Changes In Vegetation Cover Research Articles

Quantifying the Impacts of Land-Cover Change on the Hydrologic Response to Hurricane Ida in the Lower Mississippi River Basin

Abstract The Lower Mississippi River basin (LMRB) has experienced significant changes in land cover and is one of the most vulnerable regions to hurricanes in the United States. Here, we study the impacts of land-cover change on the hydrologic response to Hurricane Ida in LMRB. By using an integrated surface–subsurface hydrologic model, Energy Exascale Earth System Model (E3SM) Land Model coupled with the three-dimensional ParFlow subsurface flow model (ELM-ParFlow), we simulate the effects of land-cover change on the flood volume and peak timing induced by rainfall from Hurricane Ida. The results show that land-cover changes from 1850 to 2015, which resulted in a smoother surface and less vegetation, exacerbated both flood peak time and volume induced by Hurricane Ida. The effects of land-cover changes can be decomposed into two mechanisms: a smoother surface routes more water faster to a watershed outlet and less vegetation allows more water to contribute to surface runoff. By comparing scenarios in which the two mechanisms were isolated, we found that changes in soil moisture due to vegetation cover change have more dominant effects on floods in the southern part and changes in Manning’s coefficient have the largest effect on floods in the northern part of the LMRB. The study provides important insights into the complex relationship between land-use, land-cover, and hydrologic processes in coastal regions.

Object Detection Driven Precision Forecasting in Curved Terrains

Abstract: This study introduces an inventive approach to avalanche forecast in fastener twist locales utilizing the You Simply See Once (YOLO) protest location system. Fastener twists, with their interesting geography, posture particular challenges for avalanche forecast, requiring a custom fitted arrangement that coordinating progressed computer vision strategies. The proposed technique combines high-resolution fawning symbolism information to make nitty gritty territory models of clip twist ranges. YOLO, known for its real-time question location capabilities, is adjusted to recognize potential avalanche triggers, counting slant flimsiness and changes in vegetation cover, inside these complex scenes. Real-time observing frameworks, counting ground-based sensors and climate stations, are deliberately put to ceaselessly capture natural conditions. Integration with the YOLO-based prescient demonstrate empowers the early recognizable proof of potential avalanche dangers, encouraging the usage of focused on early caution frameworks. Community engagement remains a pivotal perspective of this approach, including neighborhood inhabitants within the improvement of departure plans and readiness techniques. The cooperative energy between YOLO-based innovation and community association makes a comprehensive arrangement for proactively overseeing avalanche dangers in clip twists

Spatio-temporal dynamic analysis of greenness base on NDVI equation for change detection from 2004 to 2024 at River Nile State, Atbara City, Sudan by using remote sensing and geographical information system

Urban regions' ability to maintain high environmental standards is largely dependent on their vegetation. A decrease in the amount of vegetated area on land has resulted from city expansion and population growth. An examination of land cover change in urban settings is necessary, particularly for urban regional planning that takes green, open space into account. The purpose of this study was to examine changes in urban vegetation cover in two Medan sub-districts from 2004 to 2014. Change analysis and the Normalized Difference Vegetation Index (NDVI) were performed in the study. The range of plant diversity in these locations was Observed. The results showed changes in vegetation cover areas in the mentioned years. In 2004, most of the areas were under a highly dense vegetation class while in 2014, they were under a low-density vegetation class with new sub-class. This indicates a decrease in vegetation cover due to changes to non-vegetation cover or land cover areas with less vegetation.

