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Academic literature on the topic 'Vegetation condition'

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Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Vegetation condition"

1

De Sousa Teixeira, David Bruno. "Correlation between precipitation and vegetation indexes under preserved Caatinga condition." Journal of Hyperspectral Remote Sensing 7, no. 1 (July 12, 2017): 21. http://dx.doi.org/10.29150/jhrs.v7.1.p21-30.

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The remote sensing techniques have been improved during the last few years, and vegetation indexes have become an increasingly used instrument for the evaluation of landscape units, for instance, the Caatinga's biome. Thus, some indexes such as the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI) and the Leaf Area Index (LAI) are important tools in the study of the vegetation's behavior under the most different climatic conditions, especially in regions of the Brazilian semiarid that have scarce and poorly distributed rains, concentrated in the first half of the year. The objective of this research is to evaluate the influence of precipitation in the behavior of preserved Caatinga's vegetation through vegetation indexes using satellite images. For this, rainfall data of the Aiuaba Experimental Basin (AEB) provided by FUNCEME for the years 2003, 2004 and 2005, were analyzed. In conclusion, there is a strong correlation between rainfall precipitation and the increasing of the vegetation cover in the studied area, showing that the vegetation indexes can be considered as efficient parameters to evaluate the vegetation's behavior under preserved Caatinga condition.
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Kurbanov, R. K., and N. I. Zakharova. "Application of Vegetation Indexes to Assess the Condition of Crops." Agricultural Machinery and Technologies 14, no. 4 (December 18, 2020): 4–11. http://dx.doi.org/10.22314/2073-7599-2020-14-4-4-11.

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Monitoring of the state of agricultural crops and forecasting the crops development begin with aerial photography using a unmanned aerial vehicles and a multispectral camera. Vegetation indexes are selected empirically and calculated as a result of operations with values of diff erent spectral wavelengths. When assessing the state of crops, especially in breeding, it is necessary to determine the limiting factors for the use of vegetation indexes.(Research purpose) To analyze, evaluate and select vegetation indexes for conducting operational, high-quality and comprehensive monitoring of the state of crops and the formation of optimal management decisions.(Materials and Methods) The authors studied the results of scientifi c research in the fi eld of remote sensing technology using unmanned aerial vehicles and multispectral cameras, as well as the experience of using vegetation indexes to assess the condition of crops in the precision farming system. The limiting factors for the vegetation indexes research were determined: a limited number of monochrome cameras in popular multispectral cameras; key indicators for monitoring crops required by agronomists. After processing aerial photographs from an unmanned aerial vehicle, a high-precision orthophotomap, a digital fi eld model, and maps of vegetation indexes were created.(Results and discussion) More than 150 vegetation indexes were found. Not all of them were created through observation and experimentation. The authors considered broadband vegetation indexes to assess the status of crops in the fi elds. They analyzed the vegetation indexes of soybean and winter wheat crops in the main phases of vegetation.(Conclusions) The authors found that each vegetative index had its own specifi c scope, limiting factors and was used both separately and in combination with other indexes. When calculating the vegetation indexes for practical use, it was recommended to be guided by the technical characteristics of multispectral cameras and took into account the index use eff ectiveness at various vegetation stages.
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Jordaan, F. P., O. J. H. Bosch, M. Postma, and A. S. de Beer. "The Potch vegetation management system:the influence on vegetation condition." Journal of Arid Environments 29, no. 3 (March 1995): 403–11. http://dx.doi.org/10.1016/s0140-1963(05)80118-1.

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4

Li, Ming, Chenhao Ge, Shengwei Zong, and Guiwen Wang. "Drought Assessment on Vegetation in the Loess Plateau Using a Phenology-Based Vegetation Condition Index." Remote Sensing 14, no. 13 (June 24, 2022): 3043. http://dx.doi.org/10.3390/rs14133043.

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Frequent droughts induced by climate warming have caused increasing impacts on the vegetation of the Loess Plateau (LP). However, the effects of drought on vegetation are highly dependent on when the drought occurs and how long it lasts during the growing season. Unfortunately, most of the existing drought indices ignore the differences in the drought effects on different vegetation growth stages. In this study, we first established a phenology-based vegetation condition index, namely weighted vegetation condition index (WVCI), which accounts for the differences in vegetation sensitivity to drought by assigning specific weights to different phenological stages of vegetation. Then, we used the WVCI to reveal the temporal and spatial variations in vegetative drought from 2001 to 2019 over the LP from the aspects of drought frequency, trend and relative deviation. The results showed that (1) the LP experienced frequent droughts during the study period, but mainly mild and moderate droughts. The drought frequencies decreased from southeast to northwest, and extreme droughts rarely occurred in mountainous areas and plains. (2) The droughts in most areas of the LP tended to ease, and only a few areas in the Hetao Plain, Ningxia Plain and Fenwei Plain showed an increasing trend of drought. (3) After 2012, the departure percentage of WVCI in most areas of the LP was positive, indicating above-average vegetation conditions. (4) Compared with the well-established vegetation condition index, the WVCI proved to have the ability to monitor and assess vegetative drought on an annual scale in the LP. As a result, our research could help develop and implement drought-resistance and disaster-prevention measures on the LP.
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Keith, David, and Emma Gorrod. "The meanings of vegetation condition." Ecological Management and Restoration 7, s1 (June 2006): S7—S9. http://dx.doi.org/10.1111/j.1442-8903.2006.00285.x.

