Vegetation Disturbance Research Articles

Impacts of urban expansion on vegetation in drylands: A multiscale analysis based on the vegetation disturbance index

The rapid urban expansion in drylands has threatened local fragile vegetation in recent years. Evaluating the urban expansion impacts on local vegetation in drylands effectively is crucial for promoting regional urban sustainability. Taking the Hohhot–Baotou–Ordos–Yulin (HBOY) urban agglomeration in China as a case, we quantitatively evaluated the positive and negative urban expansion impacts on vegetation using the vegetation disturbance index. The results indicated that HBOY experienced significant urban expansion from 2000 to 2020. The urban land in HBOY expanded from 242 km2 to 1276 km2, an expansion of 1034 km2, with an annual growth rate of 8.7 %. The negative urban expansion impacts on vegetation far exceeded the positive impacts. Urban expansion negatively and positively affected 404 km2 and 169 km2 of vegetation, respectively. The former was 2.4 times that of the latter. The negative impacts on vegetation are mainly caused by the loss of cropland and grassland. Such negative impacts further affected more than 80 % of the threatened species in HBOY. Therefore, cities in drylands should balance urban development and vegetation conservation by strictly controlling cropland and grassland occupancy and promoting intelligent urban growth.

A novel framework for vegetation change characterization from time series landsat images

Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to reconstructing vegetation change history, investigating change properties, and evaluating the ecological effects. However, current remote sensing techniques are primarily focused on break detection but ignore long-term trend analysis. In this study, we proposed a novel framework based on a change detection algorithm and a trend analysis method that could integrate both short-term disturbance detection and long-term trends to comprehensively assess vegetation change. With this framework, we characterized the vegetation changes in Zhejiang Province from 1990 to 2020 using Landsat and landcover data. Benefiting from combining break detection and long-term trend analysis, the framework showcased its capability of capturing a variety of dynamics and trends of vegetation. The results show that the vegetation was browning in the plains while greening in the mountains, and the overall vegetation was gradually greening during the study period. By comparison, detected vegetation disturbances covered 57.71% of the province's land areas (accounting for 66.92% of the vegetated region) which were mainly distributed around the built-up areas, and most disturbances (94%) occurred in forest and cropland. There were two peak timings in the frequency of vegetation disturbances: around 2003 and around 2014, and the proportions of more than twice disturbances in a single location were low. The results illustrate that this framework is promising for the characterization of regional vegetation growth, including long-term trends and short-term features. The proposed framework enlightens a new direction for the continuous monitoring of vegetation dynamics.

Resistance of Lichens and Mosses of Regenerated Alpine Communities to Repeated Experimental Trampling in the Belianske Tatras, Northern Slovakia

Due to the destruction of alpine ecosystems by extreme human trampling, some alpine areas are closed to tourists. After years of regeneration, a tendency toward reopening these areas for tourism is envisaged. Although numerous studies have documented vegetative responses to trampling disturbance, research that thoroughly examines the trampling impacts on the vegetation at different organizational levels is often limited. Most of the previous studies on the human disturbance of vegetation focused on the impacts on vascular plants, while the impacts on lichens or mosses are less well-documented. To understand how regenerated communities respond to further trampling disturbance, we repeated the experimental research on short-term trampling after 14 years in three high-altitude communities in the Tatras in northern Slovakia. According to Cole and Bayfield’s protocol, we evaluated the resistance of communities trampled in 2008 and 2022, with a focus on groups of lichens and mosses and their individual species. This research brings new knowledge regarding the different behaviors of regenerated vegetation, especially lichens and mosses, to trampling disturbance. The results show that human trampling in alpine communities has a large negative impact and, therefore, management plans should discourage off-trail hiking and limit recreational activities in sensitive or reopened alpine areas.

