20) has remained almost stable, but the region with high NDVI values (above 0.70) expands during 1987–2021. Furthermore, this study finds that in 1987–2002, the increase of vegetation cover is most notable in the northern region of the study area, whereas from 2002 to 2021, the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area. From 1987 to 2021, NDVI values exhibit the most pronounced variation, with a significant increase in the “green” zone (characterized by NDVI values exceeding 0.40), indicating a substantial enhancement in the ecological environment of the oasis. The NDVI classification is validated through 50 ground validation points in the study area, demonstrating a mean accuracy of 92.00% in the detection of vegetation cover. In general, both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987, 2002, and 2021. Finally, this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

AbstractAlthough considerable effort has been deployed to understand the impact of climate variability and vegetation change on runoff in major basins across Africa, such studies are scarce in the Gulf of Guinea Basin (GGB). This study combines the Budyko framework and elasticity concept along with geospatial data to fill this research gap in 44 nested sub‐basins in the GGB. Annual rainfall from 1982 to 2021 show significant decreasing and increasing trends in the northern and southern parts of the GGB, respectively. Annual potential evapotranspiration (PET) also shows significant increasing trends with higher magnitudes observed in the northern parts of the GGB. Changing trends in climate variables corroborates with shift to arid and wetter conditions in the north and south, respectively. From 2000 to 2020 vegetation cover estimated using enhanced vegetation index (EVI) shows significant increasing trends in all sub‐basins including those experiencing a decline in annual rainfall. Vegetation composition measured using vegetation continuous fields (VCFs) from 2000 to 2020 show an increase in tree canopy cover (TC), a decline in short vegetation cover and marginal changes in bare ground cover (BG). Elasticity coefficients show that a 10% increase in annual rainfall and PET may lead to a 33% increase and 24% decline in runoff, respectively. On the other hand, a 10% increase in EVI may lead to a 4% decline in runoff while a 10% increase in TC, SV and BG may reduce runoff by 4% and increase runoff by 3% and 2%, respectively. Even though changes are marginal, decomposing vegetation into different parameters using EVI and VCFs may lead to different hydrological effects on runoff which is one of the novelties of this study that may be used for implementing nature‐based solutions. The study also demonstrates that freely available geospatial data together with analytical methods are a promising approach for understanding the impact of climate variability and vegetation change on hydrology in data‐scarce regions.

Remote sensing assessment of anthropogenic and climate variation effects on river channel morphology and vegetation: Impact of dry periods on a European piedmont river

AbstractRivers are subject to increasing human pressure, resulting in a loss of their natural characteristics, further enhanced by climate change. The present study focuses on a piedmont reach of the Italian Po River and combines Landsat satellite information with hydrological records to investigate changes in sandbars exposure and riparian vegetation coverage, considering the summer period of 1984–2022. Satellite data were handled via Google Earth Engine, looking at common indexes such as the Modified Normalized Difference Water Index, which was used to identify temporal variations in wetted channel area, and the Normalized Difference Vegetation Index, considered as a proxy of vegetation coverage variations. Changes in the river hydrology were analysed by looking at the annual minimum water levels, the discharge duration curve, the stage–discharge relationship and the yearly annual water volume. Results suggest that a process of oversimplification is affecting this reach of the Po River, showing how climate change can affect piedmont European watercourses. Indeed, after an initial period where bars tended to be barer and somehow stable over time, in the most recent decade a different trend appeared, with vegetation able to colonize the exposed sandbars more. Using the Po River as an exemplary case study, this work suggests that prolonged dry periods, which are more common in recent decades, might impact large and medium rivers located in temperate climates, favouring the development of vegetation on exposed sandbars, eventually resulting in a less dynamic active channel.