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6

Zerger, Andre, Philip Gibbons, Simon Jones, Stuart Doyle, Julian Seddon, Sue V. Briggs, and David Freudenberger. "Spatially modelling native vegetation condition." Ecological Management and Restoration 7, s1 (June 2006): S37—S44. http://dx.doi.org/10.1111/j.1442-8903.2006.00290.x.

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7

Tohir, Rizki Kurnia, Mohammad Ashari Dwiputra, and Fajar Islam Sitanggang. "BIRD DISTRIBUTION IN ITERA CAMPUS AREA BASED ON VALUE CHANGES IN NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)." Media Konservasi 26, no. 2 (October 17, 2021): 83–91. http://dx.doi.org/10.29244/medkon.26.2.83-91.

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Land-use change from a rubber plantation into the ITERA campus area causes an ecological transition. The components of ecology affected are vegetation and wildlife (bird). Geographic information systems can be used to assess the condition of vegetation and its relation to the ecological component. This study analyses bird diversity, vegetation condition through the NDVI value distribution, and then analyses the bird distribution based on vegetation condition. Observation in transect is the method for collecting bird distribution data. Analyses of vegetation condition was carried out based on NDVI. Analyses of bird distribution based on vegetation condition was carried out spatially by overlaying thematic maps of vegetation with bird distribution. This research found 28 bird species belonging to 18 families with diversity index (H’) 1.84. The highest abundance species were Lonchura punctulata, Passer montanus, and Hirundo tahitica. The NDVI values ranged from -0.64-0.87. ITERA vegetation conditions are divided into five classes: very rare vegetation (VRV), rare vegetation (RV), m vegetation (MV), dense vegetation class (DVC), and very dense vegetation (VDV). Total encounters with birds in this study were 753. The distribution of birds to the vegetation conditions in ITERA has a higher tendency and diverse vegetation have implications of birds to use the vegetation. In the VRV class, there were 4 encounters, RV 37, MV 157, DVC 235, and VDV 315. Also, the number of bird species tends to increase along with the increasing vegetation value. Lonchura punctulata is a bird with the highest abundance in each vegetation class, followed by Passer montanus and Pycnonotus aurigaster. Key words: bird distribution, ITERA, land-use change, vegetation condition
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8

KIKUCHI, Takao. "Landslide vegetation and its habitat condition." Landslides 39, no. 3 (2002): 338–42. http://dx.doi.org/10.3313/jls1964.39.3_338.

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9

Drielsma, Michael, and Simon Ferrier. "Landscape scenario modelling of vegetation condition." Ecological Management and Restoration 7, s1 (June 2006): S45—S52. http://dx.doi.org/10.1111/j.1442-8903.2006.00291.x.

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Thackway, Richard, and Robert Lesslie. "Reporting vegetation condition using the Vegetation Assets, States and Transitions (VAST) framework." Ecological Management and Restoration 7, s1 (June 2006): S53—S62. http://dx.doi.org/10.1111/j.1442-8903.2006.00292.x.

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Dissertations / Theses on the topic "Vegetation condition"

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Sheffield, Kathryn Jane, and kathryn sheffield@dpi vic gov au. "Multi-spectral remote sensing of native vegetation condition." RMIT University. Mathematical and Geospatial Sciences, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20091110.112816.

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Native vegetation condition provides an indication of the state of vegetation health or function relative to a stated objective or benchmark. Measures of vegetation condition provide an indication of the vegetation's capacity to provide habitat for a range of species and ecosystem functions through the assessment of selected vegetation attributes. Subsets of vegetation attributes are often combined into vegetation condition indices or metrics, which are used to provide information for natural resource management. Despite their value as surrogates of biota and ecosystem function, measures of vegetation condition are rarely used to inform biodiversity assessments at scales beyond individual stands. The extension of vegetation condition information across landscapes, and approaches for achieving this, using remote sensing technologies, is a key focus of the work presented in this thesis. The aim of this research is to assess the utility of multi-spectral remotely sensed data for the recovery of stand-level attributes of native vegetation condition at landscape scales. The use of remotely sensed data for the assessment of vegetation condition attributes in fragmented landscapes is a focus of this study. The influence of a number of practical issues, such as spatial scale and ground data sampling methodology, are also explored. This study sets limitations on the use of this technology for vegetation condition assessment and also demonstrates the practical impact of data quality issues that are frequently encountered in these types of applied integrated approaches. The work presented in this thesis demonstrates that while some measures of vegetation condition, such as vegetation cover and stem density, are readily recoverable from multi-spectral remotely sensed data, others, such as hollow-bearing trees and log length, are not easily derived from this type of data. The types of information derived from remotely sensed data, such as texture measures and vegetation indices, that are useful for vegetation condition assessments of this nature are also highlighted. The utility of multi-spectral remotely sensed data for the assessment of stand-level vegetation condition attributes is highly dependent on a number of factors including the type of attribute being measured, the characteristics of the vegetation, the sensor characteristics (i.e. the spatial, spectral, temporal, and radiometric resolution), and other spatial data quality considerations, such as site homogeneity and spatial scale. A series of case studies are presented in this thesis that explores the effects of these factors. These case studies demonstrate the importance of different aspects of spatial data and how data manipulation can greatly affect the derived relationships between vegetation attributes and remotely sensed data. The work documented in this thesis provides an assessment of what can be achieved from two sources of multi-spectral imagery in terms of recovery of individual vegetation attributes from remotely sensed data. Potential surrogate measures of vegetation condition that can be derived across broad scales are identified. This information could provide a basis for the development of landscape scale multi-spectral remotely sensed based vegetation condition assessment approaches, supplementing information provided by established site-based vegetation condition assessment approaches.
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Nyberg, Roger G. "Automating condition monitoring of vegetation on railway trackbeds and embankments." Doctoral thesis, Högskolan Dalarna, Informatik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:du-21465.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.
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Nyberg, Roger Gote. "Automating condition monitoring of vegetation on railway trackbeds and embankments." Thesis, Edinburgh Napier University, 2015. http://researchrepository.napier.ac.uk/Output/462294.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, aswell as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of (human) raters' visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithmwhich quantifies the vegetation cover was able to process 98% of the image data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%. Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance. A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust mo nitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed formthe foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.
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4