Analyzing Spatiotemporal Variations and Driving Factors of Grassland in the Arid Region of Northwest China Surrounding the Tianshan Mountains

The Tianshan Mountains, the largest arid mountain range in Central Asia, feature diverse terrains and significant landscape heterogeneity. The grasslands within the Xinjiang Tianshan region are particularly sensitive to climate change and human activities. However, until recently, the patterns and mechanisms underlying grassland changes in this region have been unclear. In this study, we analyzed spatial and temporal changes in grassland fractional vegetation cover (FVC) from 2001 to 2020, analyzed spatial and temporal changes in grassland, and predicted future trends using Global Land Surface Satellite (GLASS) FVC data, trend analysis, and the Hurst index method. We also explored the driving mechanisms behind these changes through the structural equation model (SEM). The results showed that from 2001 to 2020, the grassland FVC in the Tianshan region of Xinjiang was higher in the central and western regions and lower in the northern and southern regions, showing an overall fluctuating growth trend, with a change in the growth rate of 0. 0017/a (p < 0.05), and that this change was spatially heterogeneous, with the sum of significant improvement (20.6%) and slight improvement (29.9%) being much larger than the sum of significant degradation (0.6%) and slight degradation (9.5%). However, the Hurst index (H = 0.47) suggests that this trend may not continue, and there is a risk of degradation. Our study uncovers the complex interactions between the Tianshan barrier effect and grassland ecosystems, highlighting regional differences in driving mechanisms. Although the impacts of climatic conditions in grasslands vary over time in different regions, the topography and its resulting hydrothermal conditions are still dominant, and the extent of the impact is susceptible to fluctuations of varying degrees due to extreme climatic events. Additionally, the number of livestock changes significantly affects the grasslands on the southern slopes of the Tianshan Mountains, while the effects of nighttime light are minimal. By focusing on the topographical barrier effect, this study enhances our understanding of grassland vegetation dynamics in the Tianshan Mountains of Xinjiang, contributing to improved ecosystem management strategies under climate change.

Study on the Annual Runoff Change and Its Relationship with Fractional Vegetation Cover and Climate Change in the Chinese Yellow River Basin

In the context of global climate change and ecological restoration projects, significant changes have been observed in the fractional vegetation cover (FVC) in the Yellow River basin. The increased vegetation growth accelerates water consumption, exacerbating drought and water scarcity issues, thereby heightening regional water resource shortage risks. This study targets the Yellow River basin in China, employing a pixel-based model to convert NDVI into FVC datasets. We establish a pixel-wise mathematical model for annual runoff and environmental factors based on residual analysis and methods like multiple linear regression. Using climate model data from CMIP6 as independent variables, in conjunction with the statistical model, we elucidate the spatiotemporal characteristics of annual runoff in the Yellow River basin under future climate scenarios. Our results indicate that, under four different climate scenarios, the average annual runoff in the Yellow River basin is projected to increase. The increases are quantified as 0.008 mm/a, 0.065 mm/a, 0.25 mm/a, and 0.24 mm/a for SSP126, SSP245, SSP370, and SSP585 scenarios, respectively. From 2022 to 2040, the spatial distribution of the runoff change rates under the SSP245 and SSP370 scenarios show an increasing trend in upstream areas such as the Qinhe and Longmen regions, with rates ranging from 6.00 to 8.61 mm/a. During the period from 2041 to 2060, all four climate scenarios indicate minimal changes in the runoff depth in the northern part of the Yellow River basin. From 2061 to 2080, under the SSP126 and SSP245 scenarios, the spatial distribution of the runoff shows significant increases in the river source area and a decreasing trend in the middle reaches, with rates ranging from 4.52 to 11.39 mm/a. For the period from 2081 to 2100, the runoff change rates vary significantly under the four climate scenarios. These findings provide a detailed understanding of how future climate scenarios could impact water resource distribution in the Yellow River basin, offering critical insights for regional water management and policy making to mitigate potential water scarcity challenges.

Foredune morphology: Regional patterns and surfzone–beach–dune interactions along the New South Wales coast, Australia