Vegetation disturbances characterization in the Tibetan Plateau from 1986 to 2018 using Landsat time series and field observations

Disturbances in vegetated land could dramatically affect the process of vegetation growth and reshape the land cover state. The overall greenup of vegetation on the Tibetan Plateau (TP) has almost served as a consensus to date. However, we still lack consistent acquisitions on the timing, the spatial patterns, and the temporal frequency of vegetation disturbance over the TP, limiting the capacity for planning land management strategies. Therefore, we explored the spatiotemporal pattern and variation of vegetation disturbances across the TP during the past decades and analyzed the disturbance agents. We utilized 37-year Landsat time series images and field observations coupled with a temporal segmentation approach to characterize the spatiotemporal pattern of vegetation disturbances across the TP for the period 1986–2018. The results from this study revealed that 75.71 M ha (accounting for 29.34% of TP’s area) vegetation area underwent at least one disturbance, of which 8.44 M ha area ever experienced large-scale disturbances (disturbance area greater than 0.9 ha and disturbance magnitude (the difference between the spectral value of pre-disturbance and that of post-disturbance) over 0.2). Further, the spatial distributions of these large-scale disturbances varied over time: before 2002, the disturbed sites were evenly distributed over the southeast part of the TP probably induced by overgrazing and unscientific livestock management, while after 2002, most disturbances were concentrated in the south of the Yarlung Tsangpo, mainly caused by anthropogenic activities, such as urban area, roadways, railway, and water control projects. This study presents an effort to characterize vegetation disturbances and their variations over the past decades on the TP, which provides crucial insights toward a complete understanding of vegetation dynamics and its causal relationship with human activities.

Analyzing Gradual Vegetation Changes in the Athabasca Oil Sands Region Using Landsat Data

Oil sand mining in northern Alberta/Canada in the Athabasca region is a major intrusion into the otherwise pristine natural environment. The various types of oil sands mining, transport, and processing are causing large-scale discharge of pollutants. Accordingly, this study examined the gradual changes in the physically undisturbed vegetation, that occurred from 1984 to 2021 in the Athabasca oil sands monitoring region. First, the abrupt changes were masked out with the help of auxiliary and Landsat data. Subsequently, a normalized burn ratio Landsat time-series was applied to the LandTrendr algorithm on the Google Earth Engine. In order to interpret gradual changes, measurement criteria were used to describe vegetation development, vulnerability, and variability. In addition, the spatial and temporal relationship of these to oil sand opencast mines, processing facilities, and steam assisted gravity drainage (SAGD) mines was examined. The results showed that a major part of the vegetation in the Athabasca oil sand monitoring region underwent a positive development (65.9%). However, around the opencast mines a negative vegetation development and stability within a radius of 10 km could be observed. In the surroundings of processing facilities, the development and stability of vegetation was disturbed within a radius of 2 km. Thereby the analysis of land cover classes showed that deciduous, coniferous, and mixed forest are disproportionately affected. Conversely, no negative influences on neighboring vegetation could be detected around SAGD mines. The temporal analysis showed that vegetation disturbance was most pronounced between 1990 and 2000, but recovered in recent years.

The Role of Protected Areas in Mitigating Vegetation Disturbances on the Qinghai-Tibetan Plateau

Long-term vegetation dynamics with satellite observations can provide valuable insights into natural variation in ecosystems and quantify disturbances associated with external pressures. Monitoring vegetation dynamics within protected areas (PAs) is essential, given their crucial role in protecting biodiversity and maintaining ecosystem integrity. In this study, using the normalized difference vegetation index (NDVI) and Breaks For Additive Seasonal and Trend (BFAST)model, we detected vegetation dynamics especially abrupt changes inside nature reserves (NRs, the primary type of PAs) on the Qinghai-Tibetan Plateau from 2000 to 2020. We then applied the matching approach and postmatching regression to evaluate the effect of NRs on natural vegetation with average NDVI, NDVI slope, and the number of abrupt changes. Our results showed that 78.97% of the vegetation within NRs exhibited greening trends. In addition, 29.15% of the area inside of the NRs experienced 1 or more abrupt changes, with the major change type interrupted greening (15.96%), followed by greening to browning (6.27%) and browning to greening (4.00%). The NRs significantly reduced the frequency of disturbances, and older NRs also showed a higher value of average NDVI compared to those in matched unprotected areas. Postregression models indicated that vegetation in newer NRs tended to be more vulnerable to disturbances and stricter NR management could benefit vegetation enhancement. Our analysis offers a new approach to vegetation dynamic monitoring that considers short-term disturbances. The findings of this work can help better understand effectiveness of PAs on ecosystem protection and offer practical guidance to future PAs management.