Zimmerli, Stephan. "Vegetation und Standort von Schwingrasen in der Schweiz = Vegetation and site condition of floating mats in Switzerland /." Zürich : Geobotanisches Institut der ETH, 1988. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=8701.

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McKune, Craig. "Rangeland condition in the Ceres Karoo: the importance of long-term studies." Bachelor's thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/26017.

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The impact of the small stock industry on Succulent Karoo vegetation has long been acknowledged, and there is a need for researchers and managers to better understand the dynamics and processes leading to vegetation degradation and recovery. Despite the fact that these arid systems tend to hold high demographic inertia, as well as being prone to sudden and unpredictable events, there are few data-sets that are long enough (>50 yrs) to adequately distinguish 'noise' from true changes. This study examines an extensive data set of plant % cover, recorded using a rapid transect step-point technique, for the period between 1971 and 2002 throughout the Ceres Karoo. Correspondence analysis (CA) ordinations were used to show plant community changes from year to year at two sites: one that has been rested for many decades, and one that has used the Group Camp system since 1970. CA ordinations were also used to depict changes between 1992 and 2002 on three farms using different grazing systems. Results are discussed against the backdrop of the Stock Reduction Scheme initiated in the 1970's. Of the two farms examined from 1971 to 2002, the one using the group camp approach has shown an initial lag-period of about 10 years, and a subsequently steady and directional turnover of plant communities, increasing in cover of desirable species, until 2002. The rested farm showed no identifiable change. Of the farms studied between 1992 and 2002, a clear separation was found between the one using the Group Camp system and the others that are only grazed in winter. The former farm appeared to be showing the greatest amount of change. These results challenge the opinion that rested arid region veld is unlikely to recover. On the contrary, there has been a move toward more desirable veld since the 1970's in land that has not even been rested, but has had relatively reduced stock numbers. The more rested lands appear to be healthier than those that have been more frequently grazed, but they are not showing clear signs of change, supporting theories that arid region vegetation dynamics are characterised by a state and transition type of model. An important pattern to note is that changes from a degraded to a more desirable veld are characterised by a long lag period of more than 10 years, with subsequent changes occurring throughout a 20-year period. Thus the importance of allowing rangelands sufficient time to recover is highlighted, as is the importance of establishing, and continuing existing, long-term data sets.
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Brown, Suzanne. "A statistical analysis of sequences of roadside vegetation condition ratings using Markov chains." Thesis, Brown, Suzanne (2000) A statistical analysis of sequences of roadside vegetation condition ratings using Markov chains. Honours thesis, Murdoch University, 2000. https://researchrepository.murdoch.edu.au/id/eprint/40846/.

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This thesis explores the modelling and analysis of sequences of ratings using Markov chains. The ratings, collected by Main roads WA, are the assessments of the roadside vegetation condition of consecutive road segments made by six different people. Our objective was to model the autodependence structure of the ratings. This enables standard errors of the proportions of the five possible ratings to be determined and provides insights useful for the collection of future ratings. The autodependence of the observations in the sequences is captured using the matrix of transition probabilities for a Markov chain. These are the probabilities of the next segment of the road having a particular rating conditional on the rating of the current segment of road being known. The optimal parametrization for this matrix was then obtained using maximum likelihood estimation. We found that no simplifications to the matrix provided an adequate fit to the data. The transition matrices revealed that raters stay with the same rating as for the previous road segment approximately sixty percent of the time. The standard error and the sampling distribution of these proportions were estimated by simulation and the distributions were found to be approximately normal. The standard errors were also calculated using a mathematical approximation, but these only showed quasi agreement with the simulated values. The estimates were least satisfactory for ratings with small proportions in the Markov chain. It was found that sequential sampling is about a quarter as efficient as random sampling when standard errors from each are compared. Finally, statistical testing revealed significant differences between the transition probabilities for the urban and rural land use categories.
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Ganesh, Srinivasan. "Investigation of the utility of the vegetation condition index (VCI) as an indicator of drought." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2517.