AbstractForedunes constitute a fundamental part of the coastal environment, acting as a buffer against storm erosion and natural coastal defence. Foredune size and volume play a pivotal role in determining coastal vulnerability to marine hazards, and the governing processes driving variations in foredune morphology, particularly over regional, or larger spatial scales, are still relatively poorly understood. This paper presents a regional‐scale investigation into foredune morphology along the New South Wales (NSW) coast (SE Australia), comprising not only a state‐wide inventory of foredune morphology for use in management/hazard assessment, but also testing long‐standing hypotheses and conceptual models of the physical processes that are driving, or influencing, foredune size. We applied a remote sensing protocol to 47 foredune environments, covering the length of the NSW coastline, comparing morphology (including dune height, width, shape, and volume) of established and incipient foredunes both along, and between, sandy embayments. Results, at regional spatial scales, show that the largest foredunes (volumes up to 850 m3 m−1) occur along the central coast as large, steep landforms; intermediate‐sized dunes (550–650 m3 m−1) were found on both the Mid‐north and Far North coast, and the smallest foredunes (334–380 m3 m−1) occur on the south coast as wider dunes with steep stoss slopes. Surfzone–beach state was found to be the most significant factor influencing foredune size and volume. The more energetic and more dissipative/high‐energy intermediate surfzone–beach states were correlated with larger foredunes (i.e. greater dune volume, width and crest elevation), whereas the lower‐energy surfzone–beach states generally had smaller dunes. Changes in vegetation cover, shoreline orientation and associated onshore (and alongshore) wind systems were also demonstrated to be important factors in determining foredune morphology. The largest foredunes in NSW generally occur to the north of embayments, with dune size decreasing southward with decreasing exposure to wind/wave energy.

Directional reflectance of light from landscapes on a long transect in Australia – forest to desert

The reflectance of land and vegetation observed in satellite imagery depends on sun and viewing geometry. This bidirectional reflectance requires correction for monitoring changes in vegetation cover and condition. We used a digital camera mounted in a light aircraft, and fitted with a fisheye lens, to measure directional reflectance of a diverse range of landscapes along a long transect in Australia — between Brisbane and the Simpson desert. All, except one, of the measured directional reflectances were able to be characterised accurately (adjusted r2 > 0.95) by the product of two analytical functions. The first, G(θ1,θ2), which represents volume scattering, is a function of illumination and viewing zenith angles, θ1andθ2, and has one parameter k:

Improved urbanization-vegetation cover coordination associated with economic level in port cities along the Maritime Silk Road

The sustainability of port cities affects the competitiveness of their hinterland in international shipping and maritime trade, however, the coordinated relationship between urbanization and ecological environment in port cities has received less attention. In this study, we quantitatively analyzed the urban expansion process and vegetation cover changes in 44 port cities along the Maritime Silk Road during 2000–2020 based on multi-source remote sensing data. Adopting the urbanization-vegetation cover index (UVCI), we measured the coordination relationship between urban expansion and vegetation cover and the dynamics during 2000–2020. The results found that all port cities experienced dramatic development from 2000 to 2020, with an average increase in artificial surface area of 127.81%. The 63.64% of port cities experienced increased vegetation cover, thus the overall UVCI in the port city moved toward a more coordinated and sustainable pattern with significant heterogeneity at the economic levels. High-economy port cities have generally become more coordinated, while most low- and medium-economy cities still face challenges of conflicting urban expansion and ecological preservation. This study contributes to the development of government policies that support green and sustainable urban development in port cities, and provides insights for rationalizing development policies in port cities worldwide.

SPATIAL TEMPORAL MAPPING OF VEGETATION COVER INDICES USING SENTINEL-2 MULTISPECTRAL INSTRUMENT IN UNAAHA CITY

Vegetation cover in urban areas contributes to providing livable ecosystem services for humans. As urbanization continues to expand, vegetation cover in urban areas will change rapidly. This research aims to monitor changes in vegetation cover in the last 5 years in Unaaha City using Google Earth Engine. This study also explores vegetation index algorithms such as NDVI, EVI, SAVI, and MSARVI. The research results show that forest vegetation cover continues to decline, followed by an increase in built-up land with an average change of 1,021 ha or the equivalent of 55% of the total area. This research also found that the NDVI algorithm had the best average accuracy with a value of OA=82.54%, followed by MSARVI=73.23%, SAVI=69.52%, and EVI=63.62%. This makes the NDVI method have good accuracy requirements for identifying vegetation compared to other vegetation index algorithms.