Differences in bird community structure between riparian and upland zones in a New Guinean rainforest

Riparian forests serve as important habitats that enhance diversity of bird species and perform crucial ecosystem functions in tropical forest landscapes. We compared the community structure (represented by functional trait composition) and diversity (represented by Shannon index) of birds in riparian and upland zones in a semi-continuous primary rainforest in Papua New Guinea. Distance sampling was applied to provide unbiased abundance estimates. Bird community structure was examined by principal coordinate analysis of neighbour matrices (PCNM) in the Canoco 5 program. Analysis of diversity was performed using mixed-effects linear models in R 3.5.1. Species diversity was marginally higher in riparian zones (P = 0.065). Community structure differed significantly in riparian and upland zones (P = 0.008). Invertivorous and omnivorous birds preferred riparian habitats but frugivorous and nectivorous birds avoided riparian zones. Birds in riparian zones were characterised by preferences for high-density forest interior but birds in upland areas mostly occupied exposed canopy layers. Beak dimensions were greater in riparian zones but body mass, and lengths of wing and tarsus were greater in upland zones. Species found in riparian zones had greater geographical ranges than those in upland zones. Our results highlight the adaptability of a rainforest bird community to natural disturbances characterised by localised river flooding and riverbank erosion. For example, small invertivorous and omnivorous birds can navigate disturbed vegetation and exploit river-associated invertebrate food supply while moving to alternative food sources during intensive flooding. On the other hand, large frugivorous and nectarivorous birds are mostly sedentary and require an intact canopy layer for foraging, responding poorly to changes in vegetation structure. By moving beyond species-level relationships when examining bird community structure, we were able to better interpret and connect our findings with other studies on bird communities in tropical rainforest.

Paleoecological reconstruction of human impact on the Colombian Subandean forest during the Holocene: Insight from analysis of ecological community structure

La Pochola an archeological site located in Santa Rosa de Cabal (Departament of Risaralda, Colombia), was occupied by humans from the Early Holocene to the Late Holocene, establishing housing sites, however its unknown whether human disturbance occurred at La Pochola. Herein we carried out a paleoecological reconstruction and use ecological community approach (α and β-diversity) in order to document human vegetation disturbance Palynological reconstruction suggests that during the Middle Holocene there was anthropogenic disturbance of the vegetation around the site, increasing α diversity and decreasing β - diversity. Disturbance is associated with the use and management of useful plants, indicated mainly by the presence of maize (Zea mays) pollen and by starch grains recovered from stone tools. Because of we found pollen, starch grains of maize a domesticated plant on the palynological, and archeological records we suggest that human population during Middle Holocene employed crops in this region of Cauca.

Npphen: An R-Package for Detecting and Mapping Extreme Vegetation Anomalies Based on Remotely Sensed Phenological Variability

Monitoring vegetation disturbances using long remote sensing time series is crucial to support environmental management, biodiversity conservation, and adaptation strategies to climate change from global to local scales. However, it is difficult to assess whether a remotely detected vegetation disturbance is critical or not, since available operational remote sensing methods deliver only maps of the vegetation anomalies but not maps of how “uncommon” or “extreme” the detected anomalies are based on the available records of the reference period. In this technical note, we present a new release of the probabilistic method and its implementation, the npphen R package, designed to detect not only vegetation anomalies from remotely sensed vegetation indices, but also to quantify the position of the anomalous observations within the historical frequency distribution of the phenological annual records. This version of the R package includes two new key functions to detect and map extreme vegetation anomalies: ExtremeAnom and ExtremeAnoMap. The npphen package allows remote sensing users to detect vegetation changes for a wide range of ecosystems, taking advantage of the flexibility of kernel density estimations to account for any shape of annual phenology and its variability through time. It provides a uniform statistical framework to study all types of vegetation dynamics, contributing to global monitoring efforts such as the GEO-BON Essential Biodiversity Variables.