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Schwenke, Andrew C. "Riparian vegetation condition influences movement and microhabitat use by Mixophyes fasciolatus in South East Queensland." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/102339/4/Andrew_Schwenke_Thesis.pdf.

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Riparian vegetation has been impacted by urbanisation in many parts of Australia, resulting in population declines of numerous species of stream-associated frogs. This study was the first to investigate movement and microhabitat use of the stream-associated frog, Mixophyes fasciolatus, in sites that differed in the ecological condition of riparian vegetation in south-east Queensland. Twenty-nine frogs were tracked over a 48-hour period and their fine-scale movements and microhabitat use were examined and found to be related to riparian vegetation condition. These results have significant implications for the conservation management of this species.
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Ndou, Naledzani Nyahman. "Relating vegetation condition to grazing management systems in the central Keiskamma catchment, Eastern Cape Province, South Africa." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1020645.

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Vegetation degradation in South Africa has been identified as a serious environmental problem, especially impacting communal areas. This study investigated the spatial distribution of vegetative condition, along with related changes, deterioration and trends, across the communal villages of the central Keiskamma catchment, Eastern Cape Province. The principal hypothesis of this study was that differences in grazing management strategies may explain the variations in vegetation condition within these communal areas. This investigation assessed the status and condition of vegetation in relation to local institutional grazing management systems, in association with factoring in relevant topographical and physical elements. Topographic homogeneity of the study area was tested by extracting topographic parameters from a DEM and performing a Chi squared test. Remote sensing techniques were used to analyse the spatial and temporal variations in vegetation condition between the villages. Landsat TM images, from 1984 and 1999, in conjunction with SPOT imagery of 2011, were used to assess the spatial trends in vegetation. Land use and cover maps were generated, comprising five categories of land cover, viz. intact vegetation; transformed vegetation; degraded vegetation; bare surfaces; and water. The classification of the images was achieved using the supervised object-oriented classification techniques, which aggregates pixels of each class into homogeneous objects. Information regarding existence and functionality of local institutional structures was obtained through structured interview method. Vegetation condition was correlated to grazing management systems, with the logistic regression confirming a significant relationship between vegetation condition and grazing management systems. Analysis of vegetation condition trends revealed a decline in pristine vegetation with an increase in degraded vegetation and exposed soil throughout the villages. However, it was observed that the decrease in pristine vegetation, with the associated increase in degraded vegetation and soil, do not occur evenly among the villages of the central Keiskamma catchment; the communal areas surrounding certain villages exhibited severe degradation of soil and vegetation, while other villages demonstrated less or minimal deterioration in their environs. The topographic homogeneity of the study locale lent credence to the theory that the uneven distribution of vegetation conditions between the villages is not controlled by topographic factors. Analysis of the data, collected through interviews, revealed differences in the functionality of institutional structures between villages. A statistically significant correlation between the vegetative condition and implementation of grazing management systems, supports the postulated concept that the variances in vegetation condition of the central Keiskamma catchment reflect the efficacy or inefficiency of the settlements‘ grazing management systems. Through gathering, analysing and assessing all the data, a conclusion was drawn, which advances that the primary requirement for remedial action in reversing the current decline in vegetation condition is strengthening the local institutional management regimes throughout all villages under study.
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Williams, Jeremy Hugh. "Monitoring the condition of semi-natural vegetation : the application of remote sensing and geographical information systems (GIS)." Thesis, Bangor University, 1992. https://research.bangor.ac.uk/portal/en/theses/monitoring-the-condition-of-seminatural-vegetation--the-application-of-remote-sensing-and-geographical-information-systems-gis(c90702cb-be4f-454f-aba1-1c74484c0093).html.

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The principal objective of this thesis was to investigate the use of remote sensing and Geographical Information System (GIS) technology in the survey and monitoring of semi-natural, vegetation. The effects of acidic deposition and airborne pollutants on vegetation were of particular interest during the 1980s and early 1990s. A first experiment studied the effect of simulated acid rain on the reflectance of birch seedlings. Plants exposed to acidic treatments lost the characteristic reflectance curve shape of healthy green vegetation. Spectroradiometer data were used to discriminate between plants in different rainfall treatments. A second experiment studied the effects of combinations of pollutant gases (03, S02+NO2, and 03+SO2+NO2) and acidic mists on the reflectance of white clover. Plants in the two treatments containing ozone showed marked changes in reflectance, and were statistically separable from the control. Simple and 4-waveband vegetation indices showed positive linear relationships with shoot dry weight. Plants in the treatments containing ozone showed marked decreases in shoot dry weight and vegetation index. Airborne Thematic Mapper (ATMý data were used to study the relationships between remotely-sensed radiance and water and soil chemistry on a large flood-plain mire in south Wales. Strong relationships between radiance and chemistry were found, suggesting associations between nutrient concentrations and the health and vigour of the mire vegetation. A study on the Glyderau mountains in Snowdonia investigated the potential for mapping upland vegetation using Landsat Thematic Mapper (TM) data. It addressed the problems involved in classifying highly variable ground cover on valley floors, steep slopes and high plateaux, and the problems involved in reconciling the need for a generalised vegetation map with the fine detail present on the ground and in TM data. Pre- and post-classification digital spatial filters were used to produce TM classmaps which agreed closely with the ground survey data. GIS was used to extract management information.
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Books on the topic "Vegetation condition"

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Fried, Jeremy S. Chaparral in southern and central coastal California in the mid-1990s: Area, ownership, condition, and change. Portland, OR: U.S. Dept. of Agriculture, Pacific Northwest Research Station, 2004.