Spatial variation characteristics and influencing factors of sediment connectivity in the black soil region of northeast China

Connectivity has become an important indicator of the sediment transfer potential through sediment sources to catchment sinks. Connectivity plays a vital role in investigating the rate of soil erosion caused by runoff and sediment output across the watershed landscape. However, there have been few quantitative studies on the spatial variations in sediment connectivity in the black soil region of Northeast China. Seven classic watersheds in the northeast black soil region were selected to discover spatial variations in sediment connectivity and their influencing factors. The connectivity index (IC) was used to study the spatial variation of sediment connectivity, and the weight of IC was calculated using the vegetation cover management factor (C), which reflected the influence of human activities on the soil erosion process caused by cultivated land expansion and encroachment of forest grassland. The redundancy analysis method (RDA) was used to determine the main factors affecting the spatial variation of IC. The results showed that IC decreased from north (0.45) to south (0.12). The spatial variations of watersheds in sediment connectivity showed significant spatial heterogeneity. IC was correlated with topographic, climatic, and artificial management characteristics at 0.01 or 0.05 levels except soil structural index; RDA results showed that topography and human activities were the main factors affecting sediment connectivity. Topographic and climatic factors explained more sediment connectivity changes in the southern watersheds than in the northern watersheds, while the human activities factor explanation was the opposite of topographic factors. Human activities refer to changes in vegetation cover and soil structure and properties resulting from human logging and farming that affect sediment connectivity.

Analysis of spatial and temporal changes in vegetation cover and its drivers in the Aksu River Basin, China

Exploring vegetation dynamics in arid areas and their responses to different natural and anthropogenic factors is critical for understanding ecosystems. Based on the monthly MOD13Q1 (250 m) remote sensing data from 2000 to 2019, this study analyzed spatio-temporal changes in vegetation cover in the Aksu River Basin and predicted future change trends using one-dimensional linear regression, the Mann–Kendall test, and the Hurst index. Quantitative assessment of the magnitude of anthropogenic and natural drivers was performed using the Geodetector model. Eleven natural and anthropogenic factors were quantified and analyzed within five time periods. The influence of the driving factors on the changes in the normalized difference vegetation index (NDVI) in each period was calculated and analyzed. Four main results were found. (1) The overall vegetation cover in the region significantly grew from 2000 to 2019. The vegetation cover changes were dominated by expected future improvements, with a Hurst index average of 0.45. (2) Land use type, soil moisture, surface temperature, and potential vapor dispersion were the main drivers of NDVI changes, with annual average q-values above 0.2. (3) The driving effect of two-factor interactions was significantly greater than that of single factors, especially land use type interacts with other factors to a greater extent on vegetation cover. (4) The magnitude of the interaction between soil moisture and potential vapor dispersion and the magnitude of the interaction between anthropogenic factors and other factors showed an obvious increasing trend. Current soil moisture and human activities had a positive influence on the growth of vegetation in the area. The findings of this study are important for ecological monitoring and security as well as land desertification control.

Spatial-temporal variation and correlation between vegetation coverage and soil conservation of Ten Kongdui watershed in the Yellow River basin

The Ten Kongdui watershed is an essential part of the upper Yellow River baisn of China. The ecosystem in this region has low stability and hazards of sandstorm and soil erosion are serious. By studying the spatio-temporal changes and spatial correlation between vegetation cover and soil conservation, the inhibition effect of vegetation on soil erosion in time and space can be clarified, and the driving factors of soil erosion in a certain area can be further explained. The research results provide data support for artificial vegetation construction and soil erosion control in the Yellow River basin in the future. In this study, the invest model was used to calculate the soil retention of the watershed, and then the spatial autocorrelation analysis was used to analyze the vegetation coverage and soil retention in space. The relationship between changes of the vegetation coverage and soil conservation during 2000–2020 in the Ten Kongdui watershed is analyzed in this paper. The research shows that: (1) During the research period, the vegetation coverage maintained an increasing trend in Ten Kongdui watershed; (2) From 2000 to 2020, with the increased vegetation coverage, soil retention increased, indicating that increasing vegetation coverage can effectively prevent soil erosion; and (3) Vegetation coverage and soil conservation presented a local spatial auto-correlation, Moran’s I index was less than 0, but the years from 2000 to 2020 witnessed gradual growth of the correlation coefficient. There are significant differences in spatial distribution. ‘High-high’ and ‘low-low’ are sporadically distributed in the sandstorm area on the middle reaches of Kubuqi and sporadically in the hilly and gully areas on the upper reaches. Moreover, ‘high-low’ and ‘low-high’ correlation coefficients were distributed in gully areas on the upper reaches and alluvial plains on the lower reaches. The alluvial plains on the lower reaches are mainly farmland ecosystems, with a high NDVI in the growing season but poor soil erosion resistance and weak soil conservation ability. The results emphasized the importance of vegetation coverage change in space for soil conservation of different type of underlying surfaces. The vegetation coverage change effects of soil conservation in plain terrain will be muted. This work provided a certain theory and criterion for us to further research the predictive model of soil erosion .