Subrecent Pollen Spectra of the Middle Volga Region and their Applicability for Climate and Land-Use History Reconstruction

The paper presents the results of spore-pollen analysis of 47 surface soil samples from the Middle Volga region, taken both in territories with vegetation close to zonal one and in heavily disturbed vegetation areas and agricultural lands. The analysis showed an ambiguous relationship between subrecent spectra and modern vegetation, both local and regional. This is explained by strong anthropogenic transformation of landscapes and the spread of conifer plantations, which form the basis of the modern “pollen rain”. Comparison of the soil subrecent spectra with the spectra of the buried soils uncovered during archaeological excavations in Bolgar showed that the soils of different archaeological eras differ in the composition of the pollen preserved in them, which reflects significant changes in the landscape over time. These changes are associated mainly with the change of the dominant types of land use. It is shown that the pollen spectra of the trampled open areas (roadsides, wastelands and cattle tracks) have characteristic distinctive features, which can be used in the interpretation of the results of archaeological-soil studies.

Biocrust-linked changes in soil aggregate stability along a climatic gradient in the Chilean Coastal Range

Abstract. Biological soil crusts (biocrusts) composed of cyanobacteria, bacteria, algae, fungi, lichens, and bryophytes stabilize the soil surface. This effect has mainly been studied in arid climates, where biocrusts constitute the main biological agent to stabilize and connect soil aggregates. Besides, biocrusts are an integral part of the soil surface under Mediterranean and humid climate conditions, mainly covering open spaces in forests and on denuded lands. They often develop after vegetation disturbances, when their ability to compete with vascular plants increases, acting as pioneer communities and affecting the stability of soil aggregates. To better understand how biocrusts mediate changes in soil aggregate stability under different climate conditions, we analyzed soil aggregate samples collected under biocrust communities from four national parks in Chile along a large climatic gradient ranging from (north to south) arid (Pan de Azúcar, PA), semi-arid (Santa Gracia, SG), Mediterranean (La Campana, LC) to humid (Nahuelbuta, NA). Biocrust communities showed a stabilizing effect on the soil aggregates in dry fractions for the three northern sites and the wet aggregates for the southernmost site. Here, permanent vascular plants and higher contents of organic carbon and nitrogen in the soil control aggregate stability more than biocrusts, which are in intense competition with higher plant communities. Moreover, we found an increase in stability for aggregate size classes < 2.0 and 9.5–30.0 mm. The geometric mean diameter of the soil aggregates showed a clear effect due to the climatic gradient, indicating that the aggregate stability presents a log-normal instead of a normal distribution, with a trend of low change between aggregate size fractions. Based on our results, we assume that biocrusts affect the soil structure in all climates. Their role in aggregate stability is masked under humid conditions by higher vegetation and organic matter contents in the topsoil.

Using POI and time series Landsat data to identify and rebuilt surface mining, vegetation disturbance and land reclamation process based on Google Earth Engine