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Fried, Jeremy S. Chaparral in southern and central coastal California in the mid-1990s: Area, ownership, condition, and change. Portland, OR: U.S. Dept. of Agriculture, Pacific Northwest Research Station, 2004.

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Overton, Jacob McC. Predicting vegetation condition and weed distributions for systematic conservation management: An application of GRASP in the central South Island. Wellington, N.Z: Dept. of Conservation, 2003.

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Strawbridge, M. The extent, condition and management of remnant vegetation in water resource recovery catchments in south Western Australia: Report to the Natural Heritage Trust. East Perth, W.A: Water and Rivers Commission, 1999.

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United States. National Environmental Satellite, Data, and Information Service. Vegetation health: Surface conditions. [Washington, D.C.]: NOAA National Environmental Satellite Data and Information Service, 2001.

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Leuthold, Barbara. Vegetations- und Standortsveränderungen auf von Hochwasser überschlickten Streuwiesen =: Changes in vegetation and site conditions in wet meadows after a flood. Zürich: Geobotanisches Institut ETH, Stiftung Rübel, 1994.

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Zimmerli, Stephan. Vegetation und Standort von Schwingrasen in der Schweiz =: Vegetation and site conditions of floating mats in Switzerland. [Zürich: Geobotanisches Institut der ETH, Stiftung Rübel,], 1988.

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Ellenberg, Heinz. Vegetation ecology of Central Europe. 4th ed. Cambridge: Cambridge University Press, 1988.

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Fundação Cearense de Meteorologia e Recursos Hídricos. A zona costeira do Estado do Ceará: Compartimentação geoambiental e antropismo. Fortaleza: FUNCEME, 2009.

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Wołkowycki, Dan. Różnicowanie i ujednolicanie się flor ruderalnych w warunkach izolacji środowiskowej: Differentiation and unification of ruderal floras in environmental isolation conditions. Łódź: Polskie Tow. Botaniczne, 2000.

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Book chapters on the topic "Vegetation condition"

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Salemaa, Maija, Ilkka Vanha-Majamaa, Antti Reinikainen, and Hannu Nousiainen. "Response of understorey vegetation to heavy metal loading." In Forest Condition in a Changing Environment, 266–75. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9373-1_31.

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Whitford, Walter G., Amrita G. De Soyza, Justin W. Van Zee, Jeffery E. Herrick, and Kris M. Havstad. "Vegetation, Soil, and Animal Indicators of Rangeland Health." In Monitoring Ecological Condition at Regional Scales, 179–200. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-4976-1_15.

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Smith, E. Lamar. "Successional concepts in relation to range condition assessment." In Vegetation science applications for rangeland analysis and management, 113–33. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-3085-8_6.

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Harms, Sherri, Tsegaye Tadesse, and Brian Wardlow. "Algorithm and Feature Selection for VegOut: A Vegetation Condition Prediction Tool." In Discovery Science, 107–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04747-3_11.

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Li, Manman, and Junming Liu. "Reconstructing Vegetation Temperature Condition Index Based on the Savitzky–Golay Filter." In Computer and Computing Technologies in Agriculture IV, 629–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18354-6_74.

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Jensen, Mark E., Roland L. Redmond, Jeff P. Dibenedetto, Patrick S. Bourgeron, and Iris A. Goodman. "Application of Ecological Classification and Predictive Vegetation Modeling to Broad-Level Assessments of Ecosystem Health." In Monitoring Ecological Condition in the Western United States, 197–212. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4343-1_17.

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Pontius, Jennifer, Paul Schaberg, and Ryan Hanavan. "Remote Sensing for Early, Detailed, and Accurate Detection of Forest Disturbance and Decline for Protection of Biodiversity." In Remote Sensing of Plant Biodiversity, 121–54. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_6.

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AbstractMany ecosystems and the biodiversity they contain are currently faced with increasing disturbance frequency and intensity, concurrent with converging stress agents such as climate change, invasive species, and pollutant loads. Research has shown that the earlier decline can be detected, the more successful efforts will be in sustaining critical natural resources. While historically remote sensing (RS) has been successfully used to assess and monitor vegetation condition on a relative, coarse scale, advances in RS technologies and new modeling approaches now enable the identification and tracking of early and more subtle changes in vegetation condition, function, and structure. Here we review the current techniques used to assess and monitor forest ecosystem condition and disturbance and outline a general approach for earlier, more detailed, and accurate decline assessment. We also discuss the importance of engaging land managers, practitioners, and decision-makers in these efforts to ensure that the final products developed can be utilized by stakeholders to maximize the impact of these technologies moving forward.
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Waring, Chris, Uta Stockmann, Brendan P. Malone, Brett Whelan, and Alex B. McBratney. "Is Percent ‘Projected Natural Vegetation Soil Carbon’ a Useful Indicator of Soil Condition?" In Soil Carbon, 219–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04084-4_23.