Spatiotemporal change characteristics of vegetation coverage in Shangwan Mine of China's Shendong Mining Area.

The coal mining might cause the disturbance to the vegetation and the disturbance impacts might exist the differences for different areas, and few literatures compared and analyzed different disturbed areas based on the location of the mining face, and paid attention to the post mining self-healing effects of vegetation. Here, this paper selected the GaoFen multispectral images during 2017-2021 to study different areas of Shangwan Mine which includes the old mining area more than 5 years after mining, the new working face underground mined in 2018 and 2019, the natural growth control area and the open-pit mining affected area. The spatiotemporal changes of the surface fraction vegetation coverage (FVC) were analyzed in each area and the correlation between vegetation coverage and climatic factors was studied. The results showed that: (1) The overall vegetation coverage showed a moderate decrease trend in fluctuation from 2017 to 2021. The Open-pit mining affected areas showed the largest decline, reaching 68.3%. The FVC in the underground mining areas had a downward trend, but self-healing effect after mining was also observed. (2) The overall FVC in the study area was positively correlated with the number of precipitation days. (3) There were differences in the sensitivity to mining disturbance for different landform in the underground mining areas. (4) Although the FVC in the Old mining areas had recovered to the level of Natural growth control area, but the annual fluctuation was larger, which might mean lower ecological stability.

Woody vegetation cover change and vulnerability to deforestation in Mugulat Area, Eastern Tigray, Ethiopia

Deforestation is the main challenge that forests in Ethiopia are currently facing. Identifying the factors that have the most significant impact on woody vegetation coverage will help sustain the remaining forests and increase woody vegetation coverage in severely degraded landscapes. Therefore, this study was conducted in the Mugulat area of northern Ethiopia to determine the magnitude of woody vegetation cover change and quantify the vulnerability of woody vegetation to disturbances using GIS techniques. Landsat images from 1984, 2000, and 2017 were used for this study. Multi-criteria evaluation through the overlay weight analysis of ArcGIS 10.5 was used to evaluate the vulnerability of woody vegetation to disturbance risk. Cultivated land increased by 35.04 % from 28.51 km2 in 1984 to 38.51 km2 in 2017. Shrubland alarmingly almost reduced by half (47.49 % %) from 24.44 km2 in 1984 to 12.83 km2 in 2017. Over the last 30 years, forest land increased from 4.70 km2 in 2017 to 3.71 km2 in 1984. Along with a forest cover increase of 26.64 %, the results show that woody vegetation cover declined from 48.35 % in 1984 to 32.95 % in 2017, corresponding to an annual loss of 27.42 ha. The significant decline in shrublands is an indicator of the vulnerability of the woody vegetation cover in the study area. Over 50 % and 25 % of the vegetation cover range from very high to high vulnerability, respectively, and are susceptible to disturbance. Restoration measures must be implemented to reduce the vulnerability of the woody vegetation cover. Policymakers and decision-makers should focus on nature-based solutions and climate-smart agriculture, which can contribute to increasing woody vegetation cover.