The development of coal resources is necessary, but it has a huge negative impact on land, ecology, and the environment. With the increasing awareness of environmental protection and the requirements of related regulations, the design and practice of reclamation projects run through the mining life cycle and continue for a long time after the coal production. High-precision monitoring of mining disturbance and reclamation, quantifying the degree and time of vegetation disturbance and restoration, is of great significance to minimize the environmental effect of mining. Remote sensing, widely used as efficient monitoring tool, but there is not enough research on disturbance and reclamation monitoring taking into account large-scale areas and high temporal and spatial accuracy. Especially when mining sites remain unknown, how to distinguish the disturbance of coal mining and other human activities affecting the surface land cover has become a challenge. Therefore, this paper proposed a method to reconstruct the time series of mining disturbance and reclamation in a large area by using the POI (point of interest) and Landsat time series images using multiple buffer analysis methods. The process includes: (1) Retrieval of POI in the study area based on the public mining list using Python crawler, and buffering 100 km for preliminary extraction of potential mining areas; (2) Using spectral index mask and random forest algorithm to accurately extract the exposed coal on the Google Earth Engine (GEE) platform; (3) Buffering 10 km to identify the occurrence of disturbance and reclamation, using pixel-based temporal trajectory identification of LandTrendr algorithm under GEE. The method successful detect the change points of surface coal mining disturbance and reclamation in eastern Inner Mongolia of China. The results show that: (1) The method can effectively identify the extent of surface coal mining disturbance and reclamation, and the overall extraction accuracy is 81%. (2) Surface coal mining disturbance in eastern Inner Mongolia was concentrated in 2006–2011. By 2020, the total disturbed area is 627.8 km2, with an average annual disturbance of 18.5 km2, and the annual maximum disturbance to the ground reached 64.6 km2 in 2008. With the total reclaimed area being 236.3 km2, the reclamation rate is about 37.6%. This study provides a systematic solution and process for monitoring the disturbance and reclamation of surface coal mining in a large range with little known about the mines’ location. It can effectively identify the mining disturbance and reclamation process which can also be extended to other areas, providing a quantitative assessment of mining disturbance and reclamation, which can support further ecological restoration decision-making.

Evaluation of a random displacement model for scalar mixing in ecological channels partially covered with vegetation.

The flow structure in natural rivers may change due to the disturbance of vegetation, further affecting the transport of pollutants and sediment (Liu et al. 2020). In this paper, the random displacement model (RDM) is presented to study the material transport in the emergent vegetated flow by predicting the longitudinal dispersion coefficient (LDC), which plays an important role in the longitudinal transport of pollutants in natural rivers covered by emergent vegetation. RDM can be applied for the analysis of the vegetated flow provided that the velocity distribution and the turbulent diffusion coefficient distribution remain known. According to the experimental data on velocity and Reynolds stress, the flow field was divided into four sub-zones along the cross-sectional area where the transverse distribution of the longitudinal velocity and also transverse turbulent diffusion coefficient were determined. Moreover, the simulated results of the longitudinal dispersion coefficient were verified by using the previously measured data. In addition, the sensitivity analysis of RDM parameters was carried out. In comparison with the shear layer width and the velocity difference, the impact of vegetation zone width on the longitudinal dispersion coefficient was greater, but the model was fundamentally stable, further confirming that the analytical model can be reliable for predicting the longitudinal dispersion coefficient in the vegetated open-channel flow. Accurately estimating the longitudinal dispersion coefficient is useful for understanding the transport and fate of pollutants in river channels and, thereby, for exploring the sustainable development of the river ecological environment, as well as optimizing the planning and design of river course.

Vegetation composition and ecological characteristics of the forest in the Shawilks Mountain Range from Western Himalayas

A vital criterion for the accurate assessment of biodiversity is the qualitative examination of vegetation, which provides essential data for comprehending the general structure and function of any ecosystem. There has been a lot of research on documentation criteria, but in many tropical and subtropical locations, like the Shawilks Mountain Range (a part of the Western Himalayan region), there are still few qualitative studies of forest biodiversity. Qualitative characters indicate how species are grouped or distributed or described. Documenting higher economically valued plants with commercial potential in forest biodiversity is essential to creating a more thorough and useful understanding of the flora for future survival. The current paper is built on the scientific characterization of the floristic, functional, and habitat diversity components of the forest flora found in the Shawilks hills in India. For the floristic studies, a random sampling technique was utilized to choose sites so that plant species in diverse habitats had an equal chance of being sampled. A total of 116 species from 99 genera and 46 families were identified from the study area. The patterns of species distribution among the families were unbalanced, with 24 families being monotypic and eight families contributing half of the species. The largest family, Asteraceae, contained 11% of all species, followed by Fabaceae, (10%). Twenty-four percent of the species were found growing in forests, while 17% were found in widely dispersed habitats along roadsides and 8% were found on pedestrian trails. The leading growth form was herbaceous (53%). Therophytes, indicating disturbed vegetation, were found to be the predominant life form according to the biological spectrum. According to the phytogeographical investigation, 67% of species were native, and 33% were alien. Twelve of the 38 alien species were invasive, 17 became naturalized, and nine were causal. Research on these patterns of functional and habitat variety can greatly advance our understanding of the ecological features of the local flora. Developing management strategies to enable sustainable use and improved management of the forest landscapes in this Himalayan region may also benefit from the information.