Forest fire, thinning, and flood in wildland-urban interface: UAV and lidar-based estimate of natural disaster impacts

ContextWildland-urban interface (WUI) areas are facing increased forest fire risks and extreme precipitation events due to climate change, which can lead to post-fire flood events. The city of Flagstaff in northern Arizona, USA experienced WUI forest thinning, fire, and record rainfall events, which collectively contributed to large floods and damages to the urban neighborhoods and city infrastructure.ObjectivesWe demonstrate multi-temporal, high resolution image applications from an unoccupied aerial vehicle (UAV) and terrestrial lidar in estimating landscape disturbance impacts within the WUI. Changes in forest vegetation and bare ground cover in WUIs are particularly challenging to estimate with coarse-resolution satellite images due to fine-scale landscape processes and changes that often result in mixed pixels.MethodsUsing Sentinel-2 satellite images, we document forest fire impacts and burn severity. Using 2016 and 2021 UAV multispectral images and Structure-from-Motion data, we estimate post-thinning changes in forest canopy cover, patch sizes, canopy height distribution, and bare ground cover. Using repeat lidar data within a smaller area of the watershed, we quantify geomorphic effects in the WUI associated with the fire and subsequent flooding.ResultsWe document that thinning significantly reduced forest canopy cover, patch size, tree density, and mean canopy height resulting in substantially reduced active crown fire risks in the future. However, the thinning equipment ignited a forest fire, which burned the WUI at varying severity at the top of the watershed that drains into the city. Moderate-high severity burns occurred within 3 km of downtown Flagstaff threatening the WUI neighborhoods and the city. The upstream burned area then experienced 100-year and 200–500-year rainfall events, which resulted in large runoff-driven floods and sedimentation in the city.ConclusionWe demonstrate that UAV high resolution images and photogrammetry combined with terrestrial lidar data provide detailed and accurate estimates of forest thinning and post-fire flood impacts, which could not be estimated from coarser-resolution satellite images. Communities around the world may need to prepare their WUIs for catastrophic fires and increase capacity to manage sediment-laden stormwater since both fires and extreme weather events are projected to increase.

Cloud-Based Remote Sensing and Analysis of Vegetation Cover Changes in Key Regions of Oceania

The main objective of this research is to use cloud platforms to conduct a shallow survey of vegetation cover variations in Oceania. It is well-known that compared with the northern hemisphere, Oceania has a more unique ecosystem. The geographic position of Oceania is close to the equator. Therefore, the climate of some regions in Oceania is warm and has full precipitation, which is different from that in the Northern Hemisphere. This considerably influences changes in vegetation cover and makes comprehending vegetation cover tendency important for environmental protection measures. The change in vegetation cover from 2015 to 2022 was analyzed using cloud technology and remote sensing data. My findings mainly include the expansion and reduction of vegetation cover in major regions of Oceania. These results provide valuable insight into the dynamic properties of Oceanian ecosystems. This study contributes to a deeper understanding of the ecological environment in Oceania and highlights the potential of cloud platforms in remote sensing and ecological monitoring. These findings have important implications for environmental policies, biodiversity conservation, and sustainable resource management in the region.

Application of Remote Sensing and Geographic Information System Technologies to Assess the Impact of Mining: A Case Study at Emalahleni

This article presents an assessment of the impact of mining activities in the Emalahleni municipality, using GIS and RS technologies. The random forest algorithm was used to classify the land use and land cover in the Emalahleni municipality over a three-decade period (1990–2020). The classifications are settlement, water, mining area, vegetation, and bare land. The majority of the study area was found to be rocky ground, accounting for approximately 60% of the total study area. Change detection maps were created for vegetation and mining to assess the extent of land degradation in the study area over the three-decade period. The findings in this study highlight the importance of understanding the changes in land use and vegetation cover in the study area and its impact on the environment, as well as the local community. It is crucial to develop sustainable land management strategies that ensure that a reasonable balance concerning the economic development activities is achieved, such as mining with environmental management for its long-term viability for future generations. The data presented in this study provides a useful baseline for further research and can inform land-use planning and decision-making processes in Emalahleni.