Short-Term Foredune Dynamics in Response to Invasive Vegetation Control Actions

Efforts to control the spread of invasive alien species (IAS) in coastal dunes are essential to protect biodiversity and maintain the integrity of the ecosystem. However, the timing and extent of these control measures often do not consider their potential impact on dune morphodynamics. This study investigated how IAS control measures can affect sand dune mobility. Research involved monitoring short-term morphological and vegetation changes using close-range remote sensing along with historical wind data. Findings revealed that changes in vegetation cover significantly impacted dune system evolution, notably increasing sand mobility when IAS vegetation was removed. Considering the seasonal wind regime, dominated by offshore winds in the summer, removing vegetation during this period can promote seaward sediment transport, potentially resulting in sediment loss to the beach. These findings highlight the importance of understanding sediment mobility patterns when planning vegetation control actions within dune restoration strategies.

Multi-Temporal Analysis of the Impact of Summer Forest Dynamics on Urban Heat Island Effect in Yan’an City

In this study, MODIS land products and China land cover datasets were used to extract normalized difference vegetation index, land surface temperature, and vegetation cover type in Yan’an City during the summers of 2017–2022. On this basis, analysis of spatial change and correlation were carried out as a way to study the mitigation effect on urban heat islands in Yan’an City with forest. The study showed that: (1) The coverage of normalized difference vegetation index over 0.4 in summer in Yan’an City increased from 59.38% to 69.12%, and the vegetation showed good growth conditions. It has a spatial distribution pattern of more in the south and less in the north. (2) The proportion of the urban heat island in Yan’an City increased from 15.51% to 16.86%. Urban heat island intensity fluctuated year by year, with the maximum urban heat island intensity of 6.26 °C appearing in 2019. It has a spatial distribution pattern of less in the south and less in the north. The transition rate of temperature field grade from low to high is 73.32%, and the transition rate to low is only 0.31%. (3) There is a negative correlation between land surface temperature and normalized difference vegetation index in Yan’an City. Vegetation has a mitigating effect on the UHI and the best cooling effect among the vegetation is shown by forest. The cooling effect of forest in Yan’an City is attenuated by an increase in distance, and the effective range is greater than 1000 m. In this study, the regulation effect of forest on the urban heat island was obtained by digging deeper into the intrinsic connection between spatial change in vegetation cover and land surface temperature change in Yan’an City. It provides an important reference for the formulation of meteorological protection policy as well as the promotion of sustainable development of the urban ecological environment and is of guiding significance for future urban planning and ecological construction.

Outdoor thermal comfort in open transitional spaces with limited greenery in hot summer/cold winter climates

Regarding the constant use of transitional spaces, there is an intense interest in studies on the outdoor thermal comfort in transitional spaces, especially in regions with hot summers. This study aims to analyze the outdoor thermal comfort conditions of a transitional space focusing on vegetation cover change to distill findings into a set of design guidelines for landscape architects and urban planners to enhance the thermal comfort in open transitional spaces, especially in airport terminals with hot summer, and cold winter climate. The case study for this research is an open transitional area at the Mehr-Abad airport. Mehr-Abad airport experiences blistering summers and freezing winters. The environmental situation is analyzed using ENVI-met software. Subsequently, without-grass and without-tree scenarios were simulated to study the impact of greenery on transitional thermal comfort. The results were validated using the on-site collected data. In this study, results demonstrate that the average PET in the current situation is 39.81 ℃ in summer (hot sensation) and 5 ℃ in winter (cold sensation). Based on the results, removing the grass cover is the most suitable scenario for both summer with 35.80 ℃, and winter with 6.68 ℃. The best scenario consists of adding more deciduous trees to open transitional spaces to reduce solar shading in winter. This study provided a better understanding of the effects of vegetation in transient-oriented limited spaces on outdoor thermal comfort and looked deeper into vegetation characteristics concerning the transitional space requirements in hot summer/cold winter climates.