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Ou, WenHao, Wei Su, Chen Wu, ZhongZheng Zhu, YanMin Li, and Shi Shen. "Drought Monitoring Based on the Vegetation Temperature Condition Index by IDL Language Processing Method." In Computer and Computing Technologies in Agriculture V, 43–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27275-2_5.

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Shahfahad, Mohd Waseem Naikoo, Ishita Afreen Ahmad, Swapan Talukdar, Mohd Rihan, and Atiqur Rahman. "Spatio-temporal Analysis of Seasonal Drought Pattern Using Vegetation Condition Index in Latur District." In Springer Natural Hazards, 39–55. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3567-1_4.

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Conference papers on the topic "Vegetation condition"

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Yang, Zhengwei, Liping Di, Genong Yu, and Zeqiang Chen. "Vegetation condition indices for crop vegetation condition monitoring." In IGARSS 2011 - 2011 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2011. http://dx.doi.org/10.1109/igarss.2011.6049984.

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Zhengwei Yang, Hu Zhao, Liping Di, and Genong Yu. "A comparison of vegetation indices for corn and soybean vegetation condition monitoring." In 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009). IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5417498.

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Nyberg, R. G., N. K. Gupta, M. S. Dougherty, and S. Yella. "Machine Vision for Condition Monitoring Vegetation on Railway Embankments." In 6th IET Conference on Railway Condition Monitoring (RCM 2014). Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/cp.2014.1001.

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Dyukova, A. S., A. B. Evgrafova, and A. A. Tretiakova. "EVALUATION OF THE ECOLOGICAL CONDITION OF LAKE OF THE GALICHIAN KOSTROM REGION BY THE CONDITION OF THE COASTAL WATER VEGETATION." In Prirodopol'zovanie i ohrana prirody: Ohrana pamjatnikov prirody, biologicheskogo i landshaftnogo raznoobrazija Tomskogo Priob'ja i drugih regionov Rossii. Izdatel'stvo Tomskogo gosudarstvennogo universiteta, 2020. http://dx.doi.org/10.17223/978-5-94621-954-9-2020-38.

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Data on the diversity of coastal and aquatic vegetation of Lake Galich in the Kostroma region are presented. An assessment of the ecological state of the lake is given based on indicator plant species and the state of coastal water vegetation.
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Yang, Zhengwei, Genong Yu, Liping Di, Bei Zhang, Weiguo Han, and Rick Mueller. "Web service-based vegetation condition monitoring system - VegScape." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723618.

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Du Yongji, Li Xue, Liang Xiaohong, and Han Liebao. "The study of endophyte resistance under difficult vegetation restoring condition." In 2011 International Conference on Electric Technology and Civil Engineering (ICETCE). IEEE, 2011. http://dx.doi.org/10.1109/icetce.2011.5775306.

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Stemmler, Simon, and Dominic Wiedenmann. "Multi-sensor data acquisition for assessing the condition of vegetation." In Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, edited by Christopher M. Neale and Antonino Maltese. SPIE, 2021. http://dx.doi.org/10.1117/12.2599758.

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Zhang, Bing. "Hyperspectral remote sensing of vegetation growing condition and regional environment." In 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2010. http://dx.doi.org/10.1109/whispers.2010.5594859.

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Takeuchi, Akiko, Hidetoshi Yoshida, and Masaru Shibata. "Development of simplified PAM chlorophyll fluorometer for vegetation condition monitoring." In 2009 IEEE 13th International Symposium on Consumer Electronics. IEEE, 2009. http://dx.doi.org/10.1109/isce.2009.5156938.

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Park, Jung-Sool, Kyung-Tak Kim, and Yun-Seok Choi. "Application of Vegetation Condition Index and Standardized Vegetation Index for Assessment of Spring Drought in South Korea." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779463.

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Reports on the topic "Vegetation condition"

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Brown, R. J., W. G. Best, and G. K. Walker. Satellites Monitor Global Vegetation Condition. Natural Resources Canada/CMSS/Information Management, 1990. http://dx.doi.org/10.4095/217658.

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Thoma, David. Landscape phenology, vegetation condition, and relations with climate at Colorado National Monument, 2000–2019. National Park Service, May 2022. http://dx.doi.org/10.36967/nrr-2293476.

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Scott, J. H., D. J. Helmbrecht, and M. P. Thompson. Assessing the expected effects of wildfire on vegetation condition on the Bridger-Teton National Forest, Wyoming, USA. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2014. http://dx.doi.org/10.2737/rmrs-rn-71.

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Hudgens, Bian, Jene Michaud, Megan Ross, Pamela Scheffler, Anne Brasher, Megan Donahue, Alan Friedlander, et al. Natural resource condition assessment: Puʻuhonua o Hōnaunau National Historical Park. National Park Service, September 2022. http://dx.doi.org/10.36967/2293943.