Stream Chemistry and Forest Recovery Assessment and Prediction Modeling in Coal-Mine-Affected Watersheds in Kentucky, USA

Kentucky is one of the largest coal-producing states; surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas, vegetation change, and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age and percentage of mining, reclaimed forest, and reclaimed woods) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n = 9), summer (n = 14), and fall (n = 58) 2017 to study changes in water quality variables (SO42−, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+, Fe3+) in response to changes in land cover. Pearson correlation analyses indicated that conductivity has strong to very strong relationships with water quality variables related to coal mining (except Al3+, Fe2+, Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate regression analyses were performed, with conductivity values based on samples collected in the fall. First, conductivity responses to mining percentage, reclamation age and topographic variables were examined (adjusted R2 = 0.818, p < 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p < 0.01). Finally, reclamation age and mining percentages were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p < 0.01), with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of the mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal-Mine-Related Stream Chemistry in areas where agriculture and urban development are limited. Water quality is not suitable for various purposes due to the presence of contaminants, especially in mined sites. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining, as well as refine land reclamation practices more effectively while such practices are in action.

Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil erosion has received continuous attention. Different conservation measures such as restoring low-function forests, closing hillsides for afforestation, planting trees and grass, and constructing terraces on slope land have been implemented for controlling soil erosion problems and promoting vegetation cover change. One important task is to understand the effects of different conservation measures on reducing water and soil erosion problems. However, directly conducting the evaluation of soil erosion reduction is difficult. One solution is to evaluate the patterns and magnitudes of vegetation cover change due to implementing these measures. Therefore, this research selected Changting County, Fujian Province as a case study to examine the effects of implementing conservation measures on vegetation cover change based on time series Landsat images and field survey data. Landsat images between 1986 and 2021 were used to produce time series vegetation cover data using the Google Earth Engine. Sentinel-2 images acquired in 2021 and Landsat images in 2010 were separately used to develop land cover maps using the random forest method. The spatial distribution of different conservation measures was linked to annual vegetation cover and land cover change data to examine the effects on the change in vegetation cover. The results showed a significant reduction in bare lands and increase in pine forests. The vegetation coverage increased from 42% in 1986 to 79% in 2021 in the conservation region compared with an increase from 73% to 87% in the non-conservation region during the same period. Of the different conservation measures, the change magnitude was 0.44 for restoring low-function forests and closing hillsides for afforestation and 0.65 for multiple control measures. This research provides new insights in terms of understanding the effects of taking proper measures for reducing soil and water erosion problems and provides scientific results for decisionmaking for soil erosion controls. The strategy and method used in this research are valuable for other regions in understanding the roles of different conservation measures on vegetation cover change and soil erosion reduction through employing remote sensing technologies.

Analysing Sustainable Urban Growth: Spatio-Temporal Dynamics of Urban Expansion in Gampola Urban Centre

Urbanization is a dynamic process which can be considered as one of the most significant indicators of development. It occurs both horizontally and vertically on the Earth’s surface according to a pattern which has positive and negative implications. Some countries measure their development by the level of urbanization because it directly affects for a country’s economy. During past decades, Gampola urban centre was experiencing a gradual urban growth and several implications. This study focuses on investigating urban expansion pattern of Gampola during 16 years by analysing three distinct years 2006, 2013, and 2022. Geographic Information System (GIS) and Remote Sensing (RS) techniques were employed to examine spatio-temporal transformations and urban expansion patterns of Gampola and its outskirts. Landsat images for three distinct years were classified using pixel-based supervised classification to determine Land Use Land Cover (LULC) of the study area which achieved an impressive overall accuracy of approximately 90%. Four major LULC types were identified those are prominent in the area namely, water, built-up, forest, paddy lands and bare lands. Temporal changes of vegetation cover for 16 years were analysed further using Normalized Difference Vegetation Index (NDVI). Consequent implications on Land Surface Temperature (LST) across the time period were analysed using thermal band of Landsat images. NDVI value has decreased from +0.7 to +0.5 during 2006-2013 and up to +0.4 during 2013-2022. LST analysis revealed a rise in temperature, increasing from 29.89° C up to 31.11° C during 2006- 2013 and surging to 33.14° C by 2022. Quantifying the urban expansion of Gampola was performed using buffer analysis. Analysis of urban areas grown within 1km distanced five buffer zones from urban core was performed to quantify urban expansion. Fourth buffer zone exhibited the highest urban growth, while first buffer zone displayed lowest urban growth during 2006 to 2022. In the interval between 2013 and 2022, the fifth buffer zone appeared as the zone with the highest urban growth. Further, Landscape Expansion Index (LEI) was employed to identify the urban expansion patterns, and Gampola urban area displayed an Edge Expansion growth type. We recommend the development of urbanized areas in a sustainable and efficient manner to mitigate adverse consequences and promote balanced growth.
 