A simple model to predict the spatiotemporally vegetation dynamics in terms of precipitation and temperature.

Climate factors like precipitation and temperature fulfil a significant role in assessing the status of the vegetation. Vegetation prediction in terms of climatic conditions represents a critical issue because it helps monitor and maintain the ecosystem's well-being by maintaining track of changes in vegetation disturbance. It is challenging to locate large-scale current vegetation data for use in a variety of applications. In this study, temperature and precipitation were applied to develop a simple linear regression model that predict Normalized Difference Vegetation Index (NDVI) over the African continent. For training data, the third-general Normalized Difference Vegetation Index (NDVI3g) generated from Global Inventory Modeling and Mapping Studies (GIMMS) at a 1/12° resolution was the main input for simulation from 1982 to 2005. From 2006 to 2015, the third-general Normalized Difference Vegetation Index was used to validate the model outputs. The model's accuracy in the arid climate zone (poor vegetation areas) is stronger than in the other four climate zones of Africa, with an R2 of 74%, the lowest p-value of 0.001, the lowest root mean square error (RMSE) of 0.027 and the lowest mean absolute error (MAE) of 0.022. Based on future vegetation condition projections, this approach will assist a more effective management of the future food reservations for the battle against hunger. It will also help with the design, management, and execution of ecological restoration initiatives, research data availability as well as understanding the relationship between vegetation variation and climate variability.

Effects of frequent debris flows on barrier lake formation, sedimentation and vegetation disturbance, Palongzangbo River, Tibetan Plateau

In incised mountain valleys, debris flows often cause damage to vegetation, especially when debris flows form fans or block receiving rivers. In such contexts, riparian trees may be partially buried in aggrading fans or temporary lakes. The Guxiang gully is the largest debris flow system along the Palongzangbo River on the Tibetan Plateau and at least 13 debris flows (volume > 104 m3) have occurred since 1953. Four of these debris flows (in 1953, 1965, 1975 and 2005) dammed the river forming a barrier lake which is now more than 25 km in length. The repeated damming by debris flows has increased the dam height and thereby affected the sedimentation rates in the barrier lake. The frequent debris flow activity has prevented vegetation recovery on the fan, while sedimentation in the barrier lake has allowed vegetation to colonize the deltas. This study investigated the effects of frequent debris flow damming on sedimentation rates as well as on revegetation and tree disturbance along the river. We documented the landscape evolution and measured the sedimentation thickness and grain size of deposited material at different locations of the barrier lake using cores. We also collected and analyzed growth-ring records from disturbed trees on the fan and the deltas of the barrier lake. We found that frequent debris flows had created a stepped river morphology and greatly increased sedimentation rates in the lake, affecting vegetation on the fan and behind the dam.