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Natural Resource Condition Assessments (NRCAs) evaluate current conditions of natural resources and resource indicators in national park units (parks). NRCAs are meant to complement—not replace—traditional issue- and threat-based resource assessments. NRCAs employ a multi-disciplinary, hierarchical framework within which reference conditions for natural resource indicators are developed for comparison against current conditions. NRCAs do not set management targets for study indicators, and reference conditions are not necessarily ideal or target conditions. The goal of a NRCA is to deliver science-based information that will assist park managers in their efforts to describe and quantify a park’s desired resource conditions and management targets, and inform management practices related to natural resource stewardship. The resources and indicators emphasized in a given NRCA depend on the park’s resource setting, status of resource stewardship planning and science in identifying high-priority indicators, and availability of data and expertise to assess current conditions for a variety of potential study resources and indicators. Puʻuhonua o Hōnaunau National Historical Park (hereafter Puʻuhonua o Hōnaunau NHP) encompasses 1.7 km2 (0.7 mi2) at the base of the Mauna Loa Volcano on the Kona coast of the island of Hawaiʻi. The Kona coast of Hawaiʻi Island is characterized by calm winds that increase in the late morning to evening hours, especially in the summer when there is also a high frequency of late afternoon or early evening showers. The climate is mild, with mean high temperature of 26.2° C (79.2° F) and a mean low temperature of 16.6° C (61.9° F) and receiving on average 66 cm (26 in) of rainfall per year. The Kona coast is the only region in Hawaiʻi where more precipitation falls in the summer than in the winter. There is limited surface water runoff or stream development at Puʻuhonua o Hōnaunau NHP due to the relatively recent lava flows (less than 1,500 years old) overlaying much of the park. Kiʻilae Stream is the only watercourse within the park. Kiʻilae Stream is ephemeral, with occasional flows and a poorly characterized channel within the park. A stream gauge was located uphill from the park, but no measurements have been taken since 1982. Floods in Kiʻilae Stream do occur, resulting in transport of fluvial sediment to the ocean, but there are no data documenting this phenomenon. There are a small number of naturally occurring anchialine pools occupying cracks and small depressions in the lava flows, including the Royal Fishponds; an anchialine pool modified for the purpose of holding fish. Although the park’s legal boundaries end at the high tide mark, the sense of place, story, and visitor experience would be completely different without the marine waters adjacent to the park. Six resource elements were chosen for evaluation: air and night sky, water-related processes, terrestrial vegetation, vertebrates, anchialine pools, and marine resources. Resource conditions were determined through reviewing existing literature, meta-analysis, and where appropriate, analysis of unpublished short- and long-term datasets. However, in a number of cases, data were unavailable or insufficient to either establish a quantitative reference condition or conduct a formal statistical comparison of the status of a resource within the park to a quantitative reference condition. In those cases, data gaps are noted, and comparisons were made based on qualitative descriptions. Overall, the condition of natural resources within Puʻuhonua o Hōnaunau NHP reflects the surrounding landscape. The coastal lands immediately surrounding Puʻuhonua o Hōnaunau NHP are zoned for conservation, while adjacent lands away from the coast are agricultural. The condition of most natural resources at Puʻuhonua o Hōnaunau NHP reflect the overall condition of ecological communities on the west Hawai‘i coast. Although little of the park’s vegetation...
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Suir, Glenn, Christina Saltus, and Sam Jackson. Remote Assessment of Swamp and Bottomland Hardwood Habitat Condition in the Maurepas Diversion Project Area. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41563.

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This study used high spatial resolution satellite imagery to identify and map Bottomland Hardwood (BLH) BLH and swamp within the Maurepas Diversion Project area and use Light Detection and Ranging (Lidar) elevation data, vegetation indices, and established stand-level thresholds to evaluate the condition of forested habitat. The Forest Condition methods and data developed as part of this study provide a remote sensing-based supplement to the field-based methods used in previous studies. Furthermore, several advantages are realized over traditional methods including higher resolution products, repeatability, improved coverage, and reduced effort and cost. This study advances previous methods and provides products useful for informing ecosystem decision making related to environmental assessments.
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Tagestad, Jerry D., and Janelle L. Downs. Landscape Measures of Rangeland Condition in the BLM Owyhee Pilot Project: Shrub Canopy Mapping, Vegetation Classification, and Detection of Anomalous Land Areas. Office of Scientific and Technical Information (OSTI), December 2007. http://dx.doi.org/10.2172/1028601.

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Pradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42128.

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A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R2 value of 0.72 and average root mean square error (RMSE) of 0.042.
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Taverna, Kristin. Vegetation classification and mapping of land additions at Richmond National Battlefield Park, Virginia: Addendum to technical report NPS/NER/NRTR 2008/128. National Park Service, September 2022. http://dx.doi.org/10.36967/2294278.