 Keywords: GIS and RS, Urban expansion, LEI, LST, Sustainable development

Evaluating the relative influence of climate and human activities on recent vegetation dynamics in West Bengal, India

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70–85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

Rapid change of vegetation cover in the Huanghe (Yellow River) mouth wetland and its biogeomorphological feedbacks

Vegetation plays a crucial role in the evolutionary process of coastal wetlands through its biogeomorphological feedbacks, and has become a hot topic of worldwide concern in the context of global climate change. However, as one of the youngest wetlands, the impact of vegetation expansion on the evolution of the Huanghe mouth wetland is currently unknown. In this study, we investigated the spatial and temporal variation of the vegetation cover in the Huanghe mouth wetland over the past twenty years and quantitatively examined its biogeomorphological feedbacks on the river mouth evolution. The results showed that the vegetation cover of the Huanghe mouth wetland has expanded rapidly since 2012 due to the invasion of the exotic species Spartina alterniflora. Its biogeomorphological feedbacks controlled the spatial distribution of surface sediments in the Huanghe mouth wetland and also altered the sediment budget in subaqueous and subaerial deltas. The land-building efficiency of the Huanghe sediment jumped to 101.76 km2/Gt, more than four times that of the pre-invasion period. Compared with other coastal wetlands in the world, the unique feature of high suspended sediment concentration (SSC) makes the Huanghe mouth wetland with high accretion rate under the influence of vegetation. The present study reveals the rapid changes of the vegetation cover and its biogeomorphological feedbacks in the Huanghe mouth wetland, and highlights that the vegetation plays a more critical role in the morphological evolution of the highly turbid river mouth.

Susceptibility of Landslide Debris Flow in Yanghe Township Based on Multi-Source Remote Sensing Information Extraction Technology (Sichuan, China)

The extraction of real geological environment information is a key factor in accurately evaluating the vulnerability to geological hazards. Yanghe Township is located in the mountainous area of western Sichuan and lacks geological survey data. Therefore, it is important predict the spatial and temporal development law of landslide debris flow in this area and improve the effectiveness and accuracy of monitoring changes in landslide debris flow, this article proposes a method for extracting information on the changes in landslide debris flows combined with NDVI variation, which is based on short baseline interferometry (SBAS-InSAR) and optical remote sensing interpretation. In this article, we present relevant maps based on six main factors: vegetation index, slope, slope orientation, elevation, topographic relief, and formation lithology. At the same time, different remote sensing images were compared to improve the accuracy of landslide debris flow sensitivity assessments. The research showed that the highest altitude of the region extracted by multi-source remote sensing technology is 2877 m, and the lowest is 630 m, which can truly reflect the topographic relief characteristics of the region. The pixel binary model’s lack of regional restrictions enables a more accurate estimation of the Normalized Difference Vegetation Index (NDVI), bringing it closer to the actual vegetation situation. The study uncovered a bidirectional relationship between vegetation coverage changes and landslide deformation in the study area, revealing spatial–temporal evolution patterns. By employing multi-source remote sensing technology, the research effectively utilized changes in multi-period imagery and feature extraction methods to accurately depict the development process and distribution characteristics of landslide debris flow. This approach not only offers technical support but also provides guidance for evaluating the vulnerability of landslide debris flow in the region.