Enhanced dust emission following large wildfires due to vegetation disturbance

Enhanced dust emission following large wildfires due to vegetation disturbance

Multi-Scale Analysis for Coherent Change Detection: A Method for Extracting Typical Changed Area

Coherent change detection is a technology that utilizes phase information in complex-valued synthetic aperture radar images. It is mostly used to detect subtle changes that cannot be detected by amplitude images on the ground, and it also has excellent detection performance when it comes to low-coherence typical changed areas. However, due to its high sensitivity to changes, this technology will falsely detect areas of natural change such as vegetation disturbance, river flow, and low signal-to-noise ratio areas (e.g., uninteresting areas) as changes, resulting in false-alarm interference areas. In order to tackle this problem, this paper studies a coherent change detection method based on multi-scale analysis to extract typical changed areas in complicated scenes. The method uses an equal variance coherence estimator to calculate the coherence value, separates the interference areas and the typical changed areas using a multi-scale method, and then extracts a binary image of the typical changed areas through noise filtering and threshold segmentation. The method in this paper is experimentally verified with publicly available Airbus spaceborne SAR data, and ESAR airborne data, which is provided by the ESA. The experimental results are visualized and quantitatively evaluated. Through the results, by calculating the probability of correct classification and false-positive and other performance parameters, as well as drawing the receiver operating characteristic curve and the kappa coefficient curve of different threshold values, we find that the method has the capability to suppress the interference areas and the high detection performance of the typical changed areas. The experimental data are complicated scenes that include various types of ground object changes. The results show that the method is effective and universal and can provide reference value for the application of coherent change detection.

Object-based change detection for vegetation disturbance and recovery using Landsat time series

ABSTRACT Accurate characterization of historical trends in vegetation change at the landscape scale is necessary for resource management and ecological assessment. Vegetation disturbance and recovery are coherent spatial and temporal processes. Pixel-based change detection methods often struggle to provide reliable estimates of change events because they neglect spatial contextual information and are affected by salt-and-pepper noise. To address such problems, we propose a new approach, “object-based change detection of trends in disturbance and recovery” (Object-LT), which introduces object-based image analysis (OBIA) into the current framework of LandTrendr algorithm. We then applied this approach to detect vegetation changes during 2000–2020 in the ecologically fragile region of Guyuan, Ning Xia, China. Accuracy assessment indicated that Object-LT could accurately identify disturbance and recovery trends in vegetation with overall accuracies of 90.05% and 87.50%, respectively. Compare with pixel-based LandTrendr algorithm, Object-LT significantly improved user’s accuracy and removed salt-and-pepper noise. Spatial–temporal maps of vegetation change showed that the recovery area was 571.27 km2 while the disturbed area was 297.65 km2, accounting for 5.44% and 2.83% of the study area, respectively. This indicates a general vegetation recovery trend in the study area. Object-LT allowed for an accurate and comprehensive characterization of vegetation change over large areas, which contributes to a better understanding of change processes of vegetation landscape over time.

Impacts of Vegetation Removal on Urban Mediterranean Stream Hydrology and Hydraulics

Given the widespread presence of non-native vegetation in urban and Mediterranean watersheds, it is important to evaluate how these sensitive ecosystems will respond to activities to manage and restore native vegetation conditions. This research focuses on Del Cerro, a tributary of the San Diego River in California, where non-native vegetation dominates the riparian zone, creating flooding and fire hazards. Field data were collected in 2018 to 2021 and consisted of water depth, streamflow, and stream temperature. Our data set also captured baseline conditions in the floodplain before and after the removal of burned non-native vegetation in November 2020. Observed changes in hydrologic and geomorphic conditions were used to parameterize and calibrate a two-dimensional hydraulic model to simulate urban floodplain hydraulics after vegetation removal. We utilized the U.S. Army Corps of Engineers’ Hydrologic Engineering Center River Assessment System (HEC-RAS) model to simulate the influence of canopy loss and vegetation disturbance and to assess the impacts of vegetation removal on stream restoration. We simulated streamflow, water depth, and flood extent for two scenarios: (1) 2019; pre-restoration where non-native vegetation dominated the riparian area, and (2) 2021; post-restoration following the removal of non-native vegetation and canopy. Flooding after restoration in 2021 was more frequent compared to 2019. We also observed similar flood extents and peak streamflow for storm events that accumulated half the amount of precipitation as pre-restoration conditions. Our results provide insight into the responses of small urban stream reaches to the removal of invasive vegetation and canopy cover.