Assessing the impact of land use land cover changes on soil moisture and vegetation cover in Southern Punjab, Pakistan using multi-temporal satellite data

ABSTRACT Change in land use land cover (LULC) is driven by human activities and drives changes that limit the accessibility of services and products for livestock and humans. This study aimed to develop the spatio-temporal changes in LULC, vegetation cover, and moisture index using multi-temporal satellite data in Southern Punjab, Pakistan. Analysis of satellite data was accomplished using ArcGIS 10.4 software. Based on ground-truthing, the supervised classification technique (maximum likelihood algorithm) was used to achieve the LULC classification. The LULC change analysis revealed that vegetation area converted to the build-up area by 7.17 % and bare soil converted to urban areas by 1.68 % from 2000 to 2021. Average NDVI values were calculated at 0.23, 0.17, 0.19, and 0.14 for 2000, 2007, 2014, and 2021, respectively. In the study area, average NDMI values were observed at 0.28, 0.25, 0.2, and 0.15 for 2000, 2007, 2014, and 2021, respectively. Based on our study, the general trend in Southern Punjab is a decrease in vegetation cover, moisture index, and forest area due to an increase in build-up areas. Assessments of LULC and NDMI changes, as well as estimates of the effect on the environment, are necessary for many policy decisions and planning.

Change of vegetation cover and land use of the Pómac forest historical sanctuary in northern Peru

The dry forests of northern Peru, in the regions of Piura, Tumbes, Lambayeque, and La Libertad, have experienced significant changes as a result of deforestation and changes in land use, leading to the loss of biodiversity and resources. This work analyzed for the first time the changes in vegetation cover and land use of the Pómac Forest Historical Sanctuary (PFHS), located in the department of Lambayeque (northern Peru). The employed approach was the random forest algorithm and visually interpreted Landsat satellite images for the periods 2000–2002, 2002–2004, and 2004–2008. Gain and loss rates were computed for each period, and the recovery process was assessed using the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Results indicate an expansion of agricultural land during each period, resulting in the deforestation of 102.6 hectares of dense dry forest and 739.9 hectares of open dry forest between 2000 and 2008. The degree of reforestation in the cleared areas was measured using the NDVI and EVI indices, revealing an improvement from 0.22 in NDVI in 2009 to 0.36 in 2022, and from 0.14 to 0.21 in EVI over the same period. This study is expected to pave the way for executing land management plans, as well as the use and conservation of natural resources in the PFHS in a sustainable manner.

Decadal vegetation changes in a subarctic‐alpine ecosystem: Can effects of Iceland's largest hydropower reservoir, climate change, and herbivory be detected?

AbstractAimsWhile plot‐based vegetation surveys provide means to precisely track changes in plant species abundance and distribution, ecosystems are continuously influenced by numerous drivers, confounding interpretation of monitoring results. Following the making of Iceland's largest hydropower reservoir in 2006, a decadal vegetation monitoring was set up. Relating our results to those of different types of environmental monitoring associated with the hydropower project, we aimed to gain insights into the forces driving the spatio‐temporal vegetation pattern.LocationSubarctic‐alpine area near Hálslón reservoir, East Iceland.MethodsAt the time of its making, we conducted a baseline plant survey in a total of 72 plots, spread around Hálslón reservoir's vicinity (each containing ten 0.25 m2 subplots). Plots were located in three different habitat types (heathlands, wetlands, poorly vegetated land), at three different sites regarding direction and distance from the reservoir. A decade later, we resurveyed the plots and reviewed the results of other environmental monitoring projects in the area, mostly presented in the gray literature.ResultsTemporal changes in vegetation were mostly inconsistent between and within habitat types, but some general trends were noticed, that is, decreased lichen and fern cover in heathlands. Distance from the reservoir did not significantly affect changes in vegetation cover. The greatest overall changes were detected where great changes in herbivore land usage had been recorded during the study.ConclusionsDirect effects of Hálslón reservoir on vegetation in our study plots were not noticed. Most likely, the reservoir indirectly impacted vegetation in our study through loss of grazing area, affecting herbivore land usage, coupled with an unrelated population growth of two of the area's main wild herbivores before and during the study period. Response to climate change was not detected, potentially concealed by substantial land‐use change and a short study period.