Temporal analysis of the change in vegetation cover around the UHE Coaracy Nunes – Amapá

The construction of dams became necessary for national development, in wich the Amazon region, due to its great hydro-energy potential, became the country's hydroelectric frontier. The oldest region reservoir is the UHE Coaracy Nunes-Amapá, built in 1960 and operating since 1975. However, its construction generated several problems, such as loss of territoriality, difficulties in the subsistence of villages and modification of the environment. Therefore, understanding the changes that have occurred in the environment becomes relevant to knowledge, to enable recovery, preservation, conservation and local monitoring actions. In this way, the present study sought to understand if there were changes in the vegetation cover around the UHE Coaracy Nunes from 2000 to 2020. For this, remote sensing data were used. Eleven images obtained from the TM/Landsat-5, ETM+/Landsat 7 and OLI/Landsat-8 satellites were utilized, delimiting the study area with the creation of a polygon (buffer) around the UHE. Digital processing techniques were applied to these images with the support of pixel counting software. The Normalized Difference Vegetation Index (NDVI) was calculated, making it possible to obtain the median. The results obtained demonstrate that the image processing allowed to differentiate its constituent elements (plant cover, exposed soil and water body). The calculation of NDVI medians, for scenes between the years 2000 to 2020, ranged from 0,27 to 0,53 (mean of 0,43 ± 0,09), thus, the statistical analysis showed no relationship over the years (F1,9 = 2,31 and P = 0,16), indicating that during the analyzed period there were no changes in vegetation cover on the ground. This stability may be due to the stagnation of population growth in the city, as well as the presence of the Seringal Triunfo Natural Heritage Private Reserve within the selected area. Another factor that can be attributed to this stability is the pixel count, as the surface of water bodies was not removed. However, the use of Landast satellite images, temporal sequence and the NDVI index proved to be effective tools in remote sensing, enabling the understanding of the dynamics of vegetation cover around the UHE Coaracy Nunes, thus showing its stability in the analyzed period.

Western Caucasus regional hydroclimate controlled by cold-season temperature variability since the Last Glacial Maximum

The Caucasus region is key for understanding early human dispersal and evolution in Eurasia, and characterizing the environmental contrast between Last Glacial Maximum and Holocene is crucial for investigating human adaptation strategies to large climatic shifts. However, a paucity of high-resolution paleoclimate records leave this context largely unknown for early human populations in the Caucasus region. Based on our model-proxy comparison of high- and low-resolution records of 24 stalagmites from three caves, we find spatially distinct changes in vegetation and seasonality of precipitation, especially under glacial conditions. Supported by modern oxygen-isotope data and climate modeling, we identify a supraregional cold-season temperature control for oxygen isotopes in Black Sea speleothems, which previously had been interpreted as a local moisture-source signal. Carbon-isotope and trace-element data further suggest disproportionate changes in vegetation cover and soil dynamics at high altitudes, which would have resulted in a reduction but not a disappearance of human refugia during the Last Glacial Maximum, relative to the current interglacial. Our findings imply that abrupt climatic pressures from harsh conditions were overcome by adaptive strategies in the past.

Comparative analysis between spectral indices obtained in the Guangüiltagua metropolitan park in Quito – Ecuador, using remote sensing

The article presents an exhaustive comparative analysis of NDVI, SAVI and NDWI spectral indices, extracted from satellite images of the Guangüiltagua Metropolitan Park in Quito. The relevance of remote sensing, using satellites such as Sentinel-2, in the monitoring of biodiversity and environmental conditions is highlighted. The research emphasizes the importance of vegetation indices, especially NDVI, to assess vegetation health and detect changes in vegetation cover. The study discusses in detail vegetation sensitivity, water identification, water stress response, soil effect compensation, and specific applications of NDVI, SAVI, and NDWI. The ability of these indices to provide crucial information on ecosystem health, water presence, and potential water stress conditions in Metropolitan Park is highlighted. The methodology applied involves the use of the Copernicus platform and the Sentinel-2 satellite, with radiometric and geometric correction procedures, as well as atmospheric correction. The results obtained reveal high NDVI values, indicating a dense vegetation cover, while NDWI suggests potential areas of water scarcity. The comparative analysis between the indices offers a deeper understanding of the relationship between vegetation and water in the park.