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In 2008 and 2015, the Virginia Department of Conservation and Recreation, Division of Natural Heritage produced vegetation maps for Richmond National Battlefield Park, following the protocols of the United States Geological Survey (USGS) – National Park Service (NPS) Vegetation Mapping Program. The original 2008 report was part of a regional project to map and classify the vegetation in seven national parks in Virginia. The 2015 report was an addendum to the original report and mapped the vegetation in newly acquired parcels. Since 2015, the park has acquired an additional 820 acres of land within 12 individual parcels, including the 650 acre North Anna unit. This report is an addendum to the 2008 and 2015 reports and documents the mapping of vegetation and other land-use classes for the 12 new land parcels at Richmond National Battlefield Park, with an updated vegetation map for the entire park. The updated map and associated data provide information on the sensitivity and ecological integrity of habitats and can help prioritize areas for protection. The vegetation map of the new land parcels includes eighteen map classes, representing 14 associations from the United States National Vegetation Classification, one nonstandard, park-specific class, and three Anderson Level II land-use categories. The vegetation classification and map classes are consistent with the original 2008 report. Vegetation-map classes for the new land parcels were identified through field reconnaissance, data collection, and aerial photo interpretation. Aerial photography from 2017 served as the base map for mapping the 12 new parcels, and field sampling was conducted in the summer of 2020. Three new map classes for the Park were encountered and described during the study, all within the North Anna park unit. These map classes are Coastal Plain / Outer Piedmont Basic Mesic Forest, Northern Coastal Plain / Piedmont Oak – Beech / Heath Forest, and Southern Piedmont / Inner Coastal Plain Floodplain Terrace Forest. The examples of Coastal Plain / Outer Piedmont Basic Mesic Forest and Southern Piedmont / Inner Coastal Plain Floodplain Terrace Forest at North Anna meet the criteria of size, condition, and landscape context to be considered a Natural Heritage exemplary natural community occurrence and should be targeted for protection and management as needed. New local and global descriptions for the three map classes are included as part of this report. Refinements were made to the vegetation field key to include the new map classes. The updated field key is part of this report. An updated table listing the number of polygons and total hectares for each of the 28 vegetation- map classes over the entire park is also included in the report. A GIS coverage containing a vegetation map for the entire park with updated Federal Geographic Data Committee (FGDC) compliant metadata was completed for this project. The attribute table field names are the same as the 2008 and 2015 products, with the exception of an additional field indicating the year each polygon was last edited.
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Bryant, Duncan, Mary Bryant, Jeremy Sharp, Gary Bell, and Christine Moore. The Response of Vegetated Dunes to Wave Attack. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41580.

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Vegetation is believed to increase the stability of dunes during wave attack, but limited data is available. A physical model study was performed to evaluate changes in the dune stability with and without biomass, both above and belowground. The above and belowground biomass was modeled using wooden dowels and coir fibers, respectively. For both the collision and overwash storm impact regimes, the results of this study clearly demonstrate that the inclusion of biomass in the model dune reduces the erosion and overwash. The combination of both above and belowground biomass was the most effective at reducing erosion followed by belowground biomass, with aboveground biomass providing the smallest benefit regardless of the wave condition and water level. Additionally, the overwash of sediment and water was decreased with the inclusion of biomass, following the same trends as the erosion. As the dune eroded, the storm impact regime transitioned from collision to overwash. The inclusion of biomass delays this transition in storm impact regime, providing greater protection to coastal communities. This study highlights the need to consider dune vegetation for dune construction and coastal planning.
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Albright, Jeff, Kim Struthers, Lisa Baril, and Mark Brunson. Natural resource conditions at Valles Caldera National Preserve: Findings & management considerations for selected resources. National Park Service, June 2022. http://dx.doi.org/10.36967/nrr-2293731.

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Valles Caldera National Preserve (VALL) encompasses 35,977 ha (88,900 ac) in the Jemez Mountains of north-central New Mexico and is surrounded by the Santa Fe National Forest, the Pueblo of Santa Clara, and Bandelier National Monument. VALL’s explosive volcanic origin, about 1.23 million years ago, formed the Valles Caldera—a broad, 19- to 24-km (12- to 15-mi) wide circular depression. It is one of the world’s best examples of a young caldera (in geologic time) and serves as the model for understanding caldera resurgence worldwide. A series of resurgent eruptions and magmatic intrusive events followed the original explosion, creating numerous volcanic domes in present day VALL—one of which is Redondo Peak at an elevation of 3,430 m (11,254 ft), which is the second highest peak in the Jemez Mountains. In fact, VALL in its entirety is a high-elevation preserve that hosts a rich assemblage of vegetation, wildlife, and volcanic resources. The National Park Service (NPS) Natural Resource Condition Assessment (NRCA) Program selected VALL to pilot its new NRCA project series. VALL managers and the NRCA Program selected seven focal study resources for condition evaluation. To help us understand what is causing change in resource conditions, we selected a subset of drivers and stressors known or suspected of influencing the preserve’s resources. What is causing change in resource conditions? Mean temperatures during the spring and summer months are increasing, but warming is slower at VALL than for neighboring areas (e.g., Bandelier National Monument). The proportion of precipitation received as snow has declined. From 2000 to 2018, forest pests damaged or killed 75% of the preserve’s forested areas. Only small, forested areas in VALL were affected by forest pests after the 2011 Las Conchas and the 2013 Thompson Ridge fires. The all-sky light pollution model and the sound pressure level model predict the lowest degree of impacts from light and sound to be in the western half of the preserve